Shedding Damage Detection of Metal Underwater Pipeline External Anticorrosive Coating by Ultrasonic Imaging Based on HOG + SVM

Abstract

Underwater pipelines are the channels for oil transportation in the sea. In the course of pipeline operation, leakage accidents occur from time to time for natural and man-made reasons which result in economic losses and environmental pollution. To avoid economic losses and environmental pollution, damage detection of underwater pipelines must be carried out. In this paper, based on the histogram of oriented gradient (HOG) and support vector machine (SVM), a non-contact ultrasonic imaging method is proposed to detect the shedding damage of the metal underwater pipeline external anti-corrosion layer. Firstly, the principle of acoustic scattering characteristics for detecting the metal underwater pipelines is introduced. Following this, a HOG+SVM image-extracting algorithm is used to extract the pipeline area from the underwater ultrasonic image. According to the difference of mean gray value in the horizontal direction of the pipeline project area, the shedding damage parts are identified. Subsequently, taking the metal underwater pipelines with three layers of polyethylene outer anti-corrosive coatings as the detection object, an Autonomous Surface Vehicle (ASV) for underwater pipelines defect detection is developed to verify the detection effect of the method. Finally, the underwater ultrasonic image which used to detect the metal underwater pipeline shedding damage is obtained by acoustic sensor. The results show that the shedding damage can be detected by the proposed method. With the increase of shedding damage width, the effect of pipeline defect location detection is better.

Detection and recognition of metal surface corrosion based on CBG-YOLOv5s

“…Yeih et al [ 9 ] used the amplitude attenuation method of ultrasonic detection technology to assess damage from metal corrosion in reinforced concrete, achieving significant detection results. Hong et al [ 10 ] proposed a method for detecting the detachment of the outer protective layer of underwater metal pipes using ultrasound imaging technology based on Support Vector Machine (SVM) and Histogram of Oriented Gradients (HOG) techniques. However, this method did not perform well in detecting narrow detachment damage areas.…”

Computer Vision and Image Processing Approaches for Corrosion Detection

“…The applications of SVM for corrosion detection can be observed in water pipelines [67], underwater pipelines [68], steel bars [69], bridge cables [70], equipment [71], aircraft structures [72], wind turbine blades [73], and many more. SVM can also be improved using other methods to obtain a better accuracy for corrosion detection and assessment, such as HOG [74], scale-invariant feature transform (SIFT) [75], and speeded up robust features (SURF) [76].…”

Transient Model for the Hydrodynamic Force in a Hydraulic Capsule Pipeline Transport System

“…The use of slurry pipelines [7], gas pipelines [8], and oil pipelines [9] between cities, and even between countries, can be associated with huge economic and social efficiency. But there are still problems, such as the leakage of pipelines or explosion attacks, which may result in huge economic losses and pollution in the environment [10]. In order to meet the eco-friendly request, some monitoring methods for potential leakages have been proposed [11].…”