Pub Date : 2022-06-20DOI: 10.4995/jisdm2022.2022.13906
Barış Karadeniz, Mert Bezcioglu, C. O. Yigit, A. Dindar, B. Akpınar
Nowadays, with the developments in GNSS (Global Navigation Satellite System) technology, the data storage and data processing capacity of GPS (Global Positioning System) receivers has been gradually increased. This situation is widely used in the detection and monitoring of horizontal and vertical vibrations that occur in the structure when high temporal resolution geodetic GPS receivers are under the influence of dynamic loads such as earth crust motions, wind load, traffic load, which affect man-made engineering structures. In the study, RT DF-PPP (Real Time Dual Frequency-Precise Point Positioning) method was applied together with a GPS sensor with a sampling interval of 20 Hz, using a steel bar mounted on a steel tree model designed as a structure model, and a steel bar on which different sensors can be integrated and can provide simulation of vertical motions in detecting vertical motions occurring in structures. To evaluate the performance of the method used and to test the performance of capturing vertical displacements, the DF-RP (Dual Frequency-Relative Positioning) method was taken as reference and the results were compared with the PP-PPP (Post Process-PPP) method using the IGS-Final (International GNSS Service-Final) product. When the results are compared with the RP and PP-PPP solutions in the frequency domain of vertical motions as a result of harmonic oscillations of the high-rate RT-PPP method, it has been seen that the amplitudes and frequencies are compatible with each other. Therefore, dynamic motions that occur as a result of natural events such as earthquakes, tsunamis, landslides and volcanic eruptions can be instantly and reliably monitored and detected by the high-rate RT-PPP method. When the results were evaluated in the time domain, an improvement was observed in the RMSE (Root Mean Square Error) and maximum values of RT-PPP and PP-PPP methods according to RP after filtering. When the statistical results are examined, vertical harmonic motions of the solutions made by using both RT-PPP and PP-PPP methods can be detected with accuracy below centimeters. These results clearly show that it can detect vertical dynamic motions in engineering structures such as bridges, skyscrapers and viaducts with RT-PPP method to evaluate. Thus, by detecting the effects of dynamic motions occurring in the structure on the health of the structure, a safe environment will be provided by making a rapid hazard assessment for life safety.
如今，随着全球卫星导航系统(GNSS)技术的发展，全球定位系统(GPS)接收机的数据存储和数据处理能力逐渐提高。这种情况被广泛应用于高时分辨大地GPS接收机在地壳运动、风荷载、交通荷载等影响人工工程结构的动荷载作用下，对结构内部发生的水平和垂直振动进行检测和监测。本研究采用RT DF-PPP (Real Time Dual Frequency-Precise Point Positioning，实时双频精确点定位)方法，结合采样间隔为20 Hz的GPS传感器，将一根钢筋安装在设计为结构模型的钢树模型上，并在一根钢筋上集成不同的传感器，可以模拟垂直运动，检测结构中发生的垂直运动。为了评估所使用方法的性能并测试捕获垂直位移的性能，以DF-RP(双频相对定位)方法为参考，并使用IGS-Final(国际GNSS服务- final)产品将结果与PP-PPP (Post Process-PPP)方法进行比较。将结果与高速率RT-PPP方法在谐波引起的垂直运动频域的RP和PP-PPP解进行比较，可以看出幅值和频率是兼容的。因此，由于地震、海啸、滑坡和火山爆发等自然事件而发生的动态运动，可以通过高速率的RT-PPP方法进行即时、可靠的监测和检测。在时域评价结果时，RT-PPP和PP-PPP方法的均方根误差RMSE (Root Mean Square Error)和最大值根据RP滤波后有所改善。在对统计结果进行检验时，RT-PPP和PP-PPP两种方法得到的溶液的垂直谐波运动都可以检测到厘米以下的精度。这些结果清楚地表明，RT-PPP方法可以检测桥梁、摩天大楼和高架桥等工程结构的垂直动力运动。因此，通过检测结构中发生的动力运动对结构健康的影响，通过对生命安全进行快速危害评估，提供安全的环境。
{"title":"High-rate real-time PPP for dynamic motion detection in vertical direction","authors":"Barış Karadeniz, Mert Bezcioglu, C. O. Yigit, A. Dindar, B. Akpınar","doi":"10.4995/jisdm2022.2022.13906","DOIUrl":"https://doi.org/10.4995/jisdm2022.2022.13906","url":null,"abstract":"Nowadays, with the developments in GNSS (Global Navigation Satellite System) technology, the data storage and data processing capacity of GPS (Global Positioning System) receivers has been gradually increased. This situation is widely used in the detection and monitoring of horizontal and vertical vibrations that occur in the structure when high temporal resolution geodetic GPS receivers are under the influence of dynamic loads such as earth crust motions, wind load, traffic load, which affect man-made engineering structures. In the study, RT DF-PPP (Real Time Dual Frequency-Precise Point Positioning) method was applied together with a GPS sensor with a sampling interval of 20 Hz, using a steel bar mounted on a steel tree model designed as a structure model, and a steel bar on which different sensors can be integrated and can provide simulation of vertical motions in detecting vertical motions occurring in structures. To evaluate the performance of the method used and to test the performance of capturing vertical displacements, the DF-RP (Dual Frequency-Relative Positioning) method was taken as reference and the results were compared with the PP-PPP (Post Process-PPP) method using the IGS-Final (International GNSS Service-Final) product. When the results are compared with the RP and PP-PPP solutions in the frequency domain of vertical motions as a result of harmonic oscillations of the high-rate RT-PPP method, it has been seen that the amplitudes and frequencies are compatible with each other. Therefore, dynamic motions that occur as a result of natural events such as earthquakes, tsunamis, landslides and volcanic eruptions can be instantly and reliably monitored and detected by the high-rate RT-PPP method. When the results were evaluated in the time domain, an improvement was observed in the RMSE (Root Mean Square Error) and maximum values of RT-PPP and PP-PPP methods according to RP after filtering. When the statistical results are examined, vertical harmonic motions of the solutions made by using both RT-PPP and PP-PPP methods can be detected with accuracy below centimeters. These results clearly show that it can detect vertical dynamic motions in engineering structures such as bridges, skyscrapers and viaducts with RT-PPP method to evaluate. Thus, by detecting the effects of dynamic motions occurring in the structure on the health of the structure, a safe environment will be provided by making a rapid hazard assessment for life safety.","PeriodicalId":404487,"journal":{"name":"Proceedings of the 5th Joint International Symposium on Deformation Monitoring - JISDM 2022","volume":"108 8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129753316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-20DOI: 10.4995/jisdm2022.2022.13814
Yixiong Jing, B. Sheil, S. Acikgoz
Masonry arch bridges constitute the majority of the European bridge stock. Most of these bridges were constructed in the 19th century and feature a wide range of geometric characteristics. Since construction drawings rarely exist, the first step in the assessment of these bridges is the characterisation of their in-situ geometry, which may involve significant geometric distortions. In recent years, LIDAR devices have been widely used by bridge owners due to their ability to remotely and rapidly collect point cloud data. To enable the engineering assessment practice to benefit from this data, this research uses the recently developed deep learning (DL) neural network BridgeNet to autonomously segment masonry bridge point clouds into different components. Due to the limited availability of 3D point clouds, BridgeNet is trained using a synthetic multi-span masonry arch bridge dataset; the network is then tested on real arch bridge point clouds. By fitting appropriate primitive shapes to bridge component point clouds using Random Consensus Sampling (RANSAC) techniques the bridge geometry is effectively characterised by a few parameters.
{"title":"Extraction of key geometric parameters from segmented masonry arch bridge point clouds","authors":"Yixiong Jing, B. Sheil, S. Acikgoz","doi":"10.4995/jisdm2022.2022.13814","DOIUrl":"https://doi.org/10.4995/jisdm2022.2022.13814","url":null,"abstract":"Masonry arch bridges constitute the majority of the European bridge stock. Most of these bridges were constructed in the 19th century and feature a wide range of geometric characteristics. Since construction drawings rarely exist, the first step in the assessment of these bridges is the characterisation of their in-situ geometry, which may involve significant geometric distortions. In recent years, LIDAR devices have been widely used by bridge owners due to their ability to remotely and rapidly collect point cloud data. To enable the engineering assessment practice to benefit from this data, this research uses the recently developed deep learning (DL) neural network BridgeNet to autonomously segment masonry bridge point clouds into different components. Due to the limited availability of 3D point clouds, BridgeNet is trained using a synthetic multi-span masonry arch bridge dataset; the network is then tested on real arch bridge point clouds. By fitting appropriate primitive shapes to bridge component point clouds using Random Consensus Sampling (RANSAC) techniques the bridge geometry is effectively characterised by a few parameters.","PeriodicalId":404487,"journal":{"name":"Proceedings of the 5th Joint International Symposium on Deformation Monitoring - JISDM 2022","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128814691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-20DOI: 10.4995/jisdm2022.2022.13756
Michael Schulz, F. Schäfer, J. Rüffer
The earth is constantly exposed to endogenous and exogenous forces that cause temporally variable movements and deformations of varying degrees. The Global Monitoring (GLOMON) solution supports the monitoring of infrastructure or large areas such as mining regions using GNSS and other sensors, in order to detect deformations or surface movements. The GNSS reference stations enable the integration of other geodetic and geotechnical sensors in a global coordinate reference frame. Three dimensional coordinates are generated for each GNSS monitoring station with a precise time stamp, allowing for the web-based visualization of time series. One of the new developments presented here is the integration of the program system suite PANDA from GEOTEC GmbH into GLOMON, which supports a dynamic network adjustment. This procedure revolutionizes the approach of stable reference points for geodetic monitoring tasks, which has been valid and used for decades. The classic approach to such measurements is the assumption of a stable reference frame over a long period of time (zero measurement). Local measurements are connected to higher-level, supposedly stable reference points, such as first order GNSS reference stations. But these external reference points can also be subject to movements which, assuming stability, are projected onto the local measurements. To solve this problem, all GNSS stations are handed over to a deformation analysis after post-processing and network adjustment in order to detect displaced points. Furthermore, the concept of time-invariant reference station coordinates should be reconsidered. This means that those reference stations detected as displaced are not fundamentally excluded from the network evaluation, but their movement behavior is described by time-variant coordinates. With the introduction of movement models for reference stations, their movements are no longer projected onto local measurements of monitoring stations. This information can be used in the areas of interest, e.g. for the optimization of existing movement and deformation models. In this way, predictions about expected deformations can be made reliably.
{"title":"GLOMON-Monitoringportal for storage, management, advanced processing and intelligent visualization of GNSS- and other sensors data","authors":"Michael Schulz, F. Schäfer, J. Rüffer","doi":"10.4995/jisdm2022.2022.13756","DOIUrl":"https://doi.org/10.4995/jisdm2022.2022.13756","url":null,"abstract":"The earth is constantly exposed to endogenous and exogenous forces that cause temporally variable movements and deformations of varying degrees. The Global Monitoring (GLOMON) solution supports the monitoring of infrastructure or large areas such as mining regions using GNSS and other sensors, in order to detect deformations or surface movements. The GNSS reference stations enable the integration of other geodetic and geotechnical sensors in a global coordinate reference frame. Three dimensional coordinates are generated for each GNSS monitoring station with a precise time stamp, allowing for the web-based visualization of time series. One of the new developments presented here is the integration of the program system suite PANDA from GEOTEC GmbH into GLOMON, which supports a dynamic network adjustment. This procedure revolutionizes the approach of stable reference points for geodetic monitoring tasks, which has been valid and used for decades. The classic approach to such measurements is the assumption of a stable reference frame over a long period of time (zero measurement). Local measurements are connected to higher-level, supposedly stable reference points, such as first order GNSS reference stations. But these external reference points can also be subject to movements which, assuming stability, are projected onto the local measurements. To solve this problem, all GNSS stations are handed over to a deformation analysis after post-processing and network adjustment in order to detect displaced points. Furthermore, the concept of time-invariant reference station coordinates should be reconsidered. This means that those reference stations detected as displaced are not fundamentally excluded from the network evaluation, but their movement behavior is described by time-variant coordinates. With the introduction of movement models for reference stations, their movements are no longer projected onto local measurements of monitoring stations. This information can be used in the areas of interest, e.g. for the optimization of existing movement and deformation models. In this way, predictions about expected deformations can be made reliably.","PeriodicalId":404487,"journal":{"name":"Proceedings of the 5th Joint International Symposium on Deformation Monitoring - JISDM 2022","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123232438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-20DOI: 10.4995/jisdm2022.2022.13635
Anni Sauthoff, P. Köchert, G. Prellinger, T. Meyer, F. Pilarski, S. Weinrich, F. Schmaljohann, J. Guillory, D. Truong, Jakob Silbermann, U. Kallio, J. Jokela, F. Pollinger
Deformation monitoring requires the detection of smallest changes, always at the limits of technical feasibility. Trying to push these limits further, we have realised two terrestrial ranging instruments: a long-range 1D electro-optic distance meter and a 3D multilateration-capable sensor system of 50 m range. The former one is intended as primary standard for the calibration of geodetic instrumentation with low uncertainty to the SI definition of the metre. The latter one is intended for monitoring larger monuments like VLBI antennas. In this contribution, we describe the technical challenges and our solutions for such instrumentation. We use the two-colour method for inline refractive index compensation. As common optical source, we developed a versatile multi-wavelength generator based on two Nd:YAG lasers stabilised by a phase-locked loop realised by Field Programmable Gate Arrays (FPGA). The 1D interferometer uses custom-designed achromatic optics and a mechanical frame optimised for form stability under field conditions. The phase demodulation system allows for maximum range flexibility from several meters up to several kilometres. The base ranging unit of the 3D multilateration system adheres to a different demodulation technique, which allows a relatively simple interferometer head design. This approach requires a sophisticated source modulation scheme limiting the applicability to distances over 15 m up to approximately 50 m in our case.
{"title":"Two multi-wavelength interferometers for large-scale surveying","authors":"Anni Sauthoff, P. Köchert, G. Prellinger, T. Meyer, F. Pilarski, S. Weinrich, F. Schmaljohann, J. Guillory, D. Truong, Jakob Silbermann, U. Kallio, J. Jokela, F. Pollinger","doi":"10.4995/jisdm2022.2022.13635","DOIUrl":"https://doi.org/10.4995/jisdm2022.2022.13635","url":null,"abstract":"Deformation monitoring requires the detection of smallest changes, always at the limits of technical feasibility. Trying to push these limits further, we have realised two terrestrial ranging instruments: a long-range 1D electro-optic distance meter and a 3D multilateration-capable sensor system of 50 m range. The former one is intended as primary standard for the calibration of geodetic instrumentation with low uncertainty to the SI definition of the metre. The latter one is intended for monitoring larger monuments like VLBI antennas. In this contribution, we describe the technical challenges and our solutions for such instrumentation. We use the two-colour method for inline refractive index compensation. As common optical source, we developed a versatile multi-wavelength generator based on two Nd:YAG lasers stabilised by a phase-locked loop realised by Field Programmable Gate Arrays (FPGA). The 1D interferometer uses custom-designed achromatic optics and a mechanical frame optimised for form stability under field conditions. The phase demodulation system allows for maximum range flexibility from several meters up to several kilometres. The base ranging unit of the 3D multilateration system adheres to a different demodulation technique, which allows a relatively simple interferometer head design. This approach requires a sophisticated source modulation scheme limiting the applicability to distances over 15 m up to approximately 50 m in our case.","PeriodicalId":404487,"journal":{"name":"Proceedings of the 5th Joint International Symposium on Deformation Monitoring - JISDM 2022","volume":"AES-22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126556905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-20DOI: 10.4995/jisdm2022.2022.13837
M. Atanasova, H. Nikolov, I. Georgiev, A. Ivanov
The Bulgarian northern Black Sea coast is affected by many landslides. Landslide research is important as these phenomena cause loss of human lives and infrastructural damages. For this study a landslide area called "Dalgiya yar" was selected. The objective of this study is to provide solid grounds for monitoring the landslide processes using GNSS and SAR data. To achieve the set goals a geodynamic network was established. Those networks consist generally of two types of points – reference (located on geologically stable terrain) and survey points located within the landslide. The overall deformation analysis of the geodynamic networks is done after the third measurement cycle. The main approach to obtain the final results is based on determination of deformation components of spatially oriented triangles. For the studied period and for the mentioned area three main types of deformations have been determined by Finite Elements Method – station displacements, relative side deformations and relative principal deformations. It needs to be mentioned that due to peculiarities of the researched zone the condition that the final elements must to be configured approximately as equilateral triangles with approximately equal areas and not overlapping was not possible to be met. This is the reason to complement the GNNS results with such produced by DInSAR processing of Sentinel-1 data for the mentioned periods.
{"title":"Deformation analysis in landslides NE Bulgaria using GNSS data complemented by InSAR for better interpretation results","authors":"M. Atanasova, H. Nikolov, I. Georgiev, A. Ivanov","doi":"10.4995/jisdm2022.2022.13837","DOIUrl":"https://doi.org/10.4995/jisdm2022.2022.13837","url":null,"abstract":"The Bulgarian northern Black Sea coast is affected by many landslides. Landslide research is important as these phenomena cause loss of human lives and infrastructural damages. For this study a landslide area called \"Dalgiya yar\" was selected. The objective of this study is to provide solid grounds for monitoring the landslide processes using GNSS and SAR data. To achieve the set goals a geodynamic network was established. Those networks consist generally of two types of points – reference (located on geologically stable terrain) and survey points located within the landslide. The overall deformation analysis of the geodynamic networks is done after the third measurement cycle. The main approach to obtain the final results is based on determination of deformation components of spatially oriented triangles. For the studied period and for the mentioned area three main types of deformations have been determined by Finite Elements Method – station displacements, relative side deformations and relative principal deformations. It needs to be mentioned that due to peculiarities of the researched zone the condition that the final elements must to be configured approximately as equilateral triangles with approximately equal areas and not overlapping was not possible to be met. This is the reason to complement the GNNS results with such produced by DInSAR processing of Sentinel-1 data for the mentioned periods.","PeriodicalId":404487,"journal":{"name":"Proceedings of the 5th Joint International Symposium on Deformation Monitoring - JISDM 2022","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116653293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-20DOI: 10.4995/jisdm2022.2022.13828
L. Parente, C. Castagnetti, Eugenia Falvo, F. Grassi, F. Mancini, P. Rossi, A. Capra
Development of automated and remotely controlled procedures for accurate crack detection and analysis is an advantageous solution when compared to time-consuming and subjective crack examination conducted by operators. Recent studies have demonstrated that Machine Learning (ML) algorithms have sufficient potential for crack measurements. However, training of large amount of data is essential. When working on single sites with permanently installed fixed cameras adoption of ML solutions may be redundant. The purpose of this work is to assess the performance of a procedure for crack detection based on an easy to implement workflow supported by the use of ML and image processing algorithms. The datasets used in this work are composed of temporal sequence of single digital images. The workflow proposed includes three main modules covering acquisition, optimization and crack detection. Each module is automated and basic manual input by an operator is only required to train the classifier. The processing modules are implemented in modular open-source programs (e.g., ImageJ and Ilastik). Results obtained in controlled conditions led to a satisfactory level of detection (about 99% of the crack pattern detected). Experiments conducted on real-sites highlighted variable detection capabilities of the proposed approach (from 12 to 96%). The main limitation of the approach is the production of false-positive detection due to significant variation in illumination conditions. Further work is being conducted to define scalability of the approach and to verify deformation detection capabilities.
{"title":"Towards an automated machine learning and image processing supported procedure for crack monitoring","authors":"L. Parente, C. Castagnetti, Eugenia Falvo, F. Grassi, F. Mancini, P. Rossi, A. Capra","doi":"10.4995/jisdm2022.2022.13828","DOIUrl":"https://doi.org/10.4995/jisdm2022.2022.13828","url":null,"abstract":"Development of automated and remotely controlled procedures for accurate crack detection and analysis is an advantageous solution when compared to time-consuming and subjective crack examination conducted by operators. Recent studies have demonstrated that Machine Learning (ML) algorithms have sufficient potential for crack measurements. However, training of large amount of data is essential. When working on single sites with permanently installed fixed cameras adoption of ML solutions may be redundant. The purpose of this work is to assess the performance of a procedure for crack detection based on an easy to implement workflow supported by the use of ML and image processing algorithms. The datasets used in this work are composed of temporal sequence of single digital images. The workflow proposed includes three main modules covering acquisition, optimization and crack detection. Each module is automated and basic manual input by an operator is only required to train the classifier. The processing modules are implemented in modular open-source programs (e.g., ImageJ and Ilastik). Results obtained in controlled conditions led to a satisfactory level of detection (about 99% of the crack pattern detected). Experiments conducted on real-sites highlighted variable detection capabilities of the proposed approach (from 12 to 96%). The main limitation of the approach is the production of false-positive detection due to significant variation in illumination conditions. Further work is being conducted to define scalability of the approach and to verify deformation detection capabilities.","PeriodicalId":404487,"journal":{"name":"Proceedings of the 5th Joint International Symposium on Deformation Monitoring - JISDM 2022","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125167757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-20DOI: 10.4995/jisdm2022.2022.13649
D. Schröder, K. Anders, L. Winiwarter, D. Wujanz
The objective of this work is the development of an integrated monitoring service for the identification and evaluation of ground surface and slope movements in the context of coal mining, the prevention of natural hazards and protection of infrastructure. The focus is set on the integration of a long-range terrestrial laser scanner into a continuous monitoring system from an engineering geodetic point of view. In the Vals valley in Tyrol, a permanently installed laser scanner was successfully operated via a web portal to monitor surface processes in the area of rockfall debris on a high-mountain slope in the summers of 2020 and 2021. This paper describes the practical benefits of this permanent laser scanning installation. In addition to the potentials of automatic data acquisition, possibilities for multitemporal analysis with respect to spatio-temporally variable changes are presented, using advanced 3D change detection with Kalman filtering. The level of detection for deformation analyses therein depends on the quality of the georeferencing of the sensor and the noise within the measured point cloud. We identify and discuss temporally variable artifacts within the data based on different methods of georeferencing. Finally, we apply our change detection method on these multitemporal data to extract specific information regarding the observed geomorphologic processes.
{"title":"Permanent terrestrial LiDAR monitoring in mining, natural hazard prevention and infrastructure protection – Chances, risks, and challenges: A case study of a rockfall in Tyrol, Austria","authors":"D. Schröder, K. Anders, L. Winiwarter, D. Wujanz","doi":"10.4995/jisdm2022.2022.13649","DOIUrl":"https://doi.org/10.4995/jisdm2022.2022.13649","url":null,"abstract":"The objective of this work is the development of an integrated monitoring service for the identification and evaluation of ground surface and slope movements in the context of coal mining, the prevention of natural hazards and protection of infrastructure. The focus is set on the integration of a long-range terrestrial laser scanner into a continuous monitoring system from an engineering geodetic point of view. In the Vals valley in Tyrol, a permanently installed laser scanner was successfully operated via a web portal to monitor surface processes in the area of rockfall debris on a high-mountain slope in the summers of 2020 and 2021. This paper describes the practical benefits of this permanent laser scanning installation. In addition to the potentials of automatic data acquisition, possibilities for multitemporal analysis with respect to spatio-temporally variable changes are presented, using advanced 3D change detection with Kalman filtering. The level of detection for deformation analyses therein depends on the quality of the georeferencing of the sensor and the noise within the measured point cloud. We identify and discuss temporally variable artifacts within the data based on different methods of georeferencing. Finally, we apply our change detection method on these multitemporal data to extract specific information regarding the observed geomorphologic processes.","PeriodicalId":404487,"journal":{"name":"Proceedings of the 5th Joint International Symposium on Deformation Monitoring - JISDM 2022","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127757276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-20DOI: 10.4995/jisdm2022.2022.13787
F. Cartiaux, G. Olivetti, Valeria Fort, P. Pelletier
The Italian peninsula has numerous heritage structures, including fifty-five sites registered under the UNESCO World Heritage Convention, living testimonies of the passage of man through times. Heritage structures are subject to aging and impact from the climate, resulting in deterioration of the structural behaviour. These phenomena can significantly reduce their usability, or even undermine the stability, and eventually induce safety, and rehabilitation issues. For those primary reasons, increasing attention is given by local authorities to understand the behaviour of structures and take the right action at the right time. To preserve the cultural heritage, Structural Health Monitoring (SHM) is becoming more important, as it allows to follow the evolution of structural behaviour. The study of meaningful variables allows to identify the activated structural mechanisms and, consequently, implement timely actions against ongoing degradation phenomena. A notable example is represented by the activities undertaken by the Municipality of Bologna on the Torre della Garisenda. The structure is monitored since 2019 to study the behaviour of its basement through measurements collected by deformation and temperature sensors. The installed monitoring system allows to carry out numerous analyses: evaluation of the structural response under dynamic actions, study of the evolution of the static behaviour of the tower and analysis of the effects induced by seasonal thermal variations. Advanced algorithms for data analysis allow to develop critical analysis and interpretation on the obtained results, providing information to support decision making process. Indications on the functionality of the system and typical examples of the collected results are provided.
意大利半岛拥有众多的遗产建筑，其中55处被联合国教科文组织列入世界遗产公约，是人类穿越时代的活生生的见证。遗产结构受到老化和气候的影响，导致结构性能的恶化。这些现象会显著降低它们的可用性，甚至破坏稳定性，并最终导致安全性和修复问题。由于这些主要原因，地方当局越来越重视了解结构的行为，并在正确的时间采取正确的行动。为了保护文化遗产，结构健康监测(SHM)变得越来越重要，因为它允许跟踪结构行为的演变。对有意义的变量进行研究，可以确定激活的结构机制，从而及时采取行动，防止正在发生的退化现象。博洛尼亚市政府在Torre della Garisenda上开展的活动就是一个显著的例子。自2019年以来，该结构一直受到监测，通过变形和温度传感器收集的测量数据研究其基底的行为。安装的监测系统允许进行许多分析:评估结构在动态作用下的反应，研究塔的静态行为的演变，分析季节性热变化引起的影响。先进的数据分析算法允许对获得的结果进行批判性分析和解释，为支持决策过程提供信息。提供了系统功能的指示和收集结果的典型示例。
{"title":"Preserving the heritage of world’s monuments through Structural Health Monitoring – A case study: the Garisenda Tower","authors":"F. Cartiaux, G. Olivetti, Valeria Fort, P. Pelletier","doi":"10.4995/jisdm2022.2022.13787","DOIUrl":"https://doi.org/10.4995/jisdm2022.2022.13787","url":null,"abstract":"The Italian peninsula has numerous heritage structures, including fifty-five sites registered under the UNESCO World Heritage Convention, living testimonies of the passage of man through times. Heritage structures are subject to aging and impact from the climate, resulting in deterioration of the structural behaviour. These phenomena can significantly reduce their usability, or even undermine the stability, and eventually induce safety, and rehabilitation issues. For those primary reasons, increasing attention is given by local authorities to understand the behaviour of structures and take the right action at the right time. To preserve the cultural heritage, Structural Health Monitoring (SHM) is becoming more important, as it allows to follow the evolution of structural behaviour. The study of meaningful variables allows to identify the activated structural mechanisms and, consequently, implement timely actions against ongoing degradation phenomena. A notable example is represented by the activities undertaken by the Municipality of Bologna on the Torre della Garisenda. The structure is monitored since 2019 to study the behaviour of its basement through measurements collected by deformation and temperature sensors. The installed monitoring system allows to carry out numerous analyses: evaluation of the structural response under dynamic actions, study of the evolution of the static behaviour of the tower and analysis of the effects induced by seasonal thermal variations. Advanced algorithms for data analysis allow to develop critical analysis and interpretation on the obtained results, providing information to support decision making process. Indications on the functionality of the system and typical examples of the collected results are provided.","PeriodicalId":404487,"journal":{"name":"Proceedings of the 5th Joint International Symposium on Deformation Monitoring - JISDM 2022","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116727769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-20DOI: 10.4995/jisdm2022.2022.13868
D. Bolkas, M. O'Banion, Jakeb Prickett, Gregory Ellsworth, Gerald Rusek, Hannah J. Corson
Monitoring of dams is an essential surveying task to guarantee the safety of operation and understand the physical processes concerning their movement. Point cloud generating technologies are increasingly being utilized for monitoring of engineered structures. This paper compares point clouds acquired from terrestrial laser scanning (TLS) and small unmanned aerial systems (sUAS)-based photogrammetry for monitoring of the Francis E. Walter dam in northeast Pennsylvania. Authorized for construction by the Flood Control Act of 1946, and with renewed interest due to extensive flooding in 1955 caused by the back-to-back hurricanes Connie and Diane, this earth-filled embankment dam was completed in June of 1961 by the U.S. Army Corps of Engineers. It is currently operated in conjunction with Beltzville Lake for stage reductions on the Lehigh River. The dam is being monitored through conventional surveying methods (total station) every five years. In spring of 2021 a TLS and sUAS data acquisition took place to assess the feasibility and utility of using modern point cloud technologies for monitoring. This paper presents a comprehensive comparison and accuracy assessment of the two point cloud collection methods, considering several parameters for the generation of the sUAS photogrammetric point cloud. Results show the advantages and disadvantages of the two methods. For instance, TLS offers high accuracy (cm-level), but suffers from data gaps due to line of sight blockage/occlusion. On the other hand, sUAS photogrammetry offers more complete point clouds, but presents more challenges in georeferencing and in the generation of accurate point clouds. Similar insights and lessons learned are useful for future surveying tasks and monitoring of similar embankment dam structures.
{"title":"Comparison of TLS and sUAS point clouds for monitoring embankment dams","authors":"D. Bolkas, M. O'Banion, Jakeb Prickett, Gregory Ellsworth, Gerald Rusek, Hannah J. Corson","doi":"10.4995/jisdm2022.2022.13868","DOIUrl":"https://doi.org/10.4995/jisdm2022.2022.13868","url":null,"abstract":"Monitoring of dams is an essential surveying task to guarantee the safety of operation and understand the physical processes concerning their movement. Point cloud generating technologies are increasingly being utilized for monitoring of engineered structures. This paper compares point clouds acquired from terrestrial laser scanning (TLS) and small unmanned aerial systems (sUAS)-based photogrammetry for monitoring of the Francis E. Walter dam in northeast Pennsylvania. Authorized for construction by the Flood Control Act of 1946, and with renewed interest due to extensive flooding in 1955 caused by the back-to-back hurricanes Connie and Diane, this earth-filled embankment dam was completed in June of 1961 by the U.S. Army Corps of Engineers. It is currently operated in conjunction with Beltzville Lake for stage reductions on the Lehigh River. The dam is being monitored through conventional surveying methods (total station) every five years. In spring of 2021 a TLS and sUAS data acquisition took place to assess the feasibility and utility of using modern point cloud technologies for monitoring. This paper presents a comprehensive comparison and accuracy assessment of the two point cloud collection methods, considering several parameters for the generation of the sUAS photogrammetric point cloud. Results show the advantages and disadvantages of the two methods. For instance, TLS offers high accuracy (cm-level), but suffers from data gaps due to line of sight blockage/occlusion. On the other hand, sUAS photogrammetry offers more complete point clouds, but presents more challenges in georeferencing and in the generation of accurate point clouds. Similar insights and lessons learned are useful for future surveying tasks and monitoring of similar embankment dam structures.","PeriodicalId":404487,"journal":{"name":"Proceedings of the 5th Joint International Symposium on Deformation Monitoring - JISDM 2022","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122107600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-20DOI: 10.4995/jisdm2022.2022.13836
M. Henriques, D. Roque
Like in other surveying works, UAV flights require prior work that involves flight planning and equipment preparation and, often, many complementary tasks. These may involve bringing together technicians from different domains, booking a car and possibly accommodation, and some time-consuming complementary bureaucratic work. Teams operating UAVs know how much the flights are affected by weather conditions. The wind is the weather variable that, in proportion (number of occurrences per year), causes the major number of changes to a scheduled work. Obtaining reliable information about the intensity of the wind, a few days in advance, is an asset for those who have to carry out the various tasks mentioned previously. There are several websites from which one can access weather forecasts. Is any website better because it presents more reliable data? The data and the analysis presented in the paper will give some clues. The data includes wind speed, registered daily, at 12:00 (pm) for a year, by a meteorological station with online data, which belongs to a meteorological institute. Also on a daily basis, several websites with meteorological data were consulted, and wind speed forecasts for the same hour for up to four days in advance were collected. An analysis of the data can provide information about whether there is a website that stands out for the quality of the forecasts, and if there is a need to consult several websites to have better information.
{"title":"Planning UAV surveys: can we rely on wind forecasts?","authors":"M. Henriques, D. Roque","doi":"10.4995/jisdm2022.2022.13836","DOIUrl":"https://doi.org/10.4995/jisdm2022.2022.13836","url":null,"abstract":"Like in other surveying works, UAV flights require prior work that involves flight planning and equipment preparation and, often, many complementary tasks. These may involve bringing together technicians from different domains, booking a car and possibly accommodation, and some time-consuming complementary bureaucratic work. Teams operating UAVs know how much the flights are affected by weather conditions. The wind is the weather variable that, in proportion (number of occurrences per year), causes the major number of changes to a scheduled work. Obtaining reliable information about the intensity of the wind, a few days in advance, is an asset for those who have to carry out the various tasks mentioned previously. There are several websites from which one can access weather forecasts. Is any website better because it presents more reliable data? The data and the analysis presented in the paper will give some clues. The data includes wind speed, registered daily, at 12:00 (pm) for a year, by a meteorological station with online data, which belongs to a meteorological institute. Also on a daily basis, several websites with meteorological data were consulted, and wind speed forecasts for the same hour for up to four days in advance were collected. An analysis of the data can provide information about whether there is a website that stands out for the quality of the forecasts, and if there is a need to consult several websites to have better information.","PeriodicalId":404487,"journal":{"name":"Proceedings of the 5th Joint International Symposium on Deformation Monitoring - JISDM 2022","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133627303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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