Monitoring of the Looseness in Cargo Bolts under Random Excitation Based on Vibration Transmissibility

Guangming Dong,Jin Chen,Fagang Zhao,Jean-Jacques Sinou

doi:10.1155/2021/8841940

Abstract

Bolted joints are widely used in industrial applications and joint failure can cause a disastrous accident if loosening happens. Bolt loosening detection can be made by regular manual inspection or by using sensors based on different physical principles, such as acoustoelastic effect, piezoelectric active sensing, and electromechanical impedance. Compared with the above methods, vibration based bolt looseness monitoring using accelerometers is appealing for its economy and convenience for measurement. In this paper, cargo bolts looseness monitoring under random excitation is studied based on vibration transmissibility, which overcomes the drawback of commonly used vibration methods in finding local bolt looseness. Vibration transmissibility analysis only uses two vibration transducers to monitor bolt group looseness, where the vibration signal below the cargo bolts is used as the “input” and the other one above the cargo bolts is used as the “output.” There are 12 bolts in the cargo bolts studied in this paper, providing an essential clamping force to fix cargo during transportation. Six kinds of bolt group looseness with an increasing degree are simulated in the experiment. The experimental analysis shows that variation of the spectral moment can be used to monitor the global variation of the torque wrench exerted on the cargo bolts. The early stage of the bolt group looseness is that some one or two bolts begin to loose; however, the spectrum moment factor is insensitive to the local bolt looseness in the bolt group. To address this issue, the eigensystem realization algorithm (ERA) based on random input and output is utilized to find the subtle eigenvalue variation of the system matrix, which is neglected by the frequency transmissibility function. The experimental results show the effectiveness of the proposed method for detecting local bolt looseness.

Highlights

Bolted joints are widely used in mechanical and civil structures, such as machine tools, industrial robots, transport machines, bridges, and steel towers
The vibration signal below the cargo bolts is used as the “input,” and the vibration signal above the cargo bolts is used as the “output”; the concept of vibration transmissibility is used for bolt looseness monitoring. e frequency transmissibility function is calculated, and the derived spectrum moment factor is found to be related to the variation of torque level of the whole bolt group
E organization of this paper is as follows: the second section describes the studied cargo bolts and bolt looseness simulation; the third section shows the effectiveness of the frequency transmissibility function on bolt group looseness while showing its insensitivity to local bolt looseness; and the fourth and fifth sections give the solution based on identification in the state-space domain

Summary

Introduction

Bolted joints are widely used in mechanical and civil structures, such as machine tools, industrial robots, transport machines, bridges, and steel towers. Using random excitation as a controlled input can be found in [29], where the authors studied statistical properties in time domain and signal power in different frequency bands for the measured vibration data, by which the bolt loosening can be detected. The spectrum moment factor is insensitive to the local bolt looseness in the bolt group To address this issue, the algorithm for the identification of a balanced state-space representation is utilized to find the subtle eigenvalue variation of the system matrix, which is neglected by the frequency transmissibility function. E organization of this paper is as follows: the second section describes the studied cargo bolts and bolt looseness simulation; the third section shows the effectiveness of the frequency transmissibility function on bolt group looseness while showing its insensitivity to local bolt looseness; and the fourth and fifth sections give the solution based on identification in the state-space domain.

The Proposed Algorithm for Cargo Bolts Looseness Monitoring

Physical Mode Determination through Stabilization

Experimental Results