In this paper we describe an online system for real-time detection of common failure modes of arrays of MEMS microphones. We describe a system with a specific focus on reduced computational complexity for application in embedded microprocessors. The system detects deviations is long-term spectral content and microphone covariance to identify failures while being robust to the false negatives inherent in a passively driven online system. Data collected from real compromised microphones show that we can achieve high rates of failure detection.
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