Identification and fault diagnosis of an industrial gas turbine prototype model

被引：0

作者：

Simani, S ^{[1
]}

Patton, RJ ^{[1
]}

Daley, S ^{[1
]}

Pike, A ^{[1
]}

机构：

[1] Univ Ferrara, Dipartimento Ingn, I-44100 Ferrara, Italy

来源：

PROCEEDINGS OF THE 39TH IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-5 | 2000年

关键词：

fault diagnosis; analytical redundancy; model-based approach; system identification; industrial gas turbine;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper addresses a model-based procedure exploiting analytical redundancy for the detection and isolation of faults of a power plant. The residual generation is performed by means of output observers and Kalman filters in connection with the uncertainty affecting the measurements acquired from the monitored system. The model of the process under investigation required to design observers and filters is obtained by identification The proposed fault detection and isolation tool has been tested on a simulated model of an industrial gas turbine prototype.

引用

页码：2615 / 2620

页数：6

共 50 条

[31] Gas path component fault diagnosis of an industrial gas turbine under different load condition using online sequential extreme learning machine [J].

Montazeri-Gh, Morteza ;

Nekoonam, Ali .

ENGINEERING FAILURE ANALYSIS, 2022, 135

[32] SISO System Model Identification and Fault Diagnosis [J].

Zhou, Yuguo ;

Fan, Yongle ;

Zhao, Lina ;

Yin, Shanshan .

PROCEEDINGS OF 2018 IEEE 3RD ADVANCED INFORMATION TECHNOLOGY, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (IAEAC 2018), 2018, :1866-1870

[33] Fault diagnosis of wind turbine gearbox based on model fusion [J].

Sun W. ;

Deng A. ;

Deng M. ;

Liu Y. ;

Cheng Q. .

Taiyangneng Xuebao/Acta Energiae Solaris Sinica, 2022, 43 (01) :64-72

[34] Fault diagnosis for a turbine engine [J].

Diao, YX ;

Passino, KM .

CONTROL ENGINEERING PRACTICE, 2004, 12 (09) :1151-1165

[35] Enhancing Gas Turbine Fault Diagnosis Using a Multi-Scale Dilated Graph Variational Autoencoder Model [J].

Zhang, Kun ;

Li, Hongren ;

Wang, Xin ;

Xie, Daxing ;

Yang, Shuai .

IEEE ACCESS, 2024, 12 :104818-104832

[36] Gas Turbine Fault Diagnosis Based on ART2 Neural Network [J].

Xu Qingyang ;

Meng Xianyao ;

Wang Ning .

2008 7TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-23, 2008, :5244-5248

[37] Fault Diagnosis for Gas Turbine Blade Based on ABC- RVM algorithm [J].

Chen Li-wei ;

Pu Ying-dong .

2014 FOURTH INTERNATIONAL CONFERENCE ON INSTRUMENTATION AND MEASUREMENT, COMPUTER, COMMUNICATION AND CONTROL (IMCCC), 2014, :93-97

[38] A novel gas turbine fault diagnosis method based on transfer learning with CNN [J].

Zhong, Shi-sheng ;

Fu, Song ;

Lin, Lin .

MEASUREMENT, 2019, 137 :435-453

[39] A Support Vector Machine Fault Diagnosis Method for Gas Turbine Fuel System [J].

Yan, Li ;

Cao, Yunpeng ;

Liu, Rui ;

Zhao, Tianrui ;

Li, Shuying .

PROCEEDINGS OF TEPEN 2022, 2023, 129 :985-994

[40] Dynamic neural network-based fault diagnosis of gas turbine engines [J].

Tayarani-Bathaie, S. Sina ;

Vanini, Z. N. Sadough ;

Khorasani, K. .

NEUROCOMPUTING, 2014, 125 :153-165

← 1 2 3 4 5 →