Cross-correlation analysis of multiple fibre optic hydrophones for water pipeline leakage detection

Guo, Chengchao; Shi, K.; Chu, Xuanxuan

doi:10.1007/s13762-021-03163-y

Cited by 16 publications

(4 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Sound signals are recorded using a data logger or PC software. Guo et al, 2022;Phua et al, 2020) Ground microphone An acoustic listening device that amplifies the sound signal can be used for pinpointing the leaks. (Quintiliani et al, 2020) Flowmeter Electro-magnetic or ultrasonic flowmeters quantify the flow of fluid passing through the pipe.…”

Section: Sensing System Working Principle Examplesmentioning

confidence: 99%

State‐of‐the‐art review of leak diagnostic experiments: Toward a smart water network

Bakhtawar

Zayed

2023

WIREs Water

View full text Add to dashboard Cite

Effective water pipeline leak detection and localization can help water practitioners save water losses and reduce pipe rehabilitation budgets. Different sensing technologies can provide essential data aiding model development for predicting future leaks in the water distribution networks. Solutions for applying different sensing technologies to real water distribution networks are being developed for real‐time data collection, precise leak localization, reducing false alarms, and continuous pipeline monitoring. Experiments of different scales and specifications have been conducted to test the application and effectiveness of sensing technologies for leak diagnosis in water pipelines. Quality data collection is especially crucial for the successful implementation of these experiments. However, practitioners need help designing effective leak detection and localization experiments, wasting time, and resources. There needs to be a greater understanding of the design parameters for more accurate testing, such as sensor selection, sensor placement, ambient noise sources, and system operations. The current study, therefore, delineates design parameters for design leak diagnosis experiments for lab, testbed, and real networks. For application in real water networks, expert opinion is used to help identify the benefits and limitations and the implementation issues of available sensing technologies. An example experiment design using multi‐sensing technologies for smart leak diagnostics in Hong Kong is also presented. The study can guide water practitioners and researchers to design a multi‐sensing leak diagnostic experiments enabling a smart and sustainable utility management.This article is categorized under: Engineering Water > Methods Engineering Water > Sustainable Engineering of Water Science of Water > Water Extremes

show abstract

Section: Sensing System Working Principle Examplesmentioning

confidence: 99%

State‐of‐the‐art review of leak diagnostic experiments: Toward a smart water network

Bakhtawar

Zayed

2023

WIREs Water

View full text Add to dashboard Cite

show abstract

“…Guo, C., K. Shi, and X. Chu. on the other hand, have conducted their experiment on buried pipe using an optical fiber hydrophone and established a correlation between water leakage and distance using time delay [15]. Hydrophones are bulky and Xu et al and Phua et al have addressed this issue by developing a small hydrophone based on MEMS (micro electro mechanical sensor) technology [16,35].…”

Section: Related Workmentioning

confidence: 99%

“…The development of advanced microprocessors and improved signal-processing techniques are likely to result in a substantial boost in automation in the area of leak detection methods. Although researchers are using a wide range of sensors to collect data, accelerometer [12][13][14], acoustic sensor [15,16], flow [17][18][19][20], and pressure [21] sensor categories dominate the study area. Vibration sensors or their derivatives, such as accelerometers and acoustic sensors, are the number one choice for leakage detection and location research.…”

Section: Introductionmentioning

confidence: 99%

An Intelligent IoT and ML-Based Water Leakage Detection System

Islam,

Azam,

Shanmugam

et al. 2023

IEEE Access

View full text Add to dashboard Cite

Water is a precious resource, and much of it is wasted due to the leakage of pipelines. Timely identification of leakage could curb the wastage. Traditional leakage detection methods are time-consuming, inefficient and cause substantial water loss. Onsite, real-time leakage detection could reduce water loss and mitigate associated environmental and economic impacts. In this paper, we have proposed and developed an edge ML-based low-power IoT device to detect water leakage and notify the user. We developed the device in three stages. At first, an experiment was set up to capture real-life audio data of leak and non-leak signals.A piezoelectric contact microphone was used to capture the audio signals and to keep the unwanted environmental noise minimal. In the second step, an ML model was developed. The ML model was then quantized and pruned, resulting in a lightweight model of 11 KB in size with 98.96% accuracy. Finally, a node was implemented with an ML model and radio communication capability. If it detect ed any leakage, the node started beeping noise and broadcasting low-energy RF messages. The primary node could alert the user of potential leakage. These sensor nodes could be set up in the home or industrial environment. The device's maximum current draw was 216.8 mA while transmitting data, and the minimum current draw was only 5.46 mA while sleeping. The node could run for more than 25 days on a single 3500 mAh battery.INDEX TERMS Water leakage detection, internet of things (IoT), machine learning (ML), Sensor Networks, edge IoT.

show abstract

“…PVDF’s flexibility is a standout feature, allowing it to seamlessly adapt to diverse pipe configurations and shapes. It excels in establishing conformal contact with the intricate surfaces of plastic pipes [ 30 , 31 , 32 ]. This adaptability significantly enhances its potential for detecting leaks in various installation scenarios, making it a valuable addition to our study.…”

Section: Introductionmentioning

confidence: 99%

Comparative Study of Leak Detection in PVC Water Pipes Using Ceramic, Polymer, and Surface Acoustic Wave Sensors

Hamamed,

Mechri,

Mhammedi

et al. 2023

Sensors

View full text Add to dashboard Cite

The detection and location of pipeline leakage can be deduced from the time arrival leak signals measured by acoustic sensors placed at the pipe. Ongoing research in this field is primarily focused on refining techniques for accurately estimating the time delays. This enhancement predominantly revolves around the application of advanced signal processing methods. Additionally, researchers are actively immersed in the utilization of machine learning approaches on vibro-acoustic data files, to determine the presence or absence of leaks. Less attention has been given to evaluating the sensitivity, performance, and overall effectiveness of these sensors in leak detection; although acoustic methods have been successfully used for leak detection in metallic pipes, they are less effective in plastic pipes due to the high attenuation of leak noise signals. The primary thrust of this research centers on identifying sensors that not only possess sensitivity but also exhibit high efficiency. To accomplish this goal, we conducted an exhaustive evaluation of the performance of three distinct categories of acoustic sensors employed for detecting water leaks in plastic pipes: specifically, lead zirconate titanate (PZT) sensors, polyvinylidene fluoride (PVDF) sensors, and surface acoustic wave (SAW) sensors. Our evaluation encompassed the performance of PVDF and SAW sensors in leak detection, comparing them to PZT sensors under a variety of conditions, including different leak sizes, flow rates, and distances from the leak. The results showed that all three sensors, when they were placed in the same position, were able to detect water leaks in plastic pipes with different sensitivities. For small leaks (1 mm, 2 mm), the PVDF sensor showed the greatest sensitivity (0.4 dB/L/h, 0.33 dB/L/h), followed by the SAW sensor (0.16 dB/L/h, 0.14 dB/L/h), and finally the PZT (0.13 dB/L/h, 0.12 dB/L/h). Similarly, for larger leaks (4 mm, 10 mm), the PVDF sensor continued to show superior sensitivity (0.2 dB/L/h, 0.17 dB/L/h), followed by the SAW sensor (0.13 dB/L/h, 0.11), and finally the PZT sensor (0.12 dB/L/h, 0.1 dB/L/h), outperforming the PZT sensor. This suggests that SAW and PVDF sensors, have the potential to serve as valuable, cost-effective alternatives to traditional commercial leak noise transducers. The outcomes of this comparative study involving three acoustic sensors hold the potential to advance the development of robust and dependable systems for the detection of water leaks in plastic pipelines.

show abstract

Cross-correlation analysis of multiple fibre optic hydrophones for water pipeline leakage detection

Cited by 16 publications

References 38 publications

State‐of‐the‐art review of leak diagnostic experiments: Toward a smart water network

State‐of‐the‐art review of leak diagnostic experiments: Toward a smart water network

An Intelligent IoT and ML-Based Water Leakage Detection System

Comparative Study of Leak Detection in PVC Water Pipes Using Ceramic, Polymer, and Surface Acoustic Wave Sensors

Contact Info

Product

Resources

About