449results about How to "Satisfy real-time" patented technology

The invention relates to one digital mobile communication technique suitable for one transmission base station monitor method and system based on wireless mobile terminal, which uses GSM communication network short message channel to sort monitor data and to transmit on focus degree, wherein, the alarm information and inquire information send by real time and the operation information without alarm sends method and process technique to form alarm guide base station monitor system by network monitor center, base station and other human cell phone network.

The invention provides a vehicle license plate recognition method based on a video. According to the vehicle license plate recognition method based on the video, moving vehicles are detected and separated out with the vehicle video which is obtained through actual photographing by means of a camera serving as input, the accurate position of a vehicle license plate area is determined by conducting vertical edge extraction on a target vehicle image obtained after pre-processing, a vehicle license plate image is separated out, color correction, binaryzation and inclination correction are conducted on a vehicle license plate image, each character in the positioned vehicle license plate area is separated to serve as an independent character, feature extraction is conducted one each character, obtained feature vectors are classified through a classifier which is well trained in advance, a classification result serves as a preliminary recognition result, secondary recognition is conducted on the stained vehicle license plate characters according to a template matching algorithm imitating the visual characteristics of human eyes, and then a final vehicle license plate recognition result is obtained. The vehicle license plate recognition method based on the video has the advantages that hardware cost is reduced, the management efficiency of an intelligent transportation system is improved, the anti-jamming performance and the robustness are high, the recognition efficiency is high, and the recognition speed is high.

The invention discloses a method for scheduling satellite data product production tasks in parallel based on multithread. The method comprises the following steps: setting priorities for tasks to be scheduled for executing and realizing a uniformed interface; adding the tasks into a priority queue according to an order of the priorities from high to low; setting the maximum number and the minimal number of the tasks of a thread pool, and the longest idle time of a thread; and starting a daemon thread in the thread pool and a plurality of task threads to execute the tasks, wherein the daemon thread regulates the number of the task threads dynamically according to the situation of task amount. The method can utilize system resource rationally, aims at the data product production of a satellite ground application system, and solves the difficult points of complicated product production processes, long task executing time, large task amount, high real time and parallelism degree for scheduling the tasks and the like.

The invention relates to a method for transmitting streaming media data, comprising the following steps: a streaming media server packs streaming media into an RTP data packet by an RTP protocol and transmits the RTP data packet to a client; the client judges whether packet serial numbers of the received RTP data packet are continuous or not; if not, an RTCP retransmission request is transmitted to the streaming media server; the streaming media server analyzes the RTCP retransmission request; and a missed RTP data packet is retransmitted according to a network communication state self-adaptive regulation retransmission mode. The method and the device can satisfy the requirements of streaming media service real-time transmission and high reliability according to the actual network communication state self-adaptive regulation retransmission mode so as to achieve better streaming media service effect.

The invention discloses an inspection system and an implementation method for the electrical equipment of an unmanned aerial vehicle photovoltaic power station. The inspection system includes an airborne terminal, a ground terminal, and a wireless communication module. The camera or monitoring equipment collects the image data of the electrical equipment of the photovoltaic power station, and at the same time receives the control commands sent from the ground terminal to the airborne terminal; the ground terminal is set on the ground platform to process the data collected and sent back by the airborne terminal , to control the flight and shooting operations of the unmanned aerial vehicle on the ground; the wireless communication module completes the functions of transmitting flight control instructions, flight status data, and video return data between the airborne terminal and the ground terminal. The inspection system provides real-time high-definition viewing of infrared images and visible light images, which is convenient for timely resolution of faults. The images are analyzed on the ground side through pattern recognition. repair.

The invention provides a low power consumption hand-held electric nose system for on-site check, which comprises an electric nose box provided with a gas flow control system which gas chamber is at least provided with a mixture sensor array composed of low power consumption gas sensitive sensors, wherein the electric nose box is further provided with a necessary electric checking circuit, a wireless communication module and / or a USB module, a single chip and a DSP system for data processing and mode recognition, the electric checking circuit is provided with a CPLD circuit for checking QCM gas-sensitive sensor signal and a circuit for regulating electrochemical gas-sensitive sensor signal check and temperature humidity senor signal check. The invention can independently work without computer and automatically realize gas flow control, smell check, signal pretreatment and character extraction, mode recognition and display alarm or the like in an independent instrument, to meet the real-time, low power consumption and hand-held demands of on-site check.

The invention relates to a method and a system for building a big data distributed log. The method comprises the following steps that: 1, a log transmission sub system receives log data from a service system, generates a UUID (Universally Unique Identifier) for each piece of received log data, and sends the log data with the UUID to a log storage sub system through a plurality of nodes after the load balance; 2, the log storage system receives the log data, and stores the log data in a horizontal expansion mode; and 3, a mass log processing sub system extracts the log data stored in the log storage sub system, uses a MapReduce algorithm to regularly perform mass pre-processing on the log data, and generates a report by the hour and a report by the day to be required by an external service report system. The method and the system have the advantage that the requirements on the reliability, the real-time performance, the high performance, the high expandability and the maintainability of a log system under the big data condition can be met.

The invention discloses a visual locating system of spherical robot and a visual locating method thereof. The visual locating system is composed of a binocular visual system, a one-dimensional gyroscope, a spherical robot body, a core control system and a wireless communication module. The locating system carries out locating through cooperation of a camera and the gyroscope, and a locating algorithm is realized on line in the core control system. Data for locating are subjected to remote transmission through the wireless communication module. And a use can realize remote real time monitoring of a robot position. The locating method comprises: conducting real-time acquisition of left and right image sequences by a binocular camera, calculating the posture and location changes of the spherical robot by a binocular visual mileage calculation method, compensating a feature locating error caused by an unstable spherical robot platform through the gyroscope, and finally performing state updating by a Kalman filtering method. The whole process iterates continuously so as to realize real time calculation of the posture and location of a robot.

The invention provides a method and system for achieving integrated camera automatic focusing, and provides a zooming tracking method based on a relationship type, namely for a shot object at a fixed object distance, according to the initial zooming multiple, the value of an initial focusing position and a plurality of zooming tracking curves stored in advance, the mapping relation between the object distance interval and the focusing position is constructed, and the position to be focused is calculated in real time. Then, a gradient control function obtained by the combination of the statistical law of a lot of experimental data is utilized to achieve mobility control over a zooming motor and a focusing motor, the value of the position to be focused is improved and amended to a certain degree, the value of the position to be focused is closer to a real zooming tracking curve, and an automatic focusing effect is more accurate. Meanwhile, the zooming tracking curves are not needed to be stored in advance, all the zooming tracking curves corresponding to different object distances are not needed to be calculated point by point, an algorithm is simple, it is possible that the zooming speed meets a real-time property, and the focusing effect can meet the requirement for clearness in the whole process.

The invention provides a real-time three-dimensional double-hand gesture recognition method and system based on binocular vision. The real-time three-dimensional double-hand gesture recognition method based on binocular vision comprises the steps that initial calibration and correction are conducted on an image firstly, the outline of a gesture is extracted, two-dimension gesture recognition is conducted on the extracted gesture outline, the mass center of the gesture outline is calculated, stereo matching is conducted on the mass center obtained through calculation, three-dimensional hand gesture recognition is achieved, and corresponding gestures are displayed in a human-computer interaction module based on the three-dimensional hand gesture recognition. According to the real-time three-dimensional double-hand gesture recognition method and system based on binocular vision, binocular vision information can be utilized, and human-computer interaction, based on the three-dimensional space, of double-hand gesture change of a computer is achieved; meanwhile, extremely high real-time performance and extremely high effectiveness can be achieved, and requirements for hardware are lowered; in addition, the man-machine interaction effect is achieved, and the requirements for real-time performance and effectiveness are well met.

The method comprises: newly adding a communication scheduling layer into original data link layer of Ethernet; in relation to the standard channel using TCP / IP, newly adding a real time channel; according to the greatest common divisor of control cycle in the actual control area, using a three segmentation dividing principal to divide macro cycle into three time segmentations on time axis; the bus arbitration uses a approach of combining the distribution with the concentration, and uses a time slot distribution based scheduling approach to send the cyclic data relating to the realization of control function in the time segmentation, uses the centralized scheduling approach with priority controlling function to send the system data and non cyclic data in the time segmentation; all slave devices in the system keep the time consistence with the master device by using a clock synchronous algorithm; the logic addressing is made based on the device ID; realizing the real time Ethernet determinacy communication.

The invention relates to an automatic selection method of a dynamic scheduling strategy of a semiconductor production line. The automatic selection method comprises the following steps of: obtaining a production attribute set, a scheduling strategy set and a performance index set of the production line according to the actual semiconductor production line; obtaining various performance index values of the production line under different scheduling strategies through simulation, and establishing a sample set; training the training sample set, obtaining an optimized production attribute set and SVM (Support Vector Machine) training parameters, and forming a dynamic scheduling rule classifier A* based on SVM; inputting the A* to a test sample set, judging whether the prediction accuracy of the scheduling strategy based on a character subset is superior to that of a universal set, and if yes, training the training sample set S1 according to the obtained character subset and the SVM training parameters, and obtaining a final dynamic scheduling rule classifying model A; and inputting real-time state information of the production line to the A, and dynamically obtaining an optimized scheduling strategy. Compared with the prior art, the automatic selection method of the dynamic scheduling strategy of the semiconductor production line has the advantages that the scheduling instantaneity is good, the production efficiency is improved, and the like.

The invention discloses a convolutional neural network-based character recognition method, and mainly aims at solving the problem that existing manual engineering drawing data input is time-consuming,labor-consuming and high in error rate. The method comprises the following main steps of: 1) converting grayscale images into binary images by adoption of Otsu method-based optimal global threshold value processing; 2) rotating to correct inclined images; 3) extracting a table box by adoption of a mathematic morphological algorithm; 4) obtaining an area where characters are located; 5) rotating inclined character strings for a corresponding angle to a horizontal direction; 6) searching circles in the images by adoption of a circular Hough transformation algorithm, and extracting welding beadnumbers in an engineering drawing; 7) carrying out image-text recognition on the engineering drawing by adoption of a convolutional neural network method; 8) correcting simple errors through an encoding rule and automatically correcting recognition errors; and 9) outputting and storing the drawing data. In image-text recognition of engineering drawings, the method has high correctness and timeliness, and is capable of realizing efficient recording and management of engineering drawing data.

The invention provides a route planning method for an autonomous vehicle based on a vector map and a grid map. The route planning method comprises: planning a global shortest route of the current position of the autonomous vehicle to a target point through a global vector map; obtaining a current partial grid map of the current position of the autonomous vehicle; and according to the global shortest route, calculating a partial motion route based on the partial grid map, and controlling the autonomous vehicle to travel to the target point according to the partial motion path. According to theroute planning method for the autonomous vehicle based on the vector map and the grid map, the vector map is used as an environment model in the global route planning layer, and the grid map is used as an environment model in the partial motion route planning layer, that is, different maps are used as environment models in different planning layers, and at the same time, different types of planning algorithms are used, so that the real-time performance and accuracy of the algorithm under an actual scene are met at the same time, and the algorithm combining the vector map and the grid map greatly reduces the occupation of system operation resources.

The invention discloses a multi-template object tracking method based on CNN and CF. The present invention proposes a method of using a plurality of fixed scale values for normalizing the template before solving the convolution operation, and then reversing the most appropriate scale after obtaining the maximum response value; although the existing DSST algorithm is used to decompose the three-dimensional optimal scale search into the best position in two-dimensional space and the optimal scale mechanism is searched in one-dimensional space, the iteration is slow and the computational complexity is high; in view of the characteristics that the movement of the unmanned aerial vehicle platform is random, the speed is uncertain and so on, the method of the fixed scale value is used to not only meet the tracking algorithm needs, but also to meet the real-time operation; in the characteristic extraction stage, the two characteristics are extracted respectively, two different groups of filters are trained, according to the appearance and the background change of the current object, different weights are set for performing appearance representation of the object; and results obtained from the different characteristics are fused to obtain the tracking result.

The invention provides a method for segmenting a white blood cell image, which is characterized by comprising the following steps: firstly carrying out binaryzation on the green component picture of a color white blood cell image to obtain an initial interested region based on a significance attention mechanism of human vision; carrying out cancellation and mergence on a region by labeling the initial interested region to obtain an adaptive significance window of each cell; and finally realizing segmentation of nucleuses and cytoplasm in each adaptive significance window by a boundary-extending method. The segmentation method is used to realize the fast segmentation of the white blood cells, particularly the accurate segmentation for high-capacity pictures which are the non-standard dyed and contain overlapped cells.

The invention belongs to the technical field of radar weak and small target detection and tracking, and particularly relates to a method for conducting before-detection tracking on a weak and small target in a strong-clutter environment based on dynamic planning. The method for conducting before-detection tracking on the weak and small target in the strong-clutter environment based on dynamic planning includes the first step of preprocessing echo data received by radar to obtain a processed distance-doppler two-dimensional image, and the second step of constructing a complex number likelihood ratio function according to the distance-doppler two-dimensional image, taking the complex number likelihood ratio function as a value function for dynamic planning, and conducting before-detection tracking on the target according to a dynamic planning method so as to obtain the target track.

The invention discloses a method for fast establishing interactive tunnel and wall rock body three-dimensional models, which comprises the following steps: A. tunnel line position information base establishment: collecting tunnel line position information and establishing a line position information base; B. geological exploration base establishment: carrying out standardized processing on hole drilling data obtained through geological exploration; C. three-dimensional stratigraphical profile constraint information base establishment: collecting three-dimensional stratigraphical profile constraint information; D. three-dimensional stratigraphical boundary constraint information base establishment: collecting self defined model establishing boundary; E. real three-dimensional tunnel model establishment: precisely establishing a tunnel three-dimensional model according to the information of tunnel line positions, the tunnel hole body outer cross section and the inner cross section; F. real three-dimensional wall rock model establishment: establishing a wall rock model according to the hole drilling and stratigraphical information; and G. tunnel digging and profile real-time cutting display based on the wall rack model body unit. The model establishing efficiency and precision of the tunnel simulation and digitalized design can be improved, the real-time cutting display of the tunnel passing through the wall rock and any vertical profile can be realized, and the fast reestablishment of the model can be realized.

The multifunctional safety control system for tower crane possesses integrated several functions and is used for effective monitoring on tower crane for safe running. It consists of control circuit and system software. The control circuit consists of microprocessor module, sensor and signal processing module, relay module, keyboard and LCD module, and communication module. All the modules are installed inside one box, the sensor is connected through cable to the box, and the software has the embedded operation system muCOS-II as platform and multiple decomposed tasks for the whole system control.

The invention discloses a method and a device for acquiring target location information. The method comprises the following steps: step S1, acquiring location information of a reference point; step S2, measuring an elevation angle and an azimuth angle from the reference point to a to-be-measured target; step S3, acquiring straight-line distance from the reference point to the to-be-measured target; step S4, calculating the relative location information from the reference point to the to-be-measured target; step S5, calculating the location information of the to-be-measured target; and step S6, transmitting the location information of the to-be-measured target to application equipment. The method and the device disclosed by the invention have the advantages that the target location information can be rapidly acquired in real time under the condition that no positioning device is arranged at the measured target or the location information cannot be acquired from the interior of the target, and the measured target cannot perceive that the location information of the target is acquired by measurer. The method and the device disclosed by the invention can be widely applied to the field of measurement of location information of targets.

The invention provides a cloud detection method of an optic remote sensing image, which comprises the following steps of: 1) diving an optic remote sensing image into basic processing units; 2) diving the basic processing units into two types which are possible to be cloud or not to be cloud according to a gray threshold; 3) diving the basic processing units which are possible to be the cloud according to fractal dimension; and 4) judging an undetermined unit in a fractal dimension dividing result to be a cloud layer or an earth object material according to angle second moment. The method combines with three judging characteristic parameters according to a reasonable order, and the different characteristic parameters have different functions when detecting, thereby not only being capable of obtaining higher resolution precision, but also being capable of obviously improving the running efficiency thereof in average meaning.

The invention discloses a single classifier anomaly detection method based on a multilayer random neural network. The the method comprises: only inputting a training data set of a normal class; through multilayer ELM-AE autoencoder and decoding processing, input sample data obtaining a reconstructed characteristic value; inputting the reconstructed characteristic value into the last layer of ELM to obtain actual output; sorting the obtained distance error vectors of the actual output and output tags from large to small, and determining a threshold for separating a normal class from an abnormalclass according to a set threshold parameter; and finally, inputting the test data into the multi-layer random neural network single classification abnormity detection model, and testing the recognition effect of the model. According to the method, main information is extracted more quickly and efficiently, dimensionality reduction is carried out, and then recognition and classification are carried out. And the speed is higher, the accuracy is higher, and the generalization performance is better. The method is not only suitable for small data sets, but also suitable for high-dimensional largedata sets, and has universality. And the method has important significance for practical application in future.

The invention provides a method of adopting the quality of transmission service in a robot operating system. The method comprises a step 1 of performing node registration, a step 2 of generating a node connection topological relation; a step 3 of generating a sent data packet; a step 4 of performing communication capability negotiation; a step 5 of configuring a QoS (quality of service) strategy; and a step 6 of carrying out QoS matching and data transmission. The invention adds a transport layer mechanism to guarantee the quality of service in the communication framework, and the data issuer and the subscriber can dynamically change the QoS strategy according to the needs of both parties; when the robot node supports the transmission mechanism of QoS, the real-time, reliability and other QoS guarantees can be increased in transmission as needed; and the current ROS node software application module is supported, and the existing software application module can be used on the communication framework without modification.

The invention discloses a flexible high-voltage DC line protection method with current correlation. Through sampling current of DC-side shunt capacitor branches and a DC line entry, Pearson correlation coefficients of current of capacitor branches at two sides of the DC system and current at the DC line entry are calculated respectively, calculated correlation coefficients at two sides are finally compared, and thus, DC line fault discrimination is realized. The protection method is simple in operation, the needed sampling frequency is low, the method is not influenced by factors such as data synchronization, a fault type, a fault position, noise interference and a control mode, inner and outer faults in the DC line area can be accurately recognized, and a fault line is protected. The protection method plays an important role in safety operation of the flexible high-voltage DC transmission system.

The invention discloses a self-adaptive spectral subtraction real-time speech enhancement method. The method comprises: establishing a dynamic threshold including discrimination of voice and no voice of noise voice, providing noise spectrum time varying update principles according to the dynamic threshold; making full use of correlation extraction information among adjacent frames, and realizing a pure voice spectrum smooth estimation method. Aimed at a practical problem that voice signals are difficult to extract in unstable noise and strong background noise, the self-adaptive spectral subtraction speech enhancement method is provided. The method uses a rapid tracking noise algorithm to perform smooth update on the unstable noise frame by frame, and can preferably estimate noise spectrums. The algorithm can effectively restrain background noise, and improves voice quality and intelligibility after noise reduction. The method is low in calculation cost, and is easy to realize, and has good real-time property. The method provides a new approach for denoising of strong background noise and detection of weak signals.

A computer implemented method and system for scheduling, the method comprises: initializing the scheduling configuration information according to the configuration instruction received by a receiving device, wherein the scheduling configuration information includes scheduling time bucket, shift, scheduling personnel and rest day type; solving the rest day set of each scheduling personnel in the scheduling time bucket according to the rest day type through a computing device, wherein the computing device performs the solving according to a preset first solving method; obtaining the working day set of each scheduling personnel through the computing device; and solving the shift of each scheduling personnel in his or her working day set according to the preset algorithm through the computing device. The automation of the scheduling method is implemented in the present application. The optimal scheduling results can be solved in the background automatically under the premise that the requirements of the scheduling configuration are met, and the solved scheduling results are sufficiently random, thus greatly reducing the complexity of scheduling and improving the efficiency of scheduling.

The invention relates to a service migration method based on a particle swarm in an edge computing environment, and belongs to the technical field of mobile communication. The method comprises the following steps: S1, modeling a server; S2, reporting a service request: equipment sends own state information to a local network controller; S3, finding out the equipment of which the delay does not meet the requirement: the local network controller estimates the delay of the equipment according to the received equipment state information and the network information collected by the state collectionmodule, and judges whether the delay requirement of the corresponding type of task is met or not; and S4, formulating a migration decision: selecting the equipment which cannot meet the requirementsfor the server, comprehensively considering energy consumption and time delay in combination with factors such as task size, task type, link stability, server state and the like, and formulating the migration decision with the maximum income. According to the invention, service migration can be triggered in real time when the equipment performance does not reach the standard, and the income of service migration is maximized while the task requirements of each piece of equipment are met.

The invention provides a solution selection type trunk green wave configuration method and system. The method comprises the steps of generating a trunk information base; analyzing trunk traffic flow patterns according to current trunk traffic investigation situation, researching an intersection grouping solution during trunk green wave control in each pattern, and generating a trunk green wave configuration solution base; acquiring real-time trunk intersection traffic flow detection parameters, analyzing a real-time trunk traffic flow running pattern by similarity assessment, selecting an appropriate intersection grouping solution from the trunk green wave configuration solution base, thus realizing the configuration of trunk green wave parameters; and transmitting the generated real-time trunk green wave configuration solution to an intersection traffic signal controller to execute the solution. The solution selection type trunk green wave configuration method and system can meet the requirements of green wave configuration for instantaneity and validity, and can guarantee trunk green wave bandwidth and optimize the overall trunk traffic efficiency.

The invention discloses an undersampled spectrum sensing method based on detection of a residual correlation matrix, and solves the problem the prior art must depends on prior information that is notprone to sense. The scheme of the invention comprises the steps of sampling an input signal; acquiring a measurement matrix A and a residual matrix V; initializing a signal recovery parameter; computing a column index value I<tau> most correlated to the current residual matrix; acquiring a middle residual matrix FORMULA; acquiring a corrected residual matrix V<tau>; acquiring a detection statisticFORMULA; computing a judgment threshold FORMULA; and comparing the detection statistic FORMULA with the judgment threshold FORMULA, to acquire a signal support set. According to the method provided by the invention, the undersampled spectrum sensing is converted into binary judgment, the iterations are controlled via residual detection, the judgment threshold is not affected by noise, the excellent detection performance still can be acquired without the prior knowledge and with the extremely low noise to signal ratio and the relatively low false alarm probability, the number of sampling timesis increased and the detection performance can be significantly improved. The method is practical, low in missing and false alarm probability and low in complexity; and the sensing performance is less affected by the noise power, so as to be relatively stable.

The invention relates to a laboratory environment and equipment wireless monitoring and alarming system, belonging to the wireless monitoring field. The system comprises n wireless probes, one base station node, one PC and a prepared monitoring program therein, one GSM module and a user mobile phone, wherein, n is a positive integer; and the wireless probes establishes alletizin with the base station node through a short distance wireless communication protocol networking, the base station node is accessed into the PC by a serial port, the GSM module is accessed into the PC by a USB interface, and the PC is used for operating the monitoring program. The system can realize reconfigurability and availability of equipment by designing the wireless intelligent probes, realize convenient system layout by a short distance wireless communication technology, realize variety and realiablity of an alrming mode by the GSM module, and realize real-time property for updating wireless probe parameters by an online parameter table synchronization technology.