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Forecasting the number of failures of the steering system components with the use of the grey system theory method

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Steering systems are one of the most important components of a car and have a direct impact on safety and driving comfort. Therefore, high reliability is required of them. One of the methods of object reliability estimation may be the grey system theory. This method can be used not only to calculate the number of failures, but also to calculate the wear of mating parts, and the vibrations of engines and rolling elements. This work presents the use of the grey system theory for the examination of motor vehicle steering system reliability. The forecast number of failures was calculated for the various components of the steering system and the grey system accuracy was assessed. This is aimed at finding out how useful this theory is for forecasting the number of steering system failures.
Rocznik
Tom
Strony
85--97
Opis fizyczny
Bibliogr. 26 poz.
Twórcy
  • State University of Applied Sciences Nowy Sącz, Institute of Engineering, Zamenhofa 1A, 33-300 Nowy Sącz, Poland
  • State University of Applied Sciences Nowy Sącz, Institute of Engineering, Zamenhofa 1A, 33-300 Nowy Sącz, Poland
Bibliografia
  • 1. Bezuglov Anton, Gurcan Comert. 2016. „Short-term freeway traffic parameter prediction: Application of grey system theory models”. Expert Systems With Applications 62: 284-292.
  • 2. Bok-WonLee, Jungjun Suh, Hongchu Lee, Tae-gu Kim. 2011. „Investigations on fretting fatigue in aircraft engine compressor blade”. Engineering Failure Analysis 18 (7): 1900-1908.
  • 3. Cempel Czesław, Maciej Tabaszewski. 2007. „Application of grey system theory to modeling and forecasting in machine condition monitoring”. Diagnostyka 2(42): 11-18.
  • 4. Chen-EnTsa, Jiames Hung, Youxin Hu, Da-Yung Wang, Robert M.Pilliar, Rizhi Wang. 2021. „Improving fretting corrosion resistance of CoCrMo alloy with TiSiN and ZrN coatings for orthopedic applications”. Journal of the Mechanical Behavior of Biomedical Materials 114: 104233.
  • 5. Deng J-L. 1982. „Control Problems of Grey Systems”. Systems and Control Letters 1(5): 288-294.
  • 6. Deng Julong. 1989. „Introduction to Grey System Theory”. The Journal of Grey System 1: 1-24.
  • 7. Gabryelewicz M. 2011. Podwozia i nadwozia pojazdów samochodowych. [In Polish: Chassis and bodies of motor vehicles]. Part 2. Warsaw: WKiŁ. ISBN: 9788320618266.
  • 8. Jui-Chen Huang. 2011. „Application of grey system theory in telecare”. Computers in Biology and Medicine 41(5): 302-306.
  • 9. Kayacan Erdal, Ulutas Baris, Kaynak Okyay. 2010. „Grey system theory-based models in time series prediction”. Expert Systems with Applications 37 (2): 1784-1789.
  • 10. Kowalski Sławomir. 2018. „Analysis of the possibilities of using CrN+a-C:H:W coatings to mitigate fretting wear in push fit joints operating in rotational bending conditions”. Tribologia 1: 45-55.
  • 11. Kowalski Sławomir. 2016. „Application of dimensional analysis in the fretting wear studies”. Journal of the Balkan Tribological Association 22(4-I): 3823-3835.
  • 12. Kowalski Sławomir. 2020. „Failure analysis of the elements of a forced-in joint operating in rotational bending conditions”. Engineering Failure Analysis 118: 104864.
  • 13. Kowalski Sławomir. 2017. „Selected problems in the exploitation of wheel sets in rail vehicles”. Journal of Machine Construction and Maintenance 2: 109-116.
  • 14. Kowalski Sławomir, Mariusz Cygnar. 2019. „The application of TiSiN/TiAlN coatings in the mitigation of fretting wear in push fit joints”. Wear 426: 725-734.
  • 15. Li-Qiang Hu, Chao-Feng He, Zhao-Quan Cai, Long Wen, Teng Ren. 2018. „Track circuit fault prediction method based on grey theory and expert system”. J. Vis. Commun. Image R. 58: 37-45.
  • 16. Liu Sifeng. 2007. „The Current Developing Status on Grey System Theory” The Journal of Grey System 2: 111-123.
  • 17. Maláková Silvia, Peter Frankovský, Daniela Harachová, Vojtech Neumann. 2019. „Design of constructional optimisation determined for mixed truck gearbox”. AD ALTA Journal of Interdisciplinary Research 9: 414-417. ISSN: 1804-7890.
  • 18. Maláková Silvia, Michal Puškár, Peter Frankovský, Samuel Sivák, Maroš Palko, Miroslav Palko. 2020. „Meshing Stiffness - A Parameter Affecting the Emission of Gearboxes”. Applied Sciences 10(3): 1-12. DOI: 10.3390/app10238678.
  • 19. Mazurkiewicz D. 2014. „Computer-aided maintenance and reliability management systems for conveyor belts”. Eksploatacja i Niezawodnosc – Maintenance and Reliability 16(3): 377-382.
  • 20. Michalski R., S. Wierzbicki. 2008. „An analysis of degradation of vehicles in operation”. Eksploatacja i Niezawodnosc – Maintenance and Reliability 1: 30-32.
  • 21. Mu-Shang Yin. 2013. „Fifteen years of grey system theory research: A historical review and bibliometric analysis”. Expert Systems with Applications 40: 2767-2775.
  • 22. Shuwei Wanga, Peng Wanga, Yifei Zhang. 2020. „A prediction method for urban heat supply based on grey system theory”. Sustainable Cities and Society 52: 101819.
  • 23. Steering and suspancion components. Available at: https://en.tw-central.com.
  • 24. Tabaszewski Maciej. 2014. “Prediction of diagnostic symptom values using a set of models GM(1,1) and a moving window method”. Diagnostyka 15(3): 65-68.
  • 25. Vaičekauskis M., R. Gaidys, V. Ostaševičius. 2013. „Influence of boundary conditions on the vibration modes of the smart turning tool”. Mechanika 3: 296-300.
  • 26. Xingqi Wang, Lei Qi, Chan Chen, Jingfan Tang, Ming Jiang. 2014. „Grey System Theory based prediction for topic trend on Internet”. Engineering Applications of Artificial Intelligence 29: 191-200.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-94ea35e8-4de0-4a7e-bb1d-f4d6da456a6c
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