Research On Optimization Of Oil-pumping Unit Control System

Before the intelligent control system has not been widely applied, the oil pumping unit is usually controlled by artificial experience, which needs a lot of manpower and material resources.And pumping unit often appear empty phenomenon, which will not only cause pumping invalid stroke increased, thereby reducing the efficiency of the pumping and consume a lot of energy, and can cause mechanical loss accelerated, the maintenance costs increase.So in the production practice, we want to promote the extensive application of pumping unit intelligent control system.To realize the intelligent control of pumping unit need to know the level information, in order to determine the time of the switch machine.The level information can be indirectly reflected by the load size, and the phase current value is related to the load change, so we analyze the change of the liquid level by the current value.First, using AC transformer to collect load current value, then the data into the CPU microcomputer control system are analyzed, and the level of information to the liquid level display circuit.This paper is mainly about the modeling and design of the control system, which is based on the K nearest neighbor algorithm and the support vector machine.Finally, the optimal stopping time is optimized by using the particle swarm optimization algorithm, so as to control the motor by controlling the relays.All of the above algorithms are programmed and tested, the program is easy portingto other hardware platforms forits C++programming language.