基于提升小波-SVD差分谱的煤机设备故障诊断  

Fault Diagnosis of Coal Mining Equipment Based on Lifting Wavelet-SVD Difference Spectrum

作　　者：李臻 Li Zhen(Beijing Branch,Tiandi(Changzhou)Automation Co.,Ltd.,China Coal Technology and Engineering Group,Beijing 100028,China)

机构地区：[1]中煤科工集团天地(常州)自动化股份有限公司北京分公司,北京100028

出　　处：《煤矿机械》2024年第10期169-173,共5页Coal Mine Machinery

基　　金：天地(常州)自动化股份有限公司项目(2023GY0001;2024GY0012)。

摘　　要：针对煤机设备微弱故障特征识别困难的问题,提出了提升小波和奇异值分解(SVD)差分谱融合特征提取策略。对煤机设备的振动信号做提升小波分解得到若干个细节信号,利用这些细节信号分别构建Hankel矩阵,并根据实践经验确定Hankel矩阵的行数和列数。利用SVD对每一个Hankel矩阵做正交化分解得到奇异值序列,使用SVD差分谱选择奇异值进行SVD重构,再利用Hilbert解调方法对重构后的信号进行解调,实现煤机设备故障特征的提取。对煤矿现场的电机振动信号进行分析,结果表明,该方法对煤机设备微弱故障特征提取具有良好的效果。Aiming at the difficulty in identifying the weak fault features of coal mining equipment,a feature extraction strategy based on lifting wavelet and singular value decomposition(SVD)difference spectrum fusion was proposed.A series of detailed signals were obtained by lifting wavelet decomposition of vibration signals of coal mining equipment,and Hankel matrices were constructed by using these detailed signals respectively.Based on practical experience,the number of rows and columns of the Hankel matrix has been determined.Singular values were obtained by orthogonal decomposition of each Hankel matrix through SVD.Used SVD difference spectrum to select singular values for SVD reconstruction.Then the reconstructed signal was demodulated by Hilbert demodulation method,and the fault characteristics of coal mining equipment were extracted.The vibration signal of motor in coal mine site was analyzed.The results show that this method has a good effect on extracting weak fault features of coal mining equipment.

关 键 词：提升小波 SVD 煤机设备 故障诊断 

分 类 号：TD407[矿业工程—矿山机电]