Nowadays, with the integration of diverse mechatronic components, a mechatronic system is capable of performing more difficult and complex tasks. At the same time, it becomes more and more difficult to develop a system to ensure the safety of these complex mechatronic systems. This paper outlines a novel method for fault detection, which uses a neural network monitor based on a feed forward back propagation (FFBP) algorithm. The goal of this study is to develop a real-time capable method for detection of abnormal or faulty behavior of an automation system. An example is used to illuminate the capability of the neural network in modeling and real-time data in this work. Furthermore this method is validated on a test bed, which is developed at the institute of product development Karlsruhe (IPEK). This method will allow the monitor to detect critical state of the system due to unexpected influences in real-time, so that safety hazard to personnel and equipment caused by the fault can be prevented or mitigated.

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In 2015, it has been reported that road traffic fatality rate in Thailand ranks number 2 in the world at 36.2 per 100,000 with an annual estimate of 66 deaths every day. Based on the survey of the Road Safety Group Thailand in 2017, at least one student got injury by school transport each day. A recent survey also revealed that the number of private hire pick-up trucks as school buses in Thailand, especially in upcountry areas, is increasing due to its lower cost in comparison to that of a van or a minibus. To get the optimal capacity as vans or minibuses, pick-up trucks’ roofs were converted for the highest passenger number at the lowest cost. Therefore, to focus on the strength of converted pick-up truck’s roof is required to help reduce losses in terms of both human injury and inside cabin’s damage due to rollover accidents. This article demonstrates an approach to design the vehicle’s roof as a superstructure of school pick-up truck based on design inputs, including structural strength, capability of local motor vehicle mechanics, nature of drivers, and nature of passengers. Explicit dynamic finite element analysis is applied to simulate the investigation on full-scale prototype according to American Federal Motor Vehicle Safety Standard No 220 standard. To validate the numerical analysis results, the roof crush test of full-scale roof prototype is performed. The analysis results showed the accurate prediction on the strength and the corresponding deformations of the full-scale prototype. These findings provide means of evaluating the strength of vehicle’s roof, which can be further applied as a guideline for national regulation. This study is planned to bring this tried prototype: the superstructure of school pick-up truck’s roof, to use in a commercial scale.

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