摘要
针对传统传感器状态监测方法准确性不高的问题,提出一种组合式有源传感器状态监测与容错控制方法。该方法分为2个部分:前一部分进行传感器状态监测,包括状态信号去噪处理、小波包能量熵特征提取以及利用参数优化后的概率神经网络识别传感器健康状态3个步骤;后一部分设计容错控制模型,以状态监测结果为参考,切换控制策略,实现容错控制。实验结果表明:与其他3种传统方法相比,在该方法控制下容错控制误差在±1 r/min,波动较小,控制效果更优。
Aiming at the low accuracy of traditional sensor state monitoring methods,a state monitoring and fault-tolerant control method of combined active electronic sensor was proposed.The method was divided into two parts.The first part was to realize the state monitoring of the sensor,including state signal de-noising processing,wavelet packet energy entropy feature extraction,and using the probabilistic neural network after parameter optimization to identify the health of the sensor.The second part was to design the fault-tolerant control model,and switch the control strategy to realize the fault-tolerant control based on the state monitoring results.The experimental results show that,compared with the other three traditional methods,the fault-tolerant control error under the proposed method is between±1 r/min,the fluctuation is small,and the control effect is better.
作者
杜秀君
舒成业
DU Xiujun;SHU Chengye(School of Electronic Information and Artificial Intelligence,Yibin Vocational&Technical College,Yibin 644100,China;Sichuan Jinglong Optoelectronics Technology Co.,Ltd.,Yibin 644100,China)
出处
《成都工业学院学报》
2024年第3期61-66,共6页
Journal of Chengdu Technological University
基金
宜宾职业技术学院项目(24ZRZD-02)
宜宾职业技术学院科技创新团队项目(ybzy21cxtd-01)。
关键词
组合式有源传感器
概率神经网络
状态监测
容错控制
combined active electronic sensor
probabilistic neural network
state monitoring
fault-tolerant control
作者简介
第一作者:杜秀君(1982-),女,讲师,学士,研究方向:电子信息技术、人工智能,电子邮箱:dxj1829099@163.com。
