Condition monitoring of lubricating oils in diesel engines

柴油发动机润滑油的状态监测

• 批准号: 515552-2017
• 负责人: Miller, Ronald
• 金额: $ 4.57万
• 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: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=691153
• 关键词: Condition; monitoring; lubricating; oils; diesel

Our industrial partner, Gastops Ltd, is a Canadian world leader in condition monitoring of rotating machinery. In collaboration with Carleton University, the company is now studying physical and chemical mechanisms of degradation in lubricants, potentially enabling developments of technologies for real-time condition monitoring using on-line sensors capable of predicting the remaining useful life of a lubricating oil. This research requires two fundamental scientific contributions. The first is a means to calibrate and characterize the signals that an on-line sensor will produce. This entails careful, controlled oil degradation experiments and accurate characterizations of the resulting by-products using well-established lab-based tools. The second requirement is accurate modeling of the oil degradation processes. Once the sensor is calibrated to accurately identify the types and concentrations of key degradation by-products, it can only predict the remaining useful life of lubricating oil if a model exists to extrapolate lubricating oil conditions based on the current state of the oil and the expected operating conditions of the machinery. Our combined theoretical, computational and experimental approach will lead to the development of a chemical kinetics model with this predictive capability.

我们的工业合作伙伴Gastops Ltd是加拿大旋转机械状态监测领域的全球领导者。通过与卡尔顿大学的合作，该公司目前正在研究润滑油降解的物理和化学机制，从而有可能开发使用能够预测润滑油剩余使用寿命的在线传感器进行实时状态监测的技术。这项研究需要两个基本的科学贡献。第一种是校准和表征在线传感器将产生的信号的手段。这需要仔细，受控的石油降解实验和使用完善的实验室工具对所得副产品的准确表征。第二个要求是油降解过程的精确建模。一旦传感器被校准以准确识别关键降解副产物的类型和浓度，如果存在基于油的当前状态和机器的预期操作条件来推断润滑油条件的模型，则它只能预测润滑油的剩余使用寿命。我们的理论，计算和实验相结合的方法将导致发展的化学动力学模型，这种预测能力。