基于新陈代谢组合模型的装备故障预测  

Analysis of Equipment Fault Prediction Based on the Metabolism Combined Model

作　　者：邵延君[1] 潘宏侠[1] 马春茂[2] 刘永姜[1] 

机构地区：[1]中北大学机械工程与自动化学院,太原030051 [2]西北机电工程研究所,咸阳712099

出　　处：《振动．测试与诊断》2015年第2期359-362,403,共4页Journal of Vibration,Measurement & Diagnosis

基　　金：国家自然科学基金资助项目(51175480);山西省自然科学基金资助项目(2012011046-12;2013011024-5)

摘　　要：针对武器装备故障预测的难点,在灰色GM(1,1)模型和线性回归模型的基础上结合有效度原理建立新的组合模型,该模型是两种模型的拟合。通过对等时距测量的原始数据进行模拟和预测,来估计系统何时达到故障数据的上限,依此来推断系统的故障时间,同时引入新陈代谢法来提高此种方法的预测精度。最后以某型雷达发射机的输出电压数据为例,验证此种模型在故障预测中的有效性和实用性。Aimed at the difficulty in equipment fault prediction,a new model has been established based on the Grey GM(1,1)model and LRM combined with principles of validity.It is used to estimate when the system reaches the upper limit of the failure data by simulating and predicting the original data of the equivalent interval measurement,and to infer the system failure time according to the results.At the same time,the metabolic method is introduced to improve the prediction accuracy.Finally,the output voltage of a certain type of radar transmitter data is taken as an example to verify the effectiveness and practicality of the model in failure prediction.

关 键 词：灰色线性回归组合模型 故障预测 新陈代谢模型 有效度 

分 类 号：TH318[机械工程—机械制造及自动化]