Equipment defect time prediction method based on capacitive equipment defect data

The invention discloses an equipment defect time prediction method based on capacitive equipment defect data, and relates to the technical field of electrical equipment and information. Feature engineering processing and defect time modeling are carried out by adopting a whole set of method; for data with more abnormal values, missing values and redundant values of a power grid company, firstly missing value filling and data cleaning are performed, new features are constructed through feature decomposition, and feature dimensionality reduction and denoising are performed by using an auto-encoder; and for the processed feature data, feature model construction is performed by using various machine learning methods such as a gradient boosting tree and a deep learning method. The method has the advantages of being easy to implement, high in calculation speed, high in prediction precision, good in prediction robustness and systematized in prediction process. 该发明公开了一种基于电容型设备缺陷数据的设备缺陷时间预测方法，涉及电气设备和信息技术领域。采用一整套方法进行特征