目的 针对发附机匣齿轮振动总量与装配参数之间的关系不明晰的问题,提出一种结合Sobol敏感性分析与代理模型的参数影响评估方法。方法 首先,基于支持向量机回归（libsvm）构建发附机匣齿轮振动总量与装配参数之间的代理模型,通过蒙特卡洛方法生成装配参数的样本集,通过建立的代理模型计算样本输出,并采用Sobol敏感性分析方法,分别计算装配参数的一阶和总效应敏感性系数,从全局视角量化每个装配参数对齿轮振动总量的影响程度。最后,对敏感性结果进行排序并识别关键参数。结果 轴承外圈配合量值（喷口泵侧）和齿向公差对振动总量的贡献率最高,齿形公差与其他参数间的交互作用也对振动产生显著影响。结论 该方法可为发动机附件机匣齿轮实际振动控制及装配工艺优化提供一定理论依据和量化指导。
Abstract
The work aims to investigate the relationship between the total vibration amplitude of the bearing housing gear and assembly parameters, and propose a parameter impact evaluation method integrating Sobol sensitivity analysis with an agent model. First, an agent model linking the total vibration amplitude of the bearing housing gear to assembly parameters was constructed using support vector machine regression (libsvm). A sample set of assembly parameters was generated via the Monte Carlo method. The established agent model was employed to calculate output values for each parameter, followed by Sobol sensitivity analysis to determine both first-order and total effect sensitivity coefficients, quantifying the influence of individual assembly parameters on overall vibration amplitude from a holistic perspective. Finally, sensitivity results were ranked to identify critical parameters. Experimental findings indicated that the bearing outer ring fit dimension (on the main pump side) and tooth direction tolerance contributed most significantly to total vibration amplitude, while the interaction between tooth profile tolerance and other parameters also exhibited substantial impact. This methodology provides a theoretical foundation and quantitative guidance for vibration control and assembly process optimization of bearing housing gears.
关键词
发附机匣 /
装配参数 /
齿轮振动 /
灵敏度分析 /
支持向量机
Key words
engine accessory housing /
assembly parameters /
gear vibration /
sensitivity analysis /
support vector machine
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