Vehicle Wheel Rotation Speed Measurement Using Fourier Transform
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Solution Overview
Problem
Existing magnetic tachometers for measuring vehicle wheel rotation speed face challenges in precision and reliability, especially at low speeds and in environments with electrical, electromagnetic, or mechanical perturbations, due to sensitivity to noise and inability to filter low-frequency mechanical noise within the useful frequency band.
Innovation Solution
A method involving real-time digitization of analogue measurement signals, Fourier transform, and frequency analysis to identify the useful spectral line and determine rotation speed, with adaptive filtering and interpolation to enhance signal quality and noise resilience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the voltage threshold is decreased to improve low-speed measurement capability, then the measurement precision at low speeds is improved, but the sensitivity to parasitic noise increases
Solution Approach 1:
The patent transforms the measurement from time domain to frequency domain using Fourier transform. Instead of measuring period directly in time domain with voltage thresholds, the system analyzes frequency spectrum to identify the fundamental frequency corresponding to wheel rotation speed. This dimensional transformation allows the system to use very low voltage thresholds (down to millivolts) without being affected by noise, because the frequency analysis can distinguish the fundamental frequency from noise components.
Solution Approach 2:
The patent introduces frequency analysis as an intermediary processing step between signal acquisition and speed calculation. The Fourier transform acts as a mediator that separates the useful signal (fundamental frequency) from parasitic noise (other frequencies). This intermediary allows the system to maintain low voltage thresholds while achieving noise immunity through spectral separation.
2Reliability
If filtering is applied to reduce high-frequency perturbations, then the measurement reliability is improved, but low-frequency mechanical noise cannot be filtered as it falls within the useful frequency band
Solution Approach 1:
The patent moves the analysis from time domain to frequency domain, enabling differentiation between the fundamental frequency (useful signal) and harmonic frequencies (noise). By identifying the fundamental frequency through spectral analysis, the system can reliably measure rotation speed even when low-frequency mechanical noise is present, as the noise appears as harmonic components that can be distinguished from the fundamental.
3Adaptability or versatility
If the amplitude of the measurement signal is lower at lower rotation speeds, then the measurement range is extended to low speeds, but the frequency measurement becomes impossible in certain frequency ranges
Solution Approach 1:
The patent uses Fourier transform to convert the time-domain signal into frequency-domain representation. This allows the system to detect and measure very low amplitude signals (millivolt range) by identifying their frequency characteristics rather than relying on amplitude-based threshold detection. The fundamental frequency can be identified even when signal amplitude is extremely low, extending the measurement range to very low rotation speeds.
4Device complexity
If voltage thresholds are used for period measurement, then the measurement process is simple, but the thresholds are particularly complex to define as they affect both low-frequency measurement performance and noise robustness
Solution Approach 1:
The patent replaces time-domain threshold comparison with frequency-domain spectral analysis. Instead of defining complex voltage thresholds that must balance low-speed performance and noise immunity, the system performs Fourier transform and identifies the fundamental frequency directly from the spectrum. This eliminates the need for complex threshold definition while maintaining measurement simplicity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method improves the precision and reliability of wheel rotation speed measurement by effectively separating noise from the useful signal, allowing measurement of low speeds and reducing errors from perturbations, and provides a quality indicator for monitoring system integrity.
Implementation Method 1
a fixed portion comprising a magnetic sensor (coil of conductive wire, Hall-effect sensor, etc.) delivering a periodic measurement signal generated by a magnetic-field variation resulting from the rotation of the wheel
Implementation Method 2
calculating a Fourier transform of the time-dependent digital measurement signal in an observation window in order to obtain a frequency-dependent digital measurement signal
Data Source
AI summary
A method for measuring the rotation speed of a wheel including the steps of: acquiring an analog measurement signal (Sma) generated by a magnetic tachometer and containing a useful signal the frequency of which is representative of the rotation speed of the wheel; digitizing in real-time the analog measurement signal (Sma) in order to obtain a time-dependent digital measurement signal (Smnt); calculating a Fourier transform of the time-dependent digital measurement signal (Smnt) in order to obtain a frequency-dependent digital measurement signal (Smnf); and carrying out a frequency analysis in order to identify by a search for peaks a useful spectral line (16) so as to obtain the frequency of the useful signal and therefore the rotation speed of the wheel.