Noise Reduction Device Adaptive Non-Stationary Noise Detection
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Solution Overview
Problem
Existing noise reduction devices in aircraft struggle to accurately differentiate and effectively reduce non-stationary noise, which has different frequency characteristics than stationary noise, leading to deterioration in noise reduction accuracy.
Innovation Solution
A noise reduction device that uses a processor to convert noise signals into the frequency domain, compares these signals with a reference signal to determine if they are non-stationary, and adjusts its noise reduction signal generation accordingly, using adaptive filter coefficients to cancel non-stationary noise and prevent filter divergence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the noise reduction device processes all noise signals uniformly, then stationary noise reduction is effective, but non-stationary noise causes deterioration in accuracy and filter divergence
Solution Approach 1:
The patent implements dynamic adaptation by continuously monitoring frequency characteristics of noise signals and adjusting filter coefficients in real-time. The system transitions between different processing modes (stationary vs. non-stationary noise handling) based on detected signal characteristics, making the noise reduction device adaptive rather than static. This resolves the contradiction by allowing the system to maintain high accuracy for stationary noise while preventing divergence when non-stationary noise is detected.
Solution Approach 2:
The patent changes the parameter of filter coefficient update behavior based on noise type detection. When non-stationary noise is detected through frequency characteristic analysis, the system modifies the update rate or disables updates of filter coefficients, preventing divergence. For stationary noise, normal update procedures continue to maintain accuracy. This parameter adjustment resolves the contradiction between maintaining accuracy and preventing instability.
2Adaptability or versatility
If the device adaptively adjusts processing for different noise types, then noise reduction effectiveness improves, but system complexity increases
Solution Approach 1:
The patent segments the noise signal processing into distinct frequency characteristic bands and evaluates each segment independently. By dividing the frequency spectrum into multiple bands and analyzing characteristics in each band, the system achieves adaptability to different noise types without requiring complete reprocessing of the entire signal. This segmentation approach reduces overall complexity while maintaining versatility.
Solution Approach 2:
The patent introduces an intermediary frequency characteristic analysis stage that mediates between raw noise signals and filter processing. This intermediary layer analyzes spectral characteristics and determines appropriate processing strategies, acting as a bridge that enables adaptive behavior without directly complicating the core filter processing. The intermediary analysis simplifies the control logic while achieving adaptability.
Data Source
AI summary
A noise reduction device includes a processor that converts a noise signal collected by a microphone disposed in a control space into a noise signal in a frequency domain, a storage that stores the converted noise signal in the frequency domain as a reference signal, and a signal generator that generates a noise reduction signal for reducing the noise signal collected by the microphone at a control position of the control space. The processor determines whether or not the noise signal is non-stationary noise based on a frequency characteristic of the converted noise signal in the frequency domain and a frequency characteristic of the reference signal. When it is determined that the noise signal is the non-stationary noise, the processor controls the signal generator so as to cancel generation of the noise reduction signal.