Coplanar capacitive sensors and their applications in non-destructive evaluation: a review

Mwelango, Martin; Zhu, Teng; Wen, Kaijie; Zhang, Z.; Yuan, Xin’an; Li, W.; Yin, Xiaokang

doi:10.1080/10589759.2023.2198233

Cited by 23 publications

(4 citation statements)

References 178 publications

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“…An emerging technology for nondestructive structural testing involves the use of coplanar capacitive sensors. [ 47 ] While these sensors can be used with a wide range of materials, their primary capability lies in measuring deformation within localized areas where electrodes are positioned. By contrast, DIC can provide data across the entire field of view and can capture more detailed strain patterns.…”

Section: Discussionmentioning

confidence: 99%

Identification of Location and Geometry of Invisible Internal Defects in Structures using Deep Learning and Surface Deformation Field

Timilsina,

Jang,

et al. 2023

Advanced Intelligent Systems

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On‐site inspection of invisible subsurface defects in multiscale structural materials by conventional nondestructive testing (NDT) methods, such as X‐ray and ultrasound, requires complex sample preparation and data acquisition processes. Moreover, the inspected area is very small. Herein, a simple, inexpensive, and ultrasensitive NDT method for identifying and classifying the geometries of subsurface defects using commercial cameras, digital image correlation software, and object detection (OD) algorithms is developed. Three OD algorithms—Faster region‐based convolutional neural network (Faster R‐CNN), Mask R‐CNN, and you‐only‐look‐once (YOLO)v3—are evaluated for their ability to locate defects and identify defect geometries. Specifically, bounding boxes of two sizes (large and small) are applied to the regions of defect‐induced perturbations in strain tensors, which serve as virtual representatives of invisible subsurface defects. The performance of the proposed approach is validated on test datasets of known and unknown defect types. The experimental results confirm that the proposed approach can effectively utilize the surface deformation field information to accurately and reliably locate and identify subsurface defects. The method is nondestructive and low cost, enables real‐time detection, is robust against noise‐dominated deformation fields, and can be applied to various structural deformations. The method is therefore suitable for multiscale structural health monitoring and characterization of internal defects in materials.

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Section: Discussionmentioning

confidence: 99%

Identification of Location and Geometry of Invisible Internal Defects in Structures using Deep Learning and Surface Deformation Field

Timilsina,

Jang,

et al. 2023

Advanced Intelligent Systems

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“…A radiographic technique is applied in sandwich structures with a metal honey comb core. NDTs are developing and new techniques like coplanar capacitive sensors (CCS) [22] or mechanoluminescence (ML) combined with digital image correlation (DIC) [25] have emerged This research is based on experiments to guarantee a safe usage of the created composite structure during further flight testing. Consequently, a special deformation measurement system for UAVs was created.…”

Section: Composite Structures (Especially In Aviation Applications)mentioning

confidence: 99%

Deformation measurement system for UAV components to improve their safe operation

Czyż,

Jakubczak,

Podolak

et al. 2023

Eksploatacja i Niezawodność – Maintenance and Reliability

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The paper presents the authors’ method and test rig for performing the deformation analysis of unmanned aircraft fuselages. To conduct the analysis, the DIC system was used, as well as a test rig designed and constructed by the authors, equipped with a dedicated control and load control system. The article presents a description of the research capabilities of the test rig developed for testing the deformation of unmanned aircraft fuselages. Due to the specific operating conditions of the designed fuselage, the test rig developed allows the simulation of loads corresponding to different flight conditions. In addition, it is possible to change the forces acting on the fuselage simultaneously for all servos or each of them separately. Finally, results showing the displacement of component control points for the considered fuselage versions are presented. The tests carried out using the developed test rig allowed the verification of the maximum deformations.

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“…To date, large-volume liquid-level measuring instruments use the interdigital electrode sensor mainly based on their capacitive property [34][35][36][37][38][39]. Generally, this type of sensor is bonded up to a few kHz operational frequency measurement.…”

Section: Introductionmentioning

confidence: 99%

Study of the interdigital electrode sensor at resonance frequency during water transition

Ranjan,

Dash,

Maharana

et al. 2024

J. Inst.

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This paper uses the co-planar interdigital electrode (IDE) sensor to measure water level. The researchers generally characterize the interdigital electrode sensor as a fringe field capacitor sensor developed on the printed circuit board and utilize the capacitor sensor's properties for liquid-level measurement. The interdigital electrode sensors illustrate more than one resonance at the higher frequencies, and in this study, the first resonance frequency fr -has been utilized for the water level measurement. Three water types are examined here: distilled, tap, and river. The study assesses that with the transition of water, the permittivity between the electrodes is changed and, it leads to a change in capacitance hence, the change in resonance frequency was observed. The proposed sensor can be represented by the lumped element equivalent series RLC circuit. The developed IDE sensor has good repeatability, small variability, and small hysteresis error. The maximum standard error for distilled, tap, and river water are 0.02833, 0.02503, and 0.02618, respectively, and the hysteresis error is less than 1.903% of full-scale output variation. The maximum error for the fr estimation is about ±2 Hz.

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Coplanar capacitive sensors and their applications in non-destructive evaluation: a review

Cited by 23 publications

References 178 publications

Identification of Location and Geometry of Invisible Internal Defects in Structures using Deep Learning and Surface Deformation Field

Identification of Location and Geometry of Invisible Internal Defects in Structures using Deep Learning and Surface Deformation Field

Deformation measurement system for UAV components to improve their safe operation

Study of the interdigital electrode sensor at resonance frequency during water transition

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