计算机与数字工程2024，Vol.52Issue(2)：512-520,9.DOI:10.3969/j.issn.1672-9722.2024.02.040
基于声学特征与自编码器的机械故障检测方法
Mechanical Fault Detection Method Based on Acoustic Characteristics and Auto-encoder
摘要
Abstract
When detecting mechanical faults in the industry,only a small amount or no fault data will increase the detection difficulty and reduce the detection accuracy.To solve this problem,a mechanical equipment fault detection method is proposed based on the fusion acoustic features and auto-encoder.First,the potential features of the auto-encoder are set to 8,and its network structure is optimized.Then MSE is used as its reconstruction error function.Finally,MFCC and MAF are used as input features re-spectively.The results show that compared with BS,the method proposed in this paper can improve the average AUC and the aver-age pAUC while reducing the number of training,which can be completed better in fault detection tasks.关键词
声学特征/自编码器/故障检测Key words
acoustic characteristics/auto-encoder/fault detection分类
信息技术与安全科学引用本文复制引用
张锦豪,赵月爱..基于声学特征与自编码器的机械故障检测方法[J].计算机与数字工程,2024,52(2):512-520,9.基金项目
国家社会科学基金项目(编号:20BJL080) （编号:20BJL080）
山西省"1331工程"平台项目(编号:PT201818) （编号:PT201818）
山西省重点研发计划项目(编号:201803D121088) （编号:201803D121088）
太原师范学院研究生教育改革研究项目(编号:SYYJSJG-2153)资助. （编号:SYYJSJG-2153）
