An on-line fault diagnosis method for power electronic drives

2011 ◽  
Author(s):  
Jason M. Anderson ◽  
Robert W. Cox ◽  
Jukkrit Noppakunkajorn
Keyword(s):  
Fault Diagnosis ◽  
Power Electronic ◽  
Diagnosis Method ◽  
On Line

Remote Fault Diagnosis System for Marine Power Machinery System

2013 ◽  
pp. 292-311
Author(s):  
Chengqing Yuan ◽  
Xinping Yan ◽  
Zhixiong Li ◽  
Yuelei Zhang ◽  
Chenxing Sheng ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Heavy Load ◽  
Diagnosis System ◽  
Power Machinery ◽  
Diagnosis Method ◽  
On Line ◽  
Identification Approach ◽  
Fault Diagnosis System ◽  
Machinery System ◽  
Remote Fault Diagnosis

Marine power machinery parts are key equipments in ships. Ships always work in rigorous conditions such as offshore, heavy load, et cetera. Therefore, the failures in marine power machinery would badly threaten the safety of voyages. Keeping marine power machineries running reliably is the guarantee of voyage safety. For the condition monitoring and fault diagnosis of marine power machinery system, this study established the systemic condition identification approach for the tribo-system of marine power machinery and developed integrated diagnosis method by combining on-line and off-line ways for marine power machinery. Lastly, the remote fault diagnosis system was developed for practical application in marine power machinery, which consists of monitoring system in the ship, diagnosis system in laboratory centre, and maintenance management & maintenance decision support system.

Remote Fault Diagnosis System for Marine Power Machinery System

Data Mining ◽  
2013 ◽  
pp. 2174-2192
Author(s):  
Chengqing Yuan ◽  
Xinping Yan ◽  
Zhixiong Li ◽  
Yuelei Zhang ◽  
Chenxing Sheng ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Heavy Load ◽  
Diagnosis System ◽  
Power Machinery ◽  
Diagnosis Method ◽  
On Line ◽  
Identification Approach ◽  
Fault Diagnosis System ◽  
Machinery System ◽  
Remote Fault Diagnosis

Marine power machinery parts are key equipments in ships. Ships always work in rigorous conditions such as offshore, heavy load, et cetera. Therefore, the failures in marine power machinery would badly threaten the safety of voyages. Keeping marine power machineries running reliably is the guarantee of voyage safety. For the condition monitoring and fault diagnosis of marine power machinery system, this study established the systemic condition identification approach for the tribo-system of marine power machinery and developed integrated diagnosis method by combining on-line and off-line ways for marine power machinery. Lastly, the remote fault diagnosis system was developed for practical application in marine power machinery, which consists of monitoring system in the ship, diagnosis system in laboratory centre, and maintenance management & maintenance decision support system.

On-line hybrid fault diagnosis method for high voltage circuit breaker

2017 ◽  
Vol 33 (5) ◽  
pp. 2763-2774 ◽  
Author(s):  
Mei Fei ◽  
Pan Yi ◽  
Zhu Kedong ◽  
Zheng Jianyong
Keyword(s):  
Fault Diagnosis ◽  
High Voltage ◽  
Circuit Breaker ◽  
High Voltage Circuit Breaker ◽  
Diagnosis Method ◽  
On Line

scholarly journals Fault Diagnosis Method of Power Electronic Converter Based on Broad Learning

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Ran Han ◽  
Rongjie Wang ◽  
Guangmiao Zeng
Keyword(s):  
Fault Diagnosis ◽  
Learning System ◽  
Power Electronic ◽  
Fault Type ◽  
Fault Features ◽  
Three Phase ◽  
Power Electronic Circuits ◽  
Bridge Rectifier ◽  
Diagnosis Method ◽  
Sparse Autoencoder

In order to realize the unsupervised extraction and identification of fault features in power electronic circuits, we proposed a fault diagnosis method based on sparse autoencoder (SAE) and broad learning system (BLS). Firstly, the feature is extracted by the sparse autoencoder, and the fault samples and feature vectors are combined as the input of the broad learning system. The broad learning system is trained based on the error precision step update method, and the system is used to the fault type identification. The simulation results of the thyristor fault diagnosis of the three-phase bridge rectifier circuit show that the method is effective and has better performance than other traditional methods.

Sign in / Sign up

Export Citation Format

Share Document