Infrared thermography‐based diagnostics on power equipment: State‐of‐the‐art

Abstract

As a non‐contact temperature distribution measurement method, infrared thermography (IRT) has emerged as an indispensable tool in condition monitoring and fault diagnosis of electrical equipment based on the absolute and relative temperature values. Manual fault inspection, as an expert‐experiences based evaluation method, has formed a mature technical scheme with a large number of application cases. However, the efficiency and accuracy of manual fault inspection are being challenged by the rapid growth in the number of equipment in power grid. The situation is improving with the advanced of image processing technique. Machine‐assisted fault diagnosis provides a novel method to assist human beings to complete fault diagnosis under the intervention of human prior knowledge. However, the limitations of infrared images bring challenges to image analysis processing especially target detection. In pursuit of automatic fault diagnosis, deep learning algorithms are introduced to achieve target detection in the complex environment. This study reviews the development of IRT‐based diagnostics beginning with the general procedures, objects, and limitations of IRT‐based fault inspection, and then gives an insight into the popular machine‐assisted fault diagnosis as well as image‐based intelligent fault identification. In addition, the future recommendations of IRT are also provided from construction of intelligent infrared detection system, establishment of an open and shared infrared image database and comprehensive utilization of joint visualization diagnosis technology.

Thermal imaging and clandestine surveillance using low-cost polymers with long-wave infrared transparency

“…Infrared imaging is a rapidly growing field with established uses in surveillance (1), and in the medical (2), agricultural (3), and civil (4) and electrical engineering sectors (5). More recently, infrared imaging has become integral to navigation of drones (6) and autonomous vehicles (7), as well as space exploration (8).…”

A review of indoor-orbital electrical inspection robots in substations

“…The artificial intelligence fault diagnosis system can identify the image to obtain the maximum temperature, and then set the corresponding thresholds for the different devices. When the temperature exceeds this threshold or there is a large difference between the threshold temperature and the measured temperature, the diagnostic system will raise the alarm (Cheng and Xiang, 2019; Allan and Beaudry, 2014; Xia et al , 2021; Luo et al , 2021; Cui et al , 2013). The flow chart of the thermal image recognition is shown in Figure 18.…”

A Spatiotemporal Deep Neural Network Useful for Defect Identification and Reconstruction of Artworks Using Infrared Thermography

“…IRT is widely used in a variety of industries, from the aviation industry [ 12 ] to civil engineering [ 13 ], from stress analysis [ 14 ] to damage characterization [ 15 ], from diagnostics [ 16 ] to prognostics [ 17 ]. Owing to its advantages, this NDT method is also one of the most beneficial inspections for cultural heritage assets, a topic that is gaining more and more attention and progress [ 18 ].…”