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In distributed optical fiber pipeline pre-warning system, the sampling rate is very high for threatening event location, so vast data will be generated which is inconvenient for transfer or storage. This paper adopts the compressive sensing approach to reduce the data quantity. The sparsity of each segment of the signal is important for signal recovery, and it controls the measurement number needed. However, the sparsity of every segment is difficult to achieve. In this paper, the sequential approach is used to fix the measurement number of each segment of the optical fiber pipeline data. This segment sequential approach further reduces the amount of data on the basis of compressive sensing. Simulation is carried out on the actual optical fiber pipeline pre-warning data, and the experimental results show that the reconstruction SNR could exceed 26 dB using this algorithm.