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Advanced Hybrid Information Processing. 7th EAI International Conference, ADHIP 2023, Harbin, China, September 22-24, 2023, Proceedings, Part III

Research Article

Design of Substation Battery Condition Monitoring System Based on SDH Network

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  • @INPROCEEDINGS{10.1007/978-3-031-50549-2_24,
        author={Feng Xu and Quan Zi and Chen Zhao and Nannan Wang and Yan Wang},
        title={Design of Substation Battery Condition Monitoring System Based on SDH Network},
        proceedings={Advanced Hybrid Information Processing. 7th EAI International Conference, ADHIP 2023, Harbin, China, September 22-24, 2023, Proceedings, Part III},
        proceedings_a={ADHIP PART 3},
        year={2024},
        month={3},
        keywords={SDH Network Substation Battery Condition Monitoring TW-SDH6000 Simulation Processing Self-Healing Function Pca Method Pearson Correlation Coefficient},
        doi={10.1007/978-3-031-50549-2_24}
    }
    
  • Feng Xu
    Quan Zi
    Chen Zhao
    Nannan Wang
    Yan Wang
    Year: 2024
    Design of Substation Battery Condition Monitoring System Based on SDH Network
    ADHIP PART 3
    Springer
    DOI: 10.1007/978-3-031-50549-2_24
Feng Xu1,*, Quan Zi1, Chen Zhao1, Nannan Wang1, Yan Wang1
  • 1: Suzhou Power Supply Company
*Contact email: 19166586244@163.com

Abstract

In the process of substation battery condition monitoring, because the status parameters are real-time fluctuations, resulting in relatively large errors in the monitoring results, this paper proposes the design and research of substation battery condition monitoring system based on SDH network. TW-SDH6000 is used as the hardware device of the substation battery condition monitoring system. In the software design phase, the SDH network is used to simulate and process the battery resources, so that when the relevant equipment in the substation is abnormal and the battery status fluctuates, the self-healing function can be used to filter this part of data. In the condition monitoring phase, the PCA method is used to reduce the dimension of the original data, and Pearson correlation coefficient is used to analyze the relationship between the original data and the simulation processing results. Realize accurate monitoring. In the test results, the error of the design method for the monitoring results of battery voltage amplitude, input frequency and coil proportion is significantly lower than that of the control group.

Keywords
SDH Network Substation Battery Condition Monitoring TW-SDH6000 Simulation Processing Self-Healing Function Pca Method Pearson Correlation Coefficient
Published
2024-03-24
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-50549-2_24
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