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Insulator OOD state identification algorithm based on distribution calibration with smooth classification boundaries

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Abstract

The overhead catenary system transfers the electrical power to the motor train unit. It is an indispensable system for guaranteeing the safe operation of high-speed railways. As a core component of the overhead catenary system, the insulators must be diagnosed periodically to ensure the safe operation of the overall railway system. However, existing deep learning-based insulator state diagnosis networks rely on the independent identically distributed assumption and fail to recognize the out-of-distributed insulator states. An improved insulator state classification algorithm based on smooth decision boundaries and distribution calibration is proposed in this paper. The decision boundary of the model is smoothed by learning the neighborhoods of the current insulators in the feature space through a linear mixing mechanism. The distribution of the out-of-distributed insulators is calibrated to a Gaussian distribution for evaluation. The classifier is adjusted to recognize the out-of-distributed insulator features under the few-shot assumption. The experimental results show that the algorithm proposed in this paper can effectively improve the recognition accuracy of the out-of-distribution insulators.

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Availability of data and materials

The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.

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Funding

No funding was received for conducting this study.

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Authors and Affiliations

  1. School of Electrical Engineering, Southwest Jiaotong University, Chengdu, 611756, China

    Liang Li, Weidong Jin & Muhammad Bilal Shahid

  2. China-ASEAN International Joint Laboratory of Integrated Transportation, Nanning University, Nanning City, Guangxi Province, China

    Weidong Jin

  3. National Supercomputing Center in Shenzhen (Shenzhen Cloud Computing Center), Shenzhen, 518055, China

    Yingkun Huang

Authors
  1. Liang Li
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  2. Weidong Jin
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  3. Yingkun Huang
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  4. Muhammad Bilal Shahid
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Contributions

LL contributed to methodology, software, writing—original draft, and visualization. WJ contributed to conceptualization, writing—review and editing, and supervision. YH contributed to writing—review and editing. MBS contributed to writing—review and editing.

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Correspondence to Liang Li.

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Li, L., Jin, W., Huang, Y. et al. Insulator OOD state identification algorithm based on distribution calibration with smooth classification boundaries. SIViP 17, 3637–3645 (2023). https://doi.org/10.1007/s11760-023-02590-3

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  • DOI: https://doi.org/10.1007/s11760-023-02590-3

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