Research And Application Of Intelligent Control System In Grinding Process

The grinding process is an important part of ore dressing production,its role is to grind and classify the large particles of ore,making useful mineral sufficient monomer dissociation and avoiding crushing,providing the material which fully meet the requirement of subsequent processing.The process is complicated,with grinding particle size is difficult to detect,operating condition variable,nonlinear,time delay and so on.Grinding particle size is a key to test the grinding product,directly restricts the quality of grinding product and metal recovery rate.Therefore,carrying out the research of soft measurement technology,optimization and control,the grinding particle size be controlled within the scope of technical requirements is of great significance.The main contents of this article are as follows:First of all,the soft-sensing model of the particle size is established base on the least squares support vector machine,the improved fruit fly optimization algorithm is used to optimize the penalty coefficient and kernel parameter of the least squares support vector machine.Simulation verify the effect of the soft measurement model which real-time detects the grinding particle size,the results show that the method has fast operation speed and high prediction accuracy.Secondly,it is difficult to get the ideal grinding particle size because of the changing production conditions.Using fuzzy expert system on the basic loop automatically optimize and adjust the setting value.Then making use of fuzzy adaptive sliding mode controller to fast-track the adjusted setting value,realizing the continuous and stable control of key process parameters.Finally,in order to reduce the cost and risk of commissioning in the field,using the hardware-in-the-loop simulation experimental platform of grinding process for validation.Modular processing algorithms,and loaded into the optimization virtual device of grinding,from running effects can be seen grinding particle size is stable within the target range,the effectiveness and feasibility of the intelligent control system is validated.