摘要
电阻点焊过程易受多种故障因素的影响,针对生产过程中经常出现的电极轴向错位、工件表面未处理、工件翘曲和工件导电不良四种故障状态,通过对实时采集的电极位移信号波形的时域分析,提取了五个能表征故障状态的特征参量,建立了基于模糊相似优先比案例推理的点焊过程诊断模型。实验验证表明,基于信号特征提取表征点焊过程故障状态的方法是可行的,该模型的诊断准确率可达95%。
RSM（Resistance Spot Welding） is vulnerable to the impact of a variety of fault factors.Aiming at electrode axial misahgnment, untreated surface,workpiece warping and conductive bad of which often appear in the production process.Through time-domain analysis of electrode displacement signals curve,5 characteristic parameters are selected to taking as the faults.The case-based reasoning model based on fuzzy similar ratio is established to realize faults diagnosis in welding process.Experimental verification shows that the method based on signal feature extraction to taking as fault in welding process is feasible,and the diagnostic accuracy is 95%.
出处
《电焊机》
2008年第12期66-69,共4页
Electric Welding Machine
基金
国家自然科学基金资助项目(50275028)
关键词
电阻点焊
特征参量提取
奇异性分析
模糊相似优先比
故障诊断
resistance spot welding
characteristic parameters extraction
singularity analysis
fuzzy similar ratio
fault diagnosis
作者简介
杨乃文（1982-），男，山西太原人，硕士，主要从事焊接自动化和焊接设备的研究工作。
