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针对传感器的测量精度受温度影响较大问题,提出了一种基于云粒子群-最小二乘支持向量机(CMPSO-LSSVM)的温度补偿方法。云粒子群算法(CMPSO)将云模型算法应用于粒子群优化(PSO)算法的收敛机制,具有寻优精度高的特点。CMPSO算法对LSSVM的参数进行优化选择,建立CMPSO-LSSVM传感器温度补偿模型。将该模型应用于振弦式传感器的温度补偿,通过实验证明了该温度补偿方法优于当前其他主要方法。
Aiming at the problem that the measuring accuracy of the sensor is greatly influenced by the temperature, a temperature compensation method based on cloud particle swarm least-squares support vector machine (CMPSO-LSSVM) is proposed. The cloud particle swarm algorithm (CMPSO) applies the cloud model algorithm to the convergence mechanism of Particle Swarm Optimization (PSO) algorithm, which has the characteristics of high precision. CMPSO algorithm to optimize the parameters of the LSSVM, the establishment of CMPSO-LSSVM sensor temperature compensation model. The model is applied to the temperature compensation of the vibrating wire sensor. Experiments show that the temperature compensation method is superior to other current main methods.