Tire Pressure Detection Using Active Noise Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing tire pressure decrease detection methods using the Resonance Frequency Mechanism face challenges in accurately estimating torsional resonance frequency due to periodic noise, particularly engine noise, which is not effectively removed by current techniques, and require significant CPU resources.
Innovation Solution
The implementation of an active noise control technology, such as a delayed-x harmonics synthesizer or FIR type adaptive digital filter with an LMS algorithm, to remove periodic noise from wheel speed or acceleration signals, improving the precision of torsional resonance frequency estimation without relying on FFT processing, thus reducing CPU resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If FFT processing is used to remove periodic noise from wheel speed signals, then noise removal effectiveness is improved, but CPU resource consumption increases
Solution Approach 1:
The patent replaces the computational FFT (Fast Fourier Transform) processing system with a time-domain signal processing approach. Specifically, it uses autocorrelation-based methods to identify and remove periodic noise components from wheel speed signals without requiring frequency domain transformation, thereby reducing CPU resource consumption while maintaining noise removal effectiveness
Solution Approach 2:
The patent changes the processing domain parameter from frequency domain (FFT) to time domain (autocorrelation-based methods). By modifying the parameter of noise removal processing from spectral analysis to temporal correlation analysis, it achieves comparable noise removal performance with lower computational burden
2Device complexity
If conventional noise removal methods are used, then processing simplicity is maintained, but noise removal effectiveness is insufficient
Solution Approach 1:
The patent introduces feedback mechanisms where the estimated periodic noise components are continuously refined through autocorrelation analysis. The system uses the detected noise patterns to adjust and improve subsequent noise removal operations, creating a self-correcting process that enhances noise removal effectiveness while maintaining reasonable processing complexity
Solution Approach 2:
The patent applies vibration analysis principles by utilizing autocorrelation to detect periodic patterns in the wheel speed signals. This approach treats the noise removal problem similarly to vibration analysis, where periodic components are identified and separated from the underlying signal through correlation-based methods
Data Source
AI summary
A tire pressure decrease detection apparatus comprising a rotation speed information detection unit for detecting rotation speed information of wheels of a vehicle, a resonance frequency estimate unit for time-series estimating a torsional resonance frequency of the rotation speed information from the rotation speed information obtained by the rotation speed information detection unit, and a judgment unit for judging a decrease in pressure of tires installed in the wheels based on the estimated torsional resonance frequency. The resonance frequency estimate unit includes a noise removal unit for removing a noise superimposed on a wheel speed signal serving as the rotation speed information for each of the wheels with using an active noise control technology.