A pipeline inspection gauge based on low cost magnetic flux leakage sensing magnetometers for non-destructive testing of pipelines

Pasha, Muhammad Ahsan; Khan, Tariq Amin

doi:10.1109/icet.2016.7813212

Cited by 9 publications

(7 citation statements)

References 4 publications

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“…Other works involving MFL pipeline inspection can be found in [ 17 , 101 ]. In [ 101 ], a lightweight MFL inspection tool, using electromagnetic solenoids, was proposed for operation in small pipelines.…”

Section: Pipeline Failure Detection Methodsmentioning

confidence: 99%

“…The permanent magnets of conventional MFL PIG produce a strong adhesive magnetic force that is not suitable for the inspection of smaller pipelines. In [ 17 ], a cost-effective MFL inspection method, using commercially available magnetometer, was designed and tested.…”

Section: Pipeline Failure Detection Methodsmentioning

confidence: 99%

“…There has also been a growing interest among researchers in inspection methods based on the analysis of hydraulic parameters such as pressure and flow rate [12][13][14]. At the same time, the employment of magnetic flux leakage (MFL) sensing for pipeline failure detection has become increasingly relevant due to its applicability across various types of pipeline failures [15][16][17].…”

Section: Introductionmentioning

confidence: 99%

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Failure Detection Methods for Pipeline Networks: From Acoustic Sensing to Cyber-Physical Systems

Wong

McCann

2021

Sensors

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Pipeline networks have been widely utilised in the transportation of water, natural gases, oil and waste materials efficiently and safely over varying distances with minimal human intervention. In order to optimise the spatial use of the pipeline infrastructure, pipelines are either buried underground, or located in submarine environments. Due to the continuous expansion of pipeline networks in locations that are inaccessible to maintenance personnel, research efforts have been ongoing to introduce and develop reliable detection methods for pipeline failures, such as blockages, leakages, cracks, corrosion and weld defects. In this paper, a taxonomy of existing pipeline failure detection techniques and technologies was created to comparatively analyse their respective advantages, drawbacks and limitations. This effort has effectively illuminated various unaddressed research challenges that are still present among a wide array of the state-of-the-art detection methods that have been employed in various pipeline domains. These challenges include the extension of the lifetime of a pipeline network for the reduction of maintenance costs, and the prevention of disruptive pipeline failures for the minimisation of downtime. Our taxonomy of various pipeline failure detection methods is also presented in the form of a look-up table to illustrate the suitability, key aspects and data or signal processing techniques of each individual method. We have also quantitatively evaluated the industrial relevance and practicality of each of the methods in the taxonomy in terms of their respective deployability, generality and computational cost. The outcome of the evaluation made in the taxonomy will contribute to our future works involving the utilisation of sensor fusion and data-centric frameworks to develop efficient, accurate and reliable failure detection solutions.

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Section: Pipeline Failure Detection Methodsmentioning

confidence: 99%

Section: Pipeline Failure Detection Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Failure Detection Methods for Pipeline Networks: From Acoustic Sensing to Cyber-Physical Systems

Wong

McCann

2021

Sensors

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“…The deterioration of pipelines outside the buried environment is predominantly detected using magnetic flux leakage (MFL) [ 14 , 15 , 16 , 17 ]. Robot-assisted inspection is emerging as a viable alternative, offering operational cost savings and reducing the risk of human casualties.…”

Section: Introductionmentioning

confidence: 99%

Development of an In-Pipe Inspection Robot for Large-Diameter Water Pipes

Jeon,

Jung,

Bae

et al. 2024

Sensors

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This paper describes the development of an in-pipe inspection robot system designed for large-diameter water pipes. The robot is equipped with a Magnetic Flux Leakage (MFL) sensor module. The robot system is intended for pipes with diameters ranging from 900 mm to 1200 mm. The structure of the in-pipe inspection robot consists of the front and rear driving parts, with the inspection module located centrally. The robot is powered by 22 motors, including eight wheels with motors positioned at both the bottom and the top for propulsion. To ensure that the robot’s center aligns with that of the pipeline during operation, lifting units have been incorporated. The robot is equipped with cameras and LiDAR sensors at the front and rear to monitor the internal environment of the pipeline. Pipeline inspection is conducted using the MFL inspection modules, and the robot’s driving mechanism is designed to execute spiral maneuvers while maintaining contact with the pipeline surface during rotation. The in-pipe inspection robot is configured with wireless communication modules and batteries, allowing for wireless operation. Following its development, the inspection robot underwent driving experiments in actual pipelines to validate its performance. The field test bed used for these experiments is approximately 1 km in length. Results from the driving experiments on the field test bed confirmed the robot’s ability to navigate various curvatures and obstacles within the pipeline. It is posited that the use of the developed in-pipe inspection robot can reduce economic costs and enhance the safety of inspectors when examining aging pipes.

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“…marginal cost, long transportation distance, large volume per unit time and continuous supply [1][2][3]. However, with the extension of the service time of the pipeline, its metal properties will inevitably deteriorate or even be damaged [4,5], which will cause further corrosion or even leakage of the pipeline [6], bringing substantial economic losses and irreversible impact on the environment [7]. To ensure the pipeline's safe operation, routine inspections should be carried out every 3-5 years, and non-destructive testing should be carried out periodically.…”

Section: Introductionmentioning

confidence: 99%

An ultrasonic in-line inspection data processing method considering invalid data caused by sensor failure

Wu,

Huang,

Zhang

et al. 2023

Meas. Sci. Technol.

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Ultrasonic in-line inspection is one of the most widely adopted nondestructive testing methods for defect detection in pipelines. In practical industrial scenes, pipeline specification varies, sensor failure occurs frequently, and the number of pipeline defect samples is scarce. How to detect defects without false detection caused by invalid data and with limited labeled samples is a challenging problem in this area. An ultrasonic in-line inspection data processing method considering invalid data caused by sensor failure is proposed in this paper to enhance the accuracy of the defect and its profile detection. Firstly, the multi-channel data is aggregated according to sampling time. The data dimension is reduced, and the accuracy of the invalid waveform detection adopting isolation forest arithmetic is improved. The methods are adopted for the invalid waveforms replacement with two-dimensional cubic spline interpolation using adjacent sensors. Secondly, a natural breakpoint method is adopted to locate the echo peaks. Residual wall thickness is evaluated by calculating the time difference between the echo peaks. A fast pseudo-colorization method based on sliding windows and a morphological image processing method are proposed to detect defects and their profiles efficiently utilizing the residual wall thickness. Finally, practical in-line inspection data is utilized to evaluate the performance. The experiment results illustrate that the detection accuracy is enhanced on different sizes of pipelines without requiring labeled samples.

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A pipeline inspection gauge based on low cost magnetic flux leakage sensing magnetometers for non-destructive testing of pipelines

Cited by 9 publications

References 4 publications

Failure Detection Methods for Pipeline Networks: From Acoustic Sensing to Cyber-Physical Systems

Failure Detection Methods for Pipeline Networks: From Acoustic Sensing to Cyber-Physical Systems

Development of an In-Pipe Inspection Robot for Large-Diameter Water Pipes

An ultrasonic in-line inspection data processing method considering invalid data caused by sensor failure

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