CA Mecatrónica, Facultad de Ingeniería, Campus San Juan del Río, Universidad Autónoma de Querétaro, Av. Río Moctezuma 249, San Juan del Río, Querétaro 76807, Mexico.
Departamento de Ingeniería Eléctrica, Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022 Valencia, Spain.
Sensors (Basel). 2022 Aug 14;22(16):6075. doi: 10.3390/s22166075.
The monitoring of machine conditions is very important from the viewpoints of productivity, economic benefits, and maintenance. Several techniques have been proposed in which sensors are the key to providing relevant information to verify the system. Recently, the smart sensor concept is common, in which the sensors are integrated with a data processing unit executing dedicated algorithms used to generate meaningful information about the system in situ. Additionally, infrared thermography has gained relevance in monitoring processes, since the new infrared cameras have more resolution, smaller dimensions, reliability, functionality, and lower costs. These units were firstly used as secondary elements in the condition monitoring of machines, but thanks to modern techniques for data processing, the infrared sensors can be used to give a first, or even a direct, diagnosis in a nonintrusive way in industrial applications. Therefore, in this manuscript, the structure and development of an infrared-thermography-based smart sensor for diagnosing faults in the elements associated with induction motors, such as rolling bearings and the gearbox, is described. The smart sensor structure includes five main parts: an infrared primary sensor, a preprocessing module, an image processing module, classification of faults, and a user interface. The infrared primary sensor considers a low-cost micro thermal camera for acquiring the thermal images. The processing modules and the classification module implement the data processing algorithms into digital development boards, enabling smart system characteristics. Finally, the interface module allows the final users to require the smart sensor to perform processing actions and data visualization, with the additional feature that the diagnosis report can be provided by the system. The smart sensor is validated in a real experimental test bench, demonstrating its capabilities in different case studies.
从生产力、经济效益和维护的角度来看，监测机器状况非常重要。已经提出了几种技术，其中传感器是提供相关信息以验证系统的关键。最近，智能传感器的概念很常见，其中传感器与数据处理单元集成，执行专用算法，用于就地生成有关系统的有意义信息。此外，红外热成像在监测过程中变得越来越重要，因为新型红外摄像机具有更高的分辨率、更小的尺寸、更高的可靠性、更多的功能和更低的成本。这些单元最初被用作机器状态监测的辅助元件，但由于现代数据处理技术的应用，红外传感器可以用于在工业应用中以非侵入方式进行初步诊断，甚至直接诊断。因此，在本文中，描述了一种基于红外热成像的智能传感器的结构和发展，该智能传感器用于诊断与感应电动机相关的元件（如滚动轴承和变速箱）的故障。智能传感器结构包括五个主要部分：红外初级传感器、预处理模块、图像处理模块、故障分类和用户界面。红外初级传感器考虑使用低成本微热像仪来获取热图像。处理模块和分类模块将数据处理算法实现到数字开发板中，从而实现智能系统的特点。最后，接口模块允许最终用户要求智能传感器执行处理操作和数据可视化，并且系统还可以提供诊断报告。智能传感器在真实的实验测试台上进行了验证，展示了其在不同案例研究中的能力。
