191results about How to "Fast judgment" patented technology

The invention discloses a fault positioning method for a power distribution network by combining simulation calculation and real-time monitoring, and belongs to the technical field of fault detection of the power distribution network. The method comprises the following steps of: extracting information of a target power distribution network from the conventional power distribution network geographic information system and a power distribution network energy management system through an organizational data analysis interface to automatically generate a real-time simulation calculation model of the target network; putting forward a virtual node-based fault positioning algorithm according to the simulation calculation model so as to solve functional relation between voltage amplitude of any node and a fault position parameter when a symmetric and asymmetric fault occurs at any point in the target network; and finally calculating an accurate position of the actual fault of the power distribution network by using a small amount of real-time data of voltage drop amplitude in a fault process. By using the fault positioning method for the power distribution network by combining the simulation calculation and the real-time monitoring, the state and the parameter of the network are accurately and effectively reflected when the fault occurs, the accuracy of the fault positioning is improved, and the method is suitable for various network structures and fault types.

The invention provides a method for judging phishing websites based on non-content analysis, which comprises a server side and a client side, wherein the server side is provided with a black list, a white list, a high-risk domain database and a rule base. The method includes: using the server side to receive URL (uniform resource locator) data of unknown websites transmitted by the client side, judging the black list and the white list, comparing the URL data with data in the high-risk domain database if the URL data are not included in the black list and the white list, comparing the URL data with data in the rule base if the URL data are consistent with the data in the high-risk domain database, judging based on the high-risk domain database, the rule base and key information, and finally returning results to the client side. By the aid of the phishing website judging method, phishing website judging speed can be greatly increased, the shortcoming that an existing URL judging method fails for phishing websites emerging for the first time can be overcome, and the method has the advantages of convenience, rapidness, high efficiency and wide applicability.

The invention discloses a method and a system for preventing collision of a robot based on a current method. The method comprises the following steps: acquiring the working current value of a drivingmotor, and comparing the working current value with a corresponding standard current value-position curve, thus obtaining a comparison result of each current; judging whether each part of the robot isin collision or not according to the comparison result of each current. The system comprises a current module, a comparison module and a judgment module, wherein the current module is used for acquiring the working current value of the driving motor; the comparison module is used for comparing the working current value with the standard current value; the judgment module is used for judging whether the robot is in fault or not. According to the method and the system, disclosed by the invention, whether corresponding parts of the robot are in collision or not can be quickly judged through acquiring the working current value of the driving motor, and measures can be taken in time once the robot is in collision, so that automatic monitoring on the robot can be realized, and the safety of life and property can be ensured; the method and the system can be widely applied to the technical field of robots.

The invention discloses an early warning method and an early warning system of subway signal faults and relate to rail transit technical field. The early warning method comprises: S1: acquiring the operating state parameters of various devices of a current subway line in real time; and S2: determining whether the various devices of the subway line are normal according to the operating state parameters, and if not, generating alarm information and analyzing the same in order to generate fault information corresponding to a fault. The early warning method and the early warning system acquire the operating state parameters of various devices of the current subway line and perform determination according to the operating state parameters so as to achieve automatic fault detection and increase fault determining efficiency, and may inquire a processing prepared plan database in order to obtain a processing prepared plan corresponding to the fault information, thereby increasing fault determining speed. The early warning system may immediately publish urban rail transit signal fault information and trip references to Internet such that passengers may automatically obtain the fault information and transfer suggestion with a mobile terminal connected with Internet.

The invention discloses a system and a method for controlling a 3D model based on a gesture, and belongs to the field of 3D model control. The system for controlling the 3D model based on the gesture comprises a screen event capturer for capturing a finger event on a touch screen in real time, a gesture processor for calculating a change vector according to coordinates obtained from the screen event capturer, a 3D model renderer for controlling display of the 3D model on the screen according to the change vector, and a control instruction mapper for recording a 3D model control instruction corresponding to the gesture. The screen event capturer transmits captured finger information to the gesture processor; the gesture controller transmits the calculated change vector to the 3D model renderer; the 3D model renderer controls the display on the screen; and corresponding operation steps are correspondingly performed, so that the problems that a 3D model operation engine, for the touch screen, mentioned in the prior art is realized at most through two fingers, only supports two operations and cannot support three common operations of translation, rotation and zooming at the same time are solved.

The embodiment of the invention provides an original document determining method and device, an electronic device, and a storage medium. The method includes: receiving a to-be-processed document and calculating the simhash signature of the to-be-processed document by using a simhash algorithm; obtaining the simhash signature of a first original document from a preset original document library, calculating the similarity between the to-be-processed document and the first original document, obtaining, when the similarity between the to-be-processed document and the first original document is greater than a first preset threshold, the first original document and comparing the full text of the first original document with that of the to-be-processed document; obtaining the same content in thefirst original document and the to-be-processed document, calculating the proportion of the same content in the first original document; and marking the to-be-processed document as a non-original document when the proportion of the same content in the first original document is greater than or equal to a second preset threshold, or marking the to-be-processed document as an original document whenthe proportion of the same content in the first original document is less than the second preset threshold. The original document determining method and device can improve the accuracy of determiningthe original document.

The invention discloses a subway group abnormal behavior detection method based on station two-dimensional crowd density analysis. The method comprises the following steps: firstly, preprocessing original video data; then, using a full convolution U-Net neural network to extract target features; tracking the target feature points by using a pyramid Lucas-Kanade optical flow method and converting the target feature points into a station two-dimensional space coordinate system; and finally, training and learning the extracted group motion feature information by using a support vector machine anda random forest to complete the detection of group abnormal behaviors. The detection method provided by the invention improves the abnormal detection speed and recognition rate, ensures the applicability in different scenes, and reduces the false detection rate and omission ratio of group abnormal behavior recognition.

The invention relates to a control method for achieving cutting tool radius compensation overall interference in a numerical control system and belongs to the technical field of data system control methods. The method comprises the steps of arranging end points of line segments formed by original workpiece paths and cutting tool outer side paths in sequence, and storing the end points into event queues in sequence; judging whether event points exist in the event queues or not, if so, utilizing a scanning line to order the event points and updating state queues; and reporting that overall interference exists if intersection points of line segments in the state queues are intersection points of the line segments formed by the original workpiece paths and the cutting tool outer side paths. The method perform quick overall interference judgment based on the scanning line, operation tine is only related to the number of the intersection points of the line segments, judging speed is high, and accuracy is high. In addition, over cutting possibility can be warned in real time, the control method is suitable for complicated workpiece processing, and is simple and convenient in achieving mode and low in achieving cost.

The invention belongs to a method of judging whether a point is in a polygon, pertaining to a computer graphic and computer geometry technical field. The invention first convexly decomposes a polygon and builds a binary tree to manage these convex polygons; then the invention investigates the built binary tree according to the coordinate position of the tested point to find the convex polygon to which a leaf node of the binary tree corresponds; finally the invention tests whether the point is in the convex polygon or not, thus judging whether the tested point is in the given polygon or not. The invention has the advantages that the calculating speed is high and the storage space is saved compared with other similar methods based on polygon convex decomposition. The invention is applied to the condition that a plurality of points are judged whether in the same polygon.

The invention relates to a public scene intelligent video monitoring method based on vision saliency and depth self-coding. The method includes performing single-frame decomposition on a video, using visual saliency to extract motion information, then calculating optical flow of a moving object in adjacent frames, dividing a later detection process into a training process and a testing process, during training, using optical flow of a training sample as input of self-coding, training a whole self-coding network through minimization of a loss function, in the test stage, using optical flow of the training sample and a test sample as input, extracting a coder in the trained self-coding network, extracting features of the input through dimensionality reduction, then visualizing a result after dimensionality reduction, utilizing a suprasphere to represent a visual range of the training sample, when the test sample is input, utilizing the same method to realize visualization, and if a sample visualization result falls in a suprasphere range, judging the sample to be normal; and otherwise, if the sample visualization result falls beyond the suprasphere range, judging the sample to be abnormal, thereby realizing intelligent monitoring of the video.

The present invention provides a photovoltaic output power self-adjusting device. The device comprises a solar cell panel rotating module, a sun monitoring module, a wind power and wind direction monitoring module, a control module and a power storage module. The solar cell panel rotating module is fixed on the ground. The sun monitoring module and the wind power and wind direction monitoring module are respectively fixed on a platform higher than the horizontal placement position of a solar cell panel. The control module is respectively connected with the solar cell panel rotating module, the sun monitoring module and the wind power and wind direction monitoring module. The power storage module is respectively connected with the solar cell panel rotating module, the sun monitoring module, the wind power and wind direction monitoring module and the control module. The photovoltaic output power self-adjusting device improves the efficiency, the accuracy and the safety of related equipment itself. Meanwhile, the solar cell panel is always in an optimal working state.

The invention relates to a direct-detection type intelligent direct-current system insulation and state diagnosis instrument comprising a diagnosis host machine which mainly comprises a signal generator, a power amplifier, a signal injector, a signal receiver, a signal amplifier, an A/D (Analog to Digital) conversion module, a singlechip system and an alarm, and a handheld split core type currenttransformer. The total insulation state of a major loop is detected by using an alternating-current injection detection mode, whereas which branch generates insulation reduction on earth is detected by using the direct-current transformer. When multiple branches are grounded at the same time, the grounded branches can be detected at the same time, and the diagnosis precision is high. Meanwhile, the detection method is implemented by using a singlechip. Compared with a balanced bridge method and an alternating current injection method in the prior art, the invention adopts a microcomputer technology and has the characteristics of high integrated level, high judgment speed, high detection sensitivity, convenience in operation, strong anti-jamming capability, accuracy in fault location and the like.

The invention relates to a coronary vessel segmentation method based on an attention mechanism and a full convolutional neural network. The segmentation method comprises the following steps of 1, obtaining the input data for neural network training; 2, training a three-dimensional full convolutional network model integrated with the attention mechanism by utilizing the input data; 3, performing the coronary vessel preliminary prediction segmentation on an actual patient image by using the trained three-dimensional full convolutional network model; and 4, performing iterative optimization on the preliminary prediction segmentation result through a traditional algorithm, and obtaining a final coronary vessel segmentation result. Compared with the prior art, the method has the advantages of good segmentation result definition, high accuracy and the like.

The invention provides a car door opening safety assisting device and method and belongs to the technical field of cars. The problems that operability of car door opening safety protection is too low and safety is not high in the prior art are solved. The car door opening safety assisting device comprises a car body controller, an ignition switch, a car speed sensor, a door lock switch, a door lock motor, a left radar sensor and a right radar sensor. The car speed sensor, the ignition switch, the left radar sensor, the right radar sensor and the door lock switch are connected with the input end of the car body controller. The door lock motor is connected with the output end of the car body controller. The method comprises the steps that A, whether a car is not stopped after being automatically locked or not is judged; B, whether objects approach to the rear portions of the left side and the right side of the car or not is judged; C, corresponding actions are conducted when the objects approach to the rear portions of the left side and the right side of the car; and D, corresponding actions are conducted when no object approaches to the rear portions of the left side and the right side of the car. The car door opening safety assisting device and method can improve the operability of car door opening safety protection and the safety when passengers open car doors and get off a car.

The invention relates to a device and method for judging near field distance, which are used for judging near field distance of a UHF (Ultra-High Frequency) signal source. According to the invention, a signal emitted from the UHF signal source is received through a UHF antenna array unit, the received signal is subjected to phase difference detection through a phase difference detection unit and then converted to phase information which is recognizable to a distance judgment algorithm operational unit, and the distance judgment algorithm operational unit is used for calculating the received phase information to obtain the distance between the signal source and the UHF antenna array unit, wherein the UHF antenna array unit consists of at least 3 groups of antenna pairs which are distributed regularly in the case of meeting certain conditions, thereby the calculation of the distance judgment algorithm operational unit is greatly simplified.

The invention discloses a signalized intersection non-motor vehicle illegal cross-street behavior automatic judging method which comprises the following steps: (1) two cameras are set up in a pedestrian crossing and near range of the pedestrian crossing, relative parameters are arranged according to recorded videos; (2) a signalized intersection non-motor vehicle illegal cross-street behavior binary logit prediction model is built according to discrete choice analysis method, standardization is conducted to the binary logit prediction model by adopting a parameter progressive method, the result is marked; and (3) the parameter data are inputted in the binary logit prediction model and therefore signalized intersection non-motor vehicle illegal cross-street behaviors are obtained, when P is larger than 0.5, a non-motor crosses the street illegally; when P is smaller than 0.5, the non-motor does not cross the street illegally. The signalized intersection non-motor vehicle illegal cross-street behavior automatic judging method reduces artificial participation, improves judging speed, and enables the judging to be correct and fair, and meanwhile, provides theoretical foundation for intersection transformation through the factors which obviously influence signalized non-motor vehicle illegal cross-street behavior, and has practical engineering applying value.

The invention provides a vehicle steering judgment method based on image ambiguity comparison. The method includes the steps of collecting driving images of a vehicle at all moments in real time through a camera shooting device, receiving the driving images and dividing the driving images into a plurality of sub-images, extracting the sub-images sensitive to gray level and color gradation changes to form ROI areas, symmetrically dividing each ROI area into a left area and a right area, calculating the image ambiguity degree of each area, counting the difference values between the image ambiguity degrees of the left areas and the right areas of the ROI areas composed of 300 or more driving images corresponding to different speeds, calculating mean values and variances of all the difference values at the corresponding speeds, and judging whether the vehicle is in the turning state or not and judging the steering direction of the vehicle according to the difference value between the image ambiguity degrees of the left area and the right area of the corresponding ROI area at the current speed of the vehicle. The method is small in calculation amount, the turning state of the vehicle can be rapidly judged in real time without being limited by day or night conditions, and the method is particularly suitable for back-mounted portable navigation products.

The invention particularly relates to an event-driven intelligent processing method for automatic driving accidents. The event-driven intelligent processing method for automatic driving accidents comprises the following steps: establishing an automatic driving accident type and an accident symptom correlation model according to the characteristics of automatic driving accidents collected by a vehicle sensing module and a vehicle computing module; timely monitoring the problems that will occur in the automatic driving process, sending intelligent early warning information, and making corresponding policy adjustments; storing the causes and countermeasures of failures into cloud computing nodes for analysis to form accident analysis reports and processing strategies, thereby completing intelligent analysis of automatic driving accidents. The event-driven intelligent processing method for automatic driving accidents, combining fog computing nodes and cloud computing nodes, has rapid judgment speed, high efficiency, clear accident reasoning process and reasoning judgment and superior overall performance, and can monitor the problems that will occur in the automatic driving process in time, and issue intelligent early warning information, thereby greatly ensuring the safety of driving.

The invention relates to a fault analysis and diagnosis method for a slurry circulating pump of a desulfurizing tower, which comprises the following steps of collecting the historical data, and normalizing the processed data; constructing a training and prediction sample, and learning by adopting a BP neural network method; training of the BP neural network is completed, and constructing a slurrycirculating pump motor current analysis system; in combination with the actual desulfurization efficiency, clustering the motor current of the slurry circulating pump; constructing a probabilistic neural network model according to a classification result; utilizing a probabilistic neural network model to diagnose the motor current of the slurry circulating pump in real time, and giving a fault probability; and combining the fault prediction and diagnosis to construct a slurry circulating pump fault analysis and diagnosis system. The method is suitable for solving the problem of fault analysisand diagnosis of the slurry circulating pump in the wet desulphurization system, can help an operator to predict the type and trend of a fault which may occur in the future by using real-time operation data of the system, and has the very high practical application value.

The invention relates to the technical field of video surveillance and discloses vehicle annual survey detection method and device, wherein the method comprises the following steps: acquiring a to-be-detected image including an annual survey label; detecting the to-be-detected image step by step by using a pre-trained multistage CNN network model to obtain the position of an area box including anannual survey label to be taken as the position of the annual survey label; performing fixed point detection on the area box including the annual survey label, wherein the fixed point represents an angular point on the contour of the annual survey label; when no fixed point is detected, determining the annual survey label as an elliptical label; and when the fixed point is detected, determining the annual survey label as a rectangular label or rhombic label, wherein the area formed between the fixed points is the exact position of the annual survey label. According to the invention, on the basis of acquiring the position of the annual survey label, the area box, where the annual survey label is positioned, is subjected to fixed point detection to judge the type of the annual survey label,and thus the surveillance pressure of the traffic control department is effectively relieved.