5results about How to "Understand in time" patented technology

The invention discloses a blast furnace incoming iron management data processing system and method. Comprising a data display module, a query module, an export module and a data operation module. The data display module is provided with a converter molten steel receiving display unit, a molten steel receiving team statistical display unit, a blast furnace incoming iron scrap display unit and a blast furnace incoming iron team statistical display unit; and the converter molten steel receiving and displaying unit is used for displaying detailed data received by the converter, wherein the detailed data comprises converter heat, blast furnace heat, time, ladle number, molten iron components and operation information. According to the invention, by integrating blast furnace incoming iron related data and intensively displaying various types of data on different pages, unified management of the data is realized. Meanwhile, convenient data entry, modification and deletion operation and efficient query and export functions are achieved, the time and labor cost of data management are greatly saved, and the data management efficiency is improved.

The application discloses a GIS partial discharge pattern recognition method based on polar coordinate distribution entropy optimization, and belongs to the field of large power grid on-site power equipment defect diagnosis and recognition. Firstly, aiming at the signal missing phenomenon of photoelectric partial discharge signals, a non-subsampled contourlet transform is used to fuse and process photoelectric PRPD graphs, so that photoelectric fusion graphs are obtained. Then, feature points and scale vectors of the fusion PRPD graphs are extracted based on a KAZE algorithm. Next, the feature points are dispersed to polar coordinate expressions according to coordinates and scale vectors. Distribution entropy of each region divided on the polar coordinates is calculated to form a feature vector. Finally, the feature vector is loaded into a long short-term memory network optimized by an Adaboost algorithm to verify the accuracy of partial discharge pattern recognition. Compared with a statistical parameter method and a KAZE feature extraction method, the algorithm can better extract a PRPD graph feature vector, and the accuracy of partial discharge defect pattern recognition is significantly improved.

This invention discloses an automatic product loading device, belonging to the technical field of loading devices. Its key features include: a six-axis industrial robot, a blank material bin, multiple machining centers equipped with dual-station fixtures, a discharge conveyor belt, and a safety fence; it also includes a reversing mechanism and a robot control integrated system, with the reversing mechanism corresponding to each machining center; the robot control integrated system includes a PLC controller capable of communicating with each machining center, the six-axis industrial robot connected to the PLC controller, responding to the machining center's call signals, and performing operations such as material picking, loading and unloading at the first station, sending workpieces to the reversing mechanism for reversal, loading at the second station, and sending finished products to the discharge conveyor belt; this invention can achieve fully automatic loading and unloading, reduce labor costs, and improve production stability and quality consistency.

The utility model discloses an explosion-proof box for battery test protection, which comprises a battery test explosion-proof box body and a front turnover door, and a transparent toughened glass window is arranged in the door. An exhaust fan body is arranged on the side face of the box body, a fan assembly in the exhaust fan body is connected with a plug-in filter box containing a side face intercepting filter screen and middle activated carbon, gas in the box can be exhausted after being extracted and filtered after testing is completed, influences of peculiar smell and smoke dust on the environment and personnel are reduced, and the working progress is accelerated. A cleaning cotton wiper is arranged on the inner side face of the glass window and controlled through a movable strip block, a longitudinal connecting guide column, a transverse connecting guide column and a connecting metal wire rope, and smoke dust can be wiped to facilitate observation. The box body is provided with an operating console, a state display lamp, a bottom universal wheel body, a side-mounted sealing plate, a breathable screen frame and the like. The explosion-proof box has various functions, is convenient to operate, can effectively guarantee the safety of battery testing, improves the working efficiency and observation convenience, and has good practicability and popularization value.

The invention relates to the technical field of ecological monitoring, in particular to a mine renovation ecological restoration monitoring method based on multi-source data, which comprises the following steps: acquiring mine environment information, restoring polluted soil by using chemical agents, carrying out vegetation planting in a mine restoration area, and realizing ecological restoration through plant restoration. A standard planting area is established as a reference, vegetation growth information is obtained through aerial photography of an unmanned aerial vehicle, vegetation growth expected information is obtained according to the vegetation growth information of the mine restoration area and the standard planting area, and the area with poor vegetation growth in the mine restoration area is determined according to the expected information. According to the method, the standard planting area is established, vegetation growth of the standard planting area serves as a reference, vegetation growth expected information in the mine restoration area is obtained, sampling sites of soil, air and the like are determined again according to the expected information, the restoration situation can be known in time, and the restoration mode can be adjusted in time according to monitoring data.