基于神经网络算法的汽轮机智能检修自动化系统设计  

Design of Intelligent Maintenance Automation System for Steam Turbine Based on Neural Network Algorithm

作　　者：孙亮亮 SUN Liangliang(Guoneng Changyuan Jingmen Power Generation Co.,Ltd.,Jingmen,Hubei 448000,China)

机构地区：[1]国能长源荆门发电有限公司,湖北荆门448000

出　　处：《自动化应用》2025年第7期38-39,43,共3页Automation Application

摘　　要：提出了一种新型的注意力机制增强型循环神经网络算法(RNN),并基于该算法构建了汽轮机智能检修自动化系统。该系统能够有效分析汽轮机运行过程中的多源异构数据,实现高精度的故障诊断和检修决策。结果表明,该系统提高了汽轮机的故障检测效率和性能,促进了智能检修技术的数字化和智能化发展。This study proposes a novel attention mechanism-enhanced Recurrent Neural Network(RNN)algorithm and constructs an intelligent maintenance automation system for steam turbines based on this algorithm.The system can effectively analyze multi-source heterogeneous data during the operation of steam turbines,achieving high-precision fault diagnosis and maintenance decision-making.The results indicate that the system enhances the fault detection efficiency and performance of steam turbines,promoting the digitalization and intelligent development of intelligent maintenance technology.

关 键 词：循环神经网络 汽轮机 智能检修系统 多源异构数据 故障诊断 

分 类 号：TM62[电气工程—电力系统及自动化]