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parameter generator and five levels of voltage" were tested for each combination of stand-off and wire feed speed, such that the influence of the welding voltage could be detected. The welding parameters and the welding data collected are shown in Appendix K. Due to the differences in the resistance components present in the dip and the spray modes of metal transfer, two multiple regression models (one for each mode of metal transfer) were developed based on the model of equation (6.11). The coefficients obtained are shown in Table 6.8, together with the standard error (SE) and the coefficient of determination of the fitted models (R2). Table 6.8 - Coefficients for dip resistance based stand-off estimation models Model for dip mode metal transfer Model for spray mode metal transfer 0.00165 0.021468 al -0.000027 -0.000568 a2 - - 0 0.010645 1 -0.001485 -0.029601 2 - 0.004404 3 0.000078 0.0007 SE 0.000371 0.002110 R2 0.9900 0.9997 Obs: The coefficients marked with an hyphen ("=) did not present a good significance level and were considered null. Note that the stand-off estimation models developed present the general form shown in equation (4.8), that is, a linear model whose coefficients are functions of the welding parameters. This is very similar to the dip resistance model developed by Philpott [ref. 131] with the difference that this latter has a constant slope and the intercept is considered null (see equation 2.18). In order to validate the dip resistance based estimation models, bead-on-plate welding trials were carried out with the stand-off varying linearly in different slopes. Table 6.9 shows the welding parameters used and the start and end stand-off values. Figure 6.15 to Figure 6.28 show some of the validation results and compare the actual stand-off with the dip resistance based estimation and the estimation obtained by using equation (2.22) with the coefficients shown in equation (6.4). Note that in most situations in the dip mode of metal transfer, the stand-off predicted by the dip resistance based model is more precise and presents a smaller range of oscillation than the prediction based on the welding current cumulative differences. It should also be noted that in the spray mode of metal transfer, the dip resistance based prediction oscillates in a pattern very similar to the prediction based on the welding current cumulative differences. This can be expected since in this case the measured resistance includes the component due to the welding arc, which decisively influences the welding current. Hence, it produces a less robust stand-off estimation than in the case 6 The voltage suggested by the welding parameters generator, V,., two levels below this value, V. 4- 0.5 and V e-1.0 , and two levels above, V, a+0.5 and V,, +1.0. 139 -
of the dip mode of metal transfer. One advantage, though, is that the dip resistance based estimation model produces an absolute stand-off estimation, whereas the model proposed by Ogunbiyi produces an estimation relative to the initial welding current. Table 6.9 - Welding parameters used in the validation trials for the dip resistance based stand-off estimation models Run WFS [m/min] Vet [volts] SOdt Imml SO. a Metal transfer vall 4.5 19.1 12 20 dip val2 5.5 20.7 20 12 dip val3 6.5 21.0 12 20 dip val4 6.5 21.6 20 12 dip va15 8.5 22.2 12 20 dip va16 8.0 22.2 20 12 dip val7 10.0 32.8 12 20 spray va18 10.5 32.6 20 12 spray valll 10.0 22.4 12 20 dip va112 10.0 22.5 20 12 dip vall3 5.5 20.0 12 15 dip vall4 5.5 20.3 15 12 dip val15 8.5 22.2 12 15 dip va116 8.5 22.2 15 12 dip va117 10.0 22.4 12 15 dip va118 4.5 19.4 15 18 dip val19 6.5 21.5 18 15 dip va120 8.5 22.2 15 18 dip val21 10.5 32.7 18 15 spray va122 12.5 33.1 15 18 spray va123 14.5 33.3 18 15 spray va124 4.5 19.4 15 20 dip va125 6.5 21.6 20 15 dip va126 8.5 22.2 15 20 dip va127 10.5 32.6 20 15 spray va128 12.5 33.1 20 15 spray va129 14.5 33.7 15 20 spray SO.,, : -zstand-off` at start of the slope Weld length: 200 mm SOed : stand-off at the end of the slope Welding speed (Sw): 0.5 mlmin The dip resistance based stand-off estimation model developed above was validated for bead-on-plate welding trials carried out in the flat position. During initial flat position fillet welding trials, it was observed that the model produced a stand-off estimation with a value smaller than the actual stand-off. Considering that in fillet joints the weld pool is constricted, it can be expected that a certain bead build up will occur below the welding arc, thus effectively reducing the distance between the 140
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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
Page 113 and 114: Z Surface 4 A Y 7 M2 Open Edge Join
Page 115 and 116: WCF World Co-ordinates Frame 2a = J
Page 117 and 118: x Torch Co-ordinates Frame o Indica
Page 119 and 120: vo Ö 't7 Y7 't O m O 'S O O S O S
Page 121 and 122: ýý aý 0 oA aW ö A O Zt A OO 't
Page 123 and 124: Ti 9ý-! i4 *Tx t ap31 jx ý- ymin
Page 125 and 126: errors', (i. e. joint positioning,
Page 127 and 128: was considered to be outside the sc
Page 129 and 130: Table 4.3 - Linguistic representati
Page 131 and 132: The introduction of such a reduced
Page 133 and 134: Table 4.8 - Final welding process c
Page 135 and 136: the collection of welding data corr
Page 137 and 138: Step 4- Calculate the confidence of
Page 139 and 140: Z Table Co-ordinates Frame Y X Robo
Page 141 and 142: 5.3 Monitoring system The monitorin
Page 143 and 144: the torch end. Only one degree of f
Page 145 and 146: Current: 500 Position: 234.5 5.7.3
Page 147 and 148: I" va JI ºr ö C 3 r" r" rl f_ £-
Page 149 and 150: IgurC a. H -I UI qur vCiSUJ JpCCU C
Page 151 and 152: 126
Page 153 and 154: Table 6.1 - Welding trials carried
Page 155 and 156: Table 6.3 - Coefficients of Ogunbiy
Page 157 and 158: Note that the calibration model sho
Page 159 and 160: Table 6.6 - Welding parameters used
Page 161 and 162: constant set-up welding parameters
Page 163: stickout lengths and the temperatur
Page 167 and 168: which would become active by settin
Page 169 and 170: In section 4.2.5 it has been mentio
Page 171 and 172: 300 280 260 240 rd 35- 3D 25 20 15
Page 173 and 174: Figure 6.5 - Measured "versus" Pred
Page 175 and 176: i S 0 -0.1 -0.2 -0.3 -0.7- 68 10 12
Page 177 and 178: 32.0 E 31.5 y 31.0 30.5 30.0 j 29.5
Page 179 and 180: 35 - 30 p 15 10 0.00 2.60 5.42 8.23
Page 181 and 182: 40 35 30 25 20 15 10 A+iIII+F0.17 2
Page 183 and 184: 30 28 26 24 22 SO_act [mm] DipR [mo
Page 185 and 186: 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
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Although only linear joints were im
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for predicting possibility of bad a
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8.4 Process monitoring and control
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satisfy the required quality criter
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198
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types of joints and multi-pass weld
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[14] NEMCHINSKY, V. A. The effect o
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[38] D1LTHEY, U. , REICHELL, T. , S
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[64] KING, F-J. and HIRSCH, P. Seam
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[86] CARGNELLI, M. and ROGOWSKI, A.
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[109] KURKIN, N. S. and DRIKKER, V.
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[130] USHIO, M. , LIU, W. , MAO, W.
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[151] DAVIS, A. R. Orr-line gap det
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[177] COOK, G. E. Feedback and adap
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[201] WON, Y. J. and CHO, H. S. A f
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220
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222
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wnum: local variable which defines
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Table A. 1 - continuation List item
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Imean = a2 + b2*WFS + c2*SO + d2*SO
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TCP2 number are also defined. The o
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f ROBSET. DAT: This file is created
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Figure C. 3 - Main dialogue box of
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Choose the set of welding parameter
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Water Cooling optic fibre bundle 0
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Figure E. 1 - Main graphical screen
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242
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Table G. 2 - Interface box external
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Robot ii Controller +24W CO . +24Vd
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248
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Table 1.1 - continuation Run Vpk M
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10- y =0.001ac 0 r. dSO [mm] $0 '10
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5.00- 0.00 y=0.0019x 1000 1500 2000
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Table J. 7 - Welding data collected
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Table J. 10 - Welding data collecte
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20.00- 15. M y=0.0047x - 1.7922 10.
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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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