基于主元分析的推焦车液压系统泄漏监测  

Application of Principal Component Analysis to Diagnose Oil Leakage in Coke Pusher Hydraulic System

作　　者：李文武[1] 赵艳会[1] 邹俊[2] 傅新[2] 杨华勇[2] 

机构地区：[1]上海宝钢股份公司,上海201901 [2]浙江大学流体传动及控制国家重点实验室,杭州310027

出　　处：《机床与液压》2008年第4期199-201,共3页Machine Tool & Hydraulics

基　　金：国家自然科学基金资助项目(50575200)

摘　　要：主元分析(PCA)是一种利用数据之间相依性建立系统低维模型的方法,该方法将高度相关的过程数据投影到低维空间,并保留原有的有用信息。本文将主元分析方法引入到液压系统的泄漏检测中,与传统的故障检测方法相比,主元分析方法采用HotellingT2和Q统计作为故障检测的依据,具有不依赖过程数学模型的特点。基于多维数据驱动的PCA方法,建立液压泄漏监测装置,并将该装置应用到宝钢二期煤焦推焦机液压系统当中,结果表明泄漏监测系统能够及时、准确地发现系统泄漏故障。Principal component analysis,which projects sampling data to low-dimension spaces and preserves useful information,is a method to establish low-dimension models based on mutual dependency of sampling data.The Hotelling T^2 and Q statistics were used as rules for fault diagnosis in PCA-based method.Compared with model-based approach,it is simple and straight-forward.Based on data-driven PCA method,an oil leakage monitoring device was developed.The good performance of the leakage monitoring device was verified by the application of door-drawing hydraulic system in Baosteel coke pusher No.2.The results show the oil leakage fault can be detected timely and rightly.

关 键 词：主元分析 故障监测 取门液压系统 油液泄漏 

分 类 号：TH137[机械工程—机械制造及自动化]