KEYWORDS: Sensors, Microwave radiation, Finite element methods, Sensor performance, Safety, Data acquisition, Distance measurement, 3D modeling, Structural health monitoring, Denoising
Gas turbine engine manufacturers are in continuous strive to improve the durability and the technology behind engine development to help monitor engine health and performance. Such technologies are confined to employing highly specialized sensors within the engine compartment. The role of the sensors is to screen and track the structural response of the engine components and in particular the rotor disk due to its venerability to endure failure since it is subject to complex and harsh loading conditions. Detecting unexpected or excessive blade vibration before failure is critical to ensure safety and to achieve projected component life. Nondestructive Evaluation has been the traditional method of detection in addition to relying exclusively on visual inspections as well as other means. These methods require time and cost and do not provide accurate feedback on the health when the engine is in operation. At NASA Glenn Research Center, efforts are undergoing to develop, and test validates microwave-based blade tip timing sensors in support of these concerns and to investigate their application for propulsion health monitoring under the Transformational Tools and Technologies Project (TTTP). A set of prototype sensors is used to assess their ability and applicability in making blade tip clearance measurements in an attempt to extract the blade tip timing from the acquired raw data. The sensors are non-contact type and microwavebased technology. The study covers an experimental task to define the optimum set-up of these sensors, determine their sensitivity in making blade tip deflection measurements and validate their performance against realistic geometries in a spin rig. It also includes finite element analysis base calculations to compare with the experimental data. Data pertaining to the findings obtained from the testing as well as the analytical results are presented and discussed. This work is an extension of a prior combined experimental and computational study that is available in reference [1].
Gas turbine engine makers are always striving to implement newer technologies to help monitor the engine health and performance. Among these technologies is the employment of highly specialized sensors within the engine compartment. The sensors are to screen response of components such as rotor disk blades which are subjects to complex loading conditions and that includes combined thermal and mechanical loads. Detecting unexpected or excessive blade Vibration before failure is critical to ensure safety and to achieve expected apparatus life. Traditional detection methods have relied solely on component inspection during service or on the use of gage telemetry systems as well as other means of non-destructive evaluation. These methods require time and cost and do not provided an accurate feedback of the health when the engine is in operation. At NASA Glenn Research Center, an effort is underway to develop and test validate microwave based blade tip timing sensors in support of the latter concerns and for the purpose of investigating their application for propulsion health monitoring under the Transformational Tools and Technologies Project. This process involves working with prototype sensors to determine their applicability and assess their ability in making blade tip clearance measurements along with further refining a methodology required to extract deflection measurements from the raw data acquired from the sensors. The efforts focus specifically on the use and implementation of microwave based tip-timing sensors that are intended to be used for non-contact stress measurement application. The work includes an experimental task to define the optimum set-up of these sensors, determine their sensitivity in making blade tip deflection measurements and validate their performance against realistic geometries in a spin rig. This also includes analytical calculations to compare to the experimental results. Data pertaining to the findings obtained from the testing as well as the supportive analytical results are presented and discussed.
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