CN-121993386-A - Control method, device, storage medium and program product for air compressor unit

CN121993386ACN 121993386 ACN121993386 ACN 121993386ACN-121993386-A

Abstract

The application provides a control method, equipment, a storage medium and a program product of an air compressor unit, and relates to the technical field of industrial automation. The method comprises the steps of obtaining operation data of industrial equipment, determining weighted excitation intensity of each fuzzy rule through a multi-working condition model based on the operation data, inputting the weighted excitation intensity into a state prediction model to obtain an operation parameter adjustment strategy of an air compressor unit, and controlling the air compressor unit to operate according to the operation parameter adjustment strategy. According to the method, the boundary uncertainty of working conditions is quantified through the three-section type model logic, so that a multi-working condition model can be dynamically matched with a multi-unit start-stop combination and load fluctuation scene, control misalignment caused by fuzzy working condition division of a traditional model is avoided, the problems of energy consumption optimization, supply-demand balance and safe and stable operation of an air compressor unit under complex and variable working conditions are solved, the energy consumption minimization and air supply pressure stability of the air compressor unit under the complex working conditions are realized, and the comprehensive requirements of industrial scenes on energy efficiency and continuity are met.

Inventors

CHAI JIQIANG
WANG LIN
SHAO KAI
FENG XINGZHI
YANG JIAN
MA HAIJING
ZHANG XIANG
WU DAOXIANG
Hao Wanzong
LIU DEYAN

Assignees

卡奥斯能源科技有限公司
卡奥斯数字科技(青岛)有限公司

Dates

Publication Date: 20260508
Application Date: 20260116

Claims (10)

1. A control method of an air compressor unit, comprising: acquiring operation data of industrial equipment; Based on the operation data, determining the weighted excitation intensity of each fuzzy rule through a multi-working condition model, wherein the multi-working condition model is used for identifying the operation working condition of industrial equipment, and the weighted excitation intensity is used for reflecting the matching degree of the operation data and different working conditions; And inputting the weighted excitation intensity to a state prediction model to obtain an operation parameter adjustment strategy of the air compressor unit, and controlling the air compressor unit to operate according to the operation parameter adjustment strategy, wherein the state prediction model is used for predicting the operation parameters of industrial equipment under different working conditions.
2. The method according to claim 1, wherein the method further comprises: Establishing a multi-working-condition model based on a three-section fuzzy logic system, wherein the three-section fuzzy logic system is used for quantifying fuzzy boundaries between operation working conditions under different loads, the multi-working-condition model comprises an upper membership function and a lower membership function, the upper membership function is a function for quantifying the upper boundary uncertainty of the working conditions, and the lower membership function is a function for quantifying the lower boundary uncertainty of the working conditions; Updating the upper membership function and the lower membership function based on the operation data, and updating the multi-working condition model based on the updated upper membership function and lower membership function; The determining, based on the operation data, the weighted excitation intensity of each fuzzy rule through a multi-working condition model includes: and determining the weighted excitation intensity of each fuzzy rule through the updated multi-working condition model based on the operation data.
3. The method of claim 2, wherein updating the upper membership function and the lower membership function based on the operational data comprises: determining a prediction error of the operation data, wherein the prediction error is used for representing deviation between actual gas production and predicted gas production corresponding to the operation data of the industrial equipment; Under the condition that the prediction error of the operation data exceeds a preset error threshold, the parameter value of the upper membership function is improved, and the parameter value of the lower membership function is reduced; The method comprises the steps of setting up the inflection point of an upper membership function, setting up the width of a compression section, setting up the inflection point of a lower membership function, setting up the inflection point of the upper membership function, and setting up the width of the compression section.
4. The method of claim 1, wherein said inputting the weighted excitation intensities into a state prediction model results in an operating parameter adjustment strategy for the air compressor package, comprising: and under the multi-dimensional constraint condition of the industrial equipment, the weighted excitation intensity is input into a state prediction model to obtain an operation parameter adjustment strategy of the air compressor unit aiming at minimizing energy consumption.
5. The method of claim 4, wherein the multi-dimensional constraints include secure operation constraints, supply-demand matching constraints, and operation mechanism constraints; The safe operation constraint is used for ensuring the safety of the physical boundary of the industrial equipment, the supply and demand matching constraint is used for maintaining the balance between the output and the load demand of the air compressor unit, and the operation mechanism constraint is used for constraining the start-stop frequency and the operation duration of the industrial equipment.
6. The method according to claim 1, wherein the method further comprises: determining a start-stop candidate strategy of the air compressor unit according to the weighted excitation intensity output by the multi-working condition model; the step of inputting the weighted excitation intensity to a state prediction model to obtain an operation parameter adjustment strategy of the air compressor unit, and the step of further comprising: And inputting the weighted excitation intensity and the start-stop candidate strategy of the air compressor unit into a state prediction model to obtain the operation parameter adjustment strategy of the air compressor unit.
7. The method of claim 6, wherein the start-stop candidate strategy of the air compressor package specifically comprises at least one of the following: Selecting an efficient unit combination under a high-load working condition according to the weighted excitation intensity; and selecting an energy-saving unit combination under a low-load working condition according to the weighted excitation intensity.
8. An electronic device is characterized by comprising a memory and a processor; The memory stores computer-executable instructions; The processor executing computer-executable instructions stored in the memory, causing the processor to perform the method of any one of claims 1-7.
9. A computer readable storage medium having stored therein computer executable instructions which when executed by a processor are adapted to carry out the method of any one of claims 1-7.
10. A computer program product comprising a computer program which, when executed by a processor, implements the method of any of claims 1-7.

Description

Control method, device, storage medium and program product for air compressor unit Technical Field The present application relates to the field of industrial automation technology, and in particular, to a method, an apparatus, a storage medium, and a program product for controlling an air compressor unit. Background Air compressor units (air compressor units) are important energy-saving equipment in the industrial field, and the energy efficiency level of the air compressor units directly influences the industrial energy-saving aim. The air compressor unit is widely applied to the parallel energy supply scene of multiple units in an industrial park due to reliable operation and high efficiency. However, the operation of the air-conditioning unit in the existing industrial scene faces complex and dynamic load demands, the traditional manual control depends on experience of operators, and the load change is difficult to respond in real time, so that the air supply of the unit is unbalanced with the actual demand, further the production efficiency is reduced, and the energy waste is aggravated. Disclosure of Invention The application provides a control method, equipment, a storage medium and a program product of an air compressor unit, which are used for solving the technical problems that the traditional manual control depends on experience of operators, and the load change is difficult to respond in real time, so that the air supply and the actual demand of the unit are unbalanced, the production efficiency is reduced, and the energy waste is aggravated. In a first aspect, the present application provides a control method of an air compressor unit, including: acquiring operation data of industrial equipment; Based on the operation data, determining the weighted excitation intensity of each fuzzy rule through a multi-working condition model, wherein the multi-working condition model is used for identifying the operation working condition of industrial equipment, and the weighted excitation intensity is used for reflecting the matching degree of the operation data and different working conditions; And inputting the weighted excitation intensity to a state prediction model to obtain an operation parameter adjustment strategy of the air compressor unit, and controlling the air compressor unit to operate according to the operation parameter adjustment strategy, wherein the state prediction model is used for predicting the operation parameters of industrial equipment under different working conditions. In one possible embodiment, the method further comprises: Constructing a multi-working-condition model based on a three-section fuzzy logic system, wherein the three-section fuzzy logic system is used for quantifying fuzzy boundaries between operation working conditions under different loads, the multi-working-condition model comprises an upper membership function and a lower membership function, the upper membership function is a function for quantifying the upper boundary uncertainty of the working conditions, and the lower membership function is a function for quantifying the lower boundary uncertainty of the working conditions; Updating the upper membership function and the lower membership function based on the operation data, and updating the multi-working condition model based on the updated upper membership function and lower membership function; The determining, based on the operation data, the weighted excitation intensity of each fuzzy rule through a multi-working condition model includes: and determining the weighted excitation intensity of each fuzzy rule through the updated multi-working condition model based on the operation data. In a possible embodiment, the updating the upper membership function and the lower membership function based on the operation data includes: determining a prediction error of the operation data, wherein the prediction error is used for representing deviation between actual gas production and predicted gas production corresponding to the operation data of the industrial equipment; Under the condition that the prediction error of the operation data exceeds a preset error threshold, the parameter value of the upper membership function is improved, and the parameter value of the lower membership function is reduced; The method comprises the steps of setting up the inflection point of an upper membership function, setting up the width of a compression section, setting up the inflection point of a lower membership function, setting up the inflection point of the upper membership function, and setting up the width of the compression section. In one possible implementation manner, the step of inputting the weighted excitation intensity into a state prediction model to obtain an operation parameter adjustment strategy of the air compressor unit includes: and under the multi-dimensional constraint condition of the industrial equipment, the weighted excitation intensity is input into a