Fault diagnostics is an important research area including different techniques.Principal component analysis(PCA)is a linear technique which has been widely used.For nonlinear processes,however,the nonlinear principal ...Fault diagnostics is an important research area including different techniques.Principal component analysis(PCA)is a linear technique which has been widely used.For nonlinear processes,however,the nonlinear principal component analysis(NLPCA)should be applied.In this work,NLPCA based on auto-associative neural network(AANN)was applied to model a chemical process using historical data.First,the residuals generated by the AANN were used for fault detection and then a reconstruction based approach called enhanced AANN(E-AANN)was presented to isolate and reconstruct the faulty sensor simultaneously.The proposed method was implemented on a continuous stirred tank heater(CSTH)and used to detect and isolate two types of faults(drift and offset)for a sensor.The results show that the proposed method can detect,isolate and reconstruct the occurred fault properly.展开更多
文摘传感器作为复杂装备监测系统的关键组成部分,若发生故障会引起误报警,极大影响复杂机械系统状态监测的可靠性。针对该难题,笔者从系统角度出发,提出一种基于去趋势互相关分析(detrended cross-correlation analysis,简称DCCA)和双尺度自编码器(dual auto encoder,简称DAE)的传感器故障检测方法,记作DCCA-DAE。首先,采用DCCA方法建立耦合网络,将数据从欧氏空间扩展到拓扑空间,实现对系统多源多态监测数据蕴含信息的全面表征;其次,构建基于DAE的异常检测方法,消除工况变化对传感器监测序列产生的影响,实现工况复杂变化下的系统传感器故障准确检测;最后,利用某电厂汽轮机组历史数据,验证所提方法的综合性能。结果表明,DCCA-DAE模型特征提取能力强,检测精度显著优于传统支持向量描述和自编码器等方法,在工业场景中传感器故障检测领域具有良好的应用前景。
基金Project(1390/2)supported by Khuzestan Gas Company,Iran
文摘Fault diagnostics is an important research area including different techniques.Principal component analysis(PCA)is a linear technique which has been widely used.For nonlinear processes,however,the nonlinear principal component analysis(NLPCA)should be applied.In this work,NLPCA based on auto-associative neural network(AANN)was applied to model a chemical process using historical data.First,the residuals generated by the AANN were used for fault detection and then a reconstruction based approach called enhanced AANN(E-AANN)was presented to isolate and reconstruct the faulty sensor simultaneously.The proposed method was implemented on a continuous stirred tank heater(CSTH)and used to detect and isolate two types of faults(drift and offset)for a sensor.The results show that the proposed method can detect,isolate and reconstruct the occurred fault properly.
