title: Lifetime prediction for organic coating under alternating hydrostatic pressure by artificial neural network.
abstract: A concept for prediction of organic coatings, based on the alternating hydrostatic pressure (AHP) accelerated tests, has been presented. An AHP accelerated test with different pressure values has been employed to evaluate coating degradation. And a back-propagation artificial neural network (BP-ANN) has been established to predict the service property and the service lifetime of coatings. The pressure value (P), immersion time (t) and service property (impedance modulus |Z|) are utilized as the parameters of the network. The average accuracies of the predicted service property and immersion time by the established network are 98.6% and 84.8%, respectively. The combination of accelerated test and prediction method by BP-ANN is promising to evaluate and predict coating property used in deep sea.
authors.affiliation: Institute of Metal research, Chinese Academy of Science, Wencui Rd 62, Shenyang, 110016, China.
authors.forename: Wenliang
authors.initials: W
authors.lastname: Tian
authors.affiliation: Institute of Metal research, Chinese Academy of Science, Wencui Rd 62, Shenyang, 110016, China.
authors.forename: Fandi
authors.initials: F
authors.lastname: Meng
authors.affiliation: Institute of Metal research, Chinese Academy of Science, Wencui Rd 62, Shenyang, 110016, China.
authors.forename: Li
authors.initials: L
authors.lastname: Liu
authors.affiliation: Institute of Metal research, Chinese Academy of Science, Wencui Rd 62, Shenyang, 110016, China.
authors.forename: Ying
authors.initials: Y
authors.lastname: Li
authors.affiliation: Institute of Metal research, Chinese Academy of Science, Wencui Rd 62, Shenyang, 110016, China.
authors.forename: Fuhui
authors.initials: F
authors.lastname: Wang