Distributed Compressed Sensing of Microseismic Signals Through First Break Time Extraction and Signal Alignment

Microseismic monitoring is widely applied in dams, mines, and various fields of underground engineering. The number of sensors in microseismic monitoring systems is usually very large, which will result in a huge amount of data being produced if the Nyquist sampling theorem is used to acquire microseismic signals. To reduce the data storage costs and accelerate the transmission speed, we propose a distributed compressed sensing (CS) scheme for microseismic monitoring signals in this paper. The distributed compressed sensing scheme begins when it detects the first break time in the microseismic signal. The data recoding of the first break time is coded and transmitted together with the measured values of CS. Depending on the correlations between the microseismic signals, the first break time of the signals are aligned to that of the reference signal. Furthermore, we make use of the distributed CS to reduce the amount of data to be transmitted and to increase the reconstruction accuracy. Simulation results show that, compared with the sampling scheme based on the Nyquist sampling theorem, the independent CS scheme or the traditional distributed CS scheme, our proposed scheme improves the accuracy in the first break time detection and the reconstruction accuracy, and the scheme reduces the energy consumption at the same time.