A statistical signal processing technique was proposed and verified as independent component analysis(ICA) for fault detection and diagnosis of industrial systems without exact and detailed model.Actually,the aim is t...A statistical signal processing technique was proposed and verified as independent component analysis(ICA) for fault detection and diagnosis of industrial systems without exact and detailed model.Actually,the aim is to utilize system as a black box.The system studied is condenser system of one of MAPNA's power plants.At first,principal component analysis(PCA) approach was applied to reduce the dimensionality of the real acquired data set and to identify the essential and useful ones.Then,the fault sources were diagnosed by ICA technique.The results show that ICA approach is valid and effective for faults detection and diagnosis even in noisy states,and it can distinguish main factors of abnormality among many diverse parts of a power plant's condenser system.This selectivity problem is left unsolved in many plants,because the main factors often become unnoticed by fault expansion through other parts of the plants.展开更多
Although envelope spectrum does not involve complicated sideband,thus has a much simpler structure than the common Fourier spectrum,it is still subject to the efect of planets passing or time variant vibration transfe...Although envelope spectrum does not involve complicated sideband,thus has a much simpler structure than the common Fourier spectrum,it is still subject to the efect of planets passing or time variant vibration transfer pams.The presence of planets passing frequency,sun gear rotating frequency,or planet carrier rotating frequency in the envelope spectrum may confuse the analysis in fault diagnosis.Therefore,it is important to look for an approach to remove the interferences caused by the efect of planets passing or time variant vibration transfer paths.展开更多
基金Project(217/s/458)supported by Azarbaijan Shahid Madani University,Iran
文摘A statistical signal processing technique was proposed and verified as independent component analysis(ICA) for fault detection and diagnosis of industrial systems without exact and detailed model.Actually,the aim is to utilize system as a black box.The system studied is condenser system of one of MAPNA's power plants.At first,principal component analysis(PCA) approach was applied to reduce the dimensionality of the real acquired data set and to identify the essential and useful ones.Then,the fault sources were diagnosed by ICA technique.The results show that ICA approach is valid and effective for faults detection and diagnosis even in noisy states,and it can distinguish main factors of abnormality among many diverse parts of a power plant's condenser system.This selectivity problem is left unsolved in many plants,because the main factors often become unnoticed by fault expansion through other parts of the plants.
文摘Although envelope spectrum does not involve complicated sideband,thus has a much simpler structure than the common Fourier spectrum,it is still subject to the efect of planets passing or time variant vibration transfer pams.The presence of planets passing frequency,sun gear rotating frequency,or planet carrier rotating frequency in the envelope spectrum may confuse the analysis in fault diagnosis.Therefore,it is important to look for an approach to remove the interferences caused by the efect of planets passing or time variant vibration transfer paths.
