Effects of view angle and measurement distance on electrical equipment UV corona discharge detection

Cui, Haoyang; Huo, Sijia; Ma, Hongwei; Guo, Wencheng; Ge, Chen-Hang; Qin, Lunming

doi:10.1016/j.ijleo.2018.06.080

Cited by 9 publications

(4 citation statements)

References 11 publications

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“…As long as the speed of the detection instrument is sufficiently high and the response is fast enough, the electric signal proportional to the radiation flux can be detected. e electrical signal is amplified and converted, and the thermal image of the object to be measured is synthesized and presented on the display [9][10][11].…”

Section: Infraredmentioning

confidence: 99%

Thermal Fault Detection and Diagnosis of Electrical Equipment Based on the Infrared Image Segmentation Algorithm

2021

Advances in Multimedia

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With the advancement of social economy, electricity has gradually entered thousands of households and become a commonly used energy source. However, it cannot be ignored that electricity is dangerous in itself and should be used rationally and effectively. The fault detection of power equipment has become a top priority because they are essential tools for storing, transmitting, and transferring electric power. Based on infrared imaging technology, the principle of infrared imaging technology is introduced in this paper, and effective diagnosis methods are analyzed and summarized in detail. The effectiveness of the proposed infrared image segmentation algorithm is verified through the practical application of the infrared image segmentation algorithm in the detection of interior and exterior faults of electrical equipment.

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Section: Infraredmentioning

confidence: 99%

Thermal Fault Detection and Diagnosis of Electrical Equipment Based on the Infrared Image Segmentation Algorithm

2021

Advances in Multimedia

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“…Machine leaning can not only self-learn to improve the execution ability of a algorithm, but also summarize a large amount of data, which gives machine leaning a strong advantage in solving large-scale classification and recognition problems with unclear internal characteristics of the image. The figure is the machine leaning model proposed by Simon, a master in the field of artificial intelligence [34]. The process of machine leaning is follows: the environment provides input data to the learner, and then the learning algorithm inside the learner receives the data, analyzes the data and converts it into knowledge; the knowledge base receives and stores the knowledge, and the data in the knowledge base has an impact on the subsequent data input; after the executor completes the task, it feeds back the result to the learner, and then the learner analyzes the result and reacts; the process continues until the learning task of the given goal is completed, that is, a learner completes its training, which is shown in Fig.…”

Section: Ocr Algorithm Based On Machine Leaning 31 Recognition Princi...mentioning

confidence: 99%

Review of Optical Character Recognition for Power System Image Based on Artificial Intelligence Algorithm

Zhang¹,

Bai²,

Cui³

2023

Energy Engineering

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Optical Character Recognition (OCR) refers to a technology that uses image processing technology and character recognition algorithms to identify characters on an image. This paper is a deep study on the recognition effect of OCR based on Artificial Intelligence (AI) algorithms, in which the different AI algorithms for OCR analysis are classified and reviewed. Firstly, the mechanisms and characteristics of artificial neural network-based OCR are summarized. Secondly, this paper explores machine learning-based OCR, and draws the conclusion that the algorithms available for this form of OCR are still in their infancy, with low generalization and fixed recognition errors, albeit with better recognition effect and higher recognition accuracy. Finally, this paper explores several of the latest algorithms such as deep learning and pattern recognition algorithms. This paper concludes that OCR requires algorithms with higher recognition accuracy.

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“…Optical methods include ultraviolet sensing technology and fiber optic sensing technology. Ultraviolet sensing technology detects ultraviolet signals generated by partial discharge, effectively filtering out unwanted colors and enhancing ultraviolet intensity for improved detection results [11][12][13]. Currently, it is mainly applied to the partial discharge detection of equipment such as transformers and cables.…”

Section: Introductionmentioning

confidence: 99%

Research and Simulation of Partial Discharge Phenomenon Sensing Technology for Substation Inspection Robots

Yu,

Xu,

Yang

et al. 2024

J. Phys.: Conf. Ser.

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This paper thoroughly investigates the phenomenon of partial discharge in substations and proposes a set of simulation experimental apparatus to replicate various types of partial discharge defects in switchgear. By modifying the switchgear, incorporating models for different types of partial discharge, and equipping various standard partial discharge sensors, accurate simulations of phenomena such as point discharge, suspended discharge, gap discharge, and particle discharge are achieved. Through this system, the effectiveness of different detection methods, such as ultrasonic, high-frequency, and transient voltage methods, is validated for various defect models. Furthermore, utilizing an indoor inspection robot guide rail, the paper simulates the environment of partial discharge in substations, enabling the validation of the robot’s partial discharge detection performance and typical patterns under different conditions. This work is dedicated to providing situational awareness technology for partial discharge phenomenon detection for substation inspection robots, so that the inspection robot can detect various abnormal partial discharge phenomena in transformers or other substation equipment through micro sensors to promote the stable operation of the substation.

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Effects of view angle and measurement distance on electrical equipment UV corona discharge detection

Cited by 9 publications

References 11 publications

Thermal Fault Detection and Diagnosis of Electrical Equipment Based on the Infrared Image Segmentation Algorithm

Thermal Fault Detection and Diagnosis of Electrical Equipment Based on the Infrared Image Segmentation Algorithm

Review of Optical Character Recognition for Power System Image Based on Artificial Intelligence Algorithm

Research and Simulation of Partial Discharge Phenomenon Sensing Technology for Substation Inspection Robots

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