学术论文

      一种基于数据间相关性的激光喷丸声学监测技术

      A condition monitoring method for laser peening based on the correlation between the adjacent aata

      摘要:
      激光喷丸作为一种新兴的金属材料表面强化技术,与普通喷丸相比,具有更显著的改性作用,使其在航空等领域有着重要的应用价值。随着该技术的工业化程度不断加深,需要加强对其工作状态的监测诊断,保证其良好的运行状况。由于声学信号不仅携带有丰富的工作特征信息,而且获取成本较低,并能够实现无损检测,所以将声学信号应用于激光喷丸的状态监测。通过分析由等离子体冲击波衰减所产生的声波信号,提取信号特征,进行过程监测。针对于冲击信号的非线性特征,从信号内相邻数据间相关性的角度,提出了一种新的冲击声信号特征挖掘方法。一方面对于模拟冲击信号进行了分析,另一方面,对于激光喷丸实际声信号进行了处理,表明该方法能够识别冲击信号的特征变化,可以用于监测激光喷丸的工作过程,操作简单且速度较快,具有较好的应用前景。
      Abstract:
      As an innovative surface treatment of metal material,laser peening makes greater performance in improving the mechanical property comparing with the conventional shot peening,and it can bring significant contributions to various fields like aerocraft industry.In accordance with the developing pace of its industrialization,the condition monitoring,aiming at maintaining a good working state,is arousing more and more attentions.The acoustic signal with lower cost contains abundant information related to the operating process,and it can be used as non-destructive condition detection of the laser peening.The shock acoustic signal,which is propagating from the original plasma shock wave,was analyzed to extract the valuable characteristics to monitor the process.Considering the nonlinearity of the shock acoustic signal,a new signal processing method was proposed,based on the correlation between the neighbor data in the signal array.On one hand,it was used in analyzing the simulating shock-wave signal;on the other hand,it was applied in studying the practical signal obtained from the laser shock processing.It was shown that the novel method could detect the shock wave signal efficiently with easy and quick operation.It thus has potential in applications.
      作者: 邱辰霖 [1] 程礼 [2] 何卫锋 [2]
      Author: QIU Chenlin [1] CHENG Li [2] HE Weifeng [2]
      作者单位: 空军工程大学 航空航天工程学院,西安 710038; 北京航空航天大学 能源与动力工程学院,北京 100191 空军工程大学 航空航天工程学院,西安,710038
      刊 名: 振动与冲击 ISTICEIPKU
      年,卷(期): 2017, 36(4)
      分类号: TP391 TN249
      在线出版日期: 2017年3月20日
      基金项目: 国家自然科学基金资助项目