35results about How to "Improve judgment accuracy" patented technology

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 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.

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.

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 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 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.

This invention relates to the field of coal mine gas geological disaster prevention and intelligent identification technology, and discloses a method and system for intelligent identification and graded early warning of underground gas geological anomalies in coal mines. The method includes: S1, collecting multi-source heterogeneous monitoring data in the target area of ​​the coal mine and performing standardization processing and spatiotemporal benchmark unification; S2, constructing a multi-dimensional feature fingerprint database based on historical or accumulated standardized datasets; S3, acquiring real-time multi-source monitoring data for the current tunneling or exploration process and extracting its features; based on the multi-dimensional feature fingerprint database, using evidence theory to fuse and calculate multiple extracted real-time feature evidences to obtain a comprehensive confidence assessment result for the existence of a specific type of gas geological anomaly in the undiscovered area ahead; S4, generating graded early warning information based on the comprehensive confidence assessment result and a preset risk level threshold. This invention achieves advanced identification, risk assessment, and targeted early warning of geological disasters such as underground gas outbursts.

The present invention relates to an error determination apparatus, an error determination method, and a recording medium. An error determination apparatus (10) for determining a measurement error occurring when a workpiece is measured by a coordinate measuring machine includes: an information acquisition section (121) for acquiring motion error information indicating a measurement result of a motion error of the coordinate measuring machine and design information of the workpiece; a measurement position designation section (122) for designating a measurement position on the workpiece based on the design information; an error determination section (123) for determining a measurement error occurring in measurement at the measurement position due to the motion error based on the motion error information; and an output section (125) for outputting the measurement error determined by the error determination section (123).

The application discloses a method and device for mining data relationship of a point of interest, an equipment and a medium, and relates to the technical field of geographic information. The method comprises the following steps: acquiring position information of a point of interest; determining a road loop matched with the point of interest based on the position information; the road loop is a closed loop surrounded by external roads in road network data, and there is no road chain in the internal part of the road loop to divide the road loop into two parts; the road chain is composed of one external road or connected by two or more external roads; the external road is a road located outside the point of interest; determining a search range of the point of interest based on the road loop; and mining data relationship of the point of interest based on the search range. The application has high efficiency and recall rate when performing data mining on the point of interest.

The application is suitable for the technical field of underwater robot path planning and intelligent obstacle avoidance control, and provides a robot-specific efficient path planning and obstacle avoidance optimization method and system.The method comprises the following steps: when it is determined that the angle deviation prediction of the target robot to the narrow area to be passed is less than the upper limit value of the angle deviation, the current environment and the traffic environment dynamic influence parameters of the narrow area to be passed are acquired, and a historical cleaning operation database is called.The application realizes the dynamic perception and adjustment of the underwater robot to the slight performance difference and the environmental disturbance influence in the process of rapidly passing through the narrow area for the first time by constructing an angle deviation prediction correction mechanism based on the response lag characteristics of the propulsion motor.

The invention relates to the technical field of audio processing, in particular to an audio buffer area management method and system based on data volume self-adaption, and the method comprises the steps: determining a processing strategy according to the data volume of an audio buffer area, the processing strategy comprises the steps of directly executing data removal processing, judging whether to execute the data removal processing or not based on the fragment difference characterization value and not needing to execute the data removal processing; in the data removal processing, the removal data volume is determined based on the comprehensive evaluation value, and whether reduction adjustment is carried out on the removal data volume based on the key audio frame proportion is determined based on the removal influence coefficient; and determining a data removal strategy as a direct deletion strategy or an exchange strategy according to the residual data volume and the key frame data volume. The real-time processing capability of the system can be improved.

The invention discloses a method and a system for improving lottery sales rewarding safety based on encryption processing, and relates to the technical field of bill verification. The method comprises the following steps: based on a lottery sale terminal, obtaining a transaction timestamp of current lottery purchase, a sale terminal mark, a position code identifier and lottery type information, encoding parameters, performing encryption processing, constructing a unique dynamic encryption identifier of a lottery, and obtaining encrypted bill information. According to the method, the corresponding dynamic encryption identifier is created for each transaction by using the transaction timestamp, the point-of-sale terminal identifier and the position code identifier, so that the anti-counterfeiting capability of the bill is improved, and the judgment accuracy of the authenticity of the lottery ticket is improved by comparing the pre-stored information stored in the database with the data collected by the prize claiming terminal in the prize claiming stage; in combination with a biological recognition technology, the consistency of a prize claiming person and a ticket buyer is ensured, and the occurrence of manipulation and fraud behaviors is prevented through continuous tracking and deviation analysis of the prize winning probability of the user.

The application discloses a kind of transmission tower inclination monitoring method and system based on image analysis, belong to based on image processing monitoring technical field, specifically including monitoring platform, image acquisition unit, feature information identification unit, inclination risk determination unit, risk grade division signal and early warning unit;It is based on visual collection tower object image, calibrate multiple rigid feature points on the collected image, and establish background reference system based on absolute static background anchoring, monitor the displacement vector of multiple rigid feature points, eliminate the error brought by the influence of perspective deviation through static absolute reference system, and cross validation is carried out in combination with the same direction displacement of multiple points, to improve the determination accuracy of whether transmission tower exists inclination risk, when determining that transmission tower exists inclination risk, obtain tower inclination angle according to feature point displacement vector calculation, generate risk signal at all levels according to inclination angle change trend and carry out targeted and efficient early warning.

This invention relates to the field of sleep monitoring technology for the elderly, specifically an intelligent sleep monitoring system for the elderly. The sleep monitoring belt is responsible for the precise acquisition of physiological signals, while the millimeter-wave radar is responsible for positioning the entire bed. The two systems complement each other for calibration, significantly improving the accuracy of lying position determination and avoiding the problems of inaccurate positioning and inability to determine sleeping posture associated with traditional single monitoring devices. Furthermore, the monitoring belt and millimeter-wave radar collect data synchronously, allowing for the fusion and analysis of location data, physiological parameters, and body movement trajectories. Compared to single devices, this enables the identification of more complex combinations of sleep states, improving health early warning capabilities. The threshold of the millimeter-wave radar is optimized by combining the body movement and heart rate signals from the sleep monitoring belt, reducing the false negative rate of the millimeter-wave radar for weak breathing and body movement in the elderly, making it particularly suitable for the elderly population who are very old, have weak breathing, and exhibit little body movement. Moreover, the millimeter-wave radar's data is converted into rectangular coordinates on the bed surface, which, combined with the pressure distribution of the monitoring belt, makes the determination of the lying area more accurate.