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1 June 2023 Axis temperature anomaly data generation based on optimized generation network
Kai Huang, Kun Xie, Haigang Zhang
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Proceedings Volume 12718, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023); 127180O (2023) https://doi.org/10.1117/12.2681566
Event: International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023), 2023, Nanjing, China
Abstract
The current axis temperature discrimination system is gradually emerging a method of axis temperature status discrimination combined with neural networks. The principle is to train a neural network model with the existing axis temperature data and use the output of this model to determine the current axis temperature status. However, because the data used for the training of the axis temperature state discriminative model are less for the strong thermal class, the scale of the model used to discriminate the axis temperature state class cannot be too large, so the model discriminative results are often not particularly satisfactory. In this study, the temperature rise, column temperature rise difference, and vehicle temperature rise difference are used as feature data. Using the optimized generation network generates simulated data with probability distribution similar to that of the real strong thermal class feature data. And the T-SNE visualization and the discrimination of the actual axis temperature characteristics are used to prove the validity of the generated strong thermal class features data. The simulation results show that the generated axis temperature feature data of the strong thermal class is valid and can be used for the subsequent training of the axis temperature discriminative network.
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Kai Huang, Kun Xie, and Haigang Zhang "Axis temperature anomaly data generation based on optimized generation network", Proc. SPIE 12718, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023), 127180O (1 June 2023); https://doi.org/10.1117/12.2681566
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KEYWORDS
Data modeling
Visualization
Safety
Statistical modeling
Neural networks
Temperature metrology
Infrared radiation
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