Bolted joints are widely used for component connections due to their ease of assembly and high load-bearing capacity.However,due to improper installation and external loads,bolted connections are prone to loss of preload.Bolt loosening would reduce the reliability of the structure and even lead to structural failure.Therefore,accurate monitoring of bolt preload is crucial to en-sure the reliability and safety of the structure.Ultrasonic guided wave and electromechanical im-pedance techniques are commonly employed for structural health monitoring.In recent years,the rapid development of machine learning techniques,especially deep learning techniques,has attrac-ted widespread attention.Hence,this paper presents a review of intelligent monitoring methods for bolt preload force based on piezoelectric sensors,including the application of traditional machine learning techniques and deep learning techniques.The purpose is to sort out the current development status and important breakthroughs in the intelligent monitoring of bolt preload and provide a reference for promoting the technical development and engineering application in the field of structural health monitoring.
维普
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