公开(公告)号：US10345046B2

公开(公告)日：2019-07-09

申请号：US15605427

申请日：2017-05-25

Applicant: Northeastern University

Inventor： Zhenbang Wang ,  Yingwei Zhang ,  Lin Feng

IPC: F27D21/00 ,  H04N7/18 ,  G01M3/38 ,  G06K9/00 ,  G06K9/62 ,  G06T7/00 ,  G06T7/13 ,  G06T7/40 ,  G06T7/90 ,  F27D11/08 ,  F27D21/02

Abstract: A fault diagnosis method for an electrical fused magnesia furnace includes steps of: 1) arranging six cameras; 2) obtaining video information by the six cameras and sending the video information to a control center; then analyzing the video information by a chip of the control center; wherein a multi-view-based fault diagnosis method is used by the chip, comprising steps of: 2-1) comparing a difference between two consecutive frame histograms for shots segmentation; 2-2) computing a set of characteristic values for each shot obtained by the step 2-1), and then computing color, texture, and motion vector information; finally, evaluating shot importance via entropy; 2-3) clustering shots together by calculating similarity; 2-4) generating and optimizing a multi-view video summarization with a multi-objective optimization model; and 2-5) providing fault detection and diagnosis; and 3) displaying results of the fault detection and diagnosis on a host computer inter face of the control center.

公开(公告)号：US20170261264A1

公开(公告)日：2017-09-14

申请号：US15605427

申请日：2017-05-25

Applicant: Northeastern University

Inventor： Zhenbang Wang ,  Yingwei Zhang ,  Lin Feng

IPC: F27D21/00 ,  G06K9/20 ,  G06K9/00 ,  G06K9/62 ,  G06K9/46 ,  F27D11/08 ,  G06T7/40 ,  G06T7/13 ,  G06K9/48 ,  G06T7/00 ,  G01M3/00 ,  H04N7/18 ,  G06T7/90

CPC classification number: F27D21/0021 ,  F27D11/08 ,  F27D2021/0085 ,  F27D2021/026 ,  G01M3/38 ,  G06K9/00718 ,  G06K9/00751 ,  G06K9/00771 ,  G06K9/6212 ,  G06K2009/00738 ,  G06T7/0004 ,  G06T7/001 ,  G06T7/13 ,  G06T7/40 ,  G06T7/90 ,  G06T2207/10024 ,  G06T2207/30232 ,  H04N7/181

Abstract: A fault diagnosis method for an electrical fused magnesia furnace includes steps of: 1) arranging six cameras; 2) obtaining video information by the six cameras and sending the video information to a control center; then analyzing the video information by a chip of the control center; wherein a multi-view-based fault diagnosis method is used by the chip, comprising steps of: 2-1) comparing a difference between two consecutive frame histograms for shots segmentation; 2-2) computing a set of characteristic values for each shot obtained by the step 2-1), and then computing color, texture, and motion vector information; finally, evaluating shot importance via entropy; 2-3) clustering shots together by calculating similarity; 2-4) generating and optimizing a multi-view video summarization with a multi-objective optimization model; and 2-5) providing fault detection and diagnosis; and 3) displaying results of the fault detection and diagnosis on a host computer inter face of the control center.