ARC WELDING PROCESS SIGNATURE VISUALIZATION AND ANALYSIS

# C. Hsu[^1]

# ABSTRACT

Arc voltage-current population (histogram) density two dimensional color
plots are generated for various arc welding processes, including CV
spray, CV short-circuiting, pulsed MIG, AC submerged arc, tubular
electrodes, Surface Tension Transfer^®^ (STT^®^), and stick electrode in
pipe welding.

Actual voltage and current signals are recorded at a sufficiently high
sampling rate (50 KHz or higher). Each voltage-current data pair, or
data in combination with its first order derivates (e.g. dv/dt, di/dt)
is digitized to a pixel location on a raster image area. The occurrences
of data pairs at each location are accumulated for a fixed weld time.
Color models (e.g. RGB) are used to represent the histogram depth, based
on normalized density, from \"warm to cold\", as a signature of each
welding process. Attractors in the short region and the arc region are
identified, and the transition between regions, such as between short
and arc, is animated and analyzed statistically. Applications such as
welding process stability and welding procedure optimization, derived
from digital image processing techniques, are illustrated.

# KEYWORDS

Arc Monitor, quality monitor, weld quality assurance, arc stability,
stubbing, GMAW, GMAW-P, GMAW-S, SAW, SMAW, FCAW, STT, AC, CV, MIG, MAG,
data acquisition, SPC, histogram, statistics, pulse welding, pipe
welding, short circuiting, dip transfer, spatter, droplet transfer,
digital signal processing, digital image processing

# INTRODUCTION

Weld quality assurance is becoming an important consideration in
manufacturing industry. Many process variations in production, such as
poor part fit-up, arc blow, poor grounding or voltage sense connection,
multiple arc interference, disturbed gas shielding, poor wire feeding,
etc. can yield weld defects. A returned assembly from an automaker to
its first tier supplier incriminates not only the welding process but
also the quality inspection process. Therefore there is a growing demand
for weld quality monitors, preferably based on simple signals, such as
arc voltage and current, wire speed and gas flow rate.

Techniques using statistical process control (SPC) tools such as data
trending, tolerance chart and sequential analysis are discussed by Cook
et al. \[1\]. Statistical algorithms were developed by Quinn et al. in
CV arc welding that flag out defective welds by comparison with a
baseline of defect-free welds \[2\]. Power spectral density of arc
signals is used to predict contact tip wear \[3\] and porosity and
burn-through \[4\]. Fast Fourier Transform of the current waveform is
used to determine stability of short-circuiting metal transfer \[5\].

The goal of a weld monitor is obviously to catch *all* faults determined
by an application's acceptance criteria without *any* false alarms.
Common faults in manufacturing are burn-through, weld too cold or too
small, porosity, undercut, wire stub sticking out of the weld,
insufficient weld length, weld off joint, and weld simply missing. The
foundation of an effective statistical weld monitor comprises of 1) all
faulty welds will be accompanied by significant arc signal disturbances
above the noise level; 2) an arc signal departing from the statistical
norm will necessarily produce unacceptable weld faults. These are
presumptions in the absolute sense. In practice it is a leap of faith
from arc signal behavior to weld quality.

One commercial system based on statistical methods called ARCAgent^TM^
from Impact Engineering is applied in semi-automatic applications \[6\]
and another called ADM IV^TM^ from Computer Weld Technology is used in
hard automation and robotic applications. Fanuc's Data Monitor option
integrated in its R-J3 controller tracks statistics of up to 6 arc
signals at 250 Hz maximum rate and reports error conditions, using Data
Monitor Schedule to set upper, lower and time limits. These systems work
well to identify gross weld defects in simple CV spray process. However,
they have limitations arising from relatively low sampling rates (e.g.
10-1000 Hz) and may not be effective in pulse welding, short-circuiting
welding or STT welding. The arc waveforms are commanded at a few hundred
Hz with large swings in amplitude, which make it difficult to identify
statistical anomalies. In many automotive applications, the welds may
last one second or less, and 1 KHz sampling only captures 1,000 data
points where a good fraction is spent in arc strike, run-in, crater fill
and arc end transients.

One approach is to use the power source itself as both waveform
generator and waveform monitor in synergic pulse welding and STT
welding. This has the advantage of *a priori* knowledge of time
segmented commanded signals \[7\]. For example, the background time and
background current can be monitored and compared to programmed settings,
when the power source is adjusting background time and current to adapt
for stickout changes at a specific synergic wire speed. Fluctuation of
background current or time would be indicative of process instability.
Externally extracting peak current or monitoring average current would
not be as useful or effective when the power source uses a fixed peak
current at a given wire speed. The welder manufacturer can predetermine
fault thresholds as part of the waveform development effort, to be
adjusted for a given application if necessary.

Barborak and Conrardy used histograms of current, voltage, power and
conductance to detect stickout, gas, and wire speed disruptions in
short-circuiting welding \[8\]. Cross-plots, or scatter diagrams of
voltage and current produce a graphical view of the short-circuiting
process. Simpson applied chaos theory and drew his cross-plot on an
adaptive scale to improve resolution in regions of interest, using arc
voltage and an "artificial current" derived from the weighted time
history of arc voltage \[9\]. A plot is generated every second with a 8
KHz sampling rate for online stability computation and fault detection,
commercially known as WeldPrint^TM^.

This paper introduces a 2D color artificial image to represent a
histogram of arc signals, using arc voltage, arc current and their time
derivatives, to display and analyze the stability of many arc welding
processes.

# DATA ACQUISITION AND ANALYSIS SOFTWARE

**[Equipment]{.underline}**

Arc current and voltage are acquired using a high-speed data acquisition
device with channel-to-channel isolation, 14-bit measurement resolution,
and 250 KHz aggregated sampling rate. Most of the data is collected at
50 KHz - 75 KHz per channel. Current is measured by an AEMC MR561
current probe. The data acquisition box streams data to the laptop hard
disk through a USB connection. All instruments are NIST traceable.

**[Arc Caliper]{.underline}**

Arc Caliper is a software program developed at the Lincoln Electric
Company to analyze high-speed data acquisition files producing arc
signal and wire feeding statistics, timing and synchronization
statistics, arc start behavior, burn-back and arc ending
characteristics. Optionally a 2^nd^ order Butterworth low pass digital
filter with 3dB cutoff set at 2500 Hz can be engaged. Ad hoc algorithms
are developed to represent or estimate arc stability, spatter, heat
input, fume, operating voltage etc. for welder, feeder, robot and
consumable evaluation. It is written in Java for portability to
non-Windows platforms such as PDA or mobile phone as part of an online
user interface or as an embedded web page residing in the power source
or robot, and for ease of factory networking.

One output of Arc Caliper is the so called voltage-current population
density plot. Each voltage-current data pair is saved to a pixel
location on a raster image area. The occurrence of data pairs at each
location is accumulated for the entire weld (e.g. 20 seconds of
welding). Color models (e.g. RGB or HSB) are used to represent the
histogram depth, based on normalized density, from \"warm to cold\", as
a signature of the welding process. The signals can be played back
(animated) to reveal the dynamic behavior of a measured process and the
results can be exported as a spreadsheet.

# APPLICATIONS IN ARC WELDING PROCESSES

**[CV Spray transfer process]{.underline}**

A stable CV spray process above the transition current is simply one
blob in the VI density plot. The weld is done at about 22.5V and 365A
using S-6 wire on an inverter. A sequence of white, yellow, red, pink,
and blue is used to represent the decreasing levels of normalized
frequency of digitized voltage-current pairs, or histogram density. Most
of the data falls within the "hot zone" where the zone width corresponds
to inverter ripple and the blue fringes may be explained by the voltage
disturbances from "incipient" shorts when a droplet is stretched and may
briefly kiss the puddle surface before being detached.

![](media/image1.jpeg){width="4.643055555555556in"
height="2.5819444444444444in"}

Figure 1: CV spray VI density plot from PowerWave 455, L-56 electrode,
90% Ar+10% CO~2~

**[Pulsed spray process]{.underline}**

![](media/image2.jpeg){width="4.706944444444445in"
height="2.6534722222222222in"}

Figure 2: Pulsed spray transfer VI density plot from PowerWave 455, L-50
electrode, and 90% Ar+10% CO~2~

Two distinctive "attractors" or hot zones appear in pulsed spray
transfer process, corresponding to the high peak current and low
background current and their transition behavior. Both zones are above
12V implying that a plasma is always present.

**[CV short-circuiting process]{.underline}**

A typical CV short-circuiting process (see Figure 3) also has two zones,
one at low voltage or in a short, and the other at high voltage 15-21V.
During the short the current is slowly ramped up, applying pinch force
to the liquid bridge, until it breaks into an arc, at which instant it
snaps into the arc zone.

![](media/image3.jpeg){width="5.294444444444444in"
height="2.910416666666667in"}

Figure 3: CV short-circuiting VI density plot from PowerMIG 300, L-50
electrode, 90% Ar+10% CO~2~

**[STT controlled short-circuiting transfer process]{.underline}**

![](media/image4.jpeg){width="5.293055555555555in"
height="2.9895833333333335in"}

Figure 4: STT VI density plot from STT II, AutoWeld electrode, 75%
Ar+25% CO~2~

The low spatter STT process has four hot zones in Figure 4. A background
current of 70 amps maintains the arc and contributes to plate heating at
the right bottom corner. After the electrode initially shorts to the
weld pool, it jumps to the low voltage-low current zone to ensure a
solid short. Pinch current is then applied following the S-shaped curve
to the top left zone. Molten metal is squeezed down and the derivative
of voltage (dV/dt) is monitored. When the liquid bridge is about to
break, dV/dt increases sharply and power source reacts by driving the
process back to the low voltage-low current zone. Immediately following
the arc establishment, it swings up to the high current-high voltage
zone on the top right corner, to produce plasma force pushing down the
weld pool. Finally it returns to the background zone and stays there
until it shorts again.

**[AC submerged arc process]{.underline}**

![](media/image5.jpeg){width="6.495833333333334in"
height="3.6381944444444443in"}

Figure 5: AC sub-arc VI density plot from PowerWave AC/DC with L-60
electrode and 860 flux

The AC submerged arc process circulates between a DC positive zone and a
DC negative zone in a loop. One advantage of inverter based, computer
controlled AC sub-arc equipment is exhibited in the transition between
the two zones. The current is being reduced gradually so that
zero-crossing occurs at low current in order to reduce stress applied to
the power electronics. It also shows that the zero-crossing occurs
rapidly with a large voltage swing from the center tap choke design that
prevents arc outages.

**[CC process with stick electrode]{.underline}**

Pipe welding using E6010 electrode on an electronically controlled
engine welder is shown in Figure 6. The main hot zone is characterized
by a constant current with voltage ranging from 18-34V. The stick
electrode is being whipped back and forth, and shorting does occur as
shown in the left hot zone. Transition dynamics in the VI plot from the
shorting zone and arc zone are essential for puddle fluidity control in
all position pipe welding.

![](media/image6.jpeg){width="6.121527777777778in"
height="3.3777777777777778in"}

Figure 6: CC process VI density plot from Ranger 305G, Fleetweld^®^ 5P+
electrode

**[Globular transfer process]{.underline}**

![](media/image7.png){width="6.192361111111111in"
height="4.581944444444445in"}

Figure 7: Globular transfer VI density plot from Invertec^®^ V350,
Innershield^®^ electrode, no gas

Globular transfer is exhibited in an example of pipe cap pass welding by
an inverter V350 and self-shielded flux cored electrode shown in Figure
7. The process stays mostly in the arc region above 13V building up a
large droplet hanging at the bottom of the electrode, and occasionally
it shorts briefly to transfer the molten ball to the puddle and returns
to the arc region. The size and shape of the hot zone and its blue
fringes usually indicate the equipment's ability to hold a constant arc
length.

**[Advanced cross-plots]{.underline}**

![](media/image8.png){width="5.335416666666666in"
height="2.990972222222222in"}

Figure 8: Pulsed spray transfer V-dV density plot from PowerWave 455,
L-50 electrode, and 90% Ar+10% CO~2~

![](media/image9.png){width="5.5055555555555555in"
height="3.098611111111111in"}

Figure 9: Pulsed spray transfer V(n) vs. V(n-1) density plot from
PowerWave 455, L-50 electrode, and 90% Ar+10% CO~2~

Figure 8 illustrates pulse welding in a voltage vs. time derivative of
voltage image. Time derivate of voltage is useful in prediction of
short-to-arc transition and droplet detachment. Figure 9 illustrates the
same process in voltage vs. its immediate past. Comparing a signal to
its past history can serve as a predictor of change. Figure 10
illustrates the same process in current vs. time triggered at 150A
down-slope, where the fluctuation of the waveform including shorting
response is clearly visible. Other graphs such as voltage-time graph,
cyclical current period vs. voltage period can also provide insight into
the arc welding process. Arc power, arc impedance and their time
derivatives can also be used for plotting. In general, an arc signal
passing through a digital filter with any transfer function, with IIR or
FIR implementation in the Z domain, can be used as one axis or both axes
in the plot. Digital image processing techniques can be applied to
extract weld quality and arc stability. Unstable process tends to have
an "out-of-focus" VI plot without high frequencies in its power
spectrum. Segmentation, template matching and statistical pattern
recognition can be used to distinguish a defective weld from an
acceptable weld.

![](media/image10.png){width="6.493055555555555in"
height="3.6659722222222224in"}

Figure 10: Pulsed spray transfer arc voltage vs. time density plot from
PowerWave 455, L-50 electrode, and 90% Ar+10% CO~2~

This paper is intended to provide an overview of using a voltage-current
population density plot to characterize each arc welding process.
Concepts for using this technique in analyzing process stability, power
source and consumable dynamic performance characterization, procedure
optimization, waveform development, weld defect identification, and fume
and spatter estimation are evident but not explored in detail.

# CONCLUSION

Voltage-current cross-plot histogram population densities of many arc
welding processes are presented, including CV spray, CV
short-circuiting, STT, pulsed spray, CC stick, AC sub-arc and globular
transfer with tubular electrode. Image analysis tools can be employed to
measure arc welding process stability from artificial image created by
arc signals directly, their time derivates, or digitally filtered arc
signals.

**ACKNOWLEGEMENT**

The author wishes to express his appreciation to James Hearn for
conducting many experiments cited in this study.

# REFERENCES

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[^1]: ^\*^ Engineering Manager, The David C. Lincoln Research and
    Development Center, The Lincoln Electric Company, 22801 St. Clair
    Avenue, Cleveland, Ohio 44117