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基于双点接触法的 PZT 传感器的多重损伤检测

Multiple Damage Detection in PZT Sensor Using Dual Point Contact Method.

机构信息

Department of Mining Machinery Engineering, Indian Institute of Technology Dhanbad, Dhanbad 826004, India.

Department of Electrical Engineering, Indian Institute of Technology Delhi, New Delhi 110016, India.

出版信息

Sensors (Basel). 2022 Nov 25;22(23):9161. doi: 10.3390/s22239161.

Abstract

Lead Zirconate Titanate (PZT) is used to make ultrasound transducers, sensors, and actuators due to its large piezoelectric coefficient. Several micro-defects develop in the PZT sensor due to delamination, corrosion, huge temperature fluctuation, etc., causing a decline in its performance. It is thus necessary to identify, locate, and quantify the defects. Non-Destructive Structural Health Monitoring (SHM) is the most optimal and economical evaluation method. Traditional ultrasound SHM techniques have a huge impedance mismatch between air and solid material, and most of the popular signal processing methods define time series signals in only one domain, which provides sub-optimal results for non-stationary signals. Thus, to improve the accuracy of detection, the point contact excitation and detection method is implemented to determine the interaction of ultrasonic waves with micro-scale defects in the PZT. The signal generated from this method being non-stationary in nature, it requires signal processing with changeable resolutions at different times and frequencies. The Haar Discrete Wavelet Transformation (DWT) is applied to the time series data obtained from the coulomb coupling setup. Using the above process, defects up to 100 μm in diameter could be successfully distinguished.

摘要

锆钛酸铅(PZT)因其具有较大的压电系数,而被用于制造超声换能器、传感器和致动器。由于分层、腐蚀、巨大的温度波动等原因,PZT 传感器会产生一些微缺陷,从而导致其性能下降。因此,有必要对这些缺陷进行识别、定位和量化。无损结构健康监测(SHM)是最佳和最经济的评估方法。传统的超声 SHM 技术在空气和固体材料之间存在巨大的阻抗不匹配,并且大多数流行的信号处理方法仅在一个域中定义时间序列信号,这为非平稳信号提供了次优的结果。因此,为了提高检测的准确性,实施了点接触激励和检测方法,以确定超声波与 PZT 中的微尺度缺陷的相互作用。由于该方法产生的信号本质上是非平稳的,因此需要在不同的时间和频率下使用可变分辨率进行信号处理。哈达离散小波变换(DWT)被应用于从库仑耦合装置获得的时间序列数据。通过使用上述过程,可以成功区分直径达 100μm 的缺陷。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f7c/9738784/ca4462443175/sensors-22-09161-g001.jpg

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