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Title:
WASTEWATER TREATMENT PROCESS FAULT MONITORING METHOD USING OICA-RNN FUSION MODEL
Document Type and Number:
WIPO Patent Application WO/2021/114320
Kind Code:
A1
Abstract:
A smart fault monitoring method based on a high-order information-enhanced recurrent neural network, said method being used to carry out real-time monitoring of wastewater treatment process faults, and comprising two phases: offline training and online soft measurement. The offline phase first uses OICA to extract raw data into high-dimensional high-order information features, used for the effective processing of non-Gaussian properties of the data and determining the correlation between variables. Then training of the extracted features is carried out by means of a DRNN. In the online phase, the data are mapped directly into new high-order feature components and are classified and discriminated by the DRNN that was trained offline. If the results are fault-free, then a monitoring model composed only of OICA is used to carry out unsupervised monitoring. If a fault has still not been detected at this point, the process is determined to be fault-free, and if a fault occurs, then the process is determined to be faulty and the fault information is entered into the network training data and training is carried out, thereby continuously improving the monitoring precision of the DRNN.

Inventors:
CHANG PENG (CN)
LI ZEYU (CN)
WANG KAI (CN)
DING CHUNHAO (CN)
JIN CHEN (CN)
ZHANG XIANGYU (CN)
LU RUIWEI (CN)
WANG PU (CN)
Application Number:
PCT/CN2019/125888
Publication Date:
June 17, 2021
Filing Date:
December 17, 2019
Export Citation:
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Assignee:
UNIV BEIJING TECHNOLOGY (CN)
International Classes:
G01N33/18
Foreign References:
CN105740619A2016-07-06
CN110088619A2019-08-02
CN107741738A2018-02-27
CN106056127A2016-10-26
CN110119579A2019-08-13
JP3301428B22002-07-15
Attorney, Agent or Firm:
BEIJING SIHAI TIANDA INTELLECTUAL PROPERTY AGENCY LTD. (CN)
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