Analysis of MIG Welding with Aim on Quality

132 Pages·2008·9.28 MB·English

MasterThesis
ElectricalEngineering
Thesisno: MEE-2008:25
July2008
Analysis of MIG Welding with
Aim on Quality
Irina Gertsovich
Niklas Svanberg
DepartmentofSignalProcessing ArevaUddcombEngineering
BlekingeInstituteofTechnology PortChapman
Box520 37121Karlskrona
SE-37225Ronneby
Sweden
ThisthesisissubmittedtotheSchoolofEngineeringatBlekingeInstituteofTechnology
in partial fulfillment of the requirements for the degree of Master of Science in Electrical
Engineering. Thethesisisequivalentto2x20weeksoffulltimestudies.
ContactInformation:
Authors:
IrinaGertsovich
Address: Mandelblomsvägen13B,37252Kallinge,Sweden
E-mail: [email protected]
NiklasSvanberg
Address: Ölandsgatan8,37133Karlskrona,Sweden
E-mail: [email protected]
Externaladvisor:
NilsBjersten
UddcombEngineeringAB
Universityadvisorandexaminer:
MikaelNilsson
DepartmentofSignalProcessing,BTH
Universityadvisors:
JosefStrömBartunek
DepartmentofSignalProcessing,BTH
DepartmentofSignalProcessing Internet: www.bth.se/tek
BlekingeInstituteofTechnology Phone : [phone]
Box520 Fax : [phone]
SE-37225Ronneby
Sweden
ABSTRACT
Since1987UddcombEngineeringhasrepairedpulpsby
their own developed overlay welding method even called
Uddcombmethod. Currentlyeachweldingmachineisop-
eratedbytwopersons. ToincreaseUddcombEngineering
competitiveness the reduced number of operators is de-
sired. An installation of a monitoring system which can
aidhumansintheweldingqualitycontrolalsohelpstoim-
provecompany’sposition. Afuturegoalwouldbetomake
thismonitoringsystemautomaticwithoutahumanopera-
torintheloop.
In this thesis, arc voltage, weld current and audio sig-
nalswerecollectedandanalyzedwithaimonfindingalgo-
rithms to monitor the quality of the welding process. The
useofstatisticstoolsisthebasisfordetectingvariationsin
thevoltageandcurrentdata, associatedwithweldingpro-
cess. It has been shown that voltage signal can be used
as a part of the welding quality control. The audio sig-
nalfromweldingatlowfrequenciesvarieswiththespeed
of the process. The signal can also be incorporated in the
monitoringoftheprocess.
The use of filters, growing sums and statistics are key
elementsinthealgorithmspresentedinthisreport.
Keywords: MIG welding, Arc Voltage, Weld Cur-
rent,Audio,SignalProcessing.

Contents
Contents 5
List of Figures 7
List of Tables 13
1 Introduction 1
1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Purpose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
2 Welding 3
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2.2 Equipment in MIG/MAG Welding . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.2.1 Power Source . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.2.2 Welding Gun . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.2.3 Bobbin and wire Feeder . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.3 Extra material for welding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.4 The Arc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.5 UE Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
3 Theory of Tools 9
3.1 Statistic Measures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
3.2 Periodograms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
3.3 Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
4 The Experimental Setup 11
4.1 The Welding Equipment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
4.2 Sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
4.2.1 Microphone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
4.2.2 Current . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
4.2.3 Voltage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
4.2.4 Video . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
4.3 Other Hardware . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
4.3.1 Computers and DAQ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
4.3.2 Workpiece . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
4.4 Experimental Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
4.5 Visual Welding Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
5
6 CONTENTS
5 Analysis of Voltage and Current 21
5.1 Stationarity & Normality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
5.1.1 Voltage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
5.1.2 Current . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
5.2 Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
5.3 Method 1: Spectrograms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
5.3.1 Voltage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
5.3.2 Current . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
5.3.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
5.4 Method 2: Recursive Sum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
5.4.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
5.5 Method: Recursive Sum Combined with Filter Method . . . . . . . . . . . . . . . 58
5.5.1 Decimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
5.5.2 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
5.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
6 Analysis of Sound 69
6.1 Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
6.2 Method 1: Recursive Sum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
6.2.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
6.3 Dependency between Speed and Quality . . . . . . . . . . . . . . . . . . . . . . . 76
6.3.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
6.4 M14: Sampling Frequency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
6.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
7 Conclusions and future work 89
7.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
7.2 Future work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
Bibliography 91
A Figures from Chapter 5 93
A.1 Section 5.1: Voltage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
A.2 Section 5.1: Current . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
A.3 Section 5.3: Voltage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
A.4 Section 5.3: Current . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
A.5 Section 5.4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
B Figures from Chapter 6 115
B.1 Method 1: Recursive Sum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
List of Figures
2.1 Overview of MIG/MAG welding equipment. 1) power source, 2) welding gun, 3) electrode
bobbin, 4) wire feeder, 5) controller, 6) water supply, 7) gas supply, and 8) workpiece.. . 4
2.2 Characteristics of the power source; a) dropping b) straight c) lightly dropping. . . . . . 4
2.3 The welding gun. 1) the gas hose, 2) the contact tube, and 3) the electrode wire. . . . . 5
2.4 The end tip of the welding gun [1, p40]. 1) electrode wire, 2) contact piece, 3) gas(es),
4) drops of electrode wire, 5) area of gases, and 6) the arc area. . . . . . . . . . . . . . 5
2.5 Schematic of the voltage drop in the arc [1]. L denotes the electrode stick-out from the
e
contact tube, L denotes the arc length, U , U and U denote the anode, column and
a a co c
cathode voltage drop respectively. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.6 Schematic of the welding system’s movements. . . . . . . . . . . . . . . . . . . . . . . 8
4.1 Schematic overview of the experimental setup for measuring weld voltage, current, sound
and video. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
4.2 Pulses generated by the welding power source. . . . . . . . . . . . . . . . . . . . . . . 12
4.3 Schematic of sound measurement. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
4.4 Schematic of current measurement. . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
4.5 Schematic of the voltage splitter. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
4.6 Schematic of video monitoring and recording. . . . . . . . . . . . . . . . . . . . . . . 14
4.7 Picture of the fingercamera. The units on the ruler are centimeters. . . . . . . . . . . . 15
4.8 (a) Overview of the workpiece (b) Description of which surfaces the workpiece are divided
into and also how long they are. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
4.9 Graphical User Interface (GUI) used during the data collection. . . . . . . . . . . . . . 17
4.10 Visualweldingresultsfrommeasurements4-9. Theuppernumbersindicatewithelectrode
wire type used and the lower numbers are the wire speed [m/min]. . . . . . . . . . . . . 19
4.11 Visual welding results from measurements 1-3 and 10-12. The upper numbers indicate
with electrode wire type used and the lower numbers are the wire speed [m/min]. . . . . . 19
4.12 Visual welding results from measurements 13-14. Measurement setup: electrode wire 29.9
with speed 9 m/min. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
5.1 M1 in time domain, where (b) is only a part of the total signal in (a). . . . . . . . . . . 21
5.2 M11 in time domain, where (b) is only a part of the total signal in (a). . . . . . . . . . 22
5.3 M1statisticsmeasuresofdifferentblocksizes; (a)Mean(b)Variance; Solidlineissurface
1 and dashed line is surface 2. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
5.4 M5statisticsmeasuresofdifferentblocksizes; (a)Mean(b)Variance; Solidlineissurface
3, dashed line is surface 4 and dashdotted line is surface 5. . . . . . . . . . . . . . . . 23
5.5 Block statistics test for stationarity with 4410 samples/block on surface 1(60 seconds) in
M1; (a) Mean (b) Variance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
5.6 Histogram of (a) M1 (b) M11. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
7
8 LIST OF FIGURES
5.7 M1statisticsmeasuresofdifferentblocksizes; (a)Mean(b)Variance; Solidlineissurface
1 and dashed line is surface 2. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
5.8 M5statisticsmeasuresofdifferentblocksizes; (a)Mean(b)Variance; Solidlineissurface
3, dashed line is surface 4 and dashdotted line is surface 5. . . . . . . . . . . . . . . . 25
5.9 Block statistics test for stationarity with 4410 samples/block on surface 1(60 seconds) in
M1; (a) Mean (b) Variance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
5.10 Histogram of (a) M1 (b) M11. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
5.11 M1; (a) shows the current data with the rapidly changing characteristic when switching
row in welding process; (b) shows the voltage and it’s transients. . . . . . . . . . . . . . 27
5.12 M1; (a) shows the current data with the rapidly changing characteristic when switching
row in welding process; (b) shows the voltage and it’s transients. . . . . . . . . . . . . . 28
5.13 M1; (a) shows the current data with the rapidly changing characteristic when switching
row in welding process; (b) shows the voltage and it’s transients. . . . . . . . . . . . . . 28
5.14 Spectrogram of M1. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
5.15 Spectrogram of M2. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
5.16 Spectrogram of M3. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
5.17 Spectrogram of M10. Notice the change of surfaces at 1500 and 2500 blocks.. . . . . . . 31
5.18 Spectrogram of M11. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
5.19 Spectrogram of M12. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
5.20 Designed highpass filter for voltage. . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
5.21 M1statisticsresultsoffilteredvoltagesignalusingblocklength2048;(a)IQR(b)Variance
(c) Skewness (d) Kurtosis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
5.22 M2statisticsresultsoffilteredvoltagesignalusingblocklength2048;(a)IQR(b)Variance
(c) Skewness (d) Kurtosis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
5.23 M3statisticsresultsoffilteredvoltagesignalusingblocklength2048;(a)IQR(b)Variance
(c) Skewness (d) Kurtosis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
5.24 M10 statistics results of filtered voltage signal using block length 2048; (a) IQR (b) Vari-
ance (c) Skewness (d) Kurtosis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
5.25 M11 statistics results of filtered voltage signal using block length 2048; (a) IQR (b) Vari-
ance (c) Skewness (d) Kurtosis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
5.26 M12 statistics results of filtered voltage signal using block length 2048; (a) IQR (b) Vari-
ance (c) Skewness (d) Kurtosis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
5.27 Spectrogram of M1 over whole spectrum. . . . . . . . . . . . . . . . . . . . . . . . . . 39
5.28 Spectrogram of M1. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
5.29 Spectrogram of M2. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
5.30 Spectrogram of M3. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
5.31 Spectrogram of M10. Notice the change of surfaces at 600 and 1000 blocks. . . . . . . . 41
5.32 Spectrogram of M11. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
5.33 Spectrogram of M12. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
5.34 Designed lowpass filter for current. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
5.35 M1statisticsresultsoffilteredcurrentsignalusingblocklength512; (a)IQR(b)Variance
(c) Skewness (d) Kurtosis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
5.36 M2statisticsresultsoffilteredcurrentsignalusingblocklength512; (a)IQR(b)Variance
(c) Skewness (d) Kurtosis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
5.37 M3statisticsresultsoffilteredcurrentsignalusingblocklength512; (a)IQR(b)Variance
(c) Skewness (d) Kurtosis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
5.38 M10 statistics results of filtered current signal using block length 512; (a) IQR (b) Vari-
ance (c) Skewness (d) Kurtosis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
LIST OF FIGURES 9
5.39 M11 statistics results of filtered current signal using block length 512; (a) IQR (b) Vari-
ance (c) Skewness (d) Kurtosis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
5.40 M12 statistics results of filtered current signal using block length 512; (a) IQR (b) Vari-
ance (c) Skewness (d) Kurtosis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
5.41 Recursive sum method for voltage in M1 using block length 2048; (a) Variance (b) Skewness 50
5.42 RecursivesummethodforvoltageinM11usingblocklength2048; (a)Variance(b)Skewness 51
5.43 Recursive sum method for voltage in M5 using block length 2048; (a) Variance (b) Skewness 51
5.44 Recursive sum method for voltage in M8 using block length 2048; (a) Variance (b) Skewness 52
5.45 RecursivesummethodforcurrentinM1usingblocklength2048; (a)Variance(b)Skewness 52
5.46 RecursivesummethodforcurrentinM11usingblocklength2048;(a)Variance(b)Skewness 53
5.47 RecursivesummethodforcurrentinM5usingblocklength2048; (a)Variance(b)Skewness 53
5.48 RecursivesummethodforcurrentinM8usingblocklength2048; (a)Variance(b)Skewness 54
5.49 Recursive sum method with forgetting factor γ =0.99, voltage in M1 using block length
2048; (a) IQR (b) Variance (c) Skewness (d) Kurtosis. . . . . . . . . . . . . . . . . . 55
5.50 Recursive sum method with forgetting factor γ =0.99, voltage in M5 using block length
2048; (a) IQR (b) Variance (c) Skewness (d) Kurtosis. . . . . . . . . . . . . . . . . . 56
5.51 Recursive sum method with forgetting factor γ =0.99, voltage in M4 using block length
2048; (a) IQR (b) Variance (c) Skewness (d) Kurtosis. . . . . . . . . . . . . . . . . . 57
5.52 M1 voltage signal, highpass filtered, using recursive sum method with γ=0.99 and block
length 2048; (a) IQR (b) Variance (c) Skewness (d) Kurtosis. . . . . . . . . . . . . . . 59
5.53 M2 voltage signal, highpass filtered, using recursive sum method with γ=0.99 and block
length 2048; (a) IQR (b) Variance (c) Skewness (d) Kurtosis. . . . . . . . . . . . . . . 60
5.54 M3 voltage signal, highpass filtered, using recursive sum method with γ=0.99 and block
length 2048; (a) IQR (b) Variance (c) Skewness (d) Kurtosis. . . . . . . . . . . . . . . 61
5.55 M10 voltage signal, highpass filtered, using recursive sum method with γ=0.99 and block
length 2048; (a) IQR (b) Variance (c) Skewness (d) Kurtosis. . . . . . . . . . . . . . . 62
5.56 M11 voltage signal, highpass filtered, using recursive sum method with γ=0.99 and block
length 2048; (a) IQR (b) Variance (c) Skewness (d) Kurtosis. . . . . . . . . . . . . . . 63
5.57 M12 voltage signal, highpass filtered, using recursive sum method with γ=0.99 and block
length 2048; (a) IQR (b) Variance (c) Skewness (d) Kurtosis. . . . . . . . . . . . . . . 64
5.58 M1 voltage signal, highpass filtered, using recursive sum method with γ=0.99 and block
length 2048; (a) IQR (b) Variance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
5.59 M1 voltage signal, decimated by 2, highpass filtered, using recursive sum method with
γ=0.99 and block length 2048; (a) IQR (b) Variance. . . . . . . . . . . . . . . . . . . 66
5.60 M1 voltage signal, decimated by 3, highpass filtered, using recursive sum method with
γ=0.99 and block length 2048; (a) IQR (b) Variance. . . . . . . . . . . . . . . . . . . 66
6.1 Sampled audio signal; (a) Clipped signal from PC-1 soundcard from M1 (b) Not clipped
signal using DAQ in M14. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
6.2 Spectrogram of M3. At ≈1500 blocks the welding process proceeds on the rusty surface. . 70
6.3 Spectrogram of M12. At ≈1500 blocks the welding process proceeds on the rusty surface. 71
6.4 Designed highpass filter for sound. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
6.5 Highpass filtered sound signal in time domain; (a) M1 (b) M11 . . . . . . . . . . . . . 72
6.6 Highpass filtered M1 sound signal, using recursive sum method with γ = 0.99 and block
length 4096; (a) Variance (b) Kurtosis. At ≈1500 blocks the welding proceeds on the
rusty surface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
6.7 Highpass filtered M2 sound signal, using recursive sum method with γ = 0.99 and block
length 4096; (a) Variance (b) Kurtosis. At ≈1500 blocks the welding process proceeds on
the rusty surface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
10 LIST OF FIGURES
6.8 Highpass filtered M3 sound signal, using recursive sum method with γ = 0.99 and block
length 4096; (a) Variance (b) Kurtosis. At ≈1500 and ≈2500 blocks the welding process
proceeds on the rusty surface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
6.9 Highpass filtered M10 sound signal, using recursive sum method with γ = 0.99 and block
length 4096; (a) Variance (b) Kurtosis. At ≈1500 blocks the welding process proceeds on
the rusty surface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
6.10 Highpass filtered M11 sound signal, using recursive sum method with γ = 0.99 and block
length 4096; (a) Variance (b) Kurtosis. At ≈1500 blocks the welding process proceeds on
the rusty surface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
6.11 Highpass filtered M12 sound signal, using recursive sum method with γ = 0.99 and block
length 4096; (a) Variance (b) Kurtosis. At ≈1500 blocks the welding process proceeds on
the rusty surface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
6.12 Highpass filtered M13 sound signal, using recursive sum method with γ = 0.99 and block
length 4096; (a) Variance (b) Kurtosis. At ≈1500 blocks the welding process proceeds on
the rusty surface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
6.13 Lowpass filter with pass band 1 Hz and transition band 90 Hz. . . . . . . . . . . . . . . 77
6.14 Spectrogram of the audio record for first surface in M12. Zoomed at frequency range 0 -
500 Hz. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
6.15 Spectrogram of second surface in M2. The power of the signal is around -60 dB for the
most of the blocks. Few blocks have power over -40 dB. . . . . . . . . . . . . . . . . . 78
6.16 Spectrogram of second surface in M1. The signal has higher number of blocks with power
above -40 dB. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
6.17 Spectrogram of second surface in M3. The signal consists of blocks with power above -40
dB mostly. Only few blocks have power below -40dB. . . . . . . . . . . . . . . . . . . . 79
6.18 Spectrogram of third surface in M7. . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
6.19 Spectrogram of third surface in M8. . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
6.20 Spectrogram of third surface in M9. . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
6.21 Statistical data example for M2, surface 2 only, calculated from signal power; (a) Mean
(b) Variance (c) Skewness (d) Kurtosis. . . . . . . . . . . . . . . . . . . . . . . . . . 82
6.22 Statistical data example for M2, surface 2 only, smoothed signal power; (a) Mean (b)
Variance (c) Skewness (d) Kurtosis. . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
6.23 Mean of sound power for each speed group; (a) Original (b) Zoomed. . . . . . . . . . . 84
6.24 Mean value of averaged variance for each speed group; (a) Original (b) Zoomed. . . . . . 85
6.25 Power Spectral Density (PSD) using Welch periodogram method on M1. . . . . . . . . . 86
6.26 Power Spectral Density (PSD) using Welch periodogram method on M14. . . . . . . . . 87
A.1 M8statisticsmeasuresofdifferentblocksizes; (a)Mean(b)Variance; Solidlineissurface
1 and dashed line is surface 2. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
A.2 M11 statistics measures of different block sizes; (a) Mean (b) Variance; Solid line is
surface 3, dashed line is surface 4 and dashdotted line is surface 5. . . . . . . . . . . . 94
A.3 M8statisticsmeasuresofdifferentblocksizes; (a)Mean(b)Variance; Solidlineissurface
1 and dashed line is surface 2. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
A.4 M11 statistics measures of different block sizes; (a) Mean (b) Variance; Solid line is
surface 3, dashed line is surface 4 and dashdotted line is surface 5. . . . . . . . . . . . 95
A.5 M4statisticsresultsoffilteredvoltagesignalusingblocklength2048;(a)IQR(b)Variance
(c) Skewness (d) Kurtosis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
A.6 M5statisticsresultsoffilteredvoltagesignalusingblocklength2048;(a)IQR(b)Variance
(c) Skewness (d) Kurtosis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97