电动机拖动的启闭机荷重开度检测系统研究

Load and Opening Detection System for Hoist Driven by Motor

荷重开度一体式传感器安装在电动机输出轴与启闭机的动力输入轴之间,可以输出包括启闭机实际负载引起的总力矩及用于开度检测的计数脉冲等电信号,同时起到联轴器的作用。通过次级旋转的变压器耦合及光电耦合方法分别实现了传感器内部旋转电路的供电及总力矩与开度脉冲等电信号的非接触传输。为了从一体式传感器输出的总力矩信号中获取启闭机的实际负载,荷重检测分为2个阶段,首先利用灰色关联校正环节对传感器内部弹性轴所受总力矩对应的模数转换(ADC)输出值进行校正,将获得的趋于稳定的ADC校正值作为第1阶段实际输出值,并将该输出值作为输入变量,在第2阶段,分别利用最小二乘支持向量回归(LS-SVR)和偏最小二乘回归(PLSR)方法实现对启闭机负载的回归预测,再通过灰色关联校正环节对该负载预测值进行校正得到最终的启闭机实际负载。试验结果表明,结合灰色关联校正方法,采用LS-SVR的启闭机实际负载回归误差在±0.6%范围内,利用PLSR的启闭机负载回归误差在±1%范围内。同时,由于荷重开度一体式传感器与电动机输出轴直接连接,在启闭机升降过程中,输出的开度计数脉冲数增加,提高了开度检测分辨率,实际开度分辨率远小于1 mm。

Installed between the motor＇s shaft and the hoist power input one,an integrate sensor could output not only the total torque signal related to the change for hoist＇s load but also 60 pulses per revolution for motor＇s shaft. The hoist＇s opening could be calculated by associating the number of those pulses with some parameters of the hoist. In the integrate sensor,those rotary circuits could be powered from the rotary secondary of transformer whose primary was fixed with the sensor＇s metal shell,which was used as a part of magnetic core of the transformer. By using the photoelectric coupling method,non-contact transmission for the sensor＇s signals about the total torque and the opening was realized. Besides the torque caused by constant load,the total one also included some other torques shown as fluctuation and unsteadiness because of those factors,such as friction existing in the hoist＇s mechanical structure. In order to get the actual load from the total torque signal,two phases were selected for hoist＇s load detection. Firstly,the analog-todigital converter（ ADC） output value corresponding to the total torque was corrected though gray correlation analysis,and the corrected ADC value whose fluctuation and unsteadiness had been greatly reduced was selected to be as the result of the first phase. In the second phase,by using the result of the first phase as input variable,the hoist＇s load predicted model was founded according to the least square support vector regression（ LS-SVR） or partial least square regression（ PLSR）. Taking the first predicted value as the expected data sequence and implementing the correction based on the gray correlation analysis again,the hoist actual load was finally attained. Experiment result showed that the error of the result of load detection was less than ± 0. 6% for LS-SVR and below ± 1% for PLSR model cooperated with the correction based on the gray correlation analysis. Meanwhile,since the integrate sensor was directly installed between the motor shaft and the hoist one,the number of pulses would be greatly increased during the hoist＇s moving up and down which could well improve the opening detection resolution. The resolution of the hoist opening detection was far below 1 mm.