Autonomous navigation method for substation inspection robot based on travelling deviation

Yang, Guangsong; Xu, Wei; Li, Jian; Fu, Chongguang; Zhou, Huaibei; Zhang, Chuanyou; Shao, Guangting

doi:10.1088/1755-1315/69/1/012201

Cited by 3 publications

(1 citation statement)

References 1 publication

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“…And a large number of artificial intelligence technology has been introduced into the operation inspection platform of substation [9][10] . Among them, the research of substation robots based on multi-agent in substation inspection has been carried out, but there is no practical application system combining with practical application requirements [11][12][13][14][15] . Moreover, the image information obtained by the inspection robot and the data collected by the live line measurement system are not well combined, and the inspection results still need to be obtained by manual deep participation.…”

Section: Introductionmentioning

confidence: 99%

Design of intelligent operation inspection platform based on the multi-agent system for live line measurement of substation

Xuefeng

Guo

2022

J. Phys.: Conf. Ser.

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At present, substations are developing vigorously in an intelligent direction. In this paper, an intelligent operation inspection platform based on a multi-agent system is designed. The platform’s design includes the design of its physical architecture and its operation architecture. The physical architecture of the platform includes a substation main control server, fixed live line measurement device, intelligent operation inspection software, intelligent data centralization device, intelligent interface conversion device, wireless communication channel, etc. In terms of platform operation architecture, an operation framework based on a multi-agent system is designed, including the “environment” layer, data sensing layer, data processing layer, and analysis and decision layer, and the whole platform is built based on the concept of edge computing. To solve the task allocation problem of edge computing, a Markov decision model is designed to minimize time consumption and maximize resource utilization, and the deep Q network (DQN) algorithm is used to solve the problem. The design aims at being effective, practical, safe, compatible, easy to upgrade, and extensible, and builds an intelligent operation inspection platform for live line measurement of substation equipment based on a multi-agent system, to improve the intelligent automation level of substation operation inspection.

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Section: Introductionmentioning

confidence: 99%

Design of intelligent operation inspection platform based on the multi-agent system for live line measurement of substation

Xuefeng

Guo

2022

J. Phys.: Conf. Ser.

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Nondestructive Detection of Turbine Blade Defects in Aero-Engines Using Thermal Imaging Techniques

Jin

2024

High Temp Mat Proc

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Accurate nondestructive inspection of aero-engine turbine blades is crucial for maintaining engine stability and safety. This paper briefly overviews thermal imaging technology and turbine blades in jet engines. The thermal imaging technology was applied to the nondestructive inspection of thermal barrier coatings on turbine blades. The Faster-regional convolutional neural network (RCNN) algorithm was employed to detect defects in the thermal images, which were preprocessed using the adaptive carrier algorithm. Then experimental analyses were conducted using prepared thermal barrier coatings with three types of defect. Moreover, the Faster-RCNN algorithm combined with adaptive carrier preprocessing was compared with the convolutional neural network and Faster-RCNN algorithms combined with Gaussian filter preprocessing. The results demonstrated that the adaptive carrier preprocessing combined with Faster-RCNN method accurately identified defect types and located defects with higher precision.

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Research and Application of Image Recognition of Substation Inspection Robots based on Edge Computing and Incremental Learning

Liu¹,

Dong²,

Li³

et al. 2021

Preprint

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The large scale of the power grid and its high voltage make the fault detection have not only heavy workload but also high risks. This paper briefly introduced the inspection robot system, edge computing technology, and support vector machine (SVM)-based image recognition algorithm. To enable the inspection robot system to actively adjust the algorithm parameters and maintain the accuracy of the algorithm, the SVM algorithm was improved by the incremental learning technology. Then, the non-improved and improved SVM algorithms were simulated in MATLAB software. A one-month experiment was carried out in a substation. The results showed that the improved SVM algorithm trained faster and had a high accuracy in the face of new samples. The substation experiment verified that the inspection robot system maintained the infrared image recognition accuracy of the faulty equipment for a long time after the application of the improved SVM algorithm, and the system had a smaller delay in transmitting command information after the application of edge computing.

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Autonomous navigation method for substation inspection robot based on travelling deviation

Cited by 3 publications

References 1 publication

Design of intelligent operation inspection platform based on the multi-agent system for live line measurement of substation

Design of intelligent operation inspection platform based on the multi-agent system for live line measurement of substation

Nondestructive Detection of Turbine Blade Defects in Aero-Engines Using Thermal Imaging Techniques

Research and Application of Image Recognition of Substation Inspection Robots based on Edge Computing and Incremental Learning

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Autonomous navigation method for substation inspection robot based on travelling deviation

Cited by 3 publications

References 1 publication

Design of intelligent operation inspection platform based on the multi-agent system for live line measurement of substation

Design of intelligent operation inspection platform based on the multi-agent system for live line measurement of substation

Nondestructive Detection of Turbine Blade Defects in Aero-Engines Using Thermal Imaging Techniques

Research and Application of Image Recognition of&nbsp;Substation Inspection Robots&nbsp;based on Edge Computing and Incremental Learning

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Research and Application of Image Recognition of Substation Inspection Robots based on Edge Computing and Incremental Learning