Microphone Failure Detection via Signal Saturation Analysis
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Solution Overview
Problem
Conventional microphone failure detection methods only consider low sound signal levels and fail to detect failures when signal levels are high, neglecting potential issues in microphone systems.
Innovation Solution
A failure detection apparatus that acquires and analyzes time-series signals from sensor modules, specifically looking for saturation, amplitude changes, silence, and amplitude levels to determine the state of the sensor module, including the use of a signal analysis unit to generate analysis results and a determination unit to assess failure based on predetermined criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional microphone failure detection methods are used that only consider low sound signal levels, then detection simplicity is maintained, but detection completeness deteriorates because failures with high signal levels are not detected
Solution Approach 1:
The patent applies parameter changes by analyzing multiple signal parameters (amplitude, saturation, silence duration) instead of relying on a single parameter (low signal level). This allows the system to detect both low and high signal level failures by examining different characteristics of the time-series signal from microphones.
Solution Approach 2:
The patent uses partial action by implementing a multi-stage detection process that first checks for saturation (a specific condition), then checks for silence periods, and finally compares signal levels. This staged approach comprehensively detects various failure modes without requiring overly complex simultaneous analysis of all parameters.
2Measurement precision
If signal saturation analysis is added to detect high signal level failures, then detection precision is improved, but analysis complexity increases
Solution Approach 1:
The patent examines multiple signal parameters including amplitude ranges, saturation conditions, and silence duration. By analyzing these different parameters, the system achieves precise failure detection across various failure modes while maintaining manageable analysis complexity through structured processing.
Solution Approach 2:
The patent segments the failure detection process into distinct stages: saturation detection, silence period detection, and signal level comparison. Each stage handles a specific aspect of failure detection, making the overall complex analysis manageable through modular processing steps.
Data Source
AI summary
According to one embodiment, a failure detection apparatus includes processing circuitry. The processing circuitry acquires a time-series signal generated by a sensor module, generates an analysis result including information concerning saturation of the time-series signal by analyzing the time-series signal, and determine a failure of the sensor module based on the analysis result.