基于模糊系数适应线性神经元方法的复合转子无轴承感应电机的振动补偿控制策略
Chengling Lu1, Zebin Yang2, Xiaodong Sun3
1School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China; School of Electrical and Photoelectric Engineering, West Anhui University, Lu'An 237012, China..
ISA transactions
|September 18, 2024
概括
一种新的模糊系数自适应线性神经元方法有效地抑制了复合转子无轴感应电机 (CCR-BIM) 的转子偏心振动,比传统的PID方法表现出优越的动态性能.
科学领域:
- 机械工程 机械工程
- 控制系统工程 控制系统工程
- 电气工程 电气工程
背景情况:
- 在复合旋转机无轴承感应电机 (CCR-BIM) 中,旋转机的偏心率会引起显著的振动.
- 传统的振动补偿方法在性能上可能有局限性.
研究的目的:
- 建议使用模糊系数自适应线性神经元 (FCALN) 的CCR-BIM进行振动补偿控制方法.
- 研究CCR-BIMs与旋转器异心率的数学模型和振动机制.
主要方法:
- 开发了CCR-BIM的数学模型,并分析了不平衡振动的机制.
- 应用了FCALN算法来分解旋转器位移并提取波元件.
- 通过稳定性分析确定重量系数范围.
- 提出了一个基于FCALN的转子振动补偿方法,将其与PID进行比较.
主要成果:
- FCALN算法成功地分解了旋转器位移,并识别了与振动相关的波组件.
- 稳定性分析为重量系数提供了一个定义的范围.
- 实验和模拟结果验证了拟议的FCALN方法.
结论:
- 拟议的基于FCALN的振动补偿控制有效地抑制了CCR-BIM中的旋转器不平衡的振动.
- FCALN算法表现出卓越的动态性能,优于传统的PID方法.
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