Walsh-Hadamard transform (WriT) can solve linear error equations on Field F2, and the method can be used to recover the parameters of convolutional code. However, solving the equations with many unknowns needs enorm...Walsh-Hadamard transform (WriT) can solve linear error equations on Field F2, and the method can be used to recover the parameters of convolutional code. However, solving the equations with many unknowns needs enormous computer memory which limits the application of WriT. In order to solve this problem, a method based on segmented WriT is proposed in this paper. The coefficient vector of high dimension is reshaped and two vectors of lower dimension are obtained. Then the WriT is operated and the requirement for computer memory is much reduced. The code rate and the constraint length of convolutional code are detected from the Walsh spectrum. And the check vector is recovered from the peak position. The validity of the method is verified by the simulation result, and the performance is proved to be optimal.展开更多
Blade Tip-Timing(BTT)has been regarded as a promising way of on-line blade vibration monitoring.But blind multi-band BTT vibration reconstruction is a big challenge under variable speeds and under-sampling.In order to...Blade Tip-Timing(BTT)has been regarded as a promising way of on-line blade vibration monitoring.But blind multi-band BTT vibration reconstruction is a big challenge under variable speeds and under-sampling.In order to deal with it,a novel Compressed Sensing(CS)method is proposed based on Multi-Coset Angular Sampling(MCAS)in this paper.First,multi-coset sampling scheme of BTT vibration signals is presented.Then the CS model of BTT vibration signals is derived in order domain.A sufficient condition of the number of BTT sensors is derived for perfect reconstruction and optimal placement of BTT sensors is determined by minimizing the condition number.In the end,numerical simulations are done to validate the proposed method and the performances of four reconstruction algorithms are compared,i.e.,Orthogonal Matching Pursuit(OMP),Multiple Signal Classification(MUSIC),Basis Pursuit Denoising(BPDN)and Modified Focal Underdetermined System Solver(MFOCUSS).Influences of the sensor placement,the number of BTT sensors and measurement noises on the reconstruction performances are also testified.The results demonstrate that the proposed method is feasible and the overall performance of the BPDN algorithm is the best among the four algorithms.Also the reconstruction performance decreases with the accelerations of rotating speed.展开更多
基金supported by the National Natural Science Foundation of China(61072120)
文摘Walsh-Hadamard transform (WriT) can solve linear error equations on Field F2, and the method can be used to recover the parameters of convolutional code. However, solving the equations with many unknowns needs enormous computer memory which limits the application of WriT. In order to solve this problem, a method based on segmented WriT is proposed in this paper. The coefficient vector of high dimension is reshaped and two vectors of lower dimension are obtained. Then the WriT is operated and the requirement for computer memory is much reduced. The code rate and the constraint length of convolutional code are detected from the Walsh spectrum. And the check vector is recovered from the peak position. The validity of the method is verified by the simulation result, and the performance is proved to be optimal.
基金supported by the National Natural Science Foundation of China(No.51975206)。
文摘Blade Tip-Timing(BTT)has been regarded as a promising way of on-line blade vibration monitoring.But blind multi-band BTT vibration reconstruction is a big challenge under variable speeds and under-sampling.In order to deal with it,a novel Compressed Sensing(CS)method is proposed based on Multi-Coset Angular Sampling(MCAS)in this paper.First,multi-coset sampling scheme of BTT vibration signals is presented.Then the CS model of BTT vibration signals is derived in order domain.A sufficient condition of the number of BTT sensors is derived for perfect reconstruction and optimal placement of BTT sensors is determined by minimizing the condition number.In the end,numerical simulations are done to validate the proposed method and the performances of four reconstruction algorithms are compared,i.e.,Orthogonal Matching Pursuit(OMP),Multiple Signal Classification(MUSIC),Basis Pursuit Denoising(BPDN)and Modified Focal Underdetermined System Solver(MFOCUSS).Influences of the sensor placement,the number of BTT sensors and measurement noises on the reconstruction performances are also testified.The results demonstrate that the proposed method is feasible and the overall performance of the BPDN algorithm is the best among the four algorithms.Also the reconstruction performance decreases with the accelerations of rotating speed.