CAJ | 학술논문

把传感器硬件冗余技术、BP网络以及串并联Elman递归神经网络结合起来，提出了一种新方法用于构造具有传感器故障检测、分离且具有冗余能力的智能传感器系统. 这可以减少硬件冗余技术中使用传感器的个数，消除硬件冗余技术中对冗余传感器应具有相同参数特性的要求，同时可以提高系统预报的准确性. 仿真结果验证了这一方法的有效性.
파전감기경건용여기술、BP망락이급천병련Elman체귀신경망락결합기래，제출료일충신방법용우구조구유전감기고장검측、분리차구유용여능력적지능전감기계통. 저가이감소경건용여기술중사용전감기적개수，소제경건용여기술중대용여전감기응구유상동삼수특성적요구，동시가이제고계통예보적준학성. 방진결과험증료저일방법적유효성.
Combining the hardware redundant technology with BP neural network and Elman recurrent neural network, the paper presents a new method for constructing an intelligent sensor system with abilities of sensor fault detection, fault isolation and redundancy. With the method, the number of sensors used in the hardware redundant technology can be reduced, the demands for the sensors with the same parameter properties can be ignored and at the same time the prediction accuracy for system output also could be improved. The result of simulation for a real temperature control system show that the method is correct and practicable.