JIPS (한국정보처리학회)
Current Result Document :
| 한글제목(Korean Title) |
Remote Fault Diagnosis Method of Wind Power Generation E quipment Based on Internet of Things |
| 영문제목(English Title) |
Remote Fault Diagnosis Method of Wind Power Generation E quipment Based on Internet of Things |
| 저자(Author) |
Bing Chen
Ding Liu
|
| 원문수록처(Citation) |
VOL 18 NO. 06 PP. 0822 ~ 0829 (2022. 12) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
According to existing study into the remote fault diagnosis procedure, the current diagnostic approach has an imperfect decision model, which only supports communication in a close distance. An Internet of Things (IoT)-based remote fault diagnostic approach for wind power equipment is created to address this issue and expand the communication distance of fault diagnosis. Specifically, a decision model for active power coordination is built with the mechanical energy storage of power generation equipment with a remote diagnosis mode set by decision tree algorithms. These models help calculate the failure frequency of bearings in power generation equipment, summarize the characteristics of failure types and detect the operation status of wind power equipment through IoT. In addition, they can also generate the point inspection data and evaluate the equipment status. The findings demonstrate that the average communication distances of the designed remote diagnosis method and the other two remote diagnosis methods are 587.46 m, 435.61 m, and 454.32 m, respectively, indicating its application value. |
| 키워드(Keyword) |
Decision Tree Algorithm
Diagnostic Methods
Equipment Failure
Internet of Things
Remote Detection
Wind Power
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| 파일첨부 |
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