降雨量传感器的故障诊断方法研究

降雨量的测量对气象预报及防汛减灾具有重要作用,因此当降雨量传感器发生故障时需要能快速修复。而目前应用最广泛的翻斗式降雨量传感器其故障类型多样,致使故障诊断难度大。为此,本文提出一种基于故障树理论与灰色关联法的降雨量传感器故障诊断新方法,采用故障树理论及灰色关联分析法建立了专家系统,通过故障知识获取、故障树建立、灰色关联度获取、知识库构建和推理机推理设计,实现了降雨量传感器的故障诊断。试验验证表明,该方法故障诊断快速准确,实现系统自动诊断替代人工检测与排查,准确率可达到90%以上,提高了降雨量传感器的诊断与维修效率。

Research on Fault Diagnosis Method of Rain Sensor

The measurement of precipitation plays an important role in meteorological forecast and flood control and disaster reduction.When the rain sensor fails,it needs to be quickly repaired.At present,the cup rain sensor which is the most widely used has various types of failures,making it difficult to diagnose faults.Therefore,a rain sensor fault diagnosis method based on fault tree theory and grey correlation method has been developed.And an expert system is established by fault tree theory and grey relational analysis,through fault knowledge acquisition,fault number establishment,grey correlation degree acquisition,knowledge base construction and inference engine reasoning design,and a rain sensor fault diagnosis method has been designed.The test verification shows that the method fault diagnosis is fast and accurate,which improves the efficiency diagnosis and maintenance for the rain sensor.