Integrated Modular Avionics Fault Propagation Model Establishment and Reliability Allocation

Author(s):  
Hao Dong ◽  
Xiaohong Bao ◽  
Tingdi Zhao ◽  
Yu Xin
1999 ◽  
Vol 11 (4) ◽  
pp. 326-330
Author(s):  
Yukiyasu Shimada ◽  
◽  
Kazuhiko Suzuki

This paper presents a fault diagnostic system (FDS) using multiple neural networks for chemical plants. The fault propagation in progress is modeled by causal relationships between a fault tree (FT) and its minimal cut sets (MCSa). The measurement patterns required for training neural networks (NNs) are obtained from fault propagation model. The FDS has a circuit network and component networks. The circuit network can identify circuit malfunctions that include disturbances. The component networks can identify component malfunctions as root causes of process malfunction. We have constructed an on-line FDS by making use of proposed method and verified the effectiveness of it experimentally.


Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Yifan Chen ◽  
Genbao Zhang ◽  
Yan Ran

A comprehensive fault analysis of CNC machine tool is conducive to improving its reliability. Due to the highly complex structure of CNC machine tool, there are different degrees of coupling relationship between faults. However, the traditional fault analysis methods (FMEA, FTA, etc.) for CNC machine tool do not solve this problem perfectly. Therefore, we propose a coupling fault propagation model based on meta-action. First, in order to simplify the structural complexity of CNC machine tool, the “Function-Motion-Action (FMA)” decomposition structure is used to decompose the product function into simple meta-action, and the numerical matrix is used to quantify the coupling relationship between the meta-actions. Then, based on the fault transfer characteristics of meta-action, the fault propagation model is established, and the global risk effect (GRE) is combined to realize the comprehensive evaluation of the risk criticality of meta-actions. Finally, the rationality and validity of the method are verified by the case analysis of the automatic pallet changer (APC) of computerized numerical control (CNC) machining center.


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