Development of Advanced Condition Monitoring Techniques for Gearboxes and Bearings

齿轮箱和轴承是许多机械系统中使用最广泛的旋转部件，例如直升机，风力涡轮机和车辆。这些旋转部件的可靠和不间断运行对于工程系统的安全性和可用性至关重要。然而，由于高工作量，恶劣的工作条件或不可避免的疲劳，齿轮箱和轴承将随着时间的推移而退化，故障可能会发展。如果不能及早发现故障，设备的健康状况将继续恶化，可能造成严重的经济损失甚至灾难。有效的状态监测技术允许正确安排停机，以防止灾难性故障，从而实现更安全的操作和更高的维护成本降低。然而，为了开发有效的状态监测技术，特别是对于在变化的速度和/或负载条件下工作的齿轮箱和轴承，许多挑战还有待解决。 该研究计划旨在开发齿轮箱和轴承的先进状态监测技术，以提高系统的安全性和可用性，并降低维护成本。研究将实现三个目标：（1）开发齿轮箱和轴承的先进动态模型，以揭示齿轮和轴承的退化机理和故障特征，（2）开发在时变操作条件下工作的齿轮箱和轴承的有效早期故障检测和诊断技术，（3）综合物理模型和状态监测数据，开发有效的剩余使用寿命估算技术。 拟议的研究将有助于状态监测的科学创新和方法进步，并开发有效的故障检测，诊断和预测齿轮箱和轴承系统的模型，方法和工具。所产生的结果在现代工程系统的设计和操作中具有很好的应用潜力，如直升机，风力涡轮机和车辆。这项研究的结果可以应用在工业环境中，使加拿大工业直接受益。根据该计划培训的高素质人员将获得必要的理论和实践专业知识，以促进和推进加拿大的上级机器状态监测。

Gearboxes and bearings are the most widely used rotating components in many mechanical systems such as helicopters, wind turbines, and vehicles. Reliable and uninterrupted operation of these rotating components is crucial for the safety and availability of engineering systems. However, due to high workload, harsh operating conditions, or inevitable fatigue, gearboxes and bearings will degrade with time and faults may develop. If the faults cannot be detected early, the equipment's health will continue to degrade, perhaps causing heavy economic loss or even catastrophe. Effective condition monitoring techniques allow for properly scheduled shutdowns to prevent catastrophic failure and consequently result in a safer operation and higher maintenance cost reduction. However, many challenges have yet to be addressed in order to develop effective condition monitoring techniques especially for gearboxes and bearings working under varying speed and/or load conditions. This research program aims to develop advanced condition monitoring techniques for gearboxes and bearings in order to increase system safety and availability and reduce maintenance costs. Research will be conducted to achieve three objectives: (1) development of advanced dynamic models for gearboxes and bearings to reveal gears' and bearings' degradation mechanism and fault characteristics, (2) development of effective early fault detection and diagnosis techniques for gearboxes and bearings working under time-varying operating conditions, and (3) development of effective remaining useful life estimation techniques by integrating physical models and condition monitoring data. The proposed research will contribute to the scientific innovation and methodological advancement of condition monitoring, and develop models, methods, and tools for effective fault detection, diagnosis, and prediction of gearbox and bearing systems. The results to be generated have excellent potential for applications in the design and operation of modern engineering systems such as helicopters, wind turbines, and vehicles. The results of this research can be applied in industrial settings to benefit Canadian industries directly. Highly qualified personnel trained under this program will gain the theoretical and practical expertise necessary to promote and advance superior machine condition monitoring in Canada.