机械制造与自动化2024，Vol.53Issue(4)：67-70,105,5.DOI:10.19344/j.cnki.issn1671-5276.2024.04.012
基于自注意机制胶囊网络的行星齿轮箱故障诊断
Fault Diagnosis of Planetary Gearboxes Based on Self-attentive Mechanism Capsule Network
聂松雅 1陈则王 1杨林 1王友仁1
作者信息
- 1. 南京航空航天大学 自动化学院,江苏 南京 211106
- 折叠
摘要
Abstract
A fault diagnosis method based on self-attentive mechanism capsule network is proposed to solve the problems of limited fault data and low diagnosis accuracy for planetary gearboxes in practical engineering.The acquired planetary gearbox vibration signal is directly used as the input to extract primary features through the first wide convolutional layer and filter the high-frequency noise in the input.The self-attentive mechanism is introduced to focus on the key features of the signal.The proposed features are input into the capsule layer to further extract features and achieve fault classification.The proposed method is verified by the data of planetary gearbox experimental platform.The results show that the proposed method can still achieve good diagnostic accuracy with limited samples.关键词
行星齿轮箱/故障诊断/胶囊网络/自注意机制/小样本Key words
planetary gear box/fault diagnosis/capsule network/self-attention mechanism/small sample分类
机械制造引用本文复制引用
聂松雅,陈则王,杨林,王友仁..基于自注意机制胶囊网络的行星齿轮箱故障诊断[J].机械制造与自动化,2024,53(4):67-70,105,5.
