Time space modelling for fault diagnosis and prognosis with uncertainty management: A general theoretical formulation - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Reliability Engineering and System Safety Année : 2022

Time space modelling for fault diagnosis and prognosis with uncertainty management: A general theoretical formulation

(1) , (2) , (2) , (2) , (3) , (3) , (1, 4)
1
2
3
4

Résumé

This paper provides a general theoretical framework of time space modelling for Lebesgue sampling-based fault diagnosis and prognosis, with the detailed theoretical analysis and experimental simulation for its mathematical modelling and uncertainty quantification. The developed framework introduces the concept of sequential estimation and prediction of "Mean Reach Time" for fault degrading to predefined Lebesgue states. The proposed formulation comprehensively shows the robustness and generalization of the Time Space Model. It also demonstrates its effectiveness in reducing model complexity and elaborates its easy integration with commonly used techniques. Two applications are presented regarding batteries capacity degradation and bearings degradation. The results demonstrate the compatibility, effectiveness, and modelling simplicity of the proposed formulation.
Fichier non déposé

Dates et versions

hal-03906384 , version 1 (19-12-2022)

Identifiants

Citer

Dongzhen Lyu, Guangxing Niu, Enhui Liu, Bin Zhang, Gang Chen, et al.. Time space modelling for fault diagnosis and prognosis with uncertainty management: A general theoretical formulation. Reliability Engineering and System Safety, 2022, 226, pp.108686. ⟨10.1016/j.ress.2022.108686⟩. ⟨hal-03906384⟩
0 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook Twitter LinkedIn More