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-  2019 

车载活鱼运输制动阶段力学特性
Mechanical characteristics of vehicle mounted live fish in transport braking phase

Keywords: 活鱼运输 制动力学曲线 曲线拟合 最小二乘法 粒子群算法
transportation of live fish braking mechanical curve curve fitting least squares particle swarm optimization

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Abstract:

以鲫、草鱼、鳊、黄颡鱼为试验材料,研究车载活鱼在直线加减速运输过程中鱼体受力情况。利用最小二乘法,以高斯函数作为拟合函数,分别对以40、60、80 km/h直线行驶时制动阶段的力值曲线进行拟合,运用粒子群算法对拟合后曲线进行优化,最终曲线的决定系数为0.902~0.986,标准误差为0.058~0.145,拟合效果良好。分析了不同种类鱼和车速对拟合曲线的影响,结果表明,直线行驶时速度越大,制动阶段拟合曲线的比例系数及峰宽参数越大,在相同情况下,制动时鲫所受冲击最大(38.02 N),黄颡鱼最小(15.69 N),直线行驶时的车速和鱼的种类对位置参数无明显影响,直线行驶时的车速对拟合曲线的指数无明显影响。最后对制动阶段压力测试板进行受力分析,结果表明,制动阶段压力实测值较理论值相比偏小,相对误差在15.990%以内。
Crucian,grass carp,bream and yellow catfish were used to study the stress distribution of car borne live fish in the process of linear acceleration and deceleration.Using the least squares method and Gaussian function as the fitting function,the force value curves of the braking phase when traveling in a straight line of 40,60,80 km/h were respectively fitted,and the particle swarm algorithm was used to optimize the curve after fitting.The final curve had a coefficient of determination between 0.902 and 0.986,and the standard error was between 0.058 and 0.145.The fitting effect was good.The results of analyzing effects of different types of fish and vehicle speed on the fitting curve showed that the greater the speed in straight line driving,the larger the proportional coefficient and peak width parameter of the braking curve of the braking phase.Under the same situation,the squid was most affected by the braking (38.02 N) and the carp was the smallest (15.69 N).The speed of the vehicle and the type of fish in the straight line had no obvious influence on the position parameters,and the speed of the vehicle during straight running had no significant influence on the index of the fitted curve.The results of analyzing the force of the pressure test board in the braking phase showed that the measured value of the pressure in the braking phase was smaller than the theoretical value,and the relative error was less than 15.990%.

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