Quantitative, In-Line Spectroscopic Monitoring of Lubricating Oils in Diesel Engines

我们的工业合作伙伴Gastops Ltd是加拿大旋转机械状态监测的全球领导者，特别是风力涡轮机，发电用燃气轮机和航空发动机。与卡尔顿大学合作，该公司正在开发实时状态监测技术，该技术使用在线传感器能够预测润滑油的剩余使用寿命。这是基于对石油吸收和发出的光的实时分析，它可以告诉我们关键添加剂及其降解副产物的浓度。当这些添加剂耗尽时，油将失去其理想的性能。该公司目前使用的原型只能大致检测一种添加剂（一种以PAN分子为代表的抗氧化剂家族）。在这项工作中，我们将与他们合作，将其扩展到第二种重要类型（另一种抗氧化剂家族，以一种名为BHT的分子为代表）。这将需要不同的分析技术和石油降解过程的建模。我们结合理论，计算和实验的方法将导致高保真度的发展，预测传感器和模型的组合为这一目的。这些影响将减少不必要的润滑油更换产生的废油，延长旋转机械的使用寿命，并提高加拿大工业的能源利用效率。

Our industrial partner, Gastops Ltd, is a Canadian world leader in condition monitoring of rotary machinery, notably wind turbines, gas turbines for power generation, and aerospace engines. In collaboration with Carleton University, the company is developing technologies for real-time condition monitoring using on-line sensors capable of predicting the remaining useful life of a lubricating oil. This is based on a real-time analysis of the light absorbed and emitted by the oil, which can tell us about the concentration of key additives and their degradation by-products. When these additives are depleted, the oil will lose its desirable properties. The current prototype the company uses is only capable of approximately detecting one type of additive (a family of antioxidants typified by a molecule called PAN). In this work, we will work with them to extend this to a second important type (another family of antioxidants typified by a molecule called BHT). This will require different analytical techniques and modeling of the oil degradation process. Our combined theoretical, computational and experimental approach will lead to the development of high-fidelity, predictive combination of sensors and models for this purpose. The impacts will be reduced waste oil from unnecessary lubricant changes, longer lives for rotary machinery, and more efficient energy utilization in Canadian industry.