Halenar Igor, Halenarova Lenka, Tanuska Pavol, Vazan Pavel
Institute of Applied Informatics, Automation and Mechatronics, Faculty of Materials Science and Technology in Trnava, Slovak University of Technology in Bratislava, 812 43 Bratislava, Slovakia.
Sensors (Basel). 2024 Dec 31;25(1):180. doi: 10.3390/s25010180.
The core of this publication is the design of a system for evaluating the condition of production equipment and machines by monitoring selected parameters of the production process with an additional sensor subsystem. The main positive of the design is the processing of data from the sensor layer using artificial intelligence (AI) and expert systems (ESs) with the use of edge computing (EC). Sensor information is processed directly at the sensor level on the monitored equipment, and the results of the individual subsystems are stored in the form of triggers in a database for use in the predictive maintenance process. The whole solution includes the design of suitable sensors and of the implementation of the sensor layer, the description of data processing algorithms, the design on the communication infrastructure for the whole system, and tests in the form of experimental operation of the device in laboratory conditions. The solution includes the visualisation of the production system status for the operator using an interactive online map.
本出版物的核心是设计一个系统,通过使用额外的传感器子系统监测生产过程的选定参数,来评估生产设备和机器的状况。该设计的主要优点是利用人工智能(AI)和专家系统(ES)以及边缘计算(EC)对来自传感器层的数据进行处理。传感器信息在被监测设备的传感器层面直接进行处理,各个子系统的结果以触发器的形式存储在数据库中,以供预测性维护过程使用。整个解决方案包括合适传感器的设计和传感器层的实施、数据处理算法的描述、整个系统通信基础设施的设计,以及在实验室条件下以设备实验运行的形式进行测试。该解决方案包括使用交互式在线地图为操作员可视化生产系统状态。