UAV attitude Sensor Fault Detection Based On Fuzzy Logic and by Neural Network Model Identification
Authors
Abstract:
Fault detection has always been important in aviation systems to prevent many accidents. This process is possible in different ways. In this paper, we first identify the longitudinal axis plane model using neural network approach. Then based on the obtained model and using fuzzy logic, the aircraft status sensor fault detection unit was designed. The simulation results show that the fault detection system is able to work well, with additional alarms averaging 1 alert per 4-hour flight and miss alert rates averaging 1 alert per 2 hours. The results are confirmed by the experts from the UAV system.
similar resources
Neural Network based Sensor Fault Detection for
Sensor fault in aircraft is detected based on two different approaches. The first approach, well documented in literature, is based on algorithmic method dealing with Luenberger observers. The second approach, which is followed in this paper, is based on Knowledge based neural network fault detection (KBNNFD). KBNNFD uses gradient descent back propagation training algorithm of neural network. A...
full textSensor Fault Detection and Isolation Based on Artificial Neural Networks and Fuzzy Logic Applicated on Induction Motor for Electrical Vehicle
Received Jan 29, 2017 Revised Mar 29, 2017 Accepted Apr 10, 2017 Recently, research has picked up a fervent pace in the area of fault diagnosis of electrical vehicle. Like failures of a position sensor, a voltage sensor, and current sensors. Three-phase induction motors are the “workhorses” of industry and are the most widely used electrical machines. This paper presents a scheme for Fault Dete...
full textNeural Network based Sensor Fault Detection for Flight Control Systems
Sensor fault in aircraft is detected based on two different approaches. The first approach, well documented in literature, is based on algorithmic method dealing with Luenberger observers. The second approach, which is followed in this paper, is based on Knowledge based neural network fault detection (KBNNFD). KBNNFD uses gradient descent back propagation training algorithm of neural network. A...
full textThe Identification of Aircraft Sensor Fault Size via Fuzzy Logic
Considering the possibility of unexpected situations, the authorities feel the necessity of keeping certain sub systems or components of aircraft under continuous scrutiny. Accordingly, sensors in flight control systems are considered as one of the crucial components of the system. The failure to detect faults is quite likely to cause very serious problems, which makes it vital to carry out eff...
full textSoft Sensor Based on Fuzzy Model Identification
This paper presents an approach to build a soft sensor based on computational intelligence techniques. The goal is to identify fuzzy models from numerical data. First of all, the fuzzy model input variables are selected from the secondary variables set by applying Kohonen maps. Then, the Lipschitz quotients are used to select the lag structure of the fuzzy model. A fuzzy clustering algorithm is...
full textTopology Control in Wireless Sensor Network using Fuzzy Logic
Network sensors consist of sensor nodes in which every node covers a limited area. The most common use ofthese networks is in unreachable fields.Sink is a node that collects data from other nodes.One of the main challenges in these networks is the limitation of nodes battery (power supply). Therefore, the use oftopology control is required to decrease power consumption and increase network acce...
full textMy Resources
Journal title
volume 15 issue None
pages 71- 83
publication date 2022-01
By following a journal you will be notified via email when a new issue of this journal is published.
No Keywords
Hosted on Doprax cloud platform doprax.com
copyright © 2015-2023