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1. (WO2018057676) ANOMALY DETECTION AND NEURAL NETWORK ALGORITHMS FOR PST HYDROCYCLONE CONDITION MONITORING

Pub. No.:    WO/2018/057676    International Application No.:    PCT/US2017/052607
Publication Date: Fri Mar 30 01:59:59 CEST 2018 International Filing Date: Fri Sep 22 01:59:59 CEST 2017
IPC: G01F 1/00
G01F 1/32
G01F 25/00
G01F 1/74
G01N 9/36
G01N 15/02
G01N 29/44
Applicants: CIDRA CORPORATE SERVICES, INC.
Inventors: DAVIS, Michael, A.
Title: ANOMALY DETECTION AND NEURAL NETWORK ALGORITHMS FOR PST HYDROCYCLONE CONDITION MONITORING
Abstract:
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.