CN-115016260-B - Energy consumption modeling and process parameter optimization method for laser cleaning process

Abstract

The invention relates to a laser cleaning process energy consumption modeling and process parameter optimizing method, and belongs to the technical field of advanced manufacturing and automation. The method comprises the following steps of establishing a laser cleaning process energy consumption model based on energy consumption analysis of a laser system, a robot system, a cooling system and a dust removal system, establishing a power real-time monitoring platform to obtain energy consumption model test parameters, establishing an energy consumption-oriented laser cleaning process parameter optimization model by considering energy efficiency, surface roughness and surface oxygen content factors, solving the model by using an improved lion optimization algorithm, and carrying out example analysis. The method is simple and practical, fully considers the energy consumption and the cleaning quality in modeling, and provides good support for optimizing the energy consumption in the laser cleaning process.

Inventors

• JIANG XINGYU
• LI JIAZHEN
• WANG HONGYUE
• Suo Yingqi
• LIU TONGMING
• TIAN ZHIQIANG
• Yu Shenhong

Assignees

• 沈阳工业大学

Dates

Publication Date

20260505

Application Date

20220519

Claims (1)

1. 1. The energy consumption modeling and technological parameter optimizing method for the laser cleaning process is characterized by comprising the following steps: s1, establishing an energy consumption model of a laser cleaning process based on energy consumption analysis of a laser system, a robot system, a cooling system and a dust removal system; s2, building a power real-time monitoring platform to obtain energy consumption model test parameters; S3, establishing an energy consumption-oriented laser cleaning process parameter optimization model by considering energy efficiency, surface roughness and surface oxygen content factors; S4, solving a laser cleaning process parameter optimization model based on an improved lion group optimization algorithm; s5, analyzing the examples, Step S1 comprises the steps of: S6, constructing an equipment total energy consumption model, wherein E T ＝E l +E r +E a is the total energy consumption of the laser cleaning equipment, E l is the laser system energy consumption, E r is the robot system energy consumption, and E a is the auxiliary system energy consumption; s7, constructing a laser system energy consumption model: Wherein P lw is standby power of a laser system, E l is energy consumption of the laser system, P lc is operation power of a laser, P l is output power of the laser, and t l is operation time of the laser system; S8, constructing an energy consumption model of the robot system: E r ＝P rw ×(t t -t r )+P rwo ×t r ＝P rw ×(t t -L/v r )+P rwo ×L/v r , Wherein P rw is the standby power of the robot, P rwo is the running power of the robot, t r is the running time of the robot, v r is the running speed of the robot, and L is the cleaning length; S9, constructing an energy consumption model of an auxiliary system, wherein E a ＝E co +E ep is the energy consumption of a cooling system, E ep is the energy consumption of a dust removal system, and the energy consumption of the cooling system can be expressed as: Wherein P cw is the standby power of the cooling system, P cwo is the operating power of the cooling system, T t is the total operating time of the cooling system, eta is the heat absorption efficiency of the cooling system, rho is the cooling water density, v is the cooling water flow rate, C is the specific heat capacity of the cooling water, deltaT is the cooling water temperature difference, the energy consumption of the dedusting system can be expressed as E ep ＝P epw ×(t t -t ep )+P epwo ×t ep , wherein P epw and P epwo are the standby power and the operating power of the dedusting system respectively, and T ep is the operating time of the dedusting system; s10, a total energy consumption model in a laser cleaning process: step S2 includes the steps of: S11, building a power real-time monitoring platform based on laser cleaning equipment; S12, obtaining power of the laser in an operation state by data fitting, wherein the power is P lc =683.4+2.685×n×f, n is single pulse energy, and f is pulse frequency; S13, acquiring power parameters of a robot system; s14, acquiring a power parameter value of a cooling system; S15, acquiring the working power value of the dust removal system, Step S3 includes the steps of: S16, building an energy consumption objective function based on the energy consumption model S17, establishing an energy efficiency function S18, fitting a surface roughness function based on experimental data R a ＝6.535-0.1292n-0.021f+0.00067n 2 ; S19, fitting a surface oxygen content function based on experimental data W to ＝392.943+0.03399n 2 -0.0535v 2 -0.259f 2 -7.6515n+0.7805v-1.607f+0.0245nv+0.0845nf-0.2465vf S20, establishing a multi-objective optimization function model F(n,f,v r )＝{minE,minR a ,minW to ,maxη} Step S4 includes the steps of: S21, performing multi-objective optimization based on an improved lion group optimization algorithm; s22, selecting an optimal solution based on an entropy weight-TOPSIS method.

Description

Energy consumption modeling and process parameter optimization method for laser cleaning process Technical Field The invention relates to a laser cleaning process energy consumption modeling and process parameter optimizing method, and belongs to the technical field of advanced manufacturing and automation. Background In recent years, carbon peak and carbon neutralization have become the major matters of coping with global climate change and realizing sustainable development in countries of the world today. The first manufacturing country in the world is China, the industrial energy consumption is a main source of carbon emission, and how to save energy and reduce the carbon emission of manufacturing industry is the key of economic sustainable development of China. The laser cleaning technology is used as an important direction in the laser processing technology in the current industrial field, and utilizes high-energy pulse shock waves of laser to break acting force between pollutants and the surfaces of parts, so that the pollutants [1] are removed, and the laser cleaning technology is widely applied to the fields of aerospace, marine equipment and rail transit. However, the laser cleaning is due to the long time consumption of the laser cleaning process, and the incomplete conversion of electric energy and the incomplete utilization of laser energy cause a great deal of energy consumption in the laser cleaning process. Therefore, how to build the energy consumption model and process optimization of the laser cleaning process is the key for realizing the green high-quality development of the laser cleaning technology. Disclosure of Invention Aiming at the problems, the invention develops a method for modeling the energy consumption and optimizing the technological parameters in the laser cleaning process, analyzes the energy consumption characteristics and rules of each system of the laser cleaning equipment, and establishes an energy consumption model in the cleaning process of the laser cleaning equipment. On the basis, a multi-target optimizing model of technological parameters of a laser cleaning process with energy consumption, energy efficiency, surface roughness and surface oxygen content as targets is established, an improved lion optimizing algorithm is provided for solving, optimal technological parameters are obtained, and the effectiveness and feasibility of the model are verified through experimental cases of removing the anodic oxidation film of the aluminum material by laser. The invention relates to a method for modeling energy consumption and optimizing technological parameters in a laser cleaning process, which comprises the following steps: s1, establishing an energy consumption model of a laser cleaning process based on energy consumption analysis of a laser system, a robot system, a cooling system and a dust removal system; s2, building a power real-time monitoring platform to obtain energy consumption model test parameters; S3, establishing an energy consumption-oriented laser cleaning process parameter optimization model by considering energy efficiency, surface roughness and surface oxygen content factors; S4, solving a laser cleaning process parameter optimization model based on an improved lion group optimization algorithm; s5, analyzing examples. The step S1 comprises the following sub-steps: S6, constructing a total energy consumption model of the equipment, wherein E T＝El+Er+Ea is the total energy consumption of the laser cleaning equipment, E l is the energy consumption of a laser system, E r is the energy consumption of a robot system, and E a is the energy consumption of an auxiliary system. S7, constructing a laser system energy consumption model: Wherein P lw is standby power of the laser system, E l is energy consumption of the laser system, P lc is operation power of the laser, P l is output power of the laser, and t l is operation time of the laser system. S8, constructing a robot system energy consumption model ：Er＝Prw×(tt-tr)+Prwo×tr＝Prw×(tt-L/vr)+Prwo×L/vr,, wherein P rw is robot standby power, P rwo is robot running power, t r is robot running time, v r is robot running speed, and L is cleaning length. S9, constructing an energy consumption model of the auxiliary system, wherein E a＝Eco+Eep is the energy consumption of the cooling system, and E ep is the energy consumption of the dust removal system. The cooling system energy consumption can be expressed as: Wherein P cw is the standby power of the cooling system, P cwo is the running power of the cooling system, T t is the total running time of the cooling system, eta is the heat absorption efficiency of the cooling system, rho is the cooling water density, v is the cooling water flow rate, C is the specific heat capacity of the cooling water, and DeltaT is the cooling water temperature difference. The energy consumption of the dust removing system can be expressed as E ep＝Pepw×(tt-tep)+Pepwo×tep, wherein P epw an