Search arXivSearch

arXiv · 1912.07802

Leakage Localisation Using Cross Correlation for Wireless Three-Axis Vibration Sensors

Abstract

The objective of this paper is to investigate the application of the cross-correlation technique in localizing the leakage in Acrylonitrile Butadiene Styrene (ABS) pipeline using wireless three-axis vibration sensors. Most of the existing leak localization techniques that utilized the cross-correlation method is using acoustic and pressure sensors. This study explored the impact of using three-axis vibration sensor ADXL335 to localize the leakages in ABS pipeline. The study focused on the small leak size of 1 mm and the effect of sensor distance and different water pressure is studied. The vibration data used in the cross-correlation data were filtered against the noise interference from the water pipeline. The source of noise interference from the water pipeline are motor, water pump, and valve. The computed leak localization accuracy against the actual leak distance from the three-axis was analyzed. The leakage localization formula is improvised by adding buffer time to have an accurate result. From the experiment, it was discovered that three-axis vibration sensor can be used to localize the leakages in plastic water pipeline and it is suitable for deployment in small to medium water distribution network or within a building.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Airull Azizi Awang Lah, Rudzidatul Akmam Dzyauddin, Nelidya Md Yusoff, Mohd Ismifaizul Mohd Ismail, Noor Azurati Ahmad Salleh, Robiah Ahmad. 2019-12-17. Leakage Localisation Using Cross Correlation for Wireless Three-Axis Vibration Sensors. https://arxiv.org/abs/1912.07802

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Multi-Carrier Rydberg Atomic Quantum Receivers with Enhanced Bandwidth Feature for Communication and Sensing

Rydberg atomic quantum receivers (RAQRs) have attracted significant attention in recent years due to their ultra-high sensitivity. Although capable of precisely detecting the amplitude and phase of weak signals, conventional RAQRs face inherent limitations in accurately receiving wideband RF signals, due to the discrete nature of atomic energy levels and their intrinsic instantaneous bandwidth constraints. These limitations hinder their direct application to multi-carrier communication and sensing. To address this issue, this paper proposes a multi-carrier Rydberg atomic quantum receiver (MC-RAQR) structure with five energy levels. We derive the amplitude and phase of the MC-RAQR and extract the baseband electrical signal for signal processing. In terms of multi-carrier communication and sensing, we analyze the channel capacity and accuracy of angle of arrival (AoA) and distance parameters, respectively. Numerical results validate our proposed model, showing that the MC-RAQR can achieve up to a bandwidth of 11.7 MHz, which is 17-fold larger than the conventional RAQRs. As a result, the channel capacity and the resolution for multi-target sensing are improved significantly. Specifically, the channel capacity of MC-RAQR is 110-fold and 2.8-fold larger than the classical RF receivers and RAQRs, respectively. For sensing performance, the RMSE of AoA estimation for MC-RAQR exhibits 7.6-fold reduction, compared with the conventional RAQRs. Furthermore, the RMSE of distance estimation is $634$-fold smaller than that of the root-CRB of classical RF receivers, showing the superior performance of the MC-RAQR. This demonstrates its compatibility with waveforms such as orthogonal frequency-division multiplexing (OFDM) and its significant advantages for multi-carrier signal reception.

eess.SP

Channel Estimation in MIMO Systems Aided by Microwave Linear Analog Computers (MiLACs)

Microwave linear analog computers (MiLACs) have recently emerged as a promising solution for future gigantic multiple-input multiple-output (MIMO) systems, enabling beamforming with greatly reduced hardware and computational cost. However, channel estimation for MiLAC-aided systems remains an open problem. Conventional least squares (LS) and minimum mean square error (MMSE) estimation rely on intensive digital computation, which undermines the computational advantage offered by MiLACs. In this letter, we propose efficient LS and MMSE channel estimation schemes for MiLAC-aided MIMO systems. By designing the training precoder and combiner implemented by lossless and reciprocal MiLACs, the proposed schemes perform LS and MMSE estimation in the analog domain, leaving only simple digital scaling. They achieve identical estimation performance to their digital counterparts while significantly reducing computational complexity. Numerical results verify the effectiveness of the proposed schemes.

eess.SP

Joint Subcarrier Phase Recovery for Nonlinearity Mitigation

We propose a low-complexity phase recovery scheme that simultaneously mitigates laser phase noise and fiber nonlinearity across several subcarriers. In a long single-span link with Raman amplification, the scheme achieves 0.9 dB gain with 99 real multiplications per complex symbol.

eess.SP