| 贾 凯,江 明,袁啸林,左桂忠,陈 跃.基于代价敏感型 LightGBM 的分子泵故障检测[J].电子测量与仪器学报,2022,36(10):55-64 |
| 基于代价敏感型 LightGBM 的分子泵故障检测 |
| Fault detection of molecular pump based on cost-sensitive LightGBM |
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| DOI： |
| 中文关键词: 故障检测 磁悬浮分子泵 时频域分析 LightGBM 真空泄漏 |
| 英文关键词:fault detection magnetic molecular pump time-frequency domain analysis LightGBM vacuum leak |
| 基金项目:国家自然科学基金（11905254,12105322）项目资助 |
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| 摘要点击次数: 1066 |
| 全文下载次数: 678 |
| 中文摘要: |
| 针对 EAST 全超导托卡马克装置的分子泵在数据集不平衡条件下导致的故障识别率低,模型容易过拟合等问题,提出
了一种基于时频域分析与改进的 LightGBM 算法相结合的方法。 首先,利用在 EAST 搭建的分子泵实验平台采集正常与故障的
振动数据,再对数据进行时频域特征提取。 其次,通过优化误分类代价,建立了代价敏感型 LightGBM 故障检测架构。 最后,将
得到的特征量作为代价敏感型 LightGBM 算法的输入,实现分子泵故障检测。 经实验验证,该方法的正确率达 99. 4%,同时,所
提出的方法在误报率和漏检率方面均优于传统分类算法与 LightGBM 算法。 此方法能够有效解决模型过拟合问题,实现对分子
泵故障的高准确率检测。 |
| 英文摘要: |
| Aiming at the problem of low accuracy and overfitting in the unbalanced data of molecular pump of EAST all-superconducting
tokamak device, a method of time-frequency analysis and improved LightGBM algorithm is proposed. Firstly, the normal and fault
vibration data are collected by the molecular pump experimental platform. Then, extract the time and frequency domain features.
Moreover, the cost-sensitive LightGBM fault detection framework was established by optimizing the misclassification cost function.
Finally, the obtained features are used as the input of the cost-sensitive LightGBM algorithm for molecular pump fault detection. The
experimental results show that the fault detection accuracy is 99. 4%. Meanwhile, the proposed method can consistently outperform
traditional classifiers and LightGBM algorithms. This method can effectively solve the problem of overfitting and realize the detection of
molecular pump fault with high accuracy. |
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