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Fault Diagnosis for Manifold Absolute Pressure Sensor(MAP) of Diesel Engine Based on Elman Neural Network Observer 被引量:17
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作者 WANG Yingmin ZHANG Fujun +1 位作者 CUI Tao ZHOU Jinlong 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2016年第2期386-395,共10页
Intake system of diesel engine is a strong nonlinear system, and it is difficult to establish accurate model of intake system; and bias fault and precision degradation fault of MAP of diesel engine can't be diagnosed... Intake system of diesel engine is a strong nonlinear system, and it is difficult to establish accurate model of intake system; and bias fault and precision degradation fault of MAP of diesel engine can't be diagnosed easily using model-based methods. Thus, a fault diagnosis method based on Elman neural network observer is proposed. By comparing simulation results of intake pressure based on BP network and Elman neural network, lower sampling error magnitude is gained using Elman neural network, and the error is less volatile. Forecast accuracy is between 0.015?0.017 5 and sample error is controlled within 0?0.07. Considering the output stability and complexity of solving comprehensively, Elman neural network with a single hidden layer and with 44 nodes is presented as intake system observer. By comparing the relations of confidence intervals of the residual value between the measured and predicted values, error variance and failures in various fault types. Then four typical MAP faults of diesel engine can be diagnosed: complete failure fault, bias fault, precision degradation fault and drift fault. The simulation results show: intake pressure is observable and selection of diagnostic strategy parameter reasonably can increase the accuracy of diagnosis;the proposed fault diagnosis method only depends on data and structural parameters of observer, not depends on the nonlinear model of air intake system. A fault diagnosis method is proposed not depending system model to observe intake pressure, and bias fault and precision degradation fault of MAP of diesel engine can be diagnosed based on residuals. 展开更多
关键词 neural network diesel engine intake system fault diagnosis threshold value
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The future is frozen:cryogenic CMOS for high-performance computing
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作者 R.Saligram A.Raychowdhury Suman Datta 《Chip》 EI 2024年第1期43-54,共12页
Low temperature complementary metal oxide semiconductor(CMOS)or cryogenic CMOS is a promising avenue for the continuation of Moore’s law while serving the needs of high performance computing.With temperature as a con... Low temperature complementary metal oxide semiconductor(CMOS)or cryogenic CMOS is a promising avenue for the continuation of Moore’s law while serving the needs of high performance computing.With temperature as a control“knob”to steepen the subthreshold slope behavior of CMOS devices,the supply voltage of operation can be reduced with no impact on operating speed.With the optimal threshold voltage engineering,the device ON current can be further enhanced,translating to higher performance.In this article,the experimentally calibrated data was adopted to tune the threshold voltage and investigated the power performance area of cryogenic CMOS at device,circuit and system level.We also presented results from measurement and analysis of functional memory chips fabricated in 28 nm bulk CMOS and 22 nm fully depleted silicon on insulator(FDSOI)operating at cryogenic temperature.Finally,the challenges and opportunities in the further development and deployment of such systems were discussed. 展开更多
关键词 Cryogenic CMOS Design technology co-optimization High performance computing Parameter variation threshold voltage engineering Cryogenic Memories Interconnects
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