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Aiming at the increasingly serious pipeline damages because of the artificial factors, we investigate the characteristic of seismic signals and develop a monitoring and pre-warning system for security of pipelines based on multi-seismic sensors. There were many sensors and processing modules to acquire the seismic signals generated by the ground targets. The non-stationary signal analysis method based on empirical mode decomposition was used to process the seismic signals. The target feature vectors were composed of the normalized kurtosis extracted from the decomposition results. The single sensor's judgment was made by the main normalized kurtosis values in the important decomposed frequency bands. In this system there are many same sensors and modules, this D-S evidence reasoning was to fuse the recognition results for improving the target recognition accuracy. Then the last judgment was made. For target localization, it proposed a novel passive localization method based on TDOA (time difference of arrival). The seismic signals generated by different targets were acquired by many geophones and detection modules. As a new time-frequency method, Hilbert-Huang transform was used to process the signals and obtained the characteristic frequencies and appearance time. The arrival time difference, the sensor location and the relative position of target and sensors were analyzed and the target localization can be achieved. The processing methods above were proved effective by the experiment data analysis.