Wireless High Rotational Speed Assessment by Exploiting an RF Sensor Tag System and Equivalent-Time Reconstruction

Area of Science:

• Electromechanical Systems Engineering
• Radio-Frequency Sensing
• Signal Processing

Background:

• Accurate rotational speed monitoring is critical for industrial and electromechanical systems.
• Traditional sampling methods for RF impedance-based rotational sensing face limitations in usable speed range due to acquisition rates.
• Existing peak-based estimation methods exhibit significant errors at higher rotational speeds.

Purpose of the Study:

• To present a novel rotational speed measurement method using a wireless impedance sensing system.
• To overcome the speed range limitations of conventional sampling-based systems without requiring higher-rate instrumentation.
• To introduce and validate an equivalent-time sampling (ETS) reconstruction approach for enhanced rotational sensing.

Main Methods:

• Utilized a wireless impedance sensing system with radio-frequency coupling between a passive resonant tag and a coplanar waveguide (CPW) probe.
• Exploited periodic variations in the probe's real impedance caused by the relative alignment of the rotating tag.
• Implemented an equivalent-time sampling (ETS) approach to reconstruct the rotational waveform from sparse, nonuniform impedance samples over multiple revolutions.

Main Results:

• Achieved rotational speed measurements from 150 RPM to 4000 RPM with a mean relative estimation error below 5%.
• Demonstrated a significant improvement over conventional peak-based estimation, which showed errors exceeding 70% above 1000 RPM.
• Validated the effectiveness of the ETS approach in extending the operational range of RF impedance-based rotational sensing under undersampling conditions.

Conclusions:

• The proposed equivalent-time sampling (ETS) method effectively enhances rotational speed measurement accuracy in wireless impedance sensing systems.
• The ETS approach overcomes fundamental limitations of sampling rates, enabling reliable sensing across a wide speed range.
• The framework is generalizable to other periodic RF sensing applications where signal periodicity can be leveraged across multiple acquisition cycles.