296
D. Mishra et al.
66. Sala A, Tonolini F, Villa G, Nardoni G (1987) Monitoring of acoustic emission during the
welding process. Weld Int 1:655–658. https://doi.org/10.1080/09507118709453014
67. Jolly WD (1969) Acoustic emission exposes cracks during welding. Weld J 48:21–27
68. Luo Y, Li JL, Wu W (2013) Nugget quality prediction of resistance spot welding on aluminium
alloy based on structureborne acoustic emission signals. Sci Technol Weld Join 18:301–306.
https://doi.org/10.1179/1362171812Y.0000000102
69. Chen C, Kovacevic R, Jandgric D (2003) Wavelet transform analysis of acoustic emission in
monitoring friction stir welding of 6061 aluminum. Int J Mach Tools Manuf 43:1383–1390.
https://doi.org/10.1016/S0890-6955(03)00130-5
70. Soundararajan V, Atharifar H, Kovacevic R (2006) Monitoring and processing the acoustic
emission signals from the friction-stir-welding process. Proc Inst Mech Eng Part B J Eng
Manuf 220:1673–1685. https://doi.org/10.1243/09544054JEM586
71. Jiménez-Macías E, Sánchez-Roca A, Carvajal-Fals H et al (2014) Wavelets application in
prediction of friction stir welding parameters of alloy joints from vibroacoustic ANN-based
model. Abstr Appl Anal 2014. https://doi.org/10.1155/2014/728564
72. Subramaniam S, Narayanan S, Ashok SD (2013) Acoustic emission-based monitoring
approach for friction stir welding of aluminum alloy AA6063-T6 with different tool pin
profiles. Proc Inst Mech Eng Part B-Journal Eng Manuf 227:407–416. https://doi.org/10.
1177/0954405412472673
73. Chin BA, Madsen NH, Goodling JS (1983) Infrared Thermography for Sensing the Weld
Process. 84–86
74. Alfaro SCA, Franco FD (2010) Exploring infrared sensoring for real time welding defects
monitoring in GTAW. Sensors 10:5962–5974. https://doi.org/10.3390/s100605962
75. Khan MA, Madsen NH, Chin BA (1984) Infrared Thermography As A Control For
The Welding Process. In: Burrer GJ (ed) Thermosense VI: Thermal Infrared Sensing for
Diagnostics and Control. pp 154–163
76. Nagarajan S, Banerjee P, Chen W, Chin BA (316AD) Control of the Welding Process using
Infrared Sensors. IEEE Trans Robot Autom 8:400
77. Cullen JD, Athi N, Al-Jader M et al (2008) Multisensor fusion for on line monitoring of the
quality of spot welding in automotive industry. Meas J Int Meas Confed 41:412–423. https://
doi.org/10.1016/j.measurement.2007.01.006
78. Mahto RP, Kumar R, Pal SK, Panda SK (2018) A comprehensive study on force, temperature,
mechanical properties and micro-structural characterizations in friction stir lap welding of
dissimilar materials (AA6061-T6 & AISI304). J Manuf Process 31:624–639. https://doi.org/
10.1016/j.jmapro.2017.12.017
79. Das B, Pal S, Bag S (2019) Probing defects in friction stir welding process using temperature
profile. Sadhana - Acad Proc Eng Sci 44:1–9. https://doi.org/10.1007/s12046-019-1068-2
80. De Backer J, Bolmsjö G, Christiansson A-K (2014) Temperature control of robotic friction
stir welding using the thermoelectric effect. Int J Adv Manuf Technol 70:375–383. https://
doi.org/10.1007/s00170-013-5279-0
81. Backer J (2014) Feedback Control of Robotic Friction Stir Welding
82. Fleming P, Lammlein D, Wilkes D et al (2008) In-Process Gap Detection in Friction Stir
Welding. 1:62–67. https://doi.org/10.1108/02602280810850044
83. Yang Y, Kalya P, Landers RG, Krishnamurthy K (2008) Automatic gap detection in friction
stir butt welding operations. Int J Mach Tools Manuf 48:1161–1169. https://doi.org/10.1016/
j.ijmachtools.2008.01.007
84. Das B, Pal S, Bag S (2016a) Defect Detection in Friction Stir Welding Process Using Signal
Information and Fractal Theory. Procedia Eng 144:172–178. https://doi.org/10.1016/j.proeng.
2016.05.021
85. Das B, Pal S, Bag S (2016b) A combined wavelet packet and Hilbert-Huang transform for
defect detection and modelling of weld strength in friction stir welding process. J Manuf
Process 22:260–268. https://doi.org/10.1016/j.jmapro.2016.04.002
86. Das B, Pal S, Bag S (2017b) Torque based defect detection and weld quality modelling in
friction stir welding process. J Manuf Process 27:8–17. https://doi.org/10.1016/j.jmapro.2017.
03.012
D. Mishra et al.
66. Sala A, Tonolini F, Villa G, Nardoni G (1987) Monitoring of acoustic emission during the
welding process. Weld Int 1:655–658. https://doi.org/10.1080/09507118709453014
67. Jolly WD (1969) Acoustic emission exposes cracks during welding. Weld J 48:21–27
68. Luo Y, Li JL, Wu W (2013) Nugget quality prediction of resistance spot welding on aluminium
alloy based on structureborne acoustic emission signals. Sci Technol Weld Join 18:301–306.
https://doi.org/10.1179/1362171812Y.0000000102
69. Chen C, Kovacevic R, Jandgric D (2003) Wavelet transform analysis of acoustic emission in
monitoring friction stir welding of 6061 aluminum. Int J Mach Tools Manuf 43:1383–1390.
https://doi.org/10.1016/S0890-6955(03)00130-5
70. Soundararajan V, Atharifar H, Kovacevic R (2006) Monitoring and processing the acoustic
emission signals from the friction-stir-welding process. Proc Inst Mech Eng Part B J Eng
Manuf 220:1673–1685. https://doi.org/10.1243/09544054JEM586
71. Jiménez-Macías E, Sánchez-Roca A, Carvajal-Fals H et al (2014) Wavelets application in
prediction of friction stir welding parameters of alloy joints from vibroacoustic ANN-based
model. Abstr Appl Anal 2014. https://doi.org/10.1155/2014/728564
72. Subramaniam S, Narayanan S, Ashok SD (2013) Acoustic emission-based monitoring
approach for friction stir welding of aluminum alloy AA6063-T6 with different tool pin
profiles. Proc Inst Mech Eng Part B-Journal Eng Manuf 227:407–416. https://doi.org/10.
1177/0954405412472673
73. Chin BA, Madsen NH, Goodling JS (1983) Infrared Thermography for Sensing the Weld
Process. 84–86
74. Alfaro SCA, Franco FD (2010) Exploring infrared sensoring for real time welding defects
monitoring in GTAW. Sensors 10:5962–5974. https://doi.org/10.3390/s100605962
75. Khan MA, Madsen NH, Chin BA (1984) Infrared Thermography As A Control For
The Welding Process. In: Burrer GJ (ed) Thermosense VI: Thermal Infrared Sensing for
Diagnostics and Control. pp 154–163
76. Nagarajan S, Banerjee P, Chen W, Chin BA (316AD) Control of the Welding Process using
Infrared Sensors. IEEE Trans Robot Autom 8:400
77. Cullen JD, Athi N, Al-Jader M et al (2008) Multisensor fusion for on line monitoring of the
quality of spot welding in automotive industry. Meas J Int Meas Confed 41:412–423. https://
doi.org/10.1016/j.measurement.2007.01.006
78. Mahto RP, Kumar R, Pal SK, Panda SK (2018) A comprehensive study on force, temperature,
mechanical properties and micro-structural characterizations in friction stir lap welding of
dissimilar materials (AA6061-T6 & AISI304). J Manuf Process 31:624–639. https://doi.org/
10.1016/j.jmapro.2017.12.017
79. Das B, Pal S, Bag S (2019) Probing defects in friction stir welding process using temperature
profile. Sadhana - Acad Proc Eng Sci 44:1–9. https://doi.org/10.1007/s12046-019-1068-2
80. De Backer J, Bolmsjö G, Christiansson A-K (2014) Temperature control of robotic friction
stir welding using the thermoelectric effect. Int J Adv Manuf Technol 70:375–383. https://
doi.org/10.1007/s00170-013-5279-0
81. Backer J (2014) Feedback Control of Robotic Friction Stir Welding
82. Fleming P, Lammlein D, Wilkes D et al (2008) In-Process Gap Detection in Friction Stir
Welding. 1:62–67. https://doi.org/10.1108/02602280810850044
83. Yang Y, Kalya P, Landers RG, Krishnamurthy K (2008) Automatic gap detection in friction
stir butt welding operations. Int J Mach Tools Manuf 48:1161–1169. https://doi.org/10.1016/
j.ijmachtools.2008.01.007
84. Das B, Pal S, Bag S (2016a) Defect Detection in Friction Stir Welding Process Using Signal
Information and Fractal Theory. Procedia Eng 144:172–178. https://doi.org/10.1016/j.proeng.
2016.05.021
85. Das B, Pal S, Bag S (2016b) A combined wavelet packet and Hilbert-Huang transform for
defect detection and modelling of weld strength in friction stir welding process. J Manuf
Process 22:260–268. https://doi.org/10.1016/j.jmapro.2016.04.002
86. Das B, Pal S, Bag S (2017b) Torque based defect detection and weld quality modelling in
friction stir welding process. J Manuf Process 27:8–17. https://doi.org/10.1016/j.jmapro.2017.
03.012