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.
https://www.aes.org/e-lib/browse.cfm?elib=19350
Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!
This paper costs $33 for non-members and is free for AES members and E-Library subscribers.
Learn more about the AES E-Library
The Engineering Briefs at this Convention were selected on the basis of a submitted synopsis, ensuring that they are of interest to AES members, and are not overly commercial. These briefs have been reproduced from the authors' advance manuscripts, without editing, corrections, or consideration by the Review Board. The AES takes no responsibility for their contents. Paper copies are not available, but any member can freely access these briefs. Members are encouraged to provide comments that enhance their usefulness.
Start a discussion about this paper!
