Research on reliability evaluation of high-speed railway train control system based on fault injection

Wei, Shang; Cai, Bin; Gou, Chen-xi; Wang, Jian; Wang, Jingjing

doi:10.1109/esiat.2010.5568359

Cited by 1 publication

(1 citation statement)

References 9 publications

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“…This core feature is more logical and, as an industry-recognized report template, it can be a powerful aid to the structuring of industrial safety knowledge. The main presentation forms of industrial safety reports are [31] the Job Hazard Analysis (JHA), Failure-Type Effects (FMEA), PHA, Event Tree (ET), Accident Tree (AT), Operating Conditions Hazard Evaluation Method (OCHE), HAZOP, Quantitative Risk Assessment (QRA), Layer of Protection Analysis (LOPA), risk-based risk assessment-based equipment inspection techniques (RBI), safety integrity-level analysis (SIL), and failure assumption method (WI). Safety reporting is an analytical process of reverse reasoning whose main purpose is to explore systematically and in an organized manner whether there are hazards in process equipment or facilities [32] and which provides the necessary decisions to eliminate and reduce the hazards in the process and mitigate the consequences of accidents.…”

Section: Safety Reportmentioning

confidence: 99%

A Study on a Knowledge Graph Construction Method of Safety Reports for Process Industries

et al. 2023

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There are some representative reports in industrial safety engineering, such as the Hazard and Operability Analysis and Pre-Hazard Analysis; however, a large amount of industrial safety knowledge in the report has not been fully explored. In order to reuse and release the value of industrial safety knowledge, this paper constructs a new industrial safety knowledge extraction framework. The framework combines the asset management shell to summarize the knowledge concept entities of machine description language and model description language. According to the safety report template, the framework also constructs a new industrial safety knowledge-mapping standard structure. Specifically, firstly, considering that the knowledge structure of safety reports is different in different processes of the process industry, this paper innovatively proposes a general industrial safety knowledge-mapping standard structure, which provides a practical solution for the integration of industrial knowledge representation problems in different processes. Secondly, based on the research progress of named entities, this paper presents an industrial named entity extraction method (INERM) for the process industry. This method designs an entity weight model to calculate the entity weight of each sentence, and adds part-of-speech weight to improve the entity extraction algorithm, which alleviates the problem that the existing entity extraction methods cannot reasonably use the semantic information and context of word. Finally, we construct a triple of industrial safety knowledge based on the rules and store it in Neo4j. In this paper, four semantic-type templates and five semantic relation templates are constructed based on the new industrial safety knowledge map standardization construction process of the process industry. The comparative experiments show that the accuracy of the INERM on the test set is improved by 17 percentage points on average compared with other key entity extraction algorithms. A total of 1329 entities are constructed in the directional application example of the fluid transportation process, which provides a large number of references for the safety of the fluid transportation process and is more conducive to improving the safety guarantee of the fluid transport process.

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Section: Safety Reportmentioning

confidence: 99%