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[140] SICARD, P., LEVINE, M. D. Joint recognition and tracking for robotic arc welding. IEEE Transactions on Systems, Man, and Cybernetics, 19(4), July/August 1989,714-728. [141] BAMBA, T. An arc-welding robot with a compact visual sensor. IN: Nomura, H. et al. (Eds. ) Welding guide II - Sensors and control systems in arc welding - The state of the art in Jam. Technical Commission on Welding Processes, Japan Welding Society, 1991,11-23 to 11-27. [142] BACK, B., FRAZEN, A. See, weld. Manufacturing Engineer, 71(4), April/May, 1992,19,22-23. [143] DREWS, P., STARKE, G. Development approaches for advanced adaptive control in automated arc welding. IN: Proceedings of the I1W International Conference on Automation and Robotization in Welding and Allied Processes, 2-3 September 1985, Strasbourg, France, 115-124. [144] DAVEY, P. G. et al. Laser sensors for arc welding robots. IN: Lane, J. D. (Ed. ), Robotic Welding - International trends in manufacturing technology. Bedford, UK : IFS, 1987,105-115. [145] NIEPOLD, R., BRUMMER, F. Pass -a visual sensor for seam tracking and on-line process parameter control in arc welding applications. IN: Lane, J. D. (Ed. ), Robotic Welding - International trends in manufacturing technology. Bedford, UK : IFS, 1987,129-140. [146] NAKATA, S., JIE, H. Construction of a visual sensing system for in- process control of arc welding and its application in automatic weld line tracking - study on visual sensing systems for in-process control of arc welding (4th report). Welding International, 4(11), 1990,845-850. [147] SAMEDA, Y. Fuzzy seam-tracking controller. IN: Proceedings of the IEEE International Conference on Industrial Electronics. Control. Instrumentation. and Automation (IECON 92), 09-13 November 1992, San Diego, CA, USA, 966-970. [148] RICHARDSON, R. W. et at Coaxial arc weld pool viewing for process monitoring and control. Welding Journal, 63(3), 1984,43-50. [149] SUGA, Y. et al. Recognition of the weld line by a visual sensing system and weld line tracking in automatic welding of thin aluminum plates. Welding International, 7(4), 1993,273-279. [150] GROOM, K. N. et al. Automatic single V-groove welding utilising infrared images for error detection and correction. Welding journal, 69(12), 1990,441s to 445s. 213
[151] DAVIS, A. R. Orr-line gap detection techniques for adaptive control of GMAW. Cranfield University. M. Sc. Thesis, 1993. [152] YAMANE, S. et al. Sensing and fuzzy logic control of weld pools in pulsed MIG welding. Welding International, 7(5), 1993,378-383. [153] INOUE, K. YI, N. Application of neural network to visual inspection of weld beads. Welding International, 7(11), 1993,857-862. [154] LUCAS, W. Computers in arc welding - the next industrial revolution. Part 3: Instrumentation and process analysis. Metal Construction, 17(7), 1985,431-436. [155] VANDOREN, A. H. Data acquisition systems. Reston, VA, USA: Reston Publishing Company, 1982. [156] REHFELDT, D. et al. Microcomputer-based instrumentation for analysing and monitoring arc welding processes. 3U' TWI International Conference on Computer Technology in Welding, 4-7 June 1990, Brighton, UK, 36-45. [157] STEIN, J. and DOMNFELD, D. A classification and design methodology for manufacturing process sensor systems. IN: ISCIE Japan-USA Symposium on Flexible Automation -A Pacific Rim Conference, 1990, Kyoto, Japan, 675-679. [158] SCHELLHASE, M. Investigation into arc welding process monitoring by statistical signal analysis. IIW Doc. 212-497-81,1981. [159] DOEBELIN, E. O. Measurement systems: application and design, 4`h Edition. New York: McGraw-Hill, 1990. [160] LOVE, P. and SIMAAN, M. Automatic recognition of primitive changes in manufacturing process signals. Pattern Recognition, 21(4), 1988,333- 342. [161] CHAWLA, K. S. Objective on-line assessment of the performance of flux cored wires by real time computer based monitoring. Cranfield Institute of Technology, PhD Thesis, 1993. [162] SIEWERT, T. A. et al. Through-the-arc sensing for monitoring arc welding. IN: "International Trends in Welding Science and Technology", Proceedings of the 3d International Conference on Trends in Welding Research, 1-5 June 1992, Gatlinburg, Tennessee, USA, 1037-1040. [163] HOUPIS, C. H. and LAMONT, G. B. Digital control systems: theory. hardware, software. New York: McGraw-Hill, 1985,87-88. 214
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CRANFIELD UNIVERSITY GC CARVALHO AN
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ABSTRACT The aim of this work was t
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I dedicate this work to the memory
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FIGURES TABLES APPENDICES NOTATION
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3.3.2.1 Welding parameters generato
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References Further reading Appendic
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Figure 3.12 Offsets for weld start
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Figure 6.31 Voltage step input test
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Figure J. 2 Plot of stand-off varia
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Table A. 1 Welding extended entity
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NOTATION A, Electrode sectional are
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Pr(ign) Possibility measure of proc
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1. Introduction Welding is the thir
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Chapter 4 describes the on-line pos
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In pulse transfer, the welding curr
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Pd = Pv - pzh-s (2.1) where Pd is t
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the bridge. Another factor that ind
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establish the stable conditions for
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Philpott [ref. 21] developed an on-
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current peak at the moment the tip
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obot on the line must be individual
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collision detection capabilities wh
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cause dynamic variation in the seam
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Another type of robot static calibr
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spatter the gas nozzle is particula
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Table 2.1: Joint positioning tolera
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In order to minimise the undesirabl
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c) Ultrasonic sensors; d) Through-t
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where K,, K2, K3 and K4 are constan
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Philpott [refs. 21,131], based on t
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centre. This is attributed to the m
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technique must be employed to preve
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" digital hardware, which is basica
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" Maximum value, W.: Wmý = max(W )
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process studied over a small range.
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In-process welding control is a muc
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volume caused by the presence of a
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SHIELDING GAS IN CONSUMABLE ELECTRO
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Arc voltage Anode Arc length I Anod
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computed ideal procedure optimisnti
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CONSTANT CURRENT POWER SOURCE `j' O
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Original Surface New Surface Electr
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otating welding wire direction weld
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3.1.1.1 Robot errors A robot arm is
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3.2.2 Programming error correction
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3.3.2 Off-line programming module I
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Pen is the weld penetration (side p
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a. 2) Geometrical constraints from
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Step 11 Step 12 Step 13 Step 14 Ste
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Step 21 Step 22 If the wire feed sp
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the Y'-axis results in a positive "
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_ p1e0a - pORoba m31 Ilp! - poll (3
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of a robot in its zero position12 w
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frame points to the front of the ro
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CAD Off-line (AutoCAD) programming
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Z Surface 4 A Y 7 M2 Open Edge Join
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WCF World Co-ordinates Frame 2a = J
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x Torch Co-ordinates Frame o Indica
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vo Ö 't7 Y7 't O m O 'S O O S O S
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ýý aý 0 oA aW ö A O Zt A OO 't
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Ti 9ý-! i4 *Tx t ap31 jx ý- ymin
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errors', (i. e. joint positioning,
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was considered to be outside the sc
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Table 4.3 - Linguistic representati
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The introduction of such a reduced
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Table 4.8 - Final welding process c
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the collection of welding data corr
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Step 4- Calculate the confidence of
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Z Table Co-ordinates Frame Y X Robo
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5.3 Monitoring system The monitorin
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the torch end. Only one degree of f
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Current: 500 Position: 234.5 5.7.3
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I" va JI ºr ö C 3 r" r" rl f_ £-
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IgurC a. H -I UI qur vCiSUJ JpCCU C
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126
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Table 6.1 - Welding trials carried
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Table 6.3 - Coefficients of Ogunbiy
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Note that the calibration model sho
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Table 6.6 - Welding parameters used
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constant set-up welding parameters
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stickout lengths and the temperatur
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of the dip mode of metal transfer.
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which would become active by settin
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In section 4.2.5 it has been mentio
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300 280 260 240 rd 35- 3D 25 20 15
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Figure 6.5 - Measured "versus" Pred
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i S 0 -0.1 -0.2 -0.3 -0.7- 68 10 12
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32.0 E 31.5 y 31.0 30.5 30.0 j 29.5
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35 - 30 p 15 10 0.00 2.60 5.42 8.23
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40 35 30 25 20 15 10 A+iIII+F0.17 2
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30 28 26 24 22 SO_act [mm] DipR [mo
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22 20 18 SO_act [mm] DipR [ohm/100]
Page 187 and 188: !: 30 25 20t 10 5-- 0 Dip Transfer
Page 189 and 190: 0.430- - 0.380- - :r 0.330 fPR L- 0
Page 191 and 192: 7.2 Tests with varying stand-off an
Page 193 and 194: Table 7.3 - Bead geometry along the
Page 195 and 196: ö a2 ., u" u,.., g .,. aucyuaac VI
Page 197 and 198: 0 24-- 22-- 18 210 1 90 0 v 170 mm
Page 199 and 200: Q 34 32 3o mIm Viewing direction Fl
Page 201 and 202: ýa 34 mm JO a .. ý nn ýr "u 00 M
Page 203 and 204: 22 20 18 Viewing direction Flange W
Page 205 and 206: 36 33 31 o 29 t 350 310 o 290 U due
Page 207 and 208: I C, x -i 23 21 j 19 Q 240c WFS =10
Page 209 and 210: en 34 32 - vsec 30- 26- 24 + .. ++
Page 211 and 212: 186
Page 213 and 214: " to design and build the hardware
Page 215 and 216: Although only linear joints were im
Page 217 and 218: for predicting possibility of bad a
Page 219 and 220: 8.4 Process monitoring and control
Page 221 and 222: satisfy the required quality criter
Page 223 and 224: 198
Page 225 and 226: types of joints and multi-pass weld
Page 227 and 228: [14] NEMCHINSKY, V. A. The effect o
Page 229 and 230: [38] D1LTHEY, U. , REICHELL, T. , S
Page 231 and 232: [64] KING, F-J. and HIRSCH, P. Seam
Page 233 and 234: [86] CARGNELLI, M. and ROGOWSKI, A.
Page 235 and 236: [109] KURKIN, N. S. and DRIKKER, V.
Page 237: [130] USHIO, M. , LIU, W. , MAO, W.
Page 241 and 242: [177] COOK, G. E. Feedback and adap
Page 243 and 244: [201] WON, Y. J. and CHO, H. S. A f
Page 245 and 246: 220
Page 247 and 248: 222
Page 249 and 250: wnum: local variable which defines
Page 251 and 252: Table A. 1 - continuation List item
Page 253 and 254: Imean = a2 + b2*WFS + c2*SO + d2*SO
Page 255 and 256: TCP2 number are also defined. The o
Page 257 and 258: f ROBSET. DAT: This file is created
Page 259 and 260: Figure C. 3 - Main dialogue box of
Page 261 and 262: Choose the set of welding parameter
Page 263 and 264: Water Cooling optic fibre bundle 0
Page 265 and 266: Figure E. 1 - Main graphical screen
Page 267 and 268: 242
Page 269 and 270: Table G. 2 - Interface box external
Page 271 and 272: Robot ii Controller +24W CO . +24Vd
Page 273 and 274: 248
Page 275 and 276: Table 1.1 - continuation Run Vpk M
Page 277 and 278: 10- y =0.001ac 0 r. dSO [mm] $0 '10
Page 279 and 280: 5.00- 0.00 y=0.0019x 1000 1500 2000
Page 281 and 282: Table J. 7 - Welding data collected
Page 283 and 284: Table J. 10 - Welding data collecte
Page 285 and 286: Table J. 13 - Welding data collecte
Page 287 and 288: 20.00- 15. M y=0.0047x - 1.7922 10.
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Table J. 18 - Welding data collecte
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266
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Table K. 1- continuation Set-up par
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Table K. 1 - continuation Set-up pa
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Table K. 2 - continuation Set up pa
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Table K. 2 - Continuation Set-up pa
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Table K. 3 - Continuation Set-up pa
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Table K. 3 - Continuation Setup par
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