Ie.P. Chvertko, A.Ie. Pirumov, M.V. Shevchenko
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1 88 Наукові вісті НТУУ "КПІ" 214 / 2 UDC : Ie.P. Chvertko, A.Ie. Pirumov, M.V. Shevchenko MONITORING OF WELDING PROCESSES WITH APPLICATION OF ARTIFICIAL NEURAL NETWORKS The pper presents summry of methods of monitoring systems development for the processes involving heting of filler mteril nd/ or se metl y the electric current nd with periodicl shortges of the welding circuit. The processes investigted were MAG welding, underwter flux-cored welding nd flsh-utt welding. Detils of experiments, primry dt processing procedures sed on sttisticl nlysis methods re descried, the im of primry processing eing otining of informtive prmeters of the welding processes. Detils of neurl network structure development, trining nd control sequences genertion, nets trining nd dequcy check re presented s well. Comprison of determintion of process vritions (edge shifting, electrode outlet, vrition of gp, vrition of joint line for rc welding methods; decresing of open-circuit voltge nd specimen trvel speed for flsh-utt welding) is presented. The on-line monitoring systems sed on neurl networks developed for evlution of process devitions re lso elieved to e dequte for determintion of process violtions resulting in disturnces of welding prmeter nd cn e used for prediction of possile defects in the welded joints. Keywords: MAG welding, underwter FCAW welding, flsh-utt welding, process monitoring, detection of defects. Introduction Modern methods of non-destructive testing of welded joints often involve use of complex equipment nd re rther lour-intensive. Their ppliction reduces the overll productivity of welded structures production. However even with these methods it is not resonle from the economicl point of view to control every single weld, especilly in conditions of series mnufcture. From the other hnd, the requirements to the qulity of ll the joints within the production lot remin the sme. Currently reserch is performed to define the chrcteristics of qulity of welded joints y energy prmeters of welding with ppliction of intellectul systems. Such systems decrese prticiption of humn in the process of qulity control thus reducing its cost nd sujectivity. Evlution of possiility of development of up-to-dte systems of qulity monitoring sed on nlysis of electric process prmeters is tsk to e solved. One of the wys seems to e n ppliction of rtificil intelligence systems. For fusion nd resistnce welding processes some methods of development of qulity monitoring systems were proposed. The reltionship etween prmeters devitions nd possiility of typicl defects formtion ws defined s well for the processes mentioned [1, 2]. Such reltionships mke it possile to develop utomted systems for welding process monitoring which simultneously provide predicting of the weld qulity. For fusion welding processes it is possile to identify different disturnces y neurl networks (this pproch cn e effectively used in cse of on-site welding, for exmple, in underwter wet welding) [3, 4]. It is lso possile to develop the qulity control system sed on Fuzzy Logic methods [5]. The sme tsk cn e solved using neurl networks for pressure welding methods, for exmple, for flsh-utt welding [6]. Ojective The ojective of this work ws to mke summry of principles of development nd dequcy check of methods of welding processes monitoring nd prediction of qulity of welded joints sed on monitoring of electricl prmeters of welding. Generlly the tsks of welding processes monitoring re clssifiction-like which mkes it possile to solve them using neurl networks. Detils of experiments Reserch ws performed for three welding technologies: gs-shielded rc welding (MAG welding), underwter flux-cored rc wet welding (FCAW) nd flsh-utt welding (FBW). In ll the processes mentioned the heting of filler mteril nd/ or se metl re followed y prtil or full periodicl shortings of welding circuit. Such signl form is good for ppliction of utomted dt processing methods. In MAG welding most of such shortges re ccompnied y filler metl trnsfer to the welding pool while in underwter FCAW most of them do not provide the metl trnsfer. In FBW shortges re indicting processes of locl
2 МАТЕРІАЛОЗНАВСТВО ТА МАШИНОБУДУВАННЯ 89 contcts formtion. Periodiclly they overhet nd explode with energy relese in the welding zone. This mens tht even though the signls re like the effect of welding circuit shortges on the weld formtion differs from method to method. Bse metl nd filler mteril heting in ll the processes mentioned cn e evluted y the energy input which is defined y the vlues of current nd voltge. It should e mentioned tht in cse of FBW on the equipment with strict drives without feedck it is possile to pply singlefctor mesuring system [2]. Experiments were mde to perform recording of electricl prmeters: voltge (in the secondry circuit of the welding mchine for FBW nd rc voltge for rc welding methods) nd welding current (for rc welding methods only). Mesuring system included nlog-digitl converter E-14 (L-Crd, Russi), voltge nd current sensors (LEM, Switzerlnd) nd the system for primry dt collecting nd processing developed y the uthors. In ll the experiments the smpling frequency ws set t 1 khz which is sufficient for signl recover for the welding methods investigted [7]. The development of monitoring system sed on rtificil intelligence lgorithms involves the trining procedure. During the trining set of reference ptterns is to e nlyzed y the system. To crete the sets of reference ptterns for the trining nd dequcy check of the neurl networks severl series of experiments in welding were done for every of the methods, including welding with its prmeters set s it is recommended y literture nd with devitions from these vlues. These devitions were sed on continuous disturnces which often occur in welding production nd which were ig enough to cuse the reducing of weld qulity chrcteristics. Experiments in MAG welding were performed using the ПС-25 power source, wire feeding mechnism LISA 14RB nd А-141 utomtic welder. The se welding prmeters were set t: welding current 9 A (direct current, electrode positive), rc voltge 19 V, welding speed 18 m/hour (the speed ws stilized y the utomted system). The specimens to e welded were produced from low-cron steel 2 mm thick. For the continuous disturnces simultion specil specimens were used s shown on Fig. 1: with vrile gp, stick-out distnce, weld line shifting nd edge symmetry. а c d Fig. 1. Specimens for rc welding with continuous disturnces: edge symmetry; stick-out distnce vrition; c gp vrition; d weld line shifting Experiments in underwter FCAW were performed using АСУМ 4 utomted welder, the specilized system for welded joint moving, highpressure chmer (for simultion of depth of sumersion). The ППС-АН2 flux-cored wire (developed for underwter welding) ws used. The se underwter wet welding prmeters were set t: welding current 2 A (direct current, electrode positive), rc voltge 3 V, welding speed 8 m/hour. The specimens were mde of low-cron steel 1 mm thick, only the root runs were welded. The continuous disturnces were simulted in the sme wy s for MAG welding. Experiments in FBW were performed on the МСО-66 welding mchine with strict electricmechnicl drive without feedck. The rods mde of low-cron semi-killed steel 14 mm di were welded. The se welding prmeters were set t: open circuit voltge 4,87 V, verge speed 6,5 mm/s, djusting length 25 mm, verge upsetting speed 1 mm/s, tolernce for flshing 1 mm nd for upsetting 4 mm, time of upsetting with current on,4 s. Continuous disturnces were simulted y chnging of min process prmeters: open circuit voltge, speed nd djusting length, only one prmeter ws chnged per time. When the corresponding disturnces were ctive the welding prmeter were set t: open circuit voltge 4.17 V, speed 3 mm/s, djusting length 5 mm. As fr s in FBW the weld itself is formed during the upsetting stge, ut its qulity is significntly determined y the se metl heting during the flshing, the upsetting prmeters were kept intct for ll the experiments.
3 9 Наукові вісті НТУУ "КПІ" 214 / 2 Development of welding monitoring systems Welding process monitoring should e sed on continuous nlysis of electricl prmeters nd identifiction of possile disturnces continuously or immeditely fter the process is finished. Identifiction of such disturnces cn e performed s clssifiction of oscillogrms frgments for the prmeters to e nlyzed or s pttern recognition. The LVQ (Lernіng Vector Quntіztіon) neurl network ws pplied to solve these tsks. Preprtion of dt for network trining. After welding nd mesuring of its prmeters the dt rrys were otined for MAG welding (Fig. 2), underwter FCAW (Fig. 3) nd FBW (Fig. 4), ll of them eing quite of ig size. The preliminry dt processing nd reduction ws needed to mke it possile to pply the LVQ networks. U, V I, A ,5,1,15,2,25 Fig. 2. Frgments of rc voltge (а) nd welding current () ptterns for MAG welding I, A U, V ,5,5,5,1,1,1,15,15,15,2,25,35,45 Fig. 3. Frgments of rc voltge (а) nd welding current () ptterns for underwter FCA welding,3,2,25,3 Time, s,3,2,25,3 Time, s,35,35,35,4,4,4,4,45,45,45 U, V Fig. 4. Frgment of secondry circuit voltge pttern for flshutt welding For MAG welding severl prmeters should e nlyzed simultneously to tke into ccount the process fetures. The following vlues were chosen s the input signls for the neurl network: stndrd devitions of rc voltge σ nd,5,5,5, ,1 6,2 6,3 welding current 6,4 6,5 Time, s 6,6 6,7 6,8 6,9 2 σ I (indicte stility of the electricl prmeter during the period of time), men vlues of rc voltge μ U nd welding current μ I (indicte devitions of the prmeter from the pre-set vlue) nd the men durtion of shortges t sc (indictes the filler mteril trnsfer stility) [1]. The men durtion of shortges ws clculted y the oscillogrm of voltge. To clculte the prmeters mentioned the oscillogrms were split into sections with durtion.1 s (equl to the minimum durtion of the disturnce which cn cuse defect formtion) [8]. The finl mtrix for every experiment contined 5 vriles, its dimensions were R 5, where R = Т/1 (for smpling frequency 1 khz) numer of locks, Т overll numer of vlues recorded. For underwter FCAW the dt mtrix ws otined using the lgorithm similr to the one developed for MAG welding. The mtrix included men vlues nd stndrd devitions of rc voltge nd welding current s well s the density of shortges for ech section (the oscillogrm of voltge ws used to clculte it). The finl mtrix dimensions were R 5, where R = Т/1. Choice of different prmeters of shortges for MAG welding nd underwter FCAW ws sed on descried ove fetures of filler metl trnsfer. As fr s during underwter FCAW mostly the gloulr metl trnsfer with occsionl shortges occurs, it should e nlyzed y the density of shortges D sc. 2 U 6,1
4 МАТЕРІАЛОЗНАВСТВО ТА МАШИНОБУДУВАННЯ 91 In cse of the FBW the high-frequency component of the voltge ws otined y mens of ppliction of digitl Butterworth filter with pulsed finl chrcteristic nd frequency nd 1 Hz nd higher. To simplify the utomted dt nlysis the signl ws fterwrds turned into unidirectionl form nd integrted y sections equl to.2 s (1 periods of mins frequency) eing the minimum disturnce durtion which cn cuse defect formtion [6]. All dt rrys were reduced to the sme dimension, the lst element in ech rry eing the first signl vlue fter the current ws turned off. The finl rry dimension ws 8 1. To prevent the effect of vritions of the preset welding prmeters nd of stochstic mesurement errors on the results of dt nlysis the normliztion procedure ws pplied. The clcultions were performed ccording to the following eqution: i () min i () =, (1) mx min where i ( ) initil vlue, the one to e normlized; mx, min respectively mximum nd minimum vlues in the dt rry; i ( ) normlized vlue. As result mtrices were otined for every welding method with the minimum vlue equl to nd mximum equl to 1 in ech of them. Fig. 5. Appliction of neurl networks for MAG nd underwter FCAW (), for FBW () The dt otined were used s neurl network inputs. For the rc welding methods the tsk ws to nlyze ech section of the oscillogrm equivlent to.1 s y the vlues of 5 prmeters (the locks with their dimension 1 5 were presented one y one to the input). As result of nlysis these locks were clssified s those with or without disturnces (see Fig. 5, ). For FBW the whole dt rry ws presented to the network input. The dt were clssified s those without disturnces, those with reduced voltge (this clss included extension of the djustment length) nd those with reduces speed (see Fig. 5, ). Neurl network trining. The numer of neurons in the output (liner) lyer of the LVQ network is equl to numer of dt clsses. For rc welding methods this numer ws 2, for FBW 3. The numer of neurons in the input (competitive) lyer should exceed their numer in the output lyer t lest twice. In the empiric wy it ws defined to e 1 for ll the methods. The vlue of error limit for the trining ws set t 1 %. To prevent the reverse error propgtion the lgorithm with inertnce of weight coefficients djustment nd shifting ws pplied s well s tht of trining speed coefficient dpting. The numer of trining cycles ws set t 1. The dt were presented to the network input. The dt vector for trining included ten dt mtrices of informtive signls per every experiment. The trget vector for rc welding methods ws developed to identify the disturnce presence, for the FBW it included dt out the welding prmeters: without disturnces or with vrition of the defined prmeter. The qulity of network trining ws performed y the effectiveness fctor [9]. After the network trining the elements used for it were presented to the network input nd the numer of right responds ws clculted. For rc welding methods the numer of right nswers ws equl to numer of oscillogrm sections for which the presence of disturnce ws identified in right wy, for FBW to the numer of informtive signls clssified in right wy. The precision of trining sequence nlysis ws clculted s: B Т T =, (2) R where В numer of right responds, R totl numer of locks for trining. For ll the networks developed Т T ws equl to 1 for every welding method.
5 92 Наукові вісті НТУУ "КПІ" 214 / 2 Appliction of the developed networks for monitoring of welding processes The effectiveness of the neurl networks developed ws performed y presenting to their inputs dt mtrices which were not used for trining (the control sequence). For the welds otined during the experiments included to the control sequence some dditionl tests were done to evlute their qulity chrcteristics. For rc welding methods the visul tests were pplied while for FBW joints their tensile strength ws determined with tensile test nd the microstructure nlysis ws performed. The signls (for FBW) nd the signl sections (for rc welding) were divided into clsses y the process vritions (see Fig. 6). Effectiveness of the neurl network ppliction ws clculted s [9]: Т C Е =, (3) Т T where Т C precision of control sequence processing. As fr s for ll the networks Т T = 1, Е = Т К. The neurl networks developed successfully identified the defects which were formed s result of disturnces (see Tle). Effectiveness of networks ppliction ws higher then.85. In FBW the vrition if speed is determined error-free. The previously defined reltionships etween disturnces nd qulity chrcteristics of the welded joints [1, 4, 6] s well s the results of qulity control of the joints from the control sequence mke it possile to pply the networks developed oth for process monitoring nd for prediction of presence of typicl defects in the welded joints. Informtive signls descried in Item 3.1 of this pper pper to e qulittive chrcteristics of the corresponding welding processes. Tle. Results of ppliction of neurl networks Effectiveness of network ppliction Group of specimens MAG Underwter welding wet FCAW FBW No devitions,92,92,96 Welding with prmeter devitions,95,85 Reduced open circuit voltge,92 Reduced speed 1, The method descried cn e pplied for ll the welding methods involving heting of the filler mteril nd/ or the se metl with the electric current. The generl lgorithm of the development of utomted monitoring system sed on the rtificil intelligence ppers to e s followed: 1. Anlysis of the electricl prmeters, of their dynmics nd of reltionship etween them nd processes of heting, input of filler mterils to the welding zone nd joint formtion. The prmeters to e mesured nd requirements to the dt recording system re to e defined; 2. Development of preliminry dt processing sed on the process fetures (heting, input of filler mterils to the welding zone nd joint formtion); 3. Development of the clssifiction neurl network, including genertion of trining sequence nd network structure definition; 4. Genertion of the control sequence sed on the results of qulity control of welded joints with up-to-dte methods stted y the Stndrds; 5. Evlution of the effectiveness of network ppliction using the control sequence, conclusions out the possiility of ppliction of the network developed in the conditions of welding production. 1 Fig. 6. Exmple of neurl network ppliction for MAG process monitoring (the specimen with vrile gp): the welded joint; neurl network respond
6 МАТЕРІАЛОЗНАВСТВО ТА МАШИНОБУДУВАННЯ 93 Conclusions Monitoring of welding processes s well s prediction of formtion of typicl defects in the welded joints cn e performed utomticlly y mens of rtificil intelligence systems, in prticulr the clssifiction neurl networks. The respond of the network is clssifiction of the weld section or the whole joint s the one with its qulity ffected y the disturnces or not. The numer of clsses is to e defined for ech process seprtely. The effectiveness of LVQ neurl networks ppliction ppers to e sufficient for monitoring of MAG welding, underwter FCA welding nd flshutt welding. The generl lgorithm of the development of utomted monitoring system ws developed for the welding processes involving heting of filler mterils nd se metl with the electric current. The development includes process prmeters nlysis, development of the dt collecting system, development of the neurl network nd check of the effectiveness of its ppliction. Appliction of such method for MAG welding, underwter FCA welding nd flsh-utt welding hs shown sufficient results. It is resonle to pply the welding monitoring systems developed in the wy s descried ove in full-scle nd mss production to perform 1 % qulity control of the welded joints. If the devitions of the process re identified, the joints should e tested using stndrd methods of nondestructive testing. Further reserch should e crried out to develop integrted guidnce for formtion of informtive signls for different groups of welding methods. Reference List 1. A.E. Pirumov et l., Qulity monitoring of welding y electric chrcteristics of process, Reserch Bulletin of NTUU KPI, no. 5, pp , I.O. Skchkov nd E.P. Chvertko, Evlution of stility of the flshing process in flsh-utt welding, The Pton Welding J., no. 3, pp , E.V. Lzrson, Methods of rtificil intelligence in welding. Prt 1: Dt collecting nd formliztion, Welding Production, no. 5, pp , I.O. Skchkov et l., On neurl network ppliction for welded joint qulity control in underwter welding, The Pton Welding J., no. 6, p. 21, C.S. Wu et l., A Fuzzy Logic System for Process Monitoring nd Evlution in GMAW, Welding J., no. 2, pp , Ye. Chvertko et l., Monitoring of the process of Flsh- Butt Welding, Soldgem & Inspeçãгo, vol. 18, no. 1, pp , S.I. Bskkov, Rdio circuits nd signls. Russi, Moscow: Higher School, 2, 462 p. 8. F.N. Kisilevskiy nd V.V. Dolinenko, Mthemtic simultion nd development of MIG welding controller, The Pton Welding J., no. 2, pp , V.P. Dykonov nd V.V. Kruglov, Mthemtic pplictions for MtL. Russi, Sint-Petersurg: Piter, 21, 48 p. Рекомендована Радою зварювального факультету НТУУ КПІ Надійшла до редакції 9 січня 214 року
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