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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.
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.