Data Analysis of Bolt Length Detection Based on Ultrasonic Reflection Method

Wei, Shaoliang; Yang, Yuanjia; Fang, Cheng; Wu, Ming Jenn; Yang, Hongbo

doi:10.1109/itnec52019.2021.9586859

Cited by 1 publication

(1 citation statement)

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“…After working for a long time, it is easy to be tired, which affects the quality of defect judgment and the inspection progress. It can only judge whether there is a defect but cannot locate the defect and give specific information, such as the depth and length of the defect. The second is to use the obtained ultrasonic image data to judge whether there are defects in bolts by identifying the effective peaks in the data (Wei et al , 2021) or by three-dimensional explicit finite element simulation (Reza et al , 2022). …”

Section: Introductionmentioning

confidence: 99%

Method to detect the bolt thread defect in the aerospace vehicle with ultrasonic image and its implementation

Liu

Chen

et al. 2023

ACMM

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Purpose This study aims to solve the problems of ambiguous localization, large calculation, poor real-time and limited applicability of bolt thread defect detection. Design/methodology/approach First, the acquired ultrasound image is used to acquire the larger area of the image, which is set as the compliant threaded area. Second, based on the determined coordinates of the center point in each selected region, the set of coordinates on the left and right sides of the bolts is acquired by DBSCAN method with parameters eps and MinPts, which is determined by data set dimension D and the k-distance curve. Finally, the defect detection boundary line fitting is completed using the acquired coordinate set, and the relationship between the distance from each detection point to the curve and d, which is obtained from the measurement of the standard bolt sample with known thread defect, is used to locate the bolt thread defect simultaneously. Findings In this paper, the bolt thread defect detection method with ultrasonic image is proposed; meanwhile, the ultrasonic image acquisition system is designed to complete the real-time localization of bolt thread defects. Originality/value The detection results show that the method can effectively detect bolt thread defects and locate the bolt thread defect location with wide applicability, small calculation and good real-time performance.

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Section: Introductionmentioning

confidence: 99%