CN-120704172-B - Dynamic simulation control system of sand mixing equipment based on artificial intelligence

CN120704172BCN 120704172 BCN120704172 BCN 120704172BCN-120704172-B

Abstract

The invention belongs to the field of sand mixing equipment control, relates to a data analysis technology, and is used for solving the problem that the operation parameters of the sand mixing equipment cannot be set according to the requirements of users in the prior art, in particular to a dynamic simulation control system of the sand mixing equipment based on artificial intelligence, which comprises a simulation test module, a test analysis module, a requirement analysis module and a control execution module which are connected in sequence; the simulation test module is used for carrying out simulation test analysis on the sand mixing equipment, generating a plurality of groups of test values for the operation parameters of the sand mixing equipment, setting the operation parameters of the sand mixing equipment according to the test values, and obtaining the effect coefficient when the sand mixing process is finished.

Inventors

ZHANG KUN
FENG FUQUAN
DENG ZHONGQIANG

Assignees

山东坤铄环保科技有限公司

Dates

Publication Date: 20260508
Application Date: 20250627

Claims (7)

1. The dynamic simulation control system of the sand mixing equipment based on artificial intelligence is characterized by comprising a simulation test module, a test analysis module, a demand analysis module and a control execution module which are connected in sequence; The simulation test module is used for performing simulation test analysis on the sand mixing equipment, namely, a sand mixing formula is called, a plurality of groups of test values are generated for the operation parameters of the sand mixing equipment, and a sand mixing equipment is allocated for each group of test values; the test analysis module is used for processing and analyzing test data of the sand mixing equipment, namely marking the test numerical value as an effective numerical value or an ineffective numerical value through an effect coefficient, generating a formula optimization signal and sending the formula optimization signal to a mobile phone terminal of a manager if all the test numerical values corresponding to the same sand mixing formula are marked as the ineffective numerical value, generating a demand analysis signal and sending the demand analysis signal to the demand analysis module if the effective numerical values exist in all the test numerical values corresponding to the same sand mixing formula; The demand analysis module is used for carrying out demand analysis on the sand mixing equipment, namely acquiring a motor surface temperature value and a bearing temperature value of the sand mixing equipment in the sand mixing process, marking the sum of the maximum values of the motor surface temperature value and the bearing temperature value in the sand mixing process as a fault risk value, marking a stable demand value and an effect demand value through the fault risk value and an effect coefficient, and sending the stable demand value and the effect demand value of all the sand mixing formulas to the control execution module; the control execution module is used for carrying out sand mixing control analysis on the sand mixing equipment; The process for obtaining the effect coefficient corresponding to the test value comprises the steps of obtaining the water content of the sand material and marking the water content as a water content value when the sand mixing process is finished, calling the water content range of the sand material, marking the average value of the maximum value and the minimum value of the water content range of the sand material as a water content standard value, marking the absolute value of the difference value between the water content value and the water content standard value as a water content deviation value, marking the ratio of the water content deviation value and the water content standard value as a water content deviation coefficient, carrying out image shooting on the sand material surface to obtain a detection image when the sand mixing process is finished, eliminating the grain texture interference of the sand material of the detection image through Gaussian filtering, extracting the energy coefficient of the detection image through a gray level co-occurrence matrix, and marking the difference value between the energy coefficient and the water content deviation coefficient as the effect coefficient.
2. The dynamic simulation control system of the artificial intelligence-based sand mixing equipment according to claim 1, wherein the sand materials, the adhesive and the additives are weighed and proportioned according to a sand mixing formula, the proportioned raw materials are put into the sand mixing equipment, the operation parameters comprise the output rotating speed of a motor, the mixing time and the heating temperature, and the generation process of the test values is to randomly select one value as the test value in the value range of the corresponding operation parameters.
3. The dynamic simulation control system of the sand mixing equipment based on the artificial intelligence according to claim 2 is characterized in that the specific process of marking the test value as the effective value or the ineffective value comprises the steps of obtaining an effect threshold value through a database, comparing an effect coefficient with the effect threshold value, judging that the sand mixing effect of the corresponding sand mixing process does not meet the requirement if the effect coefficient is smaller than the effect threshold value, marking the corresponding test value as the ineffective value, and judging that the sand mixing effect of the corresponding sand mixing process meets the requirement if the effect coefficient is larger than or equal to the effect threshold value, and marking the corresponding test value as the effective value.
4. The dynamic simulation control system of the artificial intelligence-based sand mixing equipment according to claim 3, wherein the marking process of the stable demand value comprises marking an effective value corresponding to the sand mixing process with the minimum fault risk value as the stable demand value of the sand mixing formula; The marking process of the effect demand value comprises the steps of obtaining a fault risk threshold value through a database, comparing fault risk values of all sand mixing processes with the fault risk threshold value one by one, marking the corresponding sand mixing process as a safety process if the fault risk value is smaller than the fault risk threshold value, marking the corresponding sand mixing process as a risk process if the fault risk value is larger than or equal to the fault risk threshold value, and marking an effective value corresponding to the safety process with the largest effect coefficient as the effect demand value of the sand mixing formula.
5. The dynamic simulation control system of the artificial intelligence-based sand mixing equipment according to claim 4, wherein the concrete process of performing sand mixing control analysis on the sand mixing equipment by the control execution module comprises the steps of generating a control period, when a sand mixing task is received in the control period, calling a stable demand value and an effect demand value corresponding to a sand mixing formula, enabling a user to select the stable demand value or the effect demand value by himself or herself to perform numerical setting on operation parameters of the sand mixing equipment, preferably selecting the stable demand value to perform operation parameter setting when the user does not select, calculating an effect coefficient of the sand mixing process after the sand mixing is completed, and marking a difference value between an expected effect coefficient and the effect coefficient of the sand mixing process as an expected deviation value.
6. The dynamic simulation control system of the artificial intelligence-based sand mixing equipment according to claim 5, wherein the concrete process of performing sand mixing control analysis on the sand mixing equipment by the control execution module further comprises the steps of summing expected deviation values of all sand mixing processes at the end time of a control period to obtain an expected deviation coefficient, acquiring an expected deviation threshold value through a database, comparing the expected deviation coefficient with the expected deviation threshold value, judging that the overall sand mixing effect of the control period meets the requirement if the expected deviation coefficient is smaller than the expected deviation threshold value, judging that the overall sand mixing effect of the control period does not meet the requirement if the expected deviation coefficient is larger than or equal to the expected deviation threshold value, generating a retest signal and sending the retest signal to the simulation test module.
7. The dynamic simulation control system of an artificial intelligence based sand mixing device according to any one of claims 1 to 6, wherein the working method of the dynamic simulation control system of the artificial intelligence based sand mixing device comprises the following steps: step one, performing simulation test analysis on sand mixing equipment; step two, processing and analyzing test data of the sand mixing equipment; step three, carrying out demand analysis on sand mixing equipment; And fourthly, performing sand mixing control analysis on the sand mixing equipment.

Description

Dynamic simulation control system of sand mixing equipment based on artificial intelligence Technical Field The invention belongs to the field of sand mixing equipment control, relates to a data analysis technology, and in particular relates to a dynamic simulation control system of sand mixing equipment based on artificial intelligence. Background The sand mixer is a key device for mixing sand materials, adhesives and other additives in the industries of casting, chemical industry, building materials and the like, utilizes the relative motion of a grinding wheel and a grinding disc to crush materials by the rolling and grinding actions of the materials arranged between the grinding wheel and the grinding disc, and mixes the materials while crushing the materials, and the stability and the precision of a control system of the sand mixer directly influence the mixing quality and the production efficiency. The invention patent with the publication number of CN111830849B discloses a dynamic simulation system and a device of a sand mixing vehicle, and the simulation system solves the problems that in the prior art, when the sand mixing vehicle is constructed, an operation interface is displayed for data, the dynamic simulation system is not available, the operation condition of equipment cannot be intuitively known, the operability of the equipment and the identifiability of faults are poor, but the system cannot set operation parameters of the sand mixing equipment according to the requirements of users, and the operation stability and the sand mixing effect of the equipment cannot be considered. The application provides a solution to the technical problem. Disclosure of Invention The invention aims to provide a dynamic simulation control system of a sand mixing device based on artificial intelligence, which is used for solving the problem that the operation parameters of the sand mixing device cannot be set according to the requirements of users in the prior art; the invention aims to provide an artificial intelligence-based dynamic simulation control system for the sand mixing equipment, which can set the operation parameters of the sand mixing equipment according to the requirements of users. The aim of the invention can be achieved by the following technical scheme: The dynamic simulation control system of the sand mixing equipment based on artificial intelligence comprises a simulation test module, a test analysis module, a demand analysis module and a control execution module which are connected in sequence; The simulation test module is used for performing simulation test analysis on the sand mixing equipment, namely, a sand mixing formula is called, a plurality of groups of test values are generated for the operation parameters of the sand mixing equipment, and a sand mixing equipment is allocated for each group of test values; the test analysis module is used for processing and analyzing test data of the sand mixing equipment, namely marking the test numerical value as an effective numerical value or an ineffective numerical value through an effect coefficient, generating a formula optimization signal and sending the formula optimization signal to a mobile phone terminal of a manager if all the test numerical values corresponding to the same sand mixing formula are marked as the ineffective numerical value, generating a demand analysis signal and sending the demand analysis signal to the demand analysis module if the effective numerical values exist in all the test numerical values corresponding to the same sand mixing formula; The demand analysis module is used for carrying out demand analysis on the sand mixing equipment, namely acquiring a motor surface temperature value and a bearing temperature value of the sand mixing equipment in the sand mixing process, marking the sum of the maximum values of the motor surface temperature value and the bearing temperature value in the sand mixing process as a fault risk value, marking a stable demand value and an effect demand value through the fault risk value and an effect coefficient, and sending the stable demand value and the effect demand value of all the sand mixing formulas to the control execution module; The control execution module is used for carrying out sand mixing control analysis on the sand mixing equipment. Further, the sand materials, the adhesive and the additives are weighed and proportioned according to the sand mixing formula, the proportioned raw materials are put into sand mixing equipment, the operation parameters comprise motor output rotating speed, mixing time and heating temperature, and the generation process of the test values is to randomly select one value as the test value in the value range of the corresponding operation parameters. The method comprises the steps of obtaining the water content of sand materials and marking the water content as a water content value when the sand mixing process is finished, calling the water