| 摘要 |
Detecting poor data quality for a sensor includes obtaining measurement data for the sensor, determining a plurality of data quality indicators using the measurement data, combining the data quality indicators into a single scalar value, and determining if the single scalar value exceeds a predetermined threshold. Combining the data quality indicators may include, for each of the data quality indicators, squaring a difference between the measurement data for the sensor and the mean for each of the data quality indicators and dividing the result thereof by the variance to provide a partial value, wherein the single scalar value is the sum of all of the partial values. Detecting poor data quality may include providing a 1xn array of mean values for the data quality indicators, wherein there are n data quality indicators. Detecting poor data quality may include providing an nxn array of covariance values, wherein an element in the ith row and jth column represents a covariance between an ith data quality indicator and a jth data quality indicator. The single scalar value may be determined using the formula (M-X)<T>COV<-1>(M-X), where X represents a 1xn array corresponding to the measurement data for the sensor, M represents the 1xn array of mean values for the data quality indicators, COV represents the nxn array of covariance values, T represents a matrix transpose operation, and -1 represents a matrix inverse operation.
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