基于递归图和张量分解的故障可诊断性评价方法  

Evaluation Method of Fault Diagnosability Based on Recursive Plot and Tensor Decomposition

作　　者：吕佳朋 史贤俊 聂新华 秦玉峰 龙玉峰 LṺJiapeng;SHI Xianjun;NIE Xinhua;QIN Yufeng;LONG Yufeng(Naval Aviation University,Yantai 264001,Shandong,China)

机构地区：[1]海军航空大学,山东烟台264001

出　　处：《兵工学报》2023年第3期763-772,共10页Acta Armamentarii

摘　　要：可诊断性反映了系统故障诊断的难易程度,对系统进行可诊断性评价是开展故障诊断工作的前提条件。针对可诊断性评价问题,将测点信号考虑在内,提出了一种基于递归图和张量分解的故障可诊断性评价方法。利用相空间重构技术对装备在不同状态下的测点信号进行图形化表示,形成递归图;对递归图进行分析以提取其中的特征,并将该特征视为原信号特征;通过张量分解的方法,计算不同状态下信号特征之间的相似程度,作为故障诊断难易程度的基本度量。通过仿真实验对所提出的方法与仅考虑系统模型的D矩阵的可诊断性评价方法进行对比,结果表明该方法在评价可诊断性方面具有准确性和客观性。Diagnosability reflects the difficulty of diagnosing system faults,so diagnosability evaluation of the system is a prerequisite for fault diagnosis.Taking the signals of test points into consideration,a fault diagnosability evaluation method based on a recurrence plot and tensor decomposition is proposed.The phase space reconstruction technique is used to graphically represent the signals of measured points in different states to form a recurrence plot.Features are extracted through analyzing the recurrence plot,which are then regarded as the original signal features.Through tensor decomposition,the similarity between signal features in different states is calculated as a basic measure of fault diagnosis difficulty.Simulation experiments show that,compared with the previous D-matrix diagnosability evaluation method that only considers the system model,the newly proposed method has effectiveness and objectivity.

关 键 词：可诊断性评价 递归图 张量分解 相空间重构 

分 类 号：TP306[自动化与计算机技术—计算机系统结构]