5results about How to "Verify availability" patented technology

This invention relates to the field of low-altitude emergency response technology and discloses a method for joint scheduling optimization of heterogeneous equipment for low-altitude emergency response tasks. The method includes: obtaining a task set and a set of heterogeneous equipment for the low-altitude emergency response task; constructing a dual-objective joint scheduling model for the low-altitude emergency response task based on the task set and the heterogeneous equipment set; performing non-dominated sorting optimization on the dual-objective joint scheduling model to generate a Pareto optimal solution set for the low-altitude emergency response task; executing the scheduling scheme in the Pareto optimal solution set; and monitoring the heterogeneous equipment of the low-altitude emergency response task in real time based on a preset dynamic rescheduling mechanism to obtain triggering events for the heterogeneous equipment; dynamically rescheduling the scheduling scheme based on the triggering events to generate a scheduling update scheme for the low-altitude emergency response task. This invention can improve the overall success rate, resource utilization efficiency, and system robustness of low-altitude emergency response tasks.

An MIMO array sparse rapid design method of a fuzzy function generator based on deep learning comprises the following steps: firstly, directly learning a fuzzy function mapping relation corresponding to virtual array configuration and an incident angle by using a deep learning model so as to replace a traditional analysis fuzzy function calculation process depending on a manifold matrix; and then performing efficient performance evaluation on the candidate sparse array based on the fuzzy function generator, and obtaining a sparse array structure meeting the requirements of high resolution and low sidelobe in combination with an optimization strategy. By means of the technology, acceleration of more than 35 times can be achieved on the premise of not explicitly calculating the fuzzy function, the fuzzy function prediction root mean square error (RMSE) lower than 0.1 is kept, and therefore the sparse array design time is greatly shortened. Experiments on a 2T4R K-band MIMO radar prove that the designed array achieves 10 dB sidelobe level in a 100-degree field of view, the angular resolution is improved by about 32.8%, and the effectiveness and engineering application value of the method in high-resolution MIMO sparse array design are proved.

This invention provides a method for collecting gases from the pre-splitting blasting of steeply inclined, extra-thick coal seams, comprising: S1: calculating the blasting parameters for pre-splitting blasting of steeply inclined, extra-thick coal seams and determining the construction location of the blasting holes; S2: combining the blasting parameters, empirical formulas, and theoretical calculations to determine the composition and pressure of the harmful gases generated after the pre-splitting blasting of steeply inclined, extra-thick coal seams, and fixing a gas collection device at the orifice of the blasting hole; S3: selecting an extraction system based on the content of the harmful gases generated after blasting, and discharging the harmful gases collected by the gas collection device through the extraction system; S4: comparing the composition and content of the harmful gases generated after blasting with the gas drawn into the extraction system to verify the extraction effect of the extraction system. The technical solution provided by this invention can solve the problem in existing technologies of not discharging the harmful gases generated after pre-splitting blasting.

The application discloses a bearing fault diagnosis method based on multi-source time-frequency feature fusion, and comprises the following steps: acquiring a bearing vibration signal and a rotating speed signal; constructing a bearing fault identification model based on a multi-source time-frequency feature extraction and fusion framework, which is used for identifying the bearing fault; training the bearing fault identification model to obtain a trained bearing fault identification model; and inputting the bearing vibration signal and the rotating speed signal into the trained bearing fault identification model to realize bearing fault classification. Through the combination of multi-source information fusion and an attention mechanism, the application improves feature expression capability and fault identification precision under the premise of ensuring model calculation efficiency, and provides an effective implementation method for bearing fault diagnosis under complex working conditions.

This invention discloses a method and system for four-way linkage management of engineering costs based on a hybrid large model, belonging to the interdisciplinary field of engineering digitization and artificial intelligence. The method uses a multi-constraint fusion scientific computing hybrid large model as its technical foundation, constructing the model through a four-in-one mechanism of data pre-setting, boundary setting, threshold pre-setting, and dynamic data import. It adopts a hybrid architecture of decision trees and recurrent neural networks, integrating five types of constraints: construction period, resources, cost, changes, and engineering specifications. Based on this, it achieves three-dimensional synchronization, three-value quantification, three-calculation comparison, and intelligent risk control linkage, with the bill of quantities item as the smallest accounting unit. When the cost deviation exceeds the threshold, an early warning is automatically triggered, and the root cause is traced back along the data correlation link, realizing a closed-loop management system of "early warning, location, and processing." This invention solves the pain points of traditional methods, such as inaccurate calculations, delayed early warnings, and untraceable data, significantly improving the accuracy, efficiency, and reliability of cost management. This technical solution has been evaluated and certified by the Ministry of Housing and Urban-Rural Development (Jiankeping [2023] No. 066).