螺栓连接松动的监检测技术研究进展  

Detection and Monitoring Technologies for Bolt Connection Loosening:a Review

作　　者：龚裕 唐国良[2] 王孝然 刘增华 GONG Yu;TANG Guoliang;WANG Xiaoran;LIU Zenghua(College of Materials Science and Engineering,Beijing University of Technology,Beijing 100124,China;College of Mechanical and Energy Engineering,Beijing University of Technology,Beijing 100124,China;School of Information Science and Technology,Beijing University of Technology,Beijing 100124,China)

机构地区：[1]北京工业大学材料科学与工程学院,北京100124 [2]北京工业大学机械与能源工程学院,北京100124 [3]北京工业大学信息科学技术学院,北京100124

出　　处：《北京工业大学学报》2025年第2期192-213,共22页Journal of Beijing University of Technology

基　　金：国家自然科学基金资助项目(62203025)。

摘　　要：螺栓连接的完整性维护仍然是一个面临众多挑战的问题,特别是在遭受外部干扰(如振动)时,连接界面表面可能会发生大面积或局部的滑移。这种滑移现象会加剧界面间的相对运动,导致预紧力水平下降,也就是螺栓连接的松动。在过去的10年中,诸如振动法、导波法和机电阻抗法等检测方法已逐渐应用于检测螺栓连接的松动。伴随着计算能力的显著提升,机器学习算法包括神经网络和支持向量机已被开发出来,用于进一步提升螺栓松动检测方法的准确性。这些方法的融合为螺栓连接的实时健康监测提供了新的途径。该文综述了基于声弹性效应、振动、导波和机电阻抗的方法,以及基于机器学习算法的信号分析方法在螺栓连接松动检测和监测领域的应用,旨在展示近年来该领域的研究进展。The maintenance of integrity in bolted connections remains a challenging issue,especially when subjected to external disturbances such as vibrations,which may cause extensive or localized slip at the interface surfaces.This slip phenomenon exacerbates the relative motion between interfaces,leading to a decrease in preload levels,i.e.,loosening of bolted assemblies.Over the past decade,detection methods such as vibration,guided waves and electromechanical impedance techniques have been gradually applied for detecting loosening in bolted connections.With the significant advancement in computational capabilities,machine learning algorithms including neural networks and support vector machines have been developed to further enhance the accuracy of bolt loosening detection methods.The integration of these methods offers a new pathway for real-time health monitoring of bolted connections.This paper reviews the application of methods based on the acoustoelastic effect,vibration,guided waves,electromechanical impedance,and the application of signal analysis methods based on machine learning algorithms in the field of bolt connection looseness detection and monitoring,aiming to showcase the research progress in this field in recent years.

关 键 词：螺栓连接 螺栓松动 机器学习 信号分析 无损检测 结构健康监测 

分 类 号：U461[机械工程—车辆工程] TP308[交通运输工程—载运工具运用工程]