Speech signals in frequency domain were separated based on discrete wavelet transform (DWT) and independent component analysis (ICA). First, mixed speech signals were decomposed into different frequency domains by DWT...Speech signals in frequency domain were separated based on discrete wavelet transform (DWT) and independent component analysis (ICA). First, mixed speech signals were decomposed into different frequency domains by DWT and the subbands of speech signals were separated using ICA in each wavelet domain; then, the permutation and scaling problems of frequency domain blind source separation (BSS) were solved by utilizing the correlation between adjacent bins in speech signals; at last, source signals were reconstructed from single branches. Experiments were carried out with 2 sources and 6 microphones using speech signals at sampling rate of 40 kHz. The microphones were aligned with 2 sources in front of them, on the left and right. The separation of one male and one female speeches lasted 2.5 s. It is proved that the new method is better than single ICA method and the signal to noise ratio is improved by 1 dB approximately.展开更多
Based on the loading conditions of engine, applying difference method to solve the hydrodynamic lubrication equation of piston skirt movement, the force acting on piston skirt and the moment on wrist pin were obtained...Based on the loading conditions of engine, applying difference method to solve the hydrodynamic lubrication equation of piston skirt movement, the force acting on piston skirt and the moment on wrist pin were obtained. A computer program for simulating the piston second order motion was conducted to calculate the lateral motion of the upper part and the bottom part of piston skirts of the engine of automotive model CA1091. From the simulated result, the maximal impacting phase and the maximal impacting region of the piston were obtained. The result can be used for designing engine, diagnosing the noise of piston knocking cylinder wall and explaining many practical fault phenomena in theory.展开更多
基金Supported by Tianjin Municipal Science and Technology Commission (No.09JCYBJC02200)
文摘Speech signals in frequency domain were separated based on discrete wavelet transform (DWT) and independent component analysis (ICA). First, mixed speech signals were decomposed into different frequency domains by DWT and the subbands of speech signals were separated using ICA in each wavelet domain; then, the permutation and scaling problems of frequency domain blind source separation (BSS) were solved by utilizing the correlation between adjacent bins in speech signals; at last, source signals were reconstructed from single branches. Experiments were carried out with 2 sources and 6 microphones using speech signals at sampling rate of 40 kHz. The microphones were aligned with 2 sources in front of them, on the left and right. The separation of one male and one female speeches lasted 2.5 s. It is proved that the new method is better than single ICA method and the signal to noise ratio is improved by 1 dB approximately.
文摘Based on the loading conditions of engine, applying difference method to solve the hydrodynamic lubrication equation of piston skirt movement, the force acting on piston skirt and the moment on wrist pin were obtained. A computer program for simulating the piston second order motion was conducted to calculate the lateral motion of the upper part and the bottom part of piston skirts of the engine of automotive model CA1091. From the simulated result, the maximal impacting phase and the maximal impacting region of the piston were obtained. The result can be used for designing engine, diagnosing the noise of piston knocking cylinder wall and explaining many practical fault phenomena in theory.
