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Concepts for digital image evaluation are presented for Computed Radiography (CR) and Digital Detector Arrays (DDAs) used for weld inspection. The precise DDA calibration yields an extra ordinary increase of contrast sensitivity up to 10 times in relation to film radiography. Restrictions in spatial resolution caused by pixel size of the DDA are compensated by increased contrast sensitivity. First CR standards were published in 2005 to support the application of phosphor imaging plates in lieu of X-ray film, but they need already a revision based on experiences reported by many users. One of the key concepts is the usage of signal-to-noise (SNR) measurements as equivalent to the optical density of film and film system class. The contrast sensitivity, measured by IQI visibility, depends on three essential parameters: The basic spatial resolution (SRb) of the radiographic image, the achieved signal-to-noise ratio (SNR) and the specific contrast (µeff - effective attenuation coefficient). Knowing these 3 parameters for the given exposure condition, inspected material and monitor viewing condition permits the calculation of the just visible IQI element. Furthermore, this enables the optimization of exposure conditions. The new ISO/FDIS 17636-2 describes the practice for digital radiography with CR and DDAs. It considers the first time compensation principles, derived from the three essential parameters. The consequences are described.
Thermographic non-destructive testing is based on the interaction of thermal waves with inhomogeneities. The propagation of thermal waves from the heat source to the inhomogeneity and to the detection surface according to the thermal diffusion equation leads to the fact that two closely spaced defects can be incorrectly detected as one defect in the measured thermogram. In order to break this spatial resolution limit (super resolution), the combination of spatially structured heating and numerical methods of compressed sensing can be used. The improvement of the spatial resolution for defect detection then depends in the classical sense directly on the number of measurements. Current practical implementations of this super resolution detection still suffer from long measurement times, since not only the achievable resolution depends on performing multiple measurements, but due to the use of single spot laser sources or laser arrays with low pixel count, also the scanning process itself is quite slow. With the application of most recent high-power digital micromirror device (DMD) based laser projector technology this issue can now be overcome.
The objective of the report is to present the state-of-the art of non-destructive testing methods and technologies for the inspection of thick, heavily-reinforced structures, (e.g. found in nuclear power plants). Wall thicknesses can be in excess of one meter and the structures often have increased steel reinforcement density. The accessibility for any testing method may be limited due to the presence of liners and other components such as cast-in-place items. Testing methods have to provide solutions for tasks such as locating failure (inclusions, corrosion, voids, delaminations) in the structures or the assessment of the condition of the structure in general.
Reliability analysis of deteriorating structural systems requires the solution of time-variant reliability problems.
In the general case, both the capacity of and the loads on the structure vary with time. This analysis can be approached by approximation through a series of time-invariant reliability problems, which is a potentially effective strategy for cases where direct solutions of the time-variant reliability problem are challenging, e.g. for structural systems with many elements or arbitrary load processes. In this contribution, we thoroughly Review the formulation of the equivalent time-invariant reliability problems and extend this approximation to structures for which inspection and monitoring data is available. Thereafter, we present methods for efficiently evaluating the reliability over time. In particular, we propose the combination of sampling-based methods with a FORM (first-order reliability method) approximation of the series system reliability problem that arises in the computation of the lifetime reliability. The framework and algorithms are demonstrated on a set of numerical examples, which include the computation of the reliability conditional on inspection data.
Thermography is a widely accepted non-invasive measurement method and is generally used in various areas of the life cycle of infrastructure and machinery. This includes design, production and maintenance. Thermography is particularly suitable for remote inspection of large areas that are difficult to reach.
In this presentation, applications of thermography in the field of wind energy will be shown, touching on three explicit examples from rotor blade inspection.
Experimental testing and validation: Thermography can measure and visualise the stress distribution on the surface during cyclic tests of rotor blades and rotor blade sections. The so-called thermoelastic stress analysis makes use of special evaluation algorithms (Lockin analysis) of the measurement data and the cyclic loading of components. An advantage of the measurement methods compared to other measurement methods such as strain gauges or digital image correlation is that it does not require any extra treatment or sensoring of the components. In the work shown here, repair methods are optimised and evaluated in cyclic tests on shell test specimens.
Operation and maintenance: Rotor blades can be inspected from the ground during operation using passive thermography. Here, the integration of weather forecasts and conditions as input for simulations is crucial and will be demonstrated with some examples from the field. The goal of the ongoing research is to obtain detailed insights into the internal structure of the inspected rotor blades with individual measurements. A specially developed automated measuring system is able to measure a wind turbine (one-sided) within 5 minutes without impacting its operation.
Environmental impact: In cases where less strict time and economic constraints apply than in the maintenance of rotor blades in operation, thermography can also be used to realise other inspection processes that take more time. Examples of this are quality control or the characterisation of rotor blades during dismantling. In the latter case, for example, it can be crucial to know which components such as foam, balsa, belt and spar are present in which parts of the blade when dismantling the rotor blades. Long-term measurements (~1-2 h) under suitable weather conditions can provide good insights into the inner structure of the rotor blades, both during disassembly and during quality control before installation. For this purpose, the sun is used as a heat source, which induces a thermal response of the rotor blades. The thermal behaviour of the rotor blades then allows conclusions to be drawn about the internal structure.
An efficient approach to reliability analysis of deteriorating structural systems is presented, which considers stochastic dependence among element deterioration. Information on a deteriorating structure obtained through inspection or monitoring is included in the reliability assessment through Bayesian updating of the system deterioration model. The updated system reliability is then obtained through coupling the updated deterioration model with a probabilistic structural model. The underlying high-dimensional structural reliability problems are solved using subset simulation, which is an efficient and robust sampling-based algorithm suitable for such analyses. The approach is demonstrated in two case studies considering a steel frame structure and a Daniels system subjected to high-cycle fatigue.
A novel method for risk-based optimization of inspection and repair strategies for deteriorating structural systems has recently been proposed. The method defines heuristics at the system level to reduce the number of possible strategies. For each defined strategy, it computes the updated system failure probability conditional on simulated inspection and repair histories, and evaluates the associated costs and risk. The expected total service life costs and risk for a strategy are finally determined using Monte Carlo simulation. The optimal strategy minimizes the expected total service life costs and risk. We intend to adopt this approach to optimize inspection, monitoring and repair activities for offshore wind park support structures. As a first step, we simulate – in analogy to an offshore wind park – the service life performance of an inspected group of jacket-type frames. The performance is quantified in terms of the group’s system failure probability conditional on simulated inspection and repair histories. The underlying system model accounts for the structural redundancy of the frames and the interdependence among their failure events due to similar loading conditions. The model also captures stochastic dependence among the deterioration states of the frames. As part of the simulation process the a-priori unknown outcome of any planned inspection is generated conditional on the outcome of all previous inspections.
The reliability of deteriorating structures at time t is quantified by the probability that failure occurs within the period leading up to time t. This probability is often referred to as cumulative failure probability and is equal to the cumulative distribution function of the time to failure. In structural reliability, an estimate of the cumulative failure probability is obtained based on probabilistic Engineering models of the deterioration processes and structural performance. Information on the condition and the loading contained in inspection and monitoring data can be included in the probability estimate through Bayesian updating. Conditioning the
probability of failure on the inspection or monitoring outcomes available at time t (e.g. detections or no detection of damages) can lead to a reduction in that probability.
Such a drop in the cumulative failure probability might seem counterintuitive since the cumulative failure probability is a non-decreasing function of time. In this paper, we illustrate—with the help of a numerical example—that such a drop is possible because the cumulative probability before and after the updating is not based on the same information, hence not on the same probabilistic model.