A test-based methodology for the probabilistic assessment of system resilience under random disturbances

Considering the random characteristics of the disturbances that may occur on the engineering system, this paper proposes a test-based probabilistic resilience assessment methodology. It is a sampling-based test method, including five main steps: (1) the bottom-up disturbance identification; (2) the sample size determination according to the law of large numbers and the central limit theorem; (3) the sample stratification and selection based on proportion stratified sampling method; (4) resilience test and performance data collection; and (5) probabilistic resilience assessment, consisting of point estimates and confidence intervals. Besides, two probabilistic resilience measures are defined to reflect the average and the percentile characteristics of the system resilience under random disturbances, and the traditional performance normalization method is extended to adapt to different types of parameters. A wireless DC servo motor is used to verify the effectiveness of our methodology, and this generic methodology can be further applied in other engineering systems.