The working environment of deep-sea platforms is complex and harsh, with frequent incidents of fire and explosion. In the event of an accident, there is a high probability of significant casualties, environmental pollution, and economic losses. The assessment of vulnerabilities in emergency systems is instrumental in facilitating a comprehensive understanding of the safety risks confronted by offshore platforms. This assessment enables the timely identification of potential vulnerabilities in emergency systems, thereby reducing the likelihood of accidents. The present paper puts forth a vulnerability assessment model for emergency systems of offshore platforms. This model is based on the theoretical framework of cloud model theory. Firstly, an assessment index system for the vulnerability of offshore drilling platform emergencies was constructed. This system was constructed by applying the principles of human factors engineering to the specific characteristics of the emergency management system of offshore drilling platforms. Expert experience is combined with subjective weighting of risk factors through expert scoring. The objective weighting method, CRITIC, is then used to calculate the correlations and conflicts between the indicators. Finally, game theory is used to calculate the composite weights for the evaluation factors, providing the optimal weightings. In consideration of the factors that engender vulnerability, the cloud model—which is characterized by its fuzzy and random properties—was adopted for the purpose of assessing the vulnerability of the emergency response system. A standard cloud diagram was established based on the quantitative grading standards. The digital characteristic values of each risk indicator were calculated using MATLAB software, and a cloud risk assessment diagram was generated based on this, which can visually display the vulnerability level of each indicator. The research content provides a theoretical basis and reference for the daily safety management and emergency response decision-making of offshore drilling platforms.
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