公开(公告)号：US11630034B2

公开(公告)日：2023-04-18

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 ,  G05B19/04 ,  G05B19/418 ,  G05B23/02 ,  G06F18/25 ,  G06F18/214

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.