DEVELOPMENT OF A WEB APPLICATION FOR DATA ANALYSIS AND VISUALIZATION TO ENSURE THE SAFETY OF TECHNOLOGICAL PROCESSES

I. Uvaliyeva, S. Rustamov, S. Belginova, Zh. Rakhmetullina
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Abstract

Modern technologies have developed quite well lately, and in addition to the banal data collection and processing, modern algorithms are able to predict the behavior of equipment and prevent the occurrence of malfunctions and failures in advance and take actions to reduce the likelihood of an accident and warn the relevant employees. Within the framework of this study, the authors proposed the development of a web-application for the analysis and visualization of data from UK-TPP to ensure the safety of technological processes. Ust-Kamenogorsk TPP is a regional thermal power plant, heat and electricity generation covers 80% of the load of the housing and communal sector of the city and industrial enterprises. The TPP is part of the unified energy system of Kazakhstan. The application being developed has a web interface that will display and visualize data from the main sensors and instruments of the UK TPP, as well as prevent equipment malfunctions and analyze the behavior of sensors using machine learning. Node.js was chosen as the main software platform used, built on the java script programming language, using additional modules that expand the capabilities of this programming language, written in c ++, which speeds up working with data arrays, receiving, and sending them.
开发用于数据分析和可视化的网络应用程序,确保技术流程的安全
现代技术近来得到了长足的发展,除了普通的数据收集和处理外,现代算法还能预测设备的行为,提前预防故障和失灵的发生,并采取行动降低事故发生的可能性,向相关员工发出警告。在这项研究的框架内,作者建议开发一个网络应用程序,用于分析和可视化来自英国-贸易伙伴关系伙伴关系项目的数据,以确保技术流程的安全。乌斯季卡缅诺戈尔斯克热电厂是一家地区性热电厂,其供热和发电量占城市住房和社区以及工业企业负荷的 80%。该热电厂是哈萨克斯坦统一能源系统的一部分。正在开发的应用程序有一个网络界面,可以显示和可视化英国 TPP 主要传感器和仪器的数据,还可以防止设备故障,并利用机器学习分析传感器的行为。Node.js 被选为主要的软件平台,它建立在 java script 编程语言的基础上,使用附加模块扩展了这一编程语言的功能,由 c ++ 编写,可加快处理数据数组、接收和发送数据的速度。
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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