Industrial control system function safety quantitative evaluation method based on digital twinborn technology

Abstract

An industrial control system function safety quantitative evaluation method based on a digital twin technology comprises the following steps: establishing a digital twin model by taking industrial production equipment as a prototype, generating a large amount of data sets for fault diagnosis and prediction through a predictive maintenance function of the digital twin technology, then defining and calculating the offset of a given index in an industrial scene, and determining the safety of the industrial control system. The functional safety risk value of the industrial production equipment is obtained, the availability of the equipment can be reflected, the functional safety risk value of the whole industrial control system is finally fed back, and quantitative evaluation of the functional safety of the whole industrial control system is achieved.

Description

technical field [0001] The present invention relates to a technology in the field of industrial safety, in particular to a quantitative evaluation method for the functional safety of an industrial control system based on digital twin technology. Background technique [0002] The security assessment of existing industrial control systems is generally divided into two aspects: information security assessment and functional safety assessment. Among them, the information security aspect is biased towards the assessment of network security, while the functional security is biased towards the assessment of the availability of physical equipment. Most of the research at home and abroad focuses on information security, and the research on functional security is still in its infancy, and there are a lot of problems to be solved urgently. For example, the current research is still in the stage of fault detection in a certain scenario, which can only classify faults, but cannot quantit...

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Problems solved by technology

For example, the current research is still in the stage of fault detection in a certain scenario, which can only classify faults and cannot quantify the severity of faults.

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