20results about How to "Guaranteed relevance" patented technology

The utility model provides a control terminal for large-scale machine operation hydraulic data acquisition, and relates to the technical field of power electronics, the control terminal comprises a power supply module, a lightning protection module, an industrial control computer, a GPS positioning module and an alarm lamp module, the power supply module is used for converting external 220V alternating current into 24V direct current; the lightning protection module is connected with the power supply module, and the lightning protection module is connected with an external data acquisition box; the industrial control computer is connected with the power supply module and the lightning protection module. The GPS positioning module is connected with the industrial personal computer, and the GPS positioning module is used for acquiring geographic position information of the large computer in real time; the alarm lamp module is connected with the industrial personal computer, and the alarm lamp module is used for triggering sound-light alarm when the industrial personal computer detects that the hydraulic system is abnormal. According to the utility model, the stability and the reliability of the monitoring system are improved, data can be transmitted in real time, and the efficiency and the safety of railway maintenance operation are remarkably improved.

The invention relates to a QEC detection method and system based on AR. The method comprises the steps that a pre-constructed engine standard model is disassembled into part units, a three-dimensional model set in the installation process of all the part units is obtained, and the three-dimensional model obtained after installation of each part unit is finished is a part unit standard model; obtaining an engine real-time model based on AR equipment; when the difference degree between the engine real-time model and the standard model is higher than a first threshold value, a first part unit with the largest difference degree is obtained, whether the corresponding real-time model is matched with the three-dimensional model set or not is judged, if yes, the first part unit is maintained towards the corresponding standard model state, and if not, the first part unit is maintained; and when all the part units in contact with the first part unit are synchronously changed to the corresponding standard model states, the engine real-time model is obtained again to continue execution, and otherwise, a QEC request is sent out. Compared with the prior art, the method has the advantages that the safety and the efficiency of the whole QEC operation inspection and verification process are improved, and the like.

This invention discloses a non-load-bearing front engine compartment structure, a frame, and a chassis. The front engine compartment structure includes two sets of wheel arch assemblies spaced apart along the width of the vehicle body. A first crossbeam and a second crossbeam are arranged parallel to each other and spaced apart between the two sets of wheel arch assemblies. Two hinge mounting members are arranged between the two wheel arch assemblies. The hinge mounting members are provided with mounting surfaces for mounting hood hinges. The structural strength of the wheel arch assembly itself is improved by the first and second structural beams. The parallel first and second crossbeams are fixed to the two sets of wheel arch assemblies respectively, further improving the correlation and stability between structural components and maintaining the structural strength of the wheel arch assemblies as a whole. The hinge mounting members are arranged on the wheel arch assemblies to provide the mounting base for the hood hinges. Under the premise of reliable overall structural strength, the additional hood mounting structure is avoided in the front engine compartment, thus improving overall reliability and space utilization.

The invention relates to the field of wind power generation, in particular to a wind turbine generator yaw static error correction method and system based on a multi-beam laser radar. The method comprises the following steps: S1, scanning a wind field area in front of an impeller of a generator set through a multi-beam wind measurement laser radar mounted in a cabin of the wind turbine generator set to obtain parameter information of a plurality of spatial points; s2, performing fitting calculation on the parameter information system to obtain a fitting circle representing a horizontal wind vector of the wind field area, and solving the fitting circle to obtain a free flow wind direction; s3, the free flow wind direction is compared with the current cabin orientation, and a real-time static yaw error angle is obtained through calculation; generating a yaw control instruction according to a preset control strategy; s5, solving and calculating the fitting circle to obtain a transverse wind component, and correcting the yaw control instruction; according to the method, the control instruction is generated through the control strategy to drive the yaw system to perform dynamic compensation, so that the wind turbine generator can continuously maintain the optimal windward attitude, and the stability and long-term effectiveness of control are ensured.

This application provides a method for finely characterizing the fractured area of ​​the floor strata in a mining face, relating to the field of coal seam floor characterization technology. The method includes: collecting the original microseismic event signals and environmental correlation parameters corresponding to each microseismic event in the fractured area of ​​the mining face floor strata; performing feature extraction to obtain a microseismic event feature matrix corresponding to each microseismic event; inputting a microseismic event classification model to obtain the rupture correlation confidence score of the microseismic event; if the source type of any microseismic event is rupture type, and the corresponding rupture correlation confidence score is greater than a preset rupture correlation confidence score threshold, then the fractured area of ​​the mining face floor strata is characterized based on this microseismic event. This application achieves fine characterization of the fractured area of ​​the mining face floor strata, providing a reliable basis for engineering safety control.

The invention discloses a weighing experiment device and method for an electric shovel with an externally-hung load, which are characterized in that on the premise that the electric shovel is in a static state, the electric shovel meets a moment balance condition at the moment, a bucket rod and a bucket are rigid bodies, and a hinge point is a saddle rotation center, so that the moment generated by a lower-hung balancing weight on the saddle rotation center is uniform; and the moment is equal to the moment generated to the center when the material is placed in the bucket, so that the moment balance state of the electric shovel can be equivalent, the weight equivalent simulation of the lower hanging counterweight and the internal material is realized, and an accurate, efficient and safe load simulation scheme is provided for the electric shovel weighing experiment.

This invention provides a method for optimizing process parameters of aluminum foam based on physical information deep learning, belonging to the field of deep learning-based process parameter optimization. The method includes: data preprocessing, mechanical property prediction, and process parameter optimization. Data preprocessing includes generative data augmentation based on physical information, data standardization, and feature dimensionality reduction. Mechanical property prediction utilizes enhanced data of aluminum foam to predict mechanical properties by constructing a multimodal information fusion prediction framework based on graph neural networks. Process parameter optimization uses a trained graph neural network as the objective function and embeds it into an improved Bayesian optimization framework to iteratively locate the parameter combination that yields the optimal energy absorption performance. This method can not only predict the mechanical properties of aluminum foam but also optimize process parameters during its preparation, significantly reducing R&D costs, shortening the development cycle, and improving the effectiveness of material R&D.

A system for determining a non-linear surge pricing is described. Typically, the system obtains historical data, as well as original non-linear surge pricing models and service parameters, related to service usage by a user and service provision by a provider, respectively. From the data, the system determines a user pricing elastic model and a provider pricing elastic model, and optimize the objective function based on a weighted combination of the predicted number of service uses and the predicted total amount of merchandise transactions (predicted GMV), an original non-linear surge pricing model, service parameters, and one or both of a user pricing elasticity model and a provider pricing elasticity model. The optimized objective function is an updated model for non-linear surge for generating an enhanced surge multiple for a new request for service use based on the optimized objective function and the original surge multiple.

The utility model discloses mechanical processing technical field especially relates to a kind of aluminium alloy rack for cutting machine, including rack base and the rack shell of covering rack base setting, still include the feeding cabin and cutting cabin of setting on rack shell, feeding cabin is provided with feeding plate inside, rack base is provided with the feeding frame of intercommunication feeding cabin and cutting cabin, cutting frame is located on the rack base of cutting cabin one side, cutting slide rail is slidably connected with cutting saw, utilize feeding cabin and cutting cabin respectively corresponding feeding function area and cutting function area, so it can be in actual use, the cabin of two different working contents is distinguished, realize the effect of separate processing, when adjusting the working environment in feeding cabin, cutting cabin does not need to open, keep closed state, and when adjusting cutting cabin, feeding cabin keeps closed state, so two cabins are independent of each other, to be able to protect the security of surrounding working environment.

The present application relates to the technical field of data processing, and provides a label level evolution document retrieval method, device, equipment and medium, the method comprises: based on the mixed architecture of regular matching and large language model, extracting candidate labels from text content and verifying and cleaning to obtain compliance labels; according to the hierarchical structure of the label dictionary, performing bidirectional hierarchical expansion on the compliance labels to obtain a complete label set and binding storage; extracting query labels from the retrieval request and performing bidirectional hierarchical expansion to obtain a retrieval label set, and deducing a retrieval opposite label set semantically exclusive to the retrieval label set; based on the retrieval label set and the retrieval opposite label set, performing double-mode filtering retrieval, and outputting the retrieval result. The present application makes the label labeling process of the ship field document get rid of the limitation of manual operation, the label system can be continuously improved, the document retrieval can be based on the forward matching and the reverse exclusion double logic at the same time, and the fullness rate and the precision rate of the ship document retrieval are realized.

The application relates to the technical field of medical instrument, and discloses an electric pressure regulation system for an anesthesia mask pipe. The system comprises a physiological data acquisition module, which acquires multi-source physiological data to generate a synchronous data set; a multi-modal feature modeling module, which generates a multi-dimensional joint probability feature matrix by using a Bayesian probability graph model; a dynamic pressure decision module, which constructs an adaptive controller based on deep reinforcement learning to output a pressure regulation target value; and a multi-target collaborative control module, which generates a steady-state pressure control strategy by using a mixed integer programming model and an improved ant colony algorithm. In addition, the system is also provided with a virtual pressure estimation module for pressure leakage diagnosis and redundant valve switching, and an abnormal interruption protection module for guaranteeing the safety of a patient. The system realizes accurate and intelligent regulation of the pressure in the anesthesia mask pipe, and improves the safety and stability of the anesthesia process.

The application discloses a 180-degree wave direction ambiguity removing method and system for a spaceborne wave spectrometer sea wave direction spectrum, and belongs to the field of microwave remote sensing. The direction and scanning time of an incident beam are controlled through an electric scanning detection mode of the spaceborne wave spectrometer, so that the beam direction is unchanged within a time interval of delta t, that is, the observation direction of the sea surface is unchanged, so as to ensure the correlation of the sea surface, and then to ensure that two wave signals for cross spectrum calculation have sufficient correlation. The 180-degree wave direction ambiguity can be removed by using the cross spectrum method, so that the inversion precision of the spaceborne wave spectrometer sea wave spectrum and sea wave parameters is improved, and then the application of the spaceborne wave spectrometer sea wave spectrum data is promoted. The application provides the 180-degree wave direction ambiguity removing method for the spaceborne wave spectrometer sea wave direction spectrum. Since the electric scanning detection mode increases the correlation of the wave signals detected at different times, the cross spectrum method can remove the 180-degree wave direction ambiguity in the sea wave direction spectrum.

The embodiment of the invention discloses a telemarketing communication term real-time generation method and device based on multi-dimensional data fusion and closed-loop self-learning. A specific embodiment of the method comprises the following steps: in a telemarketing call process, capturing and processing a bidirectional voice signal in real time, and generating a structured dialogue text; synchronously fusing static attribute data, historical interaction records and intention and emotional states obtained by real-time analysis from the customer relationship management system, and constructing a multi-dimensional customer portrait; based on the current dialogue context and the multi-dimensional customer portrait, a retrieval enhancement generation technology is combined with a large language model to dynamically generate a personalized dialogue skill; pushing the generated verbal skill to an operation interface of telemarketing personnel in real time for reference; and after the call is finished, feedback data are collected and used for driving model self-learning optimization. According to the embodiment, the accuracy, personalization and self-adaptive capability of telemarketing communication terms can be improved.

The application provides a psychological support answer automatic generation method based on LLMs iterative correction, first constructs a seeker character image prompt, then carries out resource library retrieval according to the seeker character image prompt, and obtains a plurality of answers; uses LLMs to generate a corresponding strategy chain for each answer, and guides LLMs to select an optimal strategy chain therefrom; then generates an initial answer based on the optimal strategy chain; iteratively guides LLMs to discover the 'deficiency' information of the initial answer, and finally constructs a correction suggestion based on the 'deficiency' information of the initial answer to guide LLMs to generate a final answer. The application is based on retrieval enhancement, combines the psychological support strategy theory and the internal function of LLMs self-exploration and correction, constructs a dynamic and cooperative triple prompt framework, and guides LLMs to generate a high-quality answer with higher relevance and individualization.

The application relates to a haunch body generation method based on a catch basin building model, wherein the method comprises the following steps: acquiring geometric information of the catch basin and extracting a basic component associated with the catch basin; based on the geometric information, filtering side edges meeting a haunch condition from the catch basin as candidate haunch edges, and performing adaptive verification on boundaries of the candidate haunch edges and boundaries of the basic component to obtain a target haunch edge set; based on the target haunch edge set, determining a generation direction and a haunch section parameter of each haunch edge, and generating an initial haunch body based on the generation direction and the haunch section parameter; adjusting the initial haunch body to obtain a target haunch body, and fusing the target haunch body with the catch basin to generate a catch basin building model with the haunch body. The method solves the problem of how to improve generation efficiency and accuracy in the related art.

This invention relates to the field of machining technology, and particularly to an intelligent matching method and system for slow wire EDM machining parameters. The method involves loading electrode wire parameters and workpiece parameters to configure machining parameters and obtain first machining parameters. When the monitored environmental parameters are inconsistent with the standard environmental parameters, the method uses the electrode wire parameters, workpiece parameters, first machining parameters, and monitored environmental parameters as constraints to search the slow wire EDM machining sample set, performs lumped value evaluation, and obtains the fitted dimensions of the workpiece after cutting. When the dimensional deviation between the fitted dimensions and the standard dimensions of the workpiece after cutting is less than or equal to the dimensional tolerance, metal cutting control is performed based on the first machining parameters; otherwise, the first machining parameters are updated. This invention improves the accuracy and stability of metal cutting using slow wire EDM, reduces trial cutting costs and scrap rates, increases machining efficiency, and reduces production burden.

This invention relates to a large language model reasoning method based on relational constraints and path guidance. The method receives an input question through a large language model and generates a set of relational constraints semantically related to the input question by combining preset prompts. Using a knowledge graph as the retrieval object, multi-hop relation retrieval is performed iteratively based on the generated set of relational constraints. After each hop, the semantic similarity between candidate relations and the input question and relational constraints is calculated, constructing a constrained multi-hop relation space. The multi-hop relation space is combined with the input question, and an interpretable relational path is generated through the large language model. Based on the generated relational path, corresponding candidate subgraphs are retrieved from the knowledge graph. Through hop-by-hop entity filtering and pruning operations, the relational path is instantiated into an entity-level reasoning path. The obtained reasoning path is combined with the input question, and an accurate and interpretable answer is generated through the large language model.

This invention discloses an image recognition method for reinforcing bars, belonging to the field of image recognition technology. The method involves acquiring an image of reinforcing bars with parameter annotations, identifying the parameter annotations within the image, and expanding the range of the parameter annotations based on the pixel density surrounding them. Next, by identifying the contour of the reinforcing bars in the image, and based on the overlap between the contour and the expanded parameter annotations, a main contour containing both the reinforcing bar contour and the parameter annotations is obtained. The main contour is then expanded to retrieve other parameter annotations, resulting in candidate influence regions. Based on the overlap between the main contour and the candidate influence regions, other parameter annotations falling within the candidate response regions are matched with the reinforcing bar contour. This invention establishes a mapping between geometric topology analysis and semantic text extraction, enabling image analysis to possess geometric cognitive capabilities, thereby automatically recognizing the shape and parameter information of reinforcing bars and outputting structured data.

The invention provides an information retrieval method and device and a storage medium, and the method comprises the steps: carrying out static denseness, context denseness and sparse coding on a retrieval text, matching an associated provision set according to the static denseness, context denseness and sparse coding, then extracting a triple of associated provisions through a large language model, and determining a retrieval result by combining the to-be-retrieved text, the triple set and the associated text. Text features are comprehensively captured through multiple codes, retrieval comprehensiveness and accuracy are improved, associated texts can be simplified by extracting triads, results have basis, logic coherence and traceability are achieved, the problems that traditional retrieval is low in efficiency and fuzzy in result are solved, rail transit operation and maintenance requirements are met, personnel cost is reduced, and field response speed is improved.

This invention discloses a method, apparatus, device, medium, and product for allocating physical machine resources. The method includes grouping all physical machines in a cloud delivery environment into several physical machine groups; selecting several candidate physical machine groups that meet the needs of a target virtual machine cluster based on the resource information of each physical machine group using a minimum resource utilization priority strategy; determining a target physical machine group based on all candidate physical machine groups using a random selection strategy; and allocating the physical machines in the target physical machine group to the target virtual machine cluster. This method combines a random selection strategy with a minimum resource utilization priority strategy, using the minimum resource utilization strategy to select multiple physical machine groups and the random selection strategy to select a specific physical machine group. This solves the impracticality of the random selection strategy and the resource contention problem of minimum resource utilization, avoiding excessively long waiting times for certain tasks and affecting overall task time and performance.