集成2型模糊逻辑控制器与数字双胞胎和神经网络,用于先进的水电系统管理
Yali Zeng1, Zahraa Abed Hussein2, Mustafa Habeeb Chyad3
1Hunan University of Information Technology, Changsha, 410100, China.
Scientific reports
|February 11, 2025
概括
本研究介绍了一种先进的混合系统,该系统结合了2型模糊逻辑控制器 (T2FLC),数字双胞胎和神经网络,以实现更智能的水电管理. 这种整合大大提高了效率,减少了故障检测时间,降低了维护成本.
科学领域:
- 工程 工程师 工程师 工程师
- 控制系统 控制系统
- 人工智能的人工智能
背景情况:
- 水力发电系统面临着日益复杂的挑战,需要先进的控制来实现最佳性能和可靠性.
- 传统的控制方法与不确定性和实时适应性作斗争.
研究的目的:
- 开发和评估一种用于综合水电管理的新型混合系统.
- 提高负载管理,故障检测,运行效率和系统可靠性.
主要方法:
- 集成2型模糊逻辑控制器 (T2FLC) 来处理不确定性.
- 实施数字双胞胎技术用于实时监控和预测分析.
- 神经网络的应用用于增强预测洞察力和控制决策.
主要成果:
- 实现了负载管理效率提高10.96%,故障检测时间减少12.64%.
- 数字双胞胎将预测准确度提高了18.21%,神经网络将操作偏差降低了8.05%.
- 系统可靠性得到了11.48%的改善,维护成本降低了13.04%.
结论:
- 混合T2FLC,数字双胞胎和神经网络系统在水电管理方面取得了重大进展.
- 这种方法提高了系统性能,可靠性和成本效益.
- 为未来的水电智能控制策略提供了一个强大的框架.
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