Characterization of Industrial Coolant Fluids and Continuous Ageing Monitoring by Wireless Node—Enabled Fiber Optic Sensors

Sachat, Alexandros El; Meristoudi, Anastasia; Markos, Christos; Sakellariou, A.; Papadopoulos, Aggelos; Katsikas, Serafeim; Riziotis, Christos

doi:10.3390/s17030568

Cited by 13 publications

(10 citation statements)

References 42 publications

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“…To increase the pH sensitivity level, extra biasing voltage was provided. Another fiber-sensor reported in [ 20 ] was adopted to monitor the aging of the industrial coolant fluids by detecting their pH values. Md.…”

Section: Introductionmentioning

confidence: 99%

A Highly Birefringent Photonic Crystal Fiber for Terahertz Spectroscopic Chemical Sensing

Yang

Zhang

Shi

et al. 2021

Sensors

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A photonic crystal fiber (PCF) with high relative sensitivity was designed and investigated for the detection of chemical analytes in the terahertz (THz) regime. To ease the complexity, an extremely simple cladding employing four struts is adopted, which forms a rectangular shaped core area for filling with analytes. Results of enormous simulations indicate that a minimum 87.8% relative chemical sensitivity with low confinement and effective material absorption losses can be obtained for any kind of analyte, e.g., HCN (1.26), water (1.33), ethanol (1.35), KCN (1.41), or cocaine (1.50), whose refractive index falls in the range of 1.2 to 1.5. Besides, the PCF can also achieve high birefringence (∼0.01), low and flat dispersion, a large effective modal area, and a large numerical aperture within the investigated frequency range from 0.5 to 1.5 THz. We believe that the proposed PCF can be applied to chemical sensing of liquid and THz systems requiring wide-band polarization-maintaining transmission and low attenuation.

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Section: Introductionmentioning

confidence: 99%

A Highly Birefringent Photonic Crystal Fiber for Terahertz Spectroscopic Chemical Sensing

Yang

Zhang

Shi

et al. 2021

Sensors

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“…The research fields regarding maintenance cost reduction include periodic inspections, corrective maintenance, and condition monitoring. [5]. Condition monitoring is normally used on rotating machinery, so it is very suitable for monitoring wind turbines [6].…”

Section: Introductionmentioning

confidence: 99%

Machine Learning for Long Cycle Maintenance Prediction of Wind Turbine

Yeh

Lin

et al. 2019

Sensors

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Within Internet of Things (IoT) sensors, the challenge is how to dig out the potentially valuable information from the collected data to support decision making. This paper proposes a method based on machine learning to predict long cycle maintenance time of wind turbines for efficient management in the power company. Long cycle maintenance time prediction makes the power company operate wind turbines as cost-effectively as possible to maximize the profit. Sensor data including operation data, maintenance time data, and event codes are collected from 31 wind turbines in two wind farms. Data aggregation is performed to filter out some errors and get significant information from the data. Then, the hybrid network is built to train the predictive model based on the convolutional neural network (CNN) and support vector machine (SVM). The experimental results show that the prediction of the proposed method reaches high accuracy, which helps drive up the efficiency of wind turbine maintenance.

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“…Condition monitoring [1] is an emerging engineering area which is developing rapidly with the help of available sensing technologies, providing the means for efficient asset management and predictive maintenance in industry and infrastructures [2]. In this context, structural health monitoring (SHM) is of great importance for the management of physical infrastructures, also providing information for early damage prognosis [3].…”

Section: Introductionmentioning

confidence: 99%

A Low-Cost Phase-OTDR System for Structural Health Monitoring: Design and Instrumentation

2019

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The design, development, and testing of a low-cost phase optical time-domain reflectometry (Phase-OTDR) system, intended for use in structural health monitoring (SHM) applications, are presented. Phase-OTDR is a technology that is growing and evolving at an impressive rate. Systems based on this principle are becoming very sensitive and elaborate and can perform very accurate condition monitoring, but at the same time, they are critically alignment-dependent and prohibitively costly to be considered as viable options in real field applications. Certain Phase-OTDR systems have been applied in real field studies, but these examples are mostly a proof-of-concept. The system presented here is the result of a compromise between performance and cost, using commercial components, specifically combined and tuned for SHM applications. The design and implementation of all the electronic and optoelectronic steps are presented, and the operation of the system is demonstrated, achieving a spatial resolution of ~6 m over 5 km. This work provides useful engineering guidelines for the low-cost implementation of Phase-OTDR systems. It is anticipated that the affordable development of such interrogation systems will promote their use in a wide range of SHM applications with moderate monitoring requirements and will assist the penetration of Phase-OTDR technology in the industry.

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Characterization of Industrial Coolant Fluids and Continuous Ageing Monitoring by Wireless Node—Enabled Fiber Optic Sensors

Cited by 13 publications

References 42 publications

A Highly Birefringent Photonic Crystal Fiber for Terahertz Spectroscopic Chemical Sensing

A Highly Birefringent Photonic Crystal Fiber for Terahertz Spectroscopic Chemical Sensing

Machine Learning for Long Cycle Maintenance Prediction of Wind Turbine

A Low-Cost Phase-OTDR System for Structural Health Monitoring: Design and Instrumentation

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