22results about How to "Timely identification" patented technology

The invention relates to the technical field of intelligent fire rescue, and discloses a small self-sensing intelligent special vehicle and a control method.The small self-sensing intelligent special vehicle is characterized in that a plurality of supporting foot devices are connected to the outer side face of a lower bottom plate, a gearbox is connected to the terminal of the top of the lower bottom plate, plunger pumps are connected to the output ends of the gearbox, and the number of the plunger pumps corresponds to that of the supporting foot devices; the top of the upper top plate is connected with a recognition device, and a spraying device corresponding to the fire extinguishing agent storage box is arranged at the front end of the top of the upper top plate; one side of the top end of the middle plate is connected with a fire extinguishing agent storage box, and the middle end of the top face of the middle plate is connected with a steering assembly. According to the device, the change of a fire source can be recognized in time in a complex environment, and accurate and effective fire extinguishing measures are taken. According to the device, a brand new thought and method are brought to forest fire fighting, the fire source checking and extinguishing efficiency is improved, secondary reburning of the fire is avoided, and the overall safety and emergency response capacity of fire fighting operation are improved.

The invention belongs to the technical field of electric digital data processing, and particularly relates to a PDC drill bit torsion impact signal collecting and processing method which comprises the steps that torsion data are segmented into a plurality of torsion data windows; determining the torsion waveform complexity of the torsion data window; determining the rotation speed slippage strength and the formation meshing complexity of the torsion data window; determining an adaptive order of an AR model of the torsion data window; and performing predictive filtering on the torsion data in the torsion data window to obtain a predictive residual sequence of the torsion data window, and extracting a torsion impact signal according to numerical characteristics of the predictive residual sequence. According to the method, the numerical characteristics of the torsion data and the rotating speed data are analyzed, the order of the AR model is self-adapted, the limitation of the AR model with the fixed order is overcome, background noise is filtered out, and the accuracy and robustness of the torsion impact signal are improved.

This invention provides a method, device, electronic device, and storage medium for identifying road debris, belonging to the field of signal processing technology. The method includes: acquiring the original vibration signals corresponding to multiple grating measuring points in a grating array vibration sensing optical cable deployed on the road; determining a first energy for each grating measuring point within a first time window based on the original vibration signal; determining the occurrence time of a debris event within the first time window based on the first energy of each grating measuring point; determining a second energy for each grating measuring point within a second time window, wherein the occurrence time falls within the second time window; and determining the location of the debris on the road based on the second energy. Because the location of the debris is determined based on the energy distribution of multiple grating measuring points within a precise time window, the possibility of false alarms and missed alarms is reduced, improving the accuracy and efficiency of debris identification.

This invention discloses a semi-automatic assembly equipment for flexible copper busbar plugs. The flexible copper busbar plug includes a flexible copper busbar, a plug housing, and a sleeve. The equipment includes a rotary feeding mechanism with several carriers, and a first manual station, a second manual station, a positioning station, a crimping station, an inspection station, and a unloading station arranged sequentially along the rotation direction of the rotary feeding mechanism. The carriers are used to carry the flexible copper busbar plugs. The first manual station is used for pre-assembling the flexible copper busbar and plug housing onto the carrier. The second manual station is used for assembling the sleeve with the pre-assembled semi-finished products of the flexible copper busbar and plug housing mounted in the carrier. The unloading station includes an unloading clamping mechanism and an unloading conveying mechanism for unloading the finished flexible copper busbar plug. This invention adopts a semi-automatic design, combining manual pre-assembly with automated crimping and inspection, which reduces reliance on high-precision components and equipment costs, reduces the risk of frequent failures, and is more suitable for the production scenarios of small and medium-sized manufacturing enterprises.

This invention relates to the field of image processing technology and discloses a method and system for monitoring sewage outlets based on unmanned aerial vehicles (UAVs). The method includes: generating a dynamic flight strategy for the UAV based on meteorological information and lighting conditions of the target area; conducting preliminary monitoring of sewage outlets in the target area based on their distribution to obtain effective sewage outlet locations and images; filtering out ineffective sewage outlet locations from the distribution; compensating for ineffective sewage outlet locations using historical pollution data and a pre-set multi-period pollution model to generate a pollution heat map; extracting sewage outlet features from the effective sewage outlet images; marking anomalies in the target area's sewage outlets to obtain abnormal sewage outlet locations; conducting centralized inspections of these abnormal locations to obtain the monitoring results for the target sewage outlets. This invention effectively improves the stability of image acquisition quality, the comprehensiveness of sewage outlet location monitoring, and the accuracy of identification under extreme weather and lighting conditions.

The present application relates to the technical field of edge computing, and particularly relates to a mine environment intelligent monitoring method and system based on edge computing, which comprises: collecting multi-dimensional environment data under a mine; dividing a mine space into multiple local spaces based on three-dimensional coordinates of each sensor under the mine; determining an abnormal state value of a local space in a preset time period by using multi-dimensional environment data of the local space in the preset time period; obtaining a first initial category center point by using the abnormal state value and multi-dimensional environment data of the local space in a previous time period; obtaining a second initial category center point by using multi-dimensional environment data of the local space in a subsequent time period; iteratively updating the first and second initial category center points by using a Mini-Batch K-Means algorithm to obtain a risk value of the local space; and performing mine risk early warning based on the risk value. The present application can improve the real-time performance of underground security.

The invention discloses an equipment state prediction method and system based on a digital twin platform, and a server. The method comprises the following steps: converting voice or text information containing factory equipment operation early warning demand content into semantic information through a language generation model; screening an adaptive early warning algorithm through semantic vector matching based on a preset algorithm text mapping rule, and predicting the factory equipment operation data by adopting the matched early warning algorithm to obtain initial prediction data; performing abnormal value identification and classification processing on the initial prediction data through an abnormal detection rule, and then outputting accurate prediction data; and judging the operation state of the equipment according to the accurate prediction data, and if abnormity exists, triggering an early warning prompt and outputting a prediction analysis result. The accuracy of prediction data is effectively improved, the accuracy of equipment state judgment is guaranteed, and the production efficiency and the safety guarantee capability are further improved.

This invention discloses a method for arc detection and an arc relief device for the cable compartment of a switchgear, belonging to the field of power equipment fault handling technology. The arc detection method for the switchgear cable compartment of this invention periodically collects arc light data, current data, and pressure data, and then compares them with corresponding thresholds to confirm whether an arc has occurred. Simultaneously, it periodically collects environmental data and load data of the switchgear, updating some thresholds to make the arc fault identification more consistent with the specific installation environment and operating status of the switchgear. The arc relief device of this invention separates the arc detection circuit from the threshold update circuit; during the arc detection process, the threshold is in a latched state. This invention confirms the working priority through update signals, activation signals, and loading signals, avoiding conflicts between the arc detection and threshold update operation logic.

The application provides a target area monitoring method, device and storage medium. The target area monitoring method comprises: monitoring the stay duration of each object in a target area, wherein the target area comprises an isolation route and an area with a preset range on both sides of the isolation route; in the case that the stay duration of a target object in each object exceeds a preset time threshold, monitoring the laser receiving condition of a target receiver arranged in the target area; and determining whether a target event occurs in the target area according to the laser receiving condition. Through the target area monitoring method, the behavior that may cause a safety hazard can be found in time, i.e., it is determined that the target event occurs, and the efficiency and timeliness of finding the behavior that may cause a safety hazard are improved.

This disclosure provides a training method and apparatus for an adversarial defense model for coordinated optimization of distribution network security and economy, which can be applied to the field of distribution system optimization and scheduling technology. The method includes: obtaining a trained meta-defense model and a trained meta-attack model; performing the following operations based on an objective function until the combined performance fluctuation of the obtained defense model and attack model meets preset conditions. The objective function is constructed based on the security operation indicators and economic operation indicators of the sample distribution network: training the meta-defense model in the first state of the sample distribution network to obtain an intermediate defense model; training the meta-attack model based on attack samples in the attack sample pool to obtain an attack model; updating the attack sample pool to obtain an updated attack sample pool; obtaining the defense model; and when the combined performance fluctuation of the defense model and attack model does not meet the preset conditions, using the defense model as the meta-defense model and the attack model as the meta-attack model.

The invention relates to the technical field of data processing, in particular to a coal mine building foundation settlement monitoring and early warning system based on an intelligent sensor, which comprises a processor and a memory, the method comprises the following steps: acquiring an initial threshold value of any monitoring index at any monitoring point of a target coal mine building at the current moment; obtaining a target environment index of which the environment data exceeds the limit, and performing adaptive adjustment on the initial threshold according to the influence of the data change of each target environment index on the monitoring data of any monitoring index and the data change condition of any monitoring index in a local time range up to the current moment, according to the method, the self-adaptive threshold value of any monitoring index at any monitoring point at the current moment is obtained, monitoring and early warning are carried out on the foundation settlement risk of the target coal mine building at the future moment according to the self-adaptive threshold value of each monitoring index at each monitoring point, and the early warning accuracy is improved.

The utility model relates to the technical field of peristaltic pumps, in particular to a structure for identifying opening and closing states of a peristaltic pump. The cover body comprises a rotating part and a moving part, the moving part is arranged on the shell in a sliding mode, the rotating part is rotationally connected to the moving part, and the moving part reciprocates in the longitudinal direction of the shell through rotation of the rotating part; the contact device is installed on the shell and respectively generates a first signal and a second signal based on the action that the moving part is in contact with or away from the contact device, and the corresponding moving part is located at a first position and a second position, the closed state of the cover body can be monitored in real time through signal changes, it is guaranteed that cooling water can be continuously conveyed, and the service life of the cooling water is prolonged. The cooling effect is ensured.

The application discloses a rumor detection method and system based on heterogeneous propagation structure and dynamic feature fusion, and belongs to the fields of computer technology, artificial intelligence and social network analysis. The method steps are as follows: static features of users and posts are extracted, dynamic features of users and posts are calculated, and dynamic fusion features are obtained by fusing static and dynamic features. A heterogeneous graph sequence is constructed through the dynamic fusion features, convolution updating is carried out by using a heterogeneous graph convolution network, and a heterogeneous graph feature matrix is output. Then, a directed propagation tree is processed by using a graph attention network, and global representation of a propagation cascade is obtained. The heterogeneous graph features and the propagation cascade features are cross-time-step interacted, heterogeneous graph representation and propagation cascade representation are generated, and finally, the final representation is obtained by splicing, a rumor classification model is input, and a prediction result is obtained. The excellent performance of the application in various complex social scenes verifies the feasibility and effectiveness of the application as an efficient, accurate and excellent early warning rumor detection method.

The invention relates to a risk detection method and device for a cross-border e-commerce enterprise and a storage medium. The method comprises the steps that entity information and relation information between entities in cross-border e-commerce list data are extracted, a cross-border e-commerce knowledge graph is established, and the entities comprise subscribers, e-commerce enterprises, delivery addresses and commodities; based on the cross-border e-commerce knowledge graph, determining an order risk feature, the order risk feature being used for representing risk behaviors of an order in a transaction amount dimension, a delivery address dimension and a commodity dimension in a cross-border e-commerce transaction process; and based on the cross-border e-commerce knowledge graph and the order risk characteristics, determining a risk assessment result of the target e-commerce enterprise to indicate whether the target e-commerce enterprise has a goods collection and resale risk. According to the embodiment of the invention, the method can combine the characteristics of cross-border e-commerce services, and employs the cross-border e-commerce knowledge graph to more accurately recognize the possible collection and resale risk, thereby providing powerful support for risk management.

An automated imaging sensor testing and screening system and method are disclosed, relating to the field of imaging sensor testing. This invention addresses the significant need for automated batch testing and screening. The system includes: an integrating sphere, a testing mechanism, an electric displacement stage servo controller, and a main control computer; the integrating sphere and the testing mechanism are located on the same horizontal plane; the testing mechanism includes: a sensor mounting mechanism, a precision electric rotary stage, a precision electric Y-axis displacement stage, and a precision electric X-axis displacement stage; a precision electric Y-axis displacement stage is mounted on the precision electric X-axis displacement stage, the bottom of the precision electric rotary stage is fixed to the precision electric Y-axis displacement stage, and the sensor mounting mechanism is placed on the precision electric rotary stage; the main control computer sends control signals to the electric displacement stage servo controller; the electric displacement stage servo controller receives the control signals and adjusts the testing mechanism and integrating sphere according to the control signals to perform batch testing of the sensors under test. This invention is applied in the field of remote sensing satellite imaging technology.

The utility model provides a transportation mechanism and transportation equipment, the transportation mechanism comprises a rack, a driving part, a bearing part and an image recognition assembly, the rack is fixedly arranged, and the driving part is arranged on the rack; the bearing part is arranged on the rack and is in driving connection with the driving part, the bearing part can bear the graphite boat, and the driving part can drive the bearing part to bear the graphite boat to move in and out of the diffusion furnace; the image recognition assembly is arranged on the rack, the graphite boat is provided with an identification part, and the image recognition assembly can recognize the identification part to know whether the graphite boat deflects or not; the image recognition assembly is further in signal connection with the driving part, and the driving part receives a graphite boat deflection signal sent by the image recognition assembly and can drive the bearing part to correspondingly move and adjust. In the conveying mechanism, the driving part is used for driving the bearing part to bear the graphite boat to move, so that the graphite boat is conveyed into the diffusion furnace or conveyed out of the diffusion furnace, meanwhile, the driving part can directly or indirectly receive signal feedback of the image recognition assembly, and then the bearing part is correspondingly driven to move.

The present application relates to a multi-dimensional value evaluation method and system for scientific and technological information viewpoints based on fuzzy cumulative prospect theory, the method comprising the following steps: S1: constructing a scientific and technological information viewpoint value evaluation index system and calculating the accurate scores of several dimensions; S2: triangular fuzzy processing the accurate scores of several dimensions and calculating the comprehensive prospect value based on cumulative prospect theory; S3: linear normalization of the comprehensive prospect value of several dimensions to obtain the standardized score; S4: generating the star rating of the scientific and technological information and the corresponding decision suggestion. The system comprises an index calculation module, a fuzzy processing and prospect value calculation module, a linear normalization module and a grade evaluation module. The present application can realize comprehensive, objective and intelligent evaluation of the value of scientific and technological information viewpoints, and provides a scientific, intelligent, practical and interpretable value evaluation solution for the field of scientific and technological information analysis and decision support.

The invention discloses a difficult-to-predict branch processing method, a computer device, a medium and a product. The processing method of the difficult-to-predict branch comprises the following steps: converting a code snippet containing H2P into a plurality of basic blocks and writing the basic blocks into a preset cache; obtaining the decoded microinstruction and determining a microinstruction group; obtaining a physical address when the cache does not contain the microinstruction, and setting a hit item in the cache as a first numerical value when the microinstruction group contains the address and the deviation of a program ending address is the same as that of an access address of the microinstruction group; when hit items of all the items with the effective items being the first numerical values are all the first numerical values and the program address hits the program address in the cache, triggering the program address to access a preset cache and a preset predictor, and obtaining a prediction direction; and setting the next sequential program address of the H2P as a predicted target address corresponding to the direction opposite to the predicted direction. The method can be applied to deep assembly line and high-density H2P scenes, processing of multiple H2P branches can be achieved, and the overall performance is improved.

The application discloses a contact point identification method of an electromechanical brake system and an electromechanical brake system. In the electromechanical brake system, a thrust sensor is not arranged, an observation model for observing a motor load torque of the electromechanical brake system is constructed in advance, a driving controller in the electromechanical brake system observes the real-time motor load torque through the observation model and obtains real-time clamping force, the real-time motor rotor rotation angle at the corresponding moment is detected at the same time, comparison is made between the real-time motor rotor rotation angle and a target motor rotor rotation angle corresponding to the contact point, a rotation speed control strategy or a position control strategy is selected, the rising starting point of the real-time clamping force is identified, the contact point of the electromechanical brake system is updated by weighting, and then the process is exited. The beneficial effect is that the cost is reduced and the contact point can be identified and updated in time.

This invention belongs to the field of electrical digital data processing technology, specifically relating to a method for acquiring and processing torque impact signals from a PDC drill bit. The method includes: dividing torque data into several torque data windows; determining the torque waveform complexity of each torque data window; determining the rotational speed slip intensity and formation engagement complexity of each torque data window; determining the adaptive order of the AR model for each torque data window; performing predictive filtering on the torque data within each torque data window to obtain a prediction residual sequence for the torque data window; and extracting the torque impact signal based on the numerical characteristics of the prediction residual sequence. This invention overcomes the limitations of fixed-order AR models by analyzing the numerical characteristics of torque and rotational speed data and adaptively adjusting the order of the AR model, thereby filtering out background noise and improving the accuracy and robustness of the torque impact signal.

The invention discloses a multimedia informatization conference management method and system, and relates to the technical field of multimedia informatization conference management.The method comprises the steps that SHA256 hash calculation is carried out on extended display identification data blocks of downstream equipment before a conference, and then hash is carried out on a splicing result to obtain a topological fingerprint before the conference; converting the initial value of the number of the downstream devices of the repeats into binary vectors, performing bitwise exclusive or in sequence to obtain pre-meeting anchoring values, and constructing a topological shadow tree in combination with the mapping relation between the repeats and the downstream devices; marking a zero-topology window repetitor with the real-time downstream equipment number of 0 in the case, tracing a nearest sink node in a topological shadow tree to form a minimum influence domain, extracting an influenced display cluster identifier, and locally modifying a source cluster mapping matrix as a placeholder source; calculating an anchor value and a topological fingerprint, and verifying topological consistency through two dimensions of an anchor difference and a topological fingerprint Boolean quantity; after the conference, key data are integrated to be archived as conference management files, accurate conference topology management, efficient exception handling and problem tracing are achieved, and stable operation of the conference is guaranteed.

This invention relates to the field of single-board testing technology, specifically a single-board testing method and system based on logic configuration. The method includes: selecting several test boards based on a first human-computer interaction instruction on the test interface, and selecting several test cases based on a second human-computer interaction instruction on the test interface; a testing tool performing parallel testing on the several test boards through several network communication interfaces, and loading the corresponding several test cases; calling the test case logic file corresponding to each test case, and sequentially parsing and executing the logic rules in the test case logic file to obtain the execution result, and generating a test report. This method enables flexible selection of test boards and test cases, parallel testing of multiple test boards, and standardized configuration and precise execution of test logic, improving the efficiency, flexibility, and maintainability of single-board testing.