Multi-dimension unit life cycle evaluation method based on deep neural network

The invention provides a multi-dimension unit life cycle evaluation method based on a deep neural network, and the method comprises the steps: obtaining and normalizing feature data, and carrying out the class labeling-tag setting of all data samples; dividing samples into a test set and a training set, and training by using a deep neural network; after the model is trained, health state data are input for verification, and an evaluation result is obtained; health state data samples are updated regularly, and training and testing are carried out, so that the model is updated. According to the invention, the deep neural network is utilized to judge the evaluation level of the life cycle according to the input multi-dimensional feature data, so that the process of manual evaluation is greatly simplified, and the working efficiency is improved. 本发明提供一种基于深度神经网络多维度的机组生命周期测评方法，通过获取特征数据并归一化，对所有数据样本进行类别标注-设置标签；划分样本为测试集和训练集，并利用深度神经网络进行训练；训练模型后，输入健康状态数据进行验证，得到测评结果；定期更新健康状态数据样本，并进行训练和测试，从而更新模型。本发明利用了深度神经网络来根据输入的多维度特征数据判