Sensor Fault Diagnosis Based on Improved Dynamic Structured Residual Approach in Dynamic Processes
ICICTA), 2010 International Conference（2010）
摘要
A new sensor faults diagnosis method based on improved dynamic structured residual approach with maximized sensitivity (DSRAMS) is proposed for dynamic processes monitoring in this paper. The dynamic principal component analysis (DPCA) method is employed for system identification and model reduction. Extended incidence matrix is proposed to diagnosis the dynamical systems where one sensor fault will affect multiple elements of the measurement vector. Sensor faults sensitivity and critical sensitivity are defined, based on which an incidence matrix optimization algorithm is proposed. Simulation results in a dynamic process show the effectiveness of the proposed method.
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关键词
process monitoring,sensitivity,sensor fault,dynamic processes,dynamic structured residual approach,dynamical system,dynamic principal component analysis,system identification,sensor faults sensitivity,sensor fault diagnosis,matrix algebra,new sensor faults diagnosis,fault diagnosis,improved dynamic structured residual,extended incidence matrix,sensor fault sensitivity,dynamic structured residual approach with maximized sensitivity,dynamic process,sensors,structured residual approach,critical sensitivity,principal component analysis,dynamic process monitoring,dynamical processes monitoring,model reduction,incidence matrix optimization,maximized sensitivity,incidence matrix,intelligent sensors,noise,information technology,testing,control engineering,fault detection,dynamic system,covariance matrix
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