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Classical film radiography is a well-established NDT technique and it is most commonly used for testing weld seams and corroded pipes e.g. in oil and gas industry or in nuclear power plants. In the course of digitization, digital detector arrays (DDA) are finding their way into industrial applications and are replacing film radiography step by step. This study deals with the latest generation of DDAs, the photon counting and energy resolving detectors (PCD), and their characteristics compared to charge integrating detectors (CID). No matter which technology to use, radiography still lacks a general issue: A three-dimensional object is projected onto a two dimensional image. Of course, advanced computed tomography (CT) algorithms exist since many years, but if the object to investigate is too large to fit into the manipulation system or its shape is not appropriate, CT is not feasible or sensible to be applied. To overcome this limitation, numerous laminographic algorithms have been developed in the past. In this study, photon counting detectors are used in combination with co-planar translational laminography to gain reconstructed three-dimensional volumes. Both laminographic testing and PCDs require a serious knowledge of many parameters that can influence the image quality in the resulting datasets. These are e.g. the detector efficiency and calibration procedure, setting of energy thresholds, exposure data, number of projections, beam length correction and spatial resolution. The use of PCDs yields more variables to be considered compared to CIDs. The most important parameters in laminographic testing and in the use of PCDs are described in this study and limits are discussed.
The vast experience with the automated, ultrasonic system for the inspection of hollow railway axles used by Deutsche Bahn shows that much smaller flaws are detectable than required. This results in a number of false calls. False calls lead to unnecessary demounting and disassembling of wheelsets, which generates unnecessary additional costs. In order to adjust the sensitivity of the inspection system to reduce the number of false calls without compromising safety, the capability of the system to detect cracks needs to be comprehensively established. This capability can be quantified by using probability of detection (POD) curves for the system. The multi-parameter POD model makes it possible to include several factors that influence the crack detection in the analysis. The analysis presented in this paper shows that crack position, orientation, depth extension, and shape as well as the geometry of the axle all have influence on the ultrasonic response amplitude. For future work, calculation of the POD using multi-parameter POD model with these parameters is planned.
Today, it is an established fact that the capability of the non-destructive testing (NDT) to find flaws can be properly addressed only in terms of probability of detection (POD). The probabilistic, signal-response model, introduced in 1980s, was developed with experimental observation of eddy-current inspections of flat plate samples, containing surface breaking cracks. A linearity between the peak voltage measured by the testing system, and the crack depth was observed. The influence of the crack depth was therefore seen as the major influencing factor for the POD, whereas other factors merely caused the variability in the measurement. This model has proven itself valid for those inspection cases where there is only one main influencing factor on the POD (usually the flaw size) and other factors have a lesser influence. But with increasing requirements to quantify the capability of NDT systems in complex inspection situations, where several factors have a major influence on the POD, it has become clear that the applicability of this simple model has reached its limits. In disregard to its limitations, this model is regularly applied to those situations in which its fundamental assumptions are invalid, forcing evaluators and NDT researchers into attempts to fit the data to an unsuitable model, instead of fitting an appropriate model to the data.
The multiparameter POD model, developed in the early 2010s, enables more factors that influence detection to be simultaneously analysed, making the POD a function of multiple factors. The model is based on the inspection’s physical model, to describe the influence of different factors on the response signal. Measurement variability is obtained from the experiment. Using this model assisted determination of the POD, the necessary number of flaws for evaluation is reduced and a more comprehensive understanding of the inspection is obtained. Several examples of the successful application of the multi-parameter POD model in different fields will be presented.
Reliability of NDT is affected by human factors, which have thus far received the least amount of attention in the reliability assessments. With increased use of automation, in terms of mechanised testing (automation-assisted inspection and the corresponding evaluation of data), higher reliability standards are believed to have been achieved. However, human inspectors, and thus human factors, still play an important role throughout this process and the risks involved in this application are unknown. The aim of this study was to explore for the first time the risks associated with mechanised NDT and find ways of mitigating their effects on the inspection performance. Hence, the objectives were to identify and Analyse potential risks in mechanised NDT and devise measures against them. To address those objectives, a risk assessment in form of a Failure Modes and Effects Analysis (FMEA) was conducted. This analysis revealed potential for failure during both the acquisition and evaluation of NDT data that could be assigned to human, technology, and organisation. Since the existing preventive measures were judged to be insufficient to defend the system from identified failures, new preventive measures were suggested.
The non-destructive testing methods available for civil engineering (NDT-CE) enable the measurements of quantitative parameters, which realistically describe the characteristics of existing buildings. In the past, methods for quality evaluation and concepts for validation expanded into NDT-CE to improve the objectivity of measured data. Thereby, a metrological foundation was developed to collect statistically sound and structurally relevant information about the inner construction of structures without destructive interventions. More recently, the demand for recalculations of structural safety was identified. This paper summarizes a basic research study on structural analyses of bridges in combination with NDT. The aim is to use measurement data of nondestructive testing methods as stochastic quantities in static calculations. Therefore, a methodical interface between the guide to the expression of uncertainty in measurement and probabilistic approximation procedures (e.g. FORM) has been proven to be suitable. The motivation is to relate the scientific approach of the structural analysis with real information coming from existing structures and not with those found in the literature. A case study about the probabilistic bending proof of a reinforced concrete bridge with statistically verified data from ultrasonic measurements shows that the measuring results fulfil the requirements concerning precision, trueness, objectivity and reliability.
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.
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.
Non-destructive testing (NDT) is a major contributor to the safe railway operation. Even though NDT reliability in railway maintenance is affected by human factors, there are only just a few studies published in this field so far. Education and training of the NDT personnel are some of the most important drivers of safe and reliable NDT. Continuously improving current practices and tools used for educational purposes can be achieved not only through technical con¬tent, but also through the attention to human factors. The aim of this study was to deepen the understanding of possible human-related risks in the manual ultrasonic inspection of the hollow railway axles and to suggest measures to improve the education and training of the NDT person¬nel. This was achieved by means of Failure Modes and Effects Analysis (FMEA) carried out with eight NDT experts and by a survey of 27 experienced inspectors. The results show that failures can happen throughout the entire NDT process. Prevention of those failures could be improved through the optimization of the organization, technology, documentation and regulations, working conditions and the general process, and through the optimization of the formal education and training. Specialized training of the executives, extended training of the supervisors and the inspectors and improvement of the inspection documentation have been suggested. The study also showed potential for the improvements of the inspection in the field.
Non-destructive testing (NDT) is a major contributor to the safe railway operation. Even though NDT reliability in railway maintenance is affected by human factors, there are only just a few studies published in this field so far. Education and training of the NDT personnel are some of the most important drivers of safe and reliable NDT. Continuously improving current practices and tools used for educational purposes can be achieved not only through technical content, but also through the attention to human factors. The aim of this study was to deepen the understanding of possible human-related risks in the manual ultrasonic inspection of the hollow railway axles and to suggest measures to improve the education and training of the NDT personnel. This was achieved by means of Failure Modes and Effects Analysis (FMEA) carried out with eight NDT experts and by a survey of 27 experienced inspectors. The results show that failures can happen throughout the entire NDT process. Prevention of those failures could be improved through the optimization of the organization, technology, documentation and regulations, working conditions and the general process, and through the optimization of the formal education and training. Specialized training of the executives, extended training of the supervisors and the inspectors and improvement of the inspection documentation have been suggested. The study also showed potential for the improvements of the inspection in the field.