基于不同的CFD模拟,可解释的人工智能对中压开关装置内部弧形的建模
Mahmood Matin1,2, Amir Dehghanian3, Mohammad Dastranj1,2
1R&D Department, Kerman Tablo Corporation, Kerman, Iran.
Heliyon
|April 26, 2024
概括
人工智能模型预测中电压开关设备的内弧压力上升. 起始压力,通道总宽度和通道状况显著影响最大压力,这对安全至关重要.
科学领域:
- 电气工程 电气工程
- 计算流体动力学的流体动力学.
- 机器学习 机器学习
背景情况:
- 开关装置的内部弧形带来了重要的电热风险.
- 压力上升的变化需要先进的建模技术.
- 了解制造和环境影响是减轻弧形损坏的关键.
研究的目的:
- 调查制造和环境参数对中压开关装置内部弧压升高的影响.
- 应用人工智能来解释内部弧形建模.
- 确定影响内部弧度期间最大压力的关键因素.
主要方法:
- 开发了54个计算流体动力学 (CFD) 模型.
- 训练了一个极端梯度增强 (XGBoost) 机器学习模型.
- 使用SHAP值来确定参数的意义.
主要成果:
- 在不同的模型中,最大压力从17835.45Pa变化到144423.2Pa.
- 初始压力 (IP),通道总宽度 (TDW) 和通道状况 (DC) 被确定为最有影响力的参数.
- 基于输入参数,XGBoost模型有效地预测了最大压力.
结论:
- 制造和环境参数显著影响内部弧压.
- 人工智能和机器学习为分析复杂现象提供了强大的工具,例如开关设备的内部弧.
- 结果为设计更安全,更强大的中压开关设备提供了洞察力.
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