494results about "Safety equipments" patented technology

The invention discloses an automatic grading early warning method and system for underground operation safety. The method comprises the following steps that 1, physical sign parameters and underground environment parameters of a tested person are collected; step 2, establishing an early warning level of personnel signs and an early warning level of environmental parameters; step 3, performing dynamic fusion analysis on the early warning level of the personnel signs and the early warning level of the environmental parameters according to the collected parameter data to obtain a final early warning level; and 4, taking corresponding early warning issuing measures according to the final early warning grade. According to the method, the weight can be calculated according to the deviation degree of each index, each index corresponds to one weight, the accuracy is higher, interference of other grades is avoided, subjective influences are reduced, and the method is more suitable for analysis of various types of indexes.

The invention discloses a stress-displacement roof catastrophe intelligent early warning method, and relates to the technical field of coal mine engineering safety and supporting. The method comprises the following steps: firstly, respectively establishing a stress-time database and a displacement-time database according to a relationship between stress and time of a roof separation layer and a relationship between displacement and time of the roof separation layer, and respectively setting four early warning modules in the corresponding databases; then stress-time and displacement-time are collected in real time through a sensor, and collected data are transmitted to a corresponding data processor; after being processed by the data processor, the data are uploaded to the stress-time database and the displacement-time database, are dynamically matched with the four early warning modules in each database, and then are converted to generate early warning signals for early warning. According to the method, the principle of stress-displacement synchronization is followed, and the accuracy of early warning is remarkably improved through double monitoring means and comprehensive monitoring of the roof separation stress and displacement.

The invention discloses a coal mine underground equipment personnel collaborative safety monitoring and risk early warning method, which comprises the following steps: deploying a sensing network, and collecting and processing personnel data and equipment data; evaluating the health state of the equipment based on the equipment data; cleaning the personnel data and then constructing a trajectory model; performing risk coupling analysis based on the three-dimensional risk identification model to obtain a comprehensive risk value; and performing grading response based on the comprehensive risk value and judging whether to perform model optimization or not. The invention further discloses a coal mine underground equipment personnel collaborative safety monitoring and risk early warning system which comprises a sensing layer, the sensing layer is connected with an analysis layer through a network layer, the analysis layer is connected with an execution layer, and the execution layer is connected with the sensing layer. The invention discloses a coal mine underground equipment personnel collaborative safety monitoring and risk early warning method and system, solves the technical bottlenecks of data splitting, response lag and poor environmental adaptability of a traditional monitoring system, and reduces the accident false alarm rate by more than 35% through spatial coupling analysis.

The invention discloses a mine disaster rescue robot based on multi-modal sensing and intelligent recognition and a mine disaster monitoring method, and relates to the technical field of mine disaster rescue robots. The mine disaster rescue robot based on multi-modal sensing and intelligent recognition mainly comprises an image processing and edge calculation unit, a UWB positioning module, an inertial measurement unit, a laser radar, a binocular depth camera, a thermal imager, a sound sensor, a gas sensor, an RGB camera, a motion control unit and a power supply system. According to the mine disaster rescue robot and the mine disaster monitoring method based on the multi-mode perception and intelligent identification, the positioning precision and the autonomous navigation capability of the rescue robot in a complex mine environment can be improved, and the accuracy and the real-time performance of state judgment of trapped workers are improved.