Big Data Intelligent Selection Design Method for Rockburst-Prevention Hydraulic Supports in Rockburst Roadways
Summary
The USPTO published patent application US20260099708A1 for a big data intelligent selection design method for rockburst-prevention hydraulic supports used in rockburst roadways. The invention uses machine learning and statistical analysis to identify key factors affecting hydraulic support performance based on geological conditions, rock mechanical properties, mine face layout, and historical usage and maintenance records. The system aims to improve selection accuracy and efficiency of rockburst-prevention hydraulic supports for mining safety applications.
What changed
The USPTO published patent application US20260099708A1 titled 'Big Data Intelligent Selection Design Method for Rockburst-Prevention Hydraulic Supports in Rockburst Roadways.' The application covers a method that collects data on geological conditions, rock mechanical properties, mine face layout, and historical usage and maintenance records of previous rockburst-prevention hydraulic supports from different mining areas. Machine learning and statistical analysis methods are used to identify key factors affecting performance and provide intelligent selection recommendations.
For mining equipment manufacturers and technology developers, this patent application indicates emerging intellectual property protection around AI-driven hydraulic support selection systems for underground mining applications. Companies developing similar big data or machine learning systems for mining safety equipment should evaluate whether this published application could affect their freedom to operate or whether licensing discussions may be appropriate.
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Apr 18, 2026GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.
BIG DATA INTELLIGENT SELECTION DESIGN METHOD FOR ROCKBURST-PREVENTION HYDRAULIC SUPPORTS IN ROCKBURST ROADWAYS
Application US20260099708A1 Kind: A1 Apr 09, 2026
Inventors
Yishan PAN, Like ZHAO, Lianpeng DAI, Xueqi ZHANG, Hao LUO, Hongbin LI
Abstract
The present invention provides a big data intelligent selection design method for rockburst-prevention hydraulic supports in rockburst roadways. In the method, firstly, data on geological conditions, rock mechanical properties, mine face layout, as well as usage performance and maintenance records of previous rockburst-prevention hydraulic supports is collected from different mining areas and historical records. Then, a machine learning method and a statistical analysis method are used to identify key factors affecting the performance of the rockburst-prevention hydraulic supports from an integrated dataset, thereby providing an intelligent rockburst-prevention hydraulic support selection system. The present invention can improve the selection accuracy and efficiency of the rockburst-prevention hydraulic supports and ensure safety. Through in-depth analysis of a large amount of geological data, mine face conditions, and historical rockburst-prevention hydraulic support usage, the most suitable rockburst-prevention hydraulic support selection suggestion is provided for roadways.
CPC Classifications
G06N 3/08
Filing Date
2025-10-02
Application No.
19348119
Named provisions
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