A New Probabilistic Ellipse Imaging Method Based on Adaptive Signal Truncation for Ultrasonic Guided Wave Defect Localization on Pressure Vessels

Pressure vessels are prone to defects due to environmental conditions, which may cause serious safety hazards to industrial production. The probabilistic ellipse imaging method, based on ultrasonic guided wave, is a common method for locating defects on plate-like structures. In this paper, the rese...

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Main Authors: Qinfei Li, Zhi Luo, Gangyi Hu, Shaoping Zhou
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/22/4/1540
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author Qinfei Li
Zhi Luo
Gangyi Hu
Shaoping Zhou
author_facet Qinfei Li
Zhi Luo
Gangyi Hu
Shaoping Zhou
author_sort Qinfei Li
collection DOAJ
description Pressure vessels are prone to defects due to environmental conditions, which may cause serious safety hazards to industrial production. The probabilistic ellipse imaging method, based on ultrasonic guided wave, is a common method for locating defects on plate-like structures. In this paper, the research showed that the accuracy of the traditional probabilistic ellipse imaging method was severely affected by the truncation length of the signal. In order to improve the defect location accuracy of the probabilistic elliptic imaging algorithm, an adaptive signal truncation method based on signal difference analysis was proposed, and a novel probabilistic elliptic imaging method was developed. Firstly, the relationship model between the signal difference coefficient (SDC) and the distance coefficient was constructed. Through this model, the distance coefficient of each group signal can be calculated, so that the adaptive truncation length for each group of signals can be determined and the truncated signals used for defect imaging. Secondly, in order to improve the robustness of the new imaging method, the relationship between the defect location accuracy and SDC thresholds were investigated and the optimal threshold was determined. The experimental results showed that the probabilistic ellipse imaging algorithm, based on the new adaptive signal truncation method, can effectively locate a single defect on a pressure vessel.
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spelling doaj.art-e675164b93a64d87ba15b393bbc5d49a2023-11-23T22:01:12ZengMDPI AGSensors1424-82202022-02-01224154010.3390/s22041540A New Probabilistic Ellipse Imaging Method Based on Adaptive Signal Truncation for Ultrasonic Guided Wave Defect Localization on Pressure VesselsQinfei Li0Zhi Luo1Gangyi Hu2Shaoping Zhou3School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai 200237, ChinaSchool of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai 200237, ChinaSchool of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai 200237, ChinaSchool of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai 200237, ChinaPressure vessels are prone to defects due to environmental conditions, which may cause serious safety hazards to industrial production. The probabilistic ellipse imaging method, based on ultrasonic guided wave, is a common method for locating defects on plate-like structures. In this paper, the research showed that the accuracy of the traditional probabilistic ellipse imaging method was severely affected by the truncation length of the signal. In order to improve the defect location accuracy of the probabilistic elliptic imaging algorithm, an adaptive signal truncation method based on signal difference analysis was proposed, and a novel probabilistic elliptic imaging method was developed. Firstly, the relationship model between the signal difference coefficient (SDC) and the distance coefficient was constructed. Through this model, the distance coefficient of each group signal can be calculated, so that the adaptive truncation length for each group of signals can be determined and the truncated signals used for defect imaging. Secondly, in order to improve the robustness of the new imaging method, the relationship between the defect location accuracy and SDC thresholds were investigated and the optimal threshold was determined. The experimental results showed that the probabilistic ellipse imaging algorithm, based on the new adaptive signal truncation method, can effectively locate a single defect on a pressure vessel.https://www.mdpi.com/1424-8220/22/4/1540pressure vesselultrasonic guided wavedefect locationsignal analysisprobabilistic elliptic algorithmadaptive signal truncation
spellingShingle Qinfei Li
Zhi Luo
Gangyi Hu
Shaoping Zhou
A New Probabilistic Ellipse Imaging Method Based on Adaptive Signal Truncation for Ultrasonic Guided Wave Defect Localization on Pressure Vessels
Sensors
pressure vessel
ultrasonic guided wave
defect location
signal analysis
probabilistic elliptic algorithm
adaptive signal truncation
title A New Probabilistic Ellipse Imaging Method Based on Adaptive Signal Truncation for Ultrasonic Guided Wave Defect Localization on Pressure Vessels
title_full A New Probabilistic Ellipse Imaging Method Based on Adaptive Signal Truncation for Ultrasonic Guided Wave Defect Localization on Pressure Vessels
title_fullStr A New Probabilistic Ellipse Imaging Method Based on Adaptive Signal Truncation for Ultrasonic Guided Wave Defect Localization on Pressure Vessels
title_full_unstemmed A New Probabilistic Ellipse Imaging Method Based on Adaptive Signal Truncation for Ultrasonic Guided Wave Defect Localization on Pressure Vessels
title_short A New Probabilistic Ellipse Imaging Method Based on Adaptive Signal Truncation for Ultrasonic Guided Wave Defect Localization on Pressure Vessels
title_sort new probabilistic ellipse imaging method based on adaptive signal truncation for ultrasonic guided wave defect localization on pressure vessels
topic pressure vessel
ultrasonic guided wave
defect location
signal analysis
probabilistic elliptic algorithm
adaptive signal truncation
url https://www.mdpi.com/1424-8220/22/4/1540
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