金士杰

个人信息Personal Information

副教授

博士生导师

硕士生导师

性别:男

毕业院校:中国科学院声学研究所

学位:博士

所在单位:材料科学与工程学院

学科:材料无损检测与评价

办公地点:材料馆236

联系方式:0411-84706049

电子邮箱:jinshijie@dlut.edu.cn

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Identification of the velocity, thickness, and interfacial roughness of coating using full time-domain URCPS: Cross-correlation-based inverse problem

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论文类型:期刊论文

发表时间:2019-02-01

发表刊物:Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems

收录刊物:EI

卷号:2

期号:1

ISSN号:25723901

摘要:Aiming at characterizing interfacial roughness of thin coatings with unknown sound velocity and thickness, we derive a full time-domain ultrasonic reflection coefficient phase spectrum (URCPS) as a function of interfacial roughness based on the phase screen approximation theory. The constructed URCPS is used to determine the velocity, thickness, and interfacial roughness of specimens through the cross-correlation algorithm. The effect of detection frequency on the roughness measurement is investigated through the finite element method. A series of simulations were implemented on Nicoating specimens with a thickness of 400 lm and interfacial roughness of 1.9-39.8 lm. Simulation results indicated that the measurement errors of interfacial roughness were less than 10% when the roughness satisfies the relationship of Rq ¼ 1.6-10.0%k. The measured velocity and thicknesses were in good agreement with those imported in simulation models with less than 9.3% error. Ultrasonic experiments were carried out on two Ni-coating specimens through a flat transducer with an optimized frequency of 15 MHz. Compared with the velocities measured by time-of-flight (TOF) method, the relative errors of inversed velocities were all less than 10%. The inversed thicknesses were in good agreement with those observed by optical microscopy with less than 10.9% and 7.6% error. The averaged interfacial roughness determined by the ultrasonic inversion method was 16.9 lm and 30.7 lm, respectively. The relative errors were 5.1% and 2.0% between ultrasonic and confocal laser scanning microscope (CLSM) method, respectively. © 2019 by ASME.