1917results about How to "Real-time detection" patented technology

The invention discloses an additive manufacturing surface defect, internal defect and shape composite detection device which comprises a surface defect detection system, an internal defect detection system, a shape three-dimensional measurement system and a clamping device, wherein the surface defect detection system comprises a first CMOS industrial camera; the internal defect detection system comprises an air cylinder and a detection probe; the detection probe is used for generating a magnetic field to be close to the detected surface and establish magnetic mutual action with a workpiece to form a magnetic disturbance environment; the shape three-dimensional measurement system comprises a line laser, a light filter and a second CMOS industrial camera. The device can perform real-time and comprehensive detection on the surface defect, the internal defect and the shape three-dimensional size in additive manufacturing, transmits data to an industrial personal computer for analysis, interacts with forming milling composite route planning software, and can control a shaping device in real time to perform formation and generate a milling code and control a milling cutter to perform milling on the additive manufacturing surface.

The invention discloses a method and system for intelligently controlling temperature of concretes of a dam under construction. The system comprises a control device which communicates with a heat exchanging device and a heat exchanging auxiliary device, wherein the heat exchanging device is arranged at inner part or surface of the concrete dam, and is used for exchanging heat with the concrete dam and transmitting collected temperature information of the concrete dam to the control device; the heat exchanging auxiliary device inputs a heat exchanging medium to the heat exchanging device and outputs the medium from the heat exchanging device after the heat exchange; the control device is used for controlling the heat exchanging auxiliary device; and the control device can input a temperature control strategy of each casting bin. By the system and method disclosed by the invention, the temperature of the concrete dam can be detected in real time automatically, individualized temperature control strategies are provided to different casting bins, intelligent learning is performed according to actual conditions on site, and concrete thermal parameters which are the most accurate and realistic are selected for each casting bin, so that the precise control on water flow capacity and / or temperature can be realized, the precision for controlling the concrete dam temperature is high, the data is reliable, labour and water costs can be greatly reduced, and the anti-cracking effect of the dam is good.

The present invention relates to a space form detection device of fine-long flexible bar and its detection method. Said device is composed of fine-long flexible bar, fiber-optic grating sensor array, fiber-optic grating modulator-demodulator, local area network router, data acquisition and data processing module and display equipment. The space form detection method of fine-long flexible bar includes the following steps: utilizing a group of grating array formed from four optical fibers arranged on the fine-long flexible bar, utilizing scale factor between the off-line labeled curvature and wavelength and utilizing fiber-optic grating modulator and demodulator to measure wavelengths of 20 raster points in five discrete points of fine-long flexible bar in the space so as to obtain the space curvature size and direction of discrete point position, then utilizing data processing module to reconstruct the form of said fine-long flexible bar in space. Said device can be used for making real-time tracking detection of human body cavity channel and fine-small vessel forms in the therapeutic process.

The invention discloses a multiple dimensioned convolution neural network-based real time human body abnormal behavior identification method. A convolution neural network is used for replacing a conventional feature extraction algorithm, and the convolution neural network is improved so as to satisfy requirements for human body behavior classification; specifically, three dimensional convolution, three dimensional down-sampling, NIN, three dimensional pyramid structures are added; human body abnormal behavior feature extraction capability of the convolution neural network is enabled to be increased; training operation is performed in a specific video set, features with great classification capacity can be obtained, robustness and accuracy of a whole identification algorithm can be improved, GPU speed is increased so as to satisfy requirements for practical application, and therefore multi-channel videos can be monitored in real time.

The invention discloses a multi-information fusion based fatigue driving detecting method. A fatigue driving detecting system used in the method comprises a signal collection module, a signal processing module and an alarming module, wherein the signal collection module collects signals relative to fatigue, the signal processing module quantizes fatigue levels of a driver, extracts feature parameters which can reflect fatigue states of the driver, performs fuzzy clustering on the feature parameters, and real-timely detects the fatigue states of the driver, and the alarming module timely performs alarming when the driver is determined to be in fatigue driving. The multi-information fusion based fatigue driving detecting method consists of a plurality of steps of signal collection, fatigue level quantization and signal processing, feature parameter extraction, and fatigue determination and alarming. The fatigue driving detecting system is vehicle-mounted, has non-compulsivity, and is capable of performing real-time determination and high in determination accuracy.

A method for detecting radar mobile object of single channel synthetic hole diameter based on multivision sub image pair includes forming multiple symmetric sub image pairs by multivision image of synthetic hole diameter radar data, forming each sub image pair by two subvision images, utilizing subvision image cancellation to accumulate cancellation result by two - dimensional united means along position and distance directions for effectively suppressing background clutter interference as well as for realizing energy accumulation of mobile object then applying constant false alarm technique to finalize detection on mobile object.

The invention discloses a method and device for detecting defects and failures of a high-speed rail based on vibration signals, belonging to the technical field of railway safety monitoring and protection. The invention solves the problem that the operating efficiency of a train is seriously influenced when a current measurement device detects the defects and failures of the high-speed rail. The method comprises the following steps of: 1, acquiring a vibration signal of the high-speed rail by a vibration acceleration transducer, carrying out experience mode decomposition on the vibration signal, and acquiring n IMF (Intrinsic Mode Function) components and one residual error; 2, calculating a correlation coefficient ui (i=1, 2, ......, n) of the n IMF components acquired in the step 1 and the acquired vibration signal, and selecting the IMF component, the correlation coefficient ui of which is larger than a threshold lambda, as defect and failure feature information IMF; 3, respectively calculating power spectral density of the defect and failure feature information IMF acquired in the step 2; and 4, determining defect and failure parts of the high-speed rail according to the power spectral density of the defect and failure feature information IMF acquired in the step 3, and finishing the detection of the defects and failures of the high-speed rail.

The invention discloses a safety helmet real-time detection method based on a convolutional neural network. The method comprises the following steps: decoding a video in a multi-thread I frame extraction mode; realizing end-to-end safety helmet and face real-time detection through a YOLOv3 convolutional neural network algorithm. Provided is a method for judging whether to wear the safety helmet ornot based on the safety helmet and human face real-time detection result. For a person who does not wear the safety helmet, face recognition is realized through a FaceNet algorithm so as to carry outintelligent voice reminding on the person. And a channel pruning and quantifying method is adopted to compress the model, so that the integration of the model on the SoC system is more facilitated. According to the method, the respective advantages of YOLOv3 and FaceNet are combined, the problem of accurate end-to-end detection of the safety helmet worn in real time in the video stream is solved,real-time detection of wearing of the safety helmet in the video stream is realized, and whether a worker wears the safety helmet according to regulations or not can be monitored in real time to reduce the safety risk.

The invention relates to a robot motion estimation method based on dense optical flow. The method comprises the steps of calibrating inner parameters and outer parameters of a camera, collecting image sequences and conducting distortion correction, solving the dense optical flow through the polynomial expansion method, purifying light flow, conducting coordinate transformation between image coordinates and robot coordinates, and estimating the motion speed of a robot. The robot motion estimation method based on the dense optical flow solves the problems that in the prior art, motion estimation precision is not high, robustness is poor on the conditions that illumination is uneven and motion is vague, and the function of the camera is restricted. According to the robot motion estimation method based on dense optical flow, the dense optical flow algorithm based on polynomial reduction is introduced, so that the precision of motion estimation is improved. The RANSAC algorithm is applied to the optical flow purification process, so that the robustness of the algorithm is improved. The monocular camera is used, and a lens is arranged downwards in an inclined mode, so that a robot is made to detect the condition ahead in real time, and convenience is brought to completion of tasks such as avoiding barriers and planning paths.

The invention discloses an intelligent power grid IT asset safety monitoring system based on distributed scheduling. The system comprises multiple acquisition servers, multiple system servers and multiple database servers, wherein the acquisition servers are used for acquiring the IT asset data information and comparing the acquired IT asset data information to find vulnerability, the system servers are used for distributing received detection tasks to each acquisition server, and the database servers are used for realizing storage, update, query and statistics of a vulnerability database, a target database and a vulnerability detection result database. The system is advantaged in that through constructing a distributed database, establishing a detection cluster and realizing distributed degree scheduling, distributed operation and analysis in a real sense are realized, and high-efficiency safety monitoring on intelligent power grid IT assets is accomplished.

The invention relates to a molecular imprinting photonic crystal for detecting glucose, which belongs to the technical field of applied chemistry and clinical analysis test. A method comprises the following steps: firstly, inserting a substrate subjected to hydrophilic treatment into PMMA colloidal pellet solution, and self-assembling pellets on the substrate to obtain a three-dimensional photonic crystal template; secondly, dripping molecular imprinting pre-polymerization solution on the edge of the three-dimensional photonic crystal template, and thermally polymerizing the template; and finally, cleaning the glucose imprinting template to obtain a glucose molecular imprinting photonic crystal template. The molecular imprinting photonic crystal has specific glucose adsorption performance, enables direct observation of the change, and fulfills the aim of real-time, quick and convenient detection.

Belonging to the technical field of laser detection, the invention relates to a novel laser spectroscopy induced detection system, especially to a molten steel component online detection system, which is obtained by gathering lasers on a molten steel surface and conducting analysis through induced plasma spectroscopy. The laser spectroscopy induced online molten steel component detection system includes: a concave reflecting mirror, a convex reflecting mirror, a window mirror, a casing pipe, a steel furnace, a computer, a detection point distance dynamic monitoring system, a feedback regulation control device, a laser light source, a light beam turning system, an echelle spectrometer, an integral delay detection system, a laser beam quality control system and the like, and can realize accurate detection of manganese, magnesium, sulfur, carbon and other 20 components contained in molten steel. The detection system provided in the invention can realize real-time detection of molten steel components, reduce the smelting cost, and save resources.

The invention provides a cigarette smoke detection method based on video monitoring. The method is divided into a classifier training phase and a cigarette smoke detection phase. In the classifier training phase, geometrical characteristics and Hog characteristics of all prepared positive and negative sample sets are extracted, a support vector machine is used for training the extracted characteristic vectors, and a classifier is generated; and in the cigarette smoke detection phase, firstly, a Gaussian mixture model is utilized to obtain a foreground motion region from a video image obtained by a monitoring camera, then noisy points and cavities are removed by means of morphological filtering, projection histograms in X and Y directions are counted according to the characteristics of cigarette smoke, a precise interested region is obtained, finally characteristics of the interested region are extracted and combined into characteristic vectors, the characteristic vectors are input into the classifier, and whether the interested region has cigarette smoke is judged. The method provided by the invention has the advantages that the interference resistance is high, the detection sensitivity is high, the false alarm rate is low, the cigarette smoke can be recognized in realized, the position of the cigarette smoke is determined, and the cigarette control work of indoor public places is facilitated.

The invention provides a stereoscopic vision system and the application thereof to real time monitoring of a three-dimensional safety warning area. The stereoscopic vision system comprises a computerized binocular stereoscopic vision system designed by imitating human eyes; two groups of binocular cameras are respectively placed outside two orthogonal planes in a stereoscopic space being monitored, namely the three-dimensional safety warning area, so as to observe the same object; two groups of disparity maps are respectively obtained through a stereoscopic matching module; the depth and the position information of the object are computed, namely two groups of space coordinates comprising depth maps are respectively computed in a real time manner; and the application steps comprise the determination of elevation angles of the binocular cameras, the conversion of a coordinate system and the delimitation of the three-dimensional safety warning area. Functions of real-time monitoring of the space coordinates of objects inside and outside the three-dimensional safety warning area, and real-time warning when the object to be monitored exceeds the restriction and the constraint of the area, namely the distances from the point of the object to the planes of the three-dimensional safety warning area are smaller than the safety distance are successfully realized, the limitation existing when three-dimensional space information of the object is detected by a single group of binocular cameras is effectively overcome, and the monitoring effect is remarkably improved.

The invention provides an underground positioning and safety monitoring system on the basis of a communication network, which comprises a ground control center, a plurality of personnel positioning terminals, a plurality of short message positioning terminals, a plurality of voice communication positioning terminals, a plurality of wireless positioning base stations and a base station gateway. The personnel positioning terminals carry out timing on broadcast signals by broadcast bands; the base station gateway or the wireless base stations receive the broadcast signals, acquire contents and the signal strengths of the broadcast signals, encapsulate information according to a protocol, transmit the information to the ground control center by the network for positioning processing, and acquire corresponding position information; meanwhile, a mobile node adopts a timing POLL mechanism to receive a downlink command of a data center so as to realize bidirectional data transmission, and a network base station controls illumination equipment to realize energy-saving production according to existence or non-existence of the mobile node in a current region. The underground positioning and safety monitoring system has the characteristics of high reliability, simplicity in construction and accuracy in position.

The invention relates to a quick blind source separating fetal electrocardioscanner and a detection method. The electrocardioscanner comprises a dual channel acquisition and analog-to-digital conversion module, an FPGA provided with an internal storage, a DSP and an ARM for separating a blind source, and an output device, wherein the dual channel acquisition and analog-to-digital conversion module is electrically connected with a common electrocardiogram lead cable and the FPGA through two data channels; the FPGA is electrically connected with the DSP through two data channels; the DSP is also sequentially electrically connected with the ARM and the output device ; and the DSP and the ARM are all externally connected with a program storage and a data storage. The electrocardioscanner adopts a high-speed acquisition and processing structure, detects fetal electrocardiosignals in aliasing electrocardiosignals in real time, adopts a blind source separation method to solve the problem that time domains and frequency domains of mother electrocardiosignals and the fetal electrocardiosignals are mutually overlapped and difficult to separate, and extracts the fetal electrocardiosignals efficiently and accurately for diagnosis.

The invention provides a test platform of a drive system of an electric vehicle motor. The test platform comprises an industrial personal computer, a dynamometer system, a voltage / current sampling circuit, a torque / rotating speed sampling circuit and a power supply simulation system. When the test platform works, a road situation simulation system is used for reproducing real acceleration and deceleration conditions of vehicle driving; a load simulation, tracking, and controlling system based on model prediction control is used for realizing rapid response and precise tracking and controlling on load simulation by the dynamometer system; and then a performance analysis system is used for realizing comprehensive performance testing and analysis of the motor drive system. The test platform provided by the invention is capable of detecting the motor performance in real time to obtain data needed by drive motor studying and developing timely and effectively, so that the research and development time of the drive motor can be shortened. Therefore, the test platform plays an important role in leading standardized and information development of motor testing.

The invention relates to a co-phasing control device and control method for a spliced telescope.The device comprises a spliced telescope body, a first beam splitter, a wavefront detector, a second beam splitter, a translation error detector and a wavefront controller, wherein the first beam splitter receives emergent rays and generates first divided beams and second divided beams; the wavefront detector detects the first divided beams and obtains system aberration data and wavefront distortion aberration data of transmission paths of all spliced sub mirrors; the second beam splitter receives the second divided beams and generates third divided beams and fourth divided beams; the translation error detector detects the third divided beams and collects dispersion interference fringes between each pair of spliced sub mirrors; the wavefront controller is connected with the wavefront detector, the translation error detector and a driver of a secondary separating deformable mirror.By means of the co-phasing control device and control method for the spliced telescope, real-time detection and compensation and correction of translation, inclination and higher order aberration can be effectively achieved, and compared with the technology in a current similar system, better accuracy and instantaneity are achieved.

The invention relates to a mine gas beam tube monitoring system, comprising an automatic sampling device which consists of a gas path switching electromagnetic valve and a suction pump. The gas path switching electromagnetic valve is connected with a partial channel through a sampler and a single-core beam tube of a moisture separator and then a conduit head through a partial beam tube cable and is controlled by a programmable controller after a main beam tube cable is connected with a moisture separator box. The system is characterized in that the monitoring system also comprises an automatic sampling device which is composed of a sample making device. The sample making device consists of a non-oil injection pump and a conversion electromagnetic valve controlled by the programmable controller, a shunting needle-shaped valve with an emptying end, a dryer, a filtering device, a quantitative tube and a single-core beam tube of a flow meter which are successively connected through an automatically sampling pipe. The automatic sampling device is connected with a gas chromatography detection device for analyzing and outputting data to a computer. The computer controls the programmable controller and outputs detection results. The dryer and the filtering device are provided with long service life. The measuring point number extension is convenient and can be maintained easily. The cost is low. The sampling device samples steadily. The precision of detected gas is high. A recognition method for the gas explosiveness and the fire hazard is disclosed. The decision according to the analysis result is clear and prompt.

The invention discloses a video smog fine classification method based on a color model and motion characteristics, comprising steps of differentiating and constructing a color model on the basis of a gauss mixing model and a background, detecting a motion pixel point and performing initial screening, obtaining a motion object connected region, extracting a motion changing characteristic, setting a threshold and determining whether a suspicious smoke area exists, performing pre-processing on the suspicious smoke area, extracting a SIFT characteristic on the basis of an image block, combining with an SVM optimization random forest algorithm, performing training based on the suspicious smoke area image block and thus realizing the fine classification of the fire hazard smoke, the cigarette smoke, the water vapor, etc. The video smog fine classification method based on color model and motion characteristics performs video smoke detection based on the color model and the motion characteristic and by targeting the fine classification, realizes real-time fast smoke detection, effectively eliminates the interference having similar effect interference sources with the fire hazard smoke, and improves the detection efficiency and accuracy.

The invention discloses a high-resolution intelligent network camera array system with global synchronization function. The system adopts global synchronization signals to realize the synchronous acquisition of a camera array, comprises at least two intelligent network cameras used for image acquisition, wherein the working mode of one camera is configured as a main mode, while the other cameras are configured to be in a slave mode; the main-mode camera produces and provides global horizontal synchronization signals and vertical synchronization signals for the slave-mode cameras; and every intelligent network camera is connected with a central computer through a network and is used for receiving control commands in real time and transmitting image data so as to realize distributed computing function. The system has the advantages of satisfying the real-time high-performance processing for acquired data, realizing the global synchronous shooting of the camera array, supporting large-scale array expansion, realizing the control of the central computer over a plurality of working modes of the intelligent cameras and realizing high-resolution video-image data shooting.

The invention relates to an intelligent stage lighting cloud terminal controlling system. The intelligent stage lighting cloud terminal controlling system comprises a large dimming cabinet, a network transmission device, a cloud decoder and a cloud terminal distributor. The large dimming cabinet receives parameter information of light, codes and packs the parameter information, and then sends the parameter information to the cloud decoder through the network transmission device, the cloud decoder unpacks and decodes the received information, and then transmits the received information to the cloud terminal distributor, the cloud terminal distributor is used for controlling each stage light, stage lights send working state information to the cloud decoder through the cloud terminal distributor, the cloud decoder codes and packs the working states, and then sends the working states of the stage lights to the large dimming cabinet through the network transmission device, and the large dimming cabinet conducts unpacking and decoding on the state information and then conducts changing, storing and displaying on the state information. The intelligent stage lighting cloud terminal controlling system can monitor working states of the stage lights in real time, circuit information can be set in a remote mode, and safety is improved.

The invention discloses a target detection recognition algorithm based on 3D (Three-dimensional) trajectory analysis. In the method, a binocular camera installed above the rear door of a bus is used for collecting a video image to carry out target detection recognition, the motion positions of the same passenger at different moments are taken as movement targets, the motion targets are subjected to preliminary recognition through the depth map of a video screen image, then, a pseudo-motion target is removed, and finally, the accurate detection recognition of the motion target is realized. Through the 3D trajectory analysis, target recognition detection is carried out, trajectory tracking failure caused by illumination in a trajectory tracking process in the prior art is solved, and the accuracy of target recognition detection is improved. The target detection recognition algorithm is free from the restriction of a hardware environment, can carry out real-time detection and is high in detection accuracy. The two-dimensional trajectory of the image of the motion target is converted into a 3D trajectory under a world coordinate system, the most common problem in traditional target recognition that the target can not be detected since the target is covered is solved, and the accuracy of the target recognition detection is improved.

The invention provides a foggy day detecting method based on an image color spatial feature. The method comprises the following steps of first step, obtaining a background picture through a video image or a single image; step 2, performing color space conversion for the background picture, and extracting the color space feature: firstly performing color space conversion for the background picture, converting from an RGB (red-green-blue) color space into an HSV (hue, saturation, value) color space, and extracting the features of various components of the HSV according to the information included image; and step 3, dividing the weather information included image into a non-foggy day, a little foggy day and a dense foggy day according to the identification conditions: at first, if the identification condition 1 is met, the weather is the dense foggy day, otherwise the identification is continued; secondly, if the identification condition 2 is met, the weather is the non-foggy day, otherwise, the identification is continued; and finally, if the identification condition 3 is met, the weather is the little foggy day, otherwise, the weather is the dense foggy day. The method provided by the invention is suitable for being used for monitoring the foggy day in expressways, particularly pre-warning the emergency of agglomerate fog in partial road segments, thus, the safe road driving can be ensured.

The invention discloses a parking lot stall monitoring system based on a radio frequency identification technology and a working method of the parking lot stall monitoring system. The parking lot stall monitoring system mainly comprises a radio frequency identification reader, a radio frequency identification external antenna, a radio frequency identification tag, and a background radio frequency signal processing server. The background radio frequency signal processing server also comprises a stall real-time detection engine and a stall navigation display interface. In the system, whether a stall has a vehicle or not and whether a vehicle is parked safely in place or not can be sensed by arranging an appropriate radio frequency identification tag array in a space and utilizing the characteristic that a wireless radio frequency signal which is reflected by the tag is attenuated after being shielded by a ferromagnet, so that the data reference can be provided for a parking lot management system. The invention provides a mechanism for automatically detecting an empty stall with low cost, so that a navigation mechanism can be provided for searching the stall, the quantity and the position of the empty stall can be displayed in real time through an interference-friendly way, and whether the vehicle is parked safely or not can be detected.

The embodiment of the invention discloses a face shielding detection method and device, electronic equipment and a storage medium. The technical scheme provided by the embodiment of the invention comprises the steps of extracting a video stream of a camera, extracting a video image from the video stream, carrying out face detection based on the video image, determining a corresponding face image,carrying out face key point detection on the face image, determining corresponding face key point information, and carrying out region division on the face image according to the face key point information to obtain a plurality of corresponding face region images, further inputting the face region image into a pre-trained face shielding detection model to perform face shielding detection, and outputting a face shielding label corresponding to the face region image, wherein the face shielding label comprises corresponding shielding level and shielding object information. By adopting the technical means, the face shielding condition can be accurately detected in real time, so that the face shielding prompt can be conveniently carried out, and the use experience of a user is optimized.

The disclosed on-line detection coil for silicon steel magnetic performance comprises: from inside to outside, a frame with cavity matched size of product line, a measurement coil, the isolation layer, an excitation coil. This invention needs not special sample to reduce detection cost and improve real-time detection effect.

The invention pertains to the technical field of image processing and pattern recognition, and the invention discloses a pedestrian fast detection method based on videos. Human positive samples are collected in an actual scene in two modes including the automatic mode and the manual mode to train a human star detection template in a particular scene; video monitoring images are acquired and image pretreatment is performed so as to perform appropriate compensation on illumination mainly; treatment is performed on time domain information of an image moving object to extract the foreground region of the moving object; the pyramid layering range is determined according to the size of the foreground region to judge the foreground region whether needs to be fused, and the pyramid layers are redivided; matching is performed between the trained pedestrian template and the processed image to determine the pedestrian position; and fusion optimization is performed on the pedestrian position to select the optimal pedestrian position and mark the pedestrian. The method of the invention is suitable for the field of tracking of a plurality of human objects in different scenes to satisfy the detection robustness and real-time performance requirements at the same time.

The invention provides a moving target detection method with an adjacent frame difference method and Gaussian mixture models combined. The method includes the following steps that (1) an image sequence is obtained, wherein the image sequence comprises a current-frame image and a previous-frame image; (2) the current-frame image is divided into a temporary moving area and a temporary background area by the utilization of the improved adjacent frame difference method; (3) matching is performed on the two areas generated in the step (2) through the Gaussian mixture models, the two areas are divided into different areas according to matching results; (4) different updating is performed on the Gaussian mixture models in the different areas; (5) final moving target areas are determined according to the areas generated in the step (3). Gradient comparison and median filtering are added in the improved adjacent frame difference method, and the boundary and the anti-noise-interference capability of a moving target are highlighted. The adaptability to background and foreground conversion of the Gaussian mixture models is improved through changes of the updating rate of the Gaussian mixture models. The detection result of the method alleviates the problem of cavities generated through the adjacent frame difference method, and problem of the shadow generated by the fact that a background object is converted into a moving object suddenly is eliminated.

The embodiment of the invention provides a method and device for detecting driving behavior information based on an OBD (on-board diagnostic) terminal. The OBD terminal integrates a triaxial accelerometer; the triaxial accelerometer is used for measuring one group of or multiple groups of triaxial accelerated speeds; the method comprises the following steps: calculating the one group of or multiple groups of triaxial accelerated speeds as one group of or multiple groups of actual accelerated speeds; sequentially adopting the one group of or multiple groups of actual accelerated speeds to perform direction calibration, and working out one group of or multiple groups of direction vectors and a group of or multiple groups of turning vectors; judging whether the ratio of the direction vectors to the turning vectors exceeds a preset threshold so as to determine the corresponding driving behavior information. According to the invention, the driving behavior can be detected in real time, and the detecting accuracy can be improved; in addition, the installation of the OBD terminal does not affect the attractive appearance and the manipulation of a vehicle by a driver, so that the OBD terminal is plug-and-play, the OBD terminal application is simplified, initialization positioning is reduced or avoided, and the user experience is further improved.