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Development of a Knowledge-Based System for Diagnosing of Diesel Engines

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Vehicle and Automotive Engineering 4 (VAE 2022)

Part of the book series: Lecture Notes in Mechanical Engineering ((LNME))

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Abstract

Knowledge-Based Systems apply Artificial Intelligence techniques to solve difficult problems in complex systems that well-trained experts can only manage. These systems can support the decision-making of inexperienced people with the necessary tools to do work that requires high expertise. These systems depend on three main resources: human expertise, experiments, and previous observations. Furthermore, Knowledge-Based Systems reduce the complexity of operation and implementation, making them flexible and easy to understand. The combination of knowledge-based diagnostic methods with recording and monitoring of operating variables; furthermore, adding them to the knowledge base improves the efficiency and reliability of detecting the machine’s behaviour and the effectiveness of the whole system. The aim of the study is to develop a Knowledge-Based System including five stages that could be improved separately to optimize the operation of the machines. In addition, this system allows the evaluation, updating, modification, and integration of the rules in the knowledge base, which results in efficiency improvement of the machines’ operation. Firstly, this paper briefly introduces the different methods to analyze knowledge obtained from human experts in the most effective way. We aimed to maintain the quality of the information and define the effect that experts and the types of machines being understudied on selecting the most suitable method to deal with this information to form the final knowledge base. After it, we reviewed the theories that deal with uncertain and qualitative information and the most appropriate theory for the Knowledge-Based System. Finally, different directions in software tools for Expert Systems development were reviewed. The main added value of the study is the development of the new Knowledge-Based System, which can be handled more flexibly by inexperienced users and increase the reliability and efficiency of the marine diesel engines.

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Acknowledgements

The research was supported by the Hungarian National Research, Development, and Innovation Office - NKFIH under the project number K 134358.

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Authors and Affiliations

  1. Institute of Manufacturing Science, University of Miskolc, Faculty of Mechanical Engineering and Informatics, H-3515, Miskolc, Egyetemváros, Hungary

    Hla Gharib & György Kovács

Authors
  1. Hla Gharib
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  2. György Kovács
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Correspondence to Hla Gharib .

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Editors and Affiliations

  1. Faculty of Mechanical Engineering and Informatics, Institute of Energy Engineering and Chemical Machinery, University of Miskolc, Miskolc, Hungary

    Károly Jármai

  2. Faculty of Mechanical Engineering and Informatics, Institute of Logistics, University of Miskolc, Miskolc, Hungary

    Ákos Cservenák

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Gharib, H., Kovács, G. (2023). Development of a Knowledge-Based System for Diagnosing of Diesel Engines. In: Jármai, K., Cservenák, Á. (eds) Vehicle and Automotive Engineering 4. VAE 2022. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-031-15211-5_18

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  • DOI: https://doi.org/10.1007/978-3-031-15211-5_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-15210-8

  • Online ISBN: 978-3-031-15211-5

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