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Anomaly detection and neural network algorithms for PST hydrocyclone condition monitoring
Anomaly detection and neural network algorithms for PST hydrocyclone condition monitoring
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机译:异常检测和神经网络算法PST水力旋流性能监测
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摘要
A system includes a learning network having a signal processor configured to: receive learned signaling containing information about representative samples of conditions related to operating states of a hydrocyclone and characterized as learned samples of each condition when the learning network is trained, and raw signaling containing information about raw samples containing information about the current operation of the hydrocyclone; and determine corresponding signaling containing information about an operating state of the current operation of the hydrocyclone based upon a comparison of the learned signaling and the raw signaling.
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