全封闭往复式压缩机制造缺陷诊断方法研究

A diagnosis method for manufacturing defects of hermetic reciprocating compressor

全封闭往复式压缩机作为制冷系统的核心部件,其品质决定了整机系统的能效水平、静音效果和产品寿命。在生产线制造过程中,针对全封闭结构特点难以识别缺陷产品的短板问题,本文提出了一种基于壳体振动信号的压缩机制造缺陷诊断方法。首先通过集合经验模态分解(EEMD)对振动信号进行频谱分解,再利用多尺度样本熵(MSE)来表征不同尺度下各模态分量的复杂度并以此作为特征向量,最后利用支持向量机(SVM)完成制造缺陷的分类。实验结果表明,本文所提诊断方法能准确实现典型制造缺陷的识别与分类,为全封闭往复式压缩机制造缺陷的在线检测提供了相关理论与检测依据。

As the core component of the refrigeration system,the quality of hermetic reciprocating compressor determines the energy efficiency level,silent effect,and product life of the whole system.In the manufacturing process of the production line,in order to solve the shortcomings that it is difficult to identify the defective product due to the characteristics of the hermetic structure,this paper proposes a diagnosis method for manufacturing defects based on the vibration signal of the compressor shell.First,the ensemble empirical mode decomposition(EEMD)is used to spectrally decompose the vibration signal.Furthermore,the multiscale sample entropy(MSE)is utilized to characterize the complexity of each intrinsic mode function(IMF)at different scales,and the values are used as the feature vector.Finally,the support vector machine(SVM)is used to complete the classification of manufacturing defects.Experimental results show that the detection the proposed method can accurately identify and classify typical manufacturing defects,and provide relevant theoretical and testing base for the online detection of hermetic refrigeration compressors.