Post-Earthquake Pipeline Leak Detection Technologies

Du, Winncy Y.; Yelich, Scott W.

doi:10.1007/978-3-540-79590-2_18

Cited by 5 publications

(3 citation statements)

References 8 publications

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“…It is known that capacitive sensors achieve the highest precision of all electrical sensors, have simple and robust structures, feature high sensitivity and resolution, and allow long-term, drift-free sensing even when temperature changes. [25][26][27][28] We next derive the relation between deformation and capacitance. We adopt the model of ideal dielectric elastomers, assuming that the volume and permittivity remain constant as the elastomers deform.…”

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confidence: 99%

Ionic skin

et al. 2014

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Our skin is a stretchable, large-area sheet of distributed sensors. These properties of skin have inspired the development of mimics, with differing levels of sophistication, to enable wearable or implantable electronics for entertainment and healthcare. [1][2][3][4] "Electronic skin" is generally taken to be a stretchable sheet with area above 10 cm 2 carrying sensors for various stimuli, including deformation, pressure, light and temperature. The sensors report signals through stretchable electrical conductors [5] (e.g., carbon grease, [6] microcraked metal films, [1] serpentine metal lines, [2] graphene sheets, [7] carbon nanotubes, [8][9][10] silver nanowires, [11] gold nanomeshes, [12] and liquid metals [13,14] ). These conductors transmit signals using electrons.They meet the essential requirements of conductivity and stretchability, but struggle to meet additional requirements in specific applications, such as biocompatibility in biometric sensors, [15] and transparency in tunable optics. [16,17] By contrast, sensors in our skin report signals using ions. Here we explore the potential of ionic conductors in the development of a new type of sensory sheet, which we call "ionic skin".The sensory sheet is highly stretchable, transparent, and biocompatible. It readily monitors large deformation, such as that generated by the bending of a finger. It detects stimuli with wide dynamic range (strains from 1% to 500%). It measures pressure as low as 1 kPa, with small drift over many cycles. A sheet of distributed sensors covering a large area can report the location and pressure of touch. High transparency allows the sensory sheet to transmit electrical signals without impeding optical signals.Many ionic conductors, such as hydrogels and ionogels, are highly stretchable and transparent. [18][19][20] These gels are polymeric networks swollen with water or ionic liquids. They behave like elastic solids and eliminate the need for containers as required in the case of liquid metal conductors. Whereas familiar elastic gels, such as Jell-O, are brittle and easily rupture, the recent decade has seen the development of hydrogels and ionogels as tough as elastomers. [20][21][22] Many hydrogels are biocompatible. They can be made softer than tissues, achieving the "mechanical invisibility" required for biometric sensors, which monitor soft tissues without 3 constraining them. Although most hydrogels dry out in open air, hydrogels containing humectants retain water in environment of low humidity, and ionogels are nonvolatile in vacuum. [18][19][20] We have recently used ionic conductors-together with stretchable and transparent dielectrics-to make actuators, which deform in response to high voltages, on the order of kilovolts. [18] By contrast, the sensors described here deform in response to applied forces, giving signals that can be measured using voltages below 1 volt. To illustrate principles in our design of the ionic skin, consider a simple example-a dielectric sandwiched between two ionic conductors (Figure 1). In many...

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confidence: 99%

Ionic skin

et al. 2014

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“…These include, for instance, visual testing, penetrant testing, magnetic particle testing, magnetic flux leakage, Hall-effect, radiographic testing, ultrasonic sensors, eddy current, thermal infrared, magnetic Barkhausen effect, and acoustic emission. More comprehensive reviews of these techniques are found in [16], [17], [18], [19], [20], [21] and in the references therein.…”

Section: Introductionmentioning

confidence: 99%

Rényi Entropy Filter for Anomaly Detection With Eddy Current Remote Field Sensors

2015

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Abstract-We consider a multi-channel remote field eddy current sensor apparatus, which is installed on a mobile robot which is deployed in pipelines with the mission of detection defects. Features in raw sensory data that are associated with defects could be masked by noise and therefore difficult to identify in some instances. In order to enhance these features that potentially identify defects, we propose an entropy filter that maps raw sensory data points into a local entropy measure. In the entropy space, data is then classified by means of a thresholding procedure based on the Neymnan-Pearson criterion. The effectiveness of the algorithm is demonstrated by applying it to different data sets obtained from field trials.

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“…Several types of PIGs have been proposed in the literature [2]. Acoustic and ultrasonic sensors were tested in [3]- [6].…”

Section: Introductionmentioning

confidence: 99%

Entropy filter for anomaly detection with eddy current remote field sensors

Spinello

Gueaieb

Lee³

2011

2011 IEEE International Symposium on Robotic and Sensors Environments (ROSE)

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Abstract-We consider the problem of extracting a specific feature from a noisy signal generated by a multi-channels Remote Field Eddy Current Sensor. The sensor is installed on a mobile robot whose mission is the detection of anomalous regions in metal pipelines. Given the presence of noise that characterizes the data series, anomaly signals could be masked by noise and therefore difficult to identify in some instances. In order to enhance signal peaks that potentially identify anomalies we consider an entropy filter built on a posteriori probability density functions associated with data series. Thresholds based on the Neyman-Pearson criterion for hypothesis testing are derived. The algorithmic tool is applied to the analysis of data from a portion of pipeline with a set of anomalies introduced at predetermined locations. Critical areas identifying anomalies capture the set of damaged locations, demonstrating the effectiveness of the filter in detection with Remote Field Eddy Current Sensor.

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Post-Earthquake Pipeline Leak Detection Technologies

Cited by 5 publications

References 8 publications

Ionic skin

Ionic skin

Rényi Entropy Filter for Anomaly Detection With Eddy Current Remote Field Sensors

Entropy filter for anomaly detection with eddy current remote field sensors

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