The System of Temperature Rise Monitoring and Temperature Prediction for Power Equipment

The power equipment is an important component of the power system, which will seriously threat the stability of power system when the heat fault occurs during its running. An integrated system has been designed in this paper directed against the characteristics of thermal fault, which can implement the functionality of temperature acquisition, realtime display and fault warning. The real-time temperature can be stably collected via wireless transmission, low-power technology and so on. The dynamic threshold algorithm based on beta distribution is used to eliminate the singularity data that potential introduced in the process of data transmission or acquisition. The development trend of the equipment temperature can be predicted by means of the temperature prediction model established through the process neural network. The experimental results show that the system can effectively measure and display the temperature of power equipment and predict the development of temperature trend, which has higher precision.