Gas Turbine Blade Passing Frequency Reconstruction and Its Application for Blade Fracturing Fault Diagnosis

Yuan Xiao, Kun Feng, Zhouzheng Li, Fengshou Gu, Zhinong Jiang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Blade fracturing is a catastrophic failure to gas turbine. Condition monitoring is one of the effective methods to improve the reliability during operation. However, there are always existing two problems with blade monitoring: 1) difficult to catch the precise blade characteristic frequencies under complex conditions and 2) challenging to give early warning of blade failure. In this article, we attempt to solve these problems by means of reconstructing blade passing frequency waveform. Firstly, a novel method, high-resolution harmonic product spectrum (HR-HPS), is proposed to accurately extract the fundamental rotating frequency and to calculate blade characteristic frequencies from gas turbine casing vibration. Along with Vold-Kalman filter, the blade passing frequency waveform can be reconstructed. Numerical simulation shows that the proposed HR-HPS method can be well employed under varying operating conditions, and the accuracy of the frequency extraction plays a vital role in waveform reconstruction. Finally, blade fault diagnosis frame based on reconstruction waveform is proposed. A blade fracturing fault experiment is conducted and the result shows that the features extracted from the reconstructed waveform are more sensitive to fault severity than traditional features which can accurately identity the moment of failure and provide early warning for gas turbine blade fracturing faults.

Original languageEnglish
Title of host publicationProceedings of TEPEN 2022
Subtitle of host publicationEfficiency and Performance Engineering Network
EditorsHao Zhang, Yongjian Ji, Tongtong Liu, Xiuquan Sun, Andrew David Ball
PublisherSpringer, Cham
Pages1006-1017
Number of pages12
Volume129
ISBN (Electronic)9783031261930
ISBN (Print)9783031261923, 9783031261954
DOIs
Publication statusPublished - 4 Mar 2023
EventInternational Conference of The Efficiency and Performance Engineering Network 2022 - Baotou, China
Duration: 18 Aug 202221 Aug 2022
https://tepen.net/
https://tepen.net/conference/tepen2022/

Publication series

NameMechanisms and Machine Science
PublisherSpringer
Volume129 MMS
ISSN (Print)2211-0984
ISSN (Electronic)2211-0992

Conference

ConferenceInternational Conference of The Efficiency and Performance Engineering Network 2022
Abbreviated titleTEPEN 2022
Country/TerritoryChina
CityBaotou
Period18/08/2221/08/22
Internet address

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