Active Noise Reduction Adaptive Filter Stability
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Solution Overview
Problem
Existing active noise-reduction technologies face challenges in maintaining control stability and convergence speed of adaptive filters, leading to inefficient noise reduction due to the trade-off between these two factors, especially when environmental characteristics change or when a reference signal changes abruptly.
Innovation Solution
An active noise-reduction apparatus utilizing a reference signal generation unit with multiple reference microphones to generate reference signals, a filter processing unit to generate control signals, an averaging unit to combine these signals, a control speaker to output control sound, and a filter update unit to minimize error signals, incorporating a consensus term in update rules to improve secondary path identification precision and stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If parameters (step sizes) for controlling coefficient update amounts of adaptive filters are adjusted to prevent transient increase in input to control speaker, then control stability is improved, but convergence of adaptive filters requires much time
Solution Approach 1:
The patent segments the adaptive filter update process into two distinct phases: a transient phase where multiple reference signals are processed with larger step sizes to achieve rapid convergence, and a steady-state phase where a single reference signal is used with smaller step sizes to maintain control stability. This segmentation allows the system to optimize for both convergence speed and stability at different stages of operation.
Solution Approach 2:
The patent dynamically adjusts the update rule based on the operational phase of the system. During transient periods when reference signals change abruptly, the system uses update rules that prioritize convergence speed. Once convergence is achieved, the system transitions to update rules that prioritize stability. This dynamic adaptation resolves the contradiction by allowing different parameter settings at different times.
2Speed
If a reference signal changes abruptly at the time of generation of noise, then noise reduction response is improved, but input to control speaker increases transiently causing noise increase and unstable control
Solution Approach 1:
The patent applies preliminary action by processing multiple reference signals before generating the control signal during transient phases. This preliminary processing allows the adaptive filters to converge more quickly to optimal coefficients, enabling faster noise reduction response. The system prepares the filter coefficients in advance using multiple reference signals, which prevents the transient instability that would otherwise occur when a single reference signal is used.
Solution Approach 2:
The patent uses feedback mechanisms where the error signal from the error microphone is continuously monitored and used to update the adaptive filter coefficients. By incorporating multiple reference signals into the feedback loop during transient phases, the system can more accurately track changes in the noise characteristics and adjust the control signal accordingly, preventing transient increases in control speaker input while maintaining fast response.
3Object-affected harmful factors
If Filtered-x method is used for active noise control, then noise reduction is achieved, but secondary path identification is required in advance which cannot be used when environmental characteristics change or apparatus cannot be fixed
Solution Approach 1:
The patent replaces the static secondary path identification requirement of the Filtered-x method with a dynamic adaptive filtering approach. Instead of requiring pre-identified spatial characteristics, the system continuously adapts its filter coefficients based on real-time error signals and multiple reference signals. This dynamic adaptation allows the system to automatically adjust to changing environmental characteristics and apparatus positions without requiring re-identification of the secondary path.
Solution Approach 2:
The patent implements self-service by enabling the active noise control system to automatically identify and adapt to its own operating conditions. The multiple reference signals and adaptive filters work together to self-calibrate the system, eliminating the need for external secondary path identification. The system serves itself by continuously learning the acoustic environment through the error microphone feedback and adjusting its control strategy accordingly, making it adaptable to environmental changes and apparatus movement.
Data Source
AI summary
According to one embodiment, an active noise-reduction apparatus includes following units. The reference signal generation unit generates different reference signals based on target sound generated from a sound source. The filter processing unit generates first control signals by filtering the reference signals using first digital filters. The averaging unit generates a second control signal by averaging the first control signals. The control speaker outputs the second control signal as control sound. The error microphone detects a synthetic sound pressure of the target sound and the control sound to generate an error signal. The filter update unit updates the first digital filters so that the error signal is minimized.