PoD curves, their derivation, applications and limitations

Georgiou, George

doi:10.1784/insi.2007.49.7.409

Cited by 68 publications

(79 citation statements)

References 4 publications

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“…The most commonly used function is a cumulative log-normal distribution function [8]. A typical POD curve, as observed in previous work, is shown in Figure 3(a).…”

Section: Generation Of Pod Curvementioning

confidence: 87%

Finite Element Simulations to Predict Probability of Detection (PoD) Curves for Ultrasonic Inspection of Nuclear Components

Subair

Balasubramaniam

Rajagopal

et al. 2014

Procedia Engineering

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Nondestructive evaluation (NDE) methods for the qualification of structures in the nuclear industry are required to perform to very high standards of reliability, and hence, establishing the performance capabilities of inspection techniques is of utmost importance. The Probability of Detection (PoD) curve method has emerged as an important tool for the assessment of the performance of NDE techniques, in general. However, the conventional experimental means of generating PoD curves is very expensive, requiring large experimental data sets covering different defects as well as a range of test conditions, plant shut-down and also operator time. Several methods of achieving faster estimates for PoD curves using physics-based modelling have emerged to address this problem. However, most theoretical models remain limited to a small number of materials or defect types: thus numerical modelling techniques are very attractive, especially given the ever increasing computational power available to scientists today. This paper reports the feasibility of using Finite Element (FE) simulations to augment sparse measurements made using experiments, and predict PoD curves for ultrasonic inspection of stainless steel plates and welds. PoD curves are obtained for the case of conventional (bulk P and SV wave) ultrasonic pulse-echo inspection of surface-breaking longitudinal notches in Stainless Steel plates. The main parameters affecting the uncertainty in practical ultrasonic inspection are identified and combinations are achieved, assuming each of them varies according to a normal distribution. FE simulations are performed for each combination of parameters, viz. frequencies, wedge angles, notch dimensions, and the amplitudes of scattered UT signals so predicted are used to generate the PoD curves. The results are compared against trial experimental measurements. Approach towards generating the POD curves for ultrasonic inspection of thick austenitic stainless steel welds will be discussed.

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“…The most commonly used function is a cumulative log-normal distribution function [8]. A typical POD curve, as observed in previous work, is shown in Figure 3(a).…”

Section: Generation Of Pod Curvementioning

confidence: 87%

Finite Element Simulations to Predict Probability of Detection (PoD) Curves for Ultrasonic Inspection of Nuclear Components

Subair

Balasubramaniam

Rajagopal

et al. 2014

Procedia Engineering

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“…The POD for various crack lengths was calculated for the lab environment based on the hit-or-miss concept [33] as the ratio of the number of successful detections of a particular crack length over the total number of tests. These POD values are for discrete crack lengths.…”

Section: Probability Of Detection (Pod)mentioning

confidence: 99%

“…These POD values are for discrete crack lengths. In order to obtain a continuous POD curve, the POD was estimated by a logistic function for this data [33]. The cumulative distribution function of the log-logistic distribution is:…”

Section: Probability Of Detection (Pod)mentioning

confidence: 99%

A Probabilistic Approach to Small Fatigue Crack Initiation and Sizing Using Acoustic Emission

Keshtgar

Modarres

2017

Preprint

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Abstract:One of the major concerns in structural health management (SHM) is the early detection of a growing crack. Using this, future damage due to crack propagation can be mitigated or eliminated by implementing proper repair and maintenance. Acoustic Emission (AE) is a non-destructive testing (NDT) method with potential applications for locating and monitoring fatigue cracks. The research presented in this paper focuses on SHM using AE. A novel AE signal analysis approach was proposed in order to detect crack initiation and assess small crack lengths. Experimental investigation indicated that initiation of a crack could be identified through the statistical analysis of the resulting features of the AE signals. A probabilistic AE-based model for small fatigue crack sizing was developed and the uncertainties of the model were estimated. In addition, a probabilistic model validation approach was implemented to confirm accurate estimation of the results. The outcome of this research can be used to evaluate the integrity of structures under fatigue loading. The proposed approach can also be applied as an approach to manage health and assess prognosis of structures.

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“…The use of probability of detection (POD) curves for characterizing the SHM systems is recommended, which is defined as a statistical metric, widely employed in the NDT community. This requires a large number of inspection tasks for characterizing various configurations of damage that can potentially appear in the structure [17,18,19]. Many works have been done to extend this concept to SHM [20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,19,37].…”

Section: Introductionmentioning

confidence: 99%

A model-based approach for statistical assessment of detection and localization performance of guided wave–based imaging techniques

Moriot

Quaegebeur

Duff

et al. 2017

Structural Health Monitoring

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This paper aims at providing a framework for assessing the detection and localization performance of guided wave-based structural health monitoring (SHM) imaging systems. The assessment exploits a damage identification metric (DIM) providing a diagnostic of the structure from an image of the scatterers generated by the system, allowing detection, localization, and size estimation of the damage. Statistical probability of detection (POD) and probability of localization (POL) curves are produced based on values of the DIM for several damage sizes and positions. Instead of relying on arduous measurements on a significant number of structures instrumented in the same way, a model-based approach is considered in this paper for estimating POD and POL curves numerically. This approach is first illustrated on a simplistic model, which allows characterizing the robustness of the SHM system for various levels of noise in test signals. An experimental test case using a more realistic case with an artificial damage is then considered for validating the approach. A good agreement between experimental and numerical values of the DIM and derived POD and POL curves is observed.

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PoD curves, their derivation, applications and limitations

Cited by 68 publications

References 4 publications

Finite Element Simulations to Predict Probability of Detection (PoD) Curves for Ultrasonic Inspection of Nuclear Components

Finite Element Simulations to Predict Probability of Detection (PoD) Curves for Ultrasonic Inspection of Nuclear Components

A Probabilistic Approach to Small Fatigue Crack Initiation and Sizing Using Acoustic Emission

A model-based approach for statistical assessment of detection and localization performance of guided wave–based imaging techniques

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