高灵敏度电子地震预警器故障检测方法研究

传统基于时间序列数据挖掘的故障检测方法,缺少高灵敏度电子地震预警器灵敏度分析,故障检测率低。提出新的高灵敏度电子地震预警器故障检测方法,根据高灵敏度电子地震预警器的结构,采用质量块、铰链和延长梁构建其力学模型,得到电子预警器的灵敏度表达式,根据该表达式建立多信号模型相关矩阵,得到故障优先概率的故障源耗费,采用基于故障模式故障概率的改进多信号模型检测方法（包括故障模式概率均分法和故障模式概率优先法）,计算得到电子地震预警器故障概率表达式,实现电子地震预警器故障检测。实验结果表明,所提方法对电子地震预警器TE过程中G和I两个指标的故障检测率分别为0.989、0.905,对PL过程的故障检测时刻为180 s、故障检测率为0.412 8,都高于传统基于时间序列数据挖掘的故障检测方法,说明所提方法具有较高的故障检测性能。

A NewFault Detection Method for High-sensitivity Electronic Early-warning Device

The traditional fault detection method based on time-series data mining cannot perform sensitivity analyses of the high-sensitivity electronic earthquake early-warning device, and its fault detection rate is low. In this paper, we propose a new fault detection method for the high-sensitivity electronic earthquake warning device. Based on the device structure, we constructed a mechanical model using a mass block, hinge, and extended beam to obtain the sensitivity expression of the device. According to this expression, we established a multi-signal model correlation matrix, and obtained the fault source cost of the fault preemption probability. We adopted an improved multi-signal model detection method based on the fault probability of the fault mode in detecting faults of the electronic earthquake warning device. The experimental results show that the fault detection rates of the two indicators G and I in the TE process of the electronic earthquake warning device are 0.989 and 0.905, respectively, the fault detection time of the PL process is 180 s, and the fault detection rate is 0.412 8. These values are all higher than those obtained by the traditional fault detection method based on time-series data mining, which shows that the proposed method has higher fault detection performance.