Study of the internal environment quality monitoring system for a laboratory model of a mining separator at key sensitive points of operation and process control using artificial intelligence

• Autorzy: Romańska Anna , Dudzik Marek , Progorowicz Jakub , Kuc Sabina , Kopała Maciej , Pyznar Mateusz

Identyfikatory

DOI

10.37105/iboa.241

• Języki publikacji: EN

Abstrakty

EN

Modeling the quality of the indoor environment in buildings using neural networks, as an element supporting automatic process control, has become extremely popular nowadays. By analogy, attempts are being made to use the experience gained in construction and implement it in industry. The publication proposes a method of modeling feedforward neural networks, thanks to which it is possible to obtain the most efficient network with one hidden layer in terms of the given quality criterion. This network was implemented in the control system of the mining separator operation as part of pilot studies. The research included testing a laboratory model of the separator placed in a sea container modified for the separator function, in which modern automation technologies and monitoring of environmental parameters were integrated. Among others, time, outside temperature, set temperature, temperature error and controller output were measured. The measurements were taken at the points of installation of devices sensitive to the working environment - controllers, I/O modules, X-ray (XRT-DE) and optical analysis (VIS-NIR), enabling precise examination of the composition and quality of mineral resources. The internal environmental conditions in the housings of the above-mentioned sensitive elements and in the server room were the basis for the analysis. The aim was to develop a performance model enabling effective improvement of the working environment of all electrical and mechanical devices affecting energy efficiency and the internal environment. Separators operate in a very diverse environment, such as: tropical forests, Canadian Tundra, or desert areas in Africa, as well as EU countries, the USA and Australia. These devices are used in both open pit and underground mines. The use of modern technologies and mobile solutions in the mining industry contributes to increased efficiency, operational safety and, consequently, minimizing the negative impact on the environment. The research results confirmed that precise monitoring and control to ensure environmental conditions at selected separator points is crucial to ensuring the continuity and quality of the separation process.

Słowa kluczowe

EN

sorter; feedforward neural network; intelligent construction; intelligent building; control system; thermal comfort model

PL

inteligentne budownictwo; inteligentny budynek; system sterowania; komfort cieplny; komfort termiczny; jednokierunkowa sieć neuronowa; sortownik

• Wydawca: Centrum Rzeczoznawstwa Budowlanego Sp. z o.o.
• Czasopismo: Inżynieria Bezpieczeństwa Obiektów Antropogenicznych
• Rocznik: 2024
• Tom: Nr 4
• Strony: 97--112
• Opis fizyczny: Bibliogr. 34 poz., tab., rys., wykr.

Twórcy

autor

Romańska Anna

• Cracow University of Technology, Faculty of Electrical and Computer Engineering, Department of Automation and Informatics, Cracow, Poland

autor

Dudzik Marek

• Cracow University of Technology, Faculty of Electrical and Computer Engineering, Department of Electrical Engineering, Cracow, Poland
• Comex Polska Sp. z o. o., Poland

autor

Progorowicz Jakub

• Technical University of Kosice, Institute of Earth Resources, Faculty of Mining, Ecology, Process Control and Geotechnologies, Kosice, Slovakia
• Comex Polska Sp. z o. o., Poland

autor

Kuc Sabina

• Cracow University of Technology, Faculty of Architecture, Chair of Architectural Engineering Design, Cracow, Poland

autor

Kopała Maciej

• Cracow University of Technology, Faculty of Electrical and Computer Engineering, Students, Cracow, Poland

autor

Pyznar Mateusz

• Cracow University of Technology, Faculty of Electrical and Computer Engineering, Students, Cracow, Poland

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).