Recorded Sound Comparison for Acoustic Noise Source Isolation
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Solution Overview
Problem
Electronic devices produce and are exposed to unwanted acoustic noise, which can be difficult to identify and isolate the source of.
Innovation Solution
A system is provided that uses a playback device to produce sounds using audio files, records these sounds with recording devices, and compares the recorded sounds to the original files to determine and eliminate potential noise sources using a process of elimination, employing Fast Fourier Transform (FFT) analysis to identify noise presence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple recording devices and playback devices are used to determine noise sources through a process of elimination, then the accuracy of noise source identification is improved, but the device complexity and setup requirements worsen
Solution Approach 1:
The system segments the noise detection task by assigning different recording devices to different spatial locations or recording channels. Each recording device independently records sounds, and the processor compares recordings from multiple devices to identify which device captured the noise, thereby segmenting the overall detection problem into manageable individual device evaluations.
Solution Approach 2:
The system merges multiple recording devices and playback devices into a unified noise detection system. The processor combines the recordings from multiple recording devices and compares them collectively against the audio file to determine which device captured the noise, achieving improved identification accuracy through the combined effort of multiple components.
2Measurement precision
If FFT analysis is used to compare recorded sounds with original audio files, then the precision of noise detection is improved, but the computational requirements and processing time worsen
Solution Approach 1:
The system extracts the noise component from the recorded sound by comparing it with the original audio file using FFT analysis. The processor isolates the differences between the recorded sound and the expected sound from the audio file, extracting only the noise portion for identification and elimination purposes.
Solution Approach 2:
The system transforms the audio signals from the time domain to the frequency domain using Fast Fourier Transform (FFT) analysis. This parameter transformation allows for more precise comparison of spectral characteristics between the recorded sound and the original audio file, enabling accurate noise detection through frequency-based analysis.
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
Effectively determines and isolates internal and external noise sources by comparing recorded sounds to original audio files, enhancing user experience by reducing unwanted noise.
Implementation Method 1
employing Fast Fourier Transform (FFT) analysis to identify noise presence
Data Source
AI summary
In some examples, a non-transitory computer-readable medium stores machine-readable instructions which, when executed by a processor, cause the processor to cause a playback device to produce a sound using an audio file; cause a recording device to record the sound; compare the audio file to the recorded sound; determine, based on the comparison, whether the recorded sound comprises a noise not present in the audio file; and cause, based on the determination, a second recording device to be selected, a multiplexer to select a second playback device, or a combination thereof.