首页|基于高斯过程回归模型对一回路泄漏率的预测

基于高斯过程回归模型对一回路泄漏率的预测

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工况的剧烈变化可能导致一回路系统中法兰连接部位、泵的密封面等处发生泄漏.针对准确的泄漏物理模型很难建立的实际情况,在对不可测的温度应力参数进行正态随机游走的基础上,以高斯过程回归模型为替代模型对一回路泄露率进行预测,并对替代模型的不确定性进行定量分析.结果表明,高斯过程回归模型能够方便地实现对替代模型的不确定性评估,并且在小样本容量的情况下,能够实现对一回路泄漏率较准确的预测.
Prediction of primary circuit leakage rate based on gaussian process regression model
The leakage may occur at the flange connection part and sealing surface of pump in primary circuit system due to the drastic change of working condition.In view of the difficult to establish an accurate and complete leakage mechan-ism model,the Gaussian process regression model is used as an alternative model and the uncertainty of the alternative mod-el is calculated quantitatively.Based on the normal random walk of the unmeasurable parameters,the leakage rate of the primary circuit is predicted.The results show that the Gaussian process regression model can calculate the uncertainty of the alternative model,and can accurately predict the leakage rate of the primary circuit in the case of small samples.

gaussian process regression modelthe uncertainty of the alternative modelnormal random walkprimary circuit leakage rate

魏淋东、赵新文、朱康

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海军工程大学核科学技术学院,湖北武汉 430033

高斯过程回归模型 替代模型的不确定性 正态随机游走 一回路泄漏率

2024

舰船科学技术
中国舰船研究院,中国船舶信息中心

舰船科学技术

CSTPCD北大核心
影响因子:0.373
ISSN:1672-7649
年,卷(期):2024.46(13)
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