石油化工设备技术 ›› 2026, Vol. 47 ›› Issue (3): 52-59.doi: 10.3969/j.issn.1006-8805.2026.03.009

• 检维修技术 • 上一篇    

基于故障溯源方法的烟气轮机转子不平衡诊断分析及优化运行技术研究

彭乾冰   

  1. 中石化(天津)石油化工有限公司,天津 300271
  • 收稿日期:2026-02-02 修回日期:2026-04-25 接受日期:2026-04-30 出版日期:2026-05-15 发布日期:2026-05-19
  • 作者简介:彭乾冰,男,1992年毕业于天津科技大学化工设备与机械专业,工学学士,主要从事设备全生命周期管理工作,高级工程师。

Research on Diagnostic Analysis and Optimization Operation Technology for Rotor Imbalance in Flue Gas Turbines Based on Fault Traceability Method

Peng Qianbing   

  1. SINOPEC (Tianjin) Petrochemical Co., LTD., Tianjin, 300271
  • Received:2026-02-02 Revised:2026-04-25 Accepted:2026-04-30 Online:2026-05-15 Published:2026-05-19

摘要: 在石油化工产业中,烟气轮机是催化裂化装置的核心能源回收设备,但其烟气成分复杂,导致转子系统长期处于高温、高压、冲蚀的严苛工况下,转子不平衡故障频发,严重影响催化裂化装置的安全稳定运行。针对烟气轮机运行工况复杂、有效监测数据获取难度大的问题,文章以烟气轮机转子系统为研究对象,构建了基于故障溯源的多参数耦合诊断模型,实现了烟气轮机运行工况的多物理场仿真,并明确了转子系统的动态响应特性。为解决不平衡故障“溯源难、定量难”的行业痛点,创新性提出基于故障溯源的转子不平衡故障识别方法与不停机定量分析技术,即通过融合仿真与现场实测数据构建故障特征库,结合皮尔逊相关分析法提取现场信号特征并计算相似度,最终实现故障原因的精准定位与定量评估。

关键词: 烟气轮机, 故障诊断, 转子不平衡, 故障溯源, 多参数耦合, 相关分析

Abstract: In the petrochemical industry, the flue gas turbine is the core energy recovery equipment for catalytic cracking units. However, the complex composition of flue gas exposes its rotor system to harsh operating conditions such as high temperature, high pressure and erosion for a long time, leading to frequent rotor imbalance faults, which seriously affect the safe and stable operation of catalytic units. Aiming at the issue of complex operating conditions of flue gas turbines and difficulty in obtaining effective monitoring data, this paper took the flue gas turbine rotor system as the research object. It constructed a multi-parameter coupling diagnosis model based on fault traceability and realized the multi-physics simulation of the operating conditions of flue gas turbines and clarified the dynamic response characteristics of the rotor system. To address the persistent industry challenges of "difficult fault traceability and quantification in imbalance diagnosis," this study developed a novel methodology for rotor imbalance identification based on fault traceability and a non-stop quantitative analysis technology. By establishing a fault signature database through integration of simulation models and on-site measured data, and leveraging Pearson correlation analysis to extract on-site signal features and compute similarity index, the proposed framework enables precise root-cause localization and quantitative assessment of faults.

Key words: flue gas turbinelfault diagnosislrotor imbalancelfault traceabilitylmulti-parameter couplinglcorrelation analysis