Development of a Diagnosis Technique for Air Conditioning Systems

Niklas Huhs, J. Bartelt, O. Simanski, O. Hagendorf
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Abstract

The overall goal of this project is the development of a system to diagnose the efficiency of air conditioning systems by using modern IoT services and techniques of artificial intelligence. By finding errors in air conditioning systems, the involved company “Dr. Diestel GmbH” is able to offer optimization of the systems with low investment techniques to their customers. The process of diagnosis starts with the modelling of the investigated system and determination of measuring points. Sensors using the LoRaWAN technology are placed at these positions to measure and upload the data to the cloud. Different cloud services process the data to determine ways of optimization. To simplify and centralize the management of the used devices an application is developed, that will handle the registering of the devices in the cloud services and give an overview of a system and its measuring points. By comparing different cloud services and application frameworks, it was possible to create an easy-to-use and reliable system that handles the data flow and processing from the sensor to the diagnosis tool and guides the technician in placing and managing the sensors on site.
空调系统诊断技术的发展
该项目的总体目标是开发一个系统,通过使用现代物联网服务和人工智能技术来诊断空调系统的效率。通过发现空调系统中的错误,参与的公司“Dr. Diestel GmbH”能够以低投资技术为客户提供系统优化。诊断过程从所研究系统的建模和测量点的确定开始。使用LoRaWAN技术的传感器被放置在这些位置,以测量并将数据上传到云端。不同的云服务处理数据以确定优化方式。为了简化和集中管理使用的设备,开发了一个应用程序,该应用程序将处理云服务中设备的注册,并给出系统及其测量点的概述。通过比较不同的云服务和应用程序框架,可以创建一个易于使用且可靠的系统,该系统可以处理从传感器到诊断工具的数据流和处理,并指导技术人员在现场放置和管理传感器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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