Based On Atomic Library Optimized Logging Acoustic Signal Separation Research

With the development of blind signal separation technology.the technology has been widely used in image processing,seismic exploration.speech recognition, biomedical and so on. But most of the blind signal separation algorithm for multi-channel receiving mixed signals effective separation of overlapping single-channel mixed signal is seriously some of the existing BSS methods have some limitations. AM-FM mixed signal have been separated by domestic and foreign scholars in single-channel, and in the context of prior information that will separate the signal from the signal source verified by comparing the effectiveness of the algorithm. Existing methods has been studied the based on the use the wave to extract moment optimization atom library MP sparse decomposition algorithm longitudinal spread of logging in mixed-signal wave to be separated. Mixed signals are the various component signals of the frequency, amplitude and phase information. This information helps to analyze the calculation of the lithology, porosity, reservoir and other information.Logging acoustic signal is time-frequency overlapping signals, alone in the time domain, frequency domain, spatial domain filtering are more difficult to separate, existing methods can not achieve the desired results, how to separate logging acoustic signals, extracting more useful information is our research goal. Acoustic signals for logging in the single-channel characteristics and the principle of separation of mixed signals, the atom library optimized MP sparse decomposition method is selected, the method is applied in logging acoustic signal. Main job is as follows:1, First the blind source model is introduced, classification and separation algorithms. Then study the characteristics of logging acoustic signals, with three signal acoustic logging signal detection signal. to prepare for the next study.2, Introduce atom library optimization method. Extraction of subsequent wave moment in the application to the atom parameter settings prior to reduce errors influence. Based on the simulation experiment of model signal, the conclusion:the extraction of wave moment need to add four sampling points, can reduce the error extract wave moment. And when a signal starting point when up to 10 times overlap degree will not be correct separated. The simulation experiment of model signal, the contrast of signal and isolated the mean square error of the original signal, mean-square explain the effectiveness of separation algorithm.3, Put forward by optimizing the wave to extract combining with the MP algorithm, will extract wave moment applied to sparse decomposition of atomic parameter settings, then optimized atomic library. Respectively, the actual separation model acoustic signal wave logging. Experimental results show that the MP based on atomic library optimization method sparse decomposition of logging acoustic signals first affected each subsequent wave of mixed signal isolated, through the simulation can see running time quickly. Reduced the search optimal atomic computational complexity. Based on wavelet to extract contrast moments to optimize atoms library sparse decomposition algorithm and MP algorithm of separated signal. Conclusion, the proposed method can effectively and reduce the number of mixed signal judgment, reduce the size of the atomic library programs running time, get separation results.