Well-Conditioned Observers for High-Performance, Low-Cost, Sensing Systems

该项目涉及一个分析和开发 创新的传感系统，结合了传统的远程 传感器和信号处理技术， 信号的损坏部分。通常，在诊断系统中， 传感器输出被机器本身损坏， 传感器通常不能放置在信号到达的位置， 被测量的是生成的。例如，在机床中，一些 切削力传感器依赖于应变的测量， 机床的外座圈，其他取决于负载 在刀具转塔的底部测量，还有一些取决于 取决于进给或主轴电机消耗的电流。一 本研究开发了可监测性指数（MI）， 不仅提高了传感器的可靠性和性能， 提供了一种系统地优化设计的方法， 特殊的传感系统。设计过程产生一个简单的 合理的方法来确定最合适的信号， 测量和使用的传感器类型。技术 使用模型来校正损坏的信号属于 这类技术被称为基于模型的估计器。该感测 系统，这是基于MI的，被称为基于模型的传感 (MBS)针对刀具力和主轴轴承实施 监控现有机床及其性能， 与传统的基于模型的估计策略相比。 //

This project deals with the analysis and development of an innovative sensing system that combines conventional remote sensors and signal processing techniques that extract the corrupted portion of signals. Typically, in diagnostic systems the sensor output is corrupted by the machine itself since the sensor cannot be generally placed at the site where the signal to be measured is generated. For example, in machine tools, some cutting force sensors depend upon the measurement of strain in the outer race of the machine tools, others depend upon the load measured at the base of the tool turret, and still others depend on the current consumed by the feed or spindle motor. A monitorability index (MI) is developed in this research which not only improves the sensor reliability and performance, but also provides a means of systematically optimizing the design of a particular sensing system. The design procedure yields a simple rational method to determine the most appropriate signals to measure and the type of transducers to use. The technique of using a model to correct the corrupted signal belongs to the class of techniques known as model-based estimators. This sensing system, which is based on MI and is called Model Based Sensing (MBS) is implemented for tool force and spindle bearing monitoring on existing machine tools and its performance is compared with traditional model-based estimation strategies.*** //