Optimization of Vehicle Diagnostic Algorithms at Equipment Design Stage

The paper shows that today a worker can be considered as an integral part of the “human-machine” system in case of using modern diagnostic equipment. Therefore, in order to ensure the effectiveness of diagnosing vehicle systems, it is necessary to use engineering psychology methods at the stage of equipment design. Traditionally, the description of “human-machine” systems functioning is implemented in the form of an algorithm. Thereat, coefficients of stereotyped and logical complexity act as the criteria of the algorithm rationality. However, at the design stage, it is necessary to estimate the parameters at the preliminary stages, when the algorithm is not finally formulated; therefore, the situation of lack of initial data occurs. The paper considers the possibility of using the fuzzy logic apparatus to overcome this problem. The data determined with implementation of real diagnostic algorithms are used as initial data. The authors elaborated models for estimating the parameters of logical complexity and stereotype that give an error of no more than 10%. Based on fuzzy logic, the model was created that enables formulating recommendations for ensuring a given level of compatibility of the elements of the “human-machine” system when designing diagnostic equipment of transport enterprises.

• Record URL:
  • https://doi.org/10.1007/978-3-030-37916-2
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9783030379155
• Supplemental Notes:
  • © Springer Nature Switzerland AG 2020.
• Corporate Authors:

  Springer International Publishing

  ,    
• Authors:
  • Vasilyev, Valery
  • Ovsyannikov, Viktor
  • Kovalev, Rudolf
• Conference:
  • VIII International Scientific Siberian Transport Forum (TransSiberia 2019)
  • Location: Novosibirsk , Russia
  • Date: 2019-5-22 to 2019-5-27
• Publication Date: 2020-1

Language

• English

Media Info

• Media Type: Web
• Edition: 1
• Features: References;
• Pagination: pp 677-684
• Monograph Title: VIII International Scientific Siberian Transport Forum: TransSiberia 2019, Volume 1
• Serial:
  • Advances in Intelligent Systems and Computing
  • Volume: 1115
  • Publisher: Springer International Publishing
  • ISSN: 2194-5357
  • Serial URL: http://link.springer.com/bookseries/11156

Subject/Index Terms

• TRT Terms: Algorithms; Diagnostic tests; Equipment design; Fuzzy logic; Human machine systems; Vehicle maintenance
• Subject Areas: Data and Information Technology; Design; Highways; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01899699
• Record Type: Publication
• ISBN: 9783030379155
• Files: TRIS
• Created Date: Nov 17 2023 11:25AM