The Application of Neural Networks to Modular Arrangements of Predetermined Time Standards
Keywords:artificial neural network, modular arrangement of predetermined time standard, TensorFlow algorithm
To study the method of reducing the low-frequency vibration noise of tires, a passenger car tire (205/55R16) is taken as the research object. The dynamic grounding characteristics and vibration reduction mechanism of the cat’s paw pad are analysed. The research showed that the swing deformation characteristics of paw pads during the walking process of cats are one of the main ways to reduce the impact from the ground and achieve vibration reduction and silencing. To analyse the influence of tire grounding on noise, tire grounding is divided into five areas, and the characteristics of ten tire grounding areas are analysed through tests. Pearson correlation analysis is used to obtain the characteristics of the eight most relevant grounding parameters with tire noise, and multiple linear regression is conducted between the characteristics of the eight grounding areas. The product of the correlation coefficient and the average value of the characteristics of the ground contact area shows that the central area of the tire tread contributes the most to the tire noise. The swing deformation characteristics of the bionic cat paw pad are realized by setting the staggered side branch pipe groove in the centre of the tire, and the vibration reduction characteristics of the bionic tire are analysed using the finite element method. The results showed that when the tire rolls, the amplitude and fluctuation range of the ground radial excitation force acting on the bionic tire are reduced compared with the original tire, and the vibration and noise characteristics of the tire are improved.
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