Two-Step Neural-Network-Based Fault Isolation for Stochastic Systems
This paper studies a fault isolation method for an optical fiber vibration source detection and early warning system. We regard the vibration sources in the system as faults and then detect and isolate the faults of the system based on a two-step neural network. Firstly, the square root B-spline exp...
Main Authors: | Liping Yin, Jianguo Liu, Hongquan Qu, Tao Li |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-11-01
|
Series: | Mathematics |
Subjects: | |
Online Access: | https://www.mdpi.com/2227-7390/10/22/4261 |
Similar Items
-
Currents Analysis of a Brushless Motor with Inverter Faults—Part II: Diagnostic Method for Open-Circuit Fault Isolation
by: Cristina Morel, et al.
Published: (2023-06-01) -
Multi-Sensor Fault Detection, Identification, Isolation and Health Forecasting for Autonomous Vehicles
by: Saeid Safavi, et al.
Published: (2021-04-01) -
Improved sensor fault detection, isolation, and mitigation using multiple observers approach
by: Zheng Wang, et al.
Published: (2017-01-01) -
A Particle Filtering Approach for Fault Detection and Isolation of UAV IMU Sensors: Design, Implementation and Sensitivity Analysis
by: Egidio D’Amato, et al.
Published: (2021-04-01) -
Robust Mpc for Actuator–Fault Tolerance Using Set–Based Passive Fault Detection and Active Fault Isolation
by: Xu Feng, et al.
Published: (2017-03-01)