Study On The Friction Of The Soft Shaft

Soft shaft is one of the relatively new type of transmission parts in recent years, which has been more widely used in motorcycle, automobile, portable devices such as machine tools, airplanes or on system. The future can also be extended to all kinds of other mechanical structure. Wire winding type flexible shaft which was researched has more impact on the internal friction between spindle and hose for soft shaft transmission efficiency, working precision, stability and service life. Study of soft shaft friction is more and more highlights its importance.Particle swarm algorithm and genetic algorithm were selected in this study are two important intelligent algorithm. Intelligent algorithm can provide a good solution to solve the problem that traditional algorithm is not easy to deal with.This topic was on the research of Wuling Automobile and electric bicycle motor soft shaft, the results were as follows:(1)Soft shaft of electric bicycle and Wuling Automobile was in accordance with three kinds of different core diameters, three kinds of different lengths and ten kinds of different radius of curvature to stage 30 groups experiments. 30 groups of experimental data was measured under every experiment condition. Then the data was analyzed and set a preliminary formula of friction force.(2)Being used least squares regression analysis method and combined with the experimental data suggested that soft shaft friction experience formula was deduced. Comparison of calculation results and the actual value of friction, the total average error rate is 7.60%, especially in large diameter(3.12 mm) and diameter(2.64 mm), the average error rate is 5.90%. The formula was needed to modify as the error was relatively large.(3)Being used particle swarm optimization(pso), the correction formula of flexible shaft friction. The average error rate was 7.35%. Especially in large diameter(3.12 mm) and diameter(2.64 mm), the range of the average error rate is 3.04%, decreased by 0.25% and 2.86%, respectively. It was relatively good practicality.(4)Combined with the empirical formula and genetic algorithm, optimal qualification was explored under different constraint conditions. In order to get the minimum friction values appear when the core shaft length, diameter and radius of curvature.