Identification of bolt pre-tightening state based on cointegration analysis of vibro-acoustic modulation signals
ZHANG Junshu1, LI Dan1, REN Weixin2
1.College of Civil Engineering, Hefei University of Technology, Hefei 230009, China;
2.Key Laboratory for Resilient Infrastructures of Coastal Cities, Ministry of Education, Shenzhen University, Shenzhen 518060, China
Abstract:Vibro-acoustic modulation (VAM) can identify the structural damage using the nonlinear side-band signals induced by the interaction of low-frequency vibration and high-frequency waves. However, the side-band signals are susceptible to the boundary conditions, resulting in false diagnosis in practice. In light of the bolt connection monitoring under the influence of boundary conditions, a method based on cointegration analysis is proposed. Firstly, the amplitudes of side-band signals under different boundary fixing preloading of bolts are extracted as the cointegration variable. By performing the cointegration analysis, the bolt looseness can be identified. A robust preloading state index of bolt connections is then proposed according to the residual. The experimental results have shown that the proposed method can isolate damage-sensitive features from boundary conditions to detect the bolt looseness state, and the bolt preloading can be quantified accordingly by root mean square (RMS) value of the residual.
Key words: vibro-acoustic modulation (VAM); bolt preloading; boundary conditions; cointegration analysis; residual
张俊树1,李丹1,任伟新2. 基于振动声调制信号协整分析的螺栓预紧状态识别[J]. 振动与冲击, 2022, 41(21): 1-6.
ZHANG Junshu1, LI Dan1, REN Weixin2. Identification of bolt pre-tightening state based on cointegration analysis of vibro-acoustic modulation signals. JOURNAL OF VIBRATION AND SHOCK, 2022, 41(21): 1-6.
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