Experimental study on leak detection and location for gas pipeline based on acoustic method

Meng, Lexuan; Li, Yuxing; Wang, Wuchang; Fu, Juntao

doi:10.1016/j.jlp.2011.07.001

Cited by 182 publications

(54 citation statements)

References 5 publications

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“…These researches can be categorized into two main groups: leakage detection location and calculation its amount. In the case of leakage detection, some methods and studies for gas pipeline leak detection have been developed in recent studies [8][9][10][11][12].…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Correlations for estimating natural gas leakage from above-ground and buried urban distribution pipelines

Ebrahimi‐Moghadam

Farzaneh–Gord

Deymi–Dashtebayaz

2016

Journal of Natural Gas Science and Engineering

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Section: Accepted Manuscriptmentioning

confidence: 99%

Correlations for estimating natural gas leakage from above-ground and buried urban distribution pipelines

Ebrahimi‐Moghadam

Farzaneh–Gord

Deymi–Dashtebayaz

2016

Journal of Natural Gas Science and Engineering

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“…The spectroscopic technique based on these transitions is called molecular vibration spectroscopy. If the energy of the electromagnetic wave equals the molecular energy level of the material [18], the electromagnetic wave can be absorbed, thereby causing an electronic state transition. Thus, IR irradiation may cause a molecular vibration energy level transition as long as condition (1) is satisfied:

E_{IR} = Δ E_{molecular vibration}

…”

Section: Principlesmentioning

confidence: 99%

Development of an Optical Gas Leak Sensor for Detecting Ethylene, Dimethyl Ether and Methane

Tan

Pei

Zhu³

et al. 2013

Sensors

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In this paper, we present an approach to develop an optical gas leak sensor that can be used to measure ethylene, dimethyl ether, and methane. The sensor is designed based on the principles of IR absorption spectrum detection, and comprises two crossed elliptical surfaces with a folded reflection-type optical path. We first analyze the optical path and the use of this structure to design a miniature gas sensor. The proposed sensor includes two detectors (one to acquire the reference signal and the other for the response signal), the light source, and the filter, all of which are integrated in a miniature gold-plated chamber. We also designed a signal detection device to extract the sensor signal and a microprocessor to calculate and control the entire process. The produced sensor prototype had an accuracy of ±0.05%. Experiments which simulate the transportation of hazardous chemicals demonstrated that the developed sensor exhibited a good dynamic response and adequately met technical requirements.

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“…Recent innovations on pipeline leak detection techniques can be classified into two categories: new sensors and new algorithms. From the aspect of the sensor, some novel sensing techniques are used to detect the pipeline fault due to higher sensitivity and reliability, like fiber optic sensing [1,2], wireless sensor networks [3,4] and the acoustic method [5,6]. Among these techniques, fiber optic sensors emerged as the most appropriate for long distance pipelines with no potential safety hazard compared with traditional electrical gauges.…”

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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Experimental study on leak detection and location for gas pipeline based on acoustic method

Cited by 182 publications

References 5 publications

Correlations for estimating natural gas leakage from above-ground and buried urban distribution pipelines

Correlations for estimating natural gas leakage from above-ground and buried urban distribution pipelines

Development of an Optical Gas Leak Sensor for Detecting Ethylene, Dimethyl Ether and Methane

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

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