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Various structural failure modes exhibit great differences in occurrence probabilities, failure consequences and intrinsic characteristics, etc. Utilising these differences can enhance the effectiveness and efficiency of damage identification research, which has currently received little coverage.
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Subsequently, the optimal maintenance interval is determined by the required probability and failure probability distribution.
Such a relative difference in the system probabilities of failure associated with different copulas increases greatly with decreasing component probability of failure.
Cumulative probability function relates probability of failure with number of cycles.
However, calculated reliabilities and associated probabilities of failure often have significant uncertainties associated with the possible estimation errors relative to the 'true' failure probabilities.
Attention is paid to very low probabilities of failure.
The formulation takes into account quantitative information such as fault occurrence probabilities, sensor failure probabilities, and sensor costs.
Dependencies are represented by local conditional probability distributions (CPDs) modeling probabilities of failure, given dependances fail.
However, there are noticeable differences between the probabilities of failure of these configurations in anisotropic situations.
A finite element subroutine is developed for calculation of hazard maps and global probabilities of failure.
The analysis procedure considers both kinematic and kinetic probabilities of failure.
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