基于风电运维人员紧张程度的运维操作模式

A Method of Operation and Maintenance Based on the Pressure of the Wind Power Operation and Maintenance Personnel

安全可靠的运维是保证风电场正常运行的一个重要条件.然而大多数风电场处于环境恶劣的偏远地区,给风电运维人员带来了巨大的挑战.恶劣的运维环境降低了运维人员的可靠性,增加了运维人员人为失误的概率.近年来,由运维人员人为失误导致的事故频发,为减少人为失误导致的事故,提出了一种基于风电运维人员紧张程度的运维操作模式.以肌电图、呼吸作用和皮肤电导这3种生理信号作为运维人员紧张程度的评估参数,采用随机森林算法对运维人员的紧张程度进行分类与预测,通过实验验证了基于生理信号划分紧张程度的可行性.最后以发电机U1绕组温度超限故障为例,分析了运维人员在不同紧张程度下的操作模式.

Safe and reliable operation and maintenance is an important condition to ensure the normal operation of wind farms.However,most wind farms are in remote areas with harsh environments,which poses a huge challenge to wind power operation and maintenance personnel.Harsh operation and maintenance environments reduce the reliability of operation and maintenance personnel and increases the probability of human error by operation and maintenance personnel.In recent years,accidents caused by human error by operation and maintenance personnel have occurred frequently.In order to reduce accidents caused by human error,an operation and maintenance operation method based on the pressure of wind power operation and maintenance personnel has been proposed.The three physiological signals of electromyography,respiration and skin conductivity are used as the evaluation parameters of the pressure of the operation and maintenance personnel,and the random forest algorithm is used to classify and predict the pressure of the operation and maintenance personnel.The feasibility of dividing the pressure degree based on physiological signal is verified by experiments.Finally,taking the generator U1 winding temperature overrun fault as an example,the operation method of operation and maintenance personnel under different pressure levels are analyzed.