| Title | Dynamic Threshold Design Based on Kalman Filter in Multiple Fault Diagnosis |
| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | Gou, Linfeng, Zhou, Zihan, Liang, Aixia, Wang, Lulu, Liu, Zhidan |
| Conference Name | 2018 37th Chinese Control Conference (CCC) |
| Keywords | aerospace engines, aircraft engine, aircraft engine fault detection, bounded norm uncertainty, constant threshold, current methods, cyber physical systems, diagnosis system, dynamic threshold, dynamic threshold algorithm, dynamic threshold design, dynamic threshold range changes, Eigenvalues and eigenfunctions, Engines, fault diagnosis, human factors, isolation systems, Kalman filter, Kalman filters, Mathematical model, Metrics, multiple fault diagnosis, pubcrawl, Resiliency, robust control, Robustness, sensitivity requirements, state space equation, time domain response range calculation formula, Time factors, uncertain systems, Uncertainty |
| Abstract | The choice of threshold is an important part of fault diagnosis. Most of the current methods use a constant threshold for detection and it is difficult to meet the robustness and sensitivity requirements of the diagnosis system. This article develops a dynamic threshold algorithm for aircraft engine fault detection and isolation systems. The algorithm firstly analyzes the bounded norm uncertainty that may appear in the process of model based on the state space equation, and gives the time domain response range calculation formula under the influence of uncertain parameters; then the Kalman filter is combined to calculate the threshold with the real-time change of state; the simulation is performed at the end. The simulation results show that dynamic threshold range changes with status in real time. |
| DOI | 10.23919/ChiCC.2018.8483301 |
| Citation Key | gou_dynamic_2018 |
Dynamic Threshold Design Based on Kalman Filter in Multiple Fault Diagnosis