A data-level fusion approach for degradation modeling and prognostic analysis under multiple failure modes

2018 ◽  
Vol 50 (2) ◽  
pp. 150-165 ◽  
Author(s):  
Abdallah Chehade ◽  
Changyue Song ◽  
Kaibo Liu ◽  
Abhinav Saxena ◽  
Xi Zhang
Keyword(s):  
Failure Modes ◽  
Multiple Failure Modes ◽  
Degradation Modeling ◽  
Prognostic Analysis ◽  
Level Fusion ◽  
Fusion Approach ◽  
Data Level

Multimodal score level fusion for recognition using face and palmprint

2020 ◽  
pp. 002072092092966
Author(s):  
Milind E Rane ◽  
Umesh S Bhadade
Keyword(s):  
Recognition System ◽  
Acceptance Rate ◽  
Face Database ◽  
Biometric Recognition ◽  
False Acceptance Rate ◽  
Score Level Fusion ◽  
Score Fusion ◽  
Matching Score ◽  
Level Fusion ◽  
Fusion Approach

The paper proposes a t-norm-based matching score fusion approach for a multimodal heterogenous biometric recognition system. Two trait-based multimodal recognition system is developed by using biometrics traits like palmprint and face. First, palmprint and face are pre-processed, extracted features and calculated matching score of each trait using correlation coefficient and combine matching scores using t-norm based score level fusion. Face database like Face 94, Face 95, Face 96, FERET, FRGC and palmprint database like IITD are operated for training and testing of algorithm. The results of experimentation show that the proposed algorithm provides the Genuine Acceptance Rate (GAR) of 99.7% at False Acceptance Rate (FAR) of 0.1% and GAR of 99.2% at FAR of 0.01% significantly improves the accuracy of a biometric recognition system. The proposed algorithm provides the 0.53% more accuracy at FAR of 0.1% and 2.77% more accuracy at FAR of 0.01%, when compared to existing works.

scholarly journals Mechanism reliability and sensitivity analysis of landing gear under multiple failure modes

2021 ◽  
Vol 39 (1) ◽  
pp. 46-54
Author(s):  
Changcong Zhou ◽  
Mengyao Ji ◽  
Yishang Zhang ◽  
Fuchao Liu ◽  
Haodong Zhao
Keyword(s):  
Failure Probability ◽  
Failure Modes ◽  
Kriging Model ◽  
Landing Gear ◽  
Multiple Failure Modes ◽  
Analysis And Design ◽  
Extension System ◽  
Extension Mechanism ◽  
Assembly Error ◽  
Adaptive Kriging

For a certain type of aircraft landing gear retraction-extension mechanism, a multi-body dynamic simulation model is established, and the time-dependent curves of force and angle are obtained. Considering the random uncertainty of friction coefficient, assembly error, and the change of hinge wear under different retraction times, the reliability model is built including three failure modes of landing gear, i.e. blocking failure, positioning failure and accuracy failure. Based on the adaptive Kriging model, the reliability and sensitivity of retraction-extension system under the condition of single failure mode and multiple failure modes in series are analyzed, and the rule of reliability and sensitivity changing with the number of operations is given. The results show that the system failure probability of landing gear mechanism tends to decrease first and then increase when considering the given information of random factors, and the influences of random factors on the failure probability vary with the number of operations. This work provides a viable tool for the reliability analysis and design of landing gear mechanisms.

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