Water Pipeline Leak Measurement Using Wavelet Packet-based Adaptive ICA

Kothandaraman, Mohanaprasad; Law, Zijian; Morris, Ezra; Pua, Chang Hong; Rajasekaran, Uma

doi:10.1007/s11269-022-03119-y

Cited by 10 publications

(2 citation statements)

References 25 publications

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“…This method gave a leak localization accuracy of 96.47%. Furthermore, to improve the leak localization's accuracy, Kothandaramam et al implemented a wavelet packet decomposition along with Adaptive ICA [16]. This method was again for water pipelines with two Acousto-optic sensors.…”

Section: Introductionmentioning

confidence: 99%

A Novel Custom One-Dimensional Time-Series DenseNet for Water Pipeline Leak Detection and Localization Using Acousto-Optic Sensor

Rajasekaran,

Kothandaraman

2024

IEEE Access

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A crucial component within any structural health monitoring system is a pipeline leak detection mechanism, which is vital for preventing avoidable water loss. Contemporary literature employs machine learning and deep learning for detecting pipeline leaks and cross-correlation for leak localization. The major drawbacks in the existing methodologies are that machine learning and deep learning methods need two different architectures for leak detection and localization, and the cross-correlation needs two sensors with a denoising technique. The primary objective of this paper is to deploy a unified architecture capable of executing both the detection and localization of a leak without any denoising technique and with a single sensor. The proposed technique utilizes the data collected using an Acousto-optic sensor with two different pressures. This paper proposes a novel custom one-dimensional time-series DenseNet for leak detection and localization. The proposed method gives better accuracies compared with the existing onedimensional DenseNet-121, three different one-dimensional convolutional neural networks (1DCNN), and cross-correlation for two different pressure datasets. The proposed method's processing time is thirteen times less than the existing one-dimensional DenseNet-121, with the observed average leak detection and localization accuracy of 99.08%. The results state that the proposed novel custom one-dimensional timeseries DenseNet accurately detects and localizes the leak with less time.

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Section: Introductionmentioning

confidence: 99%

A Novel Custom One-Dimensional Time-Series DenseNet for Water Pipeline Leak Detection and Localization Using Acousto-Optic Sensor

Rajasekaran,

Kothandaraman

2024

IEEE Access

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“…For example, detecting leaks in drainage pipes [9], cavity defects in the shallow subsurface [10], the enclosed underground sewerage pipe spaces [11], and early cracking of cement concrete pavements [12,13]. Techniques for detecting structural deterioration of water mains can determine their current condition, including their structural health, impact on water quality, and hydraulic capacity [4,14]. GPR can potentially identify leaks in buried water pipes either by detecting underground voids created by the leaking water or by detecting anomalies in the depth of the pipe as the radar propagation velocity changes due to soil saturation with leaking water [15].…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of Three-Channel Drainage Pipeline Ground Penetrating Radar Device

Yang

Yan

2023

Sensors

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In order to solve the current problems that conventional video inspection can only detect, as an internal pipeline defect and drainage pipeline radar inspection device detects in a single direction and at radar frequency in water pipeline defect detection, a three-channel drainage pipeline ground penetrating radar (GPR) inspection device was designed and developed, the assembly and commissioning of the device prototype were completed, and an actual engineering test application was carried out. Focusing on the problem that the detection direction and depth of the single-channel detection device are limited, a three-channel drainage pipeline GPR inspection device is designed to realize the synchronous detection of the inside of the pipeline, the pipeline body, and the external environment of the pipeline, improving the detection depth and efficiency. According to the design scheme of the three-channel drainage pipeline GPR inspection device, the assembly of the device prototype was completed. The device contains three radar channels, the top of the main frequency of the antenna is 1.4 GHz, the two sides are 750 MHz, the video camera has a pixel count of 4 million, and the positioning accuracy is less than 1 mm, the waterproof grade is IP68, the detection accuracy of pipe deformation (slope) is 0.1°, the detection depth outside the pipe is 1.2 m, and the detection accuracy of corrosion thickness is 15 mm. In a practical application of the device, the Jianguomenqiao sewage pipeline in Beijing, China, was tested, resulting in the discovery of 87 defects, including 39 loose soil areas at the bottom of the pipe exterior, 40 void areas, and 8 cavities.

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Pressure-driven Background Leakage Models and their Application for Leak Localization Using a Multi-population Genetic Algorithm

Guan

Dong

2022

Water Resour Manage

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Water Pipeline Leak Measurement Using Wavelet Packet-based Adaptive ICA

Cited by 10 publications

References 25 publications

A Novel Custom One-Dimensional Time-Series DenseNet for Water Pipeline Leak Detection and Localization Using Acousto-Optic Sensor

A Novel Custom One-Dimensional Time-Series DenseNet for Water Pipeline Leak Detection and Localization Using Acousto-Optic Sensor

Design and Implementation of Three-Channel Drainage Pipeline Ground Penetrating Radar Device

Pressure-driven Background Leakage Models and their Application for Leak Localization Using a Multi-population Genetic Algorithm

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