Working Condition Monitoring System of Substation Robot Based on Video Monitoring

Zhao, Cuirong; Li, Juchen

doi:10.1155/2022/7840507

Cited by 5 publications

(4 citation statements)

References 18 publications

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“…In this paper, we use one-dimensional convolution to extract local spatial features of network traffic data using two convolution kernel lengths of k. The computational equation is shown in formula (2).…”

Section: Feature Extraction and Detection 1) 1d Convolutionmentioning

confidence: 99%

“…As intelligent substations become increasingly networked and digitalized, the intelligence level of terminals is rising and the traffic information attached to terminals is also exploding. Due to the openness of TCP/IP architecture, denial-ofservice attacks, APT, port scanning, and other malicious attack methods are emerging, bringing a severe test to substation network security [1][2]. Intrusion Detection System (IDS) is a network security technology that instantly monitors network security and responds proactively to network attacks [3].…”

Section: Introductionmentioning

confidence: 99%

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Anomaly detection of terminal access based on LSTM and ResNet

et al. 2023

Second International Symposium on Computer Applications and Information Systems (ISCAIS 2023)

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Massive wireless debugging terminals and complex and diverse access requirements pose significant challenges to the secure access of substation terminal equipment. It is crucial to detect anomaly network traffic to ensure the security of terminal access to the substation. At present, network traffic anomaly detection based on traditional deep learning often has the problem of low computational efficiency or weak representation ability. Given the low computational efficiency of traditional deep learning, the residual network is used to extract spatial features of data, which can effectively improve convergence speed and time efficiency. Aiming at the problem of weak representation ability of traditional machine learning methods, the long short-term memory network (LSTM) is used to improve the representation ability to learn while learning the temporal characteristics of traffic and prevent the gradient from disappearing and network degradation. Experimental results show that compared with the traditional deep learning method, the accuracy of the proposed method is improved, the F1 score reaches 90.09, and the AUC is up to 0.981. By improving anomaly detection accuracy, the paper further guarantees terminal security.

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Section: Feature Extraction and Detection 1) 1d Convolutionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Anomaly detection of terminal access based on LSTM and ResNet

et al. 2023

Second International Symposium on Computer Applications and Information Systems (ISCAIS 2023)

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“…The main factors of mis-action are the operation value of the relay (voltage and power) and the distributed capacitance value of the cable to the ground [4] . Therefore, it is urgent to monitor the distributed capacitance value of the cable and analyze the changing trend, and predict the mis-action chance of the relay [5] . Therefore, based on the analysis and study of the allowable critical value of distributed capacitance under different faults, it is necessary to build a digital model to check whether the low voltage DC system has a mis-action risk for certainly distributed capacitance [6][7][8] .…”

Section: Introductionmentioning

confidence: 99%

Development of digital model and analyzation system for typical faults of low voltage DC system

Wang,

Chen,

Xing

et al. 2024

Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023)

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The digital model for the typical faults of low voltage DC system is analyzed, and the analyzation system is developed to offline calculate and pre-analyses whether the fault results in mis-action of the low voltage DC system. Firstly, the digital model for typical faults of low voltage DC is analyzed based on the analytical method, and the mis-action power for typical faults is found. Secondly, the software for verification of the above analysis is developed, and typical cases are used to further verify the correctness and effectiveness of the developed software. In the tested case, the developed software can flexibly pre-analyses the mis-action of low voltage DC system for the targeted typical faults.

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“…Therefore, many researchers use new technologies and methods to make substations more intelligent and reduce the use of manpower and resources. Such as in [5], the intelligent monitoring system of the substation robot's working state is constructed by combining virtual reality technology. And to improve the intelligence and automation for adapting to the development of prosumer substations, Wang et al [6] propose an isolation switch opening and closing position discrimination method based on intelligent image recognition technology.…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of the Rapid Debugging and Automatic Acceptance System for the Substation Integrated Automation System

Tian,

Wu,

et al. 2023

J. Phys.: Conf. Ser.

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This article designs a rapid debugging and automatic acceptance system for the comprehensive automation system of substations, mainly used for the automatic acceptance of information in intelligent substation monitoring systems. It achieves functions such as static verification of remote configuration, synchronous acceptance of remote information and on-site monitoring information, dynamic closed-loop verification of remote information, automatic triggering of remote information, and archiving of acceptance reports; By using computer software technology, communication technology, and other technological means to improve the automation level of the comprehensive automation system acceptance of substations, reduce the participation of various departments in the acceptance process, and reduce the workload of manual operation of primary and secondary equipment addition.

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Working Condition Monitoring System of Substation Robot Based on Video Monitoring

Cited by 5 publications

References 18 publications

Anomaly detection of terminal access based on LSTM and ResNet

Anomaly detection of terminal access based on LSTM and ResNet

Development of digital model and analyzation system for typical faults of low voltage DC system

Design and Implementation of the Rapid Debugging and Automatic Acceptance System for the Substation Integrated Automation System

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