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The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Patent No.:

US 12762374 B1

PDFFull Text
Date of Patent:
Oct. 13, 2026

Filed:

Apr. 11, 2024

Multi-disaster fusion natural fission early warning method and system in coal mine

Applicant:

Ccteg Chongqing Research Institute, Chongqing, CN;

Inventors:

Haitao Sun, Chongqing, CN;

Zhigang Zhang, Chongqing, CN;

Yabo He, Chongqing, CN;

Wenji Han, Chongqing, CN;

Gangli Yao, Chongqing, CN;

Shan Si, Chongqing, CN;

Hao Wang, Chongqing, CN;

Yun Sun, Chongqing, CN;

Lang Li, Chongqing, CN;

Na Yang, Chongqing, CN;

Yanbao Liu, Chongqing, CN;

Xusheng Zhao, Chongqing, CN;

Rongjun Si, Chongqing, CN;

Shengjun Guo, Chongqing, CN;

Yunbing Hu, Chongqing, CN;

Hanying Tang, Chongqing, CN;

Mingjian Li, Chongqing, CN;

Haisheng Wang, Chongqing, CN;

Fuxiang Wu, Chongqing, CN;

Jun Xu, Chongqing, CN;

Assignee:

CCTEG CHONGQING RESEARCH INSTITUTE, Chongqing, CN;

Attorney:

Westbridge IP LLC

Primary Examiner:

Kerri L Mcnally

Int. Cl.
CPC ...
G06N 3/0442 (2023.01); G06F 18/25 (2023.01); G06N 3/09 (2023.01); G08B 21/10 (2006.01);
U.S. Cl.
CPC ...
G06N 3/0442 (2023.01); G06F 18/25 (2023.01); G06N 3/09 (2023.01); G08B 21/10 (2013.01);
Abstract

The present invention discloses a coal mine multi-disaster fusion early warning method and system, applicable in coal mine safety disaster analysis. First, it builds a model and relationship network among multi-disaster early warning entities, updating the network by specific rules. A trend prediction model using an LSTM artificial neural network is then developed for monitoring object trends, along with natural fission analysis rules. Next, a method for identifying anomalies in single disaster events is established through a disaster index prediction and early warning system. Upon detecting an anomaly in an early warning index, other disaster indexes are assessed using a depth-first traversal algorithm and natural fission rules, facilitating targeted forecasting. This invention builds a predictive relationship chain among early warning indexes through correlation analysis, providing advantages in multi-dimensional analysis and advanced trend prediction.

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Sun, Haitao. (2026). Multi-disaster fusion natural fission early warning method and system in coal mine (U.S. Patent No. 12762374). U.S. Patent and Trademark Office. https://idiyas.com/patent/badge/12762374

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