Synchronous detection of bolts looseness position and degree based on fusing electro-mechanical impedance

Wang, Lintao; Yuan, Bo; Xu, Zhenbang; Sun, Qingchao

doi:10.1016/j.ymssp.2022.109068

Cited by 36 publications

(16 citation statements)

References 24 publications

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“…They concluded that the method is immune to noise and displayed good recognition accuracy of 92%, 88%, and 82% for the first, second, and third arrangements, respectively. Wang et al 190 introduced an EMI-based method for synchronous detection of position and degree of looseness in multi-bolt structures using SVM. In the first step, they explored the effect of bolt looseness on impedance frequency peak and the relation between excitation frequency and detection range through numerical and experimental analysis.…”

Section: Support Vector Machinementioning

confidence: 99%

Review on recent advances in structural health monitoring paradigm for looseness detection in bolted assemblies

Chelimilla

Chinthapenta

Kali

et al. 2023

Structural Health Monitoring

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The integrity of bolted joints is still a challenging problem owing to the gross or localized slip at the interfacial surfaces of the joints when subjected to external disturbances such as vibrations. This slip escalates the interfacial movement and, thus, leads to a decrease in preload levels, that is, looseness of the bolted assemblies. In the last decade, modal analysis, wave propagation, and percussion methods were traditionally used to detect looseness in bolted connections. With an increase in computational power, machine learning algorithms such as neural networks, random forests, decision trees, and support vector machines complemented the traditional methods in accurate looseness estimation. Subsequently, this integration paved the path for real-time health monitoring of bolted joints. This paper summarizes recent investigations on looseness detection in bolted assemblies based on traditional methods and machine learning algorithms. The working principle, advantages, challenges, and applications of the aforementioned methods are also detailed in this paper. Apart from these investigations, the latest studies on the Internet of Things-based health monitoring of structures are also reviewed to explore their adaptability in remote monitoring of bolted connections for damage detection in the future.

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Section: Support Vector Machinementioning

confidence: 99%

Review on recent advances in structural health monitoring paradigm for looseness detection in bolted assemblies

Chelimilla

Chinthapenta

Kali

et al. 2023

Structural Health Monitoring

View full text Add to dashboard Cite

show abstract

“…By mapping the grid, the model is broken down, and 52,120 grids are chosen to establish a suitable computational model. The maximum size of the mesh finite element is 2.5 mm, which satisfies the requirement that each half-wavelength should be composed of three to five nodal points (Wang et al, 2022). This is because the longitudinal and transverse waves propagating in the aluminum plate at 110 kHz excitation frequency are about 57.96 and 29.05 mm, respectively.…”

Section: The Impedance Response Of the New Sensormentioning

confidence: 99%

An island-bridge packaging piezoelectric sensor for structural health monitoring in high-strain environments

Liao

Sun

Wang

et al. 2022

Journal of Intelligent Material Systems and Structures

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Piezoelectric sensor failure triggered by high structural strain is a critical problem in structural health monitoring (SHM) that cannot be neglected. Thus, a novel island-bridge packaging piezoelectric sensor for SHM in high-strain environments is proposed in this paper. The trapezoidal-section island-bridge structure of the new sensor greatly optimizes the high-strain survivability of the piezoelectric layer. Additionally, good impedance matching characteristics between the monitored structure and the sensor guarantee the transmission strength of high-frequency dynamic sensing signals. The feasibility of the structure and the principle of operation for the novel sensor were demonstrated via theory, simulation and experiment. Besides, an established analytical model and its simulation and experimental verification results displayed that the structural parameters of the sensor could significantly adjust the strain-bearing capacity. Under a specific parameter configuration, the strain transfer coefficient of the novel sensor was only 0.087, which was 12.1% of the conventional sensor, thus could safely operate in the monitoring structure environment of 10,000 με. On the other hand, the proposed sensor’s impedance signal strength was satisfactory in the SHM frequency range of 10–110 kHz, where its average impedance value was as high as 397.7 Ω. Moreover, the optimized signal demonstrated very good stability, reliability, and strength in the test, thus ensuring the effective monitoring of crack propagation via the new sensor. Therefore, this work is a good complement to the existing piezoelectric sensors SHM technique.

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“…21,22 Thanks to the superior performance of piezoelectric sensing technology, the research on health monitoring of bolted joints supported by the piezoelectric vibration method, 23 ultrasonic guided wave (UGW) technique, 24 and electromechanical impedance (EMI) method 25 has burst into a series of valuable achievements in recent years. 26–36 Earlier, research on piezoelectric sensing-based health monitoring techniques for bolted joints focused on investigating the feasibility and effectiveness of piezoelectric sensing in various modes of damage monitoring. 26–28 Recently, the research focus has gradually shifted to developing new damage indices (DIs), 29,31 improving damage localization techniques, 30,35 developing new application-oriented sensor devices, 33 developing integrated damage monitoring techniques, 34 introducing machine learning for damage monitoring, 32,35,36 and investigating composite monitoring techniques that can monitor damage mode and severity.…”

Section: Introductionmentioning

confidence: 99%

“…26–36 Earlier, research on piezoelectric sensing-based health monitoring techniques for bolted joints focused on investigating the feasibility and effectiveness of piezoelectric sensing in various modes of damage monitoring. 26–28 Recently, the research focus has gradually shifted to developing new damage indices (DIs), 29,31 improving damage localization techniques, 30,35 developing new application-oriented sensor devices, 33 developing integrated damage monitoring techniques, 34 introducing machine learning for damage monitoring, 32,35,36 and investigating composite monitoring techniques that can monitor damage mode and severity. 32 These achievements have made significant efforts to advance the development of SHM techniques for bolted joints with significant results.…”

Section: Introductionmentioning

confidence: 99%

A novel damage index integrating piezoelectric impedance and ultrasonic guided wave for damage monitoring of bolted joints

Liao

Sun

Wang

et al. 2023

Structural Health Monitoring

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The structural safety of bolted joints, one of the typical connection techniques utilized in engineering applications, is threatened by the harsh service environment. Herein, a novel damage index (DI) integrating piezoelectric impedance and ultrasonic guided wave is proposed for satisfying the damage monitoring needs of bolted joints. By integrating the two sensing techniques, the shortcomings of a single sensing technique in terms of signal interpretation, stability, and structural adaptability are eliminated. The novel damage severity factor DIZ-V is formed by fusing the damage indices DIZ and DIV weighted by multi-class DIs of the two sensing techniques. Thanks to DIZ-V and a damage mode identification factor presented in this paper, the damage modes and damage severity of early-stage bolt loosening and crack damage are identified. Furthermore, a novel dynamic superposition model (DSM) based on a dynamic-update baseline is developed to address the deficiency that the static baseline method (SBM) has. SBM utilizes the undamaged state signal as the baseline and has the problem of being prone to failure in the later-stage of monitoring. Thus, the phenomenon of nonlinear variation of DIZ-V caused by damage deterioration was avoided via DSM optimization. The feasibility and effectiveness of the proposed method were verified by conducting a series of practical damage identification tests on aluminum bolted joints. And the results demonstrated that the proposed technique could not only identify the severity and mode of damage, but also has excellent reliability. Therefore, the novel damage monitoring technique for bolted joints is a good complement to the existing techniques, which can provide a new strategy for damage monitoring.

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Synchronous detection of bolts looseness position and degree based on fusing electro-mechanical impedance

Cited by 36 publications

References 24 publications

Review on recent advances in structural health monitoring paradigm for looseness detection in bolted assemblies

Review on recent advances in structural health monitoring paradigm for looseness detection in bolted assemblies

An island-bridge packaging piezoelectric sensor for structural health monitoring in high-strain environments

A novel damage index integrating piezoelectric impedance and ultrasonic guided wave for damage monitoring of bolted joints

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