Study on Evaluation Method of Aluminum alloy Pulse MIG Welding Stability Based on Arc Voltage Probability Density

doi:10.4236/jsip.2011.23020

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Journal of Signal and Information Processing, 2011, 2, 159-164

doi:10.4236/jsip.2011.23020 Published Online August 2011 (http://www.SciRP.org/journal/jsip)

159

Study on Evaluation Method of Aluminum Alloy

Pulse MIG Welding Stability Based on Arc Voltage

Probability Density

Jing Nie1, Xiao-Feng Meng 1, Yu Shi2

1School of Instrumentation Science & Optoelectronics Engineering, Beihang University, Beijing, China; 2Key Laboratory of Non-

Ferrous Metal Alloys and Processing of Ministry of Education, Lanzhou University of Technology, Lanzhou, China.

Email: [email protected]

Received February 24th, 2011; revised April 16th, 2011; accepted April 25th, 2011.

ABSTRACT

Bring forward a new analytica l method in order to evaluate the stability of the process of a luminum alloy pulsed MIG

welding. The ratio of the first and the second peak in arc voltage signal probability density was selected to evaluate

aluminum alloy pulse MIG welding stability. By calculating the arc voltage signal probability density from 80 sets of

welding experiments, the ratio of the two peaks in arc voltage probability in every set was captured. And the evaluation

system of aluminum alloy pulse MIG welding stability was established. The smaller the ratio of peaks in arc voltage

signal probability density is, the better the stability of the welding will be; the bigger the ratio of peaks in arc voltage

signal probability density is, the poorer the stability of the welding will be.

Keywords: Aluminum Alloy, Pulse MIG, Welding Stability, Probability-Density, Arc Voltage

1. Introduction

The process of aluminum alloy pulse MIG welding is

characterized by its non-linearity, strong time-varying,

strong coupling between the parameters, and so forth [1].

The reason why its process is unstable has not been well

explained until now. Becaus e of the lack of the parameter

matched stability evalu ation indicators, the control of the

aluminum alloy pulse MIG welding by changing the

welding parameters is very difficult. The fail of matching

the parameter will probably lead to the instability in the

welding process or even worse. In recent years, many

scholars at home and abroad have studied the stability in

the welding process: reference [2] put forward an on-line

evaluation model of the process stability by use of the

statistical analysis and partial least-squares regression.

Reference [3] an d [4] found that the approximate entropy

of the arc signal varied with the change of the parameter.

Reference [5] and [6] analyzed the prob ability density of

the corresponding welding current and voltage and fi-

nally evaluated the welding stability.

This paper analyzed the probability density distribu-

tion of the 80 sets of voltage signal under different weld-

ing speed, wire-feeder speed and duty cycle matched pa-

rameters.

2. Experimental System

The experiment applied DELEX VIRIO MIG-400L

welding machine to pure Ar gas shield bead-on-plate

welding. The designation of the welding wire was 5356,

diameter 1.2 mm. The material of the workpiece was

aluminum50581-H321 with the thick of 6mm. The torch

was fixed during welding. And its distance between the

workpiece was unchanging. The workpiece moved on the

worktable. The initial wire extension was 15 mm. Data

acquisition card PCL812PG was applied to the welding

and its frequency was 1 kHz. The current sensor was

CSM400FA/100 mA. The time between the arc igniting

and ending was not less than 45 s. Video acquisition

captured the condition of the arc and molten pool to

judge the stability of the welding. Figure 1 was the ex-

perimental system.

Because of the finding that the duty cycle of the pulse

current, the wire-feeder speed and welding speed impact

the welding stability greatly, the experiment combined

the duty cycle, the wire-feeder speed and the welding

speed to weld. Th e base valu e o f the weld ing curren t was

25 A, the peak value 180 A, pulse frequency 40 Hz,

welding voltage 18 V, and shielding airflow 18 L/min.

Because the aluminum alloy pulse MIG welding was

Study on Evaluation Method of Aluminum Alloy Pulse MIG Welding Stability Based on Arc

160 Voltage Probability Density

x-axis

-axis

Dual-axis table

PCL-812PG

Acquisition

Motion

Control

Card

Video

Capture

Card

Power supply

Hall sensor

CCD

MIC

Isolation circuit

Stepping

Motor

Stepping

Motor

Torch

Figure 1. Experimental system.

very strict to its parameter matching, the welding pa-

rameters in Table 1 were fixed through the welding ex-

periments. These parameters could be combined ran-

domly. The maximum and minimum of single parameter

was the upper and lower limits of the matching. 5 × 4 × 4

sets of welding experiments were conducted and 80 sets

of arc voltage signals were acquired.

3. Voltage Signal Probability Distribution

Analysis

With regard to time array





t，when amplitude falls

on the range





xx , the total time is 1







When observation time tends to infinity, array X

TT is

the probability of case



xt x x











, which can be

written as limt xxT



Px xT





the prob-

ability density function can be defined as:



Px xtxx

lim x

lim limlim

xTx i

xT T





 































(1)

Probability density function constantly equals

to real-value non-negative function. The data must be

standardized before analyze its probab ility density. Ev ery

variable minus the mean and then divided by its standard

deviation, supposing the collected good-running data ma-

trix is



R

, each column corresponds to a variable

Table 1 .Welding parameters.

Welding speed

cm/min Wire feed speed

m/min Duty cycle

11 6 50

15 6.5 44

20 7 40

25 7.3 37.5

and each line corresponds to a sample. Standardized the

as follows:



11 1

11 1diag,,,

XX P





 











(2)

P—the mean of variable X,

111

,,,



















, S—the standard deviation of the va-

riable, 12

,,,

Sss s











. Then, normalize the standar-

dized data. Finally, calculate and analyze the probability

density.

Analyze the probability density of 4 sets of voltage

signal selecting from 80 sets of welding experiments

arranging from good to bad. Every set of voltage signal

cut from the 10th second and 30000 p oints wer e captur ed,

namely 30 seconds. The results are shown in Figure 2.

According to Figure 2, two peak values were found in

each set of probability density distribution figure and the

distance between the two peaks increase. In order to get

the accurate variation of the two peaks from 4 sets of

experiments, the ratio of the first peak and the second

peak was selected to reflect the variation of the distance

between the two peaks. The variation of the ratio was

shown in Figure 3.

The ratio of the two voltage probability density peaks

gradually increase in the four sets of experiments. After

comparing the corresponding weld bead, it was found

that the ratio of peaks was small when the weld bead

shaping was good, and th e opposite was big. The second

set and the fourth set were shown in Figure 4. Obviously,

the weld bead of the second set was better than that of

the fourth. And the ratio of peaks of the second set was

smaller than that of the fourth. Therefor e, the ratio of the

two peaks in voltage probability can be applied to evalu-

ate the stability of aluminum allay MIG welding.

4. Evaluation System of Welding Stability

According to the result above, 80 sets of welding voltage

signal was calculated for probability density. By making

use of the ratio of the two peaks in each set of voltage

signal probability density, the evaluation system of alu-

minum alloy pulse MIG welding stability was established.

The result is shown in Figures 5-7. What is shown in

Figures 5-7 is the fluctuation of the ratio of peaks in arc

voltage signal probability density under different pa-

rameter. The figure well reflects the aluminum alloy

pulse MIG welding stability under different welding

speed, wire feed speed and duty cycle. In aluminum alloy

pulse MIG welding, the smaller the ratio of peaks in arc

voltage signal probability denity is, the bet ter the stabi lity s

Study on Evaluation Method of Aluminum Alloy Pulse MIG Welding Stability Based on Arc

Voltage Probability Density

161

(a) (b)

Figure 2. Probability density of voltage. (a) NO.1; (b) NO.2; (c) NO.3; (d) NO.4.

(a)

(b)

Figure 4. The weld of different parameters. (a) NO.1; (b)

O.4.

Figure 3. Changes in the ratio of peaks in probability den-

sity. N

Study on Evaluation Method of Aluminum Alloy Pulse MIG Welding Stability Based on Arc

162 Voltage Probability Density

(a) (b)

Figure 5. The match of welding and wire feed speeds on different duty cycle. (a) duty cycle 50%, (b) duty cycle 44%, (c) duty

cycle 40%, (d) duty cycle 37.5%.

(a) (b)

Figure 6. The match of welding speeds and duty cycle on different wire feed speeds. (a) wire feed speed 6 m/min; (b) wire feed

speed 6.5 m/min; (c) wire feed speed 7 m/min; (d) wire feed speed 7.3 m/min.

Study on Evaluation Method of Aluminum Alloy Pulse MIG Welding Stability Based on Arc 163

Voltage Probability Density

(a) (b)

Figure 7. The match of wire feed speeds and duty cycle on different welding speeds. (a) welding speed 11 cm/min; (b) welding

speed 15 cm/min; (c) welding speed 20 cm/min; (d) welding speed 25 cm/min.

Table 2. The ratio of peaks in voltage probability density and weld forming under different welding parameters.

Number Wire feed speed m/minDuty cycle % Welding speed

cm/min Ratio of peaks in

probability density Stability Welding forming

1 6 50 11 1.3333 Stable Good

2 6 44 15 1.24 Stable Good

3 6 37.5 20 2.6111 Unstable Bad

4 6.5 44 25 2.1 Unstable Bad

5 6.5 40 15 4 Unstable Bad

6 6.5 37.5 20 3.0625 Unstable Bad

7 7 44 11 2.7778 Unstable Bad

8 7 40 25 2.35 Unstable Bad

9 7.3 50 20 0.8649 Stable Good

of the welding will be. The opposite is the instability of

the welding.

Table 2 shows the ratio of peaks in voltage probability

density and weld forming under different welding pa-

rameters, through which the ratio of peaks in arc voltage

signal probability density and the welding stability can

be compared more objectively.

5. Conclusions

1) By analyzing the ratio of peaks in arc voltage signal

probability density and comparing the welding bead, the

ratio of peaks in aluminum alloy pulse MIG welding arc

voltage signal probability density is suitable to be applied

to evaluate the welding stability.

Study on Evaluation Method of Aluminum Alloy Pulse MIG Welding Stability Based on Arc

164 Voltage Probability Density

2) According to the fluctuation condition of the ratio

of peaks in arc voltage signal probability density, the

evaluation system of aluminum alloy pulse MIG welding

stability is established. The smaller the ratio of peaks in

arc voltage signal probability density is, the better the

stability of the welding will be; the bigger the ratio of

peaks in arc voltage signal probability density is, the

poorer the stability of the welding will be.

6. Acknowledgements

This paper is supported by the National Natural Science

Foundation of China under Grant No.50675093 and Na-

tional Natural Science Foundation of International Co-

operation under Grant No.50710105060. Thanks for help

from Key Laboratory of Non-ferrous Metal Alloys and

Processing of Ministry of Education, Lanz hou University

of Technology.

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