基于混沌超声波激励的螺栓连接松动检测研究

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振动与冲击 ›› 2018, Vol. 37 ›› Issue (9) : 208-213.

论文

吴冠男，徐超

作者信息 +

Bolt looseness detection based on chaos ultrasonic excitation

WU Guan-nan, XU Chao

Author information +

文章历史 +

摘要

在服役过程中，螺栓连接受到多种环境因素的作用可能会发生预紧力下降、松动甚至松脱。连接部位早期松动的可靠检测对确保结构的可靠性和安全性具有重要的意义。本文采用高频具有混沌特征的超声波信号激励待测连接结构，采集结构的动力响应信号，利用非线性时间序列分析方法提取表征连接松动的特征参量。以螺栓搭接梁为研究对象，采用压电陶瓷片作为激励和响应信号采集元件。对响应信号进行解调和相空间重构，提取表征吸引子整体特征的Lyapunov维数和表征吸引子局部特征的平均吸引子局部方差比ALAVR作为松动指标。实验结果表明：本文的方法能够有效检测螺栓连接的松动状态；吸引子特征量ALAVR相较于Lyapunov维数对预紧力下降具有更好的检测效果；特征参量ALAVR能够有效检测出早期的螺栓松动。

Abstract

Under severe loading conditions, bolted joints in assembled structures may loosen or fail. Reliability detection for early looseness in connection positions is significant to ensure the reliability and safety of structures. Here, high-frequency ultrasonic signals with a chaotic feature were adopted to excite a connection structure to be detected to acquire dynamic response signals of the structure, and use the nonlinear time series analysis method to extract feature parameters to characterize bolt looseness. Taking a typical bolted lap beam as the study object and piezoelectric ceramic pieces as units to collect excitation and response signals, the structure’s response signals were demodulated and reconstructed in a phase space. Lyapunov dimension to characterize an attractor’s whole features and ALAVR to reflect an attractor’s local features were extracted and taken as looseness indexes. Test results showed that the proposed method can effectively detect the looseness state of bolted joints; compared with Lyapunov dimension, an attractor’s feature parameter ALAVR can better detect the decline of pre-tightening force in bolts, ALAVR can effectively detect early bolt looseness.

导出引用

吴冠男，徐超. 基于混沌超声波激励的螺栓连接松动检测研究[J]. 振动与冲击, 2018, 37(9): 208-213

WU Guan-nan, XU Chao . Bolt looseness detection based on chaos ultrasonic excitation[J]. Journal of Vibration and Shock, 2018, 37(9): 208-213

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