Analytische Chemie
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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.
Der einwandfreie Zustand der Radsätze von Schienenfahrzeugen ist von größter Bedeutung für den sicheren Betrieb. Die Radsatzwellen werden durch eine große Zahl von Lastwechseln individuell unterschiedlich beansprucht. Dabei spielen viele Einflüsse wie äußere statische und dynamische Lasten, innere Lasten aufgrund von Unwuchten und inneren Spannungen und Umweltbedingungen entscheidende Rollen. Eine regelmäßige Prüfung ist daher obligatorisch. BTD entwickelt im Rahmen eines MNPQ-Projektes in Kooperation mit der BAM eine Phased Array Technik zur automatisierten Prüfung von Radsatzwellen im eingebauten Zustand. Die schwierigen Ankoppelbedingungen aufgrund der begrenzten Zugänglichkeit, der komplexen Geometrie sowie Farbschichten und Schmutz auf der Radsatzwelle stellen hierbei große Herausforderungen dar. Zu deren Bewältigung werden neben optimierten Prüfköpfen, einer in die Wasservorlaufstrecke integrierten akustischen Linse und einer speziellen Ankoppeltechnik auch Signalverarbeitungsalgorithmen eingesetzt. Die Darstellung der Signalverarbeitung ist der Schwerpunkt dieses Beitrages. Mit Hilfe von Messdatensätzen präparierter Testwellen werden verschiedene Algorithmen erprobt und hinsichtlich der Stabilität, dem Verhalten bezüglich der Ankoppelschwankungen und veränderter Wellengeometrien und der Fähigkeit zur automatischen Unterscheidung von Fehler- und Formanzeigen bewertet. Letztlich wird die beste Lösung im entwickelten Prüfsystem eingesetzt.