The aim of this paper is to present an in-pipe modular robotic system that can navigate inaccessible industrial pipes in order to check their condition, locate leakages, and clean the ventilation systems. The aspects concerning the development of a lightweight and energy efficient modular robotic system are presented. The paper starts with a short introduction about modular inspection systems in the first chapter, followed by design aspects and finalizing with the test of the developed robotic system.
The paper presents research on the capability of the residual magnetic field (RMF) measurement system to be applied to the railway inspection for the early non-destructive detection of defects. The metal magnetic memory (MMM) phenomena are analysed using normal component Hy of self-magnetic flux leakage (SMFL), and its tangential component Hx, as well as their respective gradients. The measurement apparatus is described together with possible factors that may affect the results of measurement. The Type A uncertainty estimation and repeatability tests were performed. The results demonstrate that the system may be successfully applied to detection of head check flaws.
The article discusses "Rules for using the point rating scales for assessing the technical condition and usability of road engineering objects – second edition", which were introduced by the General Directorate for National Roads and Motorways (GDDKiA) Regulation No. 1/2019. The main objective of "Rules..." was to standardize the method of point rating assessment of technical condition and usability, and in the second edition, to take into account the latest construction and material solutions. Because the results of inspections are analyzed and compared not only at the regional but also at the national level, it is very important for all inspectors in the country to evaluate the technical condition and usability in an analogous manner. While developing the 2nd edition, the authors maintained the assumptions of continuity of inspection system, including adaptation to the inspection manuals, algorithms, and software supporting the management of bridges.
Infrared (IR) reflectography has been used for many years for the detection of underdrawings on panel paintings. Advances in the fields of IR sensors and optics have impelled the wide spread use of IR reflectography by several recognized Art Museums and specialized laboratories around the World. The transparency or opacity of a painting is the result of a complex combination of the optical properties of the painting pigments and the underdrawing material, as well as the type of illumination source and the sensor characteristics. For this reason, recent researches have been directed towards the study of multispectral approaches that could provide simultaneous and complementary information of an artwork. The present work relies on non−simultaneous multispectral inspection using a set of detectors covering from the ultraviolet to the terahertz spectra. It is observed that underdrawings contrast increases with wavelength up to 1700 nm and, then, gradually decreases. In addition, it is shown that IR thermography, i.e., temperature maps or thermograms, could be used simultaneously as an alternative technique for the detection of underdrawings besides the detection of subsurface defects.
The level of degradation of reinforced concrete bridges was evaluated based on the in-situ measurements performed on five reinforced concrete bridges under service located in the Czech Republic. The combined effect of carbonation and chlorides with respect to the corrosion of steel reinforcement, namely the pH and the amount of water-soluble chlorides, were evaluated on drilled core samples of concrete. Based on these parameters, the ratio between the concentrations of Cl– and OH, which indicates the ability of concrete to protect reinforcement, was calculated. All the data were statistically summarized and the relationships among them were provided. The main goal of this study is to evaluate the non-proportional effect of the amount of chlorides per mass of concrete on the risk of corrosion initiation and to localize the “critical” locations in the bridges that are the most affected by the degradation effects.
Despite the progress in digitization of civil engineering, the process of bridge inspection is still outdated. In most cases, its documentation consists of notes, sketches and photos. This results in significant data loss during structure maintenance and can even lead to critical failures. As a solution to this problem, many researchers see the use of modern technologies that are gaining popularity in civil engineering. Namely Building Information Modelling (BIM), 3D reconstruction and Artificial Intelligence (AI). However, despite their work, no particular solution was implemented. In this article, we evaluated the applicability of state-of-the-art methods based on a case study. We have considered each step starting from data acquisition and ending on BIM model enrichment. Additionally, the comparison of deep learning crack semantic segmentation algorithm with human inspector was performed. Authors believe that this kind of work is crucial for further advancements in the field of bridge maintenance.