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Street Lamp Fault Diagnosis System Based on Extreme Learning Machine

机译:基于极端学习机的路灯故障诊断系统

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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.
机译:鉴于城市照明系统的建设需要大量的人力部署,特别是其故障诊断问题管理。本文提出了基于街道灯系统极端学习机的故障模型检测和诊断子系统。子系统是基于复杂事件处理技术框架的事件规则响应系统的一部分。系统可以处理大量的传感器数据,执行过滤,进行复杂的数据处理和决策。实验结果表明,基于极端学习机的建议路灯故障诊断系统可以有效地诊断路灯故障并自动响应。

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