80150results about How to "High degree of automation" patented technology

A process for video content analysis to enable productive surveillance, intelligence extraction, and timely investigations using large volumes of video data. The process for video analysis includes: automatic detection of key split and merge events from video streams typical of those found in area security and surveillance environments; and the efficient coding and insertion of necessary analysis metadata into the video streams. The process supports the analysis of both live and archived video from multiple streams for detecting and tracking the objects in a way to extract key split and merge behaviors to detect events. Information about the camera, scene, objects and events whether measured or inferred, are embedded in the video stream as metadata so the information will stay intact when the original video is edited, cut, and repurposed.

A method and apparatus for controlling a parking process of a vehicle. The method including setting an upper speed limit; using a speed-limiting device to limit the speed of the vehicle at a parking speed that is less than or equal to the upper speed limit speed; suppressing an accelerator pedal speed increase request that increases the vehicle speed over the upper speed limit; and performing the assisted parking operation while limiting the vehicle speed and terminating the suppression of the increase in speed when the accelerator pedal is depressed by more than a predetermined value. Wherein the predetermined value is selected as a function of a slope on which the vehicle is located. The invention also relates to a steering system for an assisted parking procedure of a vehicle and a vehicle with such a steering system.

The invention relates to the technical field of digital earth, in particular to a digital earth prototype system comprising a data receiving and fast processing sub-system, a metadata service sub-system, a model base sub-system, a space information database sub-system, a mesh calculation sub-system, a map application service sub-system and a virtual reality sub-system. With the adoption of the invention, it is able to construct a data resource sharing platform, a knowledge sharing platform, a computation resource sharing platform and a coordinated operation platform of the digital earth prototype system. Besides, with the establishment of the prototype system, the invention resolves relevant key technologies for the construction of a technology service platform for the application of space data and forms a service system for the application of space information in earth technology.

The invention discloses an intelligent inspection system and an inspection method for an electric transmission line by an unmanned aerial vehicle. The intelligent inspection system comprises an inspection mission planning system, a dispatching system, a monitoring system, an inspection result processing platform and mobile branch stations, wherein the inspection mission planning system communicates with the inspection result processing platform and the dispatching system respectively; the inspection result processing platform and the dispatching system communicates with the monitoring system respectively; the monitoring system is connected and communicate with the mobile branch stations. The inspection method has the benefits that factors of the inspection unmanned aerial vehicle, inspection equipment, an inspector, and the like accessing the dispatching platform through a dispatching terminal can be dispatched effectively to realize equipped configuration of unmanned aerial vehicle inspection resource; the usage rates of personnel and equipment can be improved; the no-load rate and vacancy rate of the inspection equipment are reduced; through centralized monitoring of condition information inspected by the unmanned aerial vehicle, unmanned aerial vehicle inspection dispatching personnel can master unmanned aerial vehicle inspection in the large effectively; the service life of the unmanned aerial vehicle is prolonged.

The invention provides a method and a system for processing high-definition remote sensing image data by applying a rational function model, a satellite image block adjustment and auto-match and distributed parallel processing technology. The method comprises the following steps: analyzing and processing input primary image data and computing parameters of the corresponding rational function model so as to obtain a stereo image pair by applying the computed rational function model; performing measurement and singlechip orientation of a control point and a connecting point on the primary image data, and performing block adjustment processing on an error between stereo image pixel data and the primary image data so as to improve the fit precision between the stereo image pixel data and the primary image data; generating an image similar to an epipolar ray, defining a matching template, measuring matched seed points and lines, performing automatic image matching and generating a digital elevation model; and respectively generating a digital orthophoto map and a digital line graph, and finishing manufacturing a product by applying the obtained data.

The invention relates to a full-automatic flexible assembly line of a light emitting diode (LED) bulb lamp. The assembly line comprises a light source assembly workstation, a power supply assembly workstation, a lamp cover assembly workstation, an intermediate storage device, a terminal storage device, a supply device and a control system, and is provided with an assembly execution mechanism and an auxiliary execution mechanism, the assembly execution mechanism is used for inserting, clamping, gluing, locking a screw, punching a rivet and the like, the auxiliary execution mechanism is used for detecting the electrical property of a semi-finished product, feeding, blanking, turning a gesture and the like, the assembly line is a hybrid structure based on a station turntable, part transmission and station flow are realized by the station turntable, a conveying belt and a manipulator, and all parts are automatically fed. The assembly line is compact in structure and high in production rhythm, and has high reliability and flexibility, production efficiency is obviously improved, the manufacturing cost of a single piece is reduced, and the full-automatic flexible assembly line of the LED bulb lamp is realized.

The invention provides a subcritical liquid extraction device and a subcritical liquid extraction method of active ingredients of natural products, relating to a device and a method for extracting active ingredients of natural products. The device comprises a control system part and a leaching system part, wherein the leaching system part comprises an extraction tank 1, an evaporating tank 2, a buffer tank 3, a condenser 4, a solvent tank 5, an ultrasound generating device 11, a vacuum pump 9, a fire arrester 10, a compressor 8, a hot water pump 7 and a hot water box 6; the control system partcomprises a leaching temperature controller, a leaching time controller, a leaching frequency controller, a material dissolving ratio controller, an exsolution temperature regulation controller, an exsolution pressure feedback controller, an electric appliance controller of the device and an excess-temperature excess-pressure leaking alarm. The method can select different subcritical extraction media according to different extraction products, combines a subcritical liquid extraction technology and an ultrasonic extraction technology to increase extraction rate and reduce extraction time andis a new high-efficiency low-consumption environment-friendly technology for extracting active ingredients of natural products.

The invention discloses a centralized monitoring system for power transmission line routing inspection of unmanned aerial vehicles. The centralized monitoring system comprises a centralized monitoring subsystem, mobile substations and unmanned aerial vehicle flying platforms. The centralized monitoring subsystem and the mobile substations are connected in a one-to-more mode, and the mobile substations and the unmanned aerial vehicle flying platforms are connected in a one-to-one mode. By adopting a mode that remote centralized monitoring and local monitoring are combined, information including flying states, pod states, power transmission lines and routing inspection results of more than one line patrol unmanned aerial vehicles are subjected to centralized monitoring, persons, devices and routing inspection lines related to unmanned aerial vehicle routing inspection tasks are planned and managed, centralized management and defect diagnosis are performed on the routing inspection results, the informatization and automation degree of the unmanned aerial vehicle routing inspection process and routing inspection result processing are improved, the routing inspection efficiency of the unmanned aerial vehicles is improved, and a technical support is provided for safe and reliable running of routing inspection line routing inspection.

The invention provides an automatic vulnerability validation method. The method comprises the steps that firstly, validation information is collected, wherein an active detection way is adopted for carrying out information detection, topological detection, vulnerability detection and website directory structure detection on a target; secondly, the validation information is packaged, wherein suspicious vulnerability key information in vulnerability detection results is extracted, uniform-interface modularized packaging is carried out on the data; thirdly, a validation strategy is searched for, wherein according to the suspicious vulnerability identity and variety information, an appropriate attack script template and a vulnerability utilizing tool are selected; vulnerability validation is carried out, wherein scripts are called to be loaded into the packaged vulnerability information to carry out validation attack, and an utilization voucher is obtained and stored; fifthly, validation traces are removed, wherein validation attack traces are removed, sessions are recycled; finally, a scanning report is generated. The automatic vulnerability validation method solves the problem that an existing vulnerability scanning system is high in false alarm rate and cannot carry out effective validation, is automatic and procedural, can automatically recognize and validate vulnerabilities, lowers the requirement for the ability of non-professional staff and improves the vulnerability validation efficiency.

The invention discloses a regional depth edge detection and binocular stereo matching-based three-dimensional reconstruction method, which is implemented by the following steps: (1) shooting a calibration plate image with a mark point at two proper angles by using two black and white cameras; (2) keeping the shooting angles constant and shooting two images of a shooting target object at the same time by using the same camera; (3) performing the epipolar line rectification of the two images of the target objects according to the nominal data of the camera; (4) searching the neighbor regions of each pixel of the two rectified images for a closed region depth edge and building a supporting window; (5) in the built window, computing a normalized cross-correlation coefficient of supported pixels and acquiring the matching price of a central pixel; (6) acquiring a parallax by using a confidence transmission optimization method having an acceleration updating system; (7) estimating an accurate parallax by a subpixel; and (8) computing the three-dimensional coordinates of an actual object point according to the matching relationship between the nominal data of the camera and the pixel and consequently reconstructing the three-dimensional point cloud of the object and reducing the three-dimensional information of a target.

The invention discloses a testing method based on software defect mode, comprising the steps of: reading source code files of programs to be tested and SDSM description file of a defect state machine, carrying out pre-processing of the programs to be tested, analyzing the SDSM description file; carrying out lexical analysis and grammar analysis of the programs to be tested and constructing abstract syntax tree; generating a control flow graph and a symbol table according to the abstract syntax tree and carrying out the calculating and updating of variable value interval sets according to the control flow graph and the symbol table; carrying out function invoking relation analysis of the programs to be tested and generating a function invoking relation graph; searching the control flow graph by taking the function as unit according to the function invoking relation graph, calculating the state migration of each node defect state machine on the control flow graph, and reporting corresponding checking point when the defect state machine enters the defect state. The invention also discloses a testing system based on software defect mode, which comprises an input module, a defect mode uniformity testing frame and a user interface module and completes the uniform test on the programs to be tested.

The invention provides a method for automatically generating software test cases. The method comprises the following steps of: A. reading to-be-tested software, carrying out lexical analysis, syntax analysis and semantic analysis on a source program of the to-be-tested software and generating an abstract syntax tree and a control flow graph of the to-be-tested software; B. preprocessing the source program of the to-be-tested software by traversing the generated abstract syntax tree, identifying initial input-output variables and compressing the space of a definition domain of the initial input variables; and C. generating a path of program elements of the current to-be-tested software by traversing the control flow graph, carrying out assignment operation, implication operation and backtracking operation on the variables in the path, and generating the test cases. The invention also provides a system for automatically generating software test cases. The method and the system for automatically generating the software test cases can accurately and automatically generate the test cases according to the given program elements of the to-be-tested software and verify the generated test cases, thereby improving the accuracy, efficiency and automation degree of the test cases.

A system and method for event correlation and adaptive rules optimization in the context of a trouble ticket resolution system. The adaptive rules optimizer incorporates learning principles that achieve a high degree of automation while leaving control in the hands of an operator. To mitigate the effects of possible errors, the adaptive rules optimizer switches from hard decisions to soft decisions. The tickets in the queue and their related events are prioritized to mimic the best practices introduced by the support team handling the given problem, to take into account the business impact so that at each point in time the operator's work provides maximum overall benefit and to provide all auxiliary information that may be instrumental in the problem resolution process.

The invention provides a contact network three-dimensional reconstruction method based on SIFT and LBP point cloud registration. The method comprises the first step of obtaining initial three-dimensional point cloud data of the environment where parts of a contact network to be reconstructed are located through motion-sensing peripheral Kinect for Windows, and conducting denoising, simplifying, partitioning clustering, fusing and other preprocessing operations on the initial three-dimensional point cloud data to obtain single-view-angle point cloud data of the parts of the contact network to be reconstructed, the second step of extracting key points through an SIFT algorithm, constructing description vectors of the key points by means of LBP features of uniform patterns and determining the corresponding relations between the key points in different point clouds according to the distances between the vectors, the third step of completing point cloud registration through a rough registration method and an ICP fine registration method and obtaining the complete three-dimensional point cloud data of the parts of the contact network to be reconstructed, and the fourth step of completing three-dimensional reconstruction through the Poisson surface reconstruction method and obtaining a three-dimensional model. According to the method, the key factor is point cloud registration which is the key step influencing the three-dimensional reconstruction speed; the description vectors of the key points are constructed by means of the LBP features of the uniform patterns, so that vector dimensions are reduced, the matching speed of the corresponding relations is increased, registration is accelerated, and the three-dimensional reconstruction speed is increased.

The invention relates to an ectopic leaching restoring device and a restoring method for chromic slag polluted soil. The device is provided with an integrated soil leaching and dewatering system and mainly comprises a feeding system, a soil leaching-dewatering system, a waste gas treating system, an elution collecting treating system and an automatics control system. The chromic slag polluted soil firstly enters a reaction tank leaching section through the feeding system; a chrome-containing component in the soil is transferred into a liquid phase of a leaching agent; the liquid phase is rotated following a spiral stirring thruster; a muddy water mixture is conveyed into a reaction tank dewatering section; the filtrate is discharged through a tank wall with a water-permeable filtering function; the remained soil is conveyed to a mud discharging device following the rotating of the spiral stirring thruster; and lastly, the soil after being leached and dewatered is discharged. The device provided by the invention has the advantages that a power source is utilized to realize the soil leaching and muddy water separating, the energy consumption is low, the structure is simple, the use is convenient, the treating efficiency is high, and the purified degree of the polluted soil after being treated by using the device is above 85%.

The invention relates to the field of agricultural machinery, in particular to a poria cocos dicing machine. The poria cocos dicing machine comprises a machine frame, a hopper, a collection box, a transmission device, a squeezing and pushing device, a slicing device, a partition device and a dicing device. An upper installation platform and a lower installation platform are respectively arranged on the machine frame, the hopper is located on the lower right side of the upper installation platform, and the collection box is located under the hopper; the transmission device is located between the upper installation platform and the lower installation platform; the squeezing and pushing device is located behind the upper installation platform and used for pushing poria cocos onto the slicing device; the slicing device is located in front of the squeezing and pushing device and can slice the poria cocos; the partition device is located in the middle of the upper installation platform and can arrange the sliced poria cocos onto a conveying belt uniformly; the dicing device is located right in front of the partition device and can rapidly dice the sliced poria cocos which is well arranged. The poria cocos dicing machine can achieves the function that the poria cocos is sliced firstly and then diced, and solve the problems that as for conventional manual dicing, labor intensity is high and dicing efficiency is low.

The invention provides an urban rail transit panoramic monitoring video fault detection method based on depth learning. The method comprises a data set construction process, a model training generation process and an image classification recognition process. The data set construction process processes a definition abnormity video, a colour cast abnormity video and a normal video in an urban rail transit panoramic monitoring video. A training set and a test set are classified. The model training generation process comprises model training and model test. The model training is to train a fault video image recognition model based on a convolution neural network. The convolutional neural network comprises a plurality of convolution layers and a plurality of full connection layers. The model test is to calculate the test accuracy. If expectation is not fulfilled, the fault video image recognition model is optimized. The image classification recognition process comprises the steps that a single-frame image to be recognized is input into the model, and the fault video image recognition model outputs an image classification result to complete the fault image detection of the urban rail transit panoramic monitoring video.

The invention discloses a block chain technology-based electronic intelligent signing payment method and belongs to the technical field of electronic contracts. A device for implementation of the block chain technology-based electronic intelligent signing payment method comprises a public payment block chain layer, an intelligent contract platform layer, a contract creating layer and a contract signing layer; an electronic contract signing link can be effectively integrated with an electronic contract performing (payment) link, and an intelligentization and automation degree of businesses related to electronic contacts can be improved; according to the block chain technology-based electronic intelligent signing payment method, block chain technologies are introduced as an underlying technology, payment flows are unified, and complexity can be lowered; via greater self-maintenance and safety improvement of the block chain technologies than that of other payment means, usability and user experience of whole electronic contract businesses can be improved.

The invention discloses a posture and moving track positioning system and method of robot grabbing an online workpiece. The device comprises a camera support, an industrial camera, the tested workpiece, a workpiece conveying belt, a tail end executer, a robot system, a workbench, an image processor and the like. The method comprises the steps that a depth positioning model of a plane point in an absolute coordinate system in the vertical direction, a depth positioning model of a space point in the absolute coordinate system in the vertical direction, an X-axis positioning model of the plane point in the absolute coordinate system in the horizontal direction and an X-axis positioning model of the space point in the absolute coordinate system in the horizontal direction are established, three-dimensional coordinates of imaging points in all the cameras can be solved through combination of the priori knowledge of the workpiece, accordingly, and a robot can be guided to adopt the accurate tail end executer posture and movement track to intelligently grab the workpiece accurately. The posture and moving track positioning system and method have the advantages that the grabbing precision is high, the structure is simple, and cost is low.

The invention provides an automatic adobe stacking device. The device comprises an automatic control device, an adobe group conveying mechanism, a horizontal travelling mechanism, a vertical lifting mechanism arranged on the horizontal travelling mechanism, a rotation mechanism fixed on the lower end of the vertical lifting mechanism and an adobe grabbing mechanism fixed on the lower end of the rotation mechanism, wherein the adobe group conveying mechanism is arranged below the adobe grabbing mechanism; and the automatic control device is respectively connected with the adobe group conveyingmechanism, the horizontal travelling mechanism, the vertical lifting mechanism, the rotation mechanism and the adobe grabbing mechanism so as to control the operation of the mechanisms. The adobe automatic stacking device has the advantages of accurate positioning, stable direction steering, neatly stacked adobes, firmly overlapped upper and lower adobes, simple structure, high automatic degree and easiness for operation, so that the labor intensity of workers is reduced, the production efficiency of stacking is greatly improved, and the stacking quality of adobe stacks is improved.

The invention discloses a method for quickly identifying and distinguishing the variety of corn, which belongs to the technical field of the detection of agricultural products. The method identifies the variety of the corn by an image processing technology quickly. Seed image information is obtained by a scanner, corn seeds are identified by a corn variety identification system on a computer, original image information is read, the image information of each pixel in each corn is stored as a 24-bit bmp format file, and the variety of the corn is distinguished by a trained neural network classifier after image processing and feature extraction are completed. The variety distinguishing rate of the model to an unknown sample is greater than 90%, which shows that a condition that the variety of the corn seeds is distinguished by image feature information is feasible. The invention has the characteristics of high automatization degree and quick, simple and convenient operation.

The invention relates to a color image three-dimensional reconstruction method based on three-dimensional matching, comprising the following steps of: (1) simultaneously and respectively taking an image from proper angles by using two color cameras; (2) respectively calibrating the internal parameter matrixes and the external parameter matrixes of the two cameras; (3) carrying out polar line correction and image transformation according to calibrated data; (4) working out matching cost for each pixel point in the two corrected images by applying a self-adaption weight window algorithm and acquiring an initial parallax image; (5) marking the reliability coefficient of the pixel initial matching result by adopting matching cost reliability detection and left and right consistency verification; (6) carrying out color segmentation on the images through a Mean-Shift algorithm; (7) carrying out global optimization by a selective confidence propagation algorithm on the basis of color segmentation and pixel reliability classification results to obtain a final parallax image; and (8) working out the three-dimensional coordinates of actual object points on the images according to the calibrated data and the matching relation, thereby reconstructing the three-dimensional point cloud of an object.

A synchronous quick calibration method of a plurality of video cameras in a three-dimensional scanning system, which includes: (1) setting a regular truncated rectangular pyramid calibration object, setting eight calibration balls at the vertexes of the truncated rectangular pyramid, and respectively setting two reference calibration balls at the upper and lower planes; (2) using the video cameras to pick-up the calibration object, adopting the two-threshold segmentation method to respectively obtain the corresponding circles of the upper and lower planes, extracting centers of the circles, obtaining three groups of corresponding relationships between circle center points in the image and the centres of calibration ball in the space, solving the homography matrix to obtain the internal parameter matrix and external parameter matrix and obtaining the distortion coefficient, taking the solved video camera parameter as the initial values, and then using a non-linear optimization method to obtain the optimum solution of a single video camera parameter; (3) obtaining in sequence the external parameter matrix between a plurality of video cameras and a certain video camera in the space, using the polar curve geometric constraint relationship of the binocular stereo vision to establish an optimizing object function, and then adopting a non-linear optimization method to solve to get the optimum solution of the external parameter matrix between two video cameras.

The invention discloses a method for the classification of natural scene images on the basis of regional potential semantic feature, aiming at carrying out the classification of the natural scene images by utilizing the regional potential semantic information of the images and the distribution rule of the information in space. The technical proposal comprises the following steps: firstly, a representative collection of the classification of the natural scene images is established; secondly, sampling point SIFT feature extraction is carried out to the images in the representative collection of the classification of the natural scene images to generate a general visual word list; thirdly, the regional potential semantic model of an image is produced on the representative collection of the classification of the natural scene images; fourthly, the extraction of the regional potential semantic feature of the image is carried out to any image; finally, a natural scene classification model is generate, and classification is carried out to the regional potential semantic feature of the image according to the natural scene classification model. The method inducts the regional potential semantic feature, thus not only describing the regional information of image sub-blocks, but also including the distribution information of the image sub-blocks in space; compared with other methods, the method of the invention can obtain higher accuracy, and no manual labeling is needed, thus having high degree of automation.

A method is provided for comparing multiple samples of cell extract containing a plurality of components. The method comprises the steps of preparing at least two samples of cell extract from at least two groups of cells and of exposing each of said sample of said cell extract to a different one of a set of matched markers, e.g. luminescent markers, to bind the marker to the cell extract to label the cell extract, each marker within said set of markers being capable of binding to the cell extract and can be individually detected from all other markers within said set. The samples are then mixed to form a mixture and said mixture is electrophoresed to separate the components within the cell extract. At least two electronic images of the electrophoresed mixture are obtained (I) by detection of the individual markers, each image being represented by detection of a marker different from the others. One resultant electronic image (Ires) of the obtained at least two electronic images is created (II) and analyzed in order to identify spot analysis areas (III). The identified spot analysis areas are applied on the respective at least two electronic images for evaluating said areas in order to detect spots representing components of said cell extracts (IV).

Disclosed is a bag-feeding pillow type packaging machine. A horizontal bag conveyor is disposed between a bag feeder and a horizontal bag opener. A feeding part of the horizontal bag conveyor is located below the bag feeder. A discharge part of the horizontal bag conveyor is connected with the rear end of the horizontal bag opener. A bag picker is located below the horizontal bag conveyor. The bag picker extends into the bag feeder through the feeding part of the horizontal bag conveyor. The horizontal bag opener is disposed on the conveying direction of the horizontal bag conveyor, a conveying device is disposed in front of the horizontal bag opener, the conveying direction of the conveying device is perpendicular to that of the horizontal bag conveyor, a horizontal feeding device is disposed on one side of the conveying device and located on the conveying direction of the horizontal bag conveyor, a motion direction of the horizontal feeding device is perpendicular to the conveying direction of the conveying device, a sealing device is disposed on the horizontal bag opener, a finished product output device is disposed below the horizontal bag opener, and the conveying direction of the finished product output device is perpendicular to that of the horizontal bag conveyor.

The invention discloses a device and a method for automatically detecting and sorting light emitting diodes (LEDs). The system comprises a first conveying device which is used for loading materials onto LED material strips and conveying the LED material strips and is capable of dotting unqualified LED material strips, a detecting device which is used for detecting the surface appearance, the size, the color and defects of each LED bracket in the LED material strips, a second conveying device which is used for sending out the detected LED material strips, a sorting device which is used for storing out the unqualified LED material strips, a display device which is used for displaying detection data, and a control device which is used for comparing the detection data with standard data to determine whether the LED brackets are qualified or not, and controlling the whole process of material loading, detection, dotting, conveying and sorting of each device. The method comprises multiple steps of standard setting, control device startup, sampling, comparison and output. Products can be automatically classified, the automation degree is high and the labor force is effectively reduced.