【作者】 黄健康；

【导师】 樊丁； 石玗；

【作者基本信息】 兰州理工大学 ， 材料加工工程， 2007， 硕士

【摘要】 焊接是一个集声、光、电于一体的复杂的物理、化学过程，各种信号为焊接过程控制、质量控制提供重要信息。电弧声信号作为焊接过程中的伴生物之一，其蕴涵着丰富的电弧信息，它与电弧行为、熔滴过渡方式、电弧稳定性、焊缝质量等有着密切的相关性，是研究焊接过程稳定性及焊接质量监控的重要信息源之一。本课题以铝合金MIG焊电弧声为研究对象，分析了电弧声与熔滴过渡的相关性；通过ARMA双谱对不同熔滴过渡的电弧声分析确立不同熔滴过渡的电弧声模式，并通过SVM进行了模式识别；研究了电弧声信号与铝合金MIG焊缝塌陷的相关性。首先，建立了一套声、光、电同步采集实验系统，采用MATLAB软件平台对数据进行处理。通过同步信号采集和对所采集的数据进行分析得到电弧声信号的周期变化就是熔滴过渡的频率，确立了电弧声与熔滴过渡的相关性。运用不同的功率谱估计对电弧声进行了对比分析，得出AR参数化功率谱估计对电弧声频率的提取分析优势，快速获取了熔滴过渡频率，同时分析运用AR参数化功率谱估计对不同熔滴过渡的电弧声进行了分析。运用ARMA双谱估计的方法获取了不同熔滴过渡的电弧声双谱信息，通过分析从双谱信息中提取了特征值。用所获得的特征值进行SVM模式识别，得到不同熔滴过渡的电弧声能很好地进行分类和辨识，实现了基于电弧声对熔滴过渡类型进行快速识别。通过对焊接过程中电弧声和焊缝塌陷的相关性分析，发现在铝合金MIG焊过程中，电弧声信号能量和焊缝情况存在着明显的相关性，电弧声信号的总能量随着焊缝塌陷而明显增强，塌陷前与塌陷后的信号能量改变十分明显。通过电弧声信号的小波包分解，可以看出电弧声信号在不同的频率范围的能量百分比分布规律，而频率范围为[2.756 25kHz，27.562 5kHz]信号的能量变化能非常准确地检测出焊接过程中焊缝塌陷。更多还原

【Abstract】 Welding process is a complex physical and chemical process containing arc sound, arc light, and electrical signal, etc. Each kind of signals provides important information for welding process control and quality control. As a concomitant of welding process, arc sound signal contains rich information about arc and has a close relevance with arc behavior, metal transfer, stability of arc, welded joint quality and so on. It is an important information resource for studying the stability of welding process and monitoring and controlling welding quality. Arc sound in aluminum alloy MIG welding process was studied on the relativity between arc sound signal and metal transfer in this thesis. Arc sound patterns of different metal transfer were established by analyzing arc sound in different metal transfer with ARMA two-spectra, and then were used to do pattern recognition though SVM. The relativity between arc sound signal and the subsidence of aluminum alloy MIG welding bead was also studied in the thesis. The main works were done as follows:The signal gathering experiment system was developed to gather arc sound, arc light and electrical signal synchronously and MATLAB software was used to process data in the thesis.Through analyzing the signal data gathered by the signal synchronous gathering system, the relativity of arc sound and metal transfer that arc signal frequency is the same as metal transfer frequency is found. After analyzing arc sound by different power spectrum estimation methods, AR parameterization estimation power spectrum estimation method is better than others and can gain metal transfer frequency fast. Then arc sound in different metal transfer modes were analyzed by AR parameterization estimation power spectrum estimation method.The double-spectrum information of arc sound in different metal transfer mode was obtained by ARMA double-spectrum estimation method and the feature values could be detected from these double-spectrum information. SVM pattern recognition with the feature value can classify arc sound in different metal transfer mode and realize fast recognizing metal transfer mode by arc sound.The studies on the relativity between arc sound and the subsidence of welding bead show that the arc sound signal energy has some relation with welding bead. The total energy of arc sound signal increases along with the subsidence of welding bead and change largely before the subsidence and after the subsidence. Arc sound signal was processed by wavelet packet and the energy distribution rule of arc sound signal indifferent frequency range was obtained. The energy distribution of arc sound signal shows that the subsidence of welding bead can be detected accurately from the change of arc sound energy within frequency range from 2.75kHz to 27.5kHz.更多还原