This paper explores the feasibility of using physical information neural network to solve the time-dimensional infinite plate temperature field problem, and compares the method with the traditional numerical method. Physical information neural networks integrate physical principles into learning algorithms and provide a new method to handle complex partial differential equation problems. In this study, the temperature field of a one-dimensional time-varying infinite plate with an internal and no internal heat source is studied respectively. The results show that the physical information neural network can achieve the same solution accuracy and speed by relying only on random sampling points. Nevertheless, the effectiveness of physical information neural networks in solving more complex heat conduction problems still needs further research.