Dynamic Calibration of a Smart Machining System Using Robust Non-Intrusive Sensors

本研究的主要目的是研究智能机床的一些使能技术：1。基于非侵入式传感器的切削力模型在线标定；2 .基于切削能量分析的刀具状态监测；3 .颤振预测与预防；4 .机械加工工艺方案表示的信息技术。新型廉价的非侵入式传感器。该研究方法基于传感器数据和数学模型的结合，以及独特的在线校准方法，以及基于网络的机床和工艺计划数据表示方法。以颤振分析为目的的机械动力学实验表征将与时域仿真相结合，选择无颤振加工条件。在数控铣床试验台设施上使用开放式架构控制器允许通过传感器数据输入不断更新过程的数学模型。将与工业伙伴合作进行广泛的实验研究，以测试该方法对各种切削条件、切削工具和工件材料的适用性。如果成功，本研究将产生以下广泛影响：通过对机床加工能力的自我认知，大大提高了机床的可靠性；2 .对工艺能力的自我认知将使特定机器与特定加工操作的要求相匹配。可以选择加工策略和切削条件（速度、进给和切削深度）来适当地反映机床的当前能力。该项目还将支持国家标准与技术研究所的智能机器计划，并与集成制造计划的目标相一致，集成制造计划是一个由工业、学术和政府合作伙伴组成的公共/私人财团，旨在加强国家的制造业社区。

The primary objective of this research is to investigate a number of enabling technologies for a smart machine tool: 1. on-line calibration of cutting force models using non-intrusive sensors, 2. tool condition monitoring based on cutting energy analysis, 3. chatter prediction and prevention, 4. information technology for representation of machining process plans and 5. novel inexpensive non-intrusive sensors. The research approach is based on combining sensor data and mathematical models along with unique on-line calibration methods, and a web-based method for data representation of machine tools and process plans. Experimental characterization of machine dynamics for the purpose of chatter analysis will be combined with time domain simulation to choose chatter-free machining conditions. The use of an Open Architecture Controller on a numerically controlled milling machine testbed facility allows mathematical models of the process to be continuously updated by sensor data input. Extensive experimental studies will be performed in collaboration with industrial partners to test the applicability of the method to a wide variety of cutting conditions, cutting tools and workpiece materials.If successful, this research will have the following broad impacts: 1. greatly improve the reliability of machine tools by self-knowledge of their process capabilities, 2. Self-knowledge of process capabilities will allow matching of specific machines with the requirements of a particular machining operation, 3. Machining strategies and cutting conditions (speeds, feeds and cutting depths) can be chosen to appropriately reflect the current capabilities of the machine tool. This project will also support the Smart Machine Initiative of the National Institute of Standards and Technology and is consistent with the goals of the Integrated Manufacturing Initiative, a public/private consortium of industry, academic, and government partners designed to strengthen the nation's manufacturing community.