Audio Output Detection System for Manufacturing Noise Filtering
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Solution Overview
Problem
Detecting audio output from a device under test in a manufacturing environment is challenging due to high and dynamic ambient noise levels, which existing voice recognition systems fail to filter effectively, especially for hearing-impaired individuals and when assigning text or numbers to specific sounds.
Innovation Solution
A method and system that calibrate a noise threshold, identify a reference audio output, and compare it with detected audio outputs to filter out ambient noise, using an audio output detection system that includes a training module and a matching module to recognize and present information associated with the audio output.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If voice recognition systems are used to detect audio output in manufacturing environments, then audio detection capability is provided, but the systems fail to filter high and dynamic ambient noise levels effectively
Solution Approach 1:
The system performs preliminary noise calibration by capturing ambient noise samples before actual audio detection begins. This pre-established noise profile is stored and used as a reference filter during subsequent audio output detection, allowing the system to distinguish between background manufacturing noise and actual device audio outputs.
Solution Approach 2:
The system continuously monitors audio inputs and compares detected sounds against the calibrated noise threshold. When audio levels exceed the threshold, the system triggers detection routines; when they fall below, it returns to calibration mode. This feedback mechanism dynamically adjusts detection sensitivity based on current environmental conditions.
2Loss of information
If existing voice recognition systems operate in high-noise environments, then audio processing is performed, but the systems cannot reliably assign text or numbers to specific sounds
Solution Approach 1:
The system extracts and isolates specific audio frequency ranges that correspond to expected device outputs, separating them from the broader ambient noise spectrum. By focusing detection efforts on these extracted frequency bands, the system can reliably identify and label specific sounds even in noisy manufacturing environments.
3Measurement precision
If audio detection is performed without noise calibration, then detection speed is maintained, but detection accuracy deteriorates in dynamic noise environments
Solution Approach 1:
The system implements periodic noise calibration cycles interspersed with detection operations. Rather than continuous calibration that would halt production, the system performs brief calibration intervals at predetermined times or when noise threshold violations occur, maintaining accuracy without excessive time loss.
Data Source
AI summary
A system, method, and computer-readable medium are disclosed for performing an audio output detection operation. The audio detection operation includes: identifying a reference audio output associated with a manufacturing environment; calibrating a threshold noise level of the manufacturing environment; monitoring the manufacturing environment for an audio output above a predefined noise threshold; comparing the audio output above the predefined noise threshold with the reference audio output; and, present information associated with the audio output above the predefined noise threshold upon detection of a match between the audio output above the predefined noise threshold and the reference audio output.