Intelligent monitoring method and device for abnormal working conditions in heavy metal wastewater treatment process based on transfer learning and storage medium

Abstract

The invention discloses an intelligent monitoring method and device for abnormal working conditions of a heavy metal wastewater treatment process based on transfer learning and a storage medium; according to the abnormal working condition intelligent monitoring of the heavy metal wastewater treatment process based on transfer learning, data fusion in the treatment process of heavy metal wastewater from different sources is performed, and intelligent identification of abnormal working conditions in the treatment process of heavy metal wastewater from different sources can be automatically realized; the method specifically comprises the following steps: utilizing a normal sample YSD of a heavy metal wastewater treatment process with a fixed source and a normal sample YTD of a treatment process of a small amount of heavy metal wastewater with an unknown source; learning YSD to obtain a data representation dictionary DSD of the YSD, and then considering that the YSD and the YTD are different in distribution, fusing the characteristics of the YTD into a dictionary learning process by adopting a transfer learning method to obtain a dictionary DTD with stronger generalization ability. According to the method, process priori knowledge is not needed; the method can adapt to uncertain factors in a wastewater treatment system in a self-adaptive mode, changes of related indexes in the process can be detected more accurately, and timely detection and early warning are achieved.

Description

technical field [0001] The invention belongs to the field of heavy metal wastewater treatment, and in particular relates to an intelligent monitoring method, device and storage medium for abnormal working conditions in the heavy metal wastewater treatment process based on transfer learning. Background technique [0002] As an irreplaceable natural resource and environmental resource on the earth, the storage and quality of water are closely related to the survival and development of human beings. With the rapid development of industry in recent years, industrial wastewater, especially heavy metal wastewater, has caused serious environmental pollution and far-reaching harm to humans. At the same time, heavy metals have high stability in the environment, are difficult to degrade, and have a wide range of migration, which is gradually becoming a global environmental problem. [0003] Flocculation-electrochemical technology is one of the effective ways to achieve deep purificat...

AI Technical Summary

Problems solved by technology

[0004] In order to accurately identify the abnormal working conditions of the heavy metal wastewater treatment process from different sources, and at the same time overcome the problems caused by the data distribution distortion caused by the concentration data of heavy metal ions from different sources and cause the model mismatch, the present invention proposes a method based on transfer learning. An intelligent monitoring method, device, and storage medium for abnormal working conditions in the treatment process of heavy metal wastewater. The method can adapt to heavy metal wastewater from different sources and accurately identify the working conditions of the treatment process.

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