Fault diagnosis plays an important role in complicated industrial process.It is a challenging task to detect,identify and locate faults quickly and accurately for large-scale process system.To solve the problem,a nove...Fault diagnosis plays an important role in complicated industrial process.It is a challenging task to detect,identify and locate faults quickly and accurately for large-scale process system.To solve the problem,a novel Multi Boost-based integrated ENN(extension neural network) fault diagnosis method is proposed.Fault data of complicated chemical process have some difficult-to-handle characteristics,such as high-dimension,non-linear and non-Gaussian distribution,so we use margin discriminant projection(MDP) algorithm to reduce dimensions and extract main features.Then,the affinity propagation(AP) clustering method is used to select core data and boundary data as training samples to reduce memory consumption and shorten learning time.Afterwards,an integrated ENN classifier based on Multi Boost strategy is constructed to identify fault types.The artificial data sets are tested to verify the effectiveness of the proposed method and make a detailed sensitivity analysis for the key parameters.Finally,a real industrial system—Tennessee Eastman(TE) process is employed to evaluate the performance of the proposed method.And the results show that the proposed method is efficient and capable to diagnose various types of faults in complicated chemical process.展开更多
A short presentation of chemical engineering evolution,as guided by its paradigms,is exposed.The first paradigm–unit operations–has emerged as a necessity of systematization due to the explosion of chemical industri...A short presentation of chemical engineering evolution,as guided by its paradigms,is exposed.The first paradigm–unit operations–has emerged as a necessity of systematization due to the explosion of chemical industrial applications at the end of 19th century.The birth in the late 1950s of the second paradigm–transport phenomena–was the consequence of the need for a deep,scienti fic knowledge of the phenomena that explain what happens inside of unit operations.In the second part of 20th century,the importance of chemical product properties and qualities has become essentially in the market fights.Accordingly,it was required with additional and even new fundamental approaches,and product engineering was recognized as the third paradigm.Nowadays chemical industry,as a huge materials and energy consumer,and with a strong ecological impact,couldn't remain outside of sustainability requirements.The basics of the fourth paradigm–sustainable chemical engineering–are now formulated.展开更多
基金Project (61203021) supported by the National Natural Science Foundation of ChinaProject (2011216011) supported by the Key Science and Technology Program of Liaoning Province,China+1 种基金Project (2013020024) supported by the Natural Science Foundation of Liaoning Province,ChinaProject (LJQ2015061) supported by the Program for Liaoning Excellent Talents in Universities,China
文摘Fault diagnosis plays an important role in complicated industrial process.It is a challenging task to detect,identify and locate faults quickly and accurately for large-scale process system.To solve the problem,a novel Multi Boost-based integrated ENN(extension neural network) fault diagnosis method is proposed.Fault data of complicated chemical process have some difficult-to-handle characteristics,such as high-dimension,non-linear and non-Gaussian distribution,so we use margin discriminant projection(MDP) algorithm to reduce dimensions and extract main features.Then,the affinity propagation(AP) clustering method is used to select core data and boundary data as training samples to reduce memory consumption and shorten learning time.Afterwards,an integrated ENN classifier based on Multi Boost strategy is constructed to identify fault types.The artificial data sets are tested to verify the effectiveness of the proposed method and make a detailed sensitivity analysis for the key parameters.Finally,a real industrial system—Tennessee Eastman(TE) process is employed to evaluate the performance of the proposed method.And the results show that the proposed method is efficient and capable to diagnose various types of faults in complicated chemical process.
文摘A short presentation of chemical engineering evolution,as guided by its paradigms,is exposed.The first paradigm–unit operations–has emerged as a necessity of systematization due to the explosion of chemical industrial applications at the end of 19th century.The birth in the late 1950s of the second paradigm–transport phenomena–was the consequence of the need for a deep,scienti fic knowledge of the phenomena that explain what happens inside of unit operations.In the second part of 20th century,the importance of chemical product properties and qualities has become essentially in the market fights.Accordingly,it was required with additional and even new fundamental approaches,and product engineering was recognized as the third paradigm.Nowadays chemical industry,as a huge materials and energy consumer,and with a strong ecological impact,couldn't remain outside of sustainability requirements.The basics of the fourth paradigm–sustainable chemical engineering–are now formulated.
