45results about How to "Improve judgment accuracy" patented technology

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.

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 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 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.

The utility model relates to the technical field of automobile safety assistance, and discloses an automobile indirect visual field device which comprises an optical signal receiving device, a connecting pipe, a photosensitive element, an electronic display screen, a power supply device and a rearview mirror shell, the optical signal receiving device comprises a lens, the lens is arranged at one end of the connecting pipe, the connecting pipe is shaped like a Chinese character'yi ', and the photosensitive element is arranged on the connecting pipe. Two reflectors with opposite mirror surfaces are installed at the two corners in the connecting pipe, the other end of the connecting pipe is connected with the photosensitive element, the photosensitive element and the electronic display screen are connected with the power supply device through wires, and the rearview mirror shell comprises a shell body and a lens. The optical signal receiving device, the connecting pipe, the photosensitive element and the power supply device are sequentially installed in the rearview mirror shell, and a light hole is formed in the position, corresponding to the installation position of the lens, of the lens. The device can display the road condition in the view blind area for a driver in real time, and traffic accidents are avoided when the automobile changes lanes or turns.

This invention discloses a polarity testing method for metering devices suitable for high-noise environments, belonging to the field of metering device testing technology. The method includes: generating a square wave excitation signal with preset parameters based on algorithm control and applying it to the primary side of the metering device; acquiring the secondary side induced response signal, which is then synchronously transmitted after filtering, baseline drift correction, and amplitude scaling preprocessing; integrating the excitation and preprocessed signals, extracting phase difference, delay time, and amplitude characteristic parameters, and sequentially performing polarity, phase sequence, and on / off determination to obtain a preliminary comprehensive result; based on the preliminary result and characteristic parameters, outputting the determination result and confidence level through an improved CNN model, and obtaining the final polarity conclusion through weighted fusion; and visually outputting the final conclusion. This invention, through the collaborative design of precise excitation, anti-interference preprocessing, multi-dimensional preliminary determination, and AI-fused final determination, effectively suppresses noise interference, improves the accuracy and stability of polarity determination, and is suitable for high-noise scenarios such as industrial sites and substations.

The invention relates to the technical field of data processing, in particular to a multi-dimensional automobile accessory big data processing method and system based on a vertical class model, and the method comprises the steps: obtaining multi-dimensional data information of automobile accessories at regular time; according to key text information in the multi-dimensional data information, constructing a text feature vector of the automobile accessory; determining a first similarity between each attribute of each automobile accessory and the automobile accessory with the same name; obtaining the attribute importance degree of each attribute of each automobile accessory; based on a vertical class model, evaluating the similarity degree of the text feature vectors between any two automobile accessories obtained in a single time, and classifying the automobile accessories; and determining a first similarity between each attribute of any automobile accessory in the same kind of automobile accessories and the remaining automobile accessories, and calculating the automobile accessory similarity between the any automobile accessory and the remaining automobile accessories by combining the attribute importance of each attribute of the any automobile accessory so as to perform duplicate removal processing on the same kind of automobile accessories. Therefore, the duplicate removal effect of the automobile accessory data is improved.

The application provides a two-stage fusion based on sound and vibration signals for a milling cutter wear state classification method of a disc type milling cutter of a gear milling machine, relates to the fields of multi-source information fusion and fault diagnosis, and mainly comprises the following steps: 1) four noise sensors are used to collect noise signals in four directions, and the correlation degrees of the noise signals in different directions are obtained through a gray B-type correlation degree method, so that the sound signals after fusion are obtained through data stage fusion; 2) the vibration signals of the main shaft of the gear milling machine are collected, and the collected vibration signals and the fused sound signals are preprocessed and subjected to time-frequency feature extraction; a Relieff-mRMR joint algorithm is used to optimize the extracted characteristic values, and the characteristic values with greater influence are selected to construct a data set; 3) a BiLSTM is used to extract the features of the data set, and then an XGBoost is used to classify the extracted characteristic vectors, so that the classification results of different wear states of the disc type milling cutter are obtained. The two-stage fusion method is used to fuse the sound and vibration signals, so that the characteristics of tool wear can be more effectively captured, and the wear state of the disc type milling cutter of the gear milling machine can be judged.

This disclosure relates to a full-process processing method for fiber optic composite ground wires, including: a design stage where a design database is established, the structure and processing technology of the fiber optic composite ground wire are determined based on the database, and auxiliary optimization design is performed; a manufacturing stage where multiple attribute parameters of the fiber optic composite ground wire are monitored to improve quality; an operation stage where the fiber optic composite ground wire is monitored under extreme low-temperature conditions to obtain initial data; the original health indicators are input into a pre-trained health and status recognition model to obtain the status recognition results of the fiber optic composite ground wire; and an early warning is issued based on the status recognition results. The technical solution of this application improves design quality, provides early warning during the operation stage, and is beneficial for extending the lifespan of the fiber optic composite ground wire.

The application relates to an express package safety management system and method based on artificial intelligence technology, the system comprising a data acquisition layer, an intelligent analysis layer, a decision execution layer and a counter-feeding optimization layer; the data acquisition layer collects multi-source heterogeneous data of a to-be-identified package and binds the data into associated data; the intelligent analysis layer comprises at least two risk research and judgment modules arranged in parallel, each module taking different dimension data as input and output to correspond to a risk research and judgment result; the decision execution layer executes comprehensive decision on the risk research and judgment results and issues a hierarchical disposal instruction; the counter-feeding optimization layer returns the disposal result and the identification process data to a sample library to iteratively update the risk research and judgment module. The application has the advantages that multi-dimensional risk identification is mutually verified, disposal decision is hierarchical and unified, and the model can evolve with new risks.

The application provides a fake news detection method and related equipment, and belongs to the technical field of natural language processing and information authenticity detection. The method comprises the following steps: preprocessing and segmenting an original input text to obtain a sentence set and score a candidate claim set obtained; converting the sentence into a single sentence declarative expression to obtain a normalized claim, and structurally constructing the normalized claim; simultaneously performing information retrieval according to the structural construction mode to obtain a candidate evidence, performing multidimensional consistency verification on the structured claim and the candidate evidence, and scoring to obtain a total verification score; and correcting the total verification score by using the matching degree of a news site and an IP address, and outputting a verification result. The application prepositions noise processing and fact positioning, adopts a structured claim for fine-grained verification, and corrects through cross-information source matching of an IP address and a news site, so that the accuracy, interpretability and identification ability for numerical / time tampering of fake news detection are improved.

The present application provides a kind of based on conveyer belt type AI vision's shatian pear online sorting device, its structure includes: vertical column, shock-absorbing base, conveying end, substandard product collection box, good product collection structure, AI vision identification structure, mechanical arm sorter, vertical column is set to the outer edge of shock-absorbing base determines the position of conveying end and AI vision identification structure, mechanical arm sorter, conveying end one end is connected with good product collection structure;The present application is based on the ladder formed by the guide plate and the buffer plate provided by good product collection structure, combined with the further buffering of the rubber material of buffer plate and spliced deceleration block can effectively reduce the output speed of shatian pear and the distance with good product collection box, avoid the secondary damage caused by direct impact drop, combined with the cooperation of edge plate one and edge plate two can cover the edge position, prevent derailment, so as to improve the output safety protection effect and output accuracy of sorting device to shatian pear.

This invention relates to the field of electronic digital data processing and discloses a method for generating computable task semantics from SOP text for flight training. The method includes: parsing the original script to extract key elements and constructing task nodes containing target states, parameter tolerance ranges, and behavioral rules; establishing directed dependencies between nodes to generate a task semantic graph; calculating a semantic execution score factor representing the degree of convergence of the operational intent towards the target state based on the evolution trend of the controlled entity feature state vector within a preset time window; and using the numerical evolution characteristics of the score factor satisfying the convergence criterion as the basis for triggering topological migration of the task semantic graph. This invention replaces instantaneous threshold comparison with temporal residual evolution judgment, eliminating the spatiotemporal mismatch between discrete semantic commands and continuous telemetry data streams, and improving the system's fault tolerance for non-standard phase operation recognition.

When the main power source (7) is abnormal, the in-vehicle capacitor device (18) outputs the power of the capacitor (19) as a backup power source for the main power source (7). The capacitance calculation unit (26) calculates or acquires a current flowing through the capacitor (19) during the charging period and a voltage change amount of the capacitor (19) generated during the sampling period of the current, and calculates the capacitance of the capacitor (19) on the basis of the current and the voltage change amount. The deterioration determination unit (28) determines the deterioration of the capacitor (19) on the basis of the capacitance calculated by the capacitance calculation unit (26). The deterioration determination unit (28) performs deterioration determination using a calculation result of the capacitance calculation unit (26) that satisfies a condition that the amount of change in voltage is equal to or greater than a threshold value.

The application discloses a fire-fighting hidden danger identification record method based on artificial intelligence, and relates to the technical field of fire-fighting hidden danger identification.The method comprises the following steps: based on artificial intelligence, uniform dimension feature vectors are extracted from continuously acquired fire-fighting hidden danger identification data and unique identification codes are given, forming a cross-sequence consistent identification vector group; meanwhile, the overlapping relationship of the corresponding space region is continuously mapped, generating a space evolution track group; the cross-sequence consistent identification vector group and the space evolution track group are compared synchronously, the coupling relationship between the feature consistency maintenance degree and the space overlapping change trend is calculated, and it is judged whether the feature expression is consistent and the space overlapping relationship gradually changes or not.The application solves the problem that the same fire-fighting hidden danger is split and recorded under the condition that the features are consistent but the space gradually deviates, realizes the continuous association and dynamic regulation of the hidden danger identification result, and thus improves the completeness and accuracy of the identification record.

The invention relates to the field of image recognition, in particular to an image segmentation microstructure recognition method based on a convolutional neural network model, and the method comprises the steps: carrying out the sampling of a turbine blade, obtaining a plurality of samples, and carrying out the image collection of each sample after material processing, so as to obtain a plurality of target images; performing noise processing on each target image, determining an image feature state according to a contrast uniformity value and a local difference value of each target image after noise processing, and determining a final binarization threshold corresponding to each target image according to a pixel gray value corresponding to an inter-class variance or a sub-region based on the image feature state; performing threshold segmentation marking on the target image after binarization processing to obtain a label image; the ResUnet model is trained through the training data set; according to the invention, adaptive adjustment is carried out on sample processing and model training according to the actual collection condition of the collected sample, and the model training effect is improved.

The invention discloses an instability test classification detection method based on hierarchical perception, which comprises the following steps of: based on artificial code analysis, acquiring a plurality of test code data with instability; preprocessing the test code data; an instability test classification detection model is constructed and trained, wherein the instability test classification detection model comprises a UniXcoder model used for extracting code semantic feature pre-training, a structure encoder used for extracting hierarchical structure features and a classification model used for classification; and predicting new code data by using the trained instability test classification detection model, outputting a prediction result of the stability of the code data, and if a predicted label is unstable, outputting a hierarchical root cause causing the instability test at the same time.

The application discloses an ECU offline test method, system, medium and electronic equipment, comprising: obtaining configuration parameters, establishing an offline test project based on the configuration parameters; generating a corresponding offline test file based on the test case, calling the offline test file to perform offline test on the ECU; identifying whether the ECU meets the offline requirements, recording the corresponding test state, and generating a corresponding test report; offline detection of the ECU under different power supply conditions, realizing full-process automatic test of power supply control, offline test, data acquisition, compliance determination and report archiving, improving the offline detection efficiency, determination accuracy and standardization level of the ECU, and meeting the operation requirements of various vehicle-mounted ECU offline tests.

This invention discloses a method for detecting the quality of power pole splices based on the back-transmission ratio of elastic wave signals, belonging to the technical field of power facility safety evaluation. The method includes: applying vibration to the pole and acquiring the elastic wave response signal; extracting the reflection amplitude A at the splice. b And the amplitude of the reflection from the top of the pole A t This invention introduces a distance attenuation coefficient κ to construct a back-transmission ratio ζ that eliminates the influence of excitation force. Based on the elastic wave multilayer medium propagation model, a nonlinear mapping relationship between the impedance ratio η of the joint and the rod and ζ is established, and η is obtained by solving the problem. The tightness of the joint is evaluated based on the value of η; the closer η is to 1, the tighter the connection. This invention eliminates the influence of impact force by introducing a back-transmission ratio ζ and compensates for the difference in propagation distance by using an attenuation coefficient κ, thus achieving quantitative and robust detection of the joint quality and overcoming the shortcomings of traditional methods that rely on the absolute amplitude of the signal and are easily affected by medium attenuation.

The invention relates to the technical field of electrical digital data processing, and discloses a digital evaluation system for operating parameters of a remote power supply in a marine environment, which comprises an operating data access module, a data logic mapping module, a feature logic recovery module and an operating state evaluation module, the data logic mapping module maps the original electric signal sequence into a data flow pattern with plastic fluid characteristics, and establishes a logic mapping model containing virtual roll gap parameters according to logic mapping pressure caused by external environment parameters; according to the method, deep decoupling of environmental strain interference and intrinsic electrical characteristics of a power supply is realized, data space warping is effectively eliminated, the reliability of the power supply is improved, the reliability of the power supply is improved, and the reliability of the power supply is improved. And it is ensured that the operation characteristics maintain topological consistency in a multi-parameter coupling fluctuation environment.

The invention discloses a monitoring device and method for electrical fire early warning. The monitoring device comprises a monitoring analysis platform, a data storage module, an early warning monitoring module, a data collection module and a fire early warning processing module. The data storage module is used for storing the historically collected data; the data collection module is used for collecting current, voltage, temperature and humidity data in real time, analyzing the data through the monitoring analysis platform and uploading the data to the data storage module; comprising a temperature and humidity sensor and a current and voltage acquisition module and is used for acquiring current and voltage data of electrical internal equipment, and current and voltage abnormity is compared with acquired temperature and humidity data and internal and external graphs of the electrical equipment; and if only the current and the voltage are abnormal, the fire hazard early warning processing module is linked to contact an equipment management unit and arrange troubleshooting. The invention relates to the technical field of fire early warning, and particularly provides a monitoring device and method for electrical fire early warning.

The application discloses a kind of based on Beidou double-channel double power supply radar water level gauge device and system, specifically related to telemetry water level monitoring and Beidou communication technical field, including the water level value of each sampling time, main power output value and backup power output value, water level value is formed water level sequence according to sampling in succession, and when main power output is invalid and backup power output is effective, power supply path is switched to backup power, and the sampling record with sampling time and power supply source mark is output;By executing power supply switching mark, water level continuous connection arrangement, double-channel division work sending and process boundary interpretation restoration to sampling record, make first Beidou channel send water level main chain, second Beidou channel synchronously send power supply switching bit and the boundary information corresponding to unconfirmed section.

The invention discloses a susceptibility judgment method suitable for gully-type debris flow, and belongs to the technical field of debris flow prevention and control engineering, and the method comprises the following steps: 1, determining the basic parameters of gully-type debris flow through a topographic map, including the debris flow basin area A and the debris flow gully bed longitudinal gradient J; 2, conducting field investigation or looking up geological map data, obtaining lithology types of the gully-type debris flow development area, and classifying the lithology types; 3, calculating a susceptibility judgment index T of gully-type debris flow; and 4, judging the susceptibility of gully-type debris flow with different lithology according to the susceptibility judgment index T of the gully-type debris flow. According to the method, the judgment index of the gully-type debris flow susceptibility can be accurately given, the judgment precision of the gully-type debris flow susceptibility is greatly improved, and the applicability is enhanced.

The application relates to a battery preparation method. The method comprises the following steps: a battery preparation method, comprising the following steps: obtaining a winding battery cell to be processed; performing heat pressing treatment on the winding battery cell to be processed, and detecting whether the surface hardness of the winding battery cell after heat pressing reaches a preset hardness range; packaging the winding battery cell with the surface hardness reaching the preset hardness range into a shell as a target battery cell; and rejecting the winding battery cell with the surface hardness out of the preset hardness range. The scheme provided by the application can detect whether the surface hardness of the winding battery cell after heat pressing reaches the preset hardness range, package the winding battery cell with the surface hardness reaching the preset hardness range into the shell, reject the winding battery cell with the surface hardness not reaching the preset hardness range, effectively reduce the winding battery cell with excessive heat pressing entering the packaging-into-shell process, effectively improve the production quality of the battery, effectively improve the yield of the winding battery cell packaging into the shell, and thus improve the production efficiency of the battery.

The invention discloses an electromagnetic environment abnormity identification system and method based on an unmanned aerial vehicle, and the method comprises the steps: obtaining a to-be-monitored area, dividing the to-be-monitored area into space grid units, planning an identification path based on the space grid units, setting a monitoring task frequency band comprising a plurality of sub-frequency bands, and distributing the sub-frequency bands to different space grid units; the unmanned aerial vehicle flies along an identification path, and collects low-resolution spectrum data and high-resolution spectrum data of corresponding sub-bands in each space grid unit; the method comprises the following steps: aligning, grouping and splicing high-resolution frequency spectrum data, and performing frequency spectrum interpolation estimation by combining low-resolution frequency spectrum data to generate a frequency spectrum distribution model; according to the method, a spectrum body model is constructed according to a spectrum distribution model, and the electromagnetic environment abnormity is identified based on the intensity difference of a main unit and an adjacent subunit at the same frequency position. According to the invention, high-efficiency and accurate electromagnetic environment abnormity identification can be realized under limited flight conditions.

The present application relates to the field of petrochemical industry and environmental protection technology, and particularly relates to a multi-core pipe parallel type main and auxiliary cavity cyclone oil-gas-water separation system and a separation method. The method comprises obtaining the time of flight of reflected sound waves and the Doppler power spectral density diagram of the cyclone separation main cavity; determining the axial coordinate sequence and the radial coordinate sequence based on the time of flight; determining whether the cyclone intensity of the cyclone separation main cavity is qualified based on the height difference of the cyclone liquid column; in response to the unqualified cyclone intensity, determining the adjustment direction of the gas phase outlet back pressure based on the cyclone gas core ratio; based on the qualified cyclone intensity, determining whether the cyclone load of the cyclone separation auxiliary cavity is up to standard based on the frequency spectrum width value, and in response to the unqualified cyclone load, prolonging the liquid phase separation time of the cyclone separation main cavity; based on the qualified cyclone load, determining whether there is a downward trend of the oil-gas-water separation efficiency, and enabling sound early warning when the oil-gas-water separation efficiency has a downward trend. The present application solves the problem of lag in sensing the state fluctuation of the oil-gas-water mixed liquid flow field.