Determination of statistical data of conditional probabilities of the technical condition of internal combustion engines when compiling the Bayes diagnostic table
Creators
- 1. Department of Tractors, Automobiles and Power Plants of the Mechanization and Technical Service Institute, Kazan State Agrarian University, 65 K. Marksa St., 420015, Kazan (Russian Federation)
- 2. Department of General Engineering Disciplines of the Mechanization and Technical Service Institute, Kazan State Agrarian University, 65 K. Marksa St., 420015, Kazan (Russian Federation)
Description
One of attractive methods for in-place diagnostics of internal combustion engines is the method based on using the generalized Bayes formula of conditional probabilities. The article is devoted to the applicability improvement of the Bayes algorithm for assessing the technical condition of internal combustion engines. The use of this algorithm involves the compilation of a diagnostic table, the elements of which are conditional probabilities of selected diagnoses in case of a range of faults. Their relevant determination requires a large amount of statistical data, which is often lacking. To supplement deficient data and increase the reliability of obtained results, the authors propose to use a method for simulating patterns of changes in design parameters of the technical condition of internal combustion engines depending on operating time. (paper)
Availability note (English)
Available from http://dx.doi.org/10.1088/1757-899X/635/1/012017Additional details
Identifiers
Publishing Information
- Journal Title
- IOP Conference Series. Materials Science and Engineering (Online)
- Journal Volume
- 635
- Journal Issue
- 1
- Journal Page Range
- [6 p.]
- ISSN
- 1757-899X
Conference
- Title
- 10. International Conference on Mechatronics and Manufacturing
- Acronym
- ICMM 2019
- Dates
- 21-23 Jan 2019
- Place
- Bangkok (Thailand)
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 52121373
- Subject category
- S42: ENGINEERING;
- Resource subtype / Literary indicator
- Conference
- Descriptors DEI
- ALGORITHMS; COMBUSTION; DESIGN; INTERNAL COMBUSTION ENGINES; RELIABILITY
- Descriptors DEC
- CHEMICAL REACTIONS; ENGINES; HEAT ENGINES; MATHEMATICAL LOGIC; OXIDATION; THERMOCHEMICAL PROCESSES