NDLI: Application of Fault Diagnosis Expert System for Unmanned Vehicle Safety

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Application of Fault Diagnosis Expert System for Unmanned Vehicle Safety

Content Provider	Scilit
Author	Chen, Chunping Zhang, Lin Wang, Jie Zhang, Jie
Copyright Year	2019
Description	Journal: Iop Conference Series: Materials Science and Engineering In order to ensure the safety of the underwater unmanned vehicle (UUV) and reduce the risk of damage or loss during operation, the safety system will be equipped on the UUV. It can accurately locate the fault when the submersible encounters dangerous situations, such as equipment failure and cabin flooding, assess the dangerous situation and make emergency measures, so as to help the underwater unmanned submersible realize self-rescue. Fault diagnosis expert system is a knowledge-based fault diagnosis method, which is suitable for complex systems with incomplete knowledge. However, because the working environment of the underwater unmanned underwater vehicle is very complex and the fault types are diverse and change in real time, the traditional fault diagnosis expert system may not meet the response time requirements of the safety system due to the long response time required. Therefore, the finite state machine technology is applied to the diagnostic expert system to improve the response speed of the diagnostic expert system, and at the same time make the system more flexible and convenient to expand its functions. In addition, the model-based design method was applied to establish the model of the security system in stateflow, and the model verification was carried out. With the help of PLC Coder tool, the code of the target controller was generated and the algorithm was deployed.
Related Links	https://iopscience.iop.org/article/10.1088/1757-899X/608/1/012015/pdf
ISSN	17578981
e-ISSN	1757899X
DOI	10.1088/1757-899x/608/1/012015
Journal	Iop Conference Series: Materials Science and Engineering
Issue Number	1
Volume Number	608
Language	English
Publisher	IOP Publishing
Publisher Date	2019-08-01
Access Restriction	Open
Subject Keyword	Journal: Iop Conference Series: Materials Science and Engineering Marine Engineering Expert System Fault Diagnosis Underwater Unmanned
Content Type	Text
Resource Type	Article

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