Wireless Module for Nondestructive Testing/Structural Health Monitoring Applications Based on Solitary Waves

Misra, Ritesh; Jalali, Hoda; Dickerson, Samuel J.; Rizzo, Piervincenzo

doi:10.3390/s20113016

Cited by 11 publications

(2 citation statements)

References 56 publications

(94 reference statements)

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“…The array supports the propagation of the highly nonlinear solitary waves (HNSWs). These waves were used by Rizzo and co-authors for nondestructive evaluation (NDE) and structural health monitoring applications (SHM) [11][12][13][14]. This is another example of integrating multiple disciplines between the engineering development and biomedical devices developed by Rizzo and co-authors, as done for example in [15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Predicting intraocular pressure utilizing highly nonlinear solitary waves as inputs to a CNN

Hodgson,

Rizzo,

Dickerson

et al. 2024

Health Monitoring of Structural and Biological Systems XVIII

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Highly nonlinear solitary waves (HNSWs) are traditionally used in the field of nondestructive evaluation to inspect a material's property without causing damage. The research in this paper proposes a new application for HNSWs: predicting changes in intraocular pressure (IOP) to ensure optimum treatment and prevent the progression of Glaucoma in an eye. The HNSWs used for assessment were collected from a Polydimethylsiloxane (PDMS) eye model and are initiated and stored with a solitary wave transducer. To collect a full range of HNSWs that represent the biological range of IOPs in humans, the PDMS eye model is pressurized from 12mmHg to 26mmHg with 1mmHg increments and waves are collected at each pressure point. Once a HNSW is collected, it is wirelessly transmitted to a server where it is fed into a convolutional neural network to predict the IOP. This is done by extracting relevant features from the HNSW with a Fast Fourier Transform and constructing a spectrogram which can be fed into the algorithm pixel by pixel. This methodology works due to the association of frequency content in the HNSW and changes of the stiffness in the material. In the case of high IOP, the increased pressure pushes against the artificial PDMS cornea and causes it to become stiffer with a higher Young's modulus. We evaluated the ability of the algorithm to predict IOP based on the spectrogram.

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Section: Introductionmentioning

confidence: 99%

Predicting intraocular pressure utilizing highly nonlinear solitary waves as inputs to a CNN

Hodgson,

Rizzo,

Dickerson

et al. 2024

Health Monitoring of Structural and Biological Systems XVIII

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“…Second, the research tries to quantify the region of interest of the monitoring system and frames the advantages and limitations in the context of corrosion monitoring. Third, the experimental work applies for the first time ever the novel wireless transducer 72,73 designed and assembled by our group. Fourth, the analysis of the data compares the performance of the novel wireless transducers against the conventional wired transducer our group had used for the last five years.…”

Section: Introductionmentioning

confidence: 99%

Remote wireless monitoring of localized corrosion using compact solitary waves

Jalali

Misra

Dickerson

et al. 2022

Structural Health Monitoring

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This article presents a method to monitor corrosion remotely, based on highly nonlinear solitary waves, which are compact and nondispersive. In the study presented in this article, two types of solitary wave transducers were used to monitor accelerated localized corrosion on a steel plate. The first type consists of a chain of spherical particles surmounted by a commercial solenoid wired to, and controlled by, a data acquisition system used to lift and release the first particle of the chain and induce the mechanical impacts and stress waves in the chain. The chain included a piezoelectric wafer disk, also wired to the same data acquisition system, to sense, digitize, and store the propagating waves for post-processing. The second type of transducer was identical to the first one but the data acquisition system was replaced by a wireless node that communicated with a mobile device using a Bluetooth connection. Eight transducers were used to monitor the plate for over a week to detect the onset and progression of localized corrosion. Corrosion detection was performed by extracting a few features from the time waveforms and feeding these features to an outlier analysis algorithm based on the Mahalanobis distance. The results of the experiment showed the effectiveness of the proposed monitoring approach at detecting defects close to the transducers and confirm previous numerical predictions by the authors. The experiments also provided evidence that the performance of the wireless transducers is nearly identical to the performance of their wired counterparts, paving the way to a new paradigm for the structural health monitoring of remote structural components in harsh environments.

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