Choi Jihoon, Shin Joonho, Song Choonggeun, Han Suyong, Park Doo Il
School of Electronics and Information Engineering, Korea Aerospace University, Goyang-City, Gyeonggi-do 10540, Korea.
Energy Solution/Business Team, LG CNS Co., Ltd., Yeongdeungpo-gu, Seoul 07320, Korea.
Sensors (Basel). 2017 Sep 13;17(9):2104. doi: 10.3390/s17092104.
This paper proposes a new leak detection and location method based on vibration sensors and generalised cross-correlation techniques. Considering the estimation errors of the power spectral densities (PSDs) and the cross-spectral density (CSD), the proposed method employs a modified maximum-likelihood (ML) prefilter with a regularisation factor. We derive a theoretical variance of the time difference estimation error through summation in the discrete-frequency domain, and find the optimal regularisation factor that minimises the theoretical variance in practical water pipe channels. The proposed method is compared with conventional correlation-based techniques via numerical simulations using a water pipe channel model, and it is shown through field measurement that the proposed modified ML prefilter outperforms conventional prefilters for the generalised cross-correlation. In addition, we provide a formula to calculate the leak location using the time difference estimate when different types of pipes are connected.
本文提出了一种基于振动传感器和广义互相关技术的新型泄漏检测与定位方法。考虑到功率谱密度（PSD）和互谱密度（CSD）的估计误差，该方法采用了带有正则化因子的改进型最大似然（ML）预滤波器。我们通过在离散频域求和推导出时间差估计误差的理论方差，并在实际水管通道中找到使理论方差最小的最优正则化因子。通过使用水管通道模型的数值模拟，将该方法与传统的基于相关性的技术进行了比较，并且通过现场测量表明，所提出的改进型ML预滤波器在广义互相关方面优于传统预滤波器。此外，我们还提供了一个公式，用于在连接不同类型管道时使用时间差估计来计算泄漏位置。
