Author:
Louadah Hassna,Mistry Pritesh,Tucker Gareth
Publisher
Springer Nature Switzerland
Reference8 articles.
1. Ham, S., Han, S.-Y., Kim, S., Park, H.J., Park, K.-J., Choi, J.-H.: A comparative study of fault diagnosis for train door system: traditional versus deep learning approaches. Sensors 19(23), 5160 (2019). https://doi.org/10.3390/s19235160
2. Practical Reliability Engineering, 5th Edn. Wiley. https://www.wiley.com/en-gb/Practical+Reliability+Engineering%2C+5th+Edition-p-9780470979815. Accessed 25 Jul 2023
3. Aslansefat, K., Latif-Shabgahi, G., Kamarlouei, M.: A strategy for reliability evaluation and fault diagnosis of autonomous underwater gliding robot based on its fault tree. Int. J. Adv. Sci. Eng. Technol. 1(2), 83–89 (2014)
4. Cortés, J., Martino, D.D., Duran, D., López, J., Pons-Prats, J., Sánchez, J.: Development and implementation of a direct evaluation solution for fault tree analyses competing with traditional minimal cut sets methods. IEEE Trans. Rel. 72(1), 248–257 (2023). https://doi.org/10.1109/TR.2022.3175243
5. Dinmohammadi, F., Alkali, B., Shafiee, M., Bérenguer, C., Labib, A.: Risk evaluation of railway rolling stock failures using FMECA technique: a case study of passenger door system. Urban Rail. Transit. 2(3–4), 128–145 (2016). https://doi.org/10.1007/s40864-016-0043-z