HEAVY METAL WASTEWATER TREATMENT PROCESS ABNORMAL WORKING CONDITION INTELLIGENT MONITORING METHOD AND APPARATUS BASED ON TRANSFER LEARNING, AND STORAGE MEDIUM

摘要

A heavy metal wastewater treatment process abnormal working condition intelligent monitoring method and apparatus based on transfer learning, and a storage medium. In the intelligent monitoring, based on transfer learning, of a heavy metal wastewater treatment process abnormal working condition, data fusion is performed during the treatment process of heavy metal wastewater of different sources, such that intelligent identification of abnormal working conditions during the treatment process of the heavy metal wastewater of different sources can be automatically realized. The method specifically comprises: using a normal sample YSD of the treatment process of heavy metal wastewater of a fixed source and a normal sample YTD of the treatment process of a small amount of heavy metal wastewater of an unknown source; firstly, learning YSD to obtain a data representation dictionary DSD thereof; and then considering that YSD and YTD are different in terms of distribution, fusing features of YTD into a dictionary learning process by using a transfer learning method, so as to obtain a dictionary DTD of a stronger generalization ability. By means of the heavy metal wastewater treatment process abnormal working condition intelligent monitoring method based on transfer learning, uncertain factors in a wastewater treatment system can be adapted to in a self-adaptive manner, without the need for a priori knowledge of a process, changes in related indexes during the process can be detected more accurately, and detection and early warning are achieved in a timely manner.