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METHOD FOR PREDICTING A MAINTENANCE OPERATION AND RECOMMENDING MAINTENANCE FOR WATER TREATMENT EQUIPMENT

发明专利审中
29权利要求 · 4 独立
§ Ⅰ

卷宗概要

发明人

Claire VENTRESQUE; Marie GAVERIAUX; Remi CUINGNET

IPC 分类

B1D 65/10B1D 65/2C2F 1/C2F 103/8G6N 3/44G6Q 10/20

CPC 分类

B1D65/102B1D65/2C2F1/8G6N3/44G6Q10/20B1D2311/10B1D2311/14B1D2315/20B1D2321/40C2F2103/8C2F2303/14

The present invention relates to a method for automated data processing to assess the state of multiple filtration membranes used in liquid filtration. The method involves receiving data from state sensors positioned within or near a set of membranes, which process incoming water into permeate and concentrate flows. This data, collected as time series at predefined frequencies, pertains to external physical parameters. An operating indicator is determined from this data, forming a second time series. Both the first and second time series are recorded as point clouds over a specified acquisition period. An intermediate operating indicator is generated, representing the state of new, clean, or cleaned membranes, using a learned normalization model. Finally, a normalized operating indicator is produced, characterizing membrane fouling and aging, independent of environmental variations, and forming a third time series. This method enhances the accuracy of membrane state assessment in filtration systems.

原文(中文)

The present invention relates to a method for automated data processing to assess the state of multiple filtration membranes used in liquid filtration. The method involves receiving data from state sensors positioned within or near a set of membranes, which process incoming water into permeate and concentrate flows. This data, collected as time series at predefined frequencies, pertains to external physical parameters. An operating indicator is determined from this data, forming a second time series. Both the first and second time series are recorded as point clouds over a specified acquisition period. An intermediate operating indicator is generated, representing the state of new, clean, or cleaned membranes, using a learned normalization model. Finally, a normalized operating indicator is produced, characterizing membrane fouling and aging, independent of environmental variations, and forming a third time series. This method enhances the accuracy of membrane state assessment in filtration systems.