Abstract: An intelligent monitoring method and apparatus for abnormal working conditions in a heavy metal wastewater treatment process based on transfer learning and a storage medium are provided. During an intelligent monitoring, the abnormal working conditions can be automatically and intelligently recognized by fusing data in the treatment process of the heavy metal wastewater different in source; specifically, a normal sample YSD in the treatment process of the heavy metal wastewater with fixed sources and a small number of normal samples YTD in the treatment process of the heavy metal wastewater with unknown sources are utilized; and first, a data representation dictionary DSD of YSD is obtained through learning on YSD, and then considering different distribution of YSD and YTD, a transfer learning method is adopted to fuse characters of YTD into a dictionary learning process to obtain a dictionary DTD with higher generalization ability.