Study And Application Of Electrostatic Precipitator Controller's Parameter Optimization Algorithm

With high efficiency, low operation cost and good adaptability, electrostatic precipitator (ESP) is widely used in plant, cement, metallurgy and other industries, has made significant contribution on pollution control and environmental protection. But there are several problems of ESP which applying in asphalt purify, for instance can't get ideal purify result and over-dependent manly adjust, and so on.Analyzed the problems of ESP which used for purifying asphalt gas, an intelligent controller based on Field-Programmable Gate Array (FPGA) is introduced, addressed to solve spark discharge problem which has huge influence on ESP's performance. The mainly work is shown as following.(1) According to the function requirements of the ESP supply controller drawn the overall control program with FPGA as the mainly processor. The controller can timely display all kinds of states and faults information, and has RS485 communication interface, which is necessary condition for ESP distributed control system.(2) Selected key chip for the system according to the characteristic of ESP parameter and hardware source requirement. And the circuit schematics are designed based on Protel software.(3) Designed all interface logic circuits and functional logic circuits based on Quartus II integrated development Environment, and each module has passed the simulation, can obtain desired function.Accurately judgment and timely treatment of spark are the key factor of the supply controller. To suppress spark as much as possible, ESP can have higher efficiency under different conditions, not only save energy, but also ensure the facility's safety. In this thesis the following four measures to solve the spark signal suppression problem.(1) Analyzed the feature of ESP's secondary voltage closed-loop control, an incremental digital PID which have dead-zone and integral separation is introduced to the controller, the algorithm will achieve quickly response and avoid overshoot, can suppress spark discharge efficiently.(2) A spark signal prediction model based on neural network is provided, through studied the historical operating parameters of ESP then calculated the prediction operating parameters, thereby get the prediction state. After analyzed the characteristics of ESP's operating parameters, an improved neural network prediction model which including a cluster centers layer is introduced, it can significant reduce the calculation, ensure the prediction algorithm can be successfully transplanted into embedded microprocessor Nios II, and the running time satisfied the system requirement. The simulation of Matlab demonstrated that the model can accurately predict spark signal, is an effective way of float spark track control.(3) Spark discharge signal detection module is designed on FPGA, the detection measurement which based on hardware circuit can ensure spark signal is detected timely and accurately.(4) Two-broken-line tracking algorithm is provided to maintain accurately spark response, and the two-broken-line tracking module which is designed on FPGA hardware circuit can ensure the response in time.