| Title | A Sensor Fault Diagnosis Algorithm for UAV Based on Neural Network |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Xiaoqian, Xiong |
| Conference Name | 2021 International Conference on Intelligent Transportation, Big Data Smart City (ICITBS) |
| Date Published | mar |
| Keywords | Cyber-physical systems, fault diagnosis, fault diagnosis algorithm, feature extraction, human factors, Industries, Metrics, multiple fault diagnosis, Neural Network, Neural networks, Observers, pubcrawl, Resiliency, simulation, smart cities, UAV sensors |
| Abstract | To improve the security and reliability of the system in case of sensor failure, a fault diagnosis algorithm based on neural network is proposed to locate the fault quickly and reconstruct the control system in this paper. Firstly, the typical airborne sensors are introduced and their common failure modes are analyzed. Then, a new method of complex feature extraction using wavelet packet is put forward to extract the fault characteristics of UAV sensors. Finally, the observer method based on BP neural network is adopted to train and acquire data offline, and to detect and process single or multiple sensor faults online. Matlab simulation results show that the algorithm has good diagnostic accuracy and strong generalization ability, which also has certain practicability in engineering. |
| DOI | 10.1109/ICITBS53129.2021.00072 |
| Citation Key | xiaoqian_sensor_2021 |
A Sensor Fault Diagnosis Algorithm for UAV Based on Neural Network