A nonlinear ultrasonic method for real-time bolt looseness monitoring using PZT transducer–enabled vibro-acoustic modulation

Zhao, Nan; Huo, Linsheng; Song, Gangbing

doi:10.1177/1045389x19891534

Cited by 49 publications

(38 citation statements)

References 85 publications

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“…Ultrasonic non-destructive methods, such as the piezoelectric ultrasonic method [6][7][8], the EMAT ultrasonic method [9][10][11], and the acoustoelastic effect method [12][13][14][15][16][17], have been reported to measure bolt axial stress. The piezoelectric ultrasonic method is primarily used for loosening the monitoring of bolted connections.…”

Section: Introductionmentioning

confidence: 99%

A New Axial Stress Measurement Method for High-Strength Short Bolts Based on Stress-Dependent Scattering Effect and Energy Attenuation Coefficient

Chen

Yin

2022

Sensors

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The accurate estimation of axial stresses is a major problem for high-strength bolted connections that needs to be overcome to improve the assembly quality and safety of aviation structures. However, the conventional acoustoelastic effect based on velocity-stress dependence is very weak for short bolts, which leads to large estimation errors. In this article, the effect of axial stress on ultrasonic scattering attenuation is investigated by calculating the change in the energy attenuation coefficient of ultrasonic echoes after applying axial preload. Based on this effect, a stress-dependent attenuation estimation model is developed to measure the bolt axial stress. In addition, the spectrum of the first and second round-trip echoes is divided into several frequency bands to calculate the energy attenuation coefficients, which are used to select the frequency band sensitive to the axial stress changes. Finally, the estimation model between axial stress and energy attenuation coefficients in the sensitive frequency band is established under 20 steps of axial preloads. The experimental results show that the energy attenuation coefficient in the sensitive band corresponds well with axial stress. The average relative error of the predicted axial stress is 6.28%, which is better than that of the conventional acoustoelastic effect method. Therefore, the proposed approach can be used as an effective method to measure the axial stress of short bolts in the assembly of high-strength connections.

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Section: Introductionmentioning

confidence: 99%

A New Axial Stress Measurement Method for High-Strength Short Bolts Based on Stress-Dependent Scattering Effect and Energy Attenuation Coefficient

Chen

Yin

2022

Sensors

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“…It mainly aims to identify whether there is damage in the structure [27], determine the specific damage location [28], quantify the degree of structural damage, and evaluate the remaining service life of the structure [29]. In addition, piezoelectric ceramics can be used as both sensors and actuators based on the direct and inverse piezoelectric effects [30,31]. In the electro-mechanical impedance (EMI) method [32], the piezoelectric ceramic transducer acts as both an actuator and a sensor to evaluate the health state [33] of the monitored structure by comparing impedance measurements during its baseline healthy state [34] and measurements after damage has occurred [35,36].…”

Section: Introductionmentioning

confidence: 99%

Monitoring of Liquid Viscosity for Viscous Dampers through a Wireless Impedance Measurement System

Jia

Luo

2021

Applied Sciences

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Viscous dampers are a type of seismic damping equipment widely used in high-rise buildings and bridges. However, the viscosity of the damping fluid inside the viscous damper will change over time during its use, which significantly reduces the seismic performance of the viscous damper. Hence, it is necessary to monitor the viscosity of the fluid inside the damper over its service life. In this paper, a damping fluid viscosity monitoring method based on wireless impedance measurement technology is proposed. A piezoelectric sensor is installed in a damper cylinder specimen, and the viscosity of the damping fluid is determined by measuring the piezoelectric impedance value of the sensor. In this study, 10 samples of damping fluids with different viscosities are tested. In order to quantitatively correlate damping fluid viscosity and electrical impedance, a viscosity index (VI) based on the root mean square deviation (RMSD) is proposed. The experimental results show that the variation of the real part in the impedance signal can qualitatively determine the damping fluid viscosity while the proposed VI can effectively and quantitatively identify the damping fluid viscosity.

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“…Further, the fluctuation of the impedance signatures in frequency was utilized to evaluate the bolted joint with the developed "smart washer" [20]. A novel vibroacoustic modulation method was proposed to monitor the early looseness of a bolt in real time [21]. Notably, although the contact sensor-based methods are proposed to detect the decrease of preload induced by initial bolt looseness, they can also be used to detect the delayed fracture of bolts, which is a kind of brittle damage and can result in the disappearance of the preload [22,23].…”

Section: Introductionmentioning

confidence: 99%

Computer Vision‐Based Detection for Delayed Fracture of Bolts in Steel Bridges

Zhou

Huo

2021

Journal of Sensors

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The delayed fracture of high-strength bolts occurs frequently in the bolt connections of long-span steel bridges. This phenomenon can threaten the safety of structures and even lead to serious accidents in certain cases. However, the manual inspection commonly used in engineering to detect the fractured bolts is time-consuming and inconvenient. Therefore, a computer vision-based inspection approach is proposed in this paper to rapidly and automatically detect the fractured bolts. The proposed approach is realized by a convolutional neural network- (CNN-) based deep learning algorithm, the third version of You Only Look Once (YOLOv3). A challenge for the detector training using YOLOv3 is that only limited amounts of images of the fractured bolts are available in practice. To address this challenge, five data augmentation methods are introduced to produce more labeled images, including brightness transformation, Gaussian blur, flipping, perspective transformation, and scaling. Six YOLOv3 neural networks are trained using six different augmented training sets, and then, the performance of each detector is tested on the same testing set to compare the effectiveness of different augmentation methods. The highest average precision (AP) of the trained detectors is 89.14% when the intersection over union (IOU) threshold is set to 0.5. The practicality and robustness of the proposed method are further demonstrated on images that were never used in the training and testing of the detector. The results demonstrate that the proposed method can quickly and automatically detect the delayed fracture of high-strength bolts.

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A nonlinear ultrasonic method for real-time bolt looseness monitoring using PZT transducer–enabled vibro-acoustic modulation

Cited by 49 publications

References 85 publications

A New Axial Stress Measurement Method for High-Strength Short Bolts Based on Stress-Dependent Scattering Effect and Energy Attenuation Coefficient

A New Axial Stress Measurement Method for High-Strength Short Bolts Based on Stress-Dependent Scattering Effect and Energy Attenuation Coefficient

Monitoring of Liquid Viscosity for Viscous Dampers through a Wireless Impedance Measurement System

Computer Vision‐Based Detection for Delayed Fracture of Bolts in Steel Bridges

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