Magnetic Actuators for Non-Destructive Evaluation (NDE) of Rotating Machinery for Health Diagnostics and Prognostics

喷气发动机在3万英尺高空发生故障或在高峰运行时间关闭发电厂，无论是从人力还是经济角度来看，都是代价高昂的。在监测和诊断旋转机械相当严重的问题方面，已有完善的程序，但在开发检测机器状态细微变化的技术以改进诊断和制定确定剩余使用寿命的预测程序方面，进展甚微。提出的项目使用一种新颖的应用主动磁轴承（AMBs）作为执行器，将各种已知的力输入应用于旋转转子，以便在线监测和评估这些输入产生的响应信号。所提出的程序允许将多种形式的力输入信号应用于旋转结构。这种方法的一个重要方面是，AMB(s)将与传统的支撑轴承一起用于中轴位置。通过这种方式，这里开发的诊断/预后程序适用于任何可以用单个AMB执行器设计或改装的通用旋转机器，并且仍然支持原始机械轴承。在旋转机械的状态监测中，检测各种已知输入和结果输出的能力是前所未有的，所提出的技术对于提高航空航天、发电和石化行业转子轴承系统的运行安全性和降低维护成本具有广泛的意义。此外，拟议程序的本质将通过允许一种自检方法最终促进机械自我诊断和预后。

AbstractA jet engine failure at 30,000 feet or a power plant shutdown during peak operational hours can be costly from a human as well as financial standpoint. Well-established procedures exist to monitor and diagnosis fairly severe problems with rotating machinery but little progress has been made in developing techniques to detect subtle changes in machine condition for both improved diagnostics, and to develop prognostic procedures for determining remaining service life. The proposed project uses a novel application of Active Magnetic Bearings (AMBs) as actuators for applying a variety of known force inputs to a spinning rotor in order to monitor and evaluate response signals resulting from these inputs on-line. The proposed procedure allows for multiple forms of force input signals to be applied to a rotating structure. An important aspect of this approach is that the AMB(s) will be used in mid-shaft locations in conjunction with conventional support bearings. In this manner, the diagnostic/prognostic procedures are developed here for use on any general rotating machine that can be designed or retrofitted with a single AMB actuator and still be supported in the original mechanical bearings. The ability to examine a variety of known inputs and resulting outputs for condition monitoring in rotating machinery is unprecedented and the proposed technique has broad implications for improving operational safety and reducing maintenance costs in rotor-bearing systems in the aerospace, power generation, and petrochemical industries. In addition, the very nature of the proposed procedure will ultimately facilitate machinery self-diagnostics and prognostics by allowing a method for self-testing.