Sensor Signal and Information Processing II [Editorial]

This Special Issue compiles a set of innovative developments on the use of sensor signals and information processing. In particular, these contributions report original studies on a wide variety of sensor signals including wireless communication, machinery, ultrasound, imaging, and internet data, and information processing methodologies such as deep learning, machine learning, compressive sensing, and variational Bayesian. All these devices have one point in common: These algorithms have incorporated some form of computational intelligence as part of their core framework in problem solving. They have the capacity to generalize and discover knowledge for themselves, learning to learn new information whenever unseen data are captured

Detection and localisation of structural deformations using terrestrial laser scanning and generalised procrustes analysis

One of the most vital duties for engineers is to preserve life and nature by utilising safe designs that take into account environmental standards and monitoring the performance of structures against design criteria. Furthermore, monitoring can be used to determine any required maintenance of an important structure following a catastrophic event. Numerous different techniques and instruments can be employed for such a purpose with different requirements producing different results. For instance, some techniques need to embed sensors inside the building, such as Geotechnical Sensors. Others can offer high quality, but with a low point density and require fixed stations and targets, like Total Stations (TS). In such cases, the location of deformation tends to be known, such as in dams, bridges, and high-rise buildings. However, this is not always the case where it might be hard to expect deformation location as in the case of historic ruins where each part of the structure could be subject to deformation. The challenge in such case is to detect the deformation without any previous knowledge. Remote Sensing (RS) techniques, such as Digital Photogrammetry, Synthetic Aperture Radar (SAR), Interferometric Synthetic Aperture Radar (InSAR), and Terrestrial Laser Scanner (TLS) can be solutions for such an issue. Interestingly, many researchers are focusing on using TLS for monitoring owing to the great spatial resolution system can offer. However, there are three challenges in using TLS in monitoring: the first one is a huge amount of data and the difficulty of handling it; the second one is the difficulty of comparing between two epochs because observations of TLS are not repeatable; and the third issue is the noise which is attached to the data. The first problem is solved by segmentation and point structure while the second and the third ones still need more investigation, although some interesting researches have been done in this area. The aim of this research is to develop a new approach to detect and localise unpredictable deformation. It is based on TLS measurements and Generalised Procrustes Analysis (GPA) techniques to determine deformation vectors, while boxing structure and F-test are used to detect and localise deformation. In summary, after applying this approach, the whole concerned building is represented as parts, for each of which the displacement vector and the deformation probability are estimated. Ultimately, it is possible to monitor any part through different epochs. In addition, through this technique, it is possible to determine deformations - not just between two epochs, but for sequences of them. This can give more reliable results. Four validation experiments have been conducted. The first test was designed to assess the performance of the developed software and to fix some variables. Therefore, it was based on simulated data with controlled white noise, distributed according to the normal distribution, and simulated deformations. The results of this test revealed the success of the proposed algorithm to detect and to localise deformations. In addition, it showed the success when no deformations exist. Furthermore, optimistically, it could observe deformations with magnitude less than the noise level; however, the probability was only 40%. Correspondingly, real scan data with simulated deformations was used in the second test. The purpose of this test is to examine the performance of the proposed method in case of real errors budget. However, the short range of the test (about 10m), a featureless scanned area (wall only), and scanning from one position for all epochs (no need for registration) can reduce errors to a minimum. Results of this test showed the success of the proposed method to detect and localise deformations. Potentially, it can give indications for areas with deformations less than the noise level. Furthermore, results of the proposed method can be considered better than that of CloudCompare software. The third test was conducted to examine the performance of the proposed technique regarding different materials and textures. For this purpose, the Nottingham Geospatial Building (NGB) was selected with more extensive ranges (between 20-25 m). Similar to the second test, all measurements were taken from the same scanner position. To some extent, the proposed technique succeeded to detect and to localise deformations. However, the researcher does not recommend it for monitoring modern and complicated buildings, instead it has been developed for monitoring historic ruins. Finally, the proposed method was applied on the Bellmanpark Limekiln, Clitheroe, Lancashire monitoring project. This is a live project for Historic England and addresses a historic building that currently has some structural issues. The outcome of the proposed method revealed deformations in the faces South East (SE) and North East (NE). From examining these faces, three deformed areas were found: two in the face SE and one in the face NE, which might cause some cracks appeared in these faces. Alternatively, the CloudCompare software has been employed to detect deformation. Although results coincide with the proposed method for detected deformations, it cannot locate these deformations very well because it diffused over a wide area. In addition, it cannot determine actual directions of the deformations unlike the proposed method

Suitability Study of Structure-from-Motion for the Digitisation of Architectural (Heritage) Spaces to Apply Divergent Photograph Collection

The digitisation of architectural heritage has experienced a great development of low-cost and high-definition data capture technologies, thus enabling the accurate and effective modelling of complex heritage assets. Accordingly, research has identified the best methods to survey historic buildings, but the suitability of Structure-from-Motion/Multi-view-Stereo (SfM/MVS) for interior square symmetrical architectural spaces is unexplored. In contrast to the traditional SfM surveying for which the camera surrounds the object, the photograph collection approach is divergent in courtyards. This paper evaluates the accuracy of SfM point clouds against Terrestrial Laser Scanning (TLS) for these large architectural spaces with a symmetrical configuration, with the main courtyard of Casa de Pilatos in Seville, Spain, as a case study. Two different SfM surveys were conducted: (1) Without control points, and (2) referenced using a total station. The first survey yielded unacceptable results: A standard deviation of 0.0576 m was achieved in the northwest sector of the case study, mainly because of the difficulty of aligning the SfM and TLS data due to the way they are produced. This value could be admissible depending on the purpose of the photogrammetric model

As-built 3D heritage city modelling to support numerical structural analysis: application to the assessment of an archaeological remain

Terrestrial laser scanning is a widely used technology to digitise archaeological, architectural and cultural heritage. This allows for modelling the assets’ real condition in comparison with traditional data acquisition methods. This paper, based on the case study of the basilica in the Baelo Claudia archaeological ensemble (Tarifa, Spain), justifies the need of accurate heritage modelling against excessively simplified approaches in order to support structural safety analysis. To do this, after validating the 3D meshing process from point cloud data, the semi-automatic digital reconstitution of the basilica columns is performed. Next, a geometric analysis is conducted to calculate the structural alterations of the columns. In order to determine the structural performance, focusing both on the accuracy and suitability of the geometric models, static and modal analyses are carried out by means of the finite element method (FEM) on three different models for the most unfavourable column in terms of structural damage: (1) as-built (2) simplified and (3) ideal model without deformations. Finally, the outcomes show that the as-built modelling enhances the conservation status analysis of the 3D heritage city (in terms of realistic compliance factor values), although further automation still needs to be implemented in the modelling process

Beurteilung des seismischen Verhaltens von grossen Talsperren mittels geomatischer Techniken und Finite Element Modeling

The safety and efficient maintenance of dams are primary aspects in the management of such strategic works. The need to combine the security with the containment of maintenance costs directly linked to the service life of the structure, requires innovative approaches beside traditional methods. In this respect, the limited accessibility of large dams does not facilitate the use of traditional survey techniques, although a reliable terrestrial survey is still necessary, the use of Unmanned Aerial Vehicles (UAV) is well suited for this purpose. The aim of the present study is to provide a reconstruction procedure of a high detail FE model of a dam starting from an integrated UAV survey useful for a predictive and proactive maintenance of the dam system. In particular, the “Structure from Motion” (SfM) technique can be used for the reconstruction of 3D objects from 2D images. Therefore, after an integration of the UAV dense point cloud with pre-existing data sets such as design geometry, Digital Elevation Model (DEM) of the area and bathymetry of the lake, a 3D solid reconstruction of the whole dam system is possible. Important elements of the structure such as spillway, vertical joints and pulvino foundation joint and of ancillary works such as stilling basin and weight blocks are reproduced. In order to study the influence of joint modelling on the dynamic behaviour of the structure, three models have been analyzed: monolithic m., surface-to-surface joint m. and solid element joint m.. All simulations take into account the structure-foundation interaction by means of a rock mass solid and the fluid-structure interaction by means of acoustic elements. Modal analyses are therefore performed in order to obtain the dynamic properties of the models and to identify the representation which fits better with the real dynamic records (e.g. vibrodyne test, ambient vibrations). Subsequently, linear elastic dynamic analyses are performed to calibrate the damping coefficients of rock mass and structure. Finally, non-linearity is introduced in the joint elements performing non-linear dynamic damage analyses under severe earthquakes and, varying the water level, the damage distribution is investigated. The inclusion of vertical construction joints into finite element models of dams allows us to verify the behaviour of such real discontinuities under severe seismic events and therefore to verify the seismic vulnerability assessment of the whole structure.Die Sicherheit und effiziente Wartung von Staudämmen sind primäre Aspekte beim Management solcher strategischer Arbeiten. Die Notwendigkeit, die Sicherheit mit der Begrenzung von Instandhaltungskosten zu verbinden, die direkt mit der Lebensdauer der Struktur verbunden sind, erfordert innovative Ansätze neben traditionellen Methoden. In dieser Hinsicht erleichtert die beschränkte Zugänglichkeit großer Staudämme nicht die Verwendung traditioneller Vermessungstechniken, obwohl eine zuverlässige terrestrische Vermessung noch notwendig ist, ist die Verwendung von unbemannten Luftfahrzeugen (UAV) für diesen Zweck gut geeignet. Das Ziel der vorliegenden Studie ist es, ein Rekonstruktionsverfahren eines hochdetaillierten FE-Modells eines Damms ausgehend von einer integrierten UAV-Untersuchung zu erstellen, die für eine vorausschauende Instandhaltung des Staudammsystems nützlich ist. Ist nach einer Integration der UAV-Dichtepunktwolke mit bereits vorhandenen Datensätzen wie Entwurfsgeometrie, Digital Elevation Model (DEM) des Gebiets und Bathymetrie des Sees eine 3D-Rekonstruktion des gesamten Dammsystems möglich. Wichtige Elemente des Bauwerks werden wiedergegeben (i.e. Vertikalfugen, Nebenarbeiten). Um den Einfluss der Gelenkmodellierung auf das dynamische Verhalten der Struktur zu untersuchen, wurden drei Modelle analysiert: monolithische, Oberfläche-zu-Oberfläche-Verbindung und solid element joint. Alle Simulationen berücksichtigen die Struktur-Fundament-Wechselwirkung mittels eines Gesteinsmassenkörpers und die Fluid-Struktur-Wechselwirkung mittels akustischer Elemente. Es werden daher Modalanalysen durchgeführt, um die dynamischen Eigenschaften der Modelle zu erhalten und um die Darstellung zu identifizieren, die besser zu den realen dynamischen Aufzeichnungen passt. Anschließend werden lineare elastische dynamische Analysen durchgeführt, um die Dämpfungskoeffizienten von Gesteinsmasse und Struktur zu kalibrieren. Schließlich wird die Nichtlinearität in die Gelenkelemente eingeführt, die nichtlineare dynamische Schadensanalysen unter schweren Erdbeben durchführen. Bei der Variation des Wasserspiegels wird die Schadensverteilung untersucht. Die Einbeziehung von vertikalen Konstruktionsfugen in Finite-Elemente-Modelle von Dämmen ermöglicht es uns, das Verhalten solcher realen Diskontinuitäten unter schweren seismischen Ereignissen zu verifizieren und somit die Bewertung der seismischen Vulnerabilität der gesamten Struktur zu verifizieren