In order to de-noise and filter the acoustic emission(AE) signal, the adaptive filtering technology is applied to AE signal processing in view of the special attenuation characteristics of burst AE signal. According t...In order to de-noise and filter the acoustic emission(AE) signal, the adaptive filtering technology is applied to AE signal processing in view of the special attenuation characteristics of burst AE signal. According to the contradiction between the convergence speed and steady-state error of the traditional least mean square(LMS) adaptive filter, an improved LMS adaptive filtering algorithm with variable iteration step is proposed on the basis of the existing algorithms. Based on the Sigmoid function, an expression with three parameters is constructed by function translation and symmetric transformation.As for the error mutation, e(k) and e(k-1) are combined to control the change of the iteration step. The selection and adjustment process of each parameter is described in detail, and the MSE is used to evaluate the performance. The simulation results show that the proposed algorithm significantly increases the convergence speed, reduces the steady-state error, and improves the performance of the adaptive filter. The improved algorithm is applied to the AE signal processing, and the experimental signal is demodulated by an empirical mode decomposition(EMD) envelope to obtain the upper and lower envelopes. Then, the expected function related to the AE signal is established. Finally, the improved algorithm is substituted into the adaptive filter to filter the AE signal. A good result is achieved, which proves the feasibility of adaptive filtering technology in AE signal processing.展开更多
The full-waveform inversion method is a high-precision inversion method based on the minimization of the misfit between the synthetic seismograms and the observed data.However,this method suffers from cycle skipping i...The full-waveform inversion method is a high-precision inversion method based on the minimization of the misfit between the synthetic seismograms and the observed data.However,this method suffers from cycle skipping in the time domain or phase wrapping in the frequency because of the inaccurate initial velocity or the lack of low-frequency information.furthermore,the object scale of inversion is affected by the observation system and wavelet bandwidth,the inversion for large-scale structures is a strongly nonlinear problem that is considerably difficult to solve.In this study,we modify the unwrapping algorithm to obtain accurate unwrapped instantaneous phase,then using this phase conducts the inversion for reducing the strong nonlinearity.The normal instantaneous phases are measured as modulo 2π,leading the loss of true phase information.The path integral algorithm can be used to unwrap the instantaneous phase of the seismograms having time series and onedimensional(1 D)signal characteristics.However,the unwrapped phase is easily affected by the numerical simulation and phase calculations,resulting in the low resolution of inversion parameters.To increase the noise resistance and ensure the inversion accuracy,we present an improved unwrapping method by adding an envelope into the path integral unwrapping algorithm for restricting the phase mutation points,getting accurate instantaneous phase.The objective function constructed by unwrapping instantaneous phase is less affected by the local minimum,thereby making it suitable for full-waveform inversion.Further,the corresponding instantaneous phase inversion formulas are provided.Using the improved algorithm,we can invert the low-wavenumber components of the underneath structure and ensure the accuracy of the inverted velocity.Finally,the numerical tests of the 2 D Marmousi model and 3 D SEG/EAGE salt model prove the accuracy of the proposed algorithm and the ability to restore largescale low-wavenumber structures,respectively.展开更多
High-speed vehicle dynamic envelope curve is defined as the maximum limit outline affected by a variety of adverse factors while the train is running. Considering the difficulties in the current measurement system suc...High-speed vehicle dynamic envelope curve is defined as the maximum limit outline affected by a variety of adverse factors while the train is running. Considering the difficulties in the current measurement system such as complicated calibration process,cumbersome aided-instruments,strict limitation of working distance, this paper carries out an optical method in which two high-speed cameras with variable-zoom lenses are adopted as binocular stereo sensors of measurement system and a high-ac-curacy 3D target with fast reconstruction is designed. The intrinsic parameters of the sensors and the relative positions between coordinate systems are solved by the method of colinearity constrained optimization algorithm. The calibration process is easy to operate and the device is also of portability. Most importantly, the severe working distance limitation between sensors and measured body is solved, enhancing the adaptability of measurement system to environment. Experimental results show that when the sensors are in the range of 8 -16 m away from the measured body, system accuracy can reach up to ±0. 5 mm, which meets the requirements to measure the dynamic envelope curve of high-speed vehicle.展开更多
基金The National Natural Science Foundation of China(No.51575101)
文摘In order to de-noise and filter the acoustic emission(AE) signal, the adaptive filtering technology is applied to AE signal processing in view of the special attenuation characteristics of burst AE signal. According to the contradiction between the convergence speed and steady-state error of the traditional least mean square(LMS) adaptive filter, an improved LMS adaptive filtering algorithm with variable iteration step is proposed on the basis of the existing algorithms. Based on the Sigmoid function, an expression with three parameters is constructed by function translation and symmetric transformation.As for the error mutation, e(k) and e(k-1) are combined to control the change of the iteration step. The selection and adjustment process of each parameter is described in detail, and the MSE is used to evaluate the performance. The simulation results show that the proposed algorithm significantly increases the convergence speed, reduces the steady-state error, and improves the performance of the adaptive filter. The improved algorithm is applied to the AE signal processing, and the experimental signal is demodulated by an empirical mode decomposition(EMD) envelope to obtain the upper and lower envelopes. Then, the expected function related to the AE signal is established. Finally, the improved algorithm is substituted into the adaptive filter to filter the AE signal. A good result is achieved, which proves the feasibility of adaptive filtering technology in AE signal processing.
基金supported by the National Science and Technology major projects of China(No.2017ZX05032-003-002)Shandong Key Research and Development Plan Project(No.2018GHY115016)China University of Petroleum(East China)Independent Innovation Research Project(No.18CX06023A)。
文摘The full-waveform inversion method is a high-precision inversion method based on the minimization of the misfit between the synthetic seismograms and the observed data.However,this method suffers from cycle skipping in the time domain or phase wrapping in the frequency because of the inaccurate initial velocity or the lack of low-frequency information.furthermore,the object scale of inversion is affected by the observation system and wavelet bandwidth,the inversion for large-scale structures is a strongly nonlinear problem that is considerably difficult to solve.In this study,we modify the unwrapping algorithm to obtain accurate unwrapped instantaneous phase,then using this phase conducts the inversion for reducing the strong nonlinearity.The normal instantaneous phases are measured as modulo 2π,leading the loss of true phase information.The path integral algorithm can be used to unwrap the instantaneous phase of the seismograms having time series and onedimensional(1 D)signal characteristics.However,the unwrapped phase is easily affected by the numerical simulation and phase calculations,resulting in the low resolution of inversion parameters.To increase the noise resistance and ensure the inversion accuracy,we present an improved unwrapping method by adding an envelope into the path integral unwrapping algorithm for restricting the phase mutation points,getting accurate instantaneous phase.The objective function constructed by unwrapping instantaneous phase is less affected by the local minimum,thereby making it suitable for full-waveform inversion.Further,the corresponding instantaneous phase inversion formulas are provided.Using the improved algorithm,we can invert the low-wavenumber components of the underneath structure and ensure the accuracy of the inverted velocity.Finally,the numerical tests of the 2 D Marmousi model and 3 D SEG/EAGE salt model prove the accuracy of the proposed algorithm and the ability to restore largescale low-wavenumber structures,respectively.
基金National Science and Technology Major Project(No.2016ZX04003001)
文摘High-speed vehicle dynamic envelope curve is defined as the maximum limit outline affected by a variety of adverse factors while the train is running. Considering the difficulties in the current measurement system such as complicated calibration process,cumbersome aided-instruments,strict limitation of working distance, this paper carries out an optical method in which two high-speed cameras with variable-zoom lenses are adopted as binocular stereo sensors of measurement system and a high-ac-curacy 3D target with fast reconstruction is designed. The intrinsic parameters of the sensors and the relative positions between coordinate systems are solved by the method of colinearity constrained optimization algorithm. The calibration process is easy to operate and the device is also of portability. Most importantly, the severe working distance limitation between sensors and measured body is solved, enhancing the adaptability of measurement system to environment. Experimental results show that when the sensors are in the range of 8 -16 m away from the measured body, system accuracy can reach up to ±0. 5 mm, which meets the requirements to measure the dynamic envelope curve of high-speed vehicle.
