Distributed Real Time Compressor Blade Health Monitoring System

Lijie Yu and Sachin Shrivastava
Submission Type: 
Full Paper
AttachmentSizeTimestamp
phmc_16_003.pdf790.4 KBSeptember 12, 2016 - 7:41am

Compressor blades of a heavy duty industrial gas turbine need to sustain long period mechanical stress and vibration induced by high speed rotation and high pressure mass flow. High stress coupled with erosion and corrosion damage during operation is the main driver for blade cracking. Material separation of cracked rotating blade is a serious safety and reliability concern, which not only affects compressor health, but may also cause costly secondary damage at downstream. Early detection of blade anomaly and incipient crack is critical to ensure blade and compressor health and minimize service disruption. In this paper we will introduce a blade health monitoring (BHM) system developed by GE Power. BHM adopts distributed system architecture and operates continuously 24x7 to provide real time rotor blade health assessment. BHM sensors and data acquisition (DAQ) system are installed on the gas turbine to capture blade passing signals (BPS) and assess time of arrival (TOA) for each blade. Advanced signal processing algorithms process the signals locally to calculate key features that associated with blade health. Then finally, a central anomaly detection module, which is fully integrated with GE Power monitoring system, is developed to assess blade health condition and generate anomaly alarms to alert diagnostic engineer.

Publication Year: 
2016
Publication Volume: 
7
Publication Control Number: 
003
Page Count: 
8
Submission Keywords: 
gas turbine compressor
blade
health management
Submission Topic Areas: 
CBM and informed logistics
Component-level PHM
Health management system design and engineering
Industrial applications
Structural health monitoring
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