SBIR Phase II: Minimal Sensor Signal Processing for Turbine Engine Health Monitoring

SBIR 第二阶段：用于涡轮发动机健康监测的最小传感器信号处理

• 批准号: 0216021
• 负责人: Carole Teolis
• 金额: $ 50万
• 依托单位: Techno-Sciences, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-09-15 至 2005-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0216021&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Minimal; Sensor

This Small Business Innovative Research (SBIR)Phase II project will develop full waveform models and minimal sensor algorithms for the General Dynamics - Advanced Technology Systems (GDATS) eddy current sensor (ECS). These algorithms will enable the practical real-time high performance health monitoring for turbine engines. Current processing techniques could require four or more sensors; however, these approaches do not make use of all the information made available by the ESC. Using the full ECS signature, it is possible, in theory, to estimate integral vibration frequency, phase and amplitude using only a single sensor. The reduction of the number of sensors required in each engine stage could potentially save millions of dollars over the life of the engine.There are no systems commercially available today for continuous health monitoring of gas turbine engines. Once in use, this system will allow pilots to react immediately to critical engine health problems thus avoiding potentially catastrophic engine failures and loss of lives. The minimal sensor algorithms for continuous health monitoring have a large market spanning the aviation industry, as well as the rapidly expanding power industry.

该小型企业创新研究（SBIR）第二阶段项目将为通用动力-先进技术系统（GDATS）涡流传感器（ECS）开发全波形模型和最小传感器算法。 这些算法将使实用的实时高性能健康监测的涡轮机发动机。 目前的处理技术可能需要四个或更多个传感器;然而，这些方法并没有利用ESC提供的所有信息。 使用完整的ECS签名，理论上可以仅使用单个传感器来估计积分振动频率、相位和振幅。 减少每个发动机级中所需的传感器数量可能在发动机的寿命期间节省数百万美元。目前还没有商业上可用于燃气涡轮机发动机的连续健康监测的系统。 一旦投入使用，该系统将使飞行员能够立即对关键的发动机健康问题做出反应，从而避免潜在的灾难性发动机故障和生命损失。 用于连续健康监测的最小传感器算法在航空业以及快速发展的电力行业拥有巨大的市场。