Design Of Monitoring System For High-frequency Power Of Thermal Power Plant Based On IOT Technology

With the constant reinforce of our national power, the energy is needed more and more especially electricity. The electricity is mainly supplied by thermal power generation. How to reduce the pollution brought by thermal power generation has been a problem which must be solved in the context of energy conservation and emission reduction. The electrical precipitator is widely applied as a device that reducing the dust pollution. The running state of high frequency power is good or not will directly influence that the running efficiency of the electrical precipitator is high or low. Artificial monitoring is hard and dangerous because of that the environment of the heat-engine plant is very atrocious and the geographical position is far.This system can get the running data and running state of the high frequency power from a far distance by utilizing the technology of the Internet of Things to combine the upper computer monitoring platform and GPRS network and the fault diagnosis system and many kinds of monitor device running in the scene.This paper presents every part of the Internet of Things in details aiming at the requirement object. We compare merits and shortcomings of all kinds of transmission mode applied presently and ensure that utilizing the way of the combine of the GPRS and internet to transmit the data or the GPRS to achieve the mobile data transmission directly. We analyze the characteristic which the VB and serious of SQL data bank have and ensure the project that utilizing the VB and SQL to build the upper computer platform.Then we design the overall structure of the upper computer platform and present the function every module should have in details. We present the operating principle of the GPRS communication module and how to control the GPRS communication module with the upper computer. We present the structure and function of every table in the data bank in details.At last, we present the monitoring and diagnosis system of high frequency power and present the diagnosis way of three-phase rectification circuit in high frequency power in details, utilizing the MATLAB to simulate the three-phase full control rectification circuit and analyzing the output voltage wave form in every fault state. We present the wavelet analysis and the choice of the wavelet basis in details and utilize the wavelet basis which is chosen to draw the characteristic quantity of the output voltage wave form in every fault state. We ensure the structure of neural network which is used to diagnose the fault and utilize the ant colony algorithm to optimize the neural network. It enhances the diagnosis accuracy and precision of the network and reduces the time taken in the fault remove.