85results about How to "Reliable data base" patented technology

The embodiment of the invention discloses a vision localization method and device. In the method, according to a preset camera device, a preset scene is shot to obtain image data; on the one hand, according to first feature points of an image and spatial feature points in a semantic space map, vector information matching is conducted, and a first matching point set is obtained; on the other hand,second feature points, containing second semantic information, in the image data are extracted, the second feature points and the spatial feature points are subjected to semantic information matching,and a second matching point set is obtained; according to the first matching point set and the second matching point set, the target pose information and the target position information of the presetcamera device are obtained. In the method, the texture information and the semantic information of the image are utilized at the same time to extract the feature points, more feature points which aresuccessfully matched with the spatial feature points in the semantic space map can be found in the image data, a more reliable data basis is provided for calculating the target pose information and the target position information of the preset camera device, and the localization precision is higher.

A high-low-temperature high-pressure adsorption and desorption testing device comprises an inflation system, a deflation system, an adsorption system, a desorption system, a temperature control system and a data collection system. The inflation system comprises a methane inflation unit and a helium inflation unit. The deflation system comprises a vacuum pump, a vacuum container and a vacuum gauge. The temperature control system comprises a high temperature unit and a low temperature unit. The adsorption system comprises a high temperature adsorption unit and a low temperature adsorption unit. The desorption system comprises a water drainage metering device, an electronic scale and a desorption gas flowmeter. The data collection system comprises a computer and a control unit. According to the high-low-temperature high-pressure adsorption and desorption testing device, test operations are easy and convenient, the test precision is high, adsorption and desorption tests under different pressures on the high-temperature and low-temperature conditions can be simulated respectively, real-time, accurate and automatic collection of test data is achieved, the more reliable data basis is provided for research on coal gas absorption and desorption rules, and the great practical significance is achieved for efficient gas exhausting, mining and utilization.

Provided are a servo measuring testing system and method for coal sample gas adsorption and desorption. The system comprises a gas supply device, a vacuumizing device, a gas adsorption device, a gas desorption measurement device and an electric control device; the gas supply device comprises a high-pressure gas tank and a gasing tank; the vacuumizing device comprises a vacuum pump and a vacuum meter; the gas adsorption device comprises a coal sample tank, and the gas desorption measurement device comprises a water storage container, a water collection container, an electronic balance, a servo motor, a fixed support and a water guide pipe. According to the servo measuring testing system and method for coal sample gas adsorption and desorption, volume measurement of desorbed gas is converted into volume measurement of liquid water, test operation is easy and convenient, test data is accurate, and real-time precise automatic collection and real-time display of the test data are achieved; in addition, it is guaranteed that the gas desorbed from a coal sample is under the condition of one atmospheric pressure, and a more reliable data basis is provided for researching the coal-mass gas adsorption and desorption rule.

A traffic information extraction and calculation-based method for processing data of license plates comprises four steps: step (1), a vehicle license plate recognition database is established in a computer at a background processing center; step (2), vehicle license plate data, the starting point and the destination of which are designated by a user is initially matched, and a vehicle travel time testing database is established in the computer at the background processing center; step (3), information granules of a route designated by the user is structured, and ambiguous route noises in the vehicle travel time testing database are eliminated according to computer operating procedures, and then a vehicle travel time database of the designated route is acquired; and step (4), by the computer operating procedures, information granules of travel time are structured, and vehicle travel time noises in the vehicle travel time database are eliminated, and then precise travel time is acquired. The method can improve the accuracy of the vehicle travel time data, has important practical value in the field of intelligent transportation, and can be widely applied to situations such as traffic management, monitoring, law enforcement, electronic toll collection, and traveler information service.

The invention discloses a hybrid electric vehicle speed reducer load spectrum compilation method, medium and equipment, and the method comprises the steps: obtaining vehicle load data, carrying out the preprocessing, and carrying out the classification according to a power source mode and a road working condition; calculating the load data characteristic parameters according to the classification result, determining the optimal sample number of the hybrid electric vehicle under various working conditions, further determining the speed reducer torque load samples under various road working conditions, and obtaining the optimal sample loads of an engine and a driving motor on a speed reducer after superposition; carrying out the rain flow counting statistics on the optimal sample load of the speed reducer through a rain flow counting method to obtain a rain flow matrix, obtaining an extrapolated rain flow matrix after extrapolation, namely, a full-life two-dimensional load spectrum of the corresponding automobile speed reducer, and finally, after the two-dimensional load spectrum is converted into a one-dimensional load spectrum, adopting a load spectrum compilation method, and generating a load spectrum of the speed reducer of the hybrid electric vehicle. The speed reducer load spectrum compilation can be carried out on the hybrid electric vehicle under the changeable and complex working conditions.

The embodiment of the invention discloses a method and device for predicting stopping accuracy in the precise stopping stage during ATO control. The method comprises the steps that according to recorddata, corresponding to a first running process of a target train, in various sub-systems of a train control system, target record data of the precise stopping stage during ATO control is extracted; characteristic values of all characteristics in a characteristic element set corresponding to a running path are calculated through the target record data, and a first characteristic value combinationis obtained; the first characteristic value combination serves as an input parameter of a pre-trained prediction model, the stopping accuracy of the target train in the first running process is predicted through the prediction model. The prediction model is obtained through machine learning and training, automatic prediction of the stopping accuracy is achieved, and dependence on work experience is got rid of. The prediction model is obtained through training of a lot of training samples, and the prediction model has a reliable data foundation, so that the prediction result is high in interpretability and reliability.

The invention discloses a discrete manufacturing workshop material dynamic distribution system and method based on an intelligent perception network. The discrete manufacturing workshop material dynamic distribution system comprises an intelligent perception platform, a data processing module, an application service module and a PC terminal; the intelligent perception platform collects material information of a workshop, remaining quantity information of materials in a station cache area, consuming quantity information of the materials in the station cache area per unit time and position information of material tools, distribution personnel and distribution vehicles in real time, and the collected information is transmitted to the data processing module; the data processing module convertsthe format of the received data into a format which can be identified by the application service module and transmits the data to the application service module; and the application service module transmits the received information to the PC terminal of management personnel, and an improved ant colony algorithm is used for calculating a group of optimum distribution routes. According to the discrete manufacturing workshop material dynamic distribution system and method based on the intelligent perception network, uncertain factors in the distribution process of the materials are reduced, thedistribution procedures of the materials in the workshop are optimized, the response capacity of the workshop towards elastic requirements of the materials is improved, and the distribution efficiencyis improved.

Provided is a recovery and tracing method for missing data of daily electric quantity. The method comprises the following steps: acquiring user information and electric energy meter information and monthly electric quantity data thereof; obtaining daily electric quantity data of each user according to a daily electric quantity rule; examining daily electric quantity in each month and finding out the daily electric quantity which needs to be recovered in each month; adopting two multiple-imputation models based on different algorithms to recover the daily electric quantity which needs to be recovered in each month and obtaining a recovery data set; and comparing obtained daily monthly electric quantities of users with monthly electric quantities corresponding to the recovery data set and taking the recovery data set with the minimal deviation ratio as a best result set. The recovery and tracing method for missing data of daily electric quantity has the following advantages: by recovering missing value of daily electric quantity, data quality of daily electric quantity is improved, which truly reflects the real condition of daily electric quantity of each user; the method provides areal and reliable data base for the study related to electricity utilization behaviors of users; and data is recovered by the two multiple-imputation models based on the different algorithms so that accuracy of data recovery is improved.

The invention provides an image output method and an output system of a most positive face based on a multi-camera array. The method comprises the following steps of: acquiring a plurality of face images of a current face captured by a multi-camera array at a time; analyzing a rotation angle of a current face in each of the face images, and selecting a face image from which the rotation angle is the smallest; judging whether the rotation angle of the current face in the newly acquired face image is smaller than the face image with the smallest rotation angle when the multi-camera array tracksthe current face; if yes, the newly acquired face image replaces the selected face image with the smallest rotation angle until the current face leaves the tracking range, and the final face image isoutput as the most positive face image of the current face. The invention selects the most positive face image acquired by the multi-camera array based on space and time, and outputs the most positiveface image with more accuracy, thereby providing more reliable data basis for subsequent face comparison.

The invention discloses a static target restraining method for a ground surveillance radar system. The static target restraining method for the ground surveillance radar system comprises the steps that processed target detection information of the front end of a radar is obtained; interframe accumulation processing is carried out on the target detection information, and a two-dimensional image isformed according to the target detection information after the accumulation; edge extraction is carried out on the two-dimensional image, and target detection information which belongs to a same target after the extraction is obtained; static target area judgment processing is carried out on the target detection information which belongs to the same target, and a static target area range is markedout; and restraining processing is carried out on the target detection information in the static target area range, and target detection information after the static target restraining is obtained. According to the static target restraining method for the ground surveillance radar system, the problem that the ground surveillance radar system cannot accurately mark off the static target area due to variation of detection scenes and erecting sites is solved, the restraining speed of a static target and the detection precision of a moving target are improved, and a reliable data foundation is provided for subsequent track processing.

The embodiment of the invention discloses a method and device for adjusting point cloud data. A specific embodiment of the method comprises the steps of obtaining first point cloud data collected fora bridge floor and second point cloud data collected for a bridge bottom surface corresponding to the bridge floor; carrying out plane fitting on data points in the second point cloud data, and determining a fitted plane; determining a cross section type of a bridge corresponding to the bridge floor based on the fitted plane, the cross section type of the bridge being used for indicating a heightassociation relationship between the bridge floor and the bridge bottom surface; and according to the determined height association relationship between the bridge floor and the bridge bottom surfaceindicated by the cross section type of the bridge and the fitted plane, adjusting components indicating the height in the first point cloud data and the second point cloud data, and generating adjusted matching point cloud data. According to the implementation mode, matching of the bridge floor point cloud data and the bridge bottom surface point cloud data in the height direction is achieved. Furthermore, an accurate and reliable data basis can be provided for manufacturing a high-precision map near the flyover.

The invention discloses a natural crack identification method and system based on micro-electrode logging data. The method comprises a step of determining substrate resistivity characteristics of a crackless formation, a step of obtaining resistivity characteristics of a cracked formation and determining resistivity response characteristics of the cracked formation, a micro-electrode logging resistivity crack identification threshold, a micropotential and a microgradient crack resistivity differential threshold, a step of carrying out flex point analysis on a micro-electrode logging resistivity curve, obtaining micro-electrode logging resistivity flex point data, and extracting a depth position of crack development; and a step of identifying a crack according to the substrate resistivity characteristics of the crackless formation, the micro-electrode logging resistivity crack identification threshold, the micropotential, the microgradient crack resistivity differential threshold and the micro-electrode logging resistivity flex point data and calculating a logging response index of the crack. According to the method and the system, the recognition and evaluation of a single crack are achieved, the uncertainty factors of a traditional method are reduced, the precision is improved, and a reliable data basis is provided for the three-dimensional crack modeling of a cracked oil andgas reservoir.

The invention discloses a landslide depth inversion method using InSAR elevating track deformation data, and the method comprises the following steps: S1, carrying out the processing of an elevating track radar image of a landslide region through employing a time sequence InSAR technology, and obtaining the time sequence deformation data of the landslide region; s2, according to the time sequence deformation data, the spatial geometrical relationship of the landslide area and DEM data, obtaining two-dimensional deformation data of the landslide surface in the slope direction and the normal direction through calculation; and S3, constructing a landslide depth inversion model based on two-dimensional deformation under a mass conservation criterion, and calculating the landslide depth inversion model according to the two-dimensional deformation data to obtain an inversion calculation result of the landslide depth. The method is suitable for successfully extracting and obtaining the landslide mass of the InSAR deformation field of the ascending and descending orbit of the satellite, in addition, the landslide depth can be subjected to significant image inversion through the rheological parameters of the slope body substances, and the reliability and applicability of the method are significantly improved through the accuracy of the parameters.

The invention discloses an actual pupil distance measuring method, device and equipment based on a monocular camera. According to the concept, a plurality of reference points and a monocular camera are preset, specific imaging parameters are extracted from a plurality of images when a driver gazes at each reference point, camera parameters and reference point position parameters are then combined,the actual distance between the midpoint of two pupils of the driver and the camera is obtained, a pupil distance value corresponding to each image is solved based on the actual distance and each parameter, all pupil distance values based on a plurality of reference points and a plurality of images are obtained in the way, and finally rigid body parameters, namely real pupil distance characteristic information of the driver, of the driver individual is calibrated and saved through a preset pupil distance standard and all the pupil distance values. High-precision pupil distance information ofa driver individual can be obtained based on a low-cost monocular camera, and a reliable and accurate data basis is provided for subsequent human eye positioning operation.

The invention provides a line parameter double-end testing system and method based on GPS synchronization, and the system and method can effectively achieve the synchronous measurement of data parameters of head and tail ends of a power transmission line. The structure of the system comprises a head end machine and a tail end machine. The head end machine comprises a first CPU, a first GPS module, a testing power module, a first wiring conversion module, a first A/D conversion module, a first signal conditioning module, and a first voltage and current sensor. The tail end machine comprises a second CPU, a second GPS module, a second wiring conversion module, a second A/D conversion module, a second signal conditioning module, and a second voltage and current sensor. The method comprises the steps: testing power outputting, wiring reverse rotating operation, the transmission of time data and pulse per second through the GPS modules, data collection, data storage, and data calculation.

The embodiment of the invention provides an industrial Internet data security monitoring method based on a block chain. The method comprises the following steps that the block chain acquires a homomorphic tag corresponding to monitoring data through an intelligent contract; the block chain opens the access permission of the intelligent contract to an authorization verifier, so that the verifier can obtain the homomorphic tag and send challenge information generated according to the homomorphic tag to the cloud; the block chain opens the access permission of the intelligent contract to the cloud, the cloud can acquire the homomorphic tag and send the certificate generated according to the homomorphic tag and the challenge information to the verifier, so that the verifier can perform comparative analysis according to the certificate to judge whether the integrity of the monitoring data is damaged or not, and a reliable data basis is provided for industrial Internet data security monitoring. The embodiment of the invention further provides an industrial Internet data security monitoring system based on the block chain. According to the invention, reliable protection can be provided for data security of the industrial Internet.

The invention discloses a network anomaly detection method and device applied to network equipment. The method comprises the steps of: acquiring network flows of a NetFlow protocol and an sFlow protocol respectively; extracting a plurality of fields from the acquired NetFlow network flow and sFlow network flow respectively, and fusing the plurality of fields extracted respectively to generate a network flow of a preset format; and performing multi-dimensional anomaly detection on the network flow of the preset format. The method and the device can improve the comprehensiveness of network anomaly detection.

The invention provides a method and device for quickly identifying a seismic phase by using a controllable vibrating source to excite seismic signals. Fractional order Fourier transform is used to fastly identify the seismic phase of the linear frequency modulation seismic signals excited by the controllable vibrating source, linear properties of traditional Fourier transform are inherited, interference of cross terms in time-frequency analysis can be suppressed, time-frequency distribution characteristics of the linear frequency modulation seismic signals excited by the controllable vibratingsource can be improved, a pulse function is taken as an analysis object, a signal-to-noise ratio of the seismic phase can be improved, and a reliable data foundation can be provided for geological interpretation when the seismic phase is identified.

The invention relates to an intelligent tooth brushing process evaluation method, which comprises the following steps that: 1) tracking a tooth brushing process of a standard Bass tooth brushing method, and collecting a denoising signal output by a GY-521 gyroscope in an electric toothbrush; 2) checking a data interval preprocessed and labeled in S1), and if the interval time of data is shorter than t seconds, according to the time interval of t seconds, solving a mean value in the period of time; 3) training an evaluation model based on a random forest; and 4) preprocessing the data of a person who brushes teeth according to a sensor data processing method in S1), and using a trained random forest model to classify the toothbrush state of the person who brushes teeth at different moments.The method has the beneficial effects that a machine learning method is adopted to classify the tooth state of the toothbrush in each time slice in a user tooth brushing process, the tooth brushing state of the user at different moments in the tooth brushing process can be predicted, and the tooth cleaning state and strength of the user at different moments can be accurately judged.