Fusion of Real Time Thermal Image and 1D/2D/3D Depth Laser Readings for Remote Thermal Sensing in Industrial Plants by Means of UAVs and/or Robots

This paper presents fast procedures for thermal infrared remote sensing in dark, GPS-denied environments, such as those found in industrial plants such as in High-Voltage Direct Current (HVDC) converter stations. These procedures are based on the combination of the depth estimation obtained from either a 1-Dimensional LIDAR laser or a 2-Dimensional Hokuyo laser or a 3D MultiSense SLB laser sensor and the visible and thermal cameras from a FLIR Duo R dual-sensor thermal camera. The combination of these sensors/cameras is suitable to be mounted on Unmanned Aerial Vehicles (UAVs) and/or robots in order to provide reliable information about the potential malfunctions, which can be found within the hazardous environment. For example, the capabilities of the developed software and hardware system corresponding to the combination of the 1-D LIDAR sensor and the FLIR Duo R dual-sensor thermal camera is assessed from the point of the accuracy of results and the required computational times: the obtained computational times are under 10 ms, with a maximum localization error of 8 mm and an average standard deviation for the measured temperatures of 1.11 degree Celsius, which results are obtained for a number of test cases. The paper is structured as follows: the description of the system used for identification and localization of hotspots in industrial plants is presented in section II. In section III, the method for faults identification and localization in plants by using a 1-Dimensional LIDAR laser sensor and thermal images is described together with results. In section IV the real time thermal image processing is presented. Fusion of the 2-Dimensional depth laser Hokuyo and the thermal images is described in section V. In section VI the combination of the 3D MultiSense SLB laser and thermal images is described. In section VII a discussion and several conclusions are drawn

Registro espacial 2D–3D para a inspeção remota de subestações de energia

Remote inspection and supervisory control are critical features for smart factories, civilian surveillance, power systems, among other domains. For reducing the time to make decisions, operators must have both a high situation awareness, implying a considerable amount of data to be presented, and minimal sensory load. Recent research suggests the adoption of computer vision techniques for automatic inspection, as well as virtual reality (VR) as an alternative to traditional SCADA interfaces. Nevertheless, although VR may provide a good representation of a substation’s state, it lacks some real-time information, available from online field cameras and microphones. Since these two sources of information (VR and field information) are not integrated into one single solution, we miss the opportunity of using VR as a SCADA-aware remote inspection tool, during operation and disaster-response routines. This work discusses a method to augment virtual environments of power substations with field images, enabling operators to promptly see a virtual representation of the inspected area's surroundings. The resulting environment is integrated with an image-based state inference machine, continuously checking the inferred states against the ones reported by the SCADA database. Whenever a discrepancy is found, an alarm is triggered and the virtual camera can be immediately teleported to the affected region, speeding up system reestablishment. The solution is based on a client-server architecture and allows multiple cameras deployed in multiple substations. Our results concern the quality of the 2D–3D registration and the rendering framerate for a simple scenario. The collected quantitative metrics suggest good camera pose estimations and registrations, as well as an arguably optimal rendering framerate for substations' equipment inspection.CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível SuperiorCEMIG - Companhia Energética de Minas GeraisCNPq - Conselho Nacional de Desenvolvimento Científico e TecnológicoFAPEMIG - Fundação de Amparo a Pesquisa do Estado de Minas GeraisTese (Doutorado)A inspeção remota e o controle supervisório são requisitos críticos para fábricas modernas, vigilância de civis, sistemas de energia e outras áreas. Para reduzir o tempo da tomada de decisão, os operadores precisam de uma elevada consciência da situação em campo, o que implica em uma grande quantidade de dados a serem apresentados, mas com menor carga sensorial possível. Estudos recentes sugerem a adoção de técnicas de visão computacional para inspeção automática, e a Realidade Virtual (VR) como uma alternativa às interfaces tradicionais do SCADA. Entretanto, apesar de fornecer uma boa representação do estado da subestação, os ambientes virtuais carecem de algumas informações de campo, provenientes de câmeras e microfones. Como essas duas fontes de dados (VR e dispositivos de captura) não são integrados em uma única solução, perde-se a oportunidade de usar VR como uma ferramenta de inspeção remota conectada ao SCADA, durante a operação e rotinas de respostas a desastres. Este trabalho trata de um método para aumentar ambientes virtuais de subestações com imagens de campo, permitindo aos operadores a rápida visualização de uma representação virtual do entorno da área monitorada. O ambiente resultante é integrado com uma máquina de inferência estados por imagens, comparando continuamente os estados inferidos com aqueles reportados pela base SCADA. Na ocasião de uma discrepância, um alarme é gerado e possibilita que a câmera virtual seja imediatamente teletransportada para a região afetada, acelerando o processo de retomada do sistema. A solução se baseia em uma arquitetura cliente-servidor e permite múltiplas câmeras presentes em múltiplas subestações. Os resultados dizem respeito à qualidade do registro 2D–3D e à taxa de renderização para um cenário simples. As métricas quantitativas coletadas sugerem bons níveis de registro e estimativa de pose de câmera, além de uma taxa ótima de renderização para fins de inspeção de equipamentos em subestações

Remote Sensing methods for power line corridor surveys

AbstractTo secure uninterrupted distribution of electricity, effective monitoring and maintenance of power lines are needed. This literature review article aims to give a wide overview of the possibilities provided by modern remote sensing sensors in power line corridor surveys and to discuss the potential and limitations of different approaches. Monitoring of both power line components and vegetation around them is included. Remotely sensed data sources discussed in the review include synthetic aperture radar (SAR) images, optical satellite and aerial images, thermal images, airborne laser scanner (ALS) data, land-based mobile mapping data, and unmanned aerial vehicle (UAV) data. The review shows that most previous studies have concentrated on the mapping and analysis of network components. In particular, automated extraction of power line conductors has achieved much attention, and promising results have been reported. For example, accuracy levels above 90% have been presented for the extraction of conductors from ALS data or aerial images. However, in many studies datasets have been small and numerical quality analyses have been omitted. Mapping of vegetation near power lines has been a less common research topic than mapping of the components, but several studies have also been carried out in this field, especially using optical aerial and satellite images. Based on the review we conclude that in future research more attention should be given to an integrated use of various data sources to benefit from the various techniques in an optimal way. Knowledge in related fields, such as vegetation monitoring from ALS, SAR and optical image data should be better exploited to develop useful monitoring approaches. Special attention should be given to rapidly developing remote sensing techniques such as UAVs and laser scanning from airborne and land-based platforms. To demonstrate and verify the capabilities of automated monitoring approaches, large tests in various environments and practical monitoring conditions are needed. These should include careful quality analyses and comparisons between different data sources, methods and individual algorithms

Automatic Multi-source Data Fusion Technique of Powerline Corridor using UAV Lidar

China Southern Power Grid Key Technology of High Performance Integrated Small Intelligent Transmission UAV (GDKJXM20198187)

Multi-Class Simultaneous Adaptive Segmentation and Quality Control of Point Cloud Data

3D modeling of a given site is an important activity for a wide range of applications including urban planning, as-built mapping of industrial sites, heritage documentation, military simulation, and outdoor/indoor analysis of airflow. Point clouds, which could be either derived from passive or active imaging systems, are an important source for 3D modeling. Such point clouds need to undergo a sequence of data processing steps to derive the necessary information for the 3D modeling process. Segmentation is usually the first step in the data processing chain. This paper presents a region-growing multi-class simultaneous segmentation procedure, where planar, pole-like, and rough regions are identified while considering the internal characteristics (i.e., local point density/spacing and noise level) of the point cloud in question. The segmentation starts with point cloud organization into a kd-tree data structure and characterization process to estimate the local point density/spacing. Then, proceeding from randomly-distributed seed points, a set of seed regions is derived through distance-based region growing, which is followed by modeling of such seed regions into planar and pole-like features. Starting from optimally-selected seed regions, planar and pole-like features are then segmented. The paper also introduces a list of hypothesized artifacts/problems that might take place during the region-growing process. Finally, a quality control process is devised to detect, quantify, and mitigate instances of partially/fully misclassified planar and pole-like features. Experimental results from airborne and terrestrial laser scanning as well as image-based point clouds are presented to illustrate the performance of the proposed segmentation and quality control framework

Solar power generation in a mining town

Climate change is a pertinent issue facing governments and societies around the world. The industrial revolution has resulted in a steady increase in the average global temperature. The mining and energy production industries have been significant contributors to this change prompting governments to intervene by promoting low emission technology within these sectors. This thesis reviews the energy problem in Australia and the mining sector with a focus on the energy requirements and production methods utilised in Newman WA. BHP operate the largest open cut iron ore mine in the world requiring substantial amounts of energy to maintain. Renewable energy in the form of utility scale solar photovoltaics (PV) provides a solution to these problems by providing emission free energy which can be used to supplement the existing natural gas turbines in operation. This research presents a custom renewable solution for the Newman scenario considering the specific township network, local weather conditions and load profile. A summary of the required PV output is presented to supply slightly over 50% of the towns power requirements during the peak (summer) period, resulting in close to full coverage in the trough (winter) period. Power Factory is used to simulate the characteristics of the existing infrastructure and produces results of integrating PV. These results conclude that the problems requiring mitigation strategies unacceptable levels of harmonics and low power factor. Strategies are proposed to control these issues predominantly through the use of high quality, made for purpose inverters. Results show that use of inverters with harmonic filtering dramatically reduce the level of harmonic injections to an acceptable level according to Australian standards. Furthermore, the configuration of inverters to supply active and reactive power assist in mitigating low power factor problems