兵工自动化2025，Vol.44Issue(1)：15-22,8.DOI:10.7690/bgzdh.2025.01.004
压缩感知在装备故障预测与健康管理中的应用综述
Application of Compressed Sensing in Equipment Fault Prediction and Health Management
许波 1马云飞1
作者信息
- 1. 武警部队士官学校军械系,杭州 311403
- 折叠
摘要
Abstract
Aiming at the problems of high acquisition frequency,heavy load of acquisition system and redundancy of monitoring data in massive condition monitoring data,the limitation of Shannon-Nyquist sampling theorem is broken through by low-dimensional projection of original signals,which greatly alleviates the problem of information overload caused by large data of equipment.Based on the five-layer architecture of PHM,this paper summarizes the existing achievements from the aspects of the concept of compressive sensing(CS)and its application in signal restoration and noise reduction,fault diagnosis,and degradation state identification,points out the existing problems in the existing research,and puts forward the corresponding solutions.This study can provide some reference for the research of compressed sensing.关键词
压缩感知/装备状态监测/数据采集/稀疏表示/故障诊断Key words
compressed sensing/equipment condition monitoring/data acquisition/sparse representation/fault diagnosis分类
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许波,马云飞..压缩感知在装备故障预测与健康管理中的应用综述[J].兵工自动化,2025,44(1):15-22,8.
