• Wind and Structures
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• v.21 no.6
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• pp.709-726
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• 2015

In this study, a novel vision-based bolt-loosening monitoring technique is proposed for bolted joints connecting tubular steel segments of the wind turbine tower (WTT) structure. Firstly, a bolt-loosening detection algorithm based on image processing techniques is developed. The algorithm consists of five steps: image acquisition, segmentation of each nut, line detection of each nut, nut angle estimation, and bolt-loosening detection. Secondly, experimental tests are conducted on a lab-scale bolted joint model under various bolt-loosening scenarios. The bolted joint model, which is consisted of a ring flange and 32 sets of bolt and nut, is used for simulating the real bolted joint connecting steel tower segments in the WTT. Finally, the feasibility of the proposed vision-based technique is evaluated by bolt-loosening monitoring in the lab-scale bolted joint model.

• Tribology and Lubricants
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• v.35 no.1
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• pp.65-70
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• 2019

Self-loosening of bolts owing to external forces occurs in several machines that are clamped by bolts and nuts. This study focuses on the self-loosening of the aiming bolt of the head lamp in a vehicle. It is important to prevent the aiming bolt from self-loosening as it has a decisive effect on the angle of the head lamp. A nut clamped with a bolt, known as a retainer, is made of plastic and has a partial screw thread. In addition, a transverse load has a considerable impact on the self-loosening of a bolt. We concentrate on the self-loosening of a bolt by a transverse load. The aim of this study is to define the limits of the external force that loosen the bolt. Based on the above conditions, we derive a theoretical equation and develop a numerical analysis program that can calculate the limiting forces for self-loosening. To verify the developed program, we design a test device that can measure the self-loosening by applying sliding forces to the aiming bolt. Using this method, we can draw the following conclusions. First, the developed testing device is suitable to prove the theory for calculating the self-loosening force. Second, the equation confirms the relationship of bolt self-loosening between resistance torque and shear force. Finally, the equation obtains the minimum value of the resistance torque required to decrease the change in the angle of the head lamp, thereby improving the possibility of increasing the stability of the head lamp.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.12
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• pp.1004-1011
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• 2018

Recently, pyrotechnic separation nut has attracted a considerable attention because of its shock reduction effect among various pyrotechnic mechanical devices. However, its bolt loosening behavior under transverse vibration has not been studied sufficiently, since segmented nuts are utilized instead of conventional nut in pyrotechnic separation nut. With the background, bolt loosening analyses are carried out referring to Junker vibration test. The analysis procedure consists of two steps. The first step is the bolt fastening step, screwing the bolt by fastening torque. The second step is the bolt loosening step under transverse vibration. Through the procedure, bolt loosening behaviors are obtained, and the effect of clearance on loosening behavior is closely investigated for reliable design of pyrotechnic separation nut.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.4
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• pp.265-272
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• 2019

In this paper, a vision-based deep learning algorithm and image processing method are proposed to detect bolt-loosening in steel connections. To achieve this objective, the following approaches are implemented. First, a bolt-loosening detection method that includes regional convolutional neural network(RCNN)-based deep learning algorithm and Hough line transform(HLT)-based image processing algorithm are designed. The RCNN-based deep learning algorithm is developed to identify and crop bolts in a connection image. The HLT-based image processing algorithm is designed to estimate the bolt angles from the cropped bolt images. Then, the proposed vision-based method is evaluated for verifying bolt-loosening detection in a lab-scale girder connection. The accuracy of the RCNN-based bolt detector and HLT-based bolt angle estimator are examined with respect to various perspective distortions.

• Smart Structures and Systems
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• v.24 no.3
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• pp.293-301
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• 2019

Bolted joints are commonly used in civil infrastructure and mechanical assembly structures. Monitoring and identifying the connection status of bolts is the frontier problem of structural research. The existing research is mainly on the looseness of a single bolt. This article presents a study of assessing the loosening/tightening health state and identifying the loose bolt by using ultrasonic guided wave in a bolt group joint. A bolt-tightening index was proposed for evaluating the looseness of a bolt connection based on correlation coefficient. The tightening/loosening state of the bolt was simulated by changing the bolt torque. More than 180 different measurement tests for total of six bolts were conducted. The results showed that with the bolt torque increases, value of the proposed bolt-tightening index increases. The proposed bolt-tightening index trend was very well reproduced by an analytical expression using a function of the torque applied with an overall percentage error lower than 5%. The developed damage index based on the proposed bolt-tightening index can also be applied to locate the loosest bolt in a bolt group joint. To verify the effectiveness of the proposed method, a bolt group joint experiment with different positions of bolt looseness was performed. Experimental results show that the proposed approach is effective to detect and locate bolt looseness and has a good prospect of finding applications in real-time structural monitoring.

• Smart Structures and Systems
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• v.15 no.1
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• pp.41-55
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• 2015

This study proposes a laser based impedance measurement system and impedance based pipe corrosion and bolt-loosening monitoring techniques under temperature variations. For impedance measurement, the laser based impedance measurement system is optimized and adopted in this paper. First, a modulated laser beam is radiated to a photodiode, converting the laser beam into an electric signal. Then, the electric signal is applied to a MFC transducer attached on a target structure for ultrasonic excitation. The corresponding impedance signals are measured, re-converted into a laser beam, and radiated back to the other photodiode located in a data interrogator. The transmitted impedance signals are treated with an outlier analysis using generalized extreme value (GEV) statistics to reliably signal off structural damage. Validation of the proposed technique is carried out to detect corrosion and bolt-loosening in lab-scale carbon steel elbow pipes under varying temperatures. It has been demonstrated that the proposed technique has a potential to be used for structural health monitoring (SHM) of pipe structures.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.4
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• pp.221-232
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• 2023

This paper presents a novel convolutional neural network (CNN)-based approach for predicting bolt clamping force in the early bolt loosening state of bolted structures. The approach entails tightening eight bolts with different clamping forces and generating frequency responses, which are then used to create a similarity map. This map quantifies the magnitude and shape similarity between the frequency responses and the initial model in a fully fastened state. Krylov subspace-based model order reduction is employed to efficiently handle the large amount of frequency response data. The CNN model incorporates a regression output layer to predict the clamping forces of the bolts. Its performance is evaluated by training the network by using various amounts of training data and convolutional layers. The input data for the model are derived from the magnitude and shape similarity map obtained from the frequency responses. The results demonstrate the diagnostic potential and effectiveness of the proposed approach in detecting early bolt loosening. Accurate bolt clamping force predictions in the early loosening state can thus be achieved by utilizing the frequency response data and CNN model. The findings afford valuable insights into the application of CNNs for assessing the integrity of bolted structures.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.603-606
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• 2006

We present a study on the development of a practical and quantitative technique for the assessment of the structural health condition with using piezoceramic(PZT) sensors. The electro-impedance-based technique with the PZT patches is very sensitive for evaluation of the incipient and small damage in a high frequency range, and however the commonly traditional modal analysis method is effective only for considerably larger damages in low frequency range. The paper presents the technique in detecting and characterizing real-time damage on the specimen that is an aluminum plate fastened with bolts and nuts by different torques and as well a plate with a crack. By using the special arrangement of the PZT sensors, the required longitudinal wave is generated through the specimen. A large number of experiments are conducted and the different conditions of the specimens, i.e. the location and extent of loosening bolts, and the plate with a crack are simulated. respectively. Since fixing and loosening the loosened bolt is controlled by a torque wrench, we can control exactly the experiment of the different torques. Compared with the simulated healthy condition, we can find whether or not there is a damage in the specimen with using an impedance analyzer with the PZT sensors. Several indices are discussed and used for assessing the different simulated damages. As for the location of bolt loosening, the RMSD is found to be the most appropriate index for numerical assessment and as well the RMSD shows strongly linear relationship for assessing the extent of the bolt loosening, and the frequency peak shift ${\Delta}F$ is used to assess the cracked plate. The possibility of repeatability of the pristine condition signatures is also presented and the appropriate frequency range and interval are uniquely selected through large numbers of experiments.

• Smart Structures and Systems
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• v.16 no.2
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• pp.281-294
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• 2015

Bolted joint connection is the most commonly used connection element in structures and devices. The loosening due to external dynamic loads cannot be observed and measured easily and may cause catastrophic loss especially in an extreme requirement and/or environment. In this paper, an innovative Real-time Cross-Correlation Method (RCCM) for monitoring of the bolted joint loosening was proposed. We apply time reversal process on stress wave propagation to obtain correlation signal. The correlation signal's peak amplitude represents the cross-correlation between the loosening state and the baseline working state; therefore, it can detect the state of loosening. Since the bolt states are uncorrelated with noise, the peak amplitude will not be affected by noise and disturbance while it increases SNR level and increases the measured signals' reliability. The correlation process is carried out online through physical wave propagation without any other post offline complicated analyses and calculations. We implemented the proposed RCCM on a single bolt/nut joint experimental device to quantitatively detect the loosening states successfully. After that we implemented the proposed method on a real large structure (reaction wall) with multiple bolted joint connections. Loosening indexes were built for both experiments to indicate the loosening states. Finally, we demonstrated the proposed method's great anti-noise and/or disturbance ability. In the instrumentation, we simply mounted Lead Zirconium Titanate (PZT) patches on the device/structure surface without any modifications of the bolted connection. The low-cost PZTs used as actuators and sensors for active sensing are easily extended to a sensing network for large scale bolted joint network monitoring.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.8
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• pp.28-34
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• 2020

In this study, hole-boss locking washers were developed to prevent vibrational loosening, and a benchmark test was conducted to compare these washers with existing wedge locking washers, which are imported and high-priced. The developed washers consist of an upper washer with bosses and a lower washer with holes, and the bosses are caught in the holes so that the bolt is not loosened. Additionally, the top side of the upper washer and the underside of the lower washer have small wedges perpendicular to the direction of the bolt loosening, suppressing slips. A test by the Korea Test Laboratory indicated that the ratio of the loosening torque to the joining torque is greater than 70%, confirming that the developed washers have a sufficiently high anti-loosening performance. A Junker test apparatus was manufactured for the testing of vibrational loosening and a test comparison between the proposed washers and the existing wedge locking washers shows that the proposed washers have a slower reduction in the clamping force and a higher loosening-resistance in a vibrational circumstance compared with the wedge locking washers. These results indicate that the developed washers demonstrate a high performance and boast price competitiveness.