Computational Framework for Dense Sensor Network Evaluation Based on Model-Assisted Probability of Detection

Jin, Yan; Laflamme, Simon; Leifsson, Leifur

doi:10.32548/2020.me-04111

Cited by 3 publications

(2 citation statements)

References 19 publications

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“…95,96 Yan et al used a model-assisted POD approach to validate the performance of different sensor configurations. 97 Chen et al leveraged POD curves to determine the optimum Lamb wave driving frequency to detect fatigue crack growth in a metallic specimen. 98 Grooteman used POD as an objective function to obtain the OSP for optical fibers applied to a stiffened composite panel.…”

Section: Spatial Aspects Of Probability Of Detectionmentioning

confidence: 99%

Probability of detection, localization, and sizing: The evolution of reliability metrics in Structural Health Monitoring

Falcetelli

Yue

Sante

et al. 2021

Structural Health Monitoring

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The successful implementation of Structural Health Monitoring (SHM) systems is confined to the capability of evaluating their performance, reliability, and durability. Although there are many SHM techniques capable of detecting, locating and quantifying damage in several types of structures, their certification process is still limited. Despite the effort of academia and industry in defining methodologies for the performance assessment of such systems in recent years, many challenges remain to be solved. Methodologies used in Non-Destructive Evaluation (NDE) have been taken as a starting point to develop the required metrics for SHM, such as Probability of Detection (POD) curves. However, the transposition of such methodologies to SHM is anything but straightforward because additional factors should be considered. The time dependency of the data, the larger amount of variability sources and the complexity of the structures to be monitored exacerbate/aggravate the existing challenges, suggesting that much work has still to be done in SHM. The article focuses on the current challenges and barriers preventing the development of proper reliability metrics for SHM, analyzing the main differences with respect to POD methodologies for NDE. It was found that the development of POD curves for SHM systems requires a higher level of statistical expertise and their use in the literature is still limited to few studies. Finally, the discussion extends beyond POD curves towards new metrics such as Probability of Localization (POL) and Probability of Sizing (POS) curves, reflecting the diagnosis paradigm of SHM.

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Section: Spatial Aspects Of Probability Of Detectionmentioning

confidence: 99%

Probability of detection, localization, and sizing: The evolution of reliability metrics in Structural Health Monitoring

Falcetelli

Yue

Sante

et al. 2021

Structural Health Monitoring

View full text Add to dashboard Cite

show abstract

“…Although the data-based technique showed great promise at high rate state estimation, it did not provide insight into the system's physical characteristics, as it is generally the case with data-based techniques. Physics-driven methods, such as those borrowing on model reference adaptive system (MRAS) theory, showed great promise in handling nonlinearities, uncertainties, and perturbations [4,5]. MRAS was applied to the problem of high-rate state estimation in [6], where the position of a moving cart was accurately identified under 172 ms through a time-based adaptive algorithm used in reaching the reference model with an average computing time of 93 µs per step, obtained through numerical simulations conducted in MATLAB.…”

Section: Introductionmentioning

confidence: 99%

A Comparison of Time-Frequency Methods for Real-Time Application to High-Rate Dynamic Systems

et al. 2020

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High-rate dynamic systems are defined as engineering systems experiencing dynamic events of typical amplitudes higher than 100 gn for a duration of less than 100 ms. The implementation of feedback decision mechanisms in high-rate systems could improve their operations and safety, and even be critical to their deployment. However, these systems are characterized by large uncertainties, high non-stationarities, and unmodeled dynamics, and it follows that the design of real-time state-estimators for such purpose is difficult. In this paper, we compare the promise of five time-frequency representation (TFR) methods at conducting real-time state estimation for high-rate systems, with the objective of providing a path to designing implementable algorithms. In particular, we examine the performance of the short-time Fourier transform (STFT), wavelet transformation (WT), Wigner–Ville distribution (WVD), synchrosqueezed transform (SST), and multi-synchrosqueezed transform (MSST) methods. This study is conducted using experimental data from the DROPBEAR (Dynamic Reproduction of Projectiles in Ballistic Environments for Advanced Research) testbed, consisting of a rapidly moving cart on a cantilever beam that acts as a moving boundary condition. The capability of each method at extracting the beam’s fundamental frequency is evaluated in terms of precision, spectral energy concentration, computation speed, and convergence speed. It is found that both the STFT and WT methods are promising methods due to their fast computation speed, with the WT showing particular promise due to its faster convergence, but at the cost of lower precision on the estimation depending on circumstances.

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Real-Time Nondestructive Evaluation of Additive Manufacturing Using a Laser Vibrometer and Shock Tube

Liu

Laflamme

Morgan

et al. 2022

Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems

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Additive manufacturing (AM) parts retain a certain degree of individuality and could suffer from a combination of different defect types, and is therefore the non-destructive evaluation on AM parts remains a challenging task. Engineering non-contact and non-destructive real-time inspection and in-situ quality assurance of AM parts would be a net improvement compared to current quality control methods that are conducted post-production. Here, the authors propose to combine the use of a laser vibrometer with a compression-driven shock tube to assess the quality of AM parts through the evaluation of the vibration spectra of the part. An AM of a cylindrical part was selected for the study, along with different defect types and sizes. These defects include internal voids of different sizes at different locations, local changes in thickness (infill), and local changes in melting temperatures. A numerical model was created and validated using experimental data to conduct model assisted probability of detection (MAPOD). Results were analyzed by evaluating correlation matrices between different models. Results showed that vibration spectra induced by a shock wave were sensitive to different types and sizes of defects under the studied geometry. The defect index yielded an approximately linear relationship with respect to defect void severity. MAPOD curve studies revealed a minimum detectable void defect 0.039% of the AM parts volume.

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Computational Framework for Dense Sensor Network Evaluation Based on Model-Assisted Probability of Detection

Cited by 3 publications

References 19 publications

Probability of detection, localization, and sizing: The evolution of reliability metrics in Structural Health Monitoring

Probability of detection, localization, and sizing: The evolution of reliability metrics in Structural Health Monitoring

A Comparison of Time-Frequency Methods for Real-Time Application to High-Rate Dynamic Systems

Real-Time Nondestructive Evaluation of Additive Manufacturing Using a Laser Vibrometer and Shock Tube

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