Fiber Bragg grating sensor for petroleum hydrocarbon leak detection

Spirin, V. V.; Shlyagin, Mikhail G.; Miridonov, Serguei V.; Jimenez, F.J Mendieta; Gutiérrez, Rebeca

doi:10.1016/s0143-8166(00)00021-x

Cited by 47 publications

(18 citation statements)

References 5 publications

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“…The swelling behavior of the polymer produces an increase in the physical dimensions of the material, which can be readily converted to a mechanical response. Our study shows that butyl rubber can increase its volume by more than 2 times under gasoline influence (Spirin et al, 2000;Lopez et al, 2004). Furthermore, its behavior is reversible, i.e.…”

Section: Gasoline Leak Detection and Localizationmentioning

confidence: 48%

Autonomous Measurement System for Localization of Loss-Induced Perturbation Based on Transmission-Reflection Analysis

Vasily¹

2010

Advances in Measurement Systems

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Section: Gasoline Leak Detection and Localizationmentioning

confidence: 48%

Autonomous Measurement System for Localization of Loss-Induced Perturbation Based on Transmission-Reflection Analysis

Vasily¹

2010

Advances in Measurement Systems

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“…Therefore, by considering the state variables definition in (7), that is Q a (z,t) = Q(z,t) and Q a (z,t) = Q(z,t)t + F(x(t)), (11) can be rewrite in a state-space form as follows:…”

Section: Liénard-type Model For Pipelinesmentioning

confidence: 99%

“…There are different methods for leak monitoring which, according to the American Petroleum Institute [1], can be externally based LMS or internally based LMS. The first ones use a specific set of field instrumentation (e.g., sensing cables [2], [3], acoustic sensors [4], laser sensors [5], vapor sensors [6], fiber-optic cables [7], infrared radiometers or thermal cameras [8]) to monitor external pipeline parameters. While the latter use field instrumentation (e.g., flow or pressure sensors [9], [10]) to monitor internal pipeline parameters.…”

Section: Introductionmentioning

confidence: 99%

Development of a Tool for Control Loop Performance Assessment

Jiménez-Cabas

Manrique-Morelos

Meléndez-Pertuz

et al. 2020

Computational Science and Its Applications – ICCSA 2020

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This paper presents a novel non-invasive monitoring method, based on a Liénard-type model (LTM) to diagnose single and sequential leaks in liquid pipelines. The LTM describes the fluid behavior in a pipeline and is given only in terms of the flow rate. Our method was conceived to be applied in pipelines mono-instrumented with flowmeters or in conjunction with pressure sensors that are temporarily unavailable. The approach conception starts with the discretization of the LTM spatial domain into a prescribed number of sections. Such discretization is performed to obtain a lumped model capable of providing a solution (an internal flow rate) for every section. From this lumped model, a set of algebraic equations (known as residuals) are deduced as the difference between the internal discrete flows and the nominal flow (the mean of the flow rate calculated before the leak). Once the residuals are calculated a principal component analysis (PCA) is carried out to detect a leak occurrence. In the presence of a leak, the residual closest to zero will indicate the section where a leak is occurring. Some simulation-based tests in PipelineStudio® and experimental tests in a lab-pipeline illustrating the suitability of our method are shown at the end of this article.

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“…In addition, OFS are compact, immune to electromagnetic interference, exhibit high sensitivity, with good portability and low cost. The majority of the OFS involved with fuel detection has been focused on hydrocarbon leak detection [ 8 – 11 ]. There are few reports dealing with the detection of the percentage of ethanol and other contaminants in gasoline [ 12 – 14 ].…”

Section: Introductionmentioning

confidence: 99%

Gasohol Quality Control for Real Time Applications by Means of a Multimode Interference Fiber Sensor

Rodríguez

Baldovino-Pantaleón

Cruz

et al. 2014

Sensors

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In this work we demonstrate efficient quality control of a variety of gasoline and ethanol (gasohol) blends using a multimode interference (MMI) fiber sensor. The operational principle relies on the fact that the addition of ethanol to the gasohol blend reduces the refractive index (RI) of the gasoline. Since MMI sensors are capable of detecting small RI changes, the ethanol content of the gasohol blend is easily determined by tracking the MMI peak wavelength response. Gasohol blends with ethanol contents ranging from 0% to 50% has been clearly identified using this device, which provides a linear response with a maximum sensitivity of 0.270 nm/% EtOH. The sensor can also distinguish when water incorporated in the blend has exceeded the maximum volume tolerated by the gasohol blend, which is responsible for phase separation of the ethanol and gasoline and could cause serious engine failures. Since the MMI sensor is straightforward to fabricate and does not require any special coating it is a cost effective solution for real time and in-situ monitoring of the quality of gasohol blends.

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Fiber Bragg grating sensor for petroleum hydrocarbon leak detection

Cited by 47 publications

References 5 publications

Autonomous Measurement System for Localization of Loss-Induced Perturbation Based on Transmission-Reflection Analysis

Autonomous Measurement System for Localization of Loss-Induced Perturbation Based on Transmission-Reflection Analysis

Development of a Tool for Control Loop Performance Assessment

Gasohol Quality Control for Real Time Applications by Means of a Multimode Interference Fiber Sensor

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