The Quality Monitoring System Of Emulsion Explosive Based On Soft Measurement Technology

As a new type of industrial explosives,emulsion explosive has played a very important role in promoting economic development and social progress.The production of emulsion explosives is increasing,at the same time,the number of substandard products is also increasing.The quality of emulsion explosives not only affect the core competitiveness of enterprises,but also related to people's lives and property.The detonation performance of emulsion explosive is affected by detonation velocity and brisance,which are the two critical performance indexes of emulsion explosives.However,these two key performance indicators can not be measured online.At present,the detection of detonation velocity and brisance is mainly through the method of sampling detection.This off-line analysis can not guarantee the quality of the explosive product due to the long sampling period.Another way to guarantee quality is to set thresholds for these critical parameters and to warn when the parameter exceeds the threshold.In fact,even if all parameters are within the threshold,the production of emulsion explosives may still be substandard products.Therefore,there is blindness and uncertainty in the production of emulsion explosives.The control of product quality of emulsified explosives needs to develop in the direction of on-line monitoring.The development of the soft measurement technology makes it possible to monitor the quality of emulsion explosive online.In this paper,the soft measurement technology is applied to control the quality of emulsion explosives,and the quality monitoring system of emulsion explosives based on BP neural network optimized by genetic algorithm is proposed.This method is to establish the multivariable soft measurement model to predict the detonation velocity and brisance of the emulsion explosive,so that the product quality can be monitored in real time.This paper mainly carries on the following several research:(1)Study on the production process of emulsion explosives;analyze the main performance indicators of emulsion explosives and the factors affecting product quality.A soft-sensing model is proposed to measure the detonation velocity and brisance of the emulsion explosives.(2)Study on the four methods to set up the soft measurement model.In combination with the actual production of emulsion explosives,the BP neural network was used to establish the soft-sensing model of the quality monitoring system of emulsion explosives.Inorder to improve the accuracy of BP neural network model,genetic algorithm is used to optimize the BP neural network.(3)The process of establishing the soft-sensing model of the quality monitoring system of emulsion explosive is expounded,and the effectiveness of the soft-sensing model is analyzed by an example.(4)The hardware construction and the preliminary design of the software of the quality monitoring system have finished.