学习传感器数据融合,一个实用的方法

Q4 Engineering
Maik Rosenberger, Mirco Andy Eilhauer, Raik Illmann, Martin Richter, Andrei Golomoz, Gunther Notni
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引用次数: 0

摘要

工业测量任务往往不能单独使用简单的传感器系统来解决。为此,开发了许多现场总线和协议,试图实现各种传感器和执行器的强大联网。从长远来看,工业4.0和物联网背景下的技术支持这些趋势。就像温度、压力、力等过程测量变量一样,图像处理系统也已进入现代过程控制和监测系统。作为计量和IT培训的一部分,学生必须了解这些由典型过程测量变量和基于图像的变量组成的复杂物联网系统,并明智地将它们用于测量和自动化任务。为此,已经开发了特殊的电子设备,将过程测量技术中的选定传感器与图像传感器相结合。这为传感器数据融合主题提供了一个清晰和以实践为导向的练习机会,既可以用于图像处理教学,如通过旋转速率传感器和相机系统的传感器融合进行旋转位置校正,也可以用于过程测量技术教学,如从湿度和温度计算露点。选择将系统划分为用于记录传感器并传输到评估PC的微型计算机架构,以及自由选择可能的软件工具来计算传感器信息,从而为系统开发不同的学习场景。本出版物还介绍了系统的架构,与评估系统的连接以及用于教学的传感器数据融合的初步应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Learning sensor data fusion, an practical approach
Industrial measurement tasks often cannot be solved using simple sensor systems alone. To this end, the development of numerous field buses and protocols has attempted to achieve strong networking of various sensors and actuators. Technologies in the context of Industry 4.0 and IoT support these trends in the long term. Just like process measurement variables such as temperature, pressure, force, etc., image processing systems have also found their way into modern systems for process control and monitoring. Understanding these complex IoT systems consisting of typical process measurement variables and image-based variables and using them sensibly for measurement and automation tasks must be taught to students as part of their metrology and IT training. For this purpose, special electronics have been developed that combine selected sensors from process measurement technology with an image sensor. This offers the opportunity to develop a clear and practice-oriented exercise for sensor data fusion topics both for teaching in image processing, such as rotational position correction through sensor fusion of a rotation rate sensor and camera system, and for teaching in process measurement technology, such as calculating the dew point from humidity and temperature. The chosen division of the system into microcomputer architecture for recording the sensors and transmission to an evaluation PC as well as the free selection of possible software tools for the calculation of the sensor information among each other allows different learning scenarios to be developed for the system. This publication also presents the architecture of the system, the connection to an evaluation system and an initial application for sensor data fusion for use in teaching.
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来源期刊
Measurement Sensors
Measurement Sensors Engineering-Industrial and Manufacturing Engineering
CiteScore
3.10
自引率
0.00%
发文量
184
审稿时长
56 days
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