管道MIG焊双通道电弧声信号采集与特征分析

对管道MIG焊双通道信号采集和特征分析做了初步研究．因管道其内部是一个相对狭小密闭的空间,回声的干扰相对较大,经过对采集的双通道电弧声信号进行ICA信号分离,对分离后的信号做小波降噪处理,信噪比得到明显提高．对降噪后的信号从时域、频域和时频域角度,综合分析管内和管外电弧声信号与焊缝熔透状态之间的内在相关性,发现电弧声信号能量及其频谱特性与熔透状态高度相关,焊接过程中信号能量幅值随熔透增大而增大,为后续利用电弧声信号来控制焊接质量提供了基础．     

焊接电弧声信号降噪技术

焊接电弧声作为焊接过程质量监控潜在的源信号之一,在传感、转换以及传输等过程极易受到设备、环境噪声的污染,从硬件、软件两个方面分别对其进行降噪处理.硬件方面包括低噪声传声器、接地装置、消除直流偏移的交流耦合、采用仪器放大器、抗混叠滤波以及屏蔽电缆等措施;软件方面运用基于多尺度分析理论的 Mallat 算法,实现了基于 LabVIEW 的电弧声小波分解重构降噪处理.结果表明,电弧声信号经硬件、软件降噪后,不仅"毛刺"得到有效滤除,而且波形突变部分更加清晰,信噪比大幅度提高,为后续电弧声信号特征分析提取以及利用电弧声来监控焊接质量提供技术基础.

Abstract：

Arc sound is well known as one of the potential source signals for controlling of welding process quality, which is vulnerable to noise pollution by equipment and environment in sensing, conversing and transmission. Therefore, it is necessary to reduce arc sound noise by hardware and software. Hardware measures include low-noise microphone, grounding devices, eliminating the DC offset exchange coupling, equipment amplifiers, anti-alias filtering and shielding cables, etc. In terms of software, by using Mallat algorithm based on principle of multi-resolution, the noise of arc sound signal is reduced via wavelet decomposition and reconstruction based on LabVIEW. The results show that the burr of arc sound is effectively filtered out, the mutations of waveform are clearer and the noise ratio is obviously increased. The reducing noise means provide technical basis for extracting characteristics of arc signal and monitoring welding quality via arc signal.