偏最小二乘法在系统故障诊断中的应用

为研究结合关键性能指标（KPI）的偏最小二乘法（PLS）在系统故障诊断中的作用和应用,通过活性污泥数学模型（BSM1）,结合偏最小二乘算法,建立了可以模拟污水处理的仿真模型. 通过收集系统在正常情况下的输入和输出并建立关系矩阵,做到在实际应用时仅通过输入就可以判断是否出现故障. 利用仿真模型,通过改变天气、输入、先验知识的条件,并通过在仿真系统中加入可手动触发的乘法系数来模拟故障,可以验证偏最小二乘法在系统故障诊断中的表现. 研究结果表明:偏最小二乘法具有判断故障发生位置的功能. 这种功能的灵敏度和准确性可以通过结合关键性能指标而获得提升,故障诊断的灵敏度与准确性受到模型中模拟的天气因素以及算法中的先验知识的影响.

Application of PLS in system fault diagnosis

In order to study the function and application of partial least squares (PLS) combined with key performance indicators (KPI) in system fault diagnosis, a simulation model was established to simulate wastewater treatment based on the mathematical model of activated sludge (BSM1) and combined with PLS. By collecting the input and output of the system under normal conditions and establishing a relationship matrix, the determination of whether a fault occurs in actual application could be achieved simply by input. Based on the simulation model, the performance of PLS in system fault diagnosis could be verified through changing the conditions of weather, input, and prior knowledge, as well as introducing a multiplication coefficient which can be manually triggered to the simulation system to simulate the fault. Results show that the PLS method had the function of judging the location of the fault, and the sensitivity and accuracy of the function could be improved by combining with KPI. The sensitivity and accuracy of fault diagnosis were affected by the weather factors simulated in the model and the prior knowledge in the algorithm.