Quick chemical leakage predicating and warning emergency response decision-making method

Abstract

The invention relates to a quick chemical leakage predicating and warning emergency response decision-making method which combines diffusion model simulation with a neural network and a gas sensor system and is applied to quick warning and aid decision making of leakage of harmful gas in an industrial park. The method includes park risk factor identification, numerical simulation, data screening, neural network training and sensor system and neural network model integration, wherein the park risk factor identification is used for identifying various possible leakage accidents, the numerical simulation includes simulating all the possible accidents to obtain a range of influences of the harmful gas, the data screening includes extracting and reconstructing an effective part in a numerical simulation result according to actual sensor layout, the neural network training includes training specific neural network models by the aid of screened data so as to acquire model parameters aiming for the specific industrial park and surrounding conditions and using redundant data for parameter validation, and sensor system and neural network model integration includes combining the models with a sensor DCS (distributed control system).

Description

technical field [0001] The invention belongs to the technical field of safety early warning in industrial production, and in particular relates to a decision-making method for rapid chemical leakage prediction, early warning and emergency response. Background technique [0002] Many process industries will use or produce some poisonous and harmful gases (such as chlorine gas, phosgene, etc.) that are harmful to human body during the production process. It can cause serious harm to humans within a certain range. When a toxic and harmful gas leakage accident occurs, the leaked substance and the approximate location of the leak can be relatively easily determined, but it is difficult to obtain the leakage rate or leakage rate of the harmful gas on site. It is an important part of the accident emergency response process to predict the diffusion trend and influence range of toxic gas with limited information in a limited time. At present, traditional numerical diffusion predict...

AI Technical Summary

Problems solved by technology

However, the disadvantage of using numerical model analysis is that the source strength (leakage rate) and leakage form (explosion leakage / aperture leakage, etc.) For real-time or fast prediction in accident state

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