一类设备故障过程的故障趋势预测方法研究

研究了一类带有指数故障过程的故障趋势预测问题。在测量变量受到平稳噪声干扰的情况下,首先依据对测量数据的统计检验判断出故障过程,然后根据对故障过程的先验知识,利用强跟踪滤波器辨识指数趋势项的参数,同时对建模误差进行ARMA时序分析,最后结合趋势项和时序预测给出故障趋势的总体预测。仿真实验结果验证了该方法的有效性。

Study on a Fault Trend Prediction Method for a Class of Device Fault Processes

A fault trend prediction problem for a class of exponential fault process is studied.Under the condition that the measure variable is disturbed by a stationary noise,the fault process is detected by statistical analysis of the measurement firstly.According to the model assumption,the parameters of the fault trend process can be obtained by using STF(strong tracing filter).After the extraction of trend component,the modeling error series becomes a stationary series,which can be used for normal ARMA time series analysis.Finally,the whole prediction can be acquired by combining trend prediction and time series analysis.Computer simulations validate the effectiveness of the proposed method.