Abstract

Detection of incipient cracks and crack propagation in rotor blades during operation of gas compressors is an important problem from the perspective of safety, reliability, availability, and maintenance of gas turbines. In this paper we present the architecture of a blade health monitoring system that has been deployed to monitor rotor blades of the gas compressors. The system operates continuously, 24×7, with minimal human intervention to monitor a fleet of gas compressors all around the world. The compressors are retrofitted with non-contact magnetic clearance sensors to generate Blade Passing Signals (BPS) during the rotation of the blades. These signals are acquired by a Data Acquisition (DAQ) box. The DAQ extracts the Time of Arrival (TOA) of the blades and stores them. The TOA data is transferred to a central system for feature extraction at regular intervals. The extracted features natural frequencies of predetermined modes of vibration and static deflection are used to determine the health of the rotating blades and generate alarms for the Monitoring and Diagnostics (M&D) team. The M&D team monitors the health of blades using a web portal that provides visualization of data, features, and alarms.

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