To handle the effects of single event upsets（SEU）,which are common to computers in space radiation environment,a new fault-tolerant system with dual-module redundancy is proposed using dynamic reconfigurable techniq...To handle the effects of single event upsets（SEU）,which are common to computers in space radiation environment,a new fault-tolerant system with dual-module redundancy is proposed using dynamic reconfigurable technique of field programmable gate array（FPGA）. This system contains detection and backup alternative functions,that is,the self-detection and self-healing functions can be completed,and consequently a system design with low hardware redundancy and high resource utilization can be achieved successfully. So it can not only detect fault but also repair the fault effectively after failure. Hence,this method is especially practical to the dynamically reconfigurable computers based on FPGAs. Design methodology has been verified by Virtex-4 FPGA on Xilinx Ml403 development platform.展开更多
The soft fault induced by parameter variation is one of the most challenging problems in the domain of fault diagnosis for analog circuits.A new fault location and parameter prediction approach for soft-faults diagnos...The soft fault induced by parameter variation is one of the most challenging problems in the domain of fault diagnosis for analog circuits.A new fault location and parameter prediction approach for soft-faults diagnosis in analog circuits is presented in this paper.The proposed method extracts the original signals from the output terminals of the circuits under test（CUT） by a data acquisition board.Firstly,the phase deviation value between fault-free and faulty conditions is obtained by fitting the sampling sequence with a sine curve.Secondly,the sampling sequence is organized into a square matrix and the spectral radius of this matrix is obtained.Thirdly,the smallest error of the spectral radius and the corresponding component value are obtained through comparing the spectral radius and phase deviation value with the trend curves of them,respectively,which are calculated from the simulation data.Finally,the fault location is completed by using the smallest error,and the corresponding component value is the parameter identification result.Both simulated and experimental results show the effectiveness of the proposed approach.It is particularly suitable for the fault location and parameter identification for analog integrated circuits.展开更多
The central limit theorem guarantees the distribution of the measurand is Gaussian when the number of repeated measurement is infinity, but in many practical cases, the number of measurement times is limited to a give...The central limit theorem guarantees the distribution of the measurand is Gaussian when the number of repeated measurement is infinity, but in many practical cases, the number of measurement times is limited to a given number. To overcome this contradiction, this paper firstly carries out the maximum likelihood estimation for parameter q in qGaussian density model developed under the maximum Tsallis entropy principle. Then the q-Gaussian probability density function is used in the particle filter to estimate and measure the nonlinear system. The estimated parameter q is related to the ratio between the measurement variance and the given variance, which indicates that the measurement accuracy cannot be improved if we only increase the repeated measurement times. Via using the proposed q-Gaussian density model,the measurement error（the average mean square error）of the estimation results can be reduced to a considerable level where the number of repeated measurement is limited. The experimental example is given to verify the proposed model and the measurement results prove the correctness and effectiveness of it.展开更多
基金supported by the National Natural Science Foundation of China under Grant No. 60971036the National High Technology Research and Development Program of China under Grant No. 2008AA01Z104+1 种基金the Fundamental Research Funds for the Central Universities under Grant No. ZYGX2009Z004the New Century Excellent Talents in University under Grant No. NCET-08-0087
文摘To handle the effects of single event upsets（SEU）,which are common to computers in space radiation environment,a new fault-tolerant system with dual-module redundancy is proposed using dynamic reconfigurable technique of field programmable gate array（FPGA）. This system contains detection and backup alternative functions,that is,the self-detection and self-healing functions can be completed,and consequently a system design with low hardware redundancy and high resource utilization can be achieved successfully. So it can not only detect fault but also repair the fault effectively after failure. Hence,this method is especially practical to the dynamically reconfigurable computers based on FPGAs. Design methodology has been verified by Virtex-4 FPGA on Xilinx Ml403 development platform.
基金supported by the National Natural Science Foundation of China under Grant No.61371049
文摘The soft fault induced by parameter variation is one of the most challenging problems in the domain of fault diagnosis for analog circuits.A new fault location and parameter prediction approach for soft-faults diagnosis in analog circuits is presented in this paper.The proposed method extracts the original signals from the output terminals of the circuits under test（CUT） by a data acquisition board.Firstly,the phase deviation value between fault-free and faulty conditions is obtained by fitting the sampling sequence with a sine curve.Secondly,the sampling sequence is organized into a square matrix and the spectral radius of this matrix is obtained.Thirdly,the smallest error of the spectral radius and the corresponding component value are obtained through comparing the spectral radius and phase deviation value with the trend curves of them,respectively,which are calculated from the simulation data.Finally,the fault location is completed by using the smallest error,and the corresponding component value is the parameter identification result.Both simulated and experimental results show the effectiveness of the proposed approach.It is particularly suitable for the fault location and parameter identification for analog integrated circuits.
基金supported by the National Natural Science Foundation of China under Grant No.60871056 and No.61371049the specialized Research Fund for the Doctoral Program of High Education of China under Grant No.20120185110013+2 种基金the Fundamental Research Funds for the Central Universities under Grant No.267ZYGX2015KYQD021Sichuan Province Applied Basis Research Project under Grant No.2013JY0058the Key Lab Fund Project of Key Laboratory of Fluid and Power Machinery of Ministry of Education under Grant No.SZJJ2012-042
文摘The central limit theorem guarantees the distribution of the measurand is Gaussian when the number of repeated measurement is infinity, but in many practical cases, the number of measurement times is limited to a given number. To overcome this contradiction, this paper firstly carries out the maximum likelihood estimation for parameter q in qGaussian density model developed under the maximum Tsallis entropy principle. Then the q-Gaussian probability density function is used in the particle filter to estimate and measure the nonlinear system. The estimated parameter q is related to the ratio between the measurement variance and the given variance, which indicates that the measurement accuracy cannot be improved if we only increase the repeated measurement times. Via using the proposed q-Gaussian density model,the measurement error（the average mean square error）of the estimation results can be reduced to a considerable level where the number of repeated measurement is limited. The experimental example is given to verify the proposed model and the measurement results prove the correctness and effectiveness of it.
