Characterization of random fields from NDT measurements: A two stages procedure (original) (raw)
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2012
The localization of weak properties or bad behaviour of a structure is still a challenge for the improvement of Non Destructive Testing (NDT) tools. In case of random loading or material properties, this challenge is arduous because of the limited number of measures and the quasi-infinite potential positions of local failures. The paper shows that the stationary property is sufficient to find the minimum quantity of NDT measurements and their position for a given quality assessment. A measure of the quality is suggested and the illustration is performed on a one-dimensional Gaussian stochastic field for two supports: water content assessment by capacitive NDT tools and chloride ingress by semi-destructive measurements.
Optimization of geo-positioning of NDT measurements for modeling spatial field of defects
Safety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures, 2014
The localization of weak properties or bad behavior of a structure is still a very challenging task that concentrates the improvement of Non Destructive Testing (NDT) tools on more efficiency and higher structural coverage. In case of random loading or material properties, this challenge is arduous because of the limited number of measures and the quasi-infinite potential positions of local failures. The paper shows that the stationary property is useful to find the minimum quantity of NDT measurements and their position for a given quality assessment. It is shown that a two stages procedure allows us (i) to quantify the properties of the ergodic, stationary field (ii) to assess the distribution of the characteristics. The optimization is reached following a criterion based on confidence intervals of the statistics.
2019
The localization of weak properties or bad behavior of a structure is still a very challenging task that concentrates the improvement of Non Destructive Testing (NDT) tools on more efficiency and higher structural coverage. In case of random loading or material properties, this challenge is arduous because of the limited number of measures and the quasi-infinite potential positions of local failures. The paper shows that the stationary property is useful to find the minimum quantity of NDT measurements and their position for a given quality assessment. It is shown that a two stages procedure allows us (i) to quantify the properties of the ergodic, stationary field (ii) to assess the distribution of the characteristics. The optimization is reached following a criterion based on confidence intervals of the statistics. Key work : Confidence interval, probability of interval, spatial variability, Karhunen-Loève, optimization of inspection
Stochastic method for in-situ damage analysis
The European Physical Journal B, 2013
Based on the physics of stochastic processes we present a new approach for structural health monitoring. We show that the new method allows for an in-situ analysis of the elastic features of a mechanical structure even for realistic excitations with correlated noise as it appears in realworld situations. In particular an experimental setup of undamaged and damaged beam structures was exposed to a noisy excitation under turbulent wind conditions. The method of reconstructing stochastic equations from measured data has been extended to realistic noisy excitations like those given here. In our analysis the deterministic part is separated from the stochastic dynamics of the system and we show that the slope of the deterministic part, which is linked to mechanical features of the material, changes sensitively with increasing damage. The results are more significant than corresponding changes in eigenfrequencies, as commonly used for structural health monitoring.
Imprecise random field analysis for non-linear concrete damage analysis
Mechanical Systems and Signal Processing, 2021
Imprecise random fields consider both, aleatory and epistemic uncertainties. In this paper, spatially varying material parameters representing the constitutive parameters of a damage model for concrete are defined as imprecise random fields by assuming an interval valued correlation length. For each correlation length value, the corresponding random field is discretized by Karhunen-Loève expansion. In a first study, the effect of the series truncation is discussed as well as the resulting variance error on the probability box (p-box) that represents uncertainty on the damage in a concrete beam as a result of the imprecise random field. It is shown that a certain awareness for the influence of the truncation order on the local field variance is needed when the series is truncated according to a fixed mean variance error. In the following case study, the main investigation is on the propagation of imprecise random fields in the context of non-linear finite element problems, i.e. quasi-brittle damage of a four-point bended concrete beam. The global and local damage as the quantities of interest are described by a p-box. The influence of several imprecise random field input parameters to the resulting p-boxes is studied. Furthermore, it is examined whether correlation length values located within the interval, so-called intermediate values, affect the p-box bounds. It is shown that, from the engineering point of view, a pure vertex analysis of the correlation length intervals is sufficient to determine the p-box in this context.
Applications of statistical methods to nondestructive evaluation
1996
Nondestructive evaluation (NDE) techniques are used widely in many manufacturing and operational areas of industry. NDE is a highly statistical science that has developed rapidly over the past decade with relatively little input from individuals with forma1 training in statistics. This review article describes some of the many methods and applications of NDE, including eddy-current methods for detecting fatigue in jet-engine turbine disks, ultrasonic methods for detecting flaws in forged titanium, and radiographic methods for detecting out-of-control conditions in a casting process. We will also outline the important potential for increased use of modern methods of statistics to improve the practice of nondestructive evaluation. Areas of statistics important in NDE include data analysis and signal processing, decision theory, screening and calibration, the assessment of measurement capability, and the use of designed experiments for improvement of measurement/detection processes.
Construction and Building Materials, 2013
Spatial variability of concrete is an important characteristic, which qualifies the nonhomogeneity of mechanical and physical properties on structural components. Assessing it can be of great interest for either locating potential damaged areas in an existing structure, or reliability analysis. A two-stage experimental program was carried out using nondestructive testing (NDT) on laboratory concrete slabs in outdoor environment and on an existing bridge. The spatial variability was assessed at three scales: point (repeatability), local and global, for several NDT techniques (ultrasonic, electrical resistivity, radar and rebound hammer). The experimental results were analyzed using statistical and geostatistical tools (descriptive and spatial statistics).
NDTCE’09, Non-Destructive Testing in Civil Engineering
2009
Existing concrete structures such as bridge decks, slabs and tunnels require periodic inspections through the non-destructive testing methods to assess their structural integrity. Many well known non-destructive testing (NDT) methods are currently in use for the identification of the damage insurgence but they are usually limited to particular classes of structures or damages. In this work a wide-ranging non-destructive method is presented. The proposed monitoring approach involves the use of innovative sensors which can be used for both static and dynamic measurements. The method is based on the measured deformations from undamaged and damaged concrete structures subjected to environmental loads and instrumented with a set of fiber optic extensometers for measuring the long-term structural behavior. In particular, the paper is focused on data processing algorithms able to discover anomalous behavior in the structural responses. Data obtained from both computer simulations and experimental tests on pre-stressed concrete beams have been used to compare and validate several statistical procedures on data analysis without using behavior models. In particular, results from Proper Orthogonal Decomposition for damage detection are Ré sans utiliser des modèles de. En particulier, les résultats de l'application de la Proper Orthognal
Optimal embedded sensor placement for spatial variability assessment of stationary random fields
Engineering Structures
Structural reliability assessment is largely influenced by the spatial variability of material properties or defaults; however, there are still various challenges for their characterization and modeling. Structural Health Monitoring (SHM) could provide useful information in space and time for spatial variability characterization of material properties and mechanical solicitations; nevertheless, this challenge is arduous because of the large number of potential sensor positions of local disruptions/failures. This paper proposes a methodology to optimize the spatial distribution of embedded sensors used for spatial variability assessment of stationary random fields. The optimization criterion relies on the width of the confidence interval of statistics for the characteristics to identify. For sake of simplicity, the paper illustrates the method for one-dimensional problems. The proposed method is applied firstly to a numerical example were several hypothetical structural configurations that could be found in practice are studied. It is finally applied to two case studies (a reinforced concrete beam and a steel wharf) where water content and loss of steel thickness are respectively measured. The results show that the stationary property is useful to deduce the minimum quantity of sensors and their position for a given quality requirement. They also allow us to propose a criterion for defining if regular or non-regular spacing of sensors along the inspection zone is more appropriate depending on the component length and autocorrelation structure of the random field.