测控技术2025，Vol.44Issue(5)：35-45,11.DOI:10.19708/j.ckjs.2025.05.303
面向自动化试验产线的旋转机械故障诊断方法
Rotating Machinery Fault Diagnosis Methods for Automated Test Production Lines
谢思映 1梅亮 1罗俊杰1
作者信息
- 1. 航天科工防御技术研究试验中心,北京 100854
- 折叠
摘要
Abstract
In recent years,with the continuous development of the semiconductor industry,the automated test production lines appeared to cope with the phenomenon of the sudden increase in testing tasks.Rotating ma-chinery as the core equipment of the automated test production lines,will inevitably encounter a variety of fail-ures,which may lead to significant losses in production operation.In order to ensure the normal operation of the automated test production lines,it is of great significance to develop a feasible fault diagnosis method for rota-ting machinery.A rotating machinery fault diagnosis method based on dual-channel convolutional neural net-work and bidirectional long and short-term memory network(DCCNN-BiLSTM)is proposed for the common ro-tating machinery in the microelectronic device automated test production lines established by China Aerospace Science & Industry Corp Defense Technology R&T Center,which not only overcomes the problem of underuti-lizing the information of the signal data in traditional algorithms but also can automatically extract the features and diagnose faults from the original signals.That is,without any manual processing on the input original sig-nals,the fault diagnosis can be accomplished directly,which makes it easier and more efficient.关键词
产线/旋转机械/故障诊断/DCCNN/BiLSTMKey words
production line/rotating machinery/fault diagnosis/DCCNN/BiLSTM分类
计算机与自动化引用本文复制引用
谢思映,梅亮,罗俊杰..面向自动化试验产线的旋转机械故障诊断方法[J].测控技术,2025,44(5):35-45,11.
