Redirigiendo al acceso original de articulo en 20 segundos...
Inicio  /  Algorithms  /  Vol: 14 Par: 4 (2021)  /  Artículo
ARTÍCULO
TITULO

Fault Diagnosis Algorithm Based on Adjustable Nonlinear PI State Observer and Its Application in UAV Fault Diagnosis

Qing Miao    
Juhui Wei    
Jiongqi Wang and Yuyun Chen    

Resumen

Aiming at the problem of fault diagnosis in continuous time systems, a kind of fault diagnosis algorithm based on adaptive nonlinear proportional integral (PI) observer, which can realize the effective fault identification, is studied in this paper. Firstly, the stability and stability conditions of fault diagnosis method based on the PI observer are analyzed, and the upper bound of the fault estimation error is given. Secondly, the fault diagnosis algorithm based on adjustable nonlinear PI observer is designed and constructed, it is analyzed and we proved that the upper bound of fault estimation under this algorithm is better than that of the traditional method. Finally, the L-1011 unmanned aerial vehicle (UAV) is taken as the experimental object for numerical simulation, and the fault diagnosis method based on adaptive observer factor achieves faster response speed and more accurate fault identification results.

 Artículos similares

       
 
Hongfeng Gao, Tiexin Xu, Renlong Li and Chaozhi Cai    
Because the gearbox in transmission systems is prone to failure and the fault signal is not obvious, the fault end cannot be located. In this paper, a gearbox fault diagnosis method grounded on improved complete ensemble empirical mode decomposition with... ver más
Revista: Applied Sciences

 
Xiaojiao Gu, Yang Tian, Chi Li, Yonghe Wei and Dashuai Li    
The fault diagnosis method proposed in this paper can be applied to the diagnosis of bearings in machine tool spindle systems.
Revista: Applied Sciences

 
Qingyong Zhang, Changhuan Song and Yiqing Yuan    
Vehicle gearboxes are subject to strong noise interference during operation, and the noise in the signal affects the accuracy of fault identification. Signal denoising and fault diagnosis processes are often conducted independently, overlooking their syn... ver más
Revista: Applied Sciences

 
Zhenyu Yin, Feiqing Zhang, Guangyuan Xu, Guangjie Han and Yuanguo Bi    
Confronting the challenge of identifying unknown fault types in rolling bearing fault diagnosis, this study introduces a multi-scale bearing fault diagnosis method based on transfer learning. Initially, a multi-scale feature extraction network, MBDCNet, ... ver más
Revista: Applied Sciences

 
Zhuofan Xu, Jing Yan, Guoqing Sui, Yanze Wu, Meirong Qi, Zilong Zhang, Yingsan Geng and Jianhua Wang    
High-voltage circuit breakers (HVCBs) handle the important tasks of controlling and safeguarding electricity networks. In the case of insufficient data samples, improving the accuracy of the traditional HVCB mechanical fault diagnosis method is difficult... ver más
Revista: Applied Sciences