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.
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机译：提出了基于交变静水压（AHP）加速测试的有机涂层预测概念。已采用具有不同压力值的AHP加速测试来评估涂层的降解。并建立了反向传播人工神经网络（BP-ANN）来预测涂层的使用寿命和使用寿命。压力值（P），浸入时间（t）和使用性能（阻抗模量| Z |）被用作网络的参数。已建立网络的预测服务属性和浸入时间的平均准确度分别为98.6％和84.8％。结合BP-ANN的加速测试和预测方法，有望评估和预测深海中使用的涂层性能。
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