AVERAGE DIFFERENCE IN LOCAL MAXIMA AND MINIMA

Figure 12. Average difference in local maxima and minima versus integral gain (Kj).

1S


RESULTS

The tracking errors measured at increments along the length of the weld were reduced to three
values for each sample’ maximum difference in errors, root mean square (RMS) error, and average
difference between local maxima and minima. These values are illustrated for a typical weld in Figure 6.
The maximum difference in errors indicates the ability of the system to correct for the step offsets.

This quantity is pnmarily a measure of speed of response, and is not indicative of steady-state error or
stability. The RMS error is usually a good measure of overall accuracy, but in the present tests it was
dominated by the large deviations at the step offsets. Steady-state error is better evaluated by inspection
of the plot of deviation from the seam with respect to position. The third statistical value, average
difference between local maxima and minima quantifies the tendency toward oscillation in the control
response.

A plot of maximum difference in errors as a function of proportional gain (Kp) is displayed in

Figure 7. Clearly, the accuracy of response to sudden disturbances (the step offsets) was improved as
Ky was increased. The slope of the curve decreases to essentially zero around $2B to $33 ($ indicates

hexadecimal base). A plot of RMS error with respect to Kp is shown in Figure 8. Since this term was

dominated by the deviations at the step offsets, the majority of the curve is of the same shape as that in
Figure 7. However, at high values of Kp, the RMS error begins to increase as stability begins to break
down.

The average difference between local maxima and minima is plotted in Figure 9 as a function of
differential gain (Kg). After the first set of tests were conducted, a “bug” im the control algorithm was

discovered and corrected at OSU: the differential term had been negative when it should be positive.
Inspection of the curve in Figure 9 reveals that varying Kg had little effect over a large range. The

stability began to decrease for differential gains below about ~-$0A.

Increasing the seam data average weight (SDAW) tended to increase oscillation as shown
graphically in Figure 10. With the negative Ky, the effect of increasing SDAW was severely magnified.

A photograph of the actual weld sample for K 3 = -OA and SDAW = 2 is displayed in Figure 11. The
stability was clearly marginal, as no damping of the oscillation was apparent.

A plot of average difference between local maxima and minima with respect to integral gain
(K;) is shown in Figure 12. As with SDAW, the tendency to oscillate with increased values of Kj was

magnified when Kg was negative. With Ky positive, the curve in Figure 12 shows only a gradual increase
with greater levels of K,. The steady-state error showed little change with increased Kj over the stable
range. This 1s illustrated by the curves of Figures 13 and 14. With K; = 2 the plot of error with respect
to location along the joint actually showed some increase in steady-state error over that for Kj =0.

* The $ indicates hexadecimal notation, used when entering these values into the computer program.


ORIGINAL PAGE IS

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19


Figure

10.

11.
12.
13.
14.
15a.

15b.

LIST OF ILLUSTRATIONS

Classes of stability 2.0.6... ccc ccc cee cee tee eee e teen eect ene te eens
View seen by OSU welding control system ......... 0. eee eee eee cette teens
Cross-sectional view of sample edges ........... 00. c cece cece eee eee eee eees
Sample surface showing reference lines ....... 0.0.0 eee cece cece e eee
Programmed test path. ....... ccc ec cece ce eee eee eee teen eee eeenee
Representative plot showing values used for evaluation................eeeeeeees
Maximum difference in errors versus proportional gain (K,

Diet eeeeee tees

RMS error versus proportional gain (Kp) See eee eee eee eee eee e eet e ee etee
Average difference between local maxima and minima versus differential gain (Kg) ..

Average difference in local maxima and minima versus seam data
average weight (SDAW) ... 2.2.0.0... cece eee eee eee eee Lee eee e eee enee

Photograph of test sample exhibiting marginal control stability..................
Average difference in local maxima and minima versus integral gain (Kj)......-....
Representative sample showing steady-state error (Kp = 2B, K, = 00).............
Tracking error with respect to position along the joint for Ky = 2B, Kj;=0.2......
Front view photograph of test sample welded with optimal control parameters .....

Back view photograph of test sample welded with optimal control parameters... ...

13

14

15

16

16

18

19

”


{\ see State Error

Position along joint

DEVIATION OF WELO BEAD FROM JOINT
(inch)
°

-9 100 4

-0 200 4

Figure 13,

0 200 _

8
L

(inch)

°

2 Sn SO tr
(full scale)

Representative sample showing steady-state error (Ky = 2B, Kj = 00).

f\ Position along Joint

DEVIATION OF WELD BEAD FROM JOINT

-0 100

4

-0 2004

TO i) crs (full scale)

Figure 14. Tracking error with respect to position along the joint for Kp = 2B, Kj = 02.


APPROVAL

INFLUENCE OF CONTROL PARAMETERS ON THE JOINT TRACKING PERFORMANCE
OF A COAXIAL WELD VISION SYSTEM

By K. J. Gangl and J. L. Weeks

The information in this report has been reviewed for technical content. Review of any informa-
tion concerning Department of Defense or nuclear energy activities or programs has been made by the
MSFC Security Classification Officer. This report, in its entirety, has been determined to be unclassified.

al ; & WV GA LAI HE
. J. SCHWING: ER\

Director, Materials and Processes Laboratory

22 wrUS GOVERNMENT PRINTING OFFICE 1986—631-058/20062


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= Symbol Ky
= 4a
=

0.100-4
2 °
4
4
=
x
=
4
SS ~
ox
ss

<
zo
uo
3S
& 0.0507
ir
va
c
S
w
Oo
xt
&
S
=z

‘ T i
0 1 2 3

SDAW

Figure 10. Average difference in local maxima and minima versus seam data average weight (SDAW).

13


portion of the integral gain is not variable. While a certain amount of integral gain is helpful in removing
steady-state errors, too large an increase in this term can effectively decrease stability.

The proportional term produces an offset which varies linearly with error. This is generally the
most useful term in dictating the speed of response to a given error. The differential contribution to the
offset is related to the difference between the present error and that from the previous sample. This
term serves as a damper on the control response, it tends to decrease the rate of change of the offset
command.

PROCEDURE

Plan of Investigation

When developing the test to evaluate and optimize the trajectory control parameters for the OSU
vision system, care was taken to avoid catering to a particular situation. The test plates were prepared to
provide conditions for good joint detection through the entire length of the weld. This essentially
“ideal” fitup 1s considered best for adjusting the control parameters because deviations from the ideal
condition are not aiways known in advance when making production welds. In addition, isolating the
tests from the effects of jomt detection simplified the analysis considerably.

Observation of tracking performance requires a controlled disturbance of the torch from the joint
path. The test developed used a straight joint configuration for simplicity, the 1obot was programmed to
provide a ramp offset and two step offsets from the joint location. A ramp offset is a standard test
which primarily indicates the tendency toward steady state error. Step inputs are more severe disturb-
ances which better demonstrate the dynamic response.

The parameters studied were assumed to be independent of one another for the purposes of these
tests. According to Farson of OSU, this assumption is valid as long as the extremes of the usable ranges
are not approached. Thus, although extreme values were used in order to define the limits of each
parameter, the choice of optimal values was not affected because they occurred well within the usable
range.

The proportional gan (Kp) was the most influential of the parameters considered, and was there-
fore given the most study. When varying Kp, the other three parameters were left at their default values.
The optimal value of Kp was then used for the remainder of the tests.

Experimental Procedure

‘The test welds were run on square butt joints, consisting of two 0.125 in. thick, Inconel 718
plates. For welds 1 through 56, one plate was 7 in. x 2 in. and the other was 7 in. x 1.5 in. The
butting surfaces were ground flat to provide fitup with a maximum gap of 0.010 in. The top surface of
each plate was sanded in a | in. strip adjacent to the joint with 120 grit emery cloth. The plates were
wiped with acetone pnor to welding.

The procedure was revised slightly for welds 57 through 82 to umprove joint detection. The plate
dimensions for the revised procedure were 9 in. x 2 in. x 0.125 in. Both 9 in. x 0.125 in. surfaces on


BACKGROUND

When evaluating the performance of a control system, accuracy and stability are the features of
principal interest. Stability may be described as the tendency of a system to oscillate after a disturbance,
as illustrated in Figure 1. Oscillation arises from delays in the perception of and response to errors, lead-
ing to overshoot. In an absolutely unstable system, the amplitude of oscillation increases with time until
mechanical failure occurs. In a stable system, the response to an abrupt disturbance still tends to be
oscillatory, but the amplitude decreases with time until a steady state value is reached. The amplitude
of oscillation in a marginally stable system tends to remain relatively constant.

A system which exhibits absolute stability as described above may still have poor relative stability,
as reflected by the number of oscillations before the transient error is damped out. The most desirable
condition occurs when the oscillation ceases within a single cycle.

After the transient error 1s damped out, a steady state error may persist. This will be especially
true for a joint tracking system when the joint 1s skewed from the programmed path. In general,
accuracy is improved by increasing sensitivity and speed of response, but stability is thereby impenled.

The welding control system developed at Ohio State University for MSFC uses illumination from
the welding arc for vision-based tracking of square butt jomts. The view through the weld torch is
depicted in Figure 2. The trajectory control procedure begins with detection of the weld yomt. Con-
fidence in the collected image is quantified, and must be greater than a programmed threshold for correc-
tion to occur. If the decision is to track the umage feature, the present error 1s calculated as the distance
between the joint position and the center of the electrode (defined in a calibration procedure before
welding). The system’s ability to detect the weld pool center and use it in the error calculation was not
employed in the present tests, to simplify the evaluation. Once the present error is calculated, it is
averaged with preceding values by a recursive technique. The so called exponentially weighted moving
average is expressed by the following equation.

A(K) =

GD y aK-netxic
n n
where
A(K) = new average value
A(K-1) = present average value
I(k) = input factor

n = weighting factor

The weighting factor, n, defines the influence of the present error on the new average. In the OSU
system, n is defined by the user programmable seam data average weight (SDAW), with n = 2(SDAW)_
Thus n 1s always a power of 2 (1.¢., 0, 2, 4, 8, ...), and a small increment of SDAW will significantly affect
the averaging.


TECHNICAL MEMORANDUM

INFLUENCE OF CONTROL PARAMETERS ON THE JOINT TRACKING PERFORMANCE
OF A COAXIAL WELD VISION SYSTEM

INTRODUCTION AND SUMMARY

The present report is the first in a series detailing evaluation of a vision-based welding control
system developed by Ohio State University. This evaluation is a part of the program for development
and implementation of robotic technology for welding on the Space Shuttle Main Engine. The OSU
vision system was developed under contract as a part of the robotic welding system in the Materials
and Processes Laboratory’s Productivity Enhancement Facility at the George C. Marshall Space Flight
Center. The vision system is capable of two basic functions. trayectory control (seam tracking) and weld
pool width control. As a first step, this report covers an evaluation of the user programmable parameters
which dictate the correcting response to a perceived tracking error. Future work on trajectory control
will cover image acquisition and processing (joint and pool detection) and tracking accuracy under non-
ideal joint conditions. Irregularities such as mismatch, varying jomt gap and tack welds will be con-
sidered. Once the trajectory control is thoroughly explored, the weld pool width control will be
evaluated.

The evaluation of trayectory control parameters was simplified by eliminating the pool detection
capability. The electrode center, defined in a calibration procedure, was used for error calculations in
the control routine. A controlled disturbance was provided by welding on straight line square butt joints
using a programmed path with a ramp offset and two step offsets. Tracking accuracy was measured at
increments along the weld path, and the collected data was statistically reduced to three values for each
weld. Two of these values provided a direct indication of accuracy, while the third was indicative of
stability. The three gains of the proportional-integral-differential (PID) control algorithm were varied, as
well as an averaging factor. Optimal values were chosen from consideration of the three statistical values,
using both accuracy and stability as judgement criteria. Steady state error will be quantified in a later
report when tracking performance based on weld pooi location is compared with the tracking
performance examined here.

OBJECTIVE

This report represents the first n a series concerned with evaluating the OSU welding control
system’s operating performance. Considerable flexibility was provided in the design of the system via
over 100 user programmable parameters. A logical first step in the evaluation process was to optimize
these parameters for general applications.

The present study concentrated on the trajectory control response, specifically the effects of con-
trol parameters on tracking accuracy and stability. Three parameteis were identified as requiring further
study’ the proportional, differential and integral gains and the weighting factor for the exponentially
weighted moving average. The overall objective was to evaluate the effects of these parameters on the
control response using essentially ideal joint conditions, and recommend values to be used in future tests.


PAGE [S

4

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14



cursor weld joint

joint detection window

field of
view

electrode

solidified
weld bead
Figure 2. View seen by OSU welding control system.
Using the averaged value, a correcting response is calculated by a proportional-integral-differential
(PID) type algorithm. The offset command, M(k), 1s calculated by the following equation.

M(k) = Kp x [A(k)] +K, x SUM[A(K)] + Kg x [A(k-1)] - A(k)

where
M(k) = control output after sample k
A(k) = averaged error calculated from sample k
A(k~1) = averaged error from previous error (k-1)
SUM A(k) = sum of all averaged errors from 0 to k
Kp = proportional gain
Ki = integral gain
Kg = differential gain.

User control of the integral gain is limited by the fact that some integration is performed when
the control offset command, M(k), 1s converted from position correction to cross seam speed. This


CONCLUSIONS

On the basis of the tests conducted in the present study to evaluate the effects of the OSU
vision system’s control parameters, the following conclusions may be drawn:

1) Increasing the proportional gain (Kp) improved the system’s ability to correct for abrupt

offsets. However, the overall accuracy (as expressed by the RMS error) tended to decrease with levels
of Kp greater than $2B. Therefore, $2B is the optimal value for Kp.

2) Varying the differential gain (Ky) caused little change in the control response over a wide
range. Therefore, the default value, $0A, is considered optimal.

3) Increasing the integral gain (Kj) tended to reduce the stability of the control. Since no
advantage was apparent in using higher levels, the default value for K, ($00) is optimal.

4) Increasing seam data average weight (SDAW) also led to reduced stability. The default value
of $01 will be used for this parameter in future tests.

5) The optimal control parameters chosen in the present study were developed on the Advanced

Robotics Cyro 750 robot and controller, and may be unique to this system. When setting the control
parameters for other systems, these tests should be repeated.

20


“-

=

or

NASA CONTRACTOR
REPORT

JAN198 &
REGHIMED

NASA CR-178538

INFLUENCE OF CONTROL PARAMETERS ON THE JOINT TRACKING
PERFORMANCE OF A COAXIAL WELD VISION SYSTEM

By K. J. Gangl and J. L. Weeks
Rocketdyne Division
Rockwell International

Interim Report

October 1985

Prepared for
NASA-Marshall Space Flight Center
Marshall Space Flight Center, Alabama 35812

“ (NASA-CR-178538) INFLUENCE OF CONTROL N86-16587

PARAMETERS ON THE JOINI TRACKING PERFORMANCE
OF A COAXIAL WELD VISION SYSTEM (Rockwell

i Corp. 27 HC AO3/MF AO1 Unclas
Tater national Pe) P CSCL 13H G3/37 05246


Weld End Reference Weld Start

Point Line Point
Joint Center Bead Near Side
Location Location Bead Far Side
t Location

Figure 4. Sample surface showing reference lines.

Robot X-axis

f £

aN
V4 Y
0.300 Programmed Path
oaar ed

Figure 5. Programmed Test Path.

Joint Position | 2" | 2" |
— n
t

—

Evaluation

lhe plate edge used as a reference for the joint location (plate width) measurements was also used
as a reference for measuring the bead position. Vernier calipers were used to locate each edge of the
bead at 0.3 in. increments. Segments containing sharp changes were measured at smaller increments.
The bead center was defined as the average distance of the two bead edges from the single reference
point. The tracking error was calculated as the difference between the bead center location and the joint

location. :


each plate were ground flat and parallel to within 0.002 in. A bevel was then machined in the butting
surfaces to provide a 10 deg included angle, with no land. With the plates butted together at the root on
a flat surface, the joint gap at the top surface was approximately 0.020 in. Both weld joint preparations

are depicted in Figure 3.
—>f-—$ 0.010 maximum

WS

a. Configuration for samples A-DB

- 0.020

= WL AS

10°

b. Configuration for samples EB-SB

Figure 3. Cross-sectional view of sample edges.

Two marks were scribed on one plate from each joint at a spacing of 7 in., corresponding to the
start and end points of the weld. The plate width was measured at both locations with Vernier calipers,
and recorded. This identified the joint location for the evaluation, and the edge of the plate opposite
the jount was used as the reference for weld bead measurements, These features are seen in Figure 4.

The test plate was clamped in a fixture bolted to the two-axis positioner. The weld seam was
oriented parallel to the Cyro 750 robot’s x-axis, with the weld start point located at the positioner’s
center of rotation. The robot program rotated the positioner 2.5 deg from the home position and
directed the torch manipulator to trace the path shown in Figure 5. The OSU vision system was enabled
at the start of the weld. No automatic voltage control (AVC) was used.

The welding conditions were set to provide full penetration, as follows.

o Arc length = 3/32 in.

o Current = 125 Amps

o Travel speed = 5 in./min

o Primary shielding 99,999 percent pure Ar, flow rate 35 cfh

o Back shielding: 99.999 percent pure Ar, flow rate 5 cfh.

The matrix of control parameters studied 1s shown in Table 1.
6


Amplitude /\
of t time UNSTABLE

++ + t- +
Response
disturbance

failure

Amplitude /\ [\ | MARGINALLY
of 4 + ' STABLE
Response VU U \

disturbance

steady state

error
Amplitude [\
of + if $+——+— time STABLE

Response

disturbance

Figure 1. Classes of stability.


DISCUSSION

The results of the tests conducted in this study fairly clearly indicate the optimal control parame-
ters for seam tracking with the OSU vision system. A summary of the quantities used for evaluating each
Parameter is shown in Table 2. Tracking accuracy at the step offsets improved with increased Kp up to

about $2B, where the plotted curve leveled out. Further increases in Kp would decrease stability without
improving accuracy, so the value $2B is considered optimal.

Since varying Kg at positive levels showed very little effect on accuracy or stability, the proper
setting may be chosen as the default value, $0A. Some K, is desirable to filter out electronic noise, but
this term does tend to be sensitive to spurious errors.

Stability, as measured by the average difference between local maxima and minima, showed a
gradual but definite tendency to decrease with increased values of both SDAW and Kj. Since there is

no apparent advantage in increasing either of these values in terms of accuracy, they should be left at
their default values, SDAW = 1 and K; = 0.

Photographs of the weld made using the optimal set of parameters are displayed in Figure 15.
Full penetration was achieved for the full length of the weld, and the offsets were almost entirely
removed.

TABLE 2. SUMMARY OF CONTROL PARAMETER EVALUATION

Dependent Independent Characteristic Figure
Variable Variable Evaluated No.
Maximum difference Kp Control accuracy 7
in errors
RMS error Kp Control accuracy 8
Average difference Kg Control stability 9
between local maxima
and minima
SDAW Control stability 10
Kj Control stability 12
Steady-state error K; Steady-state error 13, 14


TABLE OF CONTENTS

Page
INTRODUCTION AND SUMMARY ......... 0. ese c eee e tence cece nent eee ent nenee 1
OBJECTIVE . 1... ect eeeeeenee eee eee eee tee e nent eens e tenes 1
BACKGROUND...... 0... cece ce ccc cence enn eee teen eee ete e eee e tern enna eneee 1
PROCEDURE... 0... 2c cece eee ce eee ene e eee t eee e nee ene e nee ene e eee eene 5
RESULTS... 1. c eee n ten teen teen tenet e nett nae e eee nene 9
BB EST1 OSS) (0) REN 17
CONCLUSIONS ..... 0 cece cence cece ee nee nee teen nent b eee teen ten ee tenes 20


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ACKNOWLEDGMENTS

The efforts of C. S. Jones and C. Kurgan, Metals Processes Branch, Process Engineering Division,
Materials and Processes Laboratory, NASA-MSFC, have been invaluable to the successful completion of
the work described in this report.


CONCURRENCE

INFLUENCE OF CONTROL PARAMETERS ON THE JOINT TRACKING PERFORMANCE
OF A COAXIAL WELD VISION SYSTEM
By K. J. Gangi and J. L. Weeks

Rocketdyne Division of Rockwell International

Aik Walon

J. K. Watson
Rocketdyne

GS.

C. S. Jones
Metals Processes Branch

ont ~4/,

ae Lb 2

P. H. Schuerer

Process Engineering Division

21


TECHNICAL REPORT STANDARD TITLE PAGE

1 REPORT NO.
NASA CR- 178538

2. GOVERNMENT ACCESSION NO.

3. RECIPIENTS CATALOG NO.

4, TITLE AND SUBTITLE

Influence of Control Parameters on the Joint Tracking
Performance of a Coaxial Weld Vision System

5, REPORT DATE

October 1985

6. PERFORMING ORGANIZATION CODE

7. AUTHOR(S)
K. J. Gang] and J. L. Weeks*

@, PERFORMING ORGANIZATION REPORT #

9. PERFORMING ORGANIZATION NAME AND ADDRESS

George C. Marshall Space Flight Center

Marshall Space Flight Center, AL 35812

10, WORK UNIT, NO.

1, CONTRACT OR GRANT NO.

NAS8-27980

13. TYPE OF REPOR’ & PERIOD COVERED

12 SPONSORING AGENCY NAME AND ADDRESS:

National Aeronautics and Space Administration

Washington, D.C. 20546

Contractor Report

14 SPONSORING AGENCY CODE

EH42

15, SUPPLEMENTARY NOTES

Based on development work under the direction of the Metals Processes Branch of the Materials and

Processes Laboratory

*Employees of Rocketdyne Division of Rockwell International.

16, ABSTRACT

This report describes the first phase of a series of evaluations of a vision-based welding control
sensor for the Space Shuttle Main Engine Robotic Welding System. The robotic welding system is pre-
sently under development at the Marshall Space Flight Center. This evaluation determines the standard
control response parameters necessary for proper trajectory of the welding torch along the joint.

17 KEY WORDS

Robotic Welding
Trajectory Control
Seam Tracking

18, DISTRIBUTION STATEMENT

Unclassified — Unlimited

19, SECURITY CLASSIF, (of this reperty

Unclassified

20.

SECURITY CLASSIF, (of this page)
Unclassified

21 NO. OF PAGES [22 PRICE

26 NTIS

MSFC - Form 3292 (May 1969)

For sale by National Technical Information Service, Spnngfield, Virginia

22151


TABLE 1. MATRIX OF CONTROL PARAMETERS USED IN TESTS

Ky K Kg SDAW
16 00 0A Ol
17 v0 0A Ol
18 00 OA 01
19 00 A Ol
1B 00 0A ol
1F 00 A Ol
23 00 dA Ol
2B 00 0A Ol
33 00 OA Ol
3c 00 0A Ol
1B 00 0A Ol
2B 00 0A Ol
2B 01 0A oO!
2B 02 0A Ol
2B 03 0A Ol
2B 00 -19 Ol
2B 00 -14 Ol
2B 00 OF ol
2B 00 05 Ol
2B 00 05 (OO
2B 00 OF Ol
2B 00 20. Ol
2B 00 30s
2B 00 OA 02
2B 00 0A 03

Allowable Range of Values for:

Kp= 00 to FF

Kg = 00 to FF

K, = 00 to FF (normally 00)
SDAW = 00 to FF (normally 01-04)

(n.b. All values of control parameters expressed in hexadecimal notation.)


054
0.44
Ss
= 034
g¢
eS O24
z
Fd
1s
9 T T T T T T
0 10 20 30 40 50 60
(00) (08) (14) (Ee) (28) (2) Gt)
K. Decimal Value
P

(Hexadecimal Value)

Figure 7. Maximum difference in errors versus proportional gain (Ky).

0-4
e 4
S 64
s
£2 44
2-4
° T T T T T T
0 10 20 30 40 50 60
(00) = (0A), (44) (1) (28) (32) 30)
K Decimal Value

(Hexadecimal Value)

Figure 8. RMS error versus proportional gain (K