Quantitative evaluation of bolt connection using a single piezoceramic transducer and ultrasonic coda wave energy with the consideration of the piezoceramic aging effect

Hei, Chuang; Luo, Mingzhang; Gong, Panpan; Song, Gangbing

doi:10.1088/1361-665x/ab6076

Cited by 44 publications

(34 citation statements)

References 59 publications

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“…Experimental results obtained from the three different specimens demonstrated that the method can quantify bolt looseness with an accuracy of more than 95.78%. Single monitoring indices, such as the peak value of a time reversal signal (Tao et al, 2016) and normalized coda wave energy (Hei et al, 2020), are unable to provide true quantitative monitoring due to the dispersion of the single indices. On the other hand, through powerful feature extraction and classification abilities, the trained 1DCNN model can quantitatively monitor the state of bolt looseness.…”

Section: Discussionmentioning

confidence: 99%

“…A concept of "smart washers" was proposed to monitor bolt looseness through a normalized wavelet energy index . Taking into account the aging of piezoceramic materials, the tracking of normalized coda wave energy helped to monitor the tightness of a single bolt (Hei et al, 2020). However, these methods are inadequate for conducting quantitative monitoring because they fail to accurately and quantitatively correlate bolt looseness states with a single monitoring index.…”

Section: Introductionmentioning

confidence: 99%

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Quantitative Monitoring of Bolt Looseness Using Multichannel Piezoelectric Active Sensing and CBAM-Based Convolutional Neural Network

et al. 2021

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The bolted connection is widely utilized in engineering to practically and rigidly couple structural components. The integrity of the connection is paramount to the safety of the structure and has prompted the development of many monitoring methods, including the piezoelectricity-based active sensing method. However, the active sensing method cannot quantify bolt looseness due to the unclear relationship between bolt looseness and the single monitoring index typically used in the active sensing method. Thus, the authors propose the unique combination of a one-dimensional convolutional neural network (1DCNN) and multichannel active sensing for quantitative monitoring of bolted connections. In an experiment, piezoelectric ceramic transducer (PZT) patches are bonded on steel plates connected by a bolt. Each patch is wired to a multichannel active sensing monitoring system. After obtaining multichannel stress wave signals at different looseness levels, a looseness vector is calculated to generate training and validation datasets. A baseline 1DCNN model and a novel model improved using the convolutional block attention module (CBAM) are used to monitor the bolt looseness. Finally, the authors verify that the multichannel active sensing method combined with the 1DCNN model can accurately perform quantitative monitoring of bolt looseness, and the monitoring accuracy of the baseline 1DCNN model is above 91.07% in three different specimens. Compared with the baseline 1DCNN model, the monitoring accuracy of the CBAMCNN model improved by approximately 5%. Overall, the method proposed in this article offers a new and highly accurate approach for quantitative monitoring of bolted connections.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Quantitative Monitoring of Bolt Looseness Using Multichannel Piezoelectric Active Sensing and CBAM-Based Convolutional Neural Network

et al. 2021

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“…Past researches have shown that the wavelet package-based energy is sensitive to cracks in concrete structures [62,63]. When the stress wave propagates inside the prestressed curved tendon duct, due to the duct grouting defects, reflection attenuation [64,65], scattering attenuation, and absorption attenuation of stress wave will result in a large loss of stress wave energy. Therefore, the defect degree of the curved tendon duct can be judged according to the change of energy.…”

Section: Wavelet Packet-based Energy Methodsmentioning

confidence: 99%

Detecting of the Longitudinal Grouting Quality in Prestressed Curved Tendon Duct Using Piezoceramic Transducers

Jiang

Zhang

et al. 2020

Sensors

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To understand the characteristics of longitudinal grouting quality, this paper developed a stress wave-based active sensing method using piezoceramic transducers to detect longitudinal grouting quality of the prestressed curved tendon ducts. There were four lead zirconate titanate (PZT) transducers installed in the same longitudinal plane. One of them, mounted on the bottom of the curved tendon duct, was called as an actuator for generating stress waves. The other three, pasted on the top of the curved tendon duct, were called as sensors for detecting the wave responses. The experimental process was divided into five states during the grouting, which included 0%, 50%, 75%, 90%, and 100% grouting. The voltage signals, power spectral density (PSD) energy and wavelet packet energy were adopted in this research. Experimental results showed that all the amplitudes of the above analysis indicators were small before the grouting reached 90%. Only when the grouting degree reached the 100% grouting, these parameters increased significantly. The results of different longitudinal PZT sensors were mainly determined by the distance from the generator, the position of grouting holes, and the fluidity of grouting materials. These results showed the longitudinal grouting quality can be effectively evaluated by analyzing the difference between the signals received by the PZT transducers in the curved tendon duct. The devised method has certain application value in detecting the longitudinal grouting quality of prestressed curved tendon duct.

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“…Traditional ultrasonic techniques have been investigated for axial force monitoring in bolts [ 5 , 6 ]. Transmittance [ 7 ], impedance [ 8 ], and coda wave [ 9 ] methods have also been investigated.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Guided-Wave Mixing for Condition Monitoring of Bolted Joints

Allen

2021

Sensors

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Bolted joints are fundamental to numerous structural components in engineering practice. Nevertheless, their failure or even their loosening can lead to insufficient performance and reduced structural safety. This study presents a theoretical development and experimental investigation into nonlinear guided-wave mixing for integrity monitoring of bolted joints in plates. Combinational harmonics generated due to nonlinear Lamb wave mixing and contact acoustic nonlinearity at the bolted joints were used to evaluate the applied torque level in the joint. The area of the power spectral density in the region of the sum combinational harmonic bandwidth is found to be highly correlated to the applied torque level at the joint. Moreover, the effect of the number of cycles and thus the time duration of the excitation is investigated. The results show that the combinational harmonics remain robust for different numbers of cycles in detecting bolt loosening. The findings presented in this study also provide physical insight into the phenomena of nonlinear Lamb wave mixing for evaluating applied torque in bolted joints, and the results help further advance the use of nonlinear guided waves for damage detection.

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Quantitative evaluation of bolt connection using a single piezoceramic transducer and ultrasonic coda wave energy with the consideration of the piezoceramic aging effect

Abstract: Smart Materials and Structures

Cited by 44 publications

References 59 publications

Quantitative Monitoring of Bolt Looseness Using Multichannel Piezoelectric Active Sensing and CBAM-Based Convolutional Neural Network

Quantitative Monitoring of Bolt Looseness Using Multichannel Piezoelectric Active Sensing and CBAM-Based Convolutional Neural Network

Detecting of the Longitudinal Grouting Quality in Prestressed Curved Tendon Duct Using Piezoceramic Transducers

Nonlinear Guided-Wave Mixing for Condition Monitoring of Bolted Joints

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