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- W2388781209 abstract "Principal component analysis( PCA) is a typical data dimension reduction multivariate statistical method,which has been used in fault diagnosis. PCA is applied in bridge deflection sensor fault diagnosis. Introduce theory of PCA,and study fault detection method based on PCA and fault diagnosis method based on contribution rate. Calculate squared prediction error( SPE) and Hotelling T2statistics,when statistics exceeds threshold,judge there are sensor faults in system,and by using SPE contribution figure judge fault source. By simulation,the practicability of PCA in fault diagnosis is proved,but the result also show that PCA is not so sensitive to small fault." @default.
- W2388781209 created "2016-06-24" @default.
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- W2388781209 date "2014-01-01" @default.
- W2388781209 modified "2023-09-23" @default.
- W2388781209 title "Bridge deflection sensor fault diagnosis research based on PCA" @default.
- W2388781209 hasPublicationYear "2014" @default.
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