数模联合驱动的风电机组行星齿轮箱故障诊断

曾庆涛; 唐贵华; 张旋; 程继杰; 马萍

doi:10.19912/j.0254-0096.tynxb.2025-0589

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太阳能学报 ›› 2026, Vol. 47 ›› Issue (8) : 737-746. DOI: 10.19912/j.0254-0096.tynxb.2025-0589

数模联合驱动的风电机组行星齿轮箱故障诊断

曾庆涛¹, 唐贵华², 张旋², 程继杰², 马萍³

作者信息 +

FAULT DIAGNOSIS OF PLANETARY GEARBOX OF WIND TURBINES BY DIGITAL-MODEL HYBRID DRIVATION

Zeng Qingtao¹, Tang Guihua², Zhang Xuan², Cheng Jijie², Ma Ping³

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文章历史 +

摘要

针对风电机组行星齿轮箱运行过程中难以采集大量高质量故障数据,智能诊断模型在故障样本稀缺下诊断精度低的问题,提出一种数模联合驱动的风电机组行星齿轮箱故障诊断方法。首先,基于集总参数法构建高保真风电机组行星齿轮箱动力学模型,生成伪故障数据;其次,设计融入卷积块注意力机制的域共享残差网络特征提取器提取伪数据与实测数据的关键物理特征,引入局部最大均值差异对齐伪故障数据和真实故障数据在故障类别层的特征分布,通过采用科尔莫哥罗夫-阿诺德网络模块增强网络对复杂数据关系的学习能力,实现不同类型故障的分类和识别。最后,将所提方法在风电机组行星齿轮箱故障诊断实验台上进行验证,实验结果表明,相比于其他经典方法,所提方法在故障样本稀缺的情况下具备良好的诊断效果。

Abstract

In response to the problems that it is difficult to collect a large amount of high-quality fault data during the operation of the planetary gearbox of wind turbines and that the diagnostic accuracy of intelligent diagnostic models is low under the scarcity of fault samples, a fault diagnosis method for the planetary gearbox of wind turbines driven by a combination of numerical and physical models is proposed. First, a high-fidelity dynamic model of the planetary gearbox of wind turbines is constructed based on the lumped parameter method to generate pseudo-fault data. Second, a domain-shared residual network feature extractor incorporating a convolutional block attention mechanism is designed to extract the key physical features of the pseudo-data and the measured data. The local maximum mean discrepancy is introduced to align the feature distributions of the pseudo-fault data and the real fault data at the fault category level. By adopting the Kolmogorov-Arnold network module, the network’s learning ability for complex data relationships is enhanced to achieve the classification and identification of different types of faults. Finally, the proposed method is verified on the fault diagnosis test bench of the planetary gearbox of wind turbines. The experimental results show that compared with other classic methods, the proposed method has a good diagnostic effect under the condition of scarce fault samples.

导出引用

曾庆涛, 唐贵华, 张旋, 程继杰, 马萍. 数模联合驱动的风电机组行星齿轮箱故障诊断[J]. 太阳能学报. 2026, 47(8): 737-746 https://doi.org/10.19912/j.0254-0096.tynxb.2025-0589

Zeng Qingtao, Tang Guihua, Zhang Xuan, Cheng Jijie, Ma Ping. FAULT DIAGNOSIS OF PLANETARY GEARBOX OF WIND TURBINES BY DIGITAL-MODEL HYBRID DRIVATION[J]. Acta Energiae Solaris Sinica. 2026, 47(8): 737-746 https://doi.org/10.19912/j.0254-0096.tynxb.2025-0589

中图分类号： TH17 TH133

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