Residual life prediction method for gas turbine HGP component based on multi-environmental time similarity theory

被引：0

作者：

Wan, Anping ^{[1
]}

Chen, Jianhong ^{[1
]}

Sheng, Deren ^{[1
]}

Hu, Yacai ^{[1
]}

Yao, Hua ^{[1
]}

Chen, Hui ^{[2
]}

机构：

[1] Institute of Thermal Science and Power System, Zhejiang University, Hangzhou 310027, Zhejiang Province, China

[2] Shandong Electric Power Engineering Consulting Institute Corp, Jinan 250013, Shandong Province, China

来源：

Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering | 2013年 / 33卷 / 05期

关键词：

Gases; -; Forecasting; Maintenance;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

In order to reduce the high costs of gas turbine operation and maintenance management, a novel residual life prediction method for gas turbine based on multi- environmental time similarity (METS) theory was proposed to make scientific and reasonable cost maintenance strategy of gas turbine. This method has introduced a reference gas turbine which has similar operational environment and type of the object gas turbine to obtain similarity coefficient (running hours and start/stop cycles) of the reference unit life evaluation parameters under actual operation conditions and benchmark operation conditions by using experience operational data. Based on the METS theory, the object unit factored running hours and start/stop cycles under benchmark operative conditions were obtained through calculating its actual running hours and start/stop cycles under actual operational conditions. And then the object unit residual life was predicted by comparing with maximum maintenance interval. Furthermore, in order to accurately calculate the object unit actual running hours and start/stop cycles and overcome the deficiency of the traditional statistical manual method, real-time running life and history running life calculation method were proposed to realize the development program. Finally, a factory gas turbine HGP component residual life prediction is provided as the example to verify the scientific validity and feasibility of the prediction method. © 2013 Chinese Society for Electrical Engineering.

引用

页码：95 / 101