基于关键参数的电驱动系统性能质量检测方法研究

Research on Performance Quality Testing Method of Electric Drive System Based on Key Parameters

针对电驱动系统在性能质量方面的局限性,提出了一种基于关键参数的性能检测方法。该方法引入基于梯度提升决策树的机器学习算法,构建并验证了性能质量检测模型,包含质量样本数据采集、特征工程分析、模型构建、模型融合及模型自训练机制等,实现了基于电驱动系统的生产加工关键参数判断产品性能检测质量,并结合生产实际,提出了应用场景建设思路及深化方向。结果表明,基于关键参数能够实现电驱动系统性能质量的检测。

To address the limitations of the electric drive system in terms of performance,this paper proposes a performance detection method based on key parameters,which introduces machine learning algorithm based on Gradient Boosted Decision Tree(GBDT)to construct and verify the performance quality detection model,including quality sample data collection,feature engineering analysis,model construction,model fusion and model self-training mechanism,etc.,to determine product performance inspection quality based on key production and processing parameters of electric drive system.Combined with production practice,the paper proposes the idea of application scenario construction and its deepening direction.The results show that electric drive system quality inspection can be realized based on key parameters.