1.西南石油大学 计算机与软件学院,成都 610500
2.绵阳师范学院,绵阳 621000
赵祥东,男,2000年生,四川成都人,硕士;主要研究方向为智慧新能源;E-mail:z18582485121@outlook.com。
收稿:2024-10-17,
修回:2024-11-18,
纸质出版:2026-06-15
移动端阅览
赵祥东,蒋薇,高国海,等. 基于多模态信息融合的抽油机故障诊断技术研究[J]. 机械强度,2026,48(6):62-69.
ZHAO Xiangdong,JIANG Wei,GAO Guohai,et al. Research on fault diagnosis technology of pumping units based on multi-modal information fusion[J]. Journal of Mechanical Strength,2026,48(6):62-69.
赵祥东,蒋薇,高国海,等. 基于多模态信息融合的抽油机故障诊断技术研究[J]. 机械强度,2026,48(6):62-69. DOI: 10.16579/j.issn.1001.9669.2026.06.007.
ZHAO Xiangdong,JIANG Wei,GAO Guohai,et al. Research on fault diagnosis technology of pumping units based on multi-modal information fusion[J]. Journal of Mechanical Strength,2026,48(6):62-69. DOI: 10.16579/j.issn.1001.9669.2026.06.007.
目的
2
针对抽油机故障诊断中样本不均衡和诊断信息单一的问题,提出一种基于多模态信息融合的故障诊断方法,以提升故障诊断的准确性和可靠性。
方法
2
首先,采用数据增广技术解决故障样本不均衡问题,增强少数类样本的诊断精度;其次,分别对示功图和油井动态生产数据进行特征提取,并融合这两类特征;最后,基于Transformer模型构建故障诊断框架,实现对抽油机故障的精确诊断。
结果
2
试验结果表明,提出的方法在准确率和
F
1
值上均表现优异,为抽油机故障诊断提供了更加可靠且有效的解决方案。
Objective
2
A fault diagnosis method based on multimodal information fusion was proposed. It addressed the issues of sample imbalance and limited diagnostic information in rod pump fault diagnosis. The goal was to improve the accuracy and reliability of fault diagnosis.
Methods
2
Firstly
data augmentation techniques were applied to address sample imbalance. This enhanced the diagnostic accuracy of minority class samples. Secondly
features were extracted from dynamometer cards and dynamic production data. These features were then fused. Finally
a transformer-based fault diagnosis framework was constructed. This framework achieved precise diagnosis of rod pump faults.
Results
2
The test results show that the proposed method performs well in accuracy and
F
1
-score. It offers a more reliable and effective solution for rod pump fault diagnosis.
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