Operating index optimization method in beneficiation process

Abstract

The invention discloses an operating index optimization method in the beneficiation process, and belongs to the technical field of the beneficiation process. The method comprises the steps of collecting operating indexes of various processes in the beneficiation process; optimizing the operating indexes in the beneficiation process according to the collected operating indexes and operating index boundary constraint so as to optimize the quality index and the yield index in the beneficiation process, wherein the optimization process comprises the steps of setting the boundary constraint, the target value of the quality index and the target value of the yield index of the beneficiation process, optimizing the set target value of the quality index and the set target value of the yield index, predicting the quality index and the yield index, obtaining the predicted value of the quality index and the predicted value of the yield index, correcting the preset values of the target values of the operating indexes and obtaining the optimization values of the operating indexes; and sending control instructions to the various processes in the beneficiation process according to the optimization values of the operating indexes. According to the method, by setting corresponding work condition parameters, the target values of the operating indexes corresponding to the different processes are controlled through complete flow scheme daily comprehensive production index optimization of enterprises, and coordinative optimization of the various processes in the beneficiation process is achieved.

Description

technical field [0001] The invention belongs to the technical field of beneficiation process, and relates to a method for optimizing the operation index of the beneficiation process. Background technique [0002] Mining is the industry with the longest history, and it is also the basic industry of national economic development. It involves agriculture, light industry, chemical industry, metallurgy, machinery, construction, energy, transportation, national defense and many fields of people's daily life, and has penetrated into To aerospace, information and other high-tech industries. It can be seen that the mining industry plays an irreplaceable and important role in economic development. The beneficiation process is an extremely complicated industrial process, involving multiple beneficiation process processes such as shaft furnace, ore grinding (strong and weak grinding) and magnetic separation (strong and weak magnetic beneficiation). At the same time, each process is int...

AI Technical Summary

Problems solved by technology

Most of the research on the traditional optimization control system is limited to the local optimization of a single process, without taking into account the various factors affecting the industrial production process of the beneficiation process at the same time

[0007] 2. The optimal control objective of the research is not comprehensive enough

For example, only a single indicator such as benefit or cost is considered, and indicators such as resource consumption, energy consumption, and output are ignored

[0008] 3. It is difficult to effectively integrate production process automation information and production process management information

[0009] 4. The key process indicators in the production process of the enterprise are often adjusted manually by experience

Due to the frequent and changeable production conditions and the lack of real-time process data support, it is often difficult to achieve the optimization of process indicators in this way

[0010] 5. Existing research often only studies isolated process index control algorithms, and has not passed the overall verification test in the actual environment of complex industrial processes, so it is difficult to apply to complex and changeable production processes

[0011] 6. The existing algorithm encapsulation methods only support the encapsulation of algorithms based on mathematical models and cannot be dynamically changed according to changes in environmental parameters

However, many of the optimization algorithms corresponding to each model in the index optimization control process are intelligent algorithms based on data, and the index optimization control system requires multiple algorithms to be executed interactively. The calculation environment parameters of each step are dynamically changed, and cannot be obtained through prior documents. predefined

Therefore, this encapsulation method is difficult to effectively solve the needs of actual index optimization

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