191results about How to "Improve judgment accuracy" patented technology

The invention relates to the technical field of fault detection for a wireless communication network, and discloses a fault detection method for the wireless communication network. By collecting data of base station signal strength, network delay, data packet loss rate and user equipment signal quality, the problem of insufficient fault detection caused by a single index is solved. Through multi-dimensional data acquisition, the system can comprehensively evaluate network performance, the fault detection accuracy is improved, and different fault types can be effectively identified especially in a complex fault mode. By storing the data according to the time sequence, the problem of time sequence chaos is avoided, and accurate detection of time-varying faults is ensured. The comprehensive data vector generated by each time of sampling comprises a plurality of network performance indexes, so that the fault detection and positioning capability is improved. Abnormal values are eliminated through data preprocessing, the data quality is ensured, an accurate basis is provided for subsequent analysis, and the reliability of a detection result is ensured.

The invention relates to the technical field of data processing, in particular to a shrimp group health condition assessment method based on deep clustering analysis, and the method comprises the steps: monitoring health parameters; determining a shrimp group dispersion grid; determining a temporary grid; identifying a non-shrimp group abnormal grid; calculating an actual health index; and adjusting the grid step length and evaluating health. According to the method, the health condition of the shrimp group can be accurately monitored and evaluated by combining physiological and behavior data such as real-time density, saturation and activeness, abnormal grids are eliminated step by step, more representative grids are screened out, evaluation deviation caused by environmental fluctuation or measurement errors is avoided, and the evaluation accuracy is improved. The dynamic monitoring of the health condition of the prawn group is realized, and the grid step length is automatically adjusted by comparing the ideal health index with the actual health index, so that the health assessment precision and reliability are improved, and the problem of inaccurate health assessment result caused by unstable environmental parameters is effectively solved.

The invention relates to the technical field of network advertisements, in particular to an advertisement data management system based on market trend analysis, which comprises a data acquisition module, an analysis module, a prediction module, a conversion rate calculation module and an adjustment module. The advertisement effect is reflected by acquiring click and purchase data after advertisement putting, the change trend of user behaviors is accurately recognized through the analysis module, and the user change rate is calculated, so that data support is provided for an advertisement putting strategy, and the advertisement putting strategy is more accurate by analyzing historical data, predicting the future purchase trend and comparing with predicted data in real time. The conversion rate change of the advertisement is accurately evaluated, a basis is provided for optimizing the advertisement effect, whether the advertisement putting duration needs to be adjusted or not is judged according to the comprehensive analysis of the user change rate and the conversion rate change rate, efficient utilization of advertisement resources is ensured, the accuracy and flexibility of advertisement putting are remarkably improved, the conversion rate and the return on investment of the advertisement are facilitated, and the user experience is improved. And continuous optimization and improvement of the advertisement effect are realized.

The invention, which relates to the technical field of building construction monitoring, discloses a tall template construction safety monitoring system comprising a template data acquisition module, a dynamic load analysis module, an interpolation module, a time window analysis module, an adjacent region comprehensive analysis module and an early warning module. The template data acquisition module collects stress data of a basic area in real time through a sensor network, the dynamic load analysis module dynamically adjusts division of the stress area according to the stress data, the interpolation module performs smoothing processing on the adjusted data, the time window analysis module calculates area stress fluctuation, and the time window analysis module analyzes the area stress fluctuation. The adjacent region comprehensive analysis module evaluates the stress influence of adjacent regions, the early warning module generates risk levels through fuzzy logic, and the construction report generation module is used for recording and generating a safety report; according to the invention, a local dangerous area can be better controlled and accurately positioned, and large-range blind troubleshooting is avoided, so that the safety management efficiency of a construction site is improved.

The embodiment of the invention discloses a dangerous chemical identification method, and the method comprises the steps: obtaining chemical information data, and constructing a dangerous chemical semantic database according to the chemical information data through employing a deep learning multi-modal data fusion algorithm; according to naming rules and attributes of chemicals, defining text variables and numerical variables, extracting hazardous chemical judgment conditions from the chemical information data, and establishing a hazardous chemical rule base according to the text variables, the numerical variables and the hazardous chemical judgment conditions; according to the chemical information data, establishing a hazardous chemical data model based on a graph neural network technology; constructing a hazardous chemical substance identification system by using the hazardous chemical substance semantic library, the hazardous chemical substance rule library and the hazardous chemical substance data model; and obtaining to-be-classified chemical information, and classifying to-be-classified chemicals in the to-be-classified chemical information by using a hazardous chemical identification system to obtain a hazardous chemical judgment result. According to the invention, more intelligent and accurate dangerous chemical identification is realized.

The invention relates to the technical field of airport lighting equipment, in particular to an airport navigational light control system based on flight information, which comprises an irradiation unit for outputting navigational light by using irradiation parameters to generate navigational light information, an aviation interaction unit for generating and outputting real-time flight information, and a control unit for controlling the airport navigational light according to the real-time flight information. The information receiving unit is used for receiving the real-time flight information output by the aviation interaction unit and positioning the real-time position of the aircraft in the air, and the analysis unit is used for determining whether the flight state of the aircraft meets the standard or not and the reason for the non-conformity and generating a corresponding processing instruction. And the control unit is used for receiving the corresponding processing instruction, determining the irradiation parameters of the irradiation unit and sending a corresponding notice to the aviation interaction unit. The corresponding instruction is sent to the aircraft based on the flight environment or the real-time flight state of the aircraft, the irradiation parameters of the lamplight are adjusted in a targeted mode, it is guaranteed that the aircraft can stably land to the designated site, and meanwhile the navigation aiding efficiency of the system for aircraft landing is effectively improved.

The invention relates to a system and method for assisting in judging whether salary debt behaviors exist or not, and belongs to the technical field of computer network communication. The system comprises a management server, a data acquisition module, a data analysis module, an early warning prompt module, a complaint processing module and a credit evaluation module; the data acquisition module is in bidirectional signal connection with the management server, the data analysis module is in bidirectional signal connection with the management server, the early warning prompt module is in bidirectional signal connection with the management server, and the complaint processing module is in bidirectional signal connection with the management server. According to the system and the method for assisting in judging whether the salary debt behavior of the migrant worker exists, through mutual cooperation among the management server, the data acquisition module, the data analysis module, the early warning prompt module, the complaint processing module and the credit evaluation module, key data such as fund flow and salary payment conditions of an engineering project can be monitored in real time; and early warning is immediately carried out once abnormity is found, so that the timeliness and accuracy of supervision are greatly improved.

The invention discloses a transmission line disconnection fault identification method and device based on multi-stage current comparison, and the method comprises the steps: extracting the zero-sequence current data of a fault line and the tripping signal data and reclosing signal data of a protection device from a fault recording file or a protection recording file obtained from the two sides of the fault line, the fault process of the line is divided into a plurality of stages; calculating per unit values of the current fundamental frequency amplitudes of the two sides of the fault line in each stage by taking the maximum value in the current fundamental frequency amplitudes of the stage before the fault as a current amplitude reference value; and judging the disconnection condition of the faulty line based on comparing the per-unit value with the disconnection fault judgment coefficient kdx and the grounding judgment coefficient kjd. According to the invention, the fault process is divided into a plurality of stages, and each time period in which the line may be disconnected or grounded is fully considered; the method can efficiently and accurately judge the line breaking fault of the line and whether the condition of grounding after line breaking exists, and does not cause misjudgment with the grounding fault.

The invention discloses a pump turbine phase resonance risk identification method and device, a medium and a product, and relates to the field of hydroelectric generation. The method comprises the following steps: firstly, carrying out a pressure pulsation test on the water-turbine generator set to determine each-order dominant frequency of an excitation source; calculating the wavelength of a pressure wave corresponding to each order of dominant frequency according to the working condition of the pump turbine; according to the working condition of the pump turbine, the position difference of two pressure wave transmission during two adjacent excitation is calculated; substituting the wavelength of the pressure wave corresponding to the dominant frequency of each order and the position difference under different pump turbine working conditions into a phase resonance risk coefficient calculation formula, and calculating to obtain a phase resonance risk coefficient of the pressure wave corresponding to the dominant frequency of each order; and comparing the phase resonance risk coefficient of the pressure wave corresponding to the dominant frequency of each order with the risk judgment coefficient, and identifying the harmonic order with the phase resonance risk. By adopting the method, the judgment precision of phase resonance can be improved, and the application range of the phase resonance judgment method is expanded.

The invention relates to the technical field of packaging box defect detection, in particular to a packaging box printing image defect detection method, which comprises the following steps: detecting the actual contour of a printing image and the image information of the thickness of each point position by using a detection module; establishing a coordinate system according to the image information by using a test module, marking a plurality of test points for the coordinate system according to a database, and testing the hardness of the packaging box for each test point; an analysis module judges the coining qualification of the printed image according to the actual contour of the printed image, judges the reason for the unqualified coining of the printed image according to the offset of the adjacent test points, and determines whether the coining of the printed image is qualified or not according to the reason; and the adjusting module is used for adjusting the corresponding position for judging whether the printed image coining is qualified or not according to the adjusting mode determined by the analysis module, so that the problems that a printed image packaging box produced in the prior art is insufficient in hardness, and the image is prone to deformation are solved.

The invention provides a gene EVM0016124 and application of the gene EVM0016124 in judging the dormancy degree of honeysuckle seeds. The nucleotide sequence of the gene EVM0016124 is shown as SEQ ID NO.1, and the dormancy degree of honeysuckle seeds can be judged through the expression quantity of the gene.

The invention discloses a network detection method, a related device, electronic equipment and a storage medium, and the network detection method comprises the steps: selecting an application program which currently triggers a network service request as a target application; the current network state is pre-judged based on historical network information determined after the target application and the application programs in the trusted application set recently trigger the network service requests; wherein the historical network information comprises a historical network state and a historical moment when the historical network state is determined; based on the current network state, determining a timeout request duration of the target application; wherein the timeout request duration is in positive correlation with the network quality represented by the current network state; and determining whether to prompt a network service request which cannot respond to the target application currently based on whether a request feedback result of the target application is obtained within the timeout request duration. According to the scheme, the judgment precision of the network state and the feedback speed of the application program can be improved.

The invention discloses a psychological health state assessment method based on big data, and the method comprises the steps: obtaining social media text information, voice data and physiological signals of a user, and carrying out the preprocessing of the social media text information, the voice data and the physiological signals; constructing an emotion vector by using the preprocessed social media text information, voice data and physiological signals, performing emotion division on the emotion vector through a K-means clustering algorithm, and updating the emotion vector to obtain an emotion stability index; generating personalized psychological health suggestions of the user based on the emotional stability index, dynamically adjusting the emotional state of the user according to the condition that the user accepts the personalized psychological health suggestions, and re-updating the personalized psychological health suggestions; according to the method, the emotion fluctuation of the user can be comprehensively captured, more accurate psychological health assessment is provided, and the timeliness and effectiveness of psychological health suggestions are improved.

The invention relates to a battery preparation method. The battery preparation method comprises the following steps: obtaining a to-be-treated winding battery cell; carrying out hot pressing treatment on the to-be-treated winding battery cell, and detecting whether the surface hardness of the hot-pressed winding battery cell reaches a preset hardness range or not; packaging the wound battery cell with the surface hardness reaching a preset hardness range into a shell as a target battery cell; and removing the wound battery cells with the surface hardness outside the preset hardness range. According to the scheme provided by the invention, whether the surface hardness of the wound battery cell is in the preset hardness range or not can be detected after the wound battery cell is subjected to hot pressing, the wound battery cell with the surface hardness reaching the preset hardness range is sub-packaged into the shell, and the wound battery cell with the surface hardness not reaching the preset hardness range is removed; therefore, the phenomenon that the wound battery cell subjected to excessive hot pressing enters the packaging and shell-entering process is effectively reduced, the production quality of the battery is effectively improved, the yield of packaging and shell-entering of the wound battery cell is effectively improved, and the production efficiency of the battery is improved.

The invention discloses a device for measuring the pressure of a pipeline, and belongs to the technical field of pressure detection of fluid in the pipeline. A device for measuring pipeline pressure comprises an annular walking mechanism moving in the axial direction of the interior of a pipeline, a pressure measuring mechanism used for measuring different radial angle positions of the pipeline and located in the annular walking mechanism, and a traction mechanism used for driving the annular walking mechanism to move. The two traction mechanisms are located at the two axial ends of the pipeline correspondingly. The method has the advantages that the leakage point of the pipeline can be found more timely, and the construction time of later repair is shortened.

The invention provides a maintenance site recommendation method, electronic equipment and a vehicle, and the method comprises the steps: determining a maintenance demand of the vehicle according to the obtained maintenance associated data of the vehicle; determining a target maintenance site and a recommended time range according to the maintenance associated data in response to the determined vehicle maintenance demand as maintenance; performing recommendation display on the target maintenance site within the recommendation time range; according to the maintenance site recommendation method provided by the invention, whether the vehicle needs to be maintained or not can be timely and accurately determined according to the maintenance associated data of the vehicle; when it is determined that maintenance is needed, the target maintenance site and the recommended duration range can be determined, the target maintenance site is recommended and displayed in the recommended duration range, a user is guided to go to the target maintenance site, it is ensured that the vehicle receives the maintenance service at the optimal time, the competitiveness of a 4S store is enhanced, and the maintenance efficiency is improved. The maintenance quality of the vehicle and the performance of the whole vehicle are guaranteed, and the loss rate of customers is reduced.

The invention relates to a basketball match out-of-bound detection method and system based on computer vision in the technical field of match monitoring. The method comprises the following steps: deploying a plurality of overlook camera cameras and a plurality of look-up camera cameras at a preset position of a basketball court according to a preset coverage rule; collecting identity information of each member of the teams of the two parties of the game before the game is started to obtain personnel identity information; a look-up camera is adopted to judge out-of-bound persons, and a look-down camera is combined with figure postures and basketball tracking to scientifically judge out-of-bound persons. According to the method, the out-of-bound situation can be captured in real time through the picture of the upward-looking camera, and meanwhile, the out-of-bound situation can be captured more sensitively due to the fact that the out-of-bound position is closer and the judgment precision is high; the machine position advantage of the overlook angle can bypass shielding of the bottom line, the out-of-bound condition in the range of the bottom line is directly detected, and meanwhile the out-of-bound condition is judged by directly analyzing the last ball touch record.

The invention discloses an indoor and outdoor seamless data synchronization device and method, the device comprises a GNSS module, an inertial measurement module and a programmable control module, the GNSS module is used for receiving a 1PPS signal and GPRMC information generated by an external atomic clock; the inertial measurement module is used for performing fusion processing on the position information generated by the GNSS module to generate position, attitude and speed information; the programmable control module is connected with the GNSS module and the inertial measurement module through a serial port, and is used for receiving a 1PPS signal and GPRMC information of the GNSS module, aligning a square wave generated by a local clock with a square wave of the 1PPS signal of the GNSS module, performing frequency division on the square wave according to a preset frequency, continuously and stably outputting a pulse wave signal and time information of a corresponding frequency through the serial port, and transmitting the pulse wave signal and the time information to the inertial measurement module. Clock signals are calibrated through external calibration factors, an algorithm model is arranged in the programmable control module, and when indoor and outdoor data are synchronized, the algorithm model is called to carry out deviation calculation and smooth processing on signals needing to be aligned, so that the indoor and outdoor data are synchronized.

The invention discloses a water turbine vibration monitoring method based on an optical fiber sensing technology. The method comprises the following steps: 1, installing and fixing an optical cable; 2, starting the optical cable and the water turbine, generating a reflected light signal by an optical fiber sensor on the optical cable, and then obtaining a dominant frequency amplitude and vibration data; 3, performing high-pass filtering and noise reduction processing on the vibration data; fourthly, the power of the water turbine is inverted according to the main frequency amplitude, and then an alarm threshold value is adjusted in a self-adaptive mode according to the power; 5, when the vibration data of the optical fiber sensor exceeds an alarm threshold value, giving an alarm, recording the alarm duration, then analyzing the vibration data, and carrying out first-level alarm or second-level alarm; the optical fiber sensor is used for monitoring vibration, and the anti-electromagnetic interference performance of the optical fiber sensor is good, so that the vibration monitoring effect is good; and the alarm threshold value is adjusted in a self-adaptive manner, so that false alarm or missing alarm cannot occur, and the precision is relatively high. Therefore, according to the design, the vibration monitoring effect is good, and the monitoring precision is high.

The invention discloses a dual-redundancy safety protection elevator door motor device and a using method thereof, and relates to the technical field of elevator door motor devices.The dual-redundancy safety protection elevator door motor device comprises a supporting beam, a door body, two sets of rotating wheels, two sets of power guarantee assemblies, a connecting plate and a moving belt; a moving belt is installed on the outer wall of the rotating wheel, two sets of connecting plates are installed on the outer wall of the moving belt, and one end of each connecting plate extends to the outer wall of the supporting beam. A first clamping rod is stably moved out of a clamping groove by installing a second cylinder to move, at the moment, a first moving rod moves to drive a first motor to move horizontally, the first motor moves horizontally to enable the output end of the first motor to move out of a connecting sleeve, and at the moment, the output end of the first motor of the other power guarantee assembly moves into the connecting sleeve to be used alternately. When the elevator door motor device breaks down, standby power can be replaced in time, and the functions of dual-redundancy safety protection and use safety improvement are achieved.

This application provides a systematic treatment device for building waterproofing, relating to the field of building waterproofing. It includes: a support assembly and a treatment mechanism disposed on the support assembly for treating the wall. The support assembly includes: a base plate, support legs, an upper plate, a lower plate, a drive motor, a transmission belt, and two lead screws. The support legs are fixed to the base plate. One end of each lead screw is rotatably mounted on the base plate, and the other end passes through the upper and lower plates and is threadedly connected to them. The output shaft of the drive motor is coaxially fixed to either lead screw. The transmission belt drives the transmission between the two lead screws. This application has the effect of accurately identifying leakage points.

The application relates to the technical field of solid waste treatment, and discloses an intelligent control sorting system and sorting equipment for construction waste based on AI vision, which integrates material conveying, visual sensing, multi-stage driving sorting and a central main control module; a main controller constructs a window load entropy model based on visual data, reversely adjusts the frequency of a front-end vibrating material uniformizing device to realize full-line load balancing, and effectively prevents the phenomenon of overload congestion or idling of rear-end mechanical arms; a special electro-hydraulic mixed drive gripper is arranged at the sorting end, which can intelligently switch between servo electric power soft grabbing and hydraulic rigid heavy load locking modes according to the physical properties of materials; in addition, the system calculates visual touch feature residual errors by using physical feedback in the grabbing process, and iteratively corrects the weight parameters of the visual recognition algorithm online. The application effectively solves the problems that the traditional sorting line has large flux fluctuation and complex rigid and flexible materials are difficult to be considered, and significantly improves the overall sorting efficiency and purity of the system.

The present invention relates to a driving assistance system for a vehicle, and aims to improve the vehicle. The driving assistance system for a vehicle comprises: a photographing device capable of outputting a first photographed image of an occupant, an alarm unit capable of outputting an alarm to the occupant, and a control unit. The control unit functions as the following components: a facial recognition unit that performs recognition processing of at least a portion of the occupant's face on the first photographed image; an occupant determination unit that determines the driving state of the occupant based on a second photographed image in which at least a portion of the face can be recognized by the facial recognition unit in the first photographed image, and generates a first alarm request when the occupant is not in a drivable state; and a loss determination unit that generates a second alarm request when a plurality of third photographed images in which at least a portion of the face cannot be recognized by the facial recognition unit in the images that can be output by the photographing device are generated. The alarm unit outputs an alarm to the occupant based on the first alarm request and the second alarm request.

The invention discloses a power distribution cabinet operation state monitoring control system, particularly relates to the technical field of power distribution cabinets, and aims to perform time weighted integration on a current sequence by using an electric heating time constant and an equivalent heat capacity, construct a short-time impact sensitivity coefficient, and combine impact duration, a current duty ratio and a temperature rise gradient to obtain a short-time impact sensitivity coefficient. A load process is divided into a short-time impact stage and a continuous load stage, so that an acceptable short-time current impact which is large in amplitude but not accumulated in heat and a dangerous overload process which is not extremely high in amplitude but continuously high in temperature can be distinguished physically; an electric heating accumulation index is constructed through an electric heating segmentation feature set, and a material allowable temperature rise curve is introduced to form a safe electric heating boundary model, so that a monitoring system can recognize a danger approaching trend in advance from the perspective of a heat accumulation risk.

The invention relates to a smart city early warning system, which comprises an enabling control mechanism, a takeoff and landing video recording mechanism, a multiple optimization mechanism, a first analysis device, a second analysis device and an early warning execution device. According to the invention, misoperation of the early warning system in smart city management and energy consumption of the early warning system can be reduced as much as possible.

The invention relates to a high-precision sewage disposal judgment method and system, and the method comprises the steps: obtaining an average thickness value in a plurality of cross sections of a whole river channel, and carrying out the processing of the obtained average thickness value; performing curve fitting by taking the processed average thickness value as a vertical coordinate and the spacing distance of each cross section as a horizontal coordinate to obtain a sludge average thickness fitting curve; selecting a length value x according to the size of a required sludge judgment region, calculating an area value S under a fitting curve at a certain distance x by utilizing calculus, further obtaining the sludge volume of the length section x, and correcting V according to the position of the region needing to be judged; comparing the V value with preset alarm threshold values V low, V high and V risk; and selecting a desilting device and a desilting method corresponding to the V value according to the alarm grade. According to the method, the sludge volume is adopted to represent the sludge amount, judgment is more accurate, and the corrected volume value can better reflect the actual sludge amount; the labor cost is saved, and the judgment precision of the sludge amount is greatly improved.

The stock-in / stock-out management device (30) includes: an imaging section (31) that images a plurality of images of a state in which a door of a refrigerator (20) is opened from above the refrigerator (20), the refrigerator (20) having a main body and a door attached to the main body; a setting section (37) that sets a boundary line along outlines of the main body and the door in the plurality of images; and a determination section (38) that determines whether an object is put into the refrigerator (20) or the object is taken out from the refrigerator based on whether the object moves across the set boundary line in the plurality of images.

The present invention relates to a method and system for monitoring pyrenoid algae based on binocular images, and specifically to the field of biological monitoring. The method collects binocular image data with pyrenoid algae as monitoring targets in real time, establishes an adaptive background model to achieve dynamic adaptive following of monitoring targets, generates a disparity map and generates a depth map based on focal length and baseline distance, constructs three-dimensional information of the pyrenoid algae, extracts relevant features of the pyrenoid algae, constructs a deep learning model to perform probability distribution of the health status of the pyrenoid algae, constructs support vector regression to predict the growth rate of the pyrenoid algae, improves the judgment accuracy of the health status of the algae, uses a generative adversarial network to perform AI model training to generate the best pyrenoid algae image, uses Euclidean distance to calculate the similarity between the best pyrenoid algae image and binocular image data, and more clearly understands the matching degree between the generated image and the actual image.

The embodiment of the application provides a kind of based on multi-source data fusion's unmanned aerial vehicle flight compliance determination method and device, method includes: through protocol adaptation gateway access perception equipment, UOM platform, regulatory platform, operator platform etc. Multi-business platform data, after cleaning standardization, feature is extracted, adopts the combination strategy of core association key, multi-field intersection, feature similarity matching to establish multi-source data mapping, and generates comprehensive association dataset;Association dataset is input into multidimensional determination rule system, and according to the order of report, approval, registration, flight parameter, automatically check quantitative rules, accurately determine white flight or black flight and mark the type of violation;For black flight trigger, hierarchical early warning is pushed, and the application can improve the accuracy and efficiency of unmanned aerial vehicle determination.

The application discloses a traffic abnormal event detection method based on multi-source data fusion, comprising: a single millimeter wave radar and multiple industrial cameras, target detection data is acquired for sensor characteristics; fusion information is obtained by associating multi-source information; a fusion target is tracked, a target trajectory is formed, the trajectory is smoothed and filtered, and a filtered target trajectory is formed; illegal event detection is realized by analyzing the target trajectory, the illegal events include intrusion, overspeed, underspeed, lane changing, illegal parking, reverse driving and line pressing; traffic state event detection is realized by analyzing the correlation between a lane level detection area and target data, the traffic state events include congestion, and event evidence is left for aligned event time, including event video and event photo; event reexamination is carried out for specific events through target trajectory anti-shake verification, event qualitative analysis and reporting are carried out. The application can effectively realize intelligent prevention and control of traffic safety risks, optimize traffic efficiency and reduce the probability of traffic accidents.