YConvFormer:一个轻量级和坚固的变压器,用于使用时频融合的变速箱故障诊断
Yihang Peng1, Jianjie Zhang1, Songpeng Liu1
1College of Mechanical Engineering, Xinjiang University, Urumqi 830017, China.
Sensors (Basel, Switzerland)
|August 14, 2025
概括
这项研究介绍了YConvFormer,这是一个用于稳健轻量级变速箱故障诊断的新型网络. 它通过有效处理时间频率数据和减少计算负载,提高了工业环境中的准确性.
科学领域:
- 机械工程 机械工程
- 人工智能的人工智能
- 信号处理 信号处理
背景情况:
- 在重型设备中,变速箱故障诊断面临着在动态工业环境中平衡轻量设计和强度的挑战.
- 当前的诊断算法在杂,可变的操作条件下难以实现计算效率和准确性.
- 现有的方法通常在计算上昂贵,或缺乏对环境干扰的稳定性.
研究的目的:
- 提出一个名为YConvFormer的新,轻量级和强大的诊断网络,用于变速箱故障诊断.
- 解决现有方法在实现故障检测效率和准确性方面的局限性.
- 在具有挑战性的工业环境中提高诊断性能.
主要方法:
- 引入了一个时间频率联合输入通道,集成时间域和频率域数据.
- 整合了一个高效的频道注意力机制,用于噪声过和功能增强,具有动态加权.
- 开发了一种轴向增强的广播注意力机制,用于建模远程时间依赖和频段间相互作用.
- 提出了一个YConvFormer轻量级架构,将浅层特征处理与全球本地建模相结合.
主要成果:
- YConvFormer网络在XJTU和SEU变速箱数据集上的诊断准确度显著提高.
- 与最好的基线 (LiteFormer) 相比,平均精度提高了6.55% (XJTU) 和19.58% (SEU).
- 拟议的方法有效地抑制噪声,并增强时间频特征之间的互补关系.
结论:
- YConvFormer为工业应用中的变速箱故障诊断提供了一个轻量级和强大的解决方案.
- 新的注意力机制和架构有效地提高了诊断准确性和计算效率.
- 这些发现表明,开发用于重型设备的先进诊断系统是一个有希望的方向.
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