Noise Abatement System Frequency Segmentation
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Solution Overview
Problem
Current electronic noise cancellation systems are limited in effectively canceling dynamic and high-frequency noise, with an upper frequency limit below 4 kHz and attenuation capabilities of only 10 dB to 30 dB, failing to perform well across the full audio spectrum in real-time.
Innovation Solution
The system processes discrete frequency segments to calculate precise anti-noise signals, enabling effective noise cancellation across the entire audio spectrum in real-time, even for high frequencies, by subdividing noise signals into smaller segments and applying frequency-dependent phase shifts for destructive interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional adaptive filtering (LMS) is used for noise cancellation, then low-frequency repetitive noise can be reduced by 10-30 dB, but the system cannot effectively cancel high-frequency or rapidly changing noise above 2-4 kHz
Solution Approach 1:
The patent segments the audio frequency spectrum into multiple discrete frequency bands (e.g., using FFT to divide into 64 or 128 bands). Each frequency band is processed independently with its own adaptive filter, allowing the system to handle different frequency characteristics separately. This segmentation enables effective cancellation across the entire audio spectrum rather than being limited to low frequencies.
Solution Approach 2:
The patent transforms the noise cancellation approach from time-domain adaptive filtering to frequency-domain processing. By applying FFT to convert time-domain signals into frequency-domain representations, the system can apply frequency-dependent phase shifts and independent adaptive filtering to each frequency band, effectively extending the usable frequency range beyond what conventional time-domain methods achieve.
2Measurement precision
If the noise cancellation system processes the entire audio spectrum in real-time, then high-frequency noise can be cancelled, but the processing complexity and computational requirements increase significantly
Solution Approach 1:
By dividing the audio spectrum into discrete frequency bands using FFT, the complex task of full-spectrum real-time processing is broken into multiple simpler parallel tasks. Each frequency band can be processed with relatively simple adaptive filtering operations, and the results are combined through inverse FFT. This segmentation makes real-time full-spectrum processing computationally feasible.
Solution Approach 2:
The system performs preliminary FFT transformation of the input signal before applying adaptive filtering to each frequency band. This preliminary frequency-domain conversion enables more efficient processing compared to time-domain methods, as the subsequent adaptive filtering operations in the frequency domain are computationally less intensive than equivalent time-domain operations would require.
3Reliability
If multiple microphones and complex adaptive filtering algorithms are used to extend frequency range, then high-frequency noise cancellation improves, but the system complexity and cost increase
Solution Approach 1:
The patent replaces the mechanical approach of using multiple microphones with a signal processing approach. Instead of adding more physical sensors to capture different frequency components, the system uses a single microphone input that is then processed through FFT-based frequency domain analysis and frequency-dependent phase shifting. This substitution of mechanical complexity with computational processing achieves extended frequency coverage without additional hardware.
Solution Approach 2:
The system changes the processing parameters dynamically based on frequency content. By applying frequency-dependent phase shifts and adjusting adaptive filter parameters for each frequency band independently, the system optimizes noise cancellation effectiveness across the entire audio spectrum using the same hardware infrastructure, avoiding the need for multiple microphones with fixed frequency responses.
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 approach allows for superior noise cancellation across the audio spectrum, reducing the need for multiple microphones and complex algorithms, and can be applied in various applications, including headphones, telecommunications, and electromagnetic signal processing, with potential for real-time processing of any electromagnetic signal as processing power increases.
Implementation Method 1
The basic physics of wave propagation suggests it is possible to create an 'anti-noise' wave that is 180 degrees out of phase with the noise signal, and cancel the noise completely through destructive interference.
Data Source
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AI summary
Noise abatement within a signal stream containing unwanted signal referred to as noise is performed by acquiring a digitized noise signal and using a digital processor circuit to subdivide the acquired noise signal into different frequency band segments and thereby generate a plurality of segmented noise signals. Then individually for each segmented noise signal, the processor shifts in time the segmented noise signal by an amount dependent on a selected frequency of the segmented noise signal to produce a plurality of shifted segmented noise signals. The precise time shift applied to each noise segment considers the frequency content of the segment and the system processing time. Individually for each segmented noise signal, amplitude scaling is applied. The shifted and amplitude-scaled segmented noise signals are then combined to form a composite anti-noise signal which is output into the signal stream to abate the noise through destructive interference.