Fault detection and isolation for sensor information fusion Kalman filter

2007 ◽  
Author(s):  
Ali Okatan ◽  
Chingiz Hajiyev ◽  
Ulviyya Hajiyeva
Keyword(s):  
Kalman Filter ◽  
Fault Detection ◽  
Information Fusion ◽  
Fault Detection And Isolation ◽  
Sensor Information

The Methods of Information Acquisition and Information Fusion of the Photoelectric Sensor-Based Quadrotor Unmanned Aerial Vehicle

2020 ◽  
Vol 15 (1) ◽  
pp. 82-91
Author(s):  
Fen Hang ◽  
Xiangyang Hao
Keyword(s):  
Kalman Filter ◽  
Unmanned Aerial Vehicle ◽  
Kalman Filtering ◽  
Information Fusion ◽  
Information Acquisition ◽  
Reference System ◽  
Fusion Technology ◽  
Photoelectric Sensor ◽  
Aerial Vehicle ◽  
Sensor Information

When quadrotor unmanned aerial vehicle (UAV) is performing various tasks, even a small angular error will affect the evaluation of the entire motion trajectory. The multiple photoelectric sensor information fusion technology and the ARM microprocessor platform are used to form an attitude reference system for UAV. First, the hardware design of the small quadrotor UAV attitude reference system based on an ARM is introduced. The design framework and information acquisition module are expounded. In terms of the software of the system, the photoelectric sensor is used to receive different kinds of information, and the dynamic loading component is adopted as the solution to the interface diversification problems. Based on the attitude reference system, the collected information needs to be fused. The Kalman filtering is taken as the research object. Combined with the multiple photoelectric sensor information fusion technology, the Kalman filtering method is improved in the data preprocessing, and the low-pass filtering is added. Therefore, the abnormal data is filtered, and the estimated values are converged in a short time. Then, the data fusion is performed by the joint Kalman filter, least-squares fusion, and extended Kalman filter, respectively. During the experimental process, the system is proved to have good robustness, that is, in the case of individual sensor failure, the attitude acquisition section still obtains accurate attitude information of the UAV. The attitude reference system of UAV is realized. With the help of multi-sensor/information fusion technology, the attitude of the UAV is better handled, and its flight stability is improved.

scholarly journals Sensors Information Fusion System with Fault Detection Based on Multi-Manifold Regularization Neighborhood Preserving Embedding

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1440
Author(s):  
Jianping Wu ◽  
Bin Jiang ◽  
Hongtian Chen ◽  
Jianwei Liu
Keyword(s):  
Fault Detection ◽  
Information Fusion ◽  
High Speed ◽  
Euclidean Distance ◽  
Manifold Regularization ◽  
Fusion System ◽  
Electrical Drive ◽  
High Speed Trains ◽  
Sensor Information ◽  
Drive Systems

Electrical drive systems play an increasingly important role in high-speed trains. The whole system is equipped with sensors that support complicated information fusion, which means the performance around this system ought to be monitored especially during incipient changes. In such situation, it is crucial to distinguish faulty state from observed normal state because of the dire consequences closed-loop faults might bring. In this research, an optimal neighborhood preserving embedding (NPE) method called multi-manifold regularization NPE (MMRNPE) is proposed to detect various faults in an electrical drive sensor information fusion system. By taking locality preserving embedding into account, the proposed methodology extends the united application of Euclidean distance of both designated points and paired points, which guarantees the access to both local and global sensor information. Meanwhile, this structure fuses several manifolds to extract their own features. In addition, parameters are allocated in diverse manifolds to seek an optimal combination of manifolds while entropy of information with parameters is also selected to avoid the overweight of single manifold. Moreover, an experimental test based on the platform was built to validate the MMRNPE approach and demonstrate the effectiveness of the fault detection. Results and observations show that the proposed MMRNPE offers a better fault detection representation in comparison with NPE.

Sign in / Sign up

Export Citation Format

Share Document