Pipeline Monitoring Using Highly Sensitive Vibration Sensor Based on Fiber Ring Cavity Laser

Lalam, Nageswara; Lü, Ping; Venketeswaran, Abhishek; Buric, Michael

doi:10.3390/s21062078

Cited by 12 publications

(10 citation statements)

References 19 publications

(15 reference statements)

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“…In recent years, acoustic emission monitoring based on optical fiber sensors gained a lot of attention for pipeline monitoring applications due to their high sensitivity, small size, large dynamic range, immunity to electromagnetic interference, and ability to withstand harsh environments. Several discrete fiber optic acoustic sensors are developed for pipeline monitoring such as fiber ring cavity laser [1], fiber Bragg grating (FBG) [2], and long-period grating (LPG) [3]. However, fabrication of both the FBG and LPG sensors requires expensive equipment such as an excimer laser or CO2 laser, which makes the sensor system more expensive and complex.…”

Section: Introductionmentioning

confidence: 99%

Field-testing of water pipeline flow monitoring based on SMS fiber optic acoustic sensor

Lalam¹,

Grainger

Ohodnicki

et al. 2023

Optical Waveguide and Laser Sensors II

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In this paper, we field demonstrate a water pipeline flow detection based on a simple, low-cost, and highly sensitive fiber optic acoustic sensor. The fiber acoustic sensor consists of a multimode interference effect in a single-mode-multimodesingle-mode (SMS) fiber structure. In the field test, we mounted an SMS fiber sensor on a 6" diameter water pipeline, where water flow is precisely controlled by a variable frequency driver (ABB-ACQ580 sensor-less drive). The experimental results indicate that the proposed SMS fiber acoustic sensor can be effectively applied for practical applications of pipeline flow monitoring and identify leak detection with high sensitivity and accuracy.

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Section: Introductionmentioning

confidence: 99%

Field-testing of water pipeline flow monitoring based on SMS fiber optic acoustic sensor

Lalam¹,

Grainger

Ohodnicki

et al. 2023

Optical Waveguide and Laser Sensors II

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show abstract

“…Intelligent methods can detect and analyze various information on the pipeline and are very important. The intelligent methods used in pipelines are typically based on acoustic emission (AE) signals [ 3 , 4 ]. A leak in a pipeline is an AE signal source reflecting negative pressure waves, which can be used to measure industrial pipelines in a real-time transient model using intelligent methods.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Leak Localization Approach Using Acoustic Emission for Industrial Pipelines

Gao

Piltan

Kim

2022

Sensors

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Acoustic emission techniques are widely used to monitor industrial pipelines. Intelligent methods using acoustic emission signals can analyze acoustic waves and provide important information for leak detection and localization. To address safety and protect the operation of industrial pipelines, a novel hybrid approach based on acoustic emission signals is proposed to achieve reliable leak localization. The proposed method employs minimum entropy deconvolution using the maximization kurtosis norm of acoustic emission signals to remove noise and identify important feature signals. In addition, the damping frequency energy based on the dynamic differential equation with damping term is designed to extract important energy information, and a smooth envelope for the feature signals over time is generated. The zero crossing tracks the arrival time via the envelope changes and identifies the time difference of the acoustic waves from the two channels, each of which is installed at the end of a pipeline. Finally, the time data are combined with the velocity data to localize the leak. The proposed approach has better performance than the existing generalized cross-correlation and empirical mode decomposition combined with the generalized cross-correlation methods, providing proper leak localization in the industrial pipeline.

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“…Information about the technical state of a given device has vital importance in many systems' functioning [1,2] and is a subject of meticulous research conducted by numerous academic institutions [3][4][5][6]. There are many diagnostic systems based on vibration measurement using a laser sensor [7,8], classical piezoelectric accelerometers [9,10], shape-memory sensors [11,12], and fiber optic solutions [13,14]. Very interesting results might be acquired by utilizing the elastoacoustic effect [15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Predictive Maintenance Neural Control Algorithm for Defect Detection of the Power Plants Rotating Machines Using Augmented Reality Goggles

Lalik

Wątorek

2021

Energies

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The concept of predictive and preventive maintenance and constant monitoring of the technical condition of industrial machinery is currently being greatly improved by the development of artificial intelligence and deep learning algorithms in particular. The advancement of such methods can vastly improve the overall effectiveness and efficiency of systems designed for wear analysis and detection of vibrations that can indicate changes in the physical structure of the industrial components such as bearings, motor shafts, and housing, as well as other parts involved in rotary movement. Recently this concept was also adapted to the field of renewable energy and the automotive industry. The core of the presented prototype is an innovative interface interconnected with augmented reality (AR). The proposed integration of AR goggles allowed for constructing a platform that could acquire data used in rotary components technical evaluation and that could enable direct interaction with the user. The presented platform allows for the utilization of artificial intelligence to analyze vibrations generated by the rotary drive system to determine the technical condition of a wind turbine model monitored by an image processing system that measures frequencies generated by the machine.

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Pipeline Monitoring Using Highly Sensitive Vibration Sensor Based on Fiber Ring Cavity Laser

Cited by 12 publications

References 19 publications

Field-testing of water pipeline flow monitoring based on SMS fiber optic acoustic sensor

Field-testing of water pipeline flow monitoring based on SMS fiber optic acoustic sensor

A Hybrid Leak Localization Approach Using Acoustic Emission for Industrial Pipelines

Predictive Maintenance Neural Control Algorithm for Defect Detection of the Power Plants Rotating Machines Using Augmented Reality Goggles

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