China Railway Group has been granted a patent for a method that utilizes big data to monitor and analyze large tunnel machines. The method involves dividing tunnel areas, assessing environmental conditions, analyzing drilling difficulties, confirming operation trajectories, and evaluating the health of tunnel rock drills. GlobalData’s report on China Railway Group gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on China Railway Group, Underwater tunnels was a key innovation area identified from patents. China Railway Group's grant share as of June 2024 was 59%. Grant share is based on the ratio of number of grants to total number of patents.
Method for monitoring large tunnel machines using big data
The patent US12037908B1 outlines a comprehensive method for monitoring and analyzing large tunnel machines through the automatic collection of big data. The method involves several systematic steps, beginning with the division of a tunnel operation area into sub-areas for effective monitoring. Each sub-area's environmental information, including soil moisture and geological characteristics, is collected to assess the rock drilling difficulty. This information is then used to analyze the rock drilling difficulty coefficient, which informs the confirmation of the tunnel operation trajectory. Following the completion of tunnel operations, the method includes a conformity analysis of each sub-area, identification of any abnormalities, and subsequent processing of these abnormal areas to ensure operational efficiency.
Further details of the method include the use of advanced technologies such as laser tunnel section detectors for real-time scanning and modeling of tunnel operations. The analysis of conformity involves comparing the constructed models with standard section models to identify overbreaks and underbreaks. The method also emphasizes the health evaluation of the tunnel rock drill, incorporating measurements of wear and dimensions to determine maintenance needs. By establishing a health evaluation coefficient and comparing it against predefined thresholds, the system can effectively signal when maintenance is required, thereby enhancing the operational reliability of tunnel machinery. Overall, this patent presents a structured approach to optimize tunnel operations through data-driven insights and proactive maintenance strategies.
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