Review of Bolted Connection Monitoring

Wang, Tao; Song, Gangbing; Liu, Shaopeng; Li, You–Rong; Xiao, Han

doi:10.1155/2013/871213

Cited by 119 publications

(92 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Currently, there are a few methods to monitor the condition of bolt joints by measuring the bolt axial load [1]. A common method is to employ a strain gauge to measure the bolt strain and determine the bolt preload.…”

Section: Introductionmentioning

confidence: 99%

“…d 31 and κ are the piezoelectric strain coefficient and the wave number, respectively. Equation (1) shows that the output admittance signature is affected by both the structural and sensor dynamics, since the admittance is the response of the structure to the harmonic actuation of the piezoelectric transducer and the applied load will influence the response of the structure in the presence of mechanical impedance. The stress changes at a specific location on the structure will cause resonant frequency shift, and vibration mode change of the structure, which will be reflected in changes in the admittance signature [37,38].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Bolt Looseness Detection Based on Piezoelectric Impedance Frequency Shift

et al. 2016

Self Cite

View full text Add to dashboard Cite

Abstract:In this paper, a piezoelectric impedance frequency shift method is developed to estimate the bolt preload for the detection of bolt looseness in engineering structures. An experimental device that allows the precision control of the axial preload force on a bolt is designed and fabricated. A universal testing machine is used to preload accurately on the bolt in the experiments. Under different bolt preload conditions, the impedance analyzer measures the admittance (inverse of the impedance) signal of the PZT (Lead ZirconateTitanate) patches which are bonded on the bolt head. Firstly, a wide frequency band is swept to find a sensitive frequency band of the piezoelectric admittance with the imaginary part. Then in the sensitive frequency band, a specified peak frequency of the admittance signature is chosen to investigate the frequency shift with different bolt preloads. The relationship between the specified frequency shift and the bolt preload is established. The experimental results show that the specified peak frequency decreases as the bolt preload increases for both M16 and M12 bolts, and the frequency shift has a linear relationship with the preload on the bolt. The frequencies of the real and imaginary parts of the admittance signature have the same results. Therefore, the bolt preload can be determined by measuring the specified frequency shift and this method has a good application prospect.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bolt Looseness Detection Based on Piezoelectric Impedance Frequency Shift

et al. 2016

Self Cite

View full text Add to dashboard Cite

show abstract

“…[25][26][27][28][29] The usefulness of the piezoceramic ultrasonicbased bolted connection interface loosening detection of pipe-like structures has been demonstrated by both numerical and experimental methods. 23,[30][31][32] This article aims to perform a further study on detecting the BSJ looseness of SGSs. A PZT wave energy-based method is applied in the BSJ looseness detection research under several common conditions, to establish the relationship between ultrasonic wave energy attenuations and bolt loosening levels by both experimental validation and numerical finite element analysis (FEA) simulation.…”

Section: Introductionmentioning

confidence: 99%

Connection looseness detection of steel grid structures using piezoceramic transducers

Yan

Liu

Song

et al. 2018

International Journal of Distributed Sensor Networks

Self Cite

View full text Add to dashboard Cite

Connection looseness phenomena of steel grid structures might induce issues of lowering integrity, large deformation, even total collapse of the structures. The goal of this article is to propose an evaluation method for bolt-sphere joint looseness of steel grid structures using piezoceramic guided wave-based method through experiments and numerical simulations. A single bolt-sphere joint looseness experimental model is established and tested, considering grid member connection angles of 0°, 45°, 90°, and 180°, respectively. Then, multiple bolt-sphere joint looseness detection tests by selecting six kinds of cases for a steel grid structure model are performed. Piezoceramic patch arrays bonded on the surface of grid members are used as transducers to generate and receive detection guided waves, and external torques are applied to indirectly simulate the bolt-sphere joint looseness effect. The experimental results show that the bolt-sphere joint looseness impact on the ultrasonic wave energy attenuation has a nonlinear regularity. Based on the regularity, an evaluation method and key techniques for the bolt-sphere joint looseness detection based on guided wave energy are proposed and experimentally validated. To further clarify the bolt-sphere joint looseness detection mechanism, the ABAQUS software is used for a finite element analysis of the single bolt-sphere joint looseness evaluation. The numerical and experimental results match well, verifying the feasibility of the proposed method.

show abstract

“…Contact sensor-based methods detect the damage through natural frequencies and mode shapes of the structures [13]. To date, many contact sensorsbased methods have been developed for the monitoring and damage detection of structures [14][15][16][17][18]. From the available literature, the contact sensor-based methods comprise of vibrations, wavelets, ultrasonic methods, model updating methods etc.…”

Section: Contact Sensor-based Methodsmentioning

confidence: 99%

Automated Vision-Based Loosened Bolt Detection Using the Cascade Detector

Ramana

Cha

2017

Sensors and Instrumentation, Volume 5

View full text Add to dashboard Cite

Numerous damage detection methods that use data obtained from contact sensors, physically attached to structures and human inspection methods have been developed. However, damage sensitive features used for these methods such as modal properties of steel and reinforced concrete structures are sensitive to environmental conditions such as temperature and humidity. Besides, human inspection is cost, labor extensive, and is controlled by the technical understanding of an individual. The uncertainties of the contact sensor methods are difficult to address with a regression model or any other temperature compensation method, and these are primary causes of false alarms. In order to address some of these challenges of the traditional sensing system, a vision-based remote sensing system can be one of the alternatives as it gives the explicit intuitions of structural conditions. In addition, bolted connections are common engineering practices, and very few vision-based techniques are developed for loosened bolt detection. Thus, this thesis proposes an automated vision-based method for detecting loosened structural bolts using the Viola-Jones algorithm and support vector machines. The test images of bolt connections are taken with a digital single lens reflex camera. The Viola-Jones algorithm is trained on two datasets of images with and without bolts. The trained algorithm localizes and crops all the bolts on test images. The SVM is trained on another dataset of loose and tight bolts to generate decision boundary for classification of the loosened and tight bolts. The cropped bolt images are binarized to calculate bolt features as head dimensions and exposed shank length. The extracted features are fed into a trained support vector machine to classify the loosened and tight bolts. We test our method on images taken by digital single lens reflex and smartphone cameras.iii A special feeling of gratitude to my loving parents. Their words of encouragement, support, and prayers helped me to come this far.iv

show abstract

Review of Bolted Connection Monitoring

Cited by 119 publications

References 42 publications

Bolt Looseness Detection Based on Piezoelectric Impedance Frequency Shift

Bolt Looseness Detection Based on Piezoelectric Impedance Frequency Shift

Connection looseness detection of steel grid structures using piezoceramic transducers

Automated Vision-Based Loosened Bolt Detection Using the Cascade Detector

Contact Info

Product

Resources

About