Loosening state monitoring and identification of multi-bolted flange joints based on nonlinear wave energy transmission

IF 7.9 1区 工程技术 Q1 ENGINEERING, MECHANICAL
Xu Chen, Wen Han, Zhousuo Zhang
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引用次数: 0

Abstract

Looseness detection of complex multi-bolted flange joints has long been an important problem to be focused on, especially for the scene of unknown multi-bolt loosening at the same time. In this study, a stable, efficient and robust guided wave recognition method for multi-bolt loosening is proposed for the first time by taking long-term monitoring data. This method studies the nonlinear characteristics of transmitted wave energy with bolt preload by formula. Then, a novel probability indicator reflecting the loosening position is proposed and a prior prediction model of bolt loosening degree is established. The prediction model is based on prior data fitting in a small number of working conditions, which has obvious advantages over deep learning. The simulation and experimental results based on flange pipes show that the proposed indicator can effectively determine the loosening positions of multiple bolts, and the prediction model also performs well in degree recognition. The proposed detection method has great potential in real-time monitoring applications by virtue of its high sensitivity to the loosening of multi-bolted joint structures.
基于非线性波能传输的多螺栓法兰连接松动状态监测与识别
长期以来,复杂多螺栓法兰连接的松动检测一直是一个需要重点解决的重要问题,尤其是对于多螺栓同时松动的未知现场。本研究通过长期监测数据,首次提出了一种稳定、高效、鲁棒的多螺栓松动导波识别方法。该方法通过公式研究了导波能量随螺栓预紧力变化的非线性特征。然后,提出了反映松动位置的新型概率指标,并建立了螺栓松动程度的先验预测模型。该预测模型基于少量工况下的先验数据拟合,与深度学习相比具有明显优势。基于法兰管道的仿真和实验结果表明,所提出的指标能有效确定多个螺栓的松动位置,预测模型在松动程度识别方面也表现良好。所提出的检测方法凭借其对多螺栓连接结构松动的高灵敏度,在实时监测应用中具有很大的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Mechanical Systems and Signal Processing
Mechanical Systems and Signal Processing 工程技术-工程:机械
CiteScore
14.80
自引率
13.10%
发文量
1183
审稿时长
5.4 months
期刊介绍: Journal Name: Mechanical Systems and Signal Processing (MSSP) Interdisciplinary Focus: Mechanical, Aerospace, and Civil Engineering Purpose:Reporting scientific advancements of the highest quality Arising from new techniques in sensing, instrumentation, signal processing, modelling, and control of dynamic systems
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