Abstract: The complex mechanical and electrical equipment has the characteristics includes complex structure,less samples,changeable degradation,which is difficult to make preventive maintenance,so it has great significance to research the performance degradation rules and health status evaluation of the complex electromechanical equipment.By taking the mechanical and electrical equipment as the research object,the Wiener process was used to research the performance degradation modelling and health assessment methods.A Wiener process model was established to describe the single performance degradation,and the Wiener process to the fusion of multi performance Wiener process was put forward to predict the performance degradation parameter in multi performance condition.By using Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method and Mahalanobis distance,the equipment health state space was divided with relative closeness degree,and the performance degradation path was transformed into the healthy state space to realize the complex electromechanical equipment health condition assessment.The experiment was carried out on the test platform for feed system of CNC machine tools,so that the fusion of multi-performance Wiener process analysis and the health state evaluation method were verified.

Key words: performance degradation modelling, health state evaluation, wiener process, technique for order preference by similarity to an ideal solution, mahalanobis distance

摘要： 机电装备具有结构复杂、样本量少、工况多变的特点,对其进行预防性维修十分困难,因此研究其性能退化规律以及健康状态评估对预防性维修具有重要意义。以机电装备为研究对象,利用维纳过程研究性能退化建模与健康状态评估方法。建立了描述单性能退化的维纳过程模型,并给出融合多性能退化的维纳过程模型,得到了多性能退化轨迹,实现了多性能状况下的性能退化预测。利用逼近理想解法和马氏距离,根据相对贴近度划分出装备健康状态空间,并将性能退化轨迹转换到健康状态空间中,实现了对装备健康状态的评估。在数控机床进给系统试验平台上进行实验,验证了融合多性能退化的维纳过程模型和健康状态评估方法的正确性和有效性。

关键词: 性能退化建模, 健康状态评估, 维纳过程, 逼近理想解法, 马氏距离