Real-time quantitative risk evaluation of bag dedust system based on deviation degree-FCE
In order to ensure the safe operation of bag dedust system and prevent the occurrence of dust explosion accident,a real-time quantitative risk evaluation model of bag dedust system was proposed based on deviation degree-FCE.Firstly,based on the monitoring data of the pressure difference between inlet and outlet of the dust,box temperature and lock-in ash discharge fault signal collected by the industrial Internet of Things sensor,the deviation degree was introduced to characterize the risk status of the monitoring parameters of the bag dedust system.Then,FCE was used to calculate the risk status of the bag dedust system.The analytic hierarchy process(AHP) and variable weight theory were combined to assign weights to the evaluation indicators.Based on the membership function and weighted average principle of membership degree,the risk of the bag dedust system was quantified by deviation degree,and the risk evaluation result for the bag dedust system was obtained.Finally,the monitoring data of a certain type of bag dedust system was used to verify the effectiveness of the model.The findings demonstrate that when the monitoring value of the evaluation indicators of the bag dedust system gradually approaches the alarm threshold,and the number of indicators approaching the alarm threshold increases,the risk level is higher.The evaluation results are correlated with the actual operation situation,thus validating the efficacy of the model.
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