OPC UA information model data self-adaption method based on transfer learning

The invention discloses an OPC UA information model data self-adaption method based on transfer learning, and belongs to the technical field of industrial automation. The method comprises the following steps: acquiring information of each physical entity in a digital workshop production line, and further constructing an information model of each physical entity; an information model is mapped to an address space conforming to OPC UA, mapping of the information model to an OPC UA server is achieved, an OPC UA client communicates with the OPC UA server, and obtained data is transmitted to a persistent layer data center; historical data and real-time data of each physical entity information acquired from a persistent layer data center are utilized to construct a source domain data set and a target domain data set, an instance-based transfer learning algorithm is adopted to train a quality prediction model, a swarm intelligence algorithm is combined, quality prediction model parameters are adaptively adjusted, an