A Model to Extract Wind Influence From Outdoor IR Thermal Inspections

Bortoni, Edson C.; Santos, Laerte dos

doi:10.1109/tpwrd.2013.2261692

Cited by 7 publications

(4 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Further limitations are determined by the load conditions of the power line and solar radiation, which may not heat the deteriorated joint sufficiently to be detectable by thermographic methods or mask internal heat. In [125,126], possible techniques to improve the thermal image analysis are presented. The first proposes the modeling of the wind influence, to evaluate its effect on the results of the external thermographic inspection.…”

Section: New Prognostic Systems For High-voltage Linesmentioning

confidence: 99%

A Comprehensive Review of Fault Diagnosis and Prognosis Techniques in High Voltage and Medium Voltage Electrical Power Lines

Bindi,

Piccirilli,

Luchetta

et al. 2023

Energies

View full text Add to dashboard Cite

This paper presents an extensive review of the most effective and modern monitoring methods for electrical power lines, with particular attention to high-voltage (HV) and medium-voltage (MV) systems. From a general point of view, the main objective of these techniques is to prevent catastrophic failures by detecting the partial damage or deterioration of components and allowing maintenance operations to be organized. In fact, the protection devices commonly used in transmission and distribution networks guarantee the location of faults, such as short-circuits, putting the non-functioning branch of the network out of service. Nowadays, alongside these devices, it is possible to introduce new intelligent algorithms capable of avoiding the total loss of functionality, thus improving the reliability of the entire network. This is one of the main challenges in modern smart grids, which are characterized by the massive integration of renewable energy sources and a high level of complexity. Therefore, in the first part of this paper, a general overview of the most common protection devices is proposed, followed by an analysis of the most modern prevention algorithms. In the first case, the coordination of the relays plays a fundamental role in obtaining the fault location with a high level of selectivity, while in the field of preventive analysis, it is necessary to address the implementation of artificial intelligence methods. The techniques presented in this paper provide a comprehensive description of the different monitoring approaches currently used in distribution and transmission lines, highlighting the coordination of protection relays, the computational algorithms capable of preventing failures, and the influence of the distributed generation in their management. Therefore, this paper offers an overview of the main diagnostic techniques and protection devices, highlights the critical issues that can be overcome through the introduction of artificial intelligence, and describes the main prognostic methods, focusing on their invasive level and the possibility of operating directly online. This work also highlights the main guidelines for the classification and choice between the different approaches.

show abstract

Section: New Prognostic Systems For High-voltage Linesmentioning

confidence: 99%

A Comprehensive Review of Fault Diagnosis and Prognosis Techniques in High Voltage and Medium Voltage Electrical Power Lines

Bindi,

Piccirilli,

Luchetta

et al. 2023

Energies

View full text Add to dashboard Cite

show abstract

“…In possession of the intrinsic matrix K v ∈ R 3x3 for the RGB-R image containing the focus and principal point values f , c x and c y , respectively, the points P v i from C v k can be projected into the image plane to its respective pixel location p v in homogeneous coordinates as in Equation (11). Again, to get final coordinates, one must divide the result by w v and get p v , following Equation (3).…”

Section: Point Cloud Generationmentioning

confidence: 99%

“…According to Reference [ 6 ], bad connections, unbalanced loading, excessive use, or wear out are some of the factors that cause thermal stress in electrical components, which can be detected by hotspots in thermal images. Thermal cameras and 3D thermal models have already been used, separately, in a wide range of applications, such as in the sectors of building inspection [ 7 , 8 ], defect detection [ 9 ], and energy efficiency analysis [ 10 , 11 ]. However, just a few works have already applied the combination of 3D modeling with thermal data, for example, Reference [ 12 ], which still are limited and not used in an online fashion.…”

Section: Introductionmentioning

confidence: 99%

Sensors Fusion and Multidimensional Point Cloud Analysis for Electrical Power System Inspection

Vidal

Honório

Dias

et al. 2020

Sensors

View full text Add to dashboard Cite

Thermal inspection is a powerful tool that enables the diagnosis of several components at its early stages. One critical aspect that influences thermal inspection outputs is the infrared reflection from external sources. This situation may change the readings, demanding that an expert correctly define the camera position, which is a time consuming and expensive operation. To mitigate this problem, this work proposes an autonomous system capable of identifying infrared reflections by filtering and fusing data obtained from both stereo and thermal cameras. The process starts by acquiring readings from multiples Observation Points (OPs) where, at each OP, the system processes the 3D point cloud and thermal image by fusing them together. The result is a dense point cloud where each point has its spatial position and temperature. Considering that each point’s information is acquired from multiple poses, it is possible to generate a temperature profile of each spatial point and filter undesirable readings caused by interference and other phenomena. To deploy and test this approach, a Directional Robotic System (DRS) is mounted over a traditional human-operated service vehicle. In that way, the DRS autonomously tracks and inspects any desirable equipment as the service vehicle passes them by. To demonstrate the results, this work presents the algorithm workflow, a proof of concept, and a real application result, showing improved performance in real-life conditions.

show abstract

“…The thermal analysis provides relevant information about the status of different mechanisms mounted on a transmission grid [20]. Currently, this process is carried out with a wide range of real-time monitoring devices that determine the dynamic thermal rating of a transmission grid [20][21][22] and are mounted on the line. The use of UAVs, coupled with infrared imaging could be used to autonomously detect failing components or insulator leakage currents [23].…”

Section: Introductionmentioning

confidence: 99%

Visual-Based Positioning of Aerial Maintenance Platforms on Overhead Transmission Lines

2019

View full text Add to dashboard Cite

Unmanned aerial vehicles (UAVs) are an emerging and promising alternative for monitoring of transmission lines in terms of flexibility, complexity, working speed, and cost. One of the main challenges is to enable UAVs to become as autonomous as possible. A vital component toward this direction is the robust and accurate estimation of the UAV placement with respect to the transmission grid. This work faces this challenge by developing a transmission line autonomous tracking system, which allows the placement of a commercial drone over a transmission grid using a monocular camera. This feature provides accurate positioning for the vehicle even where the Global navigation satellite system (GNSS) signal is denied, enabling to report the status of transmission lines, at any time. The system isolates transmission grid conductors in each acquired RGB-image using an image-processing algorithm based on Hough transform, morphological operations, and Gabor filters. With this information, the system computes the location of the UAV using a geometric approach that relates transmission lines building parameter and optical geometry. However, it has the problem of gradual error accumulation when the drone moves. In this regards, the estimated position of the drone is computed by the maximum likelihood estimation (MLE) by the position information estimated by visual-system, the inertial measurement unit (IMU) and GNSS. The proposed positioning system showed an efficiency of 91.44% in field experimentation in the extraction of transmission conductor, with a root mean square the error of 0.18 m in the UAV localization.

show abstract

A Model to Extract Wind Influence From Outdoor IR Thermal Inspections

Cited by 7 publications

References 5 publications

A Comprehensive Review of Fault Diagnosis and Prognosis Techniques in High Voltage and Medium Voltage Electrical Power Lines

A Comprehensive Review of Fault Diagnosis and Prognosis Techniques in High Voltage and Medium Voltage Electrical Power Lines

Sensors Fusion and Multidimensional Point Cloud Analysis for Electrical Power System Inspection

Visual-Based Positioning of Aerial Maintenance Platforms on Overhead Transmission Lines

Contact Info

Product

Resources

About