Detection of arc characteristics and weld forming quality of aluminum alloy DP-MIG welding using AE signal through resonance demodulation

被引:8
作者
He, Kuanfang [1 ]
Xia, Zixiong [1 ]
Si, Yin [1 ]
Liang, Jiahe [1 ]
Yong, Jiangfeng [1 ]
Shi, Wenqing [2 ]
机构
[1] Foshan Univ, Sch Mech & Elect Engn & Automat, Foshan 528000, Peoples R China
[2] Guangdong Ocean Univ, Coll Elect & Informat Engn, Zhanjiang 524088, Peoples R China
基金
中国国家自然科学基金;
关键词
Aluminum alloy DP-MIG welding; AE signal; HHT; Resonance demodulation; Permutation entropy; Arc stability; Welding quality detection; ACOUSTIC-EMISSION SIGNALS; FEATURE-EXTRACTION; IDENTIFICATION; STEEL;
D O I
10.1016/j.measurement.2021.110427
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Acoustic emission (AE) signals are generated during aluminum alloy double-pulse melt inert-gas (DP-MIG) welding, which contains physical information related to arc stability and weld forming quality. In this paper, the AE signal test platform of aluminum alloy DP-MIG welding is constructed. An adaptive resonance demodulation method for AE signals in unknown frequency bands is proposed, which is applied for the AE signals of the six groups different welding process parameters. The time-domain waveform and frequency spectrum of the ac-quired AE envelope signals are consistent with that of the arc current. Hilbert-Huang transform (HHT) is per -formed on the envelope signal to obtain a time-frequency diagram. The signal energy changes periodically along the time scale, and the frequency distribution ranges from 0 to 2000 Hz. The segmental entropy of the AE signal is calculated to evaluate the welding seam forming quality. The calculated entropy values of 0.6, 0.9 and 1 mean that the welding seam is formed well, the values of 1.6 and 1.9 mean that the welding seam is poor. The research provides a new and effective method for realizing the quality monitoring of aluminum alloy DP-MIG welding process.
引用
收藏
页数:18
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共 45 条
  • [1] Machine learning model to predict welding quality using air-coupled acoustic emission and weld inputs
    Asif, Kaiser
    Zhang, Lu
    Derrible, Sybil
    Indacochea, J. Ernesto
    Ozevin, Didem
    Ziebart, Brian
    [J]. JOURNAL OF INTELLIGENT MANUFACTURING, 2022, 33 (03) : 881 - 895
  • [2] An algorithm for the continuous Morlet wavelet transform
    B ssow, Richard
    [J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2007, 21 (08) : 2970 - 2979
  • [3] Permutation entropy: A natural complexity measure for time series
    Bandt, C
    Pompe, B
    [J]. PHYSICAL REVIEW LETTERS, 2002, 88 (17) : 4
  • [4] Interpreting the weld formations using acoustic emission for the carbon steels and stainless steels welds in servo-based resistance spot welding
    Charde, Nachimani
    Ahmad, Roslina
    Abidin, Nor Ishida Zainal
    [J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2016, 86 (1-4) : 1 - 8
  • [5] Application of Shannon Wavelet Entropy and Shannon Wavelet Packet Entropy in Analysis of Power System Transient Signals
    Chen, Jikai
    Dou, Yanhui
    Li, Yang
    Li, Jiang
    [J]. ENTROPY, 2016, 18 (12):
  • [6] A vision-based system for post-welding quality measurement and defect detection
    Chu, Hui-Hui
    Wang, Zong-Yi
    [J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2016, 86 (9-12) : 3007 - 3014
  • [7] Experimental investigation on microstructure, mechanical properties, and residual stresses of dissimilar welded joint of martensitic P92 and AISI 304L austenitic stainless steel
    Dak, Gaurav
    Pandey, Chandan
    [J]. INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING, 2021, 194
  • [8] Acoustic emission as a tool for prediction of nugget diameter in resistance spot welding
    Dejans, Arnout
    Kurtov, Oleksandr
    Van Rymenant, Patrick
    [J]. JOURNAL OF MANUFACTURING PROCESSES, 2021, 62 : 7 - 17
  • [9] Nonlinear finite-time Lyapunov exponent and predictability
    Ding, Ruiqiang
    Li, Jianping
    [J]. PHYSICS LETTERS A, 2007, 364 (05) : 396 - 400
  • [10] Acoustic emission method for defect detection and identification in carbon steel welded joints
    Droubi, Mohamad G.
    Faisal, Nadimul H.
    Orr, Fraser
    Steel, John A.
    El-Shaib, Mohamed
    [J]. JOURNAL OF CONSTRUCTIONAL STEEL RESEARCH, 2017, 134 : 28 - 37