{"title":"Laser ultrasound wave pattern analysis for efficient defect detection in samples with curved surfaces","authors":"","doi":"10.1016/j.pacs.2024.100654","DOIUrl":null,"url":null,"abstract":"<div><div>Many production processes involve curved sample surfaces, such as welding or additive manufacturing. These pose new challenges to characterization methods for quality inspection, which are usually optimized for flat extended sample geometries. In this paper, we present a laser ultrasound (LUS) method that can be used to efficiently detect defects (e.g., voids), without extensive scanning effort and without a prior knowledge of the defect location, in finite samples with curved surfaces. The developed method starts with generalized simulations of the LUS wave patterns in samples with varying radii of curvature and width as well as varying excitation size and mechanism (thermoelastic or ablative). Based on the wave pattern analysis, it is possible to predict how every point in the weld can be reached with only few excitation spots. In a second step, we assume a grid of finite size defects at locations at which such voids are most likely formed and perform a thorough simulation analysis that is based on B-Scans to find a few pairs of excitation–detection points most favorable for finding defects anywhere in the weld seam. These results are then compared to the wave pattern analysis, discussing similarities and deviations from the predictions. In a final step, the simulations are compared to experimental results, verifying the almost threefold increase in the detectability of defects by choosing the predicted optimal excitation–detection positions. It is expected that this method will significantly improve the reliability and time efficiency of detecting internal defects in samples with curved surfaces in potential industrial applications.</div></div>","PeriodicalId":56025,"journal":{"name":"Photoacoustics","volume":null,"pages":null},"PeriodicalIF":7.1000,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Photoacoustics","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2213597924000715","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Many production processes involve curved sample surfaces, such as welding or additive manufacturing. These pose new challenges to characterization methods for quality inspection, which are usually optimized for flat extended sample geometries. In this paper, we present a laser ultrasound (LUS) method that can be used to efficiently detect defects (e.g., voids), without extensive scanning effort and without a prior knowledge of the defect location, in finite samples with curved surfaces. The developed method starts with generalized simulations of the LUS wave patterns in samples with varying radii of curvature and width as well as varying excitation size and mechanism (thermoelastic or ablative). Based on the wave pattern analysis, it is possible to predict how every point in the weld can be reached with only few excitation spots. In a second step, we assume a grid of finite size defects at locations at which such voids are most likely formed and perform a thorough simulation analysis that is based on B-Scans to find a few pairs of excitation–detection points most favorable for finding defects anywhere in the weld seam. These results are then compared to the wave pattern analysis, discussing similarities and deviations from the predictions. In a final step, the simulations are compared to experimental results, verifying the almost threefold increase in the detectability of defects by choosing the predicted optimal excitation–detection positions. It is expected that this method will significantly improve the reliability and time efficiency of detecting internal defects in samples with curved surfaces in potential industrial applications.
PhotoacousticsPhysics and Astronomy-Atomic and Molecular Physics, and Optics
CiteScore
11.40
自引率
16.50%
发文量
96
审稿时长
53 days
期刊介绍:
The open access Photoacoustics journal (PACS) aims to publish original research and review contributions in the field of photoacoustics-optoacoustics-thermoacoustics. This field utilizes acoustical and ultrasonic phenomena excited by electromagnetic radiation for the detection, visualization, and characterization of various materials and biological tissues, including living organisms.
Recent advancements in laser technologies, ultrasound detection approaches, inverse theory, and fast reconstruction algorithms have greatly supported the rapid progress in this field. The unique contrast provided by molecular absorption in photoacoustic-optoacoustic-thermoacoustic methods has allowed for addressing unmet biological and medical needs such as pre-clinical research, clinical imaging of vasculature, tissue and disease physiology, drug efficacy, surgery guidance, and therapy monitoring.
Applications of this field encompass a wide range of medical imaging and sensing applications, including cancer, vascular diseases, brain neurophysiology, ophthalmology, and diabetes. Moreover, photoacoustics-optoacoustics-thermoacoustics is a multidisciplinary field, with contributions from chemistry and nanotechnology, where novel materials such as biodegradable nanoparticles, organic dyes, targeted agents, theranostic probes, and genetically expressed markers are being actively developed.
These advanced materials have significantly improved the signal-to-noise ratio and tissue contrast in photoacoustic methods.