Cantilever damage evaluation using impedance-loaded SAW sensor with continuous wavelet analysis and machine learning

Suzuki, Sena; Kondoh, Jun

doi:10.35848/1347-4065/abf2d0

Cited by 7 publications

(4 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This allowed for decay coefficient calculation and decay type classification (linear, exponential, or mixed) based on shape changes over time and frequency. They applied three machine learning models, RF, SVM, and LightGBM, to automatically learn decay coefficient features and patterns for damage detection and severity assessment, achieving classification accuracies of 65.4%, 84.6%, and 88.5% on raw data, and 84.6%, 76.9%, and 76.9% on standardized data, respectively [131].…”

Section: Mechanical Fault Identificationmentioning

confidence: 99%

AI-Driven Sensing Technology: Review

Chen,

Xia,

Zhao

et al. 2024

Sensors

View full text Add to dashboard Cite

Machine learning and deep learning technologies are rapidly advancing the capabilities of sensing technologies, bringing about significant improvements in accuracy, sensitivity, and adaptability. These advancements are making a notable impact across a broad spectrum of fields, including industrial automation, robotics, biomedical engineering, and civil infrastructure monitoring. The core of this transformative shift lies in the integration of artificial intelligence (AI) with sensor technology, focusing on the development of efficient algorithms that drive both device performance enhancements and novel applications in various biomedical and engineering fields. This review delves into the fusion of ML/DL algorithms with sensor technologies, shedding light on their profound impact on sensor design, calibration and compensation, object recognition, and behavior prediction. Through a series of exemplary applications, the review showcases the potential of AI algorithms to significantly upgrade sensor functionalities and widen their application range. Moreover, it addresses the challenges encountered in exploiting these technologies for sensing applications and offers insights into future trends and potential advancements.

show abstract

Section: Mechanical Fault Identificationmentioning

confidence: 99%

AI-Driven Sensing Technology: Review

Chen,

Xia,

Zhao

et al. 2024

Sensors

View full text Add to dashboard Cite

show abstract

“…The research and development of SAW propagation modes and piezoelectric materials for high-performance SAW devices have been actively conducted in Japan and overseas. [1][2][3][4][5][6][7][8][9][10][11][12][13] In particular, 5 GHz bands, called the Sub-6 band in 5G communication systems, are approximately 1.5-2 times higher than those of 4G communication systems. Hence, there is a significant demand for higher frequencies in SAW filters.…”

Section: Introductionmentioning

confidence: 99%

Analysis of longitudinal leaky surface acoustic waves on piezoelectric thin plates bonded to diamond substrate

Hara

Suzuki

Kakio

et al. 2023

Jpn. J. Appl. Phys.

View full text Add to dashboard Cite

Using the finite element method, we analyzed the resonance properties of a longitudinal leaky surface acoustic wave (LLSAW) on the structure of a piezoelectric LiTaO3 (LT) or LiNbO3 (LN) thin plate bonded to a diamond support substrate. When the plate thickness was 0.3 wavelength or larger, the particle displacements of the LLSAW were substantially concentrated near the surface, and the resonance properties were significantly improved, compared to those of the single LT or LN. However, spurious responses due to other SAW modes also emerged. Regarding the LN thin plate, we obtained a phase velocity and fractional bandwidth of approximately 7300 m/s and 9.4%, respectively. Furthermore, a structure was proposed to suppress spurious responses, in which the piezoelectric thin plate is divided into two layers with different Euler angles. The spurious responses were significantly suppressed after dividing the thin plate, while the main response of the LLSAW was maintained.

show abstract

“…18) As other similar examples, wireless devices for temperature and pressure measurement and health monitoring using a surface acoustic wave sensor have been reported. [19][20][21] The use of unmanned aerial vehicles for the non-contact inspection has also been discussed. 22,23) On the other hand, bolts are a key component in maintaining the soundness of structures, and it would be useful if the axial force of bolts could be measured remotely without contact.…”

Section: Introductionmentioning

confidence: 99%

Non-contact bolt axial force measurement based on the deformation of bolt head using quartz crystal resonator and coils

Hasebe

Wada

Nakamura

2022

Jpn. J. Appl. Phys.

View full text Add to dashboard Cite

As a health monitoring tool of bolts in infrastructures, we propose a non-contact evaluation method for the axial force of a bolt. Deformation of the bolt head is measured as an electrical capacitance variation detected as a frequency shift of a simple circuit composed of a quartz crystal resonator and coils. The measurement was carried out via magnetic field coupling between the coil installed on the bolt head and another coil connected to the measurement instrument. Since the method requires no active electronic circuit or battery for the bolt, low cost and high durability can be expected. First, the circuit was analyzed and optimized using an equivalent circuit model. Then, the feasibility of the proposed method was experimentally studied using a prototype. It was demonstrated that the method enabled non-contact axial force estimation in which the dependence on the distance between the coils is sufficiently small for detecting bolt looseness.

show abstract

Cantilever damage evaluation using impedance-loaded SAW sensor with continuous wavelet analysis and machine learning

Cited by 7 publications

References 36 publications

AI-Driven Sensing Technology: Review

AI-Driven Sensing Technology: Review

Analysis of longitudinal leaky surface acoustic waves on piezoelectric thin plates bonded to diamond substrate

Non-contact bolt axial force measurement based on the deformation of bolt head using quartz crystal resonator and coils

Contact Info

Product

Resources

About