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作 者:王明分 WANG Mingfen(Shandong University of Engineering and Vocational Technology,Jinan 250200,Shandong,China)
出 处:《流体测量与控制》2023年第5期29-32,36,共5页Fluid Measurement & Control
基 金:教育部产学合作协同育人项目(221000821125005)。
摘 要:为了避免机械设备出现非常规运行状态,其表现出的故障信号特征能够被准确提取,提出了基于改进小波包变换的机械设备故障信号捕捉的方法。通过定义小波包性质的方式,对机械设备故障信号实施分解处理,完成基于改进小波包变换故障特征的提取。在此基础上,计算机械设备的故障特征熵值结果,根据单值特征参数的实时数值水平,定义特征值捕获区间的范围,完成基于改进小波包变换的机械设备故障信号捕捉方法的设计与应用。实验结果表明,在改进小波包变换原理的作用下,既定机械设备元件在运行过程中表现出的奇异值水平明显降低,对故障信号特征的准确捕获与提取起到较强的促进性作用。In order to avoid the unconventional operation state of mechanical equipment and make the fault signal characteristics can be accurately extracted,the fault signal capture method of mechanical equipment based on improved wavelet packet transformation is proposed.By defining the nature of wavelet packet,it decomposed the mechanical fault signals and extracted the fault features based on the improved wavelet packet transformation.On this basis,the fault feature entropy result of mechanical equipment is calculated,the range of feature value capture interval is defined according to the real-time numerical level of single value feature parameter,and the design and application of mechanical equipment fault signal capture method based on improved wavelet packet transformation are completed.The experimental results show that under the improvement of the wavelet packet transformation principle,the singular value level of the established mechanical equipment elements is significantly reduced,which plays a strong role in promoting the accurate capture and extraction of fault signal features.
分 类 号:TH165[机械工程—机械制造及自动化]
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