公开(公告)号：US20220373432A1

公开(公告)日：2022-11-24

申请号：US17866441

申请日：2022-07-15

Applicant: Sichuan University

Inventor： Jianbo WU ,  Ziheng HUANG ,  Zhaoyuan XU ,  Qiao QIU ,  Jun ZHENG ,  Jinhang LI ,  Zhiyuan SHI

IPC: G01M99/00 ,  G06K9/00 ,  G06K9/62

Abstract: A method for diagnosing and predicting operation conditions of large-scale equipment based on feature fusion and conversion, including: collecting a vibration signal of each operating condition of the equipment, and establishing an original vibration acceleration data set of the vibration signal; performing noise reduction on the original vibration acceleration data set, and calculating a time domain parameter; performing EMD on a de-noised vibration acceleration and calculating a frequency domain parameter; constructing a training sample data set through the time domain parameter and the frequency domain parameter; establishing a GBDT model, and inputting the training sample data set into the GBDT model; extracting a leaf node number set from a trained GBDT model; performing one-hot encoding on the leaf node number set to obtain a sparse matrix; and inputting the sparse matrix into a factorization machine to obtain a prediction result.