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
Based on the analysis and comparison of coal, oil and water consumptions in thermal power plants, thispaper introduces the present state of resources utilization in thermal power industry, and points out that the pote...Based on the analysis and comparison of coal, oil and water consumptions in thermal power plants, thispaper introduces the present state of resources utilization in thermal power industry, and points out that the poten-tial of resources saving lies mainly in cutting down coal consumption and increasing the ratio of large-sized thermalunits. Measures and suggestions for upgrading resources utilization are put forward, such as to optimize coal-firedthermal power structure, develop cogeneration, clean coal combustion techniques and gas-steam combined cycletechniques. The existing thermal power plants shall execute technical retrofits and popularize water saving techniques.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Based on the analysis and comparison of coal, oil and water consumptions in thermal power plants, thispaper introduces the present state of resources utilization in thermal power industry, and points out that the poten-tial of resources saving lies mainly in cutting down coal consumption and increasing the ratio of large-sized thermalunits. Measures and suggestions for upgrading resources utilization are put forward, such as to optimize coal-firedthermal power structure, develop cogeneration, clean coal combustion techniques and gas-steam combined cycletechniques. The existing thermal power plants shall execute technical retrofits and popularize water saving techniques.
