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用于声发射状态监测的圆柱滚子轴承中超声应力波传播的评估

Evaluation of Ultrasonic Stress Wave Transmission in Cylindrical Roller Bearings for Acoustic Emission Condition Monitoring.

作者信息

Scheeren Bart, Kaminski Miroslaw Lech, Pahlavan Lotfollah

机构信息

Department of Maritime and Transport Technology, Delft University of Technology, 2628 CD Delft, The Netherlands.

出版信息

Sensors (Basel). 2022 Feb 16;22(4):1500. doi: 10.3390/s22041500.

DOI:10.3390/s22041500
PMID:35214419
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8874969/
Abstract

In the condition monitoring of bearings using acoustic emission (AE), the restriction to solely instrument one of the two rings is generally considered a limitation for detecting signals originating from defects on the opposing non-instrumented ring or its interface with the rollers due to the signal energy loss. This paper presents an approach to evaluate transmission in low-speed roller bearings for application in passive ultrasound monitoring. An analytical framework to describe the propagation and transmission of ultrasonic waves through the geometry and interfaces of a bearing is presented. This framework has been used to evaluate the transmission of simulated damage signals in an experiment with a static bearing. The results suggest that low- to mid-frequency signals (<200 kHz), when passing through the rollers and their interfaces from one raceway to the other, can retain enough energy to be potentially detected. An average transmission loss in the range of 10-15 dB per interface was experimentally observed.

摘要

在使用声发射(AE)对轴承进行状态监测时,通常认为仅对两个套圈之一进行仪器安装存在局限性,因为信号能量损失,难以检测到来自相对未安装仪器套圈上的缺陷或其与滚子界面处产生的信号。本文提出一种方法,用于评估低速滚子轴承中的传输情况,以应用于被动超声监测。提出了一个分析框架,用于描述超声波通过轴承的几何结构和界面的传播与传输。该框架已用于在静态轴承实验中评估模拟损伤信号的传输。结果表明,低频至中频信号(<200 kHz)在从一个滚道穿过滚子及其界面传输到另一个滚道时,能够保留足够的能量以被潜在检测到。实验观察到每个界面的平均传输损耗在10 - 15 dB范围内。

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本文引用的文献

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Acoustic Emission Monitoring of Carbon Fibre Reinforced Composites with Embedded Sensors for In-Situ Damage Identification.基于嵌入式传感器的声发射监测碳纤维复合材料的实时损伤识别。
Sensors (Basel). 2021 Oct 19;21(20):6926. doi: 10.3390/s21206926.
2
Element analysis: a wavelet-based method for analysing time-localized events in noisy time series.元素分析:一种基于小波的方法,用于分析噪声时间序列中的时间局部化事件。
Proc Math Phys Eng Sci. 2017 Apr;473(2200):20160776. doi: 10.1098/rspa.2016.0776. Epub 2017 Apr 26.
基于知识的声发射分析对滚动轴承亚表面疲劳裂纹的早期检测。
Sensors (Basel). 2022 Jul 11;22(14):5187. doi: 10.3390/s22145187.