High-temperature Molten Metal Decision Support System Based On Probabilistic Linguistic Term Set

With the progress of science and technology,the level of my country's metallurgical industry has been significantly improved,and the continuous increase in output has made the development of the metallurgical industry show a steady and good trend.Due to the high-temperature molten metal operating environment and complicated process operations,and during the processing of smelting,transfer and pouring,there are a large number of high-temperature molten materials,and accidents such as explosion,splashing,leakage,and tipping are prone to occur on the job site,causing major personnel Casualties and equipment damage.In the face of such accidents,how to control accidental fatalities by minimizing accidental death rate by assembling complex and changeable accident information,executing emergency response procedures,and constructing a comprehensive accident rescue plan within a limited time is an important issue facing the development of the field of metal emergency accident handling.The accident rescue process often involves multiple decision-making experts in different departments and different fields.Due to the different interests of different experts and the different angles of consideration,the conflict of opinions in the decision-making process generally exists,and it is difficult to achieve the convergence of opinions.Therefore,this paper builds a high-temperature molten metal accident information management and decision support platform to solve the above decision needs.Through research on group decision theory and large group decision theory,this paper proposes a probabilistic semantic term cluster decision model based on fuzzy Borda method and a large group decision model that considers minority opinions and non-cooperative behaviors.On this basis,combined with field research and literature analysis,taking an aluminum production company as the research background,a comprehensive decision support system was established to meet the needs of daily management of high-temperature molten metal enterprises and the implementation of scientific disposal in response to unexpected accidents.Provide theory and application support for emergency treatment of high temperature molten metal accidents.The main work of the paper is as follows:(1)Based on the research of group decision theory,a probabilistic semantic term cluster decision model based on fuzzy Borda method is proposed.First,in view of the complexity,uncertainty and ambiguity of the decision-makers' subjective preferences in the group decision-making problem,probabilistic semantic term sets are used as the expression of the decision-makers' hesitant and uncertain evaluation information.Secondly,because different decision makers have different evaluation results on the same object set,in order to fully consider the coupling,relevance and membership of different opinions,the fuzzy Borda combination evaluation method is used to synthesize the evaluation opinions of each decision maker;the comprehensive score is calculated and get the best plan accordingly.(2)Based on the research of large group decision-making theory,a large group decision-making model that comprehensively considers minority opinions and uncooperative behaviors is proposed.Aiming at the calculation of consensus level,minority opinions and uncooperative behavior in the decision-making process of large groups,a reasonable similarity measurement method and an accurate consensus model were proposed.The specific process is: for minority opinions,by quantifying the difference between the number of subgroups that support minority opinions and the number of remaining subgroups,modify the weight of minority subgroups;for uncooperative behavior,adjust the direction and value by providing opinions,Adjust the decision-making opinions of uncooperative subgroups to improve the level of group consensus.(3)Based on the accident characteristics and corporate background of high-temperature molten metal accidents,the specific needs were extracted from management information,emergency response,decision support,etc.,and a modular high-temperature molten metal decision support system was designed from three aspects: architecture,functional structure,and database.,Using Web development tools to build a decision support system of BS mode,and finally taking an emergency rescue process of an aluminum ingot casting machine deflagration accident caused by a mixed furnace leak from an aluminum company as an example to verify the emergency decision support system of high temperature molten metal accident Feasibility and applicability.