Ultrasonic Signal Transmission Performance in Bolted Connections of Wood Structures under Different Preloads

Zilong Zhuang,Zhengguang Wang,Ying Liu,Jiawei Chen,Yabin Yu

doi:10.3390/f12060652

Abstract

In industrial applications, bolt connections are simple and economical, contributing to their popularity for use in wood packing boxes. However, they can easily fail when subjected to a continuous vibrational load under usual working conditions such as transportation and hoisting. Based on an ultrasonic technique, nondestructive evaluation can be used to quickly detect large-scale structures, but the complex propagation properties in wood limit its application. To solve this problem, a time-reversal method was adopted to predict the residual preload on bolted connections by focusing on the signals collected by wood structures, which helps to assess the structures’ reliability. In this study, the residual preload of bolted connections in wood structures was predicted using the deep-learning method, LSTM, one-dimensional Resnet and Densenet, and tree classification models. It was confirmed that the use of the time-reversal method for ultrasonic detection focused on the signals transmitted in bolted connections of wood structures and deep-learning methods are a feasible way to predict an ultrasonic transmission model.

Highlights

Wood is an organic, heterogeneous, and anisotropic material, the utility and applicability of which are determined by its mechanical properties, such as the modulus of rupture (MOR), modulus of elasticity (MOE), and tensile strength (TS) [1,2]
The five-period, single-frequency signal modulated by the Hanning window function was selected as the excitation signal, and this can be expressed as follows (Equation (8)): x(t)
The signal transmission in bolted connections of the wood structure was classified with the recurrent neural network long short-term memory (LSTM), one-dimensional WideResnet40_2, one-dimensional Densenet121, XGBOOST tree classification model, LightGBM, and the Symbolic Aggregate Approximation (SAX)-vector space model (VSM) algorithm

Summary

Introduction

Heterogeneous, and anisotropic material, the utility and applicability of which are determined by its mechanical properties, such as the modulus of rupture (MOR), modulus of elasticity (MOE), and tensile strength (TS) [1,2]. As a type of renewable material, wood is widely used in industrial production [3]. Wood plays an indispensable link between packaging and transportation. Bolted connections are commonly adopted in wood packaging. Due to being impacted by continuous vibration during transportation, bolted connections within a packing box are lost, leading to an unreliable overall structure. The strength of wood structure bolt connections depends on both the properties of wood (defects, density, quality, etc.) and bolt (quality, size, etc.). The more intuitive performance is that the residual preload on the bolt will decrease or even disappear

Methods

Results

Conclusion