562 results about "Distance threshold" patented technology

The invention relates to the technical field of data processing, and discloses a multi-data fusion method and system in airport station safety supervision and a medium. The method comprises the following steps: based on a target feature matrix, judging potential conflicts through a set safety distance threshold and a speed threshold, and constructing a risk assessment index in combination with historical risk event data to obtain a safety risk score; according to the security risk score, establishing a spatial association relationship and a risk propagation relationship between the apron targets, calculating regional risk density through a risk accumulation effect, and generating real-time security situation data; and for the real-time security situation data, calculating a target function value of security control, and setting a security constraint condition for optimization solution to form a control strategy parameter. According to the invention, effective fusion of multi-source heterogeneous data is realized, accurate awareness of the security situation of the station level is constructed, and an optimized management and control strategy is generated based on situation information, so that the accuracy and real-time performance of security supervision of the station level are improved.

The invention provides an industrial visual anomaly recognition method, system and device based on multi-modal feedback and a medium, and belongs to the technical field of industrial visual detection.The method comprises the steps that a production line video stream is collected in real time, an ROI is automatically segmented, a picture sequence is generated, features of a set dimension are extracted, and the features of the set dimension are extracted; comparing a preset dynamic distance threshold with a feature library, and preliminarily identifying an abnormal image; a cue word of a detection requirement is constructed, the cue word and abnormal related information are input into the multi-modal large model, and a determined abnormal image is output; using the determined abnormal image to construct a data set to train a target detection model, and adjusting the learning rate in the training process; and inputting pictures captured in an industrial scene into the deep learning model, the multi-modal large model and the target detection model in sequence to obtain a recognition result, feeding back the recognition result to a user for confirmation, adding the recognition result to the data set, and optimizing training of the target detection model. According to the invention, accurate identification of abnormal images in industrial production is realized, and the identification efficiency is high.

The invention relates to the technical field of river section measurement, in particular to a river measurement data preprocessing method based on artificial intelligence. The method comprises the following steps: obtaining river section measuring point data, and carrying out measuring point density evaluation on the river section measuring point data based on different scales and section elevation changes so as to obtain high-density measuring point data; performing section thalweg point and turning point identification based on adjacent measuring point slope change on the high-density measuring point data, and performing measuring point thinning processing of retaining thalweg points and turning points so as to obtain a retaining measuring point data set; according to the preset section line and the reserved measuring point data set, the measuring points exceeding the preset measuring point deviation distance threshold value are automatically detected and calibrated, coordinate reconstruction and position correction are conducted on the measuring points deviating from the preset section line, and therefore calibrated measuring point data are obtained. The problems of uneven data, missed measurement and deviation in traditional measurement can be effectively solved, and river channel measurement data are more accurate and complete.

The invention discloses an Internet of Things card anomaly detection method and system based on an improved K-means algorithm. The method comprises the following steps: S1, collecting and preprocessing feature data of an Internet of Things card; s2, performing clustering analysis on the preprocessed feature data by using an improved K-means algorithm; s3, calculating a distance threshold value of abnormal judgment according to a clustering result; and S4, judging whether the to-be-detected Internet of Things card is abnormal or not according to the threshold value. The system comprises a data preprocessing module, a clustering analysis module and an anomaly detection module. The invention aims to provide an efficient and intelligent anomaly detection method for the use behavior of the Internet of Things card through an improved K-means algorithm, and by automatically identifying the abnormal use behavior of the Internet of Things card in different application scenes, the accuracy of management and safety monitoring is improved, and malicious abuse and illegal behaviors are reduced.

The invention relates to the technical field of safety monitoring, and particularly discloses an operation safety distance management method based on laser radar point cloud data, and the method comprises the steps: generating a dangerous point cloud set based on an initial three-dimensional point cloud model of a complete field environment; performing coordinate transformation on the point cloud data currently collected by the three-dimensional laser radar equipment based on the rigid body transformation matrix to obtain current point cloud data; registering the current point cloud data with the initial three-dimensional point cloud model and identifying all independent dynamic targets; determining a danger approaching trend of each independent dynamic target based on the motion prediction trajectory of each independent dynamic target; determining a dynamic safety distance threshold value of each dangerous dynamic target based on the danger approaching trend and the response delay of each independent dynamic target and the additional safety distance of the corresponding dangerous source area; triggering a corresponding alarm mechanism based on the dynamic safety distance threshold and the distance between the point cloud set of each independent dynamic target and the dangerous point cloud set; and the overall safety of a working site is improved.

The invention discloses a high-precision plane fitting method for a multi-noise point cloud, and the method comprises the steps: carrying out the plane rough fitting of an original point cloud after down-sampling, taking the longest side of a minimum bounding box of a lower sampling point cloud as a distance threshold value, and calculating the distance weight of each point through a weight mathematical model, then, plane fine fitting is carried out on the weighted down-sampling point cloud, the distance weight of each point is updated after each fitting, plane fitting is carried out on the point cloud of which the weight is updated again, and a fine fitting plane of the down-sampling point cloud is calculated in an iterative manner; and finally, calculating the distance weight of each point in the original point cloud based on the fine fitting plane and the iterated distance threshold value, performing plane fitting on the weighted original point cloud in an iteration mode, and finally obtaining the fine fitting plane of the original point cloud. According to the technical scheme, the method is high in stability and low in calculation amount, can obtain a high-precision fitting plane in a weighted iteration mode under the condition of more noise, and is suitable for different types of point cloud data.

According to the transformer substation construction safety distance monitoring method, device and equipment and the storage medium provided by the embodiment of the invention, the three-dimensional target detection model is established through the obtained point cloud data of the transformer substation, and the first three-dimensional target detection is carried out based on the three-dimensional target detection model so as to detect whether the electrified equipment exists in the to-be-monitored area; and under the condition of determining that the electrified equipment exists in the to-be-monitored area, obtaining three-dimensional position information corresponding to the electrified equipment, dividing a risk area based on the three-dimensional position information, and then performing secondary three-dimensional target detection based on the three-dimensional target detection model so as to detect whether an invader exists in the risk area. When the condition that an invader exists in the risk area is determined, the type of the invader is further judged, namely whether the invader is an invader or a construction machine is judged, and finally the Euclidean distance between the electrified equipment and the invader is calculated based on the boundary information; and if the Euclidean distance exceeds a preset distance threshold, outputting alarm information based on the category information.

The invention discloses an anomaly detection method based on global reachability density and an adaptive threshold mechanism, which comprises the following steps: collecting single-index historical water quality monitoring data of a target monitoring station, extracting a subsequence with a fixed length through a sliding window mode, constructing a neighbor index structure and extracting neighborhood information, acquiring a k neighbor set of each data point; respectively calculating the local accessibility density of each data point in the local neighborhood of the data point; respectively calculating the global reachability density of each data point; performing statistical summary on GRD values of all data points in the sample set, calculating a mean value and a standard deviation of the GRD values, and defining a dynamically adjusted distance threshold value based on a variable coefficient; and an abnormal score function fusing local and global density features is further constructed, and abnormal point determination is realized according to a distance threshold. The method is suitable for complex time sequence water quality monitoring data, can effectively improve the recognition accuracy of weak anomalies, local drifts and extreme abrupt changes, and has high universality and robustness.

The invention relates to the technical field of data processing, in particular to an engineering quality early warning method and system based on data mining, and the method comprises the steps: obtaining a historical parameter time sequence of an engineering transformer, and inputting the historical parameter time sequence into a time sequence model to obtain a prediction parameter time sequence; taking a plurality of dimension parameters at the same moment as a data point, calculating a Manhattan distance between any data point and other data points, and taking the data points with the Manhattan distances smaller than a set distance threshold as neighborhood data points of the any data point; and calculating an abnormal score of the any data point by using an improved local abnormal factor algorithm, and if the data point whose abnormal score is higher than a set score threshold is an abnormal data point, determining that the moment corresponding to the abnormal data point is an abnormal moment, and performing early warning. According to the invention, the problem of insufficient accuracy and applicability during engineering quality supervision is solved.

The invention discloses a multi-level hybrid obstacle avoidance control method adaptive to environment complexity, and relates to the technical field of robot control, and the method comprises the steps: obtaining the global map information of an inspection environment, dividing a map into grid units, marking static obstacles, and calculating a global path of an inspection robot from a starting position to a target position through an A * algorithm; position and speed information of a dynamic obstacle is obtained in real time through a laser radar, a gravitational field model and a repulsive force field model are established, a gravitational field is generated by a target point, and a repulsive force field is generated by the detected dynamic obstacle. According to the invention, by establishing an obstacle classification mechanism based on the distance threshold, quantitative evaluation of the threat degree is realized, and the problem of low control efficiency caused by adopting a unified processing strategy for all obstacles in a traditional method is avoided.

The invention relates to a radar working mode open set identification method and device for a double-path auto-encoder, and the method comprises the steps: inputting a to-be-identified sample into a trained DA network, and obtaining a to-be-identified feature vector; wherein the DA network is obtained by training according to a training data set and a mixed loss function; the training data set is obtained according to an original pulse sequence; the mixed loss function is constructed according to a cross entropy loss function, a center loss function and a reconstruction loss function; calculating the distance between the to-be-identified feature vector and the known category feature center to obtain a first distance; wherein the known category feature center is obtained by inputting a training data set into a DA network for training; and obtaining an identification result of the to-be-identified sample according to the first distance and a distance threshold. According to the method, the distinguishability of different radar working modes is improved through the DA network, and the DA network has good generalization and robustness in a complex non-ideal scene through the mixed loss function.

The invention discloses an electrical pin position deviation detection method and system and electronic equipment, and belongs to the technical field of visual processing, and the method comprises the steps: determining a reference region and a reference point, and then determining a standard template used for aligning and matching an image through the reference region and the reference point in a standard workpiece; after a detection image is obtained, an alignment area is determined according to the corresponding position of a reference area in a reference template in the detection image, then the position of a first detection point is determined in the detection image by taking the alignment area as a reference according to the relative position relation between the reference area and a reference point, and the first detection point is a point aligned with the reference point in the detection image. The reference point is also a reference point for position offset judgment; image elements are determined, a second detection point is determined in the detection image based on the image elements, and the second detection point is a target point for position deviation judgment; whether the electrical pin has position offset is determined by determining whether the distance between the first detection point and the second detection point is beyond a distance threshold.

The invention discloses an intelligent e-commerce user abnormal behavior detection method and system. The method comprises the steps of data acquisition, data preprocessing, data processing and e-commerce user abnormal behavior detection. The invention belongs to the field of anomaly detection, and particularly relates to an intelligent e-commerce user abnormal behavior detection method and system, and the method comprises the steps: filtering a part of abnormal behaviors in advance through designing low-fluctuation users, sudden abnormal users and diverse abnormal users; based on design distance measurement, the similarity of user behavior sequences is measured, and secondary optimization is carried out on the centroid, so that the adaptability of the centroid to user behavior distribution is improved; the accuracy of final user abnormal behavior detection is improved; by designing a dynamic distance threshold and multi-dimensional feature evaluation, comprehensively considering the user behavior data, and dynamically adjusting an anomaly detection threshold according to the distribution characteristics of the user behavior data, an abnormal user is accurately identified, the misjudgment risk is reduced, and the detection accuracy is improved.

A method, computer program product, and computing system for processing a dataset of query-answer pairs. Synthetic variations of queries are generated and each of the synthetic variations of queries are mapped to a corresponding answer from the dataset. An embedding dataset is generated by transforming the synthetic variations into synthetic query embeddings and the queries into query embeddings. A first set of embeddings is defined for storage in a semantic cache and a second set of embeddings are defined and are not stored in the semantic cache. A separate distance threshold is assigned to each embedding of the first set of embeddings and a pairwise distance between each query and the synthetic variations is determined. Distance thresholds for respective pairwise distances between a query and synthetic variations of the query are generated. Subsequent queries are processed using the semantic cache and the distance thresholds.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes of medical health, financial science and technology, leasing and the like, and discloses an operation authenticity verification method, which comprises the following steps: executing operator identity verification, and generating a verification record; starting a countdown mechanism, and monitoring terminal position information; when the initial verification distance accords with a first preset distance threshold value, generating a job permission instruction and receiving task data; acquiring real-time position information of the terminal, and determining a submission verification distance; when the submitted verification distance accords with a second preset distance threshold value, a verification passing timestamp is extracted, and a time effectiveness state is generated; and when the state is valid, storing the task data and the space-time verification information. According to the invention, identity verification and position verification are combined to ensure that an operator executes a task at a target location; the countdown mechanism limits the operable time after identity verification, so that the equipment is prevented from being transferred to others for use; the timeliness verification mechanism ensures that the data submission time is reasonable, and the authenticity and safety of task execution are improved.

The embodiment of the invention provides an underground pipeline extraction method, system and device based on point cloud and a storage medium, and belongs to the technical field of point cloud space geometry extraction. According to the scheme, underground pipeline point cloud data are obtained; segmenting the pipeline point cloud data to obtain a segmentation result; when the segmentation result is a single-pipe scene, principal component analysis and cylinder fitting are carried out based on all pipeline point cloud data to obtain a normal vector and a pipeline radius of each data point; performing plane cutting according to the normal vector to obtain a tangential plane, and obtaining a pipeline center line based on the tangential plane; determining a distance threshold parameter according to the radius of the pipeline; based on the distance threshold parameter, performing segmented straight line fitting on the pipeline center line through a random sampling consistency algorithm to obtain a center line point set; performing feature extraction on the center line point set to obtain feature points; determining a connection relationship of adjacent feature points according to the geometrical relationship; the pipeline reconstruction model obtained based on the connection relation can be suitable for complex scenes, and the calculation efficiency is improved.

The invention discloses an underground mine 4D millimeter wave radar ghosting noise automatic marking method and system. The method comprises the steps that first laser radar point cloud data and first 4D millimeter wave radar point cloud data are aligned at the same time reference through a timestamp nearest neighbor matching method, and a time synchronization data pair is obtained; according to the method, the function of accurately identifying and marking the ghosting noise of the 4D millimeter wave radar by combining the high-precision characteristic of the laser radar is realized, the marking efficiency is greatly improved, the marking cost is reduced, the function of detecting the ghosting noise in a mode of combining a distance threshold method and a clustering analysis method is realized, and the accuracy of the ghosting noise of the 4D millimeter wave radar is improved. The detection speed is guaranteed, the marking precision is improved, various complex conditions in the underground mine environment can be handled without depending on a specific signal model and an environment hypothesis, the safety and stability of a mine automation system are improved, remarkable economic and social benefits are achieved, and the method is suitable for being widely popularized and used.

A wireless transmit receive unit (WTRU) is configured to receive configuration information for reporting Global Navigation Satellite System (GNSS) assistance information (AI). The configuration information comprises a reporting trigger threshold that is at least one of a distance threshold or a time offset threshold. The WTRU determines that the reporting trigger threshold is exceeded and reports GNSS AI. The GNSS AI comprises at least one of a GNSS validity duration or a GNSS acquisition time. The GNSS validity duration comprises an indication of a time duration associated with a validity of a GNSS acquisition, an indication of a time duration associated with expiration of the GNSS acquisition, or a WTRU location associated with the GNSS acquisition. The GNSS acquisition time comprises a time to acquire a GNSS position.

A method for updating a reference position based on a non-terrestrial network (NTN) by a user equipment (UE) in a wireless communication system may include: acquiring reference position related information from a base station; and determining whether a distance between the UE and a reference position is less than a distance threshold based on the reference position related information, if the distance between the UE and the reference position is less than the distance threshold, not performing a measurement for cell reselection, and if the distance between the UE and the reference position is greater than the distance threshold, not performing a measurement for cell reselection. If so, performing a measurement for cell reselection; and if the distance between the UE and the reference location is less than the distance threshold, performing a reference location update based on a reference location related timer.

A text processing method, which is executed by means of a computer device. The method comprises: acquiring source text to be processed, wherein the source text comprises a plurality of tokens (S501); on the basis of a relative distance between paired tokens in the source text, determining a relative position code corresponding to the relative distance between the paired tokens, and obtaining position code information comprising the relative position code (S502); acquiring a distance threshold value, determining from the position code information a first relative position code that corresponds to a relative distance exceeding the distance threshold value, and calling a text processing model to map the first relative position code in the position code information to a position code range of the text processing model, so as to obtain mapped position code information (S503); and calling the text processing model to perform semantic understanding on the source text on the basis of the mapped position code information, so as to generate semantically associated text for the source text (S504).

The invention discloses a distance measurement method and device based on target width and electronic equipment, and relates to the field of automatic driving, and the method comprises the steps: collecting an image in front of a vehicle, and recognizing a target in the image; determining a first target distance corresponding to the image; when the first target distance is smaller than a distance threshold value, judging that the first target distance is an estimated distance corresponding to each frame of image, and determining a target measurement width corresponding to each frame of image according to the first target distance, the focal length and the pixel width of the vehicle tail; performing fusion updating on the target measurement width corresponding to the current frame image and the previous frame image to obtain the updated target measurement width; when the updating frequency is greater than a frequency threshold and a first target distance corresponding to the subsequent frame image is greater than a distance threshold, determining a second target distance corresponding to the subsequent frame image; and fusing the first target distance and the second target distance corresponding to the subsequent frame image to obtain an estimated distance corresponding to the target in the subsequent frame image. According to the method, the inter-vehicle distance measurement precision is improved.

Aspects of the present disclosure are directed to triggering object transitions between near-field and far-field regions in an artificial reality environment. For example, the near-field region can be within arm's length for the user, while the far-field region can be greater than arm's length from the user. Objects can be displayed within these regions such that the user can interact with the objects in the artificial reality environment. A field manager can cause a displayed object to transition from the near-field region to the far-field region and / or from the far-field region to the near-field region. The field manager can compare sensed user movements to one or more trigger criteria (e.g., distance threshold(s), velocity threshold(s), etc.) to trigger transition of an object between field regions.

The invention relates to a method and a device for generating a video with a body and electronic equipment. The method comprises the following steps: analyzing a task instruction and initial environment observation data, generating a key operation step sequence and an associated object set thereof, and constructing a three-dimensional physical constraint graph; generating an initial action video sequence based on the coding condition; in response to single-frame action execution, calculating a spatial error index, and if the object contact distance deviation, the trajectory collision probability or the physical constraint violation value exceeds a preset threshold, triggering the space-time diffusion model to generate a correction frame based on the current physical constraint graph; in response to the completion of the key operation steps, verifying the semantic matching degree of the generated result and the task target, and if the key object attribute loss or the operation logic error is detected, regenerating the task operation step sequence and the physical constraint graph; and updating the object position, the distance threshold and the motion feasible region in the physical constraint graph, and inputting the space-time diffusion model. According to the method, the problems of physical consistency deficiency, error accumulation and semantic understanding splitting are solved.

The invention discloses a method for detecting gluing defects and a storage medium thereof, and relates to the technical field of gluing detection.The method comprises the following steps that S10, a line laser sensor scans a gluing workpiece to obtain a gluing workpiece point cloud, and scans an unglued standard workpiece to obtain a standard template workpiece point cloud; s20, fitting to obtain a reference plane of a workpiece point cloud of a gluing workpiece point cloud standard template, and intercepting a gluing to-be-detected area point cloud and a template to-be-detected area point cloud; s30, point cloud registration is carried out on the point cloud of the gluing to-be-detected area and the point cloud of the template to-be-detected area; s40, performing point distance threshold judgment on the point cloud of the to-be-detected gluing area after registration, and performing separation to obtain a pure colloid point cloud; and S50, judging that the point cloud of the pure colloid in the region is unqualified according to the fact that the cross section width and the cross section area of the point cloud of the pure colloid are smaller than a preset threshold value. According to the invention, the gluing defect can be detected more accurately, and the efficiency is high.

The present application relates to the field of information retrieval, and in particular relates to a data processing method, an electronic device, a readable storage medium, and a program product. In the method, when a query result of a query vector needs to be searched in a constructed graph index, neighbor nodes of at least some nodes among multiple nodes included in the graph index satisfy at least one of the following: the included angle between two vectors obtained by subtracting a node from any two neighbor nodes of the node is greater than or equal to a first angle threshold value, the distance between any two neighbor nodes of the node is greater than or equal to a first distance threshold value, and the number of neighbor nodes of the node within a preset space range is smaller than a first number. Thus, the neighbor nodes of the nodes in the constructed graph index are relatively dispersed in space, and the problem that a query result falls into a local optimum due to being unable to find nodes at a certain portion of space during a node-based neighbor node search process, because the nodes are densely distributed at a certain position, is avoided.

The invention discloses a communication method and a related device, and the method comprises the steps: distinguishing different tracks / adjacent regions according to the coverage condition of an actual adjacent region, and providing different distance thresholds for controlling whether terminal equipment starts the measurement of the track / adjacent region or not, different track / neighbor cell adaptations are distinguished, and different distance thresholds are provided to control whether the terminal device uses the track / neighbor cell as the target cell for cell reselection, so that the communication performance is improved.

The invention provides a belt tearing detection method and device based on three-dimensional vision. The method comprises the steps of calculating a spatial distance value between each target point and an adjacent point in three-dimensional point cloud data in a direction perpendicular to a tangential direction of a laser arc, screening points of which the spatial distance values exceed a preset distance threshold value, forming an initial candidate point set, starting from each point, expanding a space through a breadth-first search algorithm, and obtaining a target candidate point set, calculating the length and depth of each connected domain; and taking the connected domain meeting the threshold condition as a corresponding potential crack, forming a potential crack set by the spatial position information of all the potential cracks, and generating a belt tearing detection result containing the spatial position information of the real crack and the corresponding alarm level. According to the technical scheme provided by the invention, high-precision dynamic identification and alarm of the surface crack of the belt are realized, the false detection rate is effectively reduced, and the industrial safety monitoring efficiency is improved.

A method of updating, by a user equipment (UE), a reference location based on non-terrestrial networks (NTN) in a wireless communication system may include acquiring reference location related information from a base station; as an operation of determining whether a distance between the UE and a reference location is less than a distance threshold based on the reference location related information, not performing measurement for cell reselection if the distance between the UE and the reference location, and performing the measurement for the cell reselection if the distance between the UE and the reference location is greater than the distance threshold; and performing reference location update based on a reference location related timer if the distance between the UE and the reference location is less than the distance threshold.

The invention provides a GIS buffer generation method and system based on fuzzy semantics and geographic constraints, and belongs to the technical field of geographic information systems.The method comprises the steps that fuzzy descriptors, membership values and geographic entity types are input into a pre-trained language-space mapping model, and basic distance parameters are obtained; querying a spatial database based on the geographic entity keywords, obtaining geometric features associated with the geographic entities, and calculating feature lengths corresponding to the geometric features; correcting the basic distance parameter based on the intention direction, the membership value, the geographic entity type and the feature length expressed by the fuzzy description word to obtain a geographic distance threshold; generating an initial two-dimensional buffer polygon based on the geographic distance threshold and the spatial geometric features of the geographic entity; and querying a digital elevation model to obtain topographic data based on the initial two-dimensional buffer region polygon, and generating a three-dimensional buffer region curved surface through a gradient sensitive interpolation algorithm. According to the invention, the accuracy of generating the GIS buffer area is improved.

A method in an illustrative embodiment includes determining that a first object authenticated by an electronic device is accessing the electronic device. The method further includes, in response to a second object being detected within a detection range using a radar of the electronic device, determining, based on a detected signal, that the second object is a person. The method further includes determining a distance and an angle between the second object and the electronic device based on an azimuth signal in the detected signal. The method further includes in response to determining that the distance is less than a distance threshold and the angle is less than an angle threshold, determining, based on the biological feature signal, whether the second object is trustworthy. The method further includes deauthenticating the first object in response to determining that the second object is untrustworthy.