Vibration signals from diesel engine contain many different components mainly caused by combustion and mechanism operations,several blind source separation techniques are available for decomposing the signal into its ...Vibration signals from diesel engine contain many different components mainly caused by combustion and mechanism operations,several blind source separation techniques are available for decomposing the signal into its components in the case of multichannel measurements,such as independent component analysis（ICA）.However,the source separation of vibration signal from single-channel is impossible.In order to study the source separation from single-channel signal for the purpose of source extraction,the combination method of empirical mode decomposition（EMD） and ICA is proposed in diesel engine signal processing.The performance of the described methods of EMD-wavelet and EMD-ICA in vibration signal application is compared,and the results show that EMD-ICA method outperforms the other,and overcomes the drawback of ICA in the case of single-channel measurement.The independent source signal components can be separated and identified effectively from one-channel measurement by EMD-ICA.Hence,EMD-ICA improves the extraction and identification abilities of source signals from diesel engine vibration measurements.展开更多
A novel blind source separation （BSS） algorithm based on the combination of negentropy and signal noise ratio （SNR） is presented to solve the deficiency of the traditional independent component analysis （ICA） al...A novel blind source separation （BSS） algorithm based on the combination of negentropy and signal noise ratio （SNR） is presented to solve the deficiency of the traditional independent component analysis （ICA） algorithm after the introduction of the principle and algorithm of ICA. The main formulas in the novel algorithm are elaborated and the idiographic steps of the algorithm are given. Then the computer simulation is used to test the performance of this algorithm. Both the traditional FastlCA algorithm and the novel ICA algorithm are applied to separate mixed signal data. Experiment results show the novel method has a better performance in separating signals than the traditional FastlCA algorithm based on negentropy. The novel algorithm could estimate the source signals from the mixed signals more precisely.展开更多
This letter proposes two algorithms: a novel Quantum Genetic Algorithm (QGA)based on the improvement of Han's Genetic Quantum Algorithm (GQA) and a new Blind Source Separation (BSS) method based on QGA and Indepen...This letter proposes two algorithms: a novel Quantum Genetic Algorithm (QGA)based on the improvement of Han's Genetic Quantum Algorithm (GQA) and a new Blind Source Separation (BSS) method based on QGA and Independent Component Analysis (ICA). The simulation result shows that the efficiency of the new BSS method is obviously higher than that of the Conventional Genetic Algorithm (CGA).展开更多
Blind separation of source signals usually relies either on the condition of statistically independence or involving their higher-order cumulants. The model of two channels signal separation is considered. A criterion...Blind separation of source signals usually relies either on the condition of statistically independence or involving their higher-order cumulants. The model of two channels signal separation is considered. A criterion based on correlation functions is proposed. It is proved that the signals can be separated, using only the condition of noncorrelation. An algorithm is derived, which only involves the solution to quadric nonlinear equations.展开更多
基金supported by National Natural Science Foundation of China (Grant No. 50975192)Tianjin Municipal Natural Science Foundation of China (Grant No. 10YFJZJC14100)
文摘Vibration signals from diesel engine contain many different components mainly caused by combustion and mechanism operations,several blind source separation techniques are available for decomposing the signal into its components in the case of multichannel measurements,such as independent component analysis（ICA）.However,the source separation of vibration signal from single-channel is impossible.In order to study the source separation from single-channel signal for the purpose of source extraction,the combination method of empirical mode decomposition（EMD） and ICA is proposed in diesel engine signal processing.The performance of the described methods of EMD-wavelet and EMD-ICA in vibration signal application is compared,and the results show that EMD-ICA method outperforms the other,and overcomes the drawback of ICA in the case of single-channel measurement.The independent source signal components can be separated and identified effectively from one-channel measurement by EMD-ICA.Hence,EMD-ICA improves the extraction and identification abilities of source signals from diesel engine vibration measurements.
文摘A novel blind source separation （BSS） algorithm based on the combination of negentropy and signal noise ratio （SNR） is presented to solve the deficiency of the traditional independent component analysis （ICA） algorithm after the introduction of the principle and algorithm of ICA. The main formulas in the novel algorithm are elaborated and the idiographic steps of the algorithm are given. Then the computer simulation is used to test the performance of this algorithm. Both the traditional FastlCA algorithm and the novel ICA algorithm are applied to separate mixed signal data. Experiment results show the novel method has a better performance in separating signals than the traditional FastlCA algorithm based on negentropy. The novel algorithm could estimate the source signals from the mixed signals more precisely.
基金Supported by the National Natural Science Foundation of China (No.60171029)
文摘This letter proposes two algorithms: a novel Quantum Genetic Algorithm (QGA)based on the improvement of Han's Genetic Quantum Algorithm (GQA) and a new Blind Source Separation (BSS) method based on QGA and Independent Component Analysis (ICA). The simulation result shows that the efficiency of the new BSS method is obviously higher than that of the Conventional Genetic Algorithm (CGA).
文摘Blind separation of source signals usually relies either on the condition of statistically independence or involving their higher-order cumulants. The model of two channels signal separation is considered. A criterion based on correlation functions is proposed. It is proved that the signals can be separated, using only the condition of noncorrelation. An algorithm is derived, which only involves the solution to quadric nonlinear equations.
