This paper reports a distributed optical fiber pipeline safety early warning system which based on the BP neural network signal recognition algorithm.Using the time-domain,frequency-domain features of short-time and long-time of the vibration signals,the BP neural network model is trained.The model realizes the intelligent distinguish of artificial dig or mechanical dig.The maximum false alarm rate of BP classifier model is 3.3 %,the average false alarm rate is 1 %,the maximum missing alarm rate is 3.2 %,and the average missing alarm rate is 1 %.The BP model is applied to the signal distinguish test with different time lengths,and the lowest rate of missing alarm rate is 5 %.Therefore,the BP signal distinguish algorithm can effectively identify and classify the pipeline intrusion signal,and improve the reliability of the sensor system.