Research Initiation: Adaptive Compensation of In-Process Sensors

本研究启动提案中提出的研究问题 是开发一种校正滤波器的设计方法， 将承认和补偿工作的影响， 环境对传感器动态特性的影响。 显著 测量的准确性和可靠性的改进可以 使用这些自调整传感器可以改善 现有生产系统的性能。 这种方法可能是 能够提高实施高性能的可行性 控制、监测和诊断所需的制造系统 未来的工厂。 自校正传感器设计的系统方法 制造系统将试图推进过程中的计量 通过整合现代工程的两个重要元素。 这些 主要内容有：（1）对安装在特定环境中的传感器进行建模， 机床作为多自由度系统的部件。 基于第一原理的衍生模型将封装 关于传感器、机床和相关设备的先验知识 制造过程;（2）基于时间序列的在线 这些模型的实时参数的识别 随机干扰的存在。 本研究的目标是实现一个原型的纠正 滤波器能够跟踪和补偿的影响 环境对典型力和力矩动态性能的影响 传感器. 该过滤器将被构建为高速， 多处理机系统

The research issue addressed in this research initiation proposal is to develop a design methodology of corrective filters which would recognize and compensate the impact of the working environment on the dynamic characteristics of sensors. Significant improvements in the accuracy and reliability of measurements may be possible with these self-tuning sensors to improve the performance of existing production systems. This approach may be able to improve the feasibility of implementing high performance control, monitoring and diagnosis of manufacturing systems needed for the factories of the future. The systematic approach to the design of self-tuning sensors for manufacturing systems will attempt to advance in-process metrology by integrating two important elements of modern engineering. These elements are: (1) The modeling of sensors installed on particular machine tools as components of multi-degree-of-freedom systems. The derived models, based on first principles, will encapsulate the a priori knowledge about the sensors, machines tools and relevant manufacturing processes; and (2) the time series based, on-line identification of real-time parameters of these models in the presence of stochastic disturbances. The goal of this research is to implement a prototype corrective filter capable of tracking and compensating the impact of the environment on the dynamic performance of typical force and torque sensors. This filter will be built as a high speed, multi-processor system.