Research On Radio Frequency Identification Anti-collision Algorithm Based On Particle Swarm Optimization And Application In The Oil Field

In this paper, a set of RFID (Radio Frequency Identification) technology based oil andwater wells data acquisition and inspection system is designed, the problem of RFID tagscollision in the system is emphatically analyzed, and a new type of anti-collision algorithmis proposed. The specific ideas of this algorithm are: by introducing the chaos strategy and thegenetic algorithm, the standard particle swarm optimization(pso) is improved,and the adaptivechaotic particle swarm genetic algorithm is formed; the grouping mechanism and piecewiserecognition mechanism are introduced to improve the basic binary algorithm(bs); then the twoimproved algorithms are combined, and the proposed RFID anti-collision algorithm is formedin this paper. Through simulations and practical tests, the time of RFID tags’ identification isshortened and the efficiency of it is enhanced further by this algorithm.The research content inthis paper is expanded around the multiple tags anti-collision problems in the RFID system.The main research works include:(1) The adaptive chaotic particle swarm genetic algorithm (ACPSO-GA algorithm) isput forward: according to the variation rate of the fitness value, the size of the inertia weightis adjusted, and the searching performance of particle swarm optimization is improved; thechaotic mapping is introduced to initialize the parameters of the particle population, and theprecision of algorithm convergence is enhanced; the mechanism of premature judgment isintroduced, and the particle population is made to jump out of local optimum by the ideas ofselection, crossover and mutation of the genetic algorithm. The ACPSO-GA and PSOalgorithm are compared together through four classical test functions, by which the merits anddemerits of the algorithm are analyzed.(2) The basic binary anti-collision of RFID is improved: the grouping mechanism andpiecewise recognition mechanism are introduced to form the grouping mechanism based onanti-collision algorithm (GPA anti-collision algorithm). Through the better global searchcapability of ACPSO-GA algorithm, the GPA anti-collision algorithm is optimized, thus theRFID tags are quickly identified one by one, which improves the working efficiency. It isobtained by the simulation experiment using MATLAB, that the ACPSO-GA-GPAanti-collision algorithm has ascension in each aspect, when comparing with the GPAanti-collision algorithm and the BS algorithm.(3) The design of the oil and water wells data acquisition and inspection system basedon.NET platform is accomplished: operations such as data acquisition, inspection andpostback of the oil and water wells are realized by the handheld device, the analysis andprocessing of the returned data information of the oil and water wells are achieved by theupper monitoring center, then the change trend diagram of the oil and water wells data isformed, and when it’s combined with the geographic information system GIS, the day and thehistorical curves are generated and stored, which facilitates the staff’s looking up. TheACPSP-GA-GPA anti-collision algorithm is applied to the problem of RFID tags collision in the oil and water wells inspection system, and through the anti-collision experiment using40RFID tags, it is concluded that the improved algorithm is superior to the unimprovedalgorithm.