Defect Detection in Pipes using a Mobile Laser-Optics Technology and Digital Geometry

Tezerjani, Abbasali Dehghan; Mehrandezh, Mehran; Paranjape, Raman

doi:10.1051/matecconf/20153206006

Cited by 8 publications

(2 citation statements)

References 9 publications

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“…Secondly, it is difficult or impossible to determine outer defects. Finally, this method highly depends on the inspector's skill in processing the images, and limits the moving speed and increases the cost [138], [139]. In recent years, novel research has applied deep learning and computer vision to improve the accuracy and speed of visual inspection [140]- [142].…”

Section: E Other Methodsmentioning

confidence: 99%

A Review of Inspection Methods for Continuously Monitoring PVC Drinking Water Mains

Tran¹,

Le²,

Yntema³

et al. 2022

IEEE Internet Things J.

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The drinking water mains, mostly buried underground and stay there for decades, require proper maintenance to prevent failures. Among different kinds of material, polyvinyl chloride (PVC) has been widely used due to positive features such as high durability, corrosion resistance, low price, and easy installation. To the best of our knowledge, this is the first paper that reviews the inspection methods toward continuously monitoring the structural health of PVC drinking water mains. To understand which properties need inspecting, we first investigated the attributes that influence PVC pipe and joint failures. Then, we reviewed the methods that have already been applied or can inspect these influencing attributes. We categorized the prospects into five groups: sound wave, fiber optic sensing, hydraulic monitoring, multiple discrete sensors, and other inline methods. Finally, we discussed the possibility and challenges in implementing these methods into a continuous monitoring system of PVC water mains for early failure warning. The result, which includes active sound wave, fiber optic sensing, hydraulic vibration, multiple discrete sensors methods, can help future researchers select the appropriate methods to develop the continuous monitoring system for the PVC water mains.Index Terms-drinking water mains, PVC pipe, pipeline inspection, continuous monitoring, early failure warning, leak, pipe crack. I. INTRODUCTIONG RADUALLY, polyvinyl chloride (PVC) has become the dominant material in the Dutch drinking water mains due to its many advantages such as high durability, resistance to many chemicals, low price, and great flexibility [1]. Although more reliable than other pipes [2], PVC mains also become old

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Section: E Other Methodsmentioning

confidence: 99%

A Review of Inspection Methods for Continuously Monitoring PVC Drinking Water Mains

Tran¹,

Le²,

Yntema³

et al. 2022

IEEE Internet Things J.

View full text Add to dashboard Cite

show abstract

“…From the perspective of a single image, the pipeline image may have a lot of noise including the image itself and labels, which makes it difficult to train a perfect model. In addition, the detailed area in the image may have low brightness, and it is difficult to distinguish some defects by naked eyes, which further increases the difficulty of pipeline defection [ 35 , 36 , 37 , 38 ].…”

Section: Related Workmentioning

confidence: 99%

An Automatic Defect Detection System for Petrochemical Pipeline Based on Cycle-GAN and YOLO v5

Chen

Li³

et al. 2022

Sensors

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Defect detection of petrochemical pipelines is an important task for industrial production safety. At present, pipeline defect detection mainly relies on closed circuit television method (CCTV) to take video of the pipeline inner wall and then detect the defective area manually, so the detection is very time-consuming and has a high rate of false and missed detections. To solve the above issues, we proposed an automatic defect detection system for petrochemical pipeline based on Cycle-GAN and improved YOLO v5. Firstly, in order to create the pipeline defect dataset, the original pipeline videos need pre-processing, which includes frame extraction, unfolding, illumination balancing, and image stitching to create coherent and tiled pipeline inner wall images. Secondly, aiming at the problems of small amount of samples and the imbalance of defect and non-defect classes, a sample enhancement strategy based on Cycle-GAN is proposed to generate defect images and expand the data set. Finally, in order to detect defective areas on the pipeline and improve the detection accuracy, a robust defect detection model based on improved YOLO v5 and Transformer attention mechanism is proposed, with the average precision and recall as 93.10% and 90.96%, and the F1-score as 0.920 on the test set. The proposed system can provide reference for operators in pipeline health inspection, improving the efficiency and accuracy of detection.

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Review of optical detection technologies for inner-wall surface defects

Liu

Hong-shun

Jiao

et al. 2023

Optics & Laser Technology

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Defect Detection in Pipes using a Mobile Laser-Optics Technology and Digital Geometry

Cited by 8 publications

References 9 publications

A Review of Inspection Methods for Continuously Monitoring PVC Drinking Water Mains

A Review of Inspection Methods for Continuously Monitoring PVC Drinking Water Mains

An Automatic Defect Detection System for Petrochemical Pipeline Based on Cycle-GAN and YOLO v5

Review of optical detection technologies for inner-wall surface defects

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