Complex processes often work with multiple operation regions, it is critical to develop effective monitoring approaches to ensure the safety of chemical processes. In this work, a discriminant local consistency Gaussi...Complex processes often work with multiple operation regions, it is critical to develop effective monitoring approaches to ensure the safety of chemical processes. In this work, a discriminant local consistency Gaussian mixture model(DLCGMM) for multimode process monitoring is proposed for multimode process monitoring by integrating LCGMM with modified local Fisher discriminant analysis(MLFDA). Different from Fisher discriminant analysis(FDA) that aims to discover the global optimal discriminant directions, MLFDA is capable of uncovering multimodality and local structure of the data by exploiting the posterior probabilities of observations within clusters calculated from the results of LCGMM. This may enable MLFDA to capture more meaningful discriminant information hidden in the high-dimensional multimode observations comparing to FDA. Contrary to most existing multimode process monitoring approaches, DLCGMM performs LCGMM and MFLDA iteratively, and the optimal subspaces with multi-Gaussianity and the optimal discriminant projection vectors are simultaneously achieved in the framework of supervised and unsupervised learning. Furthermore, monitoring statistics are established on each cluster that represents a specific operation condition and two global Bayesian inference-based fault monitoring indexes are established by combining with all the monitoring results of all clusters. The efficiency and effectiveness of the proposed method are evaluated through UCI datasets, a simulated multimode model and the Tennessee Eastman benchmark process.展开更多
With respect to sensitivity,selectivity and speed of operation,the current differential scheme is a better way to protect transmission lines than overcurrent and distance-based schemes.However,the protection scheme ca...With respect to sensitivity,selectivity and speed of operation,the current differential scheme is a better way to protect transmission lines than overcurrent and distance-based schemes.However,the protection scheme can be severely influenced by the Line Charging Capacitive Current(LCCC)with increased voltage level and Current Transformer(CT)saturation under external close-in faults.This paper presents a new UHV/EHV current-based protection scheme using the ratio of phasor summation of the two-end currents to the local end current,instead of summation of the two-end currents,to discriminate the internal faults.The accuracy and effectiveness of the proposed protection technique are tested on the 110 kV Western System Coordinating Council(WSCC)9-bus system using PSCAD/MATLAB.The simulation results confirm the reliable operation of the proposed scheme during internal/external faults and its independence from fault location,fault resistance,type of fault,and variations in source impedance.Finally,the effectiveness of the proposed scheme is also verified with faults during power swing and in series compensated lines.展开更多
基金Supported by the National Natural Science Foundation of China(61273167)
文摘Complex processes often work with multiple operation regions, it is critical to develop effective monitoring approaches to ensure the safety of chemical processes. In this work, a discriminant local consistency Gaussian mixture model(DLCGMM) for multimode process monitoring is proposed for multimode process monitoring by integrating LCGMM with modified local Fisher discriminant analysis(MLFDA). Different from Fisher discriminant analysis(FDA) that aims to discover the global optimal discriminant directions, MLFDA is capable of uncovering multimodality and local structure of the data by exploiting the posterior probabilities of observations within clusters calculated from the results of LCGMM. This may enable MLFDA to capture more meaningful discriminant information hidden in the high-dimensional multimode observations comparing to FDA. Contrary to most existing multimode process monitoring approaches, DLCGMM performs LCGMM and MFLDA iteratively, and the optimal subspaces with multi-Gaussianity and the optimal discriminant projection vectors are simultaneously achieved in the framework of supervised and unsupervised learning. Furthermore, monitoring statistics are established on each cluster that represents a specific operation condition and two global Bayesian inference-based fault monitoring indexes are established by combining with all the monitoring results of all clusters. The efficiency and effectiveness of the proposed method are evaluated through UCI datasets, a simulated multimode model and the Tennessee Eastman benchmark process.
文摘With respect to sensitivity,selectivity and speed of operation,the current differential scheme is a better way to protect transmission lines than overcurrent and distance-based schemes.However,the protection scheme can be severely influenced by the Line Charging Capacitive Current(LCCC)with increased voltage level and Current Transformer(CT)saturation under external close-in faults.This paper presents a new UHV/EHV current-based protection scheme using the ratio of phasor summation of the two-end currents to the local end current,instead of summation of the two-end currents,to discriminate the internal faults.The accuracy and effectiveness of the proposed protection technique are tested on the 110 kV Western System Coordinating Council(WSCC)9-bus system using PSCAD/MATLAB.The simulation results confirm the reliable operation of the proposed scheme during internal/external faults and its independence from fault location,fault resistance,type of fault,and variations in source impedance.Finally,the effectiveness of the proposed scheme is also verified with faults during power swing and in series compensated lines.