| 摘要 |
To allow early sensing of anomalies in a manufacturing plant or other infrastructure (plant), provided is a method that acquires data of runtime status of said plant from a plurality of sensors of said plant, makes a model from training data that corresponds to the regular runtime status of said plant, employs the training data thus modeled in computing a anomaly measure of the data acquired from the sensors, and detects anomalies. In computing the anomaly measure, the anomaly is detected by recursively carrying out: a derivation of a residual error from the training data thus modeled acquired from the plurality of sensors, a removal of a signal having a residual error that is greater than a predetermined value, and a computation of the anomaly measure for the data that is acquired from the plurality of sensors whereupon the signal having the large residual error is removed.
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