Application of TLS Technology for Documentation of Brickwork Heritage Buildings and Structures

Damięcka-Suchocka, Marzena; Katzer, Jacek; Suchocki, Czesław

doi:10.3390/coatings12121963

Cited by 4 publications

(2 citation statements)

References 45 publications

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“…Identifikáciou zmien vlastností skenovaných povrchov na základe "near-infrared" intenzity sa zaoberá niekoľko publikácií ako napr. [8][9][10][11].…”

Section: Obr 1 Priradenie Farby K Bodom Mračna Na Základe Intenzity O...unclassified

Dátovo-orientovaný prístup na zníženie vlhkosti v pamiatkových budovách

et al. 2023

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Dnes sa v praxi používa viacero metód merania zameraných na identifikáciu úrovne vlhkosti stavebných konštrukcií. Namerané dáta je možné prepojiť s informačným modelom stavby, výsledkom čoho bude usporiadaná databáza, čo umožní nielen lepšie a komplexnejšie vyhodnocovanie, ale umožní automatizáciu vyhodnocovania s využitím umelej inteligencie. Problémom je najmä absencia informačných modelov stavby, ktoré obzvlášť pri historických objektoch nie sú k dispozícii. V tomto článku sa zameriavame na vytvorenie metodiky pre systematický zber údajov o vlhkostných pomeroch v konštrukciách pamiatkových objektov, ktorá bude podkladom pre návrh vhodných opatrení na úpravu. Prvým krokom je digitalizácia stavby prostredníctvom fotogrametrie, prípadne terestrického laserového skenovania. Druhým krokom je vytvorenie informačného modelu stavby. Posledným krokom je prepojenie informácií z merania s informačným modelom stavby. Obohatenie BIM o dátový súbor vlhkostných záznamov z rôznych budov môže výrazne prispieť lepšiemu pochopeniu miery zavlhnutia, identifikácii príčin a tiež napomôcť k výberu vhodných opatrení na základe navrhnutých opatrení v minulosti.

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“…Identifikáciou zmien vlastností skenovaných povrchov na základe "near-infrared" intenzity sa zaoberá niekoľko publikácií ako napr. [8][9][10][11].…”

Section: Obr 1 Priradenie Farby K Bodom Mračna Na Základe Intenzity O...unclassified

Dátovo-orientovaný prístup na zníženie vlhkosti v pamiatkových budovách

et al. 2023

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“…Such collaborations have been taking advantage of image-based methods to improve the inspection of buildings, showing excellent reactions from research communities and inspection teams in the field. The evaluation and monitoring of the state of conservation of buildings has shown significant growth not only in the field of preserving vestiges of architectural heritage but also monitor and maintain contemporary constructions and structures [1,2]. This is entirely in line with the new Construction 4.0 paradigm, which can benefit the areas of intelligent design, construction, and maintenance.…”

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confidence: 98%

StainView: A Fast and Reliable Method for Mapping Stains in Facades Using Image Classification in HSV and CIELab Colour Space

et al. 2023

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The new Construction 4.0 paradigm takes advantage of existing technologies. In this scope, the development and application of image-based methods for evaluating and monitoring the state of conservation of buildings has shown significant growth, including support for maintenance plans. Recently, powerful algorithms have been applied to automatically evaluate the state of conservation of buildings using deep learning frameworks, which are utilised as a black-box approach. The large amount of data required for training, the difficulty in generalising, and the lack of parameters to assess the quality of the results often make it difficult for non-experts to evaluate them. For several applications and scenarios, simple and more intuitive image-based approaches can be applied to support building inspections. This paper presents the StainView, which is a fast and reliable method. The method is based on the classification of the mosaic image, computed from a systematic acquisition, and allows one to (i) map stains in facades; (ii) locate critical areas; (iii) identify materials; (iv) characterise colours; and (v) produce detailed and comprehensive maps of results. The method was validated in three identical buildings in Bairro de Alvalade, in Lisbon, Portugal, that present different levels of degradation. The comparison with visual inspection demonstrates that StainView enables the automatic location and mapping of critical areas with high efficiency, proving to be a useful tool for building inspection: differences were of approximately 5% for the facade with the worst and average state of conservation, however, the values deteriorate for the facade under good conditions, reaching the double of percentage. In terms of processing speed, StainView allows a facade mapping that is 8–12 times faster, and this difference tends to grow with the number of evaluated façades.

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