Fiber Bragg grating (FBG) sensors have attracted a considerable amount of interest for their superior characteristics. However, the FBG sensors made on bare fibers are easily damaged. For their safe use in engineering, the glass core of optical fibers is coated with softer low modulus protective coatings. A portion of the host material strain is absorbed by the protective coatings when the strain transfers from the host material to the fiber core, and hence only a segment of structural strain is sensed. By introducing the shear modulus of the host material, a novel analytical model is developed for evaluating the sensing strain of the embedded FBG sensors in composite structures based on the strain in a host material. The average strain transfer ratio is deduced to describe the percentage transferred to the optical fiber core from the host material. It is concluded that the shear modulus of the host material influences strain transmission, especially when it is much lower than the modulus of the fiber cor...

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.

Pipelines are widely used for the transport of a large variety of fluids, such as natural gas, across long distances. While pipelines provide a convenient mode of transportation of fluids, their safe usage is one of the foremost concerns especially if their contents are harmful to the environment or if the hosting area is prone to third-party intrusions. Thus, rapid detection and localization of pipeline leakage is paramount to the minimization of damage brought to the environment and stakeholders in the event of an unexpected leakage. In this work, a novel hoop strain based negative pressure wave (NPW) approach was used to detect and localize pipeline leakages in a 180 ft PVC pipeline equipped with five manually controllable leakage points. Using the new approach, both the arrival time of the NPW and the energy attenuation profile of the NPW can be used to detect and localize leakages with higher accuracy and in a wider variety of situations. The time of arrival approach allowed accurate (within 7.33% error) and repeatable localization of the leakage points; however, using the energy attenuation of the NPW, leakages with low leakage rates (<5 lpm) can also be detected, albeit at the cost of inaccuracies at the inlet and outlet of the pipeline (8.3% error in the ends vs. 4.3% error in the body). Copyright © 2014 John Wiley & Sons, Ltd.

Pipeline leakage and corrosion are two serious threats to pipeline safety operation. Therefore, to ensure the safety operation of long-distance pipeline, it is of great significance to conduct pipeline monitoring. Since hoop strain is an effective indicator to reflect the inner pressure fluctuation and the wall thickness reduction of the pipeline, a method of monitoring leakage and corrosion simultaneously was proposed based on hoop strain measurement. In order to test the hoop strain variation, this paper introduces a fiber Bragg grating (FBG) strain hoop sensor. To verify the monitoring method and the performance of this FBG strain sensor, a pipeline leakage simulation experiment and corrosion simulation experiment were conducted on an actual pipeline and a polyvinyl chloride (PVC) pipe model, respectively. The experimental results demonstrate that the pipeline leakage and corrosion can be detected by the FBG hoop strain sensor. The FBG strain hoop sensor is a promising device in pipeline safety monitoring.