Recent applications of fiber optic sensors to health monitoring in civil engineering

Li, Hong‐Nan; Li, Dongsheng; Song, Gangbing

doi:10.1016/j.engstruct.2004.05.018

Cited by 768 publications

(447 citation statements)

References 44 publications

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“…Optical fibers are widely applied in various sensing systems, owing to the excellent properties, such as small dimensions, flexibility, embeddability, high temperature endurance, dielectric nature, immunity to corrosion, as compared with traditional sensors, and being light weight [1]. Optical fiber sensors have been developed to measure a variety of physical quantities such as strain, temperature and vibration.…”

Section: Introductionmentioning

confidence: 99%

The Effects of Adhesive and Bonding Length on the Strain Transfer of Optical Fiber Sensors

Her

Huang

2016

Applied Sciences

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Optical fiber sensors have been extensively adapted as structural health monitoring devices. Due to the existence of the adhesive layer, a portion of the strain is absorbed by the adhesive. As a result, the structural strain sensed by the optical fiber is underestimated and required to be corrected. An analytical solution is presented through which it is possible to establish the relationship between the strains in the host structure and the surface bonded optical fiber sensor. Experimental measurements based on the Mach-Zehnder interferometric technique were performed to validate the theoretical prediction and reveal the differential strains between the optical fiber strain sensor and test specimen. Parametric studies show that the percentage of the strain in the test specimen actually transferred to the optical fiber is dependent on the bonding length of the optical fiber and the adhesive. The strain transfer is increasing from 56% to 82% as the bonding length increases from 5 cm to 12 cm with the epoxy adhesive. The general trend of the strain transfer obtained from both experimental tests and theoretical predictions shows that the longer the bonding length and the stiffer the adhesive, the more strain is transferred to the optical fiber.

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Section: Introductionmentioning

confidence: 99%

The Effects of Adhesive and Bonding Length on the Strain Transfer of Optical Fiber Sensors

Her

Huang

2016

Applied Sciences

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“…In [9], FOS has been used for monitoring the chloride penetration in a bridge spanning 67 m long. In [10][11][12][13][14], FOS has been used for chloride limit monitoring. Figure 1 shows corrosion in steel due to chloride attack [33].…”

Section: Theoretical Background 31 Corrosion Processmentioning

confidence: 99%

Threshold-based Energy Efficient Clustering Protocol for Corrosion Risk Monitoring of Reinforced Concrete

Senniappan¹,

Subramanian²

2017

IJCA

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In recent years, wireless sensor networks (WSN) are being used by a wide range of applications. Sensor nodes are used for gathering data about the various physical parameters of the system under study. As sensor nodes are battery powered, energy efficiency is an important challenge faced by WSN. Clustering is a technique for improving the energy efficiency of the sensor network. The reported piece of work uses the soft computing technique, Biogeography-Based Krill Herd Algorithm (BBKH) for energy efficient clustering that results in improving the network lifetime. While cluster heads are selected, the rate adjustment is made for congestion mitigation. Likewise, a threshold based data forwarding method is also employed for further improvement of the network lifetime. Based on threshold principle, sending of similarly sensed data repeatedly is avoided. The network lifetime is compared before and later on using the threshold value. The obtained results after using the threshold concept are 18.80 % better than its threshold free counterpart. The proposed method is used in structural health monitoring (SHM) application where the corrosion risk is monitored in the reinforced concrete structures.

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“…Fiber optic sensors, with the advantages of immunity to electromagnetic interference, high accuracy and multiplexibility, are now widely used to detect pipeline fault since there are many probable dangers related to gas or liquid pipelines [12,13]. A novel FBG hoop strain sensor has been developed and encapsulated in our lab to measure the pipeline hoop strain variation induced by leaks or other pressure drop cases [14,15].…”

Section: Introductionmentioning

confidence: 99%

Pipeline Leak Localization Based on FBG Hoop Strain Sensors Combined with BP Neural Network

Jia

Ren

et al. 2018

Applied Sciences

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Featured Application: A pipeline leakage localization method using self-developed FBG hoop strain sensors combined with BP neural network is proposed and validated. Abstract: Pipelines function as blood vessels serving to bring life-necessities, so their safe usage is one of the foremost concerns. In our previous work, a fiber Bragg grating (FBG) hoop strain sensor with enhanced sensitivity was developed to measure the pressure drop induced by pipeline leakage. Some hoop strain information during the leakage transient process can be extracted from the amount of FBG hoop strain sensors set along the pipeline. In this paper, an integrated approach of a back-propagation (BP) neural network and hoop strain measurement is first proposed to locate the leak points of the pipeline. Five hoop strain variations are employed as input neurons to achieve pattern recognition so as to predict the leakage point. The RMS error can be as low as 1.01% when choosing appropriate hidden layer neurons. Furthermore, the influence of noise on the network's performance is investigated through superimposing Gaussian noise with a different level. The results demonstrate the feasibility and robustness of the neural network for pipeline leakage localization.

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Recent applications of fiber optic sensors to health monitoring in civil engineering

Cited by 768 publications

References 44 publications

The Effects of Adhesive and Bonding Length on the Strain Transfer of Optical Fiber Sensors

The Effects of Adhesive and Bonding Length on the Strain Transfer of Optical Fiber Sensors

Threshold-based Energy Efficient Clustering Protocol for Corrosion Risk Monitoring of Reinforced Concrete

Pipeline Leak Localization Based on FBG Hoop Strain Sensors Combined with BP Neural Network

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