After being studied the coupling mechanism between the batch drilling process quality fluctuation and monitoring signal features differences, the drilling step quality evaluation index, system and method based on the monitoring signal features will be presented to break through the consistency quality control problem of the high-precision batch drilling step. In the drilling process, when the relative contact position between the drill and the workpiece is changed instantly, there is mutation phenomenon of all kinds of monitor signals. On the basis of incorporating the drilling theory, machining monitoring technology , computer science theory and signal processing method, we will carry out theoretical research, drilling experiment and simulation to achieve the following objectives: 1) To extract drilling process monitoring signal transient features when the relative contact position between the tool and workpiece is changed instantly,and to construct the transient feature model between monitor signals and drilling process to divide the drilling stage; 2) To explore the drilling mechanism of the titanium alloy material of different drilling stage, and to expound the evolution coupling mechanism between the drilling step quality fluctuation and the various monitoring signal features differences; 3) To study the coupling mechanism between the fluctuation of the drilling step quality parameters and the difference of the various monitor signal features, and to construct the quality evaluation index of drilling step based on monitor signals features; 4) To design an eigenvector database to describe the batch drilling process step quality based on the monitor signals; and to adopt the principles of incremental clustering in order to study the batch machining process quality classification, prediction algorithm based on the transient feature model for evaluating and optimizing the test results. The research of this project could be used to realize the on-line quality control in the batch machining process step.
将批量钻削工步质量波动与钻削工步过程监控信号特征变化有机结合,基于两者耦合机制的研究,提出基于监控信号特征的工步质量评价指标、体系和方法,突破目前高精度批量钻削工步加工质量一致性检测控制难题。通过理论建模,实验和仿真分析,以钻削过程中刀具与工件相对接触位置瞬态改变时,各种监控传感器信号产生的突变机理研究为出发点,建立工步钻削过程与多传感器监控信号瞬态特征映射模型;划分切削阶段,研究工步过程中不同钻削阶段的瞬态切削机理,阐明工步质量波动与钻削监控信号各种时频域特征变化的演变规律;研究工步质量表征参数与监控信号统计特征和时频域内微结构过程特征耦合机制,构造基于监控信号时频域特征的工步质量评价指标;构建描述批量钻削工步过程质量的监控信号特征向量数据库,研究基于增量聚类思想的批量钻削工步过程质量在线检测算法,评估优化检测结果。为在线高精度批量切削工步质量一致性控制和检测提供理论基础。
在航空航天、汽车、电子等领域,孔系类零部件孔系钻削质量一致性是衡量与保证产品工作性能的关键因素。钻削过程处于封闭或半封闭环境,传统质量检测方法很难实现孔系类零部件高效、高精度、低成本的加工要求。本项目通过理论建模,实验和仿真分析,基于孔系加工质量波动与钻削过程监测信号变化间的耦合现象,提出了一种基于监测信号特征变化的孔系加工质量一致性检测方法。首先通过机理数学建模、有限元分析和实验数据处理等手段,研究了钻削过程中钻刃切入、切出工件、正常钻削以及退刀阶段中的监测信号与动力学参数变化,发现钻削过程中刀具与工件相对接触位置瞬态改变时,可根据监测信号RMS幅值特征突变有效划分钻削阶段,构建监测信号与钻削过程的映射模型;其次研制了一套钻削过程信号监测系统,可实现钻削过程的钻削力、主轴三向振动、工件三向振动、声发射、主轴电机功率信号检测以及钻削过程高速摄像;第三结合统计分析方法,采用短时傅立叶变换、小波变换、Hilbert-Huang变换、高阶谱等时频分析方法研究了钻削过程中不同监测信号在幅值、频率以及相位上的突变特征,研究表明:对钻削过程监测信号进行小波分析、Hilbert-Huang变换以及高阶谱分析,可获得与钻削质量波动密切相关的信号特征;第四开展了孔系钻削过程质量表征参数波动与多传感器监控信号特征变化耦合机制研究,结果表明监测信号偏离高斯分布的程度与孔系加工质量分布密切相关;第五融合监测信号统计特征、小波包能量谱、高阶谱等特征,构造了一个基于监控信号特征的钻削质量评价指标,并采用主成分分析(PCA)、可视化FCM聚类等方法对孔系钻削过程质量表征参数与信号特征进行匹配和模式识别研究,结果表明对孔系钻削过程监测信号的边际谱特征和双谱进行主成分分析聚类,可直观有效得到孔系钻削过程质量波动的分布状况。通过本项目研究,有效证明了孔系钻削过程监测信号特征变化与孔系加工质量波动存在对应关系,为实现孔系类零部件在线加工质量检测提供了一种新方法。
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数据更新时间:2023-05-31
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