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| 焊接过程声信号在线检测技术现状与展望 |
| Status and Prospect of On-Line Acoustic Signal Detection Technology in Welding |
| Received:June 02, 2021 |
| DOI：10.3969/j.issn.1674-6457.2022.01.021 |
| 中文关键词: 焊接质量 声学检测 声发射 电弧声 模式识别 |
| 英文关键词: welding quality acoustic detection acoustic emission arc sound pattern recognition |
| 基金项目:广州市科技计划(202002020068) |
| Author Name | Affiliation | | FANG Hai-ji | Guangdong Provincial Welding Engineering Technology Research Center, Guangdong University of Technology, Guangzhou 510006, China | | LYU Bo | Guangdong Provincial Welding Engineering Technology Research Center, Guangdong University of Technology, Guangzhou 510006, China | | ZHANG Yan-xi | Guangdong Provincial Welding Engineering Technology Research Center, Guangdong University of Technology, Guangzhou 510006, China | | LU Xin-zhao | Guangdong Jingtai Civil Air Defense Engineering Company, Zhaoqing 526238, China | | GAO Xiang-dong | Guangdong Provincial Welding Engineering Technology Research Center, Guangdong University of Technology, Guangzhou 510006, China |
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| 中文摘要: |
| 基于焊接过程声信号的声学检测技术是一种实时采集和检测缺陷的有效方法，对材料内部结构变化反映明显。概述了常规焊接缺陷无损检测方法的优缺点，对焊接过程声信号的分类和声信号采集系统进行了论述，分析总结了声发射信号和可听声信号的发声机理、检测原理和信号处理方法，并阐述其在焊接质量在线检测领域的研究现状及应用，特别是焊接缺陷、熔滴过渡形式和熔透状态的识别与预测。为了满足在线检测要求，包含声学检测在内的多传感信息融合焊接系统研究是关键，智能传感、信号处理、自动控制与人工智能技术的进一步研究能促进焊接产业的长足发展。 |
| 英文摘要: |
| The detection technology based on acoustic signal during welding is effective for real-time collection and detection of welding defects, and reflects the changes in internal structure of weldments. The advantages and disadvantages of conventional non-destructive testing methods for welding defects were summarized. The classification of acoustic signals and the acoustic signal acquisition system during welding were discussed. The sounding mechanisms, detection principles and signal processing methods of acoustic emission signal and audible acoustic signal were analyzed and summarized. Also, the research status and application of online detection on welding quality were described, especially the identification and prediction of welding defects, droplet transition forms and penetration status. Research on the welding system of multi-sensor information fusion including acoustic inspection is the key to meet the requirements of online detection. The further research of intelligent sensing, signal processing, automatic control and artificial intelligence technology can promote the rapid development of the welding industry. |
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