中国机械工程2024，Vol.35Issue(1)：125-135,11.DOI:10.3969/j.issn.1004-132X.2024.01.012
仿真数据驱动的长期服役电梯导轨故障迁移诊断方法
Simulation Data-driven Migration Diagnosis Method for Guide Rail Faults in Long-term Service Elevators
摘要
Abstract
The existing researches of fault diagnosis of elevator guide rails has some problems,such as scarcity of horizontal vibration classification data and large difference in the distribution of training and test data sets.A simulation data-driven fault migration diagnosis method for long-term service elevator guide rails was proposed.Firstly,the horizontal dynamics model of the elevator car was constructed,different types of guide rail fault excitations as system input for simulation and rich horizontal abnormal vibration data of elevator car were obtained.Secondly,the residual network and convolutional attention mechanism were integrated to extract fault features,and the sub-domain adap-tive method was used to align the conditional distribution of source domain and target domain in unsu-pervised scenarios.Finally,the elevator horizontal vibration data under different working conditions were used as the target domain to verify the proposed method.The experimental results show that the proposed method has high fault diagnosis accuracy in unsupervised cross-domain scenarios,which pro-vides a reference for solving the problems of scarcity of fault data for long-term service elevators.关键词
仿真数据驱动/长期服役电梯/水平振动/子领域自适应/故障诊断Key words
simulation data-driven/long-term service elevator/horizontal vibration/subdomain adaptation/fault diagnosis分类
机械制造引用本文复制引用
肖刚,顾海瑞,董锦锦,王琪冰,陆佳炜..仿真数据驱动的长期服役电梯导轨故障迁移诊断方法[J].中国机械工程,2024,35(1):125-135,11.基金项目
国家自然科学基金(61976193) （61976193）
浙江省"尖兵"研发攻关计划(2023C01022) （2023C01022）
湖州市重点研发科技计划(2022ZD2019) （2022ZD2019）
