关键词: 管道安全监测, 预警系统, 目标识别, 经验模态分解, 地震波传感器, 数据融合方法, 特征向量, 地震信号

Abstract:

A method for extraction of target features in the pipeline security monitoring and pre-warning system based on multi-seismic sensors was studied with data fusion to improve recognition rate.Many sensors and processing modules were used 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 normalized kurtosis extracted from the decomposed results was composed of the feature vectors.The decision of single sensor was made of the major normalized kurtosis in the main decomposed frequency bands.The D-S evidence reasoning was used to fuse these individual recognition results for improving recognition rate,and the final decision was obtained.The experiment data were acquired and analyzed.The analysis results verified the validity of the new method.

Key words: pipeline security monitoring, pre-warning system, target recognition, empirical mode decomposition, seismic sensor, data fusion method, feature vector, seismic signal