基于相对湿度的棉花回潮率在线检测

Online detection of cotton moisture regain based on relative humidity

为了解决棉花加工过程中回潮率的在线检测问题,提出了一种基于相对湿度的棉花回潮率在线检测方法.硬件设计采用HIH3610湿度传感器和DS2438温度电压检测器,得到了采样探头气窗内的空气温度和相对湿度.利用BP神经网络建立了温度、相对湿度与棉花回潮率的关系模型.结果表明,随着相对湿度的升高,棉花的平衡回潮率显著增大,随着温度的升高,平衡回潮率逐渐减少;湿度达到平衡的时间约为10 s;采样延时对一个棉包产生的不良率为4.65%;BP模型的回潮率最大绝对误差小于0.2%.所得结论表明,基于相对湿度的棉花回潮率检测方法满足棉花加工行业对回潮率控制精度和实时性的要求.

In order to solve the online detection of moisture regain in the processing course of cotton, an online detection method for cotton moisture regain based on relative humidity was proposed. The hardware was designed with adopting an HIH3610 humidity sensor as well as a DS2438 temperature and voltage detector. Then the air temperature and relative humidity in the louver of sampling probe were obtained. The relational model for the temperature, relative humidity and cotton moisture regain was established with the BP neural network. The results show that with increasing the relative humidity, the equilibrium cotton moisture regain obviously increases. With increasing the temperature, the equilibium moisture regain gradually decreases. And the time to reach the moisture balance is about 10 s. In addition, the defective percent of a cotton bale due to the sampling delay is 4.65 %, and the maximum absolute error of moisture regain for BP model is less than 0.2%. The obtained conclusions show that the online detection method for cotton moisture regain based on relative humidity can meet the requirements in the control accuracy and real time performances for the cotton processing industry.