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2 RADA PROGRAMOWA / PROGRAM COUNCIL PRZEWODNICZĄCY / CHAIRMAN: prof. dr hab. dr h.c. mult. Czesław CEMPEL Politechika Pozańska REDAKTOR NACZELNY / CHIEF EDITOR: prof. dr hab. iż. Ryszard MICHALSKI UWM w Olsztyie CZŁONKOWIE / MEMBERS: prof. dr hab. iż. Ja ADAMCZYK AGH w Krakowie prof. Jérôme ANTONI Uiversity of Techology of Compiege Frace prof. dr. Ioais ANTONIADIS Natioal Techical Uiversity Of Athes Greece dr iż. Roma BARCZEWSKI Politechika Pozańska prof. dr hab. iż. Walter BARTELMUS Politechika Wrocławska prof. dr hab. iż. Wojciech BATKO AGH w Krakowie prof. dr hab. iż. Lesław BĘDKOWSKI WAT Warszawa prof. dr hab. iż. Adam CHARCHALIS Akademia Morska w Gdyi prof. dr hab. iż. Wojciech CHOLEWA Politechika Śląska prof. dr hab. iż. Zbigiew DĄBROWSKI Politechika Warszawska prof. dr hab. iż. Maria DOBRY Politechika Pozańska prof. Wiktor FRID Royal Istitute of Techology i Stockholm Swede dr iż. Tomasz GAŁKA Istytut Eergetyki w Warszawie prof. Le GELMAN Crafield Uiversity Eglad prof. dr hab. iż. Ja KICIŃSKI IMP w Gdańsku prof. dr hab. iż. Jerzy KISILOWSKI Politechika Warszawska prof. dr hab. iż. Daiel KUJAWSKI Wester Michiga Uiversity USA prof. dr hab. Wojciech MOCZULSKI Politechika Śląska prof. dr hab. iż. Staisław NIZIŃSKI UWM w Olsztyie prof. Vasyl OSADCHUK Politechika Lwowska Ukraie prof. dr hab. iż. Staisław RADKOWSKI Politechika Warszawska prof. Bob RANDALL Uiversity of South Wales Australia prof. dr Raj B. K. N. RAO Presidet COMADEM Iteratioal Eglad prof. Vasily S. SHEVCHENKO BSSR Academy of Scieces Mińsk Belarus prof. Mead SIDAHMED Uiversity of Techology Compiege Frace prof. dr hab. iż. Tadeusz UHL AGH w Krakowie prof. Vitalijus VOLKOVAS Kauas Uiversity of Techology Lithuaia prof. dr hab. iż. Adrzej WILK Politechika Śląska dr Gajraj Sigh YADAVA Idia Istitute of Techology Idia prof. Alexadr YAVLENSKY J/S Compay "Vologda Bearig Factory" Russia prof. dr hab. iż. Bogda ŻÓŁTOWSKI UTP w Bydgoszczy WYDAWCA: Polskie Towarzystwo Diagostyki Techiczej 0-98 Warszawa ul. Augustówka 5 REDAKTOR NACZELNY: prof. dr hab. iż. Ryszard MICHALSKI SEKRETARZ REDAKCJI: dr iż. Sławomir WIERZBICKI CZŁONKOWIE KOMITETU REDAKCYJNEGO: dr iż. Krzysztof LIGIER dr iż. Paweł MIKOŁAJCZAK ADRES REDAKCJI: UWM w Olsztyie Redakcja Diagostyki ul. Oczapowskiego Olszty Polad tel.: , fax: KONTO PTDT: Bak PEKAO SA O/Warszawa r kota: NAKŁAD: 350 egzemplarzy Wydaie dofiasowae przez Miistra Nauki i Szkolictwa Wyższego

3 DIAGNOSTYKA (49)/009 Spis treści / Cotets Valety SKALSKY, Oleh SERHIYENKO, Tetiaa SELIVONCHYK, Yaroslav TOLOPKO Natioal Academy of Scieces of Ukraie, Lviv...3 Calculatio Ad Optimizatio Of Waveguide Geometry For Acoustic Emissio Sigals Marek FIDALI, Grzegorz URBAN EK Silesia Uiversity of Techology...7 Optimizatio Of A Set Of Thermovisio Image Features With The Use Of Evolutioary Algorithms Optymalizacja zbioru cech obrazów termowizyjych z zastosowaiem algorytmów ewolucyjych Domiik WACHLA Silesia Uiversity of Techology...3 A Framework For Kowledge Acqusitio System I Perspective View Of Diagostic Of Rotatig Machiery System pozyskiwaia wiedzy z perspektywy diagostyki maszy wirikowych Jerzy BRZÓZKA Maritime Uiversity of Szczeci...7 MFC/IMC Scheme As A Fault Tolerat Cotrol Structure Odpory a uszkodzeia układ regulacji typu MFC/IMC Przemysław SIMIŃSKI, Maciej ZAJĄC Military Istitute of Armour ad Automotive Techology i Sulejówek...5 Simulatio Model For Testig Patrol-Itervetio Vehicle Model symulacyjy do badań samochodu patrolowo-iterwecyjego E. GRUDZIŃSKI Wrocław Uiversity of Techology, P. DUB, P. DRABYCH, L. DYKMAROVA, V. NICHOGA Physico-Mechaical Istitute of the Natioal Academy of Scieces of Ukraie, L. SOPILNYK Lviv Polytechic Natioal Uiversity...9 Applicatio Of Alteratig Electromagetic Fields I Techical Diagostics Of Egieerig Objects Of Log-Term Usage Piotr PRZYSTAŁKA Silesia Uiversity of Techology...33 Fault Detectio Ad Isolatio For Dyamic Processes Usig Recurret Neural Networks Detekcja i lokalizacja uszkodzeń procesów dyamiczych z użyciem sieci rekurecyjych Zeo SYROKA Uiwersytet Warmińsko Mazurski w Olsztyie...4 The Patter Spectrum Of The Electrical Machie With Usig Classical Discrete Orthogoal Polyomials Wzorzec widmowy maszyy elektryczej z wykorzystaiem klasyczych dyskretych wielomiaów ortogoalych Piotr BIELAWSKI Maritime Uiversity of Szczeci...45 Coditio Moitorig Of Marie Power Plats Diagostyka siłowi okrętowych Marek FIDALI, Aa TIMOFIEJCZUK Silesia Uiversity of Techology...49 Assessmet Of Welded Joits Quality By Meas Of Aalysis Of Their Thermovisio Images Recorded Durig Weldig Process Ocea jakości połączeń spawaych a podstawie wyików aalizy obrazów termowizyjych zarejestrowaych podczas procesu spawaia Łukasz JEDLIŃSKI, Jausz KISIEL, Józef JONAK Lubli Uiversity of Techology...57 Diagosig The Coditio Of Gear Trasmissio O The Basis Of Periodic Ad Residual Compoets Of The Sigal Spectrum Diagozowaie stau przekładi zębatej w oparciu o składowe okresowe i widmo resztkowe sygału Jacek DZIURDŹ, Wojciech SKÓRSKI Warsaw Uiversity of Techology...63 Aalysis Of Noliear Effects I Diagostics Of Composite Structures Aaliza zjawisk ieliiowych w diagozowaiu kostrukcji kompozytowych

4 DIAGNOSTYKA (49)/009 SPIS TREŚCI / CONTENTS Bogusław ŁAZARZ, Heryk MADEJ, Piotr CZECH Silesia Uiversity of Techology...67 Takig Advatage Of Empirical Mode Decompositio I Diagosig Gear Faults Wykorzystaie empiryczej dekompozycji sygału w diagostyce uszkodzeń przekładi zębatych Heryk MADEJ, Piotr CZECH Silesia Uiversity of Techology...73 Diagostics Of Clearace I The Pisto-Cylider Assembly Usig Hoelder Coefficiets Diagozowaie luzu w układzie tłok-cylider z wykorzystaiem współczyików Hoeldera Leszek MAJKUT Akademia Góriczo Huticza...79 Vibratio Based Damage Detectio Usig Laplace Wavelet Wykorzystaie falki Laplace a w diagostyce uszkodzeń Łukasz KONIECZNY, Rafał BURDZIK Silesia Uiversity of Techology...83 The Ifluece Of Oil Leak I Vehicle Shock Absorber O Its Dumpig Characteristics Wpływ ubytku oleju w amortyzatorze samochodowym a jego charakterystyki tłumieia Joaa WILCZARSKA Uiwersytet Techologiczo-Przyrodiczy w Bydgoszczy...87 The Implemetatio Of The Methodology Of The Machies State Geesis Implemetacja metodyki geezowaia stau maszy Joaa WILCZARSKA Uiwersytet Techologiczo-Przyrodiczy w Bydgoszczy...93 Model Of Machie State Geesis Model geezowaia stau maszy Sławomir AUGUSTYN Natioal Defece Uiversity...97 Decisioal Model For Aircraft Safe System Model decyzyjy dla bezpieczeństwa eksploatacji loticzej Tomasz FIGLUS, Adrzej WILK Politechika Śląska...0 Diagosis Of Trasmissio Tooth Chippig Usig Discrete Wavelet Trasformatio Diagozowaie wykruszeia zęba przekładi przy użyciu dyskretego rozkładu falkowego Adrzej GĘBURA, Tomasz TOKARSKI Istytut Techiczy Wojsk Loticzych w Warszawie...05 Diagosis By FAM-C Method Of A Support s Bearigs Turbie Egie Diagozowaie metodą FAM-C podpór łożyskowych loticzego silika turbiowego Radosław ZIMROZ Politechika Wrocławska...3 Applicatio Of Wavelet Aalysis Diagostics Of Locac Faults I Drivig Uits Of Miig Machies Zastosowaie aalizy falkowej w diagostyce uszkodzeń lokalych układów apędowych maszy góriczych Lesław BĘDKOWSKI, Tadeusz DĄBROWSKI Wojskowa Akademia Techicza...3 Ucertaity I Processes Of Diagosig Ad Supervisig Niepewość w procesach diagozowaia i dozorowaia Warto przeczytać / Worth to read...30

5 DIAGNOSTYKA (49)/009 SKALSKY, SERHIYENKO, SELIVONCHYK, TOLOPKO, Calculatio Ad Optimizatio Of Waveguide 3 CALCULATION AND OPTIMIZATION OF WAVEGUIDE GEOMETRY FOR ACOUSTIC EMISSION SIGNALS Valety SKALSKY, Oleh SERHIYENKO, Tetiaa SELIVONCHYK, Yaroslav TOLOPKO H. V. Karpeko Physico-Mechaical Istitute of Natioal Academy of Scieces of Ukraie, Lviv, Naukova Str 5., Lviv, 7960,Ukraie, Summary Optimizatio of geometrical sizes of the waveguide of elastic acoustic emissio (AE) waves, which is used i the search of hydroge iduced crackig durig thermal cyclig of structure alloys i a gaseous hydroge eviromet, is cosidered. A waveguide is cosidered as o acoustic system that has the discrete spectrum of eigefrequecies. Distributio of temperature field alog the waveguide is calculated, decay of elastic АЕ waves is estimated. Basig o the obtaied results the desig implemetatio of the waveguide is carried out. Keywords: acoustic emissio, fiite elemets method, waveguide, eergy losses, temperature distributio.. INTRODUCTION I ivestigatio of physical ad chemical properties of materials ad goods by the method of acoustic emissio (АЕ) we ofte face a situatio, whe locatio of АЕ trasducer (АЕT) oto the tested object (TО) is impossible because of some reasos. I such cases, it is reasoable to use waveguides of АЕ sigals, which typically have a cylidrical form. Oe face of the waveguide is attached to the TО ad o the opposite face, the АЕT is located. However, waveguides as acoustic systems have the discrete spectrum of their eigefrequecies. As a result, the broadbad АЕ sigal from a source, passig through a waveguide, chages: the spectral compoets of a sigal, which correspod to eigefrequecies of waveguide oscillatios, will icrease ad others will decay. Therefore, it is importat that the geometrical parameters of the waveguide could provide the compliace of its eigefrequecies with the operatig bad of AET.. CALCULATION OF WAVEGUIDE EIGENFREQUENCIES The problem of elastic waves propagatio i cylidrical bodies was cosidered particularly i refereces [-3]. I the paper [4] the approximatio method based o the limitig iterpolatio method [5] for fidig the eigefrequecies was proposed. Accordig to this method, the limitig cases of iterpolatio are exactly take ito accout, ad approximatio parameters could be foud at certai itermediate poits of the fuctioal depedeces obtaied for these limitig cases. The essece of the method of optimizatio of waveguide sizes cosists i the followig. At first, takig ito cosideratio the structural parameters or requiremets of the TО operatio, the legth l ad the diameter d of the waveguide are to be specified. If the ratio of l/d is i the rage from 0.3 to 3, the itricate threedimesioal problem has to be solved for fidig the eigefrequecies f pq of the waveguide. Usig the approximatio equatio obtaied i [4] we ca fid the eigefrequecies i simpler maer: ( d) ( d, ) ( r c ) αpqαpq αpq f pq = 0.3 () [( ( ) ( )) () / m d, d r m ] ( ( d, ) ( d) m l αpq αpq αpq + αpq αpq) where p ad q are the itegers, с is the velocity of trasversal wave, α ( d ) pq is the phase costat, which is determied from the solutio of the system of trascedet eigevalue equatios for a disk, α ( d, ) pq is the value of α ( d ) pq for the case l/d>>, ( r α ) pq is the phase costat, which is determied from the solutio of the system of trascedet eigevalue equatios for a rod, m is the approximatio parameter. Selectig accordig to approximatio equatio () the least from the values of f pq, we fid the AET dimesios with the proper operatig bad. I the case l/d > 3, istead of equatio () we ca use the depedece for fidig f pq [6]: f p, q = ( cq x / ) l () where = c / c0 ( + ν) x, c = / ρ is the soud 0 E velocity i a bar, с is the phase velocity, ν is the Poisso's ratio. Here q is a positive odd iteger, related with the wavelegth. Approximatio equatio () obtaied i [4] allows to estimate the eigefrequecies of cylider waveguide of a fiite legth, exactly takig ito accout the limitig cases of iterpolatio: short rod (disk) ad log rod, whose eigefrequecies are kow [6]. However, if the waveguide has more complicated shape the umerical methods of calculatio have to be used, i particular the fiite elemet method (FEM) [7]. Havig calculatio data o eigefrequecies of the waveguide, we may optimize its geometry takig ito accout temperature operatig rage

6 4 DIAGNOSTYKA (49)/009 SKALSKY, SERHIYENKO, SELIVONCHYK, TOLOPKO, Calculatio Ad Optimizatio Of Waveguide ad structural features of TО usig the methodological approach described i the papers [8, 9]. The FEM calculatio of eigefrequecies ad correspodig vibratio modes of the waveguide we realized usig the approach method described i the paper [8]. I this case, the equatio for calculatio of the eigefrequecies takes the form: ' ' ( ) ϕ( h a) + ( ex) [ x ϕ( k a) ] = 0 x, (3) yj ( ) where ( ) 0 y ν ' ϕ y =, e =, h = h γ, J( y) ν ' k = k γ, h = ωc, k = ωc, J 0() і J ( ) are the Bessel fuctios of first kid of the zero ad first order, respectively, c ad c are the velocities of logitudial ad trasversal waves, respectively, ω is the agular frequecy, a is the radius of the waveguide, l is its legth. Takig ito cosideratio that the cylider is bouded by two plae surfaces, the distace betwee which is l, the legitimate values of γ are πq γ q = l, where q is the positive odd umber. The desig features of the chamber, i which we ivestigated the effect of eviromet o AE sigals, imposed the coditio that the legth of the waveguide is ot greater tha 0,5 m ad the diameter is 4 mm. Usig equatio (3) eigefrequecies were foud from the followig formula: πq c f pq = x p, (4) l where x p is the solutio of equatio (3). The eigefrequecy f pq of the first mode (p = q = ) of the oscillatio, obtaied from (4) for ν=0,8, Youg's modulus E=.07x0 5 MPa, ρ= 7800 kg/m3, a = 0,00 m ad l = 0.43 m was 995 Hz. The FEM calculatio of the eigefrequecy f pq of the first mode (p = q = ) of cylider waveguide coducted for the same values of the Poisso's ratio, Youg's modulus, desity, radius ad the legth of a cylider gives the value of 967 Hz. Thus, the relative error of FEM calculatio i compariso with (4) does ot exceed 0.93%. We coducted the FEM calculatio usig threedimesioal fiite elemets with 0 odes. The cylider was divided alog its geeratig lie by 4, alog the radius of the base by 5 ad alog the cotour of the base by 8 parts. The two times icrease of the mash desity gave the relative error of the fudametal frequecy calculatio of 0.43%. Therefore this meshig we used i further FEM calculatios. Similar FEM calculatios were coducted also for the waveguide show i Fig.. The oe ed of the waveguide was attached to the specime ad AET was located o the free ed. The waveguide legth was 0.43 m. The icrease of umber of the odes i two times gave the relative error of the foud eigefrequecies, which did ot exceed 3.4% i the frequecies rage of khz correspodig to the operatig bad of AET used i experimetal research for АЕ recordig. The total umber of foud eigefrequecies i this rage was 47. Fig.. Geeral view of the waveguide for recordig АЕ: is the waveguide, is the cocetrator, 3 is the specime of structural material, 4 is the clamp, 5 is AET, 6 is the clamp, 7 is the plug Distributio of the dimesioless ormal displacemet o the face of the waveguide for f = 4,07x0 5 Hz is show i Fig.. Fig.. Distributio of the dimesioless ormal displacemet o the waveguide face for f = 4,07x0 5 Hz Fig. shows that the maximal value of the dimesioless ormal displacemet is at the ceter of the waveguide face. 3. EXPERIMENTAL DETERMINATION OF LOSSES IN THE WAVEGUIDE Elastic waves propagatio i a solid occurs with the losses of eergy caused by physical processes, which accompay elastic oscillatios. For estimatio of these loses i waveguides i laboratory we coducted the experimetal ivestigatio usig the method developed i the paper [9]. The experimetal setup is show i Fig. 3. The cylidrical rod made of steel 45 (state of delivery) with the diameter of 4 mm ad the legth of 0.43 m was used as a AE waveguide.

7 DIAGNOSTYKA (49)/009 SKALSKY, SERHIYENKO, SELIVONCHYK, TOLOPKO, Calculatio Ad Optimizatio Of Waveguide 5 Fig. 3. Experimetal setup for determiatio of losses i a waveguide: is the base, is the waveguide, 3 is the soud-simulator of AE, 4 is the AET, 5 is the preamplifier, 6 is the filter bak, 7 is the power amplifier, 8 is the processig uit, 9 is the geerator of electric pulses, 0 is the fast-actig recorder The soud-simulator was used as a AE source [0]. It was mouted with the glue layer o the duralumi base of the dimesios m at differet distaces from the waveguide face. The АE pulses were excited by a electric pulse of rectagular shape geerated by the simulatio uit cotaied i the АVN-3 device. Oe face of the waveguide was rigidly attached to the base ad o the opposite waveguide face the AET was located. It had resoace frequecy of 55 khz. Electric АЕ sigals from AET were trasmitted through the preamplifier, the filter bak of high ad low frequecies, the power amplifier to the sigal processig uit. The AE sigal parameters, amely amplitudes, cumulative cout, ad total cout rate, were recorded o paper by the fast-actig recorder []. Comparig amplitudes of iitial АЕ sigals with the recorded oes, we measured the losses i the waveguide. The amplificatio factor of the АЕ sigal path was 70 db (amplificatio factor of the preamplifier was 34 db) i the frequecy rage khz, ad the trasfer costat of filters was earby oe. Fig. 4. Depedece of amplitude of elastic АЕ waves chages o the diameter of waveguide ad distace to the source of simulatio The results of experimets have show that the losses i the waveguide were % i the case of the elastic АЕ waves simulatio ear the waveguide face, which is rigidly attached to the base. I Fig. 4 variatio of АЕ amplitudes, depedig o the distace to the source of AE simulatio ad the diameter of the waveguide, is preseted. Fig.4 shows that for idetical legths of the waveguide the greater losses i the elastic АЕ waves were observed for the greater distaces to the source ad the diameter of the waveguide. Thus, applicatio of АЕ waveguides requires to take ito accout the losses of AE sigals ad to select AET with lower resoace frequecies, which lie i the calculated rage of a waveguide eigefrequecies. 4. ESTIMATION OF LENGTHWISE DISTRIBUTION OF WAVEGUIDE TEMPERATURE FIELD Optimizatio of the waveguide dimesios is closely coected with the accout of temperature field effect o the operatig part of AET. Let us cosider the case of the cylider rod, which oe face cotacts with TО heated to the statioary temperature ad a lateral surface is surrouded by air of temperature Т a. If we suppose that a heat iterchage betwee a waveguide ad eviromet is quasi-static, the temperature T at the surface is determied by the equatio []: l ( l x) T = ( T T ) λ + a ch R T (5) 0 a l l λr where Т a is the temperature of air, α is the calorific efficiecy, λ is the heat coductivity, R is the waveguide radius, l is its legth, x is the ruig coordiate of the waveguide legth. Whe the exteral heat iterchage takes the form of atural covectio of air, the calorific efficiecy ca be foud from the depedece: ( T T ) 4 gβ α = 0.47λ a a (6) Rν where λ a is the heat coductivity of air, g is the acceleratio of gravity, β is the liear expasio factor of air, T is the average temperature alog a rod, ν it is kiematics viscosity of air. The temperature of cold ed of cylider rod, i.e. the place, where the AET is located, accordig to [] is determied as follows: T c = + ( T Ta )[ ch l λrl] Ta 0 (7) The mai assumptios of the problem defiitio are the followig: λ =cost, α (T) = α (T a ) ad T a is idepedet o spatial coordiates. The results of umerical calculatio of temperature coditio of the waveguide made of steel 45 (state of delivery) are show i Fig.5 (dotted lie). Fig. 5 shows that the fuctio Т c (l) rapidly falls with the icrease of the waveguide legth. I Fig. 5b the results of FEM calculatio of temperature field i the waveguide show i Fig. for the same values of temperature of hot ed of the waveguide ad air as i Fig. 5a are preseted.

8 6 DIAGNOSTYKA (49)/009 SKALSKY, SERHIYENKO, SELIVONCHYK, TOLOPKO, Calculatio Ad Optimizatio Of Waveguide а b Fig. 5. Theoretical (dotted lie ) ad experimetal (dots) results of temperature distributio alog waveguide (а) ad FEM calculatio ( o C)(b) Summarizig, we may otice that reductio of waveguide legth due to desig reasos is possible oly with the simultaeous decrease of its diameter, heat coductivity of material or both factors together. 5. CONCLUSIONS Optimizatio of АЕ waveguide dimesios should be coducted usig the calculatio of its respose characteristics ad their compariso with the correspodig characteristics of АЕT, takig ito accout the distributio of temperature field alog the waveguide ad desig features of diagostic access to the locatio of AET o TO surface. Cofiguratio ad geometrical sizes of a waveguide should provide reliable protectio of АЕT agaist harmful ifluece of temperature o its operatig part. The waveguide legth should provide least decay of elastic АЕ waves. Iformatio o material fracture obtaied from elastic АЕ waves should be processed with the accout of their losses i waveguides. REFERENCES [] Skalsky V. R., Koval P. M.: Acoustic emissio i fracture of materials, wares ad structures. Methodological aspects of selectio ad processig of iformatio. Lviv, Spolom, 005. [] Imeitova V., Cheryshev B. V., Shegai V. V.: O the calculatio of free vibratios of elastic cyliders of fiite legth Reports of Academy of Scieces of USSR. 976, Vol.6, No, P. 35. [3] Gricheko V. Т.: Equilibrium ad steadystate vibratio of elastic bodies of fiite sizes. Kiev, Naukova Dumka, 978. [4] Lysak M. V., Skalsky V. R., Serhiyeko O. M.: Ivestigatio of waveguide effect o the chage i parameters of acoustic emissio sigals. Physico-chemical mechaics of materials. 994, No, P. 64. [5] Adreykiv A. Е.: Spatial problems of crack theory. Kiev, Naukova Dumka, 98 [6] Kikuchi Е.: Ultrasoic trasducers Moscow, Mir, 97. [7] Zikevich О. К.: Fiite elemet method i egieerig. Moscow, Mir, 975. [8] Skalsky V. R., Koval P. M., Serhiyeko O. M., Lototsky Yu. L.: Research of hardeig of cocrete usig the sigals of acoustic emissio. Physico-chemical mechaics of materials, 004, No5, P.04. [9] Skalsky V. R.: Some methodological grouds of devise developmet for trasferrig acoustic emissio, Egieerig Sciece, 00, No7, P.49. [0] Skalsky V. R., Augutis V. N., Vaima A. B.: Devices for selectio of acoustic emissio sigals, Proc. of Karpeko Physico- Mechaical Istitute of Natioal Academy of Scieces of Ukraie Physical methods ad devices for testig eviromets, materials ad wares, Kyiv Lviv, 00. Vol.6, P. 77. [] Tripali A. S., Builo S. I.: Acoustic emissio: Physico-mechaical aspects. Rostov-o-Do: Publ. House of Rostov State Uiversity, 986. Valetie SKALSKY, Dr. Sci (Egieerig Scieces), the head of departmet Acoustic emissio diagostics of structural elemets of Karpeko Physicomechaical Istitute of Natioal academy of Scieces of Ukraie. He is the author over 30 papers i area of techical diagostics ad odestructive testig of materials ad structural elemets. Oleh SERHIYENKO, PhD. (mathematics ad physics) the seior research fellow of departmet Acoustic emissio diagostics of structural elemets of Karpeko Physico-mechaical Istitute of Natioal academy of Scieces of Ukraie. He is the author over 40 papers i area of fracture mechaics, techical diagostics ad o-destructive testig.

9 DIAGNOSTYKA (49)/009 7 FIDALI, URBANEK, Optimizatio Of A Set Of Thermovisio Image Features With The Use Of Evolutioary OPTIMIZATION OF A SET OF THERMOVISION IMAGE FEATURES WITH THE USE OF EVOLUTIONARY ALGORITHMS Marek FIDALI, Grzegorz URBANEK Silesia Uiversity of Techology, Departmet of Fudametals of Machiery Desig Gliwice ul. Koarskiego 8a, tel (03) , fax (03) , Summary Extractio of diagostic iformatio from the thermovisio images is coected with aalysis ad evaluatio of a huge amout of differet diagostic features which could cause problems with efficiet assessmet of techical state due to iformatioal oise. I the paper, applicatio of a evolutioary algorithm for optimizatio of a set of diagostic features has bee preseted. I the case of assessmet of selected optimal features, eural classifier has bee used. A set of 59 features has bee cosidered. Classificatio results have show that the evolutioary algorithm ca be applied i selectio of relevat diagostic features. Efficiecy of classifier has come to more tha 9%. Keywords: diagostics, ifrared thermography, evolutioary algorithms, eural etworks. OPTYMALIZACJA ZBIORU CECH OBRAZÓW TERMOWIZYJNYCH Z ZASTOSOWANIEM ALGORYTMÓW EWOLUCYJNYCH Streszczeie Ocea stau techiczego maszy a podstawie obrazów termowizyjych wymaga ich aalizy i wyzaczeia zwykle dużej liczby różych cech diagostyczych, które mogą utrudiać efektywą diagozę ze względu a szum iformacyjy. W artykule przedstawioo zastosowaie algorytmu ewolucyjego do optymalizacji zbioru 59 cech diagostyczych. Do ocey zoptymalizowaego zbioru cech posłużoo się klasyfikatorem eroalym. Wyiki klasyfikacji potwierdzają przydatość zastosowaia algorytmów ewolucyjych do wyboru cech relewatych. Sprawość klasyfikacji była większa iż 9%. Słowa kluczowe: diagostyka, termowizja, algorytmy ewolucyje, sztucze sieci euroowe.. INTRODUCTION Thermographic measuremets are broadly applicable i maiteace ad assessmet of techical states of machiery ad apparatus as well as idustrial processes [9]. Techological progress ad decreasig prices of idustrial thermovisio cameras have made the applicatio of such apparatus possible to be used i cotiuous moitorig ad idetifyig of states of machies ad devices [5]. Durig cotiuous thermovisio moitorig, a huge amout of images is recorded. These thermograms have to be aalyzed i the case of extractio of diagostic iformatio. There are a lot of image aalysis methods [7], []. Most of the existig methods ca be applied i thermogram aalysis [7] ad provide useful diagostic iformatio which allows to improve ad automate the diagostic process. As a result of thermovisio image aalysis, a huge amout of features (parameters) could be extracted. O the basis of results of the research reported i literature [4], [8], it ca be stated that a large set of diagostic features ca be a source of ambiguities i estimatio of techical state due to iformatioal oise. Redudacy as well as differeces betwee diagostic features cause determiatio of reasoably small size of the feature set for diagostic purposes to be very difficult. I the case of limitatio of features set, a variety of differet methods ca be used [4]. The evolutioary algorithm ca serve as a example of such a method. These algorithms are very efficiet at searchig ad optimizig multidimesioal sets of features, which has bee cofirmed by differet applicatios [6], [3], [6]. I the paper, the applicatio of a evolutioary algorithm for the optimizatio of a set of statistical features extracted from thermovisio images recorded durig cotiuous observatio of rotatig machiery is preseted. Scietific work fiaced from resources assiged to sciece i the years as a research project.

10 8 DIAGNOSTYKA (49)/009 FIDALI, URBANEK, Optimizatio Of A Set Of Thermovisio Image Features With The Use Of Evolutioary. ACQUISITION AND ANALYSIS OF THERMOVISION IMAGES I the case of cotiuous diagostics of machiery, a cocept of a moitorig system based o recorded ad aalyzed thermovisio images has bee proposed. Durig cotiuous object observatio with the use of a thermovisio device, a sequece of thermographic images i time t ca be recorded. A sigle thermographic image ca be treated as a discrete fuctio of temperature values of two variables T(x,y), where x ad y are coordiates of coordiate system determiig spatial resolutio of the image [9], [7]. O the basis of acquired series of thermograms, a multidimesioal thermographical sigal ST(T(x,y),t) ca be defied. If we cosider a cocept [3] of covetioal real time partitio ito micro (dyamic) ad macro (operatio) time which is frequetly applied i machie diagostics [], [8], the the thermographic sigal ca be defied i these both domais. Havig take micro ad macro time cocepts ito accout, the process of aalysis of thermographic sigals ca be divided ito two stages. The first stage is coected with thermogram aalysis ad feature extractio. It has eabled us to determie diagostic sigals i micro ad/or macro time (Fig. ). thermographic images. I order to obtai relevat diagostic iformatio, proper methods of thermographic image processig should be applied... Methods of thermovisio image aalysis Image aalysis is a wide domai of sciece which icludes a lot of differet kids of methods. These methods are described i a variety of papers [7], [], [7]. Oe of the well kow groups of image aalysis methods is a method dedicated to digital-image texture aalysis [0], []. The major issue i texture aalysis is feature extractio. This operatio allows us to compute characteristics of a digital image which eables umerical descriptio of its texture properties. Feature extractio is the first stage of image texture aalysis. This stage ca also be used for thermovisio images ad the obtaied results ca be applied i such approaches as image discrimiatio, classificatio or object shape determiatio. Statistical methods, which ca be eumerated amog differet methods of texture aalysis, make it possible to represet the texture idirectly by odetermiistic properties that determie the distributios ad relatios betwee grey levels of a image []. Statistical methods allow us to defie features of a image o the basis of differet statistical characteristics calculated from [0]: histogram of a image. gradiet matrix. ru-legth matrix. co-occurrece matrix. autoregressio model... Active diagostic experimet Fig.. Idea of aalysis of thermographic sigal i both micro ad macro time domais The secod stage of aalysis refers to aalysis of diagostic sigals which were determied at the first stage. For these purposes, classical sigal aalysis methods ca be applied. Aalysis of plots of parameters i micro as well as macro time could allow us to detect early machie failures ad draw up progoses related to a period of safe operatio. Durig this period, all repair procedures could be prepared. Cotiuous thermovisio diagostics of objects is coected with coductio of ecessary ad systematic actios cosistig i extractig of diagostic data which are decoded i recorded I order to verify usefuless of statistical methods for the aalysis of thermovisio images as well as for machiery diagostics, a active diagostic experimet has bee carried out. The experimet has bee performed with the use of a laboratory stad. The stad is located i the Laboratory of Techical Diagostics of Departmet of Fudametals of Machiery Desig ad cosists of a laboratory model of rotatig machiery ad thermovisio system (Fig. ). The aim of the experimet was to acquire thermographic sigals. As a result of diagostic experimets, series of thermograms recorded durig object operatio i differet techical states have bee obtaied. Thermographic images have bee acquired durig thermovisio observatios every 30 secods. The total umber of recorded images came to 840. The machie was workig with rotatio speed equal to 50 rmp.

11 DIAGNOSTYKA (49)/009 9 FIDALI, URBANEK, Optimizatio Of A Set Of Thermovisio Image Features With The Use Of Evolutioary Fig.. Visualizatio of laboratory stad -frame, -rotor,3-couplig, 4-bearigs set, 5-shaft, 6-break set, 7- air pump, 8- throttle valve, 9-thermovisio camera, 0-motor cotroller The followig techical states were simulated durig machie operatio: S machie without faults 40 images S 50% throttlig of air pump - 0 images S3 90% throttlig of air pump 0 images S4-90% throttlig of air pump + clearace of secod bearig moutig 0 images S5 load of disk brake 0 images S6 faulty bearig o 0 images..3. Estimated features of thermovisio images Recorded thermovisio images have bee aalyzed with the use of selected statistical texture aalyses. I this case, specialized software MaZda dedicated to calculatio of texture parameters (features) i digitized images has bee applied. MaZda was origially developed i 996 at the Istitute of Electroics, Techical Uiversity of Lodz (TUL), Polad for mammogram aalysis [5]. The software is able to aalyze gray scale digital images with separated regios of iterest ad extract up to 59 differet statistical parameters (features). Ever sice, i the case of thermogram aalysis, it was ecessary to separate regios of iterest (ROI) i the images. Five regios of iterest have bee defied (Fig. 3). Fig. 3. Exemplary thermographic image with selected regios of iterest (ROI) ROI motor, ROI couplig, ROI 3 bearig o, ROI 4 bearig o, ROI 5 pump For each regio of iterest (ROI) of every recorded image, 59 features have bee extracted The followig features [0][] have bee take ito cosideratio: 9 features estimated o the basis of histogram of the image (mea, variace, skewess, kurtosis ad five histogram percetiles for %, 0%, 50%, 90%, ad 99%), 5 features estimated o the basis of gradiet matrix (absolute gradiet mea, variace, skewess, kurtosis, ad percetage of o-zero gradiets), 0 features estimated o the basis of cooccurrece matrix. ( features calculated for matrices costructed for five distaces betwee image pixels (d=,, 3, 4 ad 5), ad for the four directios as i the case of ru-legth matrix features), 0 features estimated o the basis of ru legth matrix (short ru emphasis iverse momet, log ru emphasis momet, gray level ouiformity, ru legth ouiformity ad fractio of image i rus, separately for horizotal, vertical, 45 ad 35 directios) 5 features estimated o the basis of autoregressive model parameters (θi, i=,...,4 selected pixel-to-pixel relatio, oise stadard deviatio) 3. OPTIMIZATION OF A SET OF THERMOGRAPHIC IMAGE FEATURES I the case of the proposed diagostic method based o thermographic images, it is importat to fid such relevat features of images that ca be applied i a effective maer for the evaluatio of machie techical state. This is ot a simple task due to a large set of features which ca be extracted from the image with the use of statistical methods of image aalysis. Therefore it is importat to idetify a limited set of relevat ad optimal diagostic features. There are a few ways of limitatio of a set of features. Oe of the effective but time cosumig methods is comprehesive searchig. Good results i optimizatio of feature space ca be obtaied o the basis of discrimiat aalysis, ad, i particular, exteded Fisher s criterio [4], [5]. Aother way which provides very good results is the applicatio of evolutioary algorithms [6], [6]. As opposed to the kow feature selectio methods, evolutioary algorithms are able to search for a optimal set of features amog the whole feature set. The advatage of this strategy maifests itself i the fact that features are estimated i a global maer which allows cosideratio of relatio betwee features [6]. The evolutioary algorithms have bee applied to optimize features set extracted from thermal images which were recorded durig machie operatio. The type ad umber of features were selected by the evolutioary algorithm (Fig. 4) i a automatic way.

12 0 DIAGNOSTYKA (49)/009 FIDALI, URBANEK, Optimizatio Of A Set Of Thermovisio Image Features With The Use Of Evolutioary Maximizatio of efficiecy of state classifier has bee used as a optimizatio criterio. Classificatio of techical state has bee performed with the use of eural etworks implemeted i the algorithm. iput weights values= ad biases values=0. Parameters of euros of hidde ad output layers have bee determied as a result of etwork traiig. Traiig of the etwork has bee coducted with the use of geeral purpose, scaled cojugate gradiet backpropagatio algorithm []. The efficiecy of the classificatio has bee assessed by meas of calculatio of a relative umber of correctly classified examples: l eff = 00% l w () where: l umber of correctly classified examples, l w umber of all classified examples. L i L L out Fig. 4. Scheme of a evolutioary algorithm It has bee assumed that the populatio cosists of 30 idividuals. The geotype of a idividual is a biary vector with 59 bits. Each of these bits correspods to oe of cosidered features. Whe the value of the x bit is, it meas that feature No. x is selected for optimal features set. The pheotype of the idividual is the classifier idetified for features whose idetifiers are i the geotype. The classifier is a eural etwork (sectio 3.) The value of fitess fuctio for a idividual is the efficiecy of the classifier. The algorithm uses four operators [6], [3]: proportioal selectio, two-poit crossover (features replacemet), uiform mutatio, elitist successio. For the algorithm, the followig two termiatio coditios have bee determied: achievig 000 geeratios or, achievig 500 geeratios without icreasig the value of fitess fuctio. 3.. Neural etwork classifier I the case of machie techical state classificatio, a eural etwork has bee applied as a state classifier. The cosidered eural etwork has a simple structure due to a small umber of learig examples. O the basis of publicatio [], [8], it is assumed that a total umber of etwork parameters should amout to less tha /5 of the umber of learig examples. A structure as well as parameters of eural etworks have bee show i Fig. 5. The etwork has 3 layers: iput (L i ), hidde (L ) ad output (L out ). All euros i iput layer have Fig. 5. The structure of eural etwork classifier Tab..Parameters of eural etwork layer Li L Lout umber N (optimal umber 3 of euros of features) trasfer logsigmoid logsigmoid liear fuctio 3.. Optimizatio results Results of feature space optimizatio were preseted i Tab.. For each regio ofiterest, a huge set of 59 features has bee limited to o more tha features. Oe ca observe that features basig o a co-occurrece matrix were domiat i the optimal set of features. For every cosidered regio of iterest, selected features allow for classificatio of machie techical state with efficiecy greater tha 9%. Figure 6 shows plot of selected feature i fuctios of image umbers. Oe ca observe that i most of the cosidered ROIs chages of parameters have bee correlated with chages of machie techical state. Chages of techical state have bee visually detectable for parameters estimated i most of the cosidered regios of iterest. Less sesitive to techical chages was the couplig area (ROI) where it was difficult to detect techical chages. Couplig was rotated durig observatio ad cooled. It makes small temperature chages durig subtle techical state (S to S, S to S3, S3 to S4) chages udetectable.

13 DIAGNOSTYKA (49)/009 FIDALI, URBANEK, Optimizatio Of A Set Of Thermovisio Image Features With The Use Of Evolutioary Tab.. Results of optimizatio of thermovisio ROI No Classificatio 0,9 0,9 0,94 0,94 0,93 Efficiecy No of features Selected features 'S(,0)SumEtrp' 'S(0,)Correlat' 'S(0,)SumOfSqs' 'S(,)DifVarc' 'S(,)DifEtrp' 'S(,0)DifEtrp' 'S(0,)SumOfSqs' 'S(,)SumOfSqs' 'S(,)SumAverg' 'S(,)DifVarc' 'S(3,0)DifEtrp' 'S(3,3)AgScMom' 'S(3,3)SumVarc' 'S(4,4)SumOfSqs' 'S(4,4)DifVarc' 'S(4,-4)IvDfMom' 'S(4,-4)SumAverg' 'S(5,-5)DifVarc' '45dgr_RLNoUi' '35dr_RLNoUi' 'S(,)Correlat' 'S(,)SumOfSqs' 'S(,)SumEtrp' 'S(,-)Cotrast' 'S(,0)Etropy' 'S(,)SumVarc' 'S(,-)Correlat' 'S(,-)DifEtrp' 'S(3,3)SumVarc' 'S(3,3)DifEtrp' 'S(4,0)SumEtrp' 'S(4,0)Etropy' 'S(0,4)SumVarc' 'S(4,-4)SumEtrp' 'S(5,0)Correlat' 'S(5,0)SumEtrp' 'S(5,0)DifVarc' 'S(5,5)AgScMom' 'Horzl_GLevNoU' 'Vertl_RLNoUi' '35dr_LgREmph' 'S(0,)DifVarc' 'S(,)DifVarc' 'S(,-)Cotrast' 'S(,0)SumVarc' 'S(3,0)SumAverg' 'S(3,-3)SumAverg' 'S(3,-3)DifVarc' 'S(4,0)SumVarc' 'S(0,4)Cotrast' 'S(0,4)Etropy' 'S(4,-4)SumOfSqs' 'S(0,5)AgScMom' 'S(0,5)SumOfSqs' 'S(5,5)SumOfSqs' 'S(5,-5)SumVarc' 'Vertl_GLevNoU' '35dr_RLNoUi' 'GrNoZeros' 'Perc.0%' 'S(,-)SumVarc' 'S(0,)Cotrast' 'S(0,)SumVarc' 'S(,)DifVarc' 'S(,-)SumAverg' 'S(3,0)SumAverg' 'S(3,-3)SumEtrp' 'S(4,0)SumOfSqs' 'S(4,0)IvDfMom' 'S(4,-4)AgScMom' 'S(5,5)SumVarc' 'S(5,5)DifVarc' 'Vertl_ShrtREmp' '45dgr_Fractio' '35dr_LgREmph' 'S(,)SumAverg' 'S(,)SumEtrp' 'S(,-)Correlat' 'S(0,)SumEtrp' 'S(3,0)SumAverg' 'S(0,3)Cotrast' 'S(3,3)SumAverg' 'S(3,3)DifVarc' 'S(3,-3)SumOfSqs' 'S(4,4)Correlat' 'S(5,0)AgScMom' 'S(5,0)IvDfMom' 'S(0,5)SumEtrp' 'S(5,5)Correlat' 'S(5,5)SumEtrp' 'S(5,-5)SumOfSqs' 'S(5,-5)DifEtrp' 'Vertl_RLNoUi' 'Sigma' ROI S S S3 S4 S ROI a r c )D i fv S (3,3 ROI ROI ROI Fig. 6. Plot of diagostic sigal of Differece of Variace S(3,3) value extracted from all cosidered regios of iterest as a fuctio of umbers of cosecutive recorded images 3. CONCLUSIONS I the paper, results of study aimig at search for set of optimal diagostic features of thermographic images have bee preseted. Thermograms recorded durig a active diagostic experimet have bee aalyzed with the use of differet methods of statistical texture aalysis. As a result of the aalysis, a set of 59 diagostic features for every regio of iterest of each of 840 recorded images has bee obtaied. Five regios of iterest have bee cosidered. I order to detect optimal features, a evolutioary algorithm has bee applied. The assessmet of feature relevace has bee performed o the basis of classificatio results ad a simple eural etwork classifier has bee applied. The results of the research show that it is possible to fid such a optimal set of features of thermographic images that ca be used for classificatio of techical state of a machie with

14 DIAGNOSTYKA (49)/009 FIDALI, URBANEK, Optimizatio Of A Set Of Thermovisio Image Features With The Use Of Evolutioary high efficiecy. The usefuless of applicatio of evolutioary algorithms as oe stage of this procedure has bee proved. Authors expected that a umber of optimal features could be limited to 0. These features should allow for classificatio with higher efficiecy. It requires a icrease i a geeratio umber ad a algorithm modificatio. Such research is beig curretly coducted, however, due to cosiderable time cosumig computatio, results will be preseted i further publicatios. Results of the research also show that the proposed cocept of aalysis of sequece of thermovisio images ca be used for idetificatio of chages of techical states durig machie operatio. The aalysis of determied diagostic sigals idicates possibilities of applicatio of statistical methods of thermogram aalysis for determiatio of oe dimesioal diagostic sigal. Havig cosidered the discussed results, it ca be stated that cotiuatio of the research i this area is ecessary. Further research should be focused o improvig of the evolutioary algorithm i the case of obtaiig a umber of relevat features which should be as small as possible. Aother directio of the research will be focused o verificatio of other methods of image processig that could be useful for idetificatio ad classificatio of machie techical state. LITERATURA [] Aberdee D., Baxter J., Edwards R.: 9 /MFlops/s, Ultra-Large-Scale Neural- Network Traiig o a PIII Luster. citeseer.ist.psu.edu/aberdee00cmflopss.html. (000). [] Cempel Cz.: Fudametals of vibroacoustical coditio moitorig, i: A. Davies (ed), Hadbook of Coditio Moitorig. Techiques ad Methodology, Lodo, Chapma ad Hall, 998, pp [3] Cholewa W.: Method of machie diagostics with applicatio of fuzzy sets. Zeszyty Naukowe Nr 764. Politechika Śląska, Gliwice 983. (i Polish). [4] Ciupke K.: A comparative study o methods of reductio ad selectio of iformatio i techical diagostics. Mech. Syst. Sigal Process. 005 vol. 9, p [5] Fidali M.: A idea of cotiuous thermographic moitorig of machiery. QIRT 008 Proceedigs, 9th Iteratioal Coferece o Qualitative IfraRed Thermography, July -5, 008 Kraków, Polad. [6] Goldberg D. E.: Geetic Algorithms i Search, Optimizatio, ad Machie Learig, Addiso Wesley Publishig Compay, Ic., 989. [7] Gozales C. R.: Witz P.: Digital Image Processig. Addiso-Wesley Publishig Compay 987. [8] Korbicz J., Kościely J. M., Kowalczuk Z., Cholewa W. (Eds.): Fault diagosis. Models, artificial iteligece, applicatios, Spriger Verlag, Berli Heidelberg, 004. [9] Madura H.: Thermographic measuremets i practice. Agecja wydawicza PAK, Warszawa 004. (i Polish). [0] Materka A., Strzelecki M., Lerski R., Schad L.: Evaluatio of Texture Features of Test Objects for Magetic Resoace Imagig, Jue 999, Ifotech Oulu Workshop o Texture Aalysis i Machie Visio, Oulu, Filad, 3-9. [] Materka A., Strzelecki M.: Texture Aalysis Methods - A Review. Techical Uiversity of Lodz, 998, COST B Report. [] Matlab Help. [3] Michalewicz Z.: Geetic Algorithms + Data Structures = Evolutioary Programs. Spriger Verlag, Berli, (99). [4] Strzelecki M., Materka A.: Europea Project Cost B Quatitatio Of Magetic Resoace Image Texture. Zeszyty Naukowe 'Elektroika', vol. 4, 999, 5-4 (i Polish). [5] Thomas R. A.: The thermography moitorig hadbook. Coxmoor Publishig, Oxford, UK [6] Urbaek G.: Applicatio of evolutioary algorithms to idetificatio of diagostic iverse models, KPKM, Gliwice 006 (i Polish). [7] Wróbel Z., Koprowski R.: Thermographic image processig. Proceedigs of VI krajowej koferecji Termografia i termometria w podczerwiei. Ustroń 004. (i Polish). Marek FIDALI, PhD, assistat professor at Departmet of Fudametals of Machiery Desig. Mai area of research: techical diagostics, thermovisio, modal aalysis, sigal ad image processig Grzegorz URBANEK, PhD, desiger (automotive idustry), ethusiast for evolutioary algorithms

15 DIAGNOSTYKA (49)/009 WACHLA, A Framework For Kowledge Acqusitio System I Perspective View Of Diagostic 3 A FRAMEWORK FOR KNOWLEDGE ACQUSITION SYSTEM IN PERSPECTIVE VIEW OF DIAGNOSTIC OF ROTATING MACHINERY* Domiik WACHLA Silesia Uiversity of Techology, Departmet of Fudametals of Machiery Desig Koarskiego 8A str., Gliwice, Polad Summary A cocept of kowledge acquisitio system for the eeds of diagostic of rotor machies was preseted i the article. The cocept was developed o assumptio that kowledge would be acquired iductively through aalysis of measure ad simulative data. The foudig of the system was cosidered, The architecture was particularly described ad example of its applicatio was provided, as well. Keywords: kowledge acquisitio, diagostic of rotatig machiery, databases, support vector machies. SYSTEM POZYSKIWANIA WIEDZY Z PERSPEKTYWY DIAGNOSTYKI MASZYN WIRNIKOWYCH Streszczeie W artykule przedstawioo kocepcję systemu pozyskiwaia wiedzy dla potrzeb diagostyki maszy wirikowych. Kocepcję opracowao przyjmując założeie, że wiedza będzie pozyskiwaa w sposób idukcyjy poprzez aalizę daych pomiarowych lub symulacyjych. Omówioo geezę powstaia systemu. Szczegółowo opisao architekturę oraz pokazao przykład zastosowaia. Słowa kluczowe: pozyskiwaie wiedzy, diagostyka maszy wirikowych, bazy daych, metoda wektorów wspomagających.. INTRODUCTION Kowledge i techical diagostics is a kowledge which correspods to relatios occurrig betwee observed symptoms ad determied classes of techical state of a machie. Curretly coducted research cocetrates o acquisitio of the kowledge with applicatio of adequate umerical models of machies. Diagostic relatios (techical state symptom) are the result of aalysis of a model reactio to give chages of values of cotrol parameters. Provisio of a large amout of data is the basic feature of kowledge acquisitio based o a model approach. It results i a adequately cosiderable umber of diagostic relatios of which oly few have geeral meaig. As a cosequece, all defied relatios have to be cosidered i the process of diagosig a machie, which may decrease the efficiecy ad effectiveess of the process. Due to the above, aother cocise form of descriptio of these relatios is ecessary. The relatios may for istace be represeted i a form of decisio tables or decisio trees, eural models, euro-fuzzy models, ad others. Obtaiig a descriptio i oe of the listed forms requires applicatio of adequate methods of their idetificatio, which, i tur, results i preparatio ad use of appropriate tools.. A FRAMEWORK OF THE SYSTEM The architecture of the developed system of diagostic kowledge acquisitio was based o a two-fold model. The first layer is the base layer. Its purpose is to esure realizatio of tasks cocerig low-level computatios ad data maagemet. The base layer cosists of MATLAB eviromet ad MySQL Database Maagemet System. The two metioed elemets were chose due to criteria formulated at the stage of the system requiremets specificatio. The database system supports maagemet of big sets of data ad costitutes the secod elemet of the base layer. Due to its popularity ad availability, MySQL system was applied i the proposed architectural solutio. The commuicatio ad the exchage of data betwee MATLAB ad MySQL is esured by SQL iterface. A layer of implemetatio of algorithms costitutes the secod layer of the system architecture. This layer aims at providig fuctioality which facilitates realizatio of the process of database kowledge acquisitio. Accordig to the CRISP-DM methodology [6], the process of database kowledge acquisitio was divided ito a umber of stages e.g: data preprocessig, feature extractio ad selectio, data modelig, etc. Havig take the above iformatio ito accout, 4 routie toolboxes were distiguished i the layer of algorithm implemetatio. The * This work was supported by the polish Miistry of Sciece ad Higher Educatio (grat No. PBZ-KBN-05/T0/003)

16 4 DIAGNOSTYKA (49)/009 WACHLA, A Framework For Kowledge Acqusitio System I Perspective View Of Diagostic routie toolboxes provide fuctioality of the system withi: data maagemet, data preprocessig, feature/attribute selectio, data modelig. A umber of supportig procedures was implemeted withi the toolboxes of data maagemet. The procedures ivolved: eterig source data from the files geerated by the NLDW-MESWIR system [5] eterig ad savig data i the biary files i the iteral format of the MATLAB eviromet (mat-files), eterig ad savig data from/ito the files i the XML format, commuicatio ad exchage of data with the MySQL database server. The eterig ad readig of data from/ito the XML files from the level of the MATLAB eviromet is realized by meas of praser's XML laguage. The SQL iterface allows for direct commuicatio ad exchage of data betwee MATLAB ad the database. The iterface fuctioality facilitates data maagemet through formulatio of questios which are compatible with sematics ad specificity of the SQL laguage. A toolbox of data preprocessig icludes, i the first place, routies which support preparatio of the data acquired from the NDLW-MESWIR system. I particular, these are the routies of computatio of Mea Absolute Value (AVE), Room Mea Square Value (RMS), amplitude -phase spectrum, etc., ad routies of three- ad five-poit differetiatio of time series. I additio, the toolbox reders available a procedure of discretizatio of cotiuous attributes accordig to the algorithm which was itroduced by Fayyad ad Irai []. This procedure is used amog others by algorithms of feature selectio [4]. A metaprocedure costitutig implemetatio of the CFS algorithm (Correlatio-base Feature Selectio) [4] is the basic elemet of a toolbox of features/attributes selectio. The fuctioig of the CFS algorithm is based o the search of feature space alog with cosideratio of criterial fuctio which provides quatitative iformatio about the importace of the chose subsets of features. The operatio of the CFS algorithm requires implemetatio of at least oe method of the search of state space. Due to this requiremet, the feature selectio toolbox provides implemetatio of two algorithms of the search of state space, i.e. the Best First algorithm [7] ad the Simple Geetic Algorithm [3]. A toolbox of algorithms of data modelig is a ext elemet of the implemetatio layer. The procedures implemet algorithms of the Support Vector Machies (SVM) method [], i.e. C-SVM, ν-svm, ε-svr ad ν-svr [9]. The C-SVM ad ν-svm algorithms are applied i costructio of classifyig models, whereas the ε-svr ad ν-svr algorithms are used i modelig of regressive problems. For the eeds of the system, the LibSVM [] toolbox was adapted; the toolbox icludes implemetatios of the metioed SVM algorithms. The other uit of data modelig supports validatio of geerated models through: routies which determie values of model statistics such as classifier performace [0], ad a set of routies which implemet some techiques of model evaluatio e.g. k-fold cross-validatio [8]. 3. EXAMPLE OF SYSTEM APPLICATION To show capabilities of the system, a problem of detectig ad locatig cracks i the shafts of a high power turbie uit was cosidered. Moreover, it was assumed that the costructed classifier should locate the cracks i the shafts with accuracy of a selected stage of the turbie set. The solutio to the established task required realizatio of a umber of ordered activities which resulted from the methodology of data kowledge acquisitio. I particular: acquisitio of a set of source data, defiitio ad determiatio of features from the set of source data, costructio of a set of learig examples, idetificatio ad validatio of the classifier. 3.. The Source Data The eeded data were obtaied from a umber of simulatios coducted with a applicatio of a umerical model of a 00 MW turbie set. The model was costructed at IMP PAN i Gdańsk. It was built as a FEM model of a TK 7 turbie uit at Kozieice S.A power plat. The model was adjusted to a real object o the basis of data gathered by the DT00- diagostic system [5]. I order to costruct a model of a turbie set, the NLDW-MESWIR system was used [5]. O the basis of the objectives of the research, a pla of geeratig learig data was prepared. A set of 9 cases which iclude a process of crackig i the turbie set i 4 locatios was take ito accout. The 4 locatios iclude: a high pressure stage (HP), a itermediate pressure stage (IP), a low pressure stage (LP) ad a geerator (GEN). The set was supplemeted with a base case which was iterpreted as a referece state i which o defects occur. A detailed pla of geeratig learig data was preseted i the Tab.. A simulative experimet was carried out for each plaed case. The results of calculatios coducted with the use of the NLDW- MESWIR system were copied ito text files.

17 DIAGNOSTYKA (49)/009 WACHLA, A Framework For Kowledge Acqusitio System I Perspective View Of Diagostic 5 Tab.. The pla of geeratig source data: α p -agular positio of the crack, Wp - o-dimesioal coefficiet of the depth of the crack Defect ame Elemet No. α p W p Example No. Class label Base case PBARTMAX Cracks i HP stage 3 70 {0.050, 0.075, 0.00,, 0.650} 6 CRHB Cracks i IP stage 59 0 {0.050, 0.075, 0.00,, 0.650} 7 5 CRIDA Cracks i LP stage {0.050, 0.075, 0.00,, 0.475} 5 69 CRLFB Cracks i geerator 5 5 {0.050, 0.075, 0.00,, 0.600} 70 9 CRGBC 3.. Learig Data I diagostic of rotatig machiery, the fudametal evaluatio of a techical state is based o aalysis of chose frequecy compoets of amplitude-phase spectra of mechaical vibratios [5]. The frequecy compoets are coected with rotatio velocity of a rotor. I particular, the elemets 0.5X, 0.33X, 0.5X, X, X, 3X ad 4X are evaluated; where X i [Hz] deotes a omial frequecy of rotatio of a rotor. Havig take the above ito accout, it was assumed that the learig examples would be costructed as sets of a selected frequecy compoets of amplitude-phase spectra defied for vibratio sigals which were obtaied at the stage of geeratig source data. Two sets of learig examples were established. A divisio criterio was applied i relatio to the sigal category. The first set of learig examples was defied for the velocity of absolute vibratios fixed i the x ad y directios. The secod set was established for relative vibratios fixed i the x ad y directios, as well. I each sets of learig examples, 96 features were marked. The research objectives, i.e. classifiers iductio, require a defiitio of a set of adequate categories for the cosidered problem. O the basis of the pla of geeratig learig data (tab. ), 5 categories were defied ad labeled as: CRHB, CRIDA, CRLFB, CRGBC ad PBARTMAX. The two complete sets of learig examples were obtaied Feature Selectio Accordig to the methodology of kowledge discovery from databases, a stage of idetifyig ad verifyig the classifier should be preceded by a stage of the relevat feature selectio. Such a procedure aims at acquirig models which are characteristic of decreased complexity as well as icreased geeralizig capabilities. For this reaso, the process of relevat feature selectio was coducted usig CFS algorithm [4]. The scheme of feature selectio cosisted of experimets where the followig algorithms were used for searchig of feature space: The Best First algorithm [7] oce, The simple geetic algorithm [3] te times. Withi the Best First algorithm, a strategy of bi directioal search was used. I tur, for the simple geetic algorithm, values of parameters recommeded i the literature [3] were assumed. The etire umber of features i both sets of learig examples was reduced from 69 to: 69, for the set of learig examples costructed o the velocity of absolute vibratios, 4, for the set of learig examples costructed o the relative vibratios. The details of the obtaied results are show i [] Idetificatio ad Validatio of a Classifier Takig ito accout the objectives of the coducted ivestigatios, the ν-svc algorithm was cosidered to be applied i buildig a classifier for detectio ad localizatio of cracks i shafts of the turbie set. The idetificatio of SVM classifiers was coducted for: sets of learig examples cotaiig a complete set of features, sets of learig examples cotaiig oly the features marked i the selectio process. The followig idetifiers distiguishig these sets were accepted i order to differetiate betwee the particular learig sets: FS a idetifier for learig sets with a complete set of features, BF a idetifier for learig sets i which features were selected by meas of the Best First algorithm, GA GA0 a idetifier for learig sets i which features were selected as a result of a tefold activatio of the geetic algorithm. Tab.. The SVM classifiers idetificatio scheme Model ID Kerel fuctio ν C γ SVM-LIN Liear 0..0 SVM-RBF RBF The accepted categories of determied SVM models ad the applied learig parameters of the ν- SVC algorithm were preseted i the Tab.. The values of the ν ad C metaparameters were selected o the basis of our ow kowledge ad o the preexperimets. The method of k-fold cross validatio with a set of learig examples divided ito 3 subsets was applied i the process of the classifier idetificatio. The quality of the idetified classifiers was measured by calculatio of, amog

18 6 DIAGNOSTYKA (49)/009 WACHLA, A Framework For Kowledge Acqusitio System I Perspective View Of Diagostic others, a classifier performace. The obtaied results were preseted i Fig.. a) b) Fig.. Classifiers performace: a) absolute vibratios b) relative vibratios The results (Fig. ) prove high efficiecy of the procured SMV classifiers ot oly for the complete sets of learig examples (FS), but also for the sets of learig data created o the basis of selected sets of relevat features (BF, GA-GA0). It eeds to be oted that the highest efficiecy of the SVM classifiers is observed i the case of the complete sets of learig data; the efficiecy slightly decreases alog with the decrease i the umber of features i the learig sets. Such a pheomeo may result, amog others, from the maer i which the SVM method fuctios or from the properties of the CFS algorithm. Due to the limited scope of the coducted research, the obtaied results caot costitute a explicit recommedatio to omit the stage of the feature selectio i the process of kowledge acquisitio. Noetheless, they prove that the prepared system requires further study. 4. SUMMARY While preparig the system, it was take ito accout that the system is meat to acquire diagostic kowledge with the use of learig data geerated by the NLDW MESWIR software o the basis of the model of a power plat turbie set. The system verificatio was coducted alog with realizatio of a practical task cocerig model (kowledge) acquisitio for a hypothetical problem of idetificatio of a classifier which detects ad locates cracks i the shaft of the turbie set. Such a approach facilitated examiatio of the system as far as the implemetatio ad the correctess of the project assumptios are cocered; the project assumptios are coected with the system fuctioality. The acquired results prove validity of the assumptios ad the practical usefuless of the system. Additioally, data cocerig the system areas requirig supplemetatio ad correctios were obtaied. REFERENCES [] Chag C. C., Li C. J. LIBSVM: a library for support vector machies, 00. cjli/libsvm. [] Fayyad U. M., Irai K. B.: Multi-Iterval Discretizatio of Cotiuous-Valued Attributes for Classificatio Learig. I 3 th Iteratioal Joit Coferece o Ucertaily i Artificial Itelligece (IJCAI93), pages 0 09, Chambery, Frace, 993. [3] Goldberg D. E. Geetic Algorithms i Search, Optimizatio, ad Machie Learig. Addiso- Wesley Professioal, 989. [4] Hall M. Correlatio-based Feature Selectio for Machie Learig. PhD thesis, Waikato Uiversity, Departmet of Computer Sciece, Hamilto, NZ, 998. [5] Kiciński J. et al.: Modelowaie i diagostyka oddziaływań mechaiczych, aerodyamiczych i magetyczych w turbozespołach eergetyczych (i Polish). IMP PAN, Gdańsk, [6] Larose D. T.: Discoverig Kowledge i Data: A Itroductio to Data Miig. Wiley- Itersciece, 004. [7] Michalewicz Z., Fogel D. B.: How to Solve It: Moder Heuristics. Spriger-Verlag, Berli Heidelberg, 004. [8] Moczulski W.: Metody pozyskiwaia wiedzy dla potrzeb diagostyki maszy (i Polish). Zeszyt 30, Politechika Śląska, Gliwice, 997. [9] Schölkopf B., Smola A. J. Learig with Kerels: Support Vector Machies, Regularizatio, Optimizatio, ad Beyod. MIT Press, Cambridge, MA, USA, 00. [0] Witte I. H., Frak E.: Data Miig: Practical machie learig tools ad techiques. Morga Kaufma, Sa Fracisco, editio, 005. [] Vapik V.: The Nature of Statistical Learig Theory. Spriger-Verlag, New York, 995. [] Wachla D. System Verificatio. I Ciupke K., Moczulski W. eds., Kowledge Acqusitio For Hybrid Systems of Risk Assessmet Ad Critical Machiery Diagosis. ITE, Radom, 008. Domiik WACHLA (PhD Eg.) is a assistat professor at the Faculty of Mechaical Egieerig at Silesia Uiversity of Techology i Gliwice. His research is focused o the applicatio of methods of artificial itelligece i the techical diagostics of machiery ad idustrial processes.

19 DIAGNOSTYKA (49)/009 BRZÓZKA, MFC/IMC Scheme As A Fault Tolerat Cotrol Structure 7 MFC/IMC SCHEME AS A FAULT TOLERANT CONTROL STRUCTURE Jerzy BRZÓZKA Maritime Uiversity of Szczeci, Departmet of Vessel s Cotrol Systems Szczeci, Podgóra 5/53 St., Polad; Summary The paper deals with the fault tolerat cotrol i two-loop cotrol system structure (MFC/IMC, Model Followig Cotrol/Iteral Model Cotrol). System cosists of the model of a oliear plat ( mai ship egie) ad two PID cotrollers. I distictio from other works o this subject (the MFC/IMC structure), special attetio was paid to robustess of the liearized structure to perturbatios caused by the plat parameters chages, differet ucertaities, chages of the operatig poits ad tuig parameters of the cotrollers as well as catastrophic failures formed i the cosidered structure. The simulatios carried out i MATLAB /Simulik software. Keywords: robust cotrol, fault tolerat cotrol, process perturbatio, model followig cotrol (MFC). ODPORNY NA USZKODZENIA UKŁAD REGULACJI TYPU MFC/IMC Streszczeie Artykuł dotyczy regulacji odporej w dwu pętlowej strukturze MFC/IMC zawierającej model ieliiowego obiektu regulacji (prędkości obrotowej wału okrętowego silika główego) i dwa regulatory PID. W odróżieiu od iych prac a temat struktury MFC/IMC, w artykule tym szczególą uwagę zwrócoo a odporość struktury zliearyzowaej a perturbacje parametrów regulowaego procesu, odporość a perturbacje spowodowae różymi zaburzeiami, p. wywołaymi zmiaami puktów pracy obiektu, parametrami regulatorów lub uszkodzeiami katastroficzymi struktury. Symulacje zostały wykoae w programie MATLAB /Simulik. Słowa kluczowe: regulacja odpora, regulacja tolerująca uszkodzeia, perturbacje procesu, regulacja śledząca z modelem.. INTRODUCTION Fault tolerace of dyamic systems ca be achieved either from system robustess to faults ad other ucertaities, or from cotroller recofiguratio or restructurig i respose to special faults. Actually, a well-desiged cotrol system may have some fault tolerace capabilities what ca be desiged (e.g., by properly choosig feedback gais) to compesate for some system ucertaities such as disturbaces ad oise, ad the fault ca be cosidered as a kid of system ucertaity. This paper proposes a fault-tolerat cotrol strategy for fault based o the use of MFC/IMC structure. There is o eed to desig special diagostic observers which is the mai advatage of this structure.. PROPERTIES OF A LINEAR MFC/IMC STRUCTURE Accordig to [5] the MFC/IMC structure is show i Fig.. The special advatage of MFC/IMC structure is that the model M(s) does ot have to be exactly equal to the process P(s), because i such a situatio the process P(s) is cotrolled by the sum of two compoets: cotrol sigals from R m (s) ad R(s) cotrollers. If M(s) = P(s) the R(s) cotroller does ot work ad preseted structure acts as a classical fixed value cotrol loop. This structure is ofte described as the system with two-degree-offreedom (DOF). r(s) + R m (s) M(s) R(s) d(s) + + P(s) + + Fig.. Geeral block diagram of MFC/IMC structure, where idividual trasfer fuctios mea: M(s) model, P(s) plat, R m (s) model cotroller, R(s) plat cotroller ad r(s) set poit value, y(s) process cotrolled value, d(s) disturbaces Plat trasfer fuctio P(s) is give by Eq. (): P( s) = M ( s) + Δ( s), () ( ) where ) (s Δ is plat perturbatios. Fuctios S ad T have bee assumed as measures of robustess ad IAE (Itegral of the Absolute Error) criterio for step resposes as a performace idex. The simulatios ad calculatios were carried out i MATLAB. + y(s)

20 8 DIAGNOSTYKA (49)/009 BRZÓZKA, MFC/IMC Scheme As A Fault Tolerat Cotrol Structure O the basis of Fig., the process cotrolled value y(s) is give by Eq. (): where: y ( s) = r( s) S( s) + d( s) T ( s), () Rm ( s) P( s) ( + R( s) M ( s) ) ( R ( s) + R( s) + R ( s) R( s) M ( s) ) S( s) =, (3) + P( s) m is the sesitivity trasfer fuctio ad T( s) = + P( s), (4) ( R ( s) + R( s) R ( s) R( s) M ( s) ) m + is the complemetary sesitivity trasfer fuctio. Addig Eq. (3) ad Eq. (4) yields equatio (5), which represets the relatio betwee sesitivity fuctios S(s) ad T(s): m m ( R( s) P( s) ) T ( ) S ( s) = + s. (5) 3. EXEMPLARY MFC/IMC STRUCTURE As a example, the dyamics of the revolutio speed cotrol of the mai ship egie (Fig. ad Fig. 3) has bee cosidered as a plat. 3.. Plat A liearized real plat has bee created as a approximatio of the oliear cotiuous fuctios f (for dead zoe) ad f s (for saturatio) at the give operatig poit (A; op). Liearizatio of these gives (6): um (6) 4 3 s s + 03s s where values of um of the trasfer fuctios (6) are give i the Table. Table. Values of the trasfer fuctio umerator (6) at a give operatig poit A A = um= Block diagram of the plat is show i Fig.. Fig.. Block diagram of the oliear, cotiuous real plat of the mai ship egie (values of plat parameters: k c = 0.8; T cc = 0.05 sec; T = 3 sec; k t = 0.5) 3.. Model The block diagram of a oliear model of the mai ship egie dyamics is show i Fig.3 [3]. The same (idepedetly of a operatig poit) model i the form of the first-order plus time-delay was take for the process. The time-delay was replaced by secod-order Pade approximatio. Liearizatio of the model (Fig. 3) was performed by meas of the describig fuctios J (A) for dead zoe ad J s (A) for saturatio at give operatig poits. Fig. 3. Block diagram of the oliear, ocotiuous model for the mai ship egie dyamics (values of model parameters: dead zoe 0.; 0.; saturatio.;.; τ = 0.05 sec; k cm = 0.8; T ccm = 0. sec; T m =.5 sec; k tm = 0.) 3.3. Cotrollers Plat cotroller R m (s) ad correctig cotroller R(s) have bee tued i Simulik Respose Optimizatio toolbox for fully oliear MFC/IMC structure. The tuig parameters of the process ad correctig PID cotrollers are: k m = 3; T cm = 0 sec; T dm = 0.7 sec ad k k = ; T ck = 5 sec; T dk = 0.05 sec, respectively. 4. ANALYSIS OF EXEMPLARY FAULTS IN MFC/IMC STRUCTURE 4.. Stability aalysis The stability study of the oliear MFC/IMC structures (at differet parameters of the process, model or cotrollers, discoected outputs of R(s) or R m (s) cotrollers, discoected model s output) has bee doe by meas of the roots computatio of the characteristic equatios for the give liearized scheme. I these cases, the characteristic equatios have the followig forms (7 0): for the fully workig structure: + P( s) ( Rm ( s) + R( s) + Rm ( s) R( s) M ( s) ) = 0, (7) for discoected output of R M : + P( s) R( s) ( + Rm ( s) M ( s) ) = 0, (8) for discoected output of R (R m works, oly): + P( s) Rm ( s) = 0, (9) For discoected output of M: + P( s) ( R( s) + Rm ( s) ) = 0. (0) It is easy to otice that characteristic equatios (7 0) are created by rejectio of eedless compoets i equatio (7). These equatios are sometimes called a iterval polyomials.

Fig 5 Spectrograms of the original signal (top) extracted shaft-related GAD components (middle) and

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