Weak vibration signal detection based on frequency domain cumulative averaging with DVS system

Accurate detection of weak vibration signals by distributed vibration sensing (DVS) system plays an important role in early warning of large infrastructures. In this paper, a frequency domain cumulative averaging (FDCA) algorithm is proposed to overcome the problem that weak vibrations cannot be identified and localized when the signal-to-noise ratio (SNR) of the weak vibration signals is less than or equal to 1. The proposed method periodically truncates the weak vibration signal in the time domain and performs power spectrum estimation separately. Subsequently, the power spectrum obtained in the frequency domain is cumulatively averaged to improve the SNR of the weak vibration signal and reduce the spectral variance. Finally, the averaged spectrum obtained at each position is used to construct a three-dimensional spectrogram of position-frequency-spectral power, which allows the identification of weak vibration signals with high spatial resolution. The experimental results well demonstrate that the proposed method can detect weak vibration signals acting on a sensing fiber with a length of 1 m, and the SNR is improved by 6.9 dB. In addition, the proposed method is further used for the detection of weak vibration signals generated by self-oscillation and external excitation in simply supported beams. Moreover, we theoretically and experimentally illustrate that there is a good inverse relationship between the amplitude of the weak vibration signals and the length of the sensing fiber. The proposed method can well improve the monitoring capability of the DVS system in weak vibration signals such as hydroacoustic signals and pipeline microleakage.