Research On The Prediction Of The Optimum Proportion Of Lubricating Grease Additives Based On RSM And PSO-BP

Lubricating grease is an indispensable material for construction machinery,which has both lubricating functions and sealing and anti-corrosion functions.It is the core of protective materials for modern mechanical equipment.Therefore,optimizing the lubricating grease with excellent performance is crucial to ensuring the stable operation of major equipment.Starting with two commonly used composite greases(complex lithium grease and complex calcium sulfonate grease),this paper uses algorithms to achieve the scientific combination of two types of grease and extreme pressure antiwear agents.Response surface methodology is used to design experiments,and optimization algorithms are used to establish a mathematical model for predicting the tribological properties of lubricating greases.The main research contents and conclusions are as follows:(1)Composite lithium based grease and composite calcium sulfonate based grease were prepared,and the physicochemical and tribological properties of composite lubricating greases with different levels of two factors(composite lithium based grease and composite calcium sulfonate based grease)were deeply studied.The influence of the levels of each factor on the physical and tribological properties of each composite grease was revealed.The research found that the waterproof performance of the composite calcium sulfonate grease is superior,and the corrosion resistance of the composite lithium grease is better.The SPSS analysis method was used to calculate the optimal ratio of the composite lubricating grease.Based on the evaluation of the effectiveness of composite grease by drop point measurement and copper corrosion test,the lubrication mechanism of composite grease was discussed from the perspective of the interaction between the two greases.(2)Using calcium metaborate modified with oleic acid as a antifriction and antiwear agent,the tribological properties of composite lubricating grease were studied.The optimal concentration of each antifriction and antiwear agent was obtained by uniform test method.Using composite test-response surface analysis method,the optimal synergistic concentration of the oleic acid modifier was 0.6 wt%,the concentration of calcium metaborate was 1.5 wt%,and the optimal ratio of complex lubricating grease was(complex lithium grease:complex calcium sulfonate grease)3:7.(3)Based on the previous research,a response surface analysis experimental prediction model was designed.According to the prediction model,the optimal response surface ratio of complex lubricating grease was obtained as(complex lithium grease:complex calcium sulfonate grease:calcium metaborate)/(3.082:6.788:1.479 wt%).Collate the experimental data of response surface method and uniform experiment to establish a prediction model,and establish a mathematical regression model based on BP neural network optimized by particle swarm optimization.Based on the PSO-BP algorithm,the friction coefficient was accurately predicted,and the determination coefficient R2 reached 95.10%,which was verified through experiments.