摘要
针对故障预测具有不确定性的特点,本文将模糊数学中的隶属度函数和粒子滤波算法相结合设计故障预测的方法.新方法利用粒子滤波算法对设备运行的未来状态进行预测,再设计描述设备运行状态的正常隶属度函数和异常隶属度函数,利用计算出的未来状态的预测值计算并比较正常和异常隶属度函数值,依据比较结果对潜在故障进行预测.实验验证了该方法的可行性,可及时准确地预测出系统故障.
As fault prediction has the characteristics of uncertainty, we design a method for fault prediction, which combines fuzzy mathematics membership function with particle filter algorithm to predict fault. The new method uses particle filter algorithm to calculate the future state of the device operation, and then designs the normal membership function and the abnormal membership function of the device operation state, calculates and compares the value of the normal and abnormal membership function by using the calculated results and based on the comparison result to predict potential failure. The feasibility of the proposed method is verified by experiments, which can predict the failure of the system in time.
出处
《计算机系统应用》
2016年第6期119-124,共6页
Computer Systems & Applications
基金
福建省自然科学基金(2013J01223)
福建师范大学"网络与信息安全关键理论和技术"校创新团队(IRTL1207)
关键词
正常隶属度
异常隶属度
粒子滤波
故障预测
状态空间模型
normal membership degree
abnormal membership degree
particle filter
fault prediction
state space model
