Independent component analysis was applied to analyze the acoustic signals from diesel engine. First the basic prin-ciple of independent component analysis (ICA) was reviewed. Diesel engine acoustic signal was decompo...Independent component analysis was applied to analyze the acoustic signals from diesel engine. First the basic prin-ciple of independent component analysis (ICA) was reviewed. Diesel engine acoustic signal was decomposed into several inde-pendent components (ICs); Fourier transform and continuous wavelet transform (CWT) were applied to analyze the independent components. Different noise sources of the diesel engine were separated, based on the characteristics of different component in time-frequency domain.展开更多
In order to reduce the hidden danger of noise which can be charactered by singularity spectrum, a new algorithm based on wavelet transform modulus maxima method was proposed. Singularity analysis is one of the most pr...In order to reduce the hidden danger of noise which can be charactered by singularity spectrum, a new algorithm based on wavelet transform modulus maxima method was proposed. Singularity analysis is one of the most promising new approaches for extracting noise hidden information from noisy time series . Because of singularity strength is hard to calculate accurately, a wavelet transform modulus maxima method was used to get singularity spectrum. The singularity spectrum of white noise and aluminium interconnection electromigration noise was calculated and analyzed. The experimental results show that the new algorithm is more accurate than tradition estimating algorithm. The proposed method is feasible and efficient.展开更多
Shear probe works under a tough environment where the turbulence signals to be measured are very weak. The measured turbulence signals often contain a large amount of noise. Due to wide frequency band, noise signals c...Shear probe works under a tough environment where the turbulence signals to be measured are very weak. The measured turbulence signals often contain a large amount of noise. Due to wide frequency band, noise signals cannot be effectively removed by traditional methods based on Fourier transform. In this paper, a wavelet thresholding denoising method is proposed for turbulence signal processing in that wavelet analysis can be used for multi-resolution analysis and can extract local characteristics of the signals in both time and frequency domains. Turbulence signal denoising process is modeled based on the wavelet theory and characteristics of the turbulence signal. The threshold and decomposition level, as well as the procedure of the turbulence signal denoising, are determined using the wavelet thresholding method. The proposed wavelet thresholding method was validated by turbulence signal denoising of the Western Pacific Ocean trial data. The results show that the propsed method can reduce the noise in the measured signals by shear probes, and the frequency spectrums of the denoised signal correspond well to the Nasmyth spectrum.展开更多
. This paper proposes a novel remote sensing signal de-noising algorithm based on neural networks and tensor analysis. The defects exist in a constant deviation between the wavelet coeffi cients and that the wavelet c.... This paper proposes a novel remote sensing signal de-noising algorithm based on neural networks and tensor analysis. The defects exist in a constant deviation between the wavelet coeffi cients and that the wavelet coefficients of the noisy signal to estimate the discontinuity of hard threshold function and soft threshold function, limiting its further application in order to overcome this shortcoming, this paper proposes a new threshold function, compared with the original threshold function, a new threshold function is simple and easy to calculate, not only with the soft threshold function is continuous. To deal with this drawback, we integrate the NN to enhance the model. Neural network belongs to the basic unsupervised learning of neural networks, the principle of competition based on the mechanism of learning and biological and the memory capacity can be increased as the number of learning patterns increases, not only offi ine learning can also be carried out on-line ＂learning while learning＂ type. The integrated algorithm can host better performance.展开更多
The chattering noise problem of reed switch sensor signal for Automatic Meter Reading system was analyzed experimentally under various types of external vibrations and shocks. The external vibration level amplitude wa...The chattering noise problem of reed switch sensor signal for Automatic Meter Reading system was analyzed experimentally under various types of external vibrations and shocks. The external vibration level amplitude was measured with an accelerometer. To apply for water flow measurement devices, the reed switch sensors should keep high reliability. But the measured digital meter data are occurred difference or errors by chattering noise. The reed switch contains chattering error by itself at the force equivalent position. The vibrations such as passing vehicle near to the reed switch installed location causes chattering. In order to reduce chattering error, most system uses just software methods, for example using digital filter algorithm and also statistical calibration methods. However software approaches were implemented for reducing chattering error, there has still generated chattering error due to external mechanical vibrations and magnetic field. The chattering errors can be reduced by changing leaf spring structure using mechanical hysteresis characteristics.展开更多
This paper derives an approximate formula for probability density function(PDF) of received signal-to-interference-and-noise ratio(SINR) at user terminal when matched filter(MF) is adopted at a base station(BS).This d...This paper derives an approximate formula for probability density function(PDF) of received signal-to-interference-and-noise ratio(SINR) at user terminal when matched filter(MF) is adopted at a base station(BS).This distribution of SINR can be used to make an analysis of average sum-rate,outage probability,and symbol error rate of massive MIMO downlink with MF at BS.From simulation,it is found that the derived approximate analytical expression for PDF of SINR is consistent with the simulated exact PDF from the definition of SINR in medium-scale and large-scale MIMO systems.展开更多
The improvement of the signal to noise ratio （SNR） has significant meaning to the fiber Bragg grating （FBG） sensing system. The source of the noise as well as the signal attenuation of the FBG sensing system is an...The improvement of the signal to noise ratio （SNR） has significant meaning to the fiber Bragg grating （FBG） sensing system. The source of the noise as well as the signal attenuation of the FBG sensing system is analyzed. It is found that optical noise caused by the optical return loss （ORL） is the main source of noises in the system, and the coupler is the main source of attenuation of the signal. The cause of the ORL in fiber-optic elements （such as jumper cables connector and fiber end） is presented. In addition, suggestions to optimize the fiber optical sensing network in order to improve the SNR are presented. Methods to suppress noises caused by the fiber end interfaces of FBGs, including using index-matching fluid, bending fiber p!gtails in the way mentioned in this paper and cleaving the slant angle of the fiber interfaces to be 8, all contribute to the optimized SNR. Besides, the thermo-weld method is suggested to be used for both parallel and serial FBG setups to provide a low insertion loss. The results would be a useful engineering tool to design the high SNR optical sensing system.展开更多
基金Project (No. 50575203) supported by the National Natural ScienceFoundation of China
文摘Independent component analysis was applied to analyze the acoustic signals from diesel engine. First the basic prin-ciple of independent component analysis (ICA) was reviewed. Diesel engine acoustic signal was decomposed into several inde-pendent components (ICs); Fourier transform and continuous wavelet transform (CWT) were applied to analyze the independent components. Different noise sources of the diesel engine were separated, based on the characteristics of different component in time-frequency domain.
基金Foundation item: National Natural Science Foundation of China(No.60372072)
文摘In order to reduce the hidden danger of noise which can be charactered by singularity spectrum, a new algorithm based on wavelet transform modulus maxima method was proposed. Singularity analysis is one of the most promising new approaches for extracting noise hidden information from noisy time series . Because of singularity strength is hard to calculate accurately, a wavelet transform modulus maxima method was used to get singularity spectrum. The singularity spectrum of white noise and aluminium interconnection electromigration noise was calculated and analyzed. The experimental results show that the new algorithm is more accurate than tradition estimating algorithm. The proposed method is feasible and efficient.
基金Supported by National Natural Science Foundation of China (No. 50835006 and No. 51005161)National High-Tech R&D Program ("863"Program) of China (No. 2010AA09Z102)
文摘Shear probe works under a tough environment where the turbulence signals to be measured are very weak. The measured turbulence signals often contain a large amount of noise. Due to wide frequency band, noise signals cannot be effectively removed by traditional methods based on Fourier transform. In this paper, a wavelet thresholding denoising method is proposed for turbulence signal processing in that wavelet analysis can be used for multi-resolution analysis and can extract local characteristics of the signals in both time and frequency domains. Turbulence signal denoising process is modeled based on the wavelet theory and characteristics of the turbulence signal. The threshold and decomposition level, as well as the procedure of the turbulence signal denoising, are determined using the wavelet thresholding method. The proposed wavelet thresholding method was validated by turbulence signal denoising of the Western Pacific Ocean trial data. The results show that the propsed method can reduce the noise in the measured signals by shear probes, and the frequency spectrums of the denoised signal correspond well to the Nasmyth spectrum.
文摘. This paper proposes a novel remote sensing signal de-noising algorithm based on neural networks and tensor analysis. The defects exist in a constant deviation between the wavelet coeffi cients and that the wavelet coefficients of the noisy signal to estimate the discontinuity of hard threshold function and soft threshold function, limiting its further application in order to overcome this shortcoming, this paper proposes a new threshold function, compared with the original threshold function, a new threshold function is simple and easy to calculate, not only with the soft threshold function is continuous. To deal with this drawback, we integrate the NN to enhance the model. Neural network belongs to the basic unsupervised learning of neural networks, the principle of competition based on the mechanism of learning and biological and the memory capacity can be increased as the number of learning patterns increases, not only offi ine learning can also be carried out on-line ＂learning while learning＂ type. The integrated algorithm can host better performance.
文摘The chattering noise problem of reed switch sensor signal for Automatic Meter Reading system was analyzed experimentally under various types of external vibrations and shocks. The external vibration level amplitude was measured with an accelerometer. To apply for water flow measurement devices, the reed switch sensors should keep high reliability. But the measured digital meter data are occurred difference or errors by chattering noise. The reed switch contains chattering error by itself at the force equivalent position. The vibrations such as passing vehicle near to the reed switch installed location causes chattering. In order to reduce chattering error, most system uses just software methods, for example using digital filter algorithm and also statistical calibration methods. However software approaches were implemented for reducing chattering error, there has still generated chattering error due to external mechanical vibrations and magnetic field. The chattering errors can be reduced by changing leaf spring structure using mechanical hysteresis characteristics.
基金Supported by the National Natural Science Foundation of China(No.61271230,61301107)the Fundamental Research Funds for the Central Universities(No.30920130122004)Open Research Fund of National Mobile Communications Research Laboratory,Southeast University(No.2013D02)
文摘This paper derives an approximate formula for probability density function(PDF) of received signal-to-interference-and-noise ratio(SINR) at user terminal when matched filter(MF) is adopted at a base station(BS).This distribution of SINR can be used to make an analysis of average sum-rate,outage probability,and symbol error rate of massive MIMO downlink with MF at BS.From simulation,it is found that the derived approximate analytical expression for PDF of SINR is consistent with the simulated exact PDF from the definition of SINR in medium-scale and large-scale MIMO systems.
文摘The improvement of the signal to noise ratio （SNR） has significant meaning to the fiber Bragg grating （FBG） sensing system. The source of the noise as well as the signal attenuation of the FBG sensing system is analyzed. It is found that optical noise caused by the optical return loss （ORL） is the main source of noises in the system, and the coupler is the main source of attenuation of the signal. The cause of the ORL in fiber-optic elements （such as jumper cables connector and fiber end） is presented. In addition, suggestions to optimize the fiber optical sensing network in order to improve the SNR are presented. Methods to suppress noises caused by the fiber end interfaces of FBGs, including using index-matching fluid, bending fiber p!gtails in the way mentioned in this paper and cleaving the slant angle of the fiber interfaces to be 8, all contribute to the optimized SNR. Besides, the thermo-weld method is suggested to be used for both parallel and serial FBG setups to provide a low insertion loss. The results would be a useful engineering tool to design the high SNR optical sensing system.
