An automated system for electrical power symbol placement in electrical plan drawing

An electrical plan drawing–sometimes called a wiring diagram or electrical drawing–consists of lines and symbols. Electrical plan drawings are prepared on 2D architectural floor plans using Computer-Aided Design and/or Drafting (CAD) programs. The placement/drawing of electrical power symbols–such a...

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Autores principales: Bayram Akgul, Hakan Kutucu
Formato: article
Lenguaje:EN
Publicado: Taylor & Francis Group 2022
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Acceso en línea:https://doaj.org/article/f1e2c29cfa5340df9886d03188eb766e
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spelling oai:doaj.org-article:f1e2c29cfa5340df9886d03188eb766e2021-12-01T14:40:58ZAn automated system for electrical power symbol placement in electrical plan drawing0005-11441848-338010.1080/00051144.2021.2008620https://doaj.org/article/f1e2c29cfa5340df9886d03188eb766e2022-01-01T00:00:00Zhttp://dx.doi.org/10.1080/00051144.2021.2008620https://doaj.org/toc/0005-1144https://doaj.org/toc/1848-3380An electrical plan drawing–sometimes called a wiring diagram or electrical drawing–consists of lines and symbols. Electrical plan drawings are prepared on 2D architectural floor plans using Computer-Aided Design and/or Drafting (CAD) programs. The placement/drawing of electrical power symbols–such as sockets, lights, and switches–is the first step of an electrical plan drawing. For this purpose, a smart system has been developed in this study to automatically draw/place electrical power symbols in appropriate locations. The system is based on the detection and classification/recognition of furnishing (decorative) symbols in the floor plans. We have created a furnishing symbol dataset drawing on dozens of architectural plan drawings that contain symbols of the most commonly used tools in floor plans, such as furniture, appliances, plumbing, doors, and windows. We used a Deep Convolutional Neural Network (D-CNN) with transfer learning–Inception-v3 model– to classify furnishing symbols. We tested the model on 20 real floor plans and achieved a very satisfactory accuracy of 97.05% in furnishing symbol classification. The symbol drawing step, which is the first step of drawing the electrical plan, was automated using the work developed, thus achieving the aim of saving time and labour. Experimental studies show the effectiveness of the proposed automated system.Bayram AkgulHakan KutucuTaylor & Francis Grouparticlecomputer-aided designelectrical plan drawingdeep learningtransfer learningautomated designControl engineering systems. Automatic machinery (General)TJ212-225AutomationT59.5ENAutomatika, Vol 63, Iss 1, Pp 78-89 (2022)
institution DOAJ
collection DOAJ
language EN
topic computer-aided design
electrical plan drawing
deep learning
transfer learning
automated design
Control engineering systems. Automatic machinery (General)
TJ212-225
Automation
T59.5
spellingShingle computer-aided design
electrical plan drawing
deep learning
transfer learning
automated design
Control engineering systems. Automatic machinery (General)
TJ212-225
Automation
T59.5
Bayram Akgul
Hakan Kutucu
An automated system for electrical power symbol placement in electrical plan drawing
description An electrical plan drawing–sometimes called a wiring diagram or electrical drawing–consists of lines and symbols. Electrical plan drawings are prepared on 2D architectural floor plans using Computer-Aided Design and/or Drafting (CAD) programs. The placement/drawing of electrical power symbols–such as sockets, lights, and switches–is the first step of an electrical plan drawing. For this purpose, a smart system has been developed in this study to automatically draw/place electrical power symbols in appropriate locations. The system is based on the detection and classification/recognition of furnishing (decorative) symbols in the floor plans. We have created a furnishing symbol dataset drawing on dozens of architectural plan drawings that contain symbols of the most commonly used tools in floor plans, such as furniture, appliances, plumbing, doors, and windows. We used a Deep Convolutional Neural Network (D-CNN) with transfer learning–Inception-v3 model– to classify furnishing symbols. We tested the model on 20 real floor plans and achieved a very satisfactory accuracy of 97.05% in furnishing symbol classification. The symbol drawing step, which is the first step of drawing the electrical plan, was automated using the work developed, thus achieving the aim of saving time and labour. Experimental studies show the effectiveness of the proposed automated system.
format article
author Bayram Akgul
Hakan Kutucu
author_facet Bayram Akgul
Hakan Kutucu
author_sort Bayram Akgul
title An automated system for electrical power symbol placement in electrical plan drawing
title_short An automated system for electrical power symbol placement in electrical plan drawing
title_full An automated system for electrical power symbol placement in electrical plan drawing
title_fullStr An automated system for electrical power symbol placement in electrical plan drawing
title_full_unstemmed An automated system for electrical power symbol placement in electrical plan drawing
title_sort automated system for electrical power symbol placement in electrical plan drawing
publisher Taylor & Francis Group
publishDate 2022
url https://doaj.org/article/f1e2c29cfa5340df9886d03188eb766e
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