When using a miniature single sensor boundary layer probe, the time sequences of the stream-wise velocity in the turbulent boundary layer （TBL） are measured by using a hot wire anemometer. Beneath the fully develope...When using a miniature single sensor boundary layer probe, the time sequences of the stream-wise velocity in the turbulent boundary layer （TBL） are measured by using a hot wire anemometer. Beneath the fully developed TBL, the wall pressure fluctuations are attained by a microphone mechanism with high spatial resolution. Analysis on the statistic and spectrum properties of velocity and wall pressure reveals the relationship between the wall pressure fluctuation and the energy-containing structure in the buffer layer of the TBL. Wavelet transform shows the multi-scale natures of coherent structures contained in both signals of velocity and pressure. The most intermittent wall pressure scale is associated with the coherent structure in the buffer layer. Meanwhile the most energetic scale of velocity fluctuation at y＋ = 14 provides a specific frequency f9 ≈ 147 Hz for wall actuating control with Ret = 996.展开更多
This paper proposes a novel microphone array speech denoising scheme based on tensor filtering methods including truncated HOSVD(High-Order Singular Value Decomposition), low rank tensor approximation and multi-mode W...This paper proposes a novel microphone array speech denoising scheme based on tensor filtering methods including truncated HOSVD(High-Order Singular Value Decomposition), low rank tensor approximation and multi-mode Wiener filtering. Microphone array speech signal is represented in three-order tensor space with channel, time, and spectrum modes and then tensor filtering model can be designed to process the multiway array data. As to the first method, noise can be reduced through the truncated HOSVD which is a simple scheme in tensor processing. It is more accurate to find the lower-rank approximation of the three-order tensor with Tucker model. Then MDL(Minimum Description Length) criterion is used to estimate the optimal tensor rank in the second method. Further, multimode Wiener filtering approach upon tensor analysis can be considered as the spanning of one-mode wiener filtering. How to take advantages of tensor model to obtain a set of filters is the heart of the novel scheme. The performances of the proposed three approaches are evaluated with objective indexes and listening quality test. The experimental results indicate that the proposed tenor filtering methods have potential ability of retrieving the target signal from noisy microphone array signal and the multi-mode Wiener filtering method provides the best denoising results among the three ones.展开更多
In this paper, the frequency-domain Frost algorithm is enhanced by using conjugate gradient techniques for speech enhancement. Unlike the non-adaptive approach of computing the optimum minimum variance distortionless ...In this paper, the frequency-domain Frost algorithm is enhanced by using conjugate gradient techniques for speech enhancement. Unlike the non-adaptive approach of computing the optimum minimum variance distortionless response （MVDR） solution with the correlation matrix inversion, the Frost algorithm implementing the stochastic constrained least mean square （LMS） algorithm can adaptively converge to the MVDR solution in mean-square sense, but with a very slow convergence rate. In this paper, we propose a frequency-domain constrained conjugate gradient （FDCCG） algorithm to speed up the convergence. The devised FDCCG algorithm avoids the matrix inversion and exhibits fast convergence. The speech enhancement experiments for the target speech signal corrupted by two and five interfering speech signals are demonstrated by using a four-channel acoustic-vector-sensor （AVS） micro-phone array and show the superior performance.展开更多
Microphone array can be used in sound source localization and separation. But gain, phase, and position errors can seriously influence the performance of localization algorithms such as multiple signal classification ...Microphone array can be used in sound source localization and separation. But gain, phase, and position errors can seriously influence the performance of localization algorithms such as multiple signal classification （MUSIC） algorithm. In this paper, a new calibration method for microphone array with gain, phase, and position errors is proposed. Unlike traditional calibration methods for antenna array, the proposed method can be used in the broadband and near-field signal model such as microphone array with arbitrary sensor geometries in one plane. Computer simulations are presented and simulation results show the new method having good performance.展开更多
As the requirements of production process is getting higher and higher with the reduction of volume,microphone production automation become an urgent need to improve the production efficiency.The most important part i...As the requirements of production process is getting higher and higher with the reduction of volume,microphone production automation become an urgent need to improve the production efficiency.The most important part is studied and a precise algorithm of calculating the deviation angle of four types microphones is proposed,based on the feature extraction and visual detection.Pretreatment is performed to achieve the real-time microphone image.Canny edge detection and typical feature extraction are used to distinguish the four types of microphones,categorizing them as type M1 and type M2.And Hough transformation is used to extract the image features of microphone.Therefore,the deviation angle between the posture of microphone and the ideal posture in 2Dplane can be achieved.Depending on the angle,the system drives the motor to adjust posture of the microphone.The final purpose is to realize the high efficiency welding of four different types of microphones.展开更多
基金Project supported by the National Basic Research Program of China(Grant Nos.2012CB720101 and 2012CB720103)the National Natural Science Foundation of China(Grant Nos.11272233,11332006,and 11411130150)
文摘When using a miniature single sensor boundary layer probe, the time sequences of the stream-wise velocity in the turbulent boundary layer （TBL） are measured by using a hot wire anemometer. Beneath the fully developed TBL, the wall pressure fluctuations are attained by a microphone mechanism with high spatial resolution. Analysis on the statistic and spectrum properties of velocity and wall pressure reveals the relationship between the wall pressure fluctuation and the energy-containing structure in the buffer layer of the TBL. Wavelet transform shows the multi-scale natures of coherent structures contained in both signals of velocity and pressure. The most intermittent wall pressure scale is associated with the coherent structure in the buffer layer. Meanwhile the most energetic scale of velocity fluctuation at y＋ = 14 provides a specific frequency f9 ≈ 147 Hz for wall actuating control with Ret = 996.
基金supported by the National Natural Science Foundation of China(No.61571044,No.11590772,No.61473041 and No.61620106002)
文摘This paper proposes a novel microphone array speech denoising scheme based on tensor filtering methods including truncated HOSVD(High-Order Singular Value Decomposition), low rank tensor approximation and multi-mode Wiener filtering. Microphone array speech signal is represented in three-order tensor space with channel, time, and spectrum modes and then tensor filtering model can be designed to process the multiway array data. As to the first method, noise can be reduced through the truncated HOSVD which is a simple scheme in tensor processing. It is more accurate to find the lower-rank approximation of the three-order tensor with Tucker model. Then MDL(Minimum Description Length) criterion is used to estimate the optimal tensor rank in the second method. Further, multimode Wiener filtering approach upon tensor analysis can be considered as the spanning of one-mode wiener filtering. How to take advantages of tensor model to obtain a set of filters is the heart of the novel scheme. The performances of the proposed three approaches are evaluated with objective indexes and listening quality test. The experimental results indicate that the proposed tenor filtering methods have potential ability of retrieving the target signal from noisy microphone array signal and the multi-mode Wiener filtering method provides the best denoising results among the three ones.
基金supported by the Human Sixth Sense Programme at the Advanced Digital Sciences Center from Singapore’s Agency for Science,Technology and Research
文摘In this paper, the frequency-domain Frost algorithm is enhanced by using conjugate gradient techniques for speech enhancement. Unlike the non-adaptive approach of computing the optimum minimum variance distortionless response （MVDR） solution with the correlation matrix inversion, the Frost algorithm implementing the stochastic constrained least mean square （LMS） algorithm can adaptively converge to the MVDR solution in mean-square sense, but with a very slow convergence rate. In this paper, we propose a frequency-domain constrained conjugate gradient （FDCCG） algorithm to speed up the convergence. The devised FDCCG algorithm avoids the matrix inversion and exhibits fast convergence. The speech enhancement experiments for the target speech signal corrupted by two and five interfering speech signals are demonstrated by using a four-channel acoustic-vector-sensor （AVS） micro-phone array and show the superior performance.
基金This work was supported by the Key Project of Science and Technology of Sichuan Province under Grant No. 04GG21-02-20.
文摘Microphone array can be used in sound source localization and separation. But gain, phase, and position errors can seriously influence the performance of localization algorithms such as multiple signal classification （MUSIC） algorithm. In this paper, a new calibration method for microphone array with gain, phase, and position errors is proposed. Unlike traditional calibration methods for antenna array, the proposed method can be used in the broadband and near-field signal model such as microphone array with arbitrary sensor geometries in one plane. Computer simulations are presented and simulation results show the new method having good performance.
基金supported by the Project of Youth Fund of the National Natural Science Foundation (No. 61203208)the National Natural Science Foundation of China(No.61327802)the Specialized Research Fund for the Doctoral Program of Higher Education (No.2013320111 0009)
文摘As the requirements of production process is getting higher and higher with the reduction of volume,microphone production automation become an urgent need to improve the production efficiency.The most important part is studied and a precise algorithm of calculating the deviation angle of four types microphones is proposed,based on the feature extraction and visual detection.Pretreatment is performed to achieve the real-time microphone image.Canny edge detection and typical feature extraction are used to distinguish the four types of microphones,categorizing them as type M1 and type M2.And Hough transformation is used to extract the image features of microphone.Therefore,the deviation angle between the posture of microphone and the ideal posture in 2Dplane can be achieved.Depending on the angle,the system drives the motor to adjust posture of the microphone.The final purpose is to realize the high efficiency welding of four different types of microphones.
