Design of Predictive Maintenance Platform for INS Based on GO Methodology and RCM

doi:10.3969/j.issn.1000-1093.2014.09.017

Abstract

Abstract: A design method of predictive maintenance platform based on GO methodology and reliability-centered maintenance(RCM) is proposed for the complex structure, reliability analysis and optimal maintenance of inertial navigation system (INS). GO methodology is applied to build the INS reliability analyses model—GO chart. In order to realize the dynamic prediction and evaluation of the residual lives of components and the system reliability, the components reliability are updated continuously based on life distribution functions and time stress samples. For the INS that fails to meet the system reliability index, the maintenance priorities of all components are given quantitatively by adopting the comprehensive evaluation method to balance the affecting factors of components: contribution to system, failure likelihood and detection difficulty. Finally, some simulations are processed under the situations of constant failure rate, variable failure rate and fault isolation of INS components. The results show that the proposed predictive maintenance platform for INS is feasible and effective, and the predicted results can be used as a reference for making scientific maintenance decisions.

Key words: system assessment and feasibility analysis, inertial navigation system, GO methodology, RCM, predictive maintenance

CLC Number:

V240.2

JIANG Xiu-hong， DUAN Fu-hai， CHEN Pu， JIN Xia. Design of Predictive Maintenance Platform for INS Based on GO Methodology and RCM[J]. Acta Armamentarii, 2014, 35(9): 1443-1450.

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