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The paper will give an overview of new methodology for evaluating the
reliability of NDE systems accurately, reliably and efficiently in accordance with the
specific requirements of industrial application. After a review of the substantive
issues from the previous workshops, the go forward guidance from these
interactions is considered.
At the beginning of the reliability analysis, the actual safety demands have to
be defined in order to fit the investigation to the level of risk when the component
would fail. Next, all the essential influencing parameters need to be documented and
transferred to an appropriate design of experiments (DOE) to determine the
reliability in terms of a qualitative assessment for lower risk or in terms of a
quantitative probability of detection (POD) or ROC (Receiver Operating
Characteristics) curves for higher safety demands. A new paradigm is offered to
consider the POD or reliability of the system as a function of the configuration of
input variables and use it for optimisation rather than for a final judgement. An
advantage for the end user is also to sample all single PODs to an integral 'Volume
POD' of a part.
Among the influencing parameters, the human factor is the most important one.
A systematic psychological approach shall help to find out where the bottlenecks are
but most importantly to provide best possible working conditions for the human
inspectors.
Human factors approach to the reliability of NDT in nuclear waste management in Sweden and Finland
(2010)
Nuclear power industry has the responsibility to manage and dispose of all radioactive waste from its
plants. Finnish Posiva and Swedish SKB are leading in the world in the development of disposal of
spent nuclear fuel. Their method consists of encapsulating spent nuclear fuel in copper canisters and
depositing them in the bedrock at a depth of about 500 meters for the next 100 000 years, leaving the
radioactivity to decrease naturally through the decay of the radioisotopes in it. The copper canisters,
consisting of a copper tube, a lid and a bottom (which make the outer shell) and an insert made of a
cast iron, need to be inspected for their structural integrity to ensure no critical defects are present in
the materials and welds that could lead to a leakage of the waste into the environment. Data acquired
by 4 different non-destructive testing (NDT) methods (i.e. UT, ET, RT and VT with a remote camera)
are evaluated by skilled human operators and therefore could be subject to human error.
Human Factors approach lies in identifying potential errors made by the human, their causes
and ways of preventing them. A customized Failure Modes and Effects Analysis (FMEA) was
conducted to anticipate possible human failures during the data evaluation. The results led to
designing several experiments (e.g. diffusion of responsibility within the 4-eye principle, over trust in
automated systems) which are being experimentally tested in ongoing projects. The results are
expected to lead to the optimization of the procedures followed by the NDT operators and
consequently to the improvement of the overall NDT reliability.
The Probability of Detection (POD) is used to evaluate the detectability of non-destructive testing (NDT) systems. The POD is highly dependent on the amount of available data. The Bayesian approach provides a solution to compute POD-curves in case of a small amount of real defects without losing the necessary information. The result contains the needed information for the computation of POD-curves for real defects with an acceptable amount of information, even for sparse amount of data. In this paper is shown limitations of the Bayesian approach and how it can be applied to NDT. The Bayesian approach is applied in this case to the evaluation of radiographic testing. Bayesian approach is applied to determine POD-curves for the inspection techniques of nuclear fuel disposal canisters. The reason for using Bayesian approach is the high safety demands and also the low amount of real defects due to the high quality of the reliable production techniques.
Currently at Deutsche Bahn (DB) ultrasonic inspections in maintenance procedures for wheelset axles with a bore hole are, to the greatest possible extent, carried out using automated ultrasonic inspection system. Although the acceptance levels are in accordance with DIN 27201 part 7, the testing results have shown in recent years that in the case of true indications, the effective defect sizes were far below the level of acceptance. Due to this experience it can be assumed that the automated ultrasonic inspection systems are testing substantially more sensitively than required. This increased sensitivity leads to an increase in false indications, generally resulting in the unnecessary demounting of wheelsets. In Research cooperation between Federal Institute for Materials Research and Testing (BAM) and DB the effective flaw detection sensitivity of existing automated ultrasonic inspection system will be determined and the true/false indication ratio optimised. Through systematic investigations with the Probability of Detection method on the existing automated ultrasonic inspection system the results could be directly applied to the optimisation of existing ultrasonic inspections of wheelset axles with a bore hole in maintenance procedures and the level of reliability can be considerably increased.
Issues that prevent Structural Health Monitoring (SHM) based on Guided Waves (GW) from being a part of today’s monitoring solutions in industry are not all obvious to the scientific community. To uncover and overcome these issues, scientists working on SHM and GW problems joined in an expert committee under the patronage of the German Society for Non-Destructive Testing. An initiated online survey among more than 700 experts and users reveals the hurdles hindering the practical application of GWbased SHM. Firstly, methods for proof of reliability of SHM approaches are missing.
Secondly, detailed understanding of phenomenological described wave-damage interactions is needed. Additionally, there are significant unsolved implementation issues and unsolved problems of signal processing including handling of environmental influences.
To enable substantial proof of reliability without unaffordable experimental effort also efficient simulation tools including realistic damage interaction are needed, enabling the joint use of experimental and simulated data to predict the capabilities of the Monitoring system. Considering these issues, the committee focusses on simulation, signal processing, as well as probability of detection and standardization. In the presented work, recent activities of the expert committee starting with survey results are summarized. An open access data basis of life-like measurements is presented to allow testing and comparison of signal processing and simulation algorithms. Finally, a strategy for efficient proof of reliability increasing the acceptance of SHM in industry and for successful Integration of SHM into real-world engineering structures is proposed.
In many industrial sectors, Structural Health Monitoring (SHM) is considered as an addition to Non-Destructive Testing (NDT) that can reduce maintenance effort during lifetime of a technical facility, structural component or vehicle. A large number of SHM methods is based on ultrasonic waves, whose properties change depending on structural health. However, the wide application of SHM systems is limited due to the lack of suitable methods to assess their reliability. The evaluation of the system performance usually refers to the determination of the Probability of Detection (POD) of a test procedure. Up to now, only few limited methods exist to evaluate the POD of SHM systems, which prevent them from being standardised and widely accepted in industry. The biggest hurdle concerning the POD calculation is the large amount of samples needed. A POD analysis requires data from numerous identical structures with integrated SHM systems. Each structure is then damaged at different locations and with various degrees of severity. All of this is connected to high costs. Therefore, one possible way to tackle this problem is to perform computer-aided investigations. In this work, the POD assessment procedure established in NDT according to the Berens model is adapted to guided wave-based SHM systems. The approach implemented here is based on solely computer-aided investigations. After efficient modelling of wave propagation phenomena across an automotive component made of a carbon fibre-reinforced composite, the POD curves are extracted. Finally, the novel concept of a POD map is introduced to look into the effect of damage position on system reliability.