Abstract | ||
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To deal with the fault of the vehicle platoon, we have established a fault detection and isolation (FDI) system with two-level fault diagnosis architecture. For simplicity, we divide the FDI architecture into two kinds: system failure and component element failure. To detect these faults, we set up the FDI mathematical model of the fleet based on the vehicular spacing, and the sensor FDI model of a certain vehicle. Meanwhile, we construct the state space model of the fleet, and design the residual generator using the space geometry method for system failure. To design the residual generation model of the fleet for component element failure, we strengthen the structure analysis of both the fleet and a certain vehicle. What's more, to elucidate the factors that cause the change of vehicle distance, the virtual force analysis is introduced. Using the adaptive threshold method, it can enhance both the sensitivity of the FDI system to the residual and the robustness to the disturbance. To promote the vehicle itself and the fleet's information perception ability, all vehicles (Autonomous Mobile Robots) are equipped with infrared distance measuring sensors, odometers, a pair of incremental optical encoders, and so on. The experimental results show that the proposed method is reliable and efficient for FDI of fleet. |
Year | DOI | Venue |
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2018 | 10.1109/ACCESS.2018.2815644 | IEEE ACCESS |
Keywords | Field | DocType |
FDI,fleet,structure analysis,virtual force analysis,residual generation,space geometry | Rotary encoder,Automotive engineering,Residual,Platoon,Fault detection and isolation,Computer science,State-space representation,Robustness (computer science),Mobile robot,Odometer,Distributed computing | Journal |
Volume | ISSN | Citations |
6 | 2169-3536 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Gaochao Wang | 1 | 0 | 0.34 |
Ying Ding | 2 | 88 | 7.62 |
Yandong Hou | 3 | 0 | 0.34 |
Yi Zhou | 4 | 51 | 5.38 |
Xiangyi Jia | 5 | 0 | 0.34 |