Fault diagnosis of Elevator Door Machines Based on Deep Convolutional Forest
Author:
Affiliation:
1. Guangdong University of Technology,Guangdong Provincial Key Laboratory of Cyber-Physical System,Guangzhou,China
Funder
Natural Science Foundation of Guangdong Province
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9911058/9911059/09911098.pdf?arnumber=9911098
Reference21 articles.
1. Transmissibility function-based fault diagnosis methods for beam-like engineering structures: a review of theory and properties
2. A fuzzy system of operation safety assessment using multi-model linkage and multi-stage collaboration for in-wheel motor;xue;IEEE Transactions on Fuzzy Systems,2021
3. A novel sparse feature extraction method based on sparse signal via dual-channel self-adaptive TQWT;junlin;Chinese Journal of Aeronautics,2021
4. Autocorrelation Aided Random Forest Classifier-Based Bearing Fault Detection Framework
5. Fault Diagnosis of a Rolling Bearing Using Wavelet Packet Denoising and Random Forests
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Research on Distributed Fault Diagnosis Model of Elevator Based on PCA-LSTM;Algorithms;2024-06-07
2. Application of Parity Relation in Elevator Fault Diagnosis;2023 35th Chinese Control and Decision Conference (CCDC);2023-05-20
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