Optical Multimode Fiber-Based Pipe Leakage Sensor Using Speckle Pattern Analysis

Water is an invaluable resource quickly becoming scarce in many parts of the world. Therefore, the importance of efficiency in water supply and distribution has greatly increased. Some of the main tools for limiting losses in supply and distribution networks are leakage sensors that enable real-time...
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Gespeichert in:

Autor*in:	Jonathan Philosof [verfasserIn] Yevgeny Beiderman [verfasserIn] Sergey Agdarov [verfasserIn] Yafim Beiderman [verfasserIn] Zeev Zalevsky [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	speckle pattern optic fiber sensor machine learning (ML) leak detection

Übergeordnetes Werk:	In: Sensors - MDPI AG, 2003, 23(2023), 8634, p 8634
Übergeordnetes Werk:	volume:23 ; year:2023 ; number:8634, p 8634

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/s23208634

Katalog-ID:	DOAJ093078579

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callnumber-first	T - Technology
author	Jonathan Philosof
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topic_title	TP1-1185 Optical Multimode Fiber-Based Pipe Leakage Sensor Using Speckle Pattern Analysis speckle pattern optic fiber sensor machine learning (ML) leak detection
topic	misc TP1-1185 misc speckle pattern misc optic fiber sensor misc machine learning (ML) misc leak detection misc Chemical technology
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title	Optical Multimode Fiber-Based Pipe Leakage Sensor Using Speckle Pattern Analysis
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title_sort	optical multimode fiber-based pipe leakage sensor using speckle pattern analysis
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title_auth	Optical Multimode Fiber-Based Pipe Leakage Sensor Using Speckle Pattern Analysis
abstract	Water is an invaluable resource quickly becoming scarce in many parts of the world. Therefore, the importance of efficiency in water supply and distribution has greatly increased. Some of the main tools for limiting losses in supply and distribution networks are leakage sensors that enable real-time monitoring. With fiber optics recently becoming a commodity, along with the sound advances in computing power and its miniaturization, multipurpose sensors relying on these technologies have gradually become common. In this study, we explore the development and testing of a multimode optic-fiber-based pipe monitoring and leakage detector based on statistical and machine learning analyses of speckle patterns captured from the fiber’s outlet by a defocused camera. The sensor was placed inside or over a PVC pipe with covered and exposed core configurations, while 2 to 8 mm diameter pipe leaks were simulated under varied water flow and pressure. We found an overall leak size determination accuracy of 75.8% for a 400 µm covered fiber and of 68.3% for a 400 µm exposed fiber and demonstrated that our sensor detected pipe bursts, outside interventions, and shocks. This result was consistent for the sensors fixed inside and outside the pipe with both covered and exposed fibers.
abstractGer	Water is an invaluable resource quickly becoming scarce in many parts of the world. Therefore, the importance of efficiency in water supply and distribution has greatly increased. Some of the main tools for limiting losses in supply and distribution networks are leakage sensors that enable real-time monitoring. With fiber optics recently becoming a commodity, along with the sound advances in computing power and its miniaturization, multipurpose sensors relying on these technologies have gradually become common. In this study, we explore the development and testing of a multimode optic-fiber-based pipe monitoring and leakage detector based on statistical and machine learning analyses of speckle patterns captured from the fiber’s outlet by a defocused camera. The sensor was placed inside or over a PVC pipe with covered and exposed core configurations, while 2 to 8 mm diameter pipe leaks were simulated under varied water flow and pressure. We found an overall leak size determination accuracy of 75.8% for a 400 µm covered fiber and of 68.3% for a 400 µm exposed fiber and demonstrated that our sensor detected pipe bursts, outside interventions, and shocks. This result was consistent for the sensors fixed inside and outside the pipe with both covered and exposed fibers.
abstract_unstemmed	Water is an invaluable resource quickly becoming scarce in many parts of the world. Therefore, the importance of efficiency in water supply and distribution has greatly increased. Some of the main tools for limiting losses in supply and distribution networks are leakage sensors that enable real-time monitoring. With fiber optics recently becoming a commodity, along with the sound advances in computing power and its miniaturization, multipurpose sensors relying on these technologies have gradually become common. In this study, we explore the development and testing of a multimode optic-fiber-based pipe monitoring and leakage detector based on statistical and machine learning analyses of speckle patterns captured from the fiber’s outlet by a defocused camera. The sensor was placed inside or over a PVC pipe with covered and exposed core configurations, while 2 to 8 mm diameter pipe leaks were simulated under varied water flow and pressure. We found an overall leak size determination accuracy of 75.8% for a 400 µm covered fiber and of 68.3% for a 400 µm exposed fiber and demonstrated that our sensor detected pipe bursts, outside interventions, and shocks. This result was consistent for the sensors fixed inside and outside the pipe with both covered and exposed fibers.
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title_short	Optical Multimode Fiber-Based Pipe Leakage Sensor Using Speckle Pattern Analysis
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Optical Multimode Fiber-Based Pipe Leakage Sensor Using Speckle Pattern Analysis

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