A novel blade tip clearance measurement method based on event capture technique

Abstract Blade tip clearance (BTC) measurement is an essential technology in turbomachinery health monitoring so as to enhance efficiency and reliability as well as to ensure timely maintenance. The existing BTC measurement methods, which based on continuous sampling technique, depend highly on the devices sampling frequency, data transmission speed, storage memory, and computation capability, can hardly achieve online real-time measurement and long-term continuous monitoring. BTC distribution of a turbomachinery possesses discreteness, symmetry, monotonicity and quasi-periodicity, based on these characteristics, this paper proposes a novel BTC measurement method based on event capture technique. The method sorts the sensors signal into distinct events according to pre-set trigger thresholds, describes the relationship between the event kinds and the BTC distribution via mathematical equations, and solves the BTC values accordingly. The measurement error, measuring sensitivity, measurable range, and solving stability of the proposed method are demonstrated. A test to validate the proposed method for BTC measurement in the inlet section of a turboengine is performed, and the results show that, the event capture technique is capable of achieving fast and accurate BTC measurement. The proposed methods own a measurement error within 0.02 mm (for dual-channel configuration) and 0.01 mm (for multi-channel configuration) comparing with the continuous sampling technique. Meanwhile their hardware resource requirement are reduced to 0.02% (for dual-channel configuration) and 0.1% (for multi-channel configuration) comparing with the continuous sampling technique. For processing these performances, the proposed method can be applied for online real-time BTC measurement and long-term continuous BTC monitoring.

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