Demonstration study for reliability assessment of SHM systems incorporating model-assisted probability of detection approach

Aldrin, John C.; Medina, Enrique A.; Santiago, Jose M.; Lindgren, Eric A.; Buynak, Charles; Knopp, Jeremy S.

doi:10.1063/1.4716398

Cited by 18 publications

(29 citation statements)

References 1 publication

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“…Model-assisted POD (MAPOD), where physics-based models of inspection are used to help quantify POD for particular kinds of inspections has, for many years, been a subject of discussion and research (e.g., Thompson 2008 andThompson 2014). Aldrin et al (2011) and Lindgren and Buynak (2011), among others, have outlined some of the general needs for applying MAPOD concepts to quantify POD in SHM applications. Janapati et al (2016) describe some of the important steps that would be needed to provide information for a MAPOD-based POD study for SHM.…”

Section: Background and Related Literaturementioning

confidence: 99%

Statistical Methods for Probability of Detection in Structural Health Monitoring

Meeker¹,

Roach²

2019

Structural Health Monitoring 2019

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There is much interest in the potential to use Structural Health Monitoring (SHM) technology to augment traditional Nondestructive Evaluation (NDE) methods to improve safety, increase asset availability, and reduce maintenance and inspection costs. SHM has the potential to be used in many areas of application including critical components in aircraft and pipelines. Probability of detection (POD) plays a critical role in aircraft structural integrity programs. As such, there has been a high interest in developing methods that can be used to assess POD in SHM applications. In contrast to traditional NDE laboratory experiments to assess POD that involve a set of specimens with cracks, SHM sensors are fixed and SHM data are acquired over time as cracks grow or otherwise evolve. Traditional statistical methods for assessing POD (e.g., as described in MIL-HDBK 1823A 2009) have to be extended to properly handle repeated-measures data. This purpose of this paper is to review the basic statistical concepts of probability of detection (POD) and to show how these concepts can and should be applied to SHM POD studies by modifying and extending existing methods for estimating POD. The methods presented here are applicable when there is a scalar damage index or other response that will be used to make a detect decision. The paper compares a simple model based on length at detection and a random effects model to describe repeated measures data.

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Section: Background and Related Literaturementioning

confidence: 99%

Statistical Methods for Probability of Detection in Structural Health Monitoring

Meeker¹,

Roach²

2019

Structural Health Monitoring 2019

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“…Hence, for a 2-D physics based model, the material matrix reduces to 4 elastic coefficients, 3 piezoelectric coefficients and 2 dielectric coefficients. Hence the piezoelectric stiffness matrix can be given as 11 13…”

Section: Physics Based Model Iiia Constitutive Equation Of Piezmentioning

confidence: 99%

“…Smith et al developed the Full Model-Assisted (FMAPOD) approach [9] and also presented a transfer function approach [10] that correlated the responses from an artificial defect to that of a real crack geometry. Aldrin et al [11] reported simulation-based POD studies for reliability assessment of structural health monitoring (SHM) systems within the framework of MAPOD. Jensen et al [12] explored uncertainty propagation through CIVA-multi technique software (CEA-LIST, France) simulation models.…”

Section: Introductionmentioning

confidence: 99%

Model-Assisted Approach for Probability of Detection (POD) in High-Temperature Ultrasonic NDE Using Low-Temperature Signals

Bilgunde

Bond

2018

Nuclear Technology

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Advanced piezoelectric-based ultrasonic transducers offer the potential for in-coolant nondestructive testing (NDT) measurements at high temperatures (HTs), including during hot standby (~260°C) for liquidsodium-cooled advanced small modular reactors. The reliability of the NDT measurements is typically quantified by the probability of detection (POD) measured at the corresponding temperature. Obtaining such data in liquid sodium is challenging. Using a model-assisted POD approach, a transfer function is reported that enables data obtained on low carbon steel specimens at room temperature to give an estimated POD at an HT. A primary source of the difference in POD between room temperature and HT is due to the transducer material temperature-dependent performance. This paper demonstrates the transfer function approach using data for modified lead zirconium titanate (PZT-5A). A physics-based model was developed using a finite element method and used to quantify reduction in the scattering amplitude for standard reflectors, side drilled holes (SDHs), for a range of sizes, from 15°C to 195°C. Scattering amplitudes for the roomtemperature-simulated data are compared with the experimental data measured at 2.25 MHz. A temperature correction and transfer functions were developed to transform the simulated temperature effect in the physicsbased model to compare with the experimental data. The model-based approach was validated with experimental data. It was seen and validated for a PZT-5A ultrasonic transducer operating at 2.25 MHz that the 95% POD at 15°C was 0.58 λ, and due to variation in temperature-dependent properties of PZT-5A, the 95% POD was achieved only for a 1.41 λ SDH diameter.

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“…The following opportunities in the POD model evaluation and application steps have the potential to impact sample and testing requirements: (a) careful model factor selection addressing system variation, (b) physics-based model calibration including uncertainty bounds assessment for the specific inspections of interest, (c) controlled physics-based model validation to ensure the model is valid over desired range of application, (d) evaluation of POD using two-level analysis to address input parameter variability with uncertainty bounds, (e) integration of experimental data generated from a designed experiment using a Bayesian framework to revise the prior distributions of inputs and achieve new posterior distributions, and (f) inverse methods to ideally address all uncontrolled parameter variations in the measurement. More information on the protocol can be found in reference [5].…”

Section: Protocolmentioning

confidence: 99%

“…For localization and characterization, the metrics and their evaluation process are the subject of current research and development [4]. This paper will present a demonstration of the damage detection protocol utilizing empirical data, models, and uncertainty analyses for characterizing SHM reliability [5].…”

Section: Introductionmentioning

confidence: 99%

Protocol and Demonstrations of Probabilistic Reliability Assessment for Structural Health Monitoring Systems (Preprint)

Lindgren¹,

Buynak²,

Knopp³

et al. 2011

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The public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Department of Defense, Washington Headquarters Services, Directorate for Information SPONSORING/MONITORING AGENCY REPORT NUMBER(S)AFRL-RX-WP-TP-2011-4400 DISTRIBUTION/AVAILABILITY STATEMENTApproved for public release; distribution unlimited. SUPPLEMENTARY NOTESThe U.S. Government is joint author of this work and has the right to use, modify, reproduce, release, perform, display, or disclose the work. PA Case Number and clearance date: 88ABW-2011-4702, 30 Aug 2011. Preprint journal article to be submitted to NDCM-XII Conference Proceedings-2011. This document contains color. ABSTRACTThis paper will describe the development of a protocol for probabilistic reliability assessment for SHM systems as well as present an experimental demonstration for a vibration-based structural damage sensing system. The results of the full validation study highlight the general protocol feasibility, emphasize the importance of evaluating key application characteristics prior to the POD study, and demonstrate an approach to quantify varying sensor durability on the POD performance. Challenges remain to properly address long time-scale effects with accelerated testing and large testing requirements due to the independence of the inspection of the inspection of each flaw location. SUBJECT TERMSmodel-assisted POD evaluation, probability of detection (POD), reliability, structural health monitoring Abstract This paper will describe the development of a protocol for probabilistic reliability assessment for SHM systems as well as present an experimental demonstration for a vibration-based structural damage sensing system. The results of the full validation study highlight the general protocol feasibility, emphasize the importance of evaluating key application characteristics prior to the POD study, and demonstrate an approach to quantify varying sensor durability on the POD performance. Challenges remain to properly address long time-scale effects with accelerated testing and large testing requirements due to the independence of the inspection of each flaw location.

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Demonstration study for reliability assessment of SHM systems incorporating model-assisted probability of detection approach

Cited by 18 publications

References 1 publication

Statistical Methods for Probability of Detection in Structural Health Monitoring

Statistical Methods for Probability of Detection in Structural Health Monitoring

Model-Assisted Approach for Probability of Detection (POD) in High-Temperature Ultrasonic NDE Using Low-Temperature Signals

Protocol and Demonstrations of Probabilistic Reliability Assessment for Structural Health Monitoring Systems (Preprint)

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