公开(公告)号：US20240184956A1

公开(公告)日：2024-06-06

申请号：US18014594

申请日：2022-06-08

Applicant: Northeastern University

Inventor： Xu LI ,  Nan CHEN ,  Jingguo DING ,  Feng LUAN ,  Yan WU ,  Bingbing MA ,  Kun GAO ,  Lifeng HUO ,  Dianhua ZHANG

IPC: G06F30/27 ,  G06F30/17 ,  G06F119/08 ,  G06F119/14

CPC classification number: G06F30/27 ,  G06F30/17 ,  G06F2119/08 ,  G06F2119/14

Abstract: The invention belongs to the technical field of quality control of steel plates and strips products, and relates to a prediction method of crown of steel plates and strips based on data driving and mechanism model fusion. By establishing an outlet crown mechanism model of a hot continuous rolling, the mechanism model and a DNN model are combined to establish a DNN model for predicting crown of steel plates and strips, and the calculated value of the mechanism model is taken as a benchmark value of the outlet crown. The deviation amount between the benchmark value and the actual values of the outlet crown is taken as output of the DNN model for predicting crown of the steel plates and strips, and then sum of the predicted value and the benchmark value based on the DNN model for predicting the crown of the steel plates is taken as the final predicted value of the crown of the steel plates and strips.

公开(公告)号：US20230152187A1

公开(公告)日：2023-05-18

申请号：US17781475

申请日：2021-07-29

Applicant: Northeastern University

Inventor： Feng LUAN ,  Xu LI ,  Ziming ZHANG ,  Yan WU ,  Yuejiao HAN ,  Dianhua ZHANG

IPC: G01M99/00 ,  H04R1/40 ,  G06N3/0464 ,  G06N3/044 ,  G06N3/045 ,  G06N3/08

CPC classification number: G01M99/005 ,  H04R1/406 ,  G06N3/0464 ,  G06N3/044 ,  G06N3/045 ,  G06N3/08

Abstract: Provided is a fault signal locating and identifying method of industrial equipment based on a microphone array. The method includes the steps of: acquiring sound signals and dividing the acquired signals into a training set, a verifying set and a test set; performing feature extraction on the sound signals in the training set, and extracting a phase spectrogram and an amplitude spectrogram of a spectrogram; sending an output of a feature extraction module, as an input, to a CNN, and in each layer of the CNN, learning a translation invariance in the spectrogram by using a 2D CNN; in between the layers of the CNN, normalizing the output by using a batch normalization, and reducing a dimension by using a maximum pooling layer along a frequency axis; sending an output from the layers of the CNN to layers of RNN; using a linear activation function; and inputting an output of a full connection layer to two parallel full connection layer branches for fault identification and fault location, respectively.

公开(公告)号：US20230004781A1

公开(公告)日：2023-01-05

申请号：US17784430

申请日：2021-07-29

Applicant: Northeastern University

Inventor： Xu LI ,  Feng LUAN ,  Lin WANG ,  Yan WU ,  Yuejiao HAN ,  Dianhua ZHANG

IPC: G06N3/04 ,  G06N3/08 ,  G06F17/16 ,  G06N3/063 ,  B21B37/38

Abstract: Provided is an LSTM-based hot-rolling roll-bending force predicting method including the steps of acquiring final rolling data of a stand of a stainless steel rolling mill when performing a hot rolling process, and dividing the data into a training set traindata and a test set testdata; normalizing the traindata; building a matrix P; using a last row of the matrix P as a label of the training set, namely a true value; calculating and updating an output value and the true value of a network; after network training is completed, taking the last m output data of the LSTM network as an input at a next moment, and then obtaining an output of the network at the next moment, wherein the output is a predicted value of the roll-bending force at the next moment; repeating the steps until a sufficient number of prediction data is obtained; and comparing the processed data with the true value in the testdata to check the validity of the network.