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Digital twins for medium span bridges – pilot project bridge Schwindegg – part 2: Asset Administration Shell The term ′digital twin′ is becoming increasingly popular in German‐speaking countries for the digital management and condition monitoring of bridges. Although standardised developments for the use of digital twins have already been initiated in industry and medicine, the first prototypes are currently being implemented in the construction industry. The digital images are typically operated in online environments that are proprietary to the project and have limited reusability. The article investigates the integration of scaling into Building Information Modelling models, which is reaching its limits due to the real‐time capability. It places existing definitions of the digital twin of the industry in the context of the construction industry. The implementation of the Isenbridge in Schwindegg as an Industry 4.0 Asset Administration Shell (AAS) is presented, building on Part 1 of this contribution. We show that an industrial, data‐driven digital twin can also be implemented technically and semantically for engineering structures. The article also presents the future challenges for evaluation and control mechanisms still to be developed for the structure. We also show a possible visualisation. The goal is to develop a syntax for the AAS' communication. [ABSTRACT FROM AUTHOR]

The 3D reconstruction of historical and cultural heritage monuments is a procedure recommended by the UNESCO World Heritage Institution since 1985. It is crucial when conserving monuments and creating digital twins. Current 3D reconstruction techniques using digital images and terrestrial laser scanning (TLS) data are considered as cost-effective and efficient methods for the production of high-quality digital 3D models. In the presented study, laser scanning and close-range photogrammetry techniques and images taken by a low-cost unmanned aerial vehicle (UAV) were applied to quickly and completely acquire the point cloud and texture of a historic church in Poland. The aim of this study was to evaluate two options for integrating TLS and UAV data, using ground control points (GCP) measured by two independent techniques: tachymetry and laser scanning. The study shows that the 3D model created based on ground control points acquired by the laser scanning technique has a mean square error RMSEXYZ = 2.5 cm on the check points. The result obtained is not much larger than the second variant of data integration, for which RMSEXYZ = 1.7 cm. Thus, the TLS method was positively evaluated as a GCP measurement technique for the integration of UAV and TLS data and the creation of cartometric 3D models of religious buildings. [ABSTRACT FROM AUTHOR]

Transformer is a key equipment for constructing power system, and its safe and stable operation is the basis of power system. In order to solve the problems of difficult identification and low detection accuracy of transformer winding at operating state, in this paper, a diagnosis method based on digital twinning technique for transformer winding failure is proposed. Firstly a digital twin transformer model with high simulation degree based on transformer entities was built, and then multiple physical field simulation were used to deduce the information change of oil tank surface vibration information of digital twin transformer under different working conditions, various winding failures. Here, the vibration signal on oil tank is effectively decomposed to extract the feature vector by independent component analysis method and wavelet packet transform, which in turn is based on neural network algorithm to learn and diagnose the failure signal of winding. In order to test the accuracy and feasibility of the method, the diagnostic test of oil tank vibration signal detection of health and fault transformer is carried out on an experimental prototype of transformer with 110 kV, and the diagnostic results show that this method can diagnose the problems occurred in transformer windings with high efficiency and accuracy. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

With the development of China's social economy, the pace of people's life is also accelerating. Therefore, in the face of the increasing pressure of life and work, people have begun to pay more and more attention to improving their physical fitness and they also pay more and more attention to sports in their spare time. The knee joint is a very important body part that will be involved in sports. Therefore, in sports, it is very important for healthy sports to pay attention to the state of the knee joint at all times and avoid injury to the knee joint during sports. The three-dimensional visual analysis of the knee joint movement trajectory in sports training refers to the trajectory capture and three-dimensional visual analysis of the knee joint movement in sports training based on the computer-based description and understanding of model technology. The three-dimensional visual analysis of the motion trajectory of the knee joint in sports training is conducive to the attention and analysis of the motion state of the knee joint in sports training, so as to help find problems and avoid knee joint damage during sports training as much as possible. This paper aims to study the 3D visualization analysis of knee joint motion trajectory in sports training based on digital twin and establish a 3D visualization system of knee joint motion trajectory based on digital twin technology, and based on this system, the three-dimensional visualization experiment of knee joint movement trajectory in sports training is carried out. The experiment concluded that the signal-to-noise ratio of the three-dimensional visualization image of the knee joint movement trajectory in sports training based on the three-dimensional visualization system established by the digital twin is 68% and the clarity is 89%. It shows that the system has a good 3D visualization effect. [ABSTRACT FROM AUTHOR]

Registering images to a building information model is an effective approach of associating as-built component status to as-designed information. However, registering a single still image to a digital twin is difficult due to pose ambiguities caused by the limited field of view in images. Several recent studies have started focusing on leveraging panoramic images to address problems, such as partial occlusions, repetitive facility components and textureless views, which could cause registration failures in existing image-based registration workflows. Even though having a bigger field of view helps in locating where the image was taken, registering a panoramic image to a building information model is still challenging due to inconsistent visual appearances, such as model vs. image visual differences caused by temporary objects in a scene, lighting condition changes, and different levels of details. In this paper, we present a novel method that registers panoramic images to a digital twin in a hierarchical way: the proposed method first performs rough registration through image retrieval using semantic segmentation, then localizes the image with a fine registration through minimizing semantic reprojection errors. Compared to existing methods, the developed method has the following contributions: 1) semantic-based image retrieval makes the rough registration process robust to lighting condition changes, texture differences, and temporary objects, 2) semantic-based image retrieval allows for bi-directional queries between a model and images, 3) reprojection-based fine registration further reduces the localization error due to the dimension reduction of features during image retrieval. Though the proposed method is developed for panoramic images, it can be generalized to monocular images at the cost of localization accuracy. The developed method was evaluated on a real-world academic building and a synthetic dataset, and the results showed that the proposed method can localize a panorama in less than a second and achieve sub-meter level localization error. • A new panorama-to-BIM registration method is developed. • A new image retrieval approach is developed for hierarchical registration. • Semantic features help address visual differences between BIM and images. • Accuracy and robustness of image-to-BIM registration are improved. [ABSTRACT FROM AUTHOR]

The idea defended in this paper consists in finding, at any time and everywhere, the arrangement of containers within a composite container. The digital image of the real arrangement obtained defines its digital twin. This image evolves at the same time as its real twin. It can be used throughout the logistics chain during loading/unloading phases in hubs, to check the completeness of a load, to find the particular position of a container, etc. This digital twin is obtained through the collection of neighborhood information from the sensor nodes embedded on each container. This embedded solution allows accessibility to this information everywhere. This proximity information and the instrumentation of the containers define new types of constraints and a new version of a packing problem. We propose here a model integrating them. This model is implemented and tested on different test cases, and numerical results are provided. These show that, under certain conditions that will be presented, it is possible to obtain the digital twin of the real arrangement. [ABSTRACT FROM AUTHOR]