Anisotropic Magnetoresistive Sensors: Dynamic Modeling and Characterization for Blade Tip-Timing Measurements

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Authors: Daniele Busti, Lorenzo Capponi, Antonella Gaspari, Laura Fabbiano, Gianluca L. Rossi
Cited by: 1
References: 37

Abstract

Monitoring of blade vibrations in turbomachinery equipped with ferromagnetic blades is currently performed using the Blade Tip-Timing (BTT) non-contact technique. To reduce measurement uncertainty on time samples, BTT systems require measurement probes to meet high dynamic performance requirements. Anisotropic magnetoresistive (AMR) sensors have recently gained interest for this application owing to their high sensitivity to magnetic flux variations and robustness in harsh, contaminated environments. However, a thorough dynamic characterization of AMR-based BTT probes remains largely unexplored, representing a critical gap in next-generation industrial measurement systems. This work presents a custom-designed signal conditioning circuit tailored for AMR-based BTT measurements, alongside a systematic methodology for characterizing its dynamic performance. The circuit is modeled as a block diagram, from which transfer functions are derived analytically and validated experimentally, providing a rigorous and reproducible framework for probe dynamic assessment. The complete instrumentation chain is then tested on a low-speed rotor test bench in a BTT configuration. Results reveal a fundamental sensitivity-bandwidth trade-off: satisfying the cutoff frequency requirement imposed by BTT applications inherently reduces signal gain below the threshold needed to resolve individual blade-passage events. This finding isolates the key design bottleneck for AMR-based BTT probes and provides quantitative guidance for future optimization of both sensor and circuit design toward industrial tip-timing deployment.

Fields of Study & Subjects

Bladed Disk Vibration Dynamics Turbomachinery Performance and Optimization Magnetic Bearings and Levitation Dynamics

Publication details

Journal / source
Sensors
Publisher
MDPI AG
Volume
26
Issue
8
Pages
2506–2506
Publication date
18 April 2026
Language
EN