Research On Detection And Extrapolation Technology Of Sliding Friction Coefficient Between Tire And Anti-skid Coating

The anti-skid coating of aircraft carrier deck bears the tasks of taking off and landing for carrier-based airplane.In the manufacture of aircraft carriers,detecting anti-skid performance is a key part of the anti-skid coating.Sliding friction coefficient is an important parameter for stands for anti-skid performance,which is related to safe landing for carrier-based airplane.Thus,measuring the coefficient of sliding friction for anti-skid coating development is necessary.This thesis develops a dynamic load tester for the sliding friction coefficient of anti-skid coating based on track angle and impact load theory of instantaneous carrierbased airplane landing.When a traditional adaptive filtering method based on the energy rule method is used to filter the noise for spike signals,false peaks is to be relected in the filtered signal.Filtering methods based on the difference of intrinsic mode function(IMF)and sorting energy are proposed for the comprehensive consideration of filter effectiveness and computation time,respectively.If the sliding friction coefficient cannot be obtained beyond the tester range,then the extrapolation technology based on the sine and successive step method is proposed to extrapolate the sliding friction coefficient.This thesis further investigates the preceding concepts mentioned,and the main research contents and results are summarized as follows.At present,the traditional tester does not comprehensively measure the sliding friction coefficient under dynamic load.For the preceding problems mentioned,the sliding friction coefficient tester is developed for tire and anti-skid coating.The lack of theoretical direction for designing the tester is resolved based on track angle and impact load for carrier-based airplane with instantaneous landing.The equipment is a rotated airplane wheel with high speed.The design aims to satisfy the need for various rotation speeds.The measured force platform for the extensive range is designed to measure at a maximum of 900 k N impact load and 600 k N friction load.Finally,the white noise is identified by power spectral density.When the traditional adaptive filtering method based on the energy rule method is used to filter out the noise of spike signals,false peaks appear in the filtered signal.a novel filtering method based on the IMF difference is proposed to filter.This method establishes the difference in frequency of noise and signal in the IMFs using the improved empirical mode decomposition(EMD)for spike signal decomposition.The difference occurs between the spike signal and IMF cumulative sum.The demarcation point is identified by mutual information.Furthermore,the peak value is obtained by re-constructing the signal with guidance from the IMFs.The results show that the filtered effectiveness improved by 7.6% and 9.3% compared to the energy rule method for friction and impact signals under certain conditions,respectively,such as high hammer drop distance and airplane speed,and identified time of relevant mode is 1.07 s.A novel filtering method based on sorting and energy is proposed for the demarcation point head of the relevant mode using the difference method based on IMFs under low tire rotation speed.This method does an enormous number test and found that it adaptively identified the demarcation point by sorting normalized computation energy–computation fuzzy entropy.The adaptive low pass filter is designed by combining it with improved EMD.Hence,noise is effectively separated.Filter effectiveness improved by 7% more than the IMF difference method,and the identified time of relevant mode is 32.23 s.The extrapolated method based on sine and successive step method is proposed to address the lack of an extrapolating model of sliding friction coefficient.This method normalizes the data using sine function and builds a training sample for support vector regression(SVR)by successive steps method.Meanwhile,the SVR parameters are optimized by intelligence algorithm.The results show that the extrapolated precision improved by 36.16%,15.82%,and 12.43% compared to those of the line and overall method,and sine and overall method,line and successive steps method when the coefficient of sliding friction decreases with the increase in hammer drop height and revolving speed of airplane wheel.This method innovatively utilizes the sine normalized method and successive steps into pretreatment for the SVR model,significantly improves the extrapolated precision,and possesses notable practicability and maneuverability.