Development of an intelligent gas turbine engine health monitoring and degradation prediction system

智能燃气轮机健康监测和退化预测系统的开发

• 批准号: 508307-2016
• 负责人: Liu, Jie
• 金额: $ 2.91万
• 依托单位: Carleton University
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=657758
• 关键词: Development; intelligent; gas; turbine; engine

Gas turbine engines (GTE) have been widely used in civilian and defense sectors for generating energy and are critical to the operation of many industrial plants, aircrafts, and heavy vehicles. Any unexpected engine failure could be costly and potentially disastrous. Monitoring and predicting the GTE's health condition is therefore critically important and necessary in industries for gaining comprehensive knowledge of the engine system, improving operation reliability, and reducing maintenance cost. Because of their tremendous importance, extensive research has been conducted over the past decades in GTE health condition monitoring and prediction as a means to provide advance warning of failure, enable forecasted maintenance, and improve system qualification. Although a variety of methods have been proposed in the literature, reliable assessment of GTE current and future health conditions still remains a challenging task in both research and industrial applications due to the inherent complexities in GTE structures and time-varying operating conditions. Partnering with an Ottawa-based company, Life Prediction Technologies (LPTi), the proposed research is aimed at developing an intelligent GTE health monitoring and degradation prediction system to address this challenge. Our ultimate goal is to develop more reliable techniques and tools for GTE health condition monitoring and prediction to help Canadian companies improve asset utilization, reduce the total cost of GTE ownership, and remain competitive in the global market.**

燃气涡轮发动机 (GTE) 已广泛应用于民用和国防领域，用于发电，对许多工厂、飞机和重型车辆的运行至关重要。任何意外的发动机故障都可能造成高昂的代价并可能造成灾难性的后果。因此，监测和预测 GTE 的健康状况对于行业中获得发动机系统的全面了解、提高运行可靠性和降低维护成本至关重要且必要。由于其极其重要，过去几十年来，人们在 GTE 健康状况监测和预测方面进行了广泛的研究，作为提供故障预警、实现预测维护和提高系统资格的手段。尽管文献中提出了多种方法，但由于 GTE 结构固有的复杂性和随时间变化的操作条件，对 GTE 当前和未来健康状况的可靠评估在研究和工业应用中仍然是一项具有挑战性的任务。拟议的研究与渥太华的 Life Prediction Technologies (LPTi) 公司合作，旨在开发智能 GTE 健康监测和退化预测系统来应对这一挑战。我们的最终目标是开发更可靠的 GTE 健康状况监测和预测技术和工具，帮助加拿大公司提高资产利用率，降低 GTE 拥有总成本，并在全球市场上保持竞争力。**