| 摘要 |
A method for data-driven anomaly detection may include monitoring a plurality of parameters associated with a plurality of subsystems of a system. The method may also include collecting data corresponding to each of the plurality of parameters from the plurality of subsystems and generating monitoring quantities based on the data. The method may also include determining if any quantities in the monitoring quantities exceed a predetermined limit. A contribution plot may be generated corresponding to each of the parameters in response to any of the quantities exceeding the predetermined limit. The method may further include determining which parameter is likely to cause an effect based on the contribution plot.
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