等距
声学
超声波传感器
能量(信号处理)
信号(编程语言)
材料科学
共振(粒子物理)
传感器
导线
声共振
光学
计算机科学
物理
数学
几何学
粒子物理学
地理
量子力学
大地测量学
程序设计语言
作者
Zhichao Cai,Yihu Sun,Zhengshi Lu,Qixiang Zhao
出处
期刊:Magnetochemistry
[Multidisciplinary Digital Publishing Institute]
日期:2023-03-22
卷期号:9 (3): 86-86
被引量:5
标识
DOI:10.3390/magnetochemistry9030086
摘要
The conventional ultrasonic thickness measurement method is ineffective in detecting the measured specimen with a step change in thickness as it is easy to cause multimode acoustic mixing in the ultrasonic detection process. To solve this problem, this paper presented an electromagnetic acoustic resonance (EMAR) moving scan identification method based on a frequency–frequency energy density precipitation (FFEDP) algorithm, which uses a standing wave resonance mode to accurately extract step thickness information and employs the algorithm to separate step thickness information. According to the simulation results, the ratio of the highest energy density of the spectrum signal on both sides of the step area to the total energy density had an opposite linear change rule with the equidistant movement of the transducer coil. The thickness step area can be identified by analyzing the crossover point of the contrast value change. The experimental results showed that the proposed method can accurately extract the thickness information under millimeter-level stepping distance for sector-notched specimens with step surfaces of different thicknesses, and at the same time realize the effective identification of the step surface.
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