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Outlier detection for sensor systems (ODSS): A MATLAB macro for evaluating microphone sensor data quality

Sensors (Switzerland) (2017) 17(10)
DOI: 10.3390/s17102329
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Abstract

Microphone sensor systems provide information that may be used for a variety of applications. Such systems generate large amounts of data. One concern is with microphone failure and unusual values that may be generated as part of the information collection process. This paper describes methods and a MATLAB graphical interface that provides rapid evaluation of microphone performance and identifies irregularities. The approach and interface are described. An application to a microphone array used in a wind tunnel is used to illustrate the methodology.

Figures

  • Table 1. Percentage of observations determined to be acceptable or rejected as outliers using a cutoff of 3.0 or the Bonferroni cutoff for various time series models. The model parameters are given in parentheses. A false rate of rejection of γ = 0.05 (5%) is expected for the Bonferroni method.
  • Figure 1. Virginia Tech wind tunnel where microphone array data were collected.
  • Figure 2. Top view of the test section used in the experiment to collect microphone array data, showing the anechoic chamber. All measurements are in meters.
  • Figure 3. Top view of the experimental layout for collecting microphone array data.
  • Figure 4. Locations of microphones to collect array data.
  • Figure 5. Spectral densities and plots identifying unusual segments in the microphone array data.
  • Figure 6. Graphical displays for channel 4 in the microphone array data.
  • Figure 7. Graphical displays for channel 6 in the microphone array data.

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CITATION STYLE

APA

Vasta, R., Crandell, I., Millican, A., House, L., & Smith, E. (2017). Outlier detection for sensor systems (ODSS): A MATLAB macro for evaluating microphone sensor data quality. Sensors (Switzerland), 17(10). https://doi.org/10.3390/s17102329

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