Monitoring and fault diagnosis system of wind-solar hybrid power station based on ZigBee and BP neural network

被引：4
|
作者：
Lu Yan [1 ]
Shen Jianwei [2 ]
机构：
[1] Quzhou Coll Technol, Dept Informat Engn, Qu Zhou, Peoples R China
[2] Zhejiang Switchgear Factory Co Ltd, High Voltage Apparat Res Inst, Quzhou, Peoples R China
来源：
AUSTRALIAN JOURNAL OF MECHANICAL ENGINEERING | 2018年 / 16卷
关键词：
ZigBee; cloud hosting; neural network;
D O I：
10.1080/1448837X.2018.1545473
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
The integration of real-time monitoring datas of wind-solar hybrid power stations was not high, and a design plan for monitoring system based on ZigBee and B/S architecture was proposed. The data acquisition module was based; a network centre based on B/S architecture was constructed with cloud hosting to process information uploaded and provide services for users through browser or WeChat. At the same time, the BP neural network was used to extract and analyse the fault data and fault type. It was verified by experiments that the system was highly automated with stable and reliable data transmission.
引用
收藏
页码：54 / 60
页数：7
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