When the bi-stable stochastic resonance method was applied to enhance weak thruster fault for autonomous underwater vehicle(AUV), the enhancement performance could not satisfy the detection requirement of weak thruste...When the bi-stable stochastic resonance method was applied to enhance weak thruster fault for autonomous underwater vehicle(AUV), the enhancement performance could not satisfy the detection requirement of weak thruster fault. As for this problem, a fault feature enhancement method based on mono-stable stochastic resonance was proposed. In the method, in order to improve the enhancement performance of weak thruster fault feature, the conventional bi-stable potential function was changed to mono-stable potential function which was more suitable for aperiodic signals. Furthermore, when particle swarm optimization was adopted to adjust the parameters of mono-stable stochastic resonance system, the global convergent time would be long. An improved particle swarm optimization method was developed by changing the linear inertial weighted function as nonlinear function with cosine function, so as to reduce the global convergent time. In addition, when the conventional wavelet reconstruction method was adopted to detect the weak thruster fault, undetected fault or false alarm may occur. In order to successfully detect the weak thruster fault, a weak thruster detection method was proposed based on the integration of stochastic resonance and wavelet reconstruction. In the method, the optimal reconstruction scale was determined by comparing wavelet entropies corresponding to each decomposition scale. Finally, pool-experiments were performed on AUV with thruster fault. The effectiveness of the proposed mono-stable stochastic resonance method in enhancing fault feature and reducing the global convergent time was demonstrated in comparison with particle swarm optimization based bi-stochastic resonance method. Furthermore, the effectiveness of the proposed fault detection method was illustrated in comparison with the conventional wavelet reconstruction.展开更多
This paper considers the stochastic resonance for a time-delayed mono-stable system, driven by correlated multiplicative and additive white noise. It finds that the output signal-to-noise ratio （SNR） varies non-mono...This paper considers the stochastic resonance for a time-delayed mono-stable system, driven by correlated multiplicative and additive white noise. It finds that the output signal-to-noise ratio （SNR） varies non-monotonically with the delayed times. The SNR varies non-monotonically with the increase of the intensities of the multiplicative and additive noise, with the increase of the correlation strength between the two noises, as well as with the system parameter.展开更多
The phenomenon of stochastic resonance （SR） in an asymmetric mono-stable system subject to two external periodic forces and multiplicative and additive noise is investigated. It is shown that the signal-to-noise rat...The phenomenon of stochastic resonance （SR） in an asymmetric mono-stable system subject to two external periodic forces and multiplicative and additive noise is investigated. It is shown that the signal-to-noise ratio （SNR） for the fundamental and higher harmonics is a non-monotonic function of the intensities of the multiplicative and additive noise, as well as of the system parameter. Moreover, the SNR for the fundamental harmonic decreases with the increase of the system asymmetry, while the SNR for the higher harmonics behaves non-monotonically as the system asymmetry varies.展开更多
基金Project(51279040)supported by the National Natural Science Foundation of China
文摘When the bi-stable stochastic resonance method was applied to enhance weak thruster fault for autonomous underwater vehicle(AUV), the enhancement performance could not satisfy the detection requirement of weak thruster fault. As for this problem, a fault feature enhancement method based on mono-stable stochastic resonance was proposed. In the method, in order to improve the enhancement performance of weak thruster fault feature, the conventional bi-stable potential function was changed to mono-stable potential function which was more suitable for aperiodic signals. Furthermore, when particle swarm optimization was adopted to adjust the parameters of mono-stable stochastic resonance system, the global convergent time would be long. An improved particle swarm optimization method was developed by changing the linear inertial weighted function as nonlinear function with cosine function, so as to reduce the global convergent time. In addition, when the conventional wavelet reconstruction method was adopted to detect the weak thruster fault, undetected fault or false alarm may occur. In order to successfully detect the weak thruster fault, a weak thruster detection method was proposed based on the integration of stochastic resonance and wavelet reconstruction. In the method, the optimal reconstruction scale was determined by comparing wavelet entropies corresponding to each decomposition scale. Finally, pool-experiments were performed on AUV with thruster fault. The effectiveness of the proposed mono-stable stochastic resonance method in enhancing fault feature and reducing the global convergent time was demonstrated in comparison with particle swarm optimization based bi-stochastic resonance method. Furthermore, the effectiveness of the proposed fault detection method was illustrated in comparison with the conventional wavelet reconstruction.
文摘This paper considers the stochastic resonance for a time-delayed mono-stable system, driven by correlated multiplicative and additive white noise. It finds that the output signal-to-noise ratio （SNR） varies non-monotonically with the delayed times. The SNR varies non-monotonically with the increase of the intensities of the multiplicative and additive noise, with the increase of the correlation strength between the two noises, as well as with the system parameter.
基金supported by the Doctor Foundation of SWUST of China under Grant No.08ZX7108
文摘The phenomenon of stochastic resonance （SR） in an asymmetric mono-stable system subject to two external periodic forces and multiplicative and additive noise is investigated. It is shown that the signal-to-noise ratio （SNR） for the fundamental and higher harmonics is a non-monotonic function of the intensities of the multiplicative and additive noise, as well as of the system parameter. Moreover, the SNR for the fundamental harmonic decreases with the increase of the system asymmetry, while the SNR for the higher harmonics behaves non-monotonically as the system asymmetry varies.
