改进型灰狼算法在热电偶动态补偿中的应用

为解决热电偶传感器在瞬态温度测试过程中因传感器动态性能不足引入动态误差影响测试精度的问题,提出基于改进型灰狼优化算法的热电偶传感器动态补偿方法.通过改变候选解产生策略和引入动态权重因子,对灰狼优化算法(GWO)进行改进,从而进一步提高了热电偶传感器的时间常数.根据热电偶传感器水浴法校准数据寻优获得补偿系统传递函数,并对实测火焰数据进行实验.实验结果表明,水浴法校准数据经补偿后时间常数由0.0685s提升为0.0147s,动态误差减小了近75%.经IGWO寻优获得的动态补偿系统,可有效地改善热电偶传感器的动态特性,减小热电偶传感器的动态误差.

Application of improved grey wolf algorithm in dynamic compensation of thermocouple

In order to solve the problem of the dynamic error affecting the test accuracy of the thermocouple sensor during the transient temperature test, the dynamic compensation method of the thermocouple sensor based on the improved gray wolf optimization(IGWO) algorithm is proposed. The gray wolf optimization(GWO) algorithm is improved by changing the candidate solution generation strategy and introducing the dynamic weighting factor, thereby further improving the time constant of the thermocouple sensor. According to the thermocouple sensor water bath method calibration data to obtain the compensation system transfer function, and experiments on the actual measured flame data is performed. The experimental results show that the time constant of the water bath calibration data is increased from 0.0685s to 0.0147s, and the dynamic error is reduced by nearly 75%. The dynamic compensation system obtained by IGWO optimization effectively improves the dynamic characteristics of the thermocouple sensor and reduces the dynamic error of the thermocouple sensor.