MEMS for diagnostic and health monitoring of complex systems

拟议的研究计划旨在开发方法，使之能够开发复杂系统的模型，用于确定其状态和条件。复杂的系统从发动机到植物，从细胞到生物。这就是这项拟议研究的基本原理。因此，需要确定系统的一些具体特征，并根据调查结果制定能够开发模型的方法。这项研究的灵感来自谷歌在自动驾驶汽车上进行的沉默实验。申请人和他最后毕业的博士生最近进行的一个项目产生了非常有趣的结果，这可能与无人驾驶汽车方法有关。该项目的重点是对车辆和受损驾驶员进行建模。因此，这种情况下的建模将针对在交通中行驶的车辆的条件。自动驾驶系统是一种常规车辆，它配备了一套传感器和关于要行驶的道路的预定信息(地图)、计算能力以及执行纠正行动的执行器，以避免任何类型的碰撞。无人驾驶汽车可能需要考虑减少传感器集，以便这样的汽车可能变得负担得起。然而，需要提供所需的信息，并将在该项目中考虑其他手段。因此，计划从相邻车辆收集关于预览道路和静止或移动障碍物的信息。系统的模型会有所不同，但性能需要保持在安全条件下。申请者计划探讨导致长期研究计划的某些方面。这是一种可以在极端恶劣的环境中工作的传感器的开发，这将使涡轮发动机的寿命能够实时预测。这涉及到新型传感器的开发研究。该计划将在短期内培养5名HQP-2博士和2名MASC学生，并将在接下来的5年内参与该计划。学生将在不同的项目上工作，但考虑到申请者多年前采用的良好研究实践，他们将(在申请者的监督/共同监督下与项目中的其他学生)互动，并将一起工作。他们将获得在某种程度上几乎没有的培训：具有机械和电气工程技能的工程师，并有能力对产品中的概念和想法进行建模和整合。这项研究的结果很容易预测。车祸每年造成100多万人死亡，5000多万人受伤。自动驾驶汽车已经被证明在(未披露的)使用条件下是极其安全的。由于谷歌没有提供这类车辆的细节，而不是所有的汽车都是经过改装的常规车辆，因此需要在这一领域进行学术研究，因为这种应用肯定具有巨大的潜力。拟议的研究从低成本仪器的概念开始。一个准确的模型将能够为合适的传感器集提供解决方案，并从相邻的车辆收集信息。另一方面，基于未开发现象的传感器的开发代表了该行业感兴趣的主题。在这两个主题中工作的学生将获得非常有价值的知识和技能，这将使他们真正同意他们的雇主。

The proposed research program is targeting the development of methodologies that will enable to develop models of complex systems that are used to establish their state and condition. Complex systems range from engines to plants and from cells to beings. This is the rationale of the proposed research. Thus, some specific features of the systems need to be defined and based on the findings a methodology that enables development of a model will be formulated. The research has been inspired by the so much kept silent experiment carried out by Google on self-driving vehicles. A recent project performed by the applicant and his last graduated PhD student yield very interesting output that could be linked to the driver-less vehicle approach. The project focused on modeling vehicle and impaired driver. Hence, the modeling in this case will target the condition of the vehicle in the context of traveling through the traffic. A self-driving system is a regular vehicle that is equipped with a set of sensors and pre-determined information (the map) about the road to be traveled, computation capabilities as well as actuators to perform the corrective action to avoid collision of any kind. The driver-less vehicle may need to consider reduced set of sensors such that such car may become affordable. However, the required information needs to be made available and other means will be considered within this project. Thus, the information about the previewed road and the static or moving obstacles is planned to be collected form the adjacent vehicles. The model of the system will be different but the performances need to remain within the safety conditions. The applicant plans to approach certain aspects that lead to the long term research plan. This is the development of sensors that could operate in extremely harsh environment and that will enable real time prediction of the life of turbine engines. This involves the research on the development of new type of sensors. The program will have as a plan in short term to train five HQP – 2 PhD and 2 MASc students will be involved in the program during the following five years. The students will work on different projects but given the good research practice adopted by the applicant many years ago, they will be interacting (with the other students already in the program under the supervision/co-supervision of the applicant) and will be working together. They will acquire training that is to some extent scarcely available: engineers with skills in both mechanical and electrical engineering and with the capability to model and integrate concepts and ideas in products. The results of this research are easily predictable. Car accidents make more than 1 million victims while more than 50 million people are injured every year. Self-driving cars have proved to be extremely safe for the (un-revealed) conditions that they have been used. As there is no detail provided by Google for this type of vehicle rather than all cars are regular vehicles that have been modified, academic research is needed in this area as the applications definitely have huge potential. The proposed research starts with the concept of low cost instrumentation. An accurate model will be able to provide solutions for suitable set of sensors and collect information from adjacent vehicles. On another hand, development of sensors based on unexploited phenomena represents a subject of interest to the industry. The students who will acquire their training while working in the two topics will gain extremely valuable knowledge and skills that will make them real assents for their employers.