Street Lamp Fault Diagnosis System Based on Extreme Learning Machine

2nd International Symposium on Application of Materials Science and Energy Materials

材料科学;能源学

Lee, Yanming^1 ; Zhang, Hongyi^1 ; Rosa, Jimmi^2

School of Opto-Electronic and Communication Engineering, Xiamen University of Technology, Xiamen, China^1

School of Engineering and Computer Science, Victoria University of Wellington, New Zealand^2

关键词: Complex event processing;    Detection and diagnosis;    Extreme learning machine;    Fault diagnosis problem;    Fault diagnosis systems;    Large amounts;    Lighting systems;    Response systems;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/490/4/042053/pdf
DOI  :  10.1088/1757-899X/490/4/042053

学科分类：材料科学（综合）

来源: IOP

【 摘 要 】

In view of the construction of urban lighting system needs a lot of manpower deployment, especially for its fault diagnosis problem management. This paper proposes a fault model detection and diagnosis subsystem based on the extreme learning machine for street lamps system. The subsystem is part of the event rule response system which is based on the complex event processing technology framework. The system can handle a large amount of sensor data, perform filtering, carry out complex data processing and decision making. The experimental results show that the proposed street lamp fault diagnosis system based on extreme learning machine can diagnose the street lamp fault effectively and respond to it automatically.