机电工程技术2024，Vol.53Issue(2)：8-12,5.DOI:10.3969/j.issn.1009-9492.2024.02.002
CWNT时频尺度多步噪声抑制的轴承故障诊断
Bearing Fault Diagnosis of Multi-step Noise Suppression at CWNT Time-frequency Scale
摘要
Abstract
In the actual working conditions,the bearing signal often has different degrees of noise interference,which is not conducive to identify the health state of the bearing,and affects the stability of the fault diagnosis seriously.For the problem of processing noisy signals,a bearing fault diagnosis method for multi-step noise suppression at CWNT time-frequency scale(CWNT)is proposed.The concentrated waveform of continuous wavelet transform(CWT)is captured by the window of variable length;the fault signal from the global perception field is filtered and the time-frequency image features are extracted;the attention mechanism is added to the channel dimension,the normalized weight to the characteristics of each channel are weighted,the complex correlation between channels are fitted to achieve the diagnostic effect of multi-step noise suppression.In order to verify the proposed diagnostic method,gaussian white noise(GWN)of 4.987%,12.538%and 31.650%is added to the Case Western Reserve University bearing data set(CWRU),and the accuracy of the validation set is 97.384%,96.701%and 95.407%,respectively.The results show that CWNT method has strong noise resistance and can improve the accuracy of fault diagnosis in noise background.关键词
故障诊断/连续小波变换/注意力机制/高斯白噪声Key words
fault diagnosis/continuous wavelet transform/attention mechanism/gaussian white noise分类
信息技术与安全科学引用本文复制引用
徐坤,刘征,朱维超,任万凯,蔡木霞..CWNT时频尺度多步噪声抑制的轴承故障诊断[J].机电工程技术,2024,53(2):8-12,5.基金项目
国家自然科学基金面上项目(52175465) （52175465）
