Investigation on the Turbine Blade Tip Clearance Monitoring Based on Eddy Current Pulse-Trigger Method

Abstract

The efficiency and reliability of turbomachinery will be improved by blade tip clearance (BTC) and blade tip timing (BTT) monitoring. Several types of sensors such as eddy-current, capacitance and optical probes are used to realize this objective. Eddy current sensor (ECS) is an ideal choice with its advantage of durablity and that it is unaffected by gas stream properties such as contamination, water vapor, and moisture. However, the bandwidth of ECS is usually less than 100 kHz, which will limit the resolution of the monitoring result. In this paper, a pulse-trigger technology based BTC method was presented. This method optimizes the static radial and circumferential calibration technology to obtain the sensitivity of the ECS in the different relative locations against the tip of blade. The information from the clearance sensor will be fused with that from the once per revolution (OPR) or key phase sensor. The method is more generally applicable in the condition where the ECS is insufficient sampling caused by the limit of narrow bandwidth, especially under the high blade tip velocity condition. A small scale and larger scale BTC measurement rig are established to validate the feasibility of this method. The small one is easy to calibrate with high accuracy and can be used to illustrate the performance of the method, while the larger scale test rig is close to real industry turbine blade. In this apparatus, the axial displacement and radial displacement of rotor vibration as well as the clearance can be monitored together so that further investigation can be conducted. Experimental research was carried out on both test rig at different rotating speed. The results show that the method presented in this paper can improve the accuracy of tip clearance monitored by ECS very well. Furthermore, this work is a proof-of-concept demonstration using a laboratory setup providing the basis for BTC active control and blade health monitoring (BHM) based on ECS.