中文摘要：

再制造发动机平衡性是影响再制造发动机使用性能的重要因素之一。分析影响再制造发动机曲轴平衡性的关键因素,探究曲轴主轴颈径向跳动、直径、圆柱度及曲轴端面跳动、弯曲度等因素不确定性的内涵;考虑各个因素测量值的离散程度及测量值与理想值的偏差程度,构建因素不确定性定量化测度模型;在以上研究基础上,提出基于改进BP神经网络（BPNN）的发动机曲轴再制造平衡性质量控制方法,其中,网络模型采用梯度下降法对输入层到隐层之间的权值和阈值进行调整,采用支持向量机调整隐层到输出层之间的权值和阈值;通过某企业再制造曲轴的质量数据表明,方法能够有效提高再制造曲轴平衡性合格率,降低曲轴加工废品率,应用实例验证了提出方法的可行性和有效性。

英文摘要：

Remanufactured crankshaft’s balance is one of the important factors affecting the performance of the remanufactured engine. The connotation of uncertainty for crankshaft main journal runout are studied, diameter, cylindrical and crankshaft runout, bending and other factors. Considering the distance between the probability distribution of each factor and the ideal value, a quantitative uncertainty measure model is built. Based on the above study, remanufactured crankshaft’s balance control method based on improved BP neural network （BPNN） is proposed. Network model adjusts weights and thresholds of input layer to the hidden layer by gradient descent, and alters weights and thresholds of hidden layer to the output layer by support vector machines. The method can effectively improve the pass rate of the remanufacturing crankshaft’ balance, and reduce the scrap rate of crankshafts. The application example demonstrates the feasibility and effectiveness.