Development of a methodology for analyzing big data in order to predict changes in the phases of the life cycle of elements of engineering equipment of buildings and structures

IF 0.1 Q4 CONSTRUCTION & BUILDING TECHNOLOGY Russian Journal of Building Construction and Architecture Pub Date : 2023-06-27 DOI:10.29039/2308-0191-2023-11-2-8-8
Andrei Sigitov
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Abstract

Introduction. Big data analysis technologies are the basis for the development of the information society. Storage and processing of "Big data" requires significant expenditures of computing power, expensive data storage systems. In the field of construction, the main source of "Big data" is the technology of "Smart home" and "Smart city". The development of a methodology for analyzing big data is aimed at reducing the cost of operating elements of engineering equipment, timely maintenance, with the aim of trouble-free operation. The presented analysis technique can be extended to any piece of equipment that collects data on its operation and condition. Materials and methods. Used data from open sources. The data for analysis were obtained from the management company Yuzhny LLC. The subject of the study is an electric ball valve. Preparation and visualization of information was carried out using Microsoft Office Excel. Results. The developed methodology for analyzing big data in order to predict changes in the phases of the life cycle of elements of engineering equipment of buildings and structures, according to the results of a preliminary analysis, showed its efficiency. High performance in the task of identifying defective products was demonstrated by the method using Shewhart's Control Charts. The use of cluster and qualimetric analysis methods in scenarios unusual for them made it possible to predict the change in the life cycle phases with an accuracy acceptable for research problems. Conclusions. The analysis technique is based on the use of modern algorithms. Algorithms themselves are often used to process big data. The scientific novelty lies in the approach to analysis, in which, unlike classical schemes, where cluster and qualimetric methods of analysis are used to find the best management solution, in this work, the purpose of the analysis is to search for equipment items close to a change in the phase of the life cycle.
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开发一种分析大数据的方法,以预测建筑和结构工程设备元素生命周期各阶段的变化
介绍。大数据分析技术是信息社会发展的基础。“大数据”的存储和处理需要大量的计算能力支出和昂贵的数据存储系统。在建筑领域,“大数据”的主要来源是“智能家居”和“智慧城市”的技术。大数据分析方法的发展旨在降低工程设备运行要素的成本,及时维护,以无故障运行为目标。所提出的分析技术可以扩展到任何一台设备,收集其运行和状态的数据。材料和方法。使用来自开放来源的数据。分析数据来自管理公司Yuzhny LLC。研究的对象是电动球阀。使用Microsoft Office Excel进行信息的准备和可视化。结果。根据初步分析的结果,用于分析大数据以预测建筑和结构工程设备元素生命周期各阶段变化的开发方法显示了其效率。通过使用休哈特控制图的方法,证明了该方法在识别缺陷产品任务中的高性能。在不寻常的情况下使用聚类和定性分析方法,可以以研究问题可接受的精度预测生命周期阶段的变化。结论。分析技术是基于现代算法的使用。算法本身通常用于处理大数据。科学的新颖性在于分析的方法,其中,不像经典的方案,其中聚类和定性的分析方法被用来寻找最佳的管理解决方案,在这项工作中,分析的目的是寻找接近生命周期阶段变化的设备项目。
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Russian Journal of Building Construction and Architecture
Russian Journal of Building Construction and Architecture CONSTRUCTION & BUILDING TECHNOLOGY-
自引率
50.00%
发文量
28
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