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Digital twin is a multi-disciplinary, multi-physical,multi-scale,multi-probability simulation process that makes full use of physical model, sensor update, operation history and other data to complete the mapping in virtual space, thereby reflecting the full life cycle of the corresponding physical equipment Process. Starting from the development trend of smart heating, and relying on the concept of industrial systems, a smart heating technology based on "digital twin" is proposed. Firstly, the basic structure of the digital twin is introduced, and the construction method of the digital twin is given. Based on the big data acquisition, processing, archiving and simulation of the virtual instrument Labview; then, based on the collected data, the twin model of the heating system is obtained. The key problems solved by the digital twin technology are discussed; finally, the neural network intelligent algorithm in Matlab is called through the Labview simulation platform to obtain parameters based on big data acquisition and optimized by the intelligent algorithm. Model simulation, optimization, feedback process. The effectiveness of the application of Labview and Matlab hybrid programming on the established twin heating platform is verified through the optimization simulation case of the heating network system.