Dynamically non-gaussian anomaly identification method for structural monitoring data

The present invention belongs to the technical field of health monitoring for civil structures, and a dynamically non-Gaussian anomaly identification method is proposed for structural monitoring data. First, define past and current observation vectors for the monitoring data and pre-whiten them; sec...

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Bibliographic Details
Main Authors Li, Hongnan, Yi, Tinghua, Huang, Haibin
Format Patent
LanguageEnglish
Published 11.05.2021
Subjects
CALCULATING
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
HANDLING RECORD CARRIERS
MEASURING
PHYSICS
PRESENTATION OF DATA
RECOGNITION OF DATA
RECORD CARRIERS
TESTING
TESTING STATIC OR DYNAMIC BALANCE OF MACHINES ORSTRUCTURES
TESTING STRUCTURES OR APPARATUS NOT OTHERWISE PROVIDED FOR
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Summary:The present invention belongs to the technical field of health monitoring for civil structures, and a dynamically non-Gaussian anomaly identification method is proposed for structural monitoring data. First, define past and current observation vectors for the monitoring data and pre-whiten them; second, establish a statistical correlation model for the whitened past and current observation vectors to obtain dynamically whitened data; then, divide the dynamically whitened data into two parts, i.e., the system-related and system-unrelated parts, which are further modelled by the independent component analysis; finally, define two statistics and determine their corresponding control limits, respectively, it can be decided that there is anomaly in the monitoring data when each of the statistics exceeds its corresponding control limit. The non-Gaussian and dynamic characteristics of structural monitoring data are simultaneously taken into account, based on that the defined statistics can effectively identify anomalies in the data.
Bibliography:Application Number: US201816090911