715 results about "Group detection" patented technology

The invention relates to the technical field of unit detection, in particular to a unit magnetic variable on-line monitoring method and system, and the method comprises the steps: carrying out the multi-source data collection through a sensor, carrying out the correction of the multi-source data through a multi-dimensional calibration mechanism, synchronizing a timestamp through a dual-synchronization system, and carrying out the frequency-band-divided conditioning and standardization processing; environmental noise in the standardized multi-source data is eliminated through an intelligent algorithm, feature vectors are extracted, and purified feature vectors are obtained; screening effective abnormal features through an isolation forest algorithm; and inputting the effective abnormal features into an LSTM prediction model to obtain a corrected prediction value, substituting the corrected prediction value into a logistic regression formula to obtain a fault prediction probability of fault occurrence, calculating a health degree score, and performing graded early warning according to the health degree score. According to the scheme, through multi-dimensional calibration, working condition adaptive feature extraction and graded early warning, the unit monitoring data precision, the fault feature recognition accuracy and the operation and maintenance decision efficiency are improved.

Systems, apparatus, articles of manufacture, and methods to utilize cached generative artificial intelligence responses are disclosed. An example apparatus includes interface circuitry to access a request to a generative artificial intelligence model, computer readable instructions, and programmable circuitry to at least one of execute or instantiate the instructions to replace a named entity within the request with a generic tag to generate a modified request, tokenize the modified request to create an array of tokens, detect a similar prior request based on the array of tokens, and after detection of the similar prior request, cause output of a cached response to the request without execution of the generative artificial intelligence model.

A method includes obtaining a first attack sequence comprising at least a first attack phase, a second attack phase, and a third attack phase. The method further includes determining that a first number of alerts generated for the first attack phase based on a set of detection operations and a second number of alerts generated for the third attack phase based on the set of detection operations satisfy a threshold criterion. The method further includes determining that a third number of alerts generated for the second attack phase based on the set of detection operations fails to satisfy the threshold criterion. The method further includes determining that the set of detection operations is to be modified to detect future malicious activities corresponding to the second attack phase.

The invention provides a linear dimension measurement method and device for the total length of a road guardrail stand column, and relates to the field of linear dimension measurement, the device is deployed on a detection vehicle, and comprises a control module, a ground penetrating radar measurement module, a 3D camera measurement module, a sensor module, a lower computer and an upper computer; according to the invention, accurate data acquisition is realized through multi-module cooperative control, and the lower computer is combined with the AI image recognition technology to realize accurate acquisition of contour data; the lower computer transmits radar original data (reflected waves and diffracted waves) and 3D contour data (column cap space coordinates) to the upper computer, the upper computer achieves data fusion through a hierarchical velocity model (time-depth conversion) and a coordinate system mapping algorithm (3D-road coordinate system), and the accuracy of the total length measurement error is greatly improved compared with that of single module detection. The method solves the problems of low efficiency, large destructiveness and poor accuracy of traditional manual detection, and has the advantages of method innovation and engineering landing.

The invention relates to the technical field of material strength detection, and discloses material strength detection equipment for file cabinet production, the material strength detection equipment comprises a machine base, a detection table arranged on the machine base and a hydraulic cylinder vertically arranged on the detection table, the output end of the hydraulic cylinder is provided with an outer frame, and at least three groups of detection assemblies are arranged in the outer frame; and each group of detection assembly comprises a plurality of groups of adjusting blocks, a connecting column fixed with the adjusting blocks, a mounting seat fixed with the connecting column, a butt joint seat detachably connected with the mounting seat, and a pressure applying head fixedly connected with the butt joint seat. According to the material strength detection equipment for file cabinet production, the detection assembly, the first adjusting mechanism and the second adjusting mechanism are arranged, pressure applying heads are arranged to be in a mutually compact state, a more concentrated load can be provided for a to-be-detected material, and the pressure applying heads which are originally compactly arranged are unfolded at equal intervals in the front-back direction of the outer frame, so that the material strength detection efficiency is improved. Pressure is applied to a plurality of front and back positions of the to-be-detected material, so that other different stress distribution conditions are provided.

The invention relates to the technical field of unit detection, and discloses an intelligent fault self-diagnosis method for an evaporative condensation integrated screw water chilling unit, which comprises the following steps of: decoupling operation data of a compressor through a blind source separation algorithm, performing image processing on operation data of a condenser in combination with a morphological analysis method, and performing fault diagnosis on the operation data of the condenser; the operation characteristics of the compressor and the operation characteristics of the condenser can be extracted respectively, effective decoupling and clear expression of coupling signals are realized, and by constructing a dual-channel LSTM network comprising a gating fusion unit and introducing a cross-channel coupling gating mechanism, the system reliability is improved. The dynamic coupling relation between the compressor and the condenser can be modeled and regulated in the time dimension, the coupling mechanism between the compressor and the condenser is truly reflected, the time sequence parameter sequence is input into the pre-trained deep LSTM network, the fault types such as control lag and performance degradation can be accurately recognized, and the fault diagnosis accuracy is improved. Therefore, the accuracy and real-time performance of fault diagnosis are improved, and the requirement for intelligent fault management of the water chilling unit is met.

The invention provides a low-illumination target detection method and system fusing multi-scale features and local detail enhancement. The system comprises a feature extraction network based on a multi-pooling pyramid and cross-stage double-mixed attention, a dynamic detail semantic fusion pyramid network and double groups of detection heads. The feature extraction network based on the multi-pooling pyramid and the cross-stage double-mixed attention comprises a convolutional layer, a C2PSA module, an MPSPPF module and a CSP-EDHAN module; the dynamic detail semantic fusion pyramid network is used for fusing shallow high-frequency details and deep semantic information through top-down and bottom-up multi-scale feature fusion and introducing a surface detail fusion module into multiple scales, so as to output a fused feature map; the double groups of detection heads adopt a decoupling detection branch design, and the position and the category of a target are directly predicted on a fused feature map. The method can remarkably improve the precision and robustness of target detection in a low-illumination environment, and is suitable for the fields of night monitoring, automatic driving, security and protection and the like.

An embodiment intrusion detection system for detecting intrusions in an in-vehicle network includes a message queue module configured to store network messages collected from the in-vehicle network in a message queue, a memory configured to securely store a ruleset comprising a set of detection rules used in a plurality of detection techniques, a rule engine configured to apply the plurality of detection techniques to the collected network messages to detect security events and configured to determine a severity score and a reliability score for each detected security event, and an interface manager configured to transmit detection reports to a remote backend server in response to detection of the security events.

The invention discloses a nuclear power plant fault diagnosis method and device, and the method comprises the steps: collecting nuclear power plant data, training and constructing an edge end model group and a cloud model group according to the nuclear power plant data, and the nuclear power plant data comprises operation regulations, real-time operation data and historical operation data; deploying the edge end model group to an edge computing node near equipment in a plant, and deploying the cloud end model group to a cloud platform; inputting the real-time operation data of the nuclear power plant into the edge end model group, detecting a fault type, reconstructing sensor parameters if the fault type is sensor abnormality, and uploading an abnormality report to the cloud platform if the fault type is system abnormality, and reasoning and tracing the abnormal report through the cloud model group, and pushing fault information and a decision scheme.

The invention relates to the technical field of impurity gas detection control, and discloses an impurity detection control method and system for high-purity oxygen, and the method comprises the steps: arranging a plurality of groups of TDLAS detection probes and temperature vibration monitoring units, and obtaining a spectrum harmonic signal and temperature and vibration data; the concentration is inverted through wavelength modulation spectrum demodulation and temperature and pressure disturbance compensation; pCA fusion denoising processing is executed through the edge calculation unit, and correction concentration is output; and abnormity is judged through a multi-scale dynamic threshold mechanism and linkage control is carried out. Compared with a common single-point probe or traditional low-pass filtering in the prior art, the technical problem that interference between impurity concentration change and environmental disturbance cannot be effectively handled especially in a high-vibration and high-temperature-difference environment is solved. According to the invention, through multi-channel cooperative weighting, PCA fusion compensation and a dynamic threshold determination mechanism, accurate detection control of the high-purity oxygen conveying pipeline in an industrial environment is realized, and the automation level of pipeline impurity gas detection control is improved.

The invention relates to a high-speed surface material scanning detection motion control device, and relates to the technical field of detection of high-speed produced surface materials, the high-speed surface material scanning detection motion control device comprises a protective shell, stand columns are arranged in the two sides of the protective shell, an upper cross beam is connected to the upper portions of the middles of the two stand columns, and a lower cross beam is arranged at the bottom of the upper cross beam; driving cavities are formed in the two sets of stand columns, driving rods are connected to the middles of the driving cavities through bearings, a driving mechanism is arranged in the middle of the driving cavity on one side, and the driving mechanism comprises a fixing box, a worm gear, a worm and a servo motor; the two groups of detection probes can be driven by the driving mechanism to do reciprocating translational motion, so that scanning detection of a face material is realized, and the two groups of transmission belts are driven by the driving rod to synchronously rotate, so that the motion trail synchronism of the upper and lower groups of detection probes is consistent, the detection precision is improved, and the detection efficiency is improved. And a water cooling system and an air cooling system are matched with each other for cooling.

Multi-timescale Doppler processing and associated systems and methods are provided. In one example, a receiver receives radar return data, where the radar return data is associated with reflections, from a scene, of a plurality of transmitted radar signals. The radar return data is processed to obtain a plurality of sets of detection data, where each set of detection data of the plurality of sets of detection data is associated with a respective processing size. Target data associated with the scene is generated based at least in part on the plurality of sets of detection data. Related systems and methods are also provided.

The invention provides a TBM tunneling tunnel vault settlement automatic measurement alarm device and an operation method, the TBM tunneling tunnel vault settlement automatic measurement alarm device comprises an arch-shaped frame, a plurality of groups of support arms are uniformly distributed on the arch-shaped frame, and each group of support arms extend outwards along the radial direction of the arch-shaped frame; the arched plates are arranged at intervals along the upper circumferential side of the arched frame; the plurality of groups of detection units are arranged on each arched plate at intervals along the length direction of the arched plate, and each detection unit comprises a mounting part detachably connected with the corresponding arched plate, a trigger part movably arranged on the mounting part, and a reference part arranged on the mounting part; and the alarm unit comprises a sensor arranged on the mounting piece, and an alarm and a power supply system which are electrically connected with the sensor. The triggering piece synchronously moves along with the settlement of the vault, the settlement of the vault can be visually observed on the basis of the reference piece, and manual intervention is not needed in the whole process; the sensor senses abnormal movement of the triggering piece in real time, and once the abnormal movement exceeds a safety threshold value, the alarm immediately gives an alarm.

The utility model provides a detection device suitable for wafer bearing piece levelness detection, the detection device is arranged on the periphery of a wafer bearing piece in the horizontal direction so as to detect the levelness of the wafer bearing piece, the detection device comprises at least one detection assembly, the detection assembly comprises a laser emitting element and a laser receiving element which are oppositely arranged, and a detection light beam emitted by the laser emitting element is propagated above the wafer bearing piece along the horizontal direction. Based on the detection assembly in the detection device, whether the levelness of the wafer bearing part meets the requirement can be rapidly and conveniently measured according to whether the laser receiving element can receive the detection light beam emitted by the laser emitting element, and the levelness detection and calibration efficiency of the wafer bearing part is effectively improved. And the bearing assembly and the multiple groups of detection assemblies are arranged, and / or the detection device and the wafer bearing piece are rotatably arranged, so that the detection efficiency is further improved.

The invention provides a remote sensing building group depth detection and change intelligent evaluation method for urban planning, and the method comprises the steps: carrying out the multi-modal data collection of a target urban region, and carrying out the standardization processing, abnormal value elimination, multi-modal alignment and interference suppression processing, and obtaining a multi-modal data set; constructing a multi-branch hybrid network, and performing triplet feature extraction on the multi-modal data set through the multi-branch hybrid network to obtain a building group fusion feature map; performing change area detection and change type classification on the two building group fusion feature maps with different time phases to obtain building group change information; and constructing a dynamic evaluation index based on the urban planning core demand, and performing building group change evaluation in combination with the building group change information. According to the method, through multi-source and multi-modal data acquisition and processing, multi-branch hybrid network triplet feature extraction and change detection and dynamic evaluation index application, urban planning core requirements are adapted, and building group detection precision and change evaluation effectiveness are improved.

The invention relates to the technical field of electronic control system testing and diagnosis, and discloses a high-precision control module detection and data analysis system and method, and the system comprises a data collection and excitation execution module which is used for carrying out data interaction with a tested control module and applying an excitation signal; the dynamic divergence calculation module is used for calculating the dynamic divergence representing the internal dynamic relation deviation degree of the tested control module according to the real-time state data of the tested control module and by comparing with a preset reference state space tensor; and the predicted deviation degree calculation module is used for calculating the predicted deviation degree between the actual state and the predicted state of the tested control module according to a preset state observer model. According to the method, a closed-loop self-adaptive test framework is adopted, active exploration is carried out by taking maximization of dynamic divergence as a target, deep faults which are difficult to expose in a conventional test and are caused by dynamic coupling failure can be efficiently found, and the depth and coverage rate of fault detection are greatly improved.

The invention relates to the technical field of digital block assessment, and discloses a digital block assessment method based on big data, which comprises the following steps: designing a block building digital twin model, scanning a block by using a panoramic scanning device and making a 3D model, displaying scanning data on the 3D model by a control terminal, and completing independent sub-region division marking on the block. Detecting environmental conditions in the block, performing simulation analysis on detection data of the plurality of groups of detection sensors, evaluating current hardware operation conditions of the block, monitoring pedestrian flow, traffic flow, flowing vendors and other flowing objects in the block, and judging whether conflicts or safety risks exist in the current block; according to block planning requirements, by combining block buildings and business district layout, assessment of possible fire-fighting risks, obtaining of fire guidance schematic diagrams and assessment of fire-fighting equipment and routes, fire-fighting setting of blocks is completed, block fire inspection and fire-fighting routes are pointed out, and block fire-fighting safety is guaranteed.

A bot detection service associated with an overlay network operates to score traffic as a probability of being a bot, as opposed to returning a binary classification (i.e., bot or human). According to the approach herein, scoring is determined through probability estimates, wherein a score (the probability) is based on considering a set of detections concurrently. In one embodiment, all (or substantially all) triggered (current) threat detections contribute to the score. The preferred approach penalizes requests that fail all (or substantially all) combinations of detection algorithms. According to a further feature, an automated tuning (autotuning) is also applied, e.g., using real-time empirical statistical models, to adapt the measurement of false positive probability for one or more threat detection algorithms to suit customer traffic trends. The approach herein is also extensible to include any number of future threat detection algorithms.

The invention relates to the technical field of USB data line testing, and discloses a USB data line testing device for protecting a connector, the USB data line testing device comprises a supporting bottom plate, a testing assembly used for testing a USB data line is arranged on the supporting bottom plate in a turnover manner, and the testing assembly comprises a detection unit and a detection head slidably connected in the detection unit; a clamping assembly is arranged at one end, far away from the turnover shaft, of the detection unit, and is used for clamping and fixing a connector of the USB data line to be tested; the bottom of the detection unit is provided with a vibration assembly used for knocking the clamping assembly and the connector of the USB data line in the clamping assembly. According to the invention, the screw rod and the guide shaft are arranged, the adjacent moving seats are linked through the driving of the screw rod and the connecting rod, the multiple groups of detection heads are driven to move and slide in the detection unit until the detection heads are plugged with the USB data line connector for testing, the plugging of an operator is not needed, and the damage of the connector caused by violent plugging of the operator is effectively avoided.

The utility model relates to a large-scale pump station unit maintenance wear detection device, and relates to the technical field of hydraulic engineering maintenance equipment, the large-scale pump station unit maintenance wear detection device comprises a fixed machine base and a detection ring arranged on the fixed machine base, the detection ring movably and coaxially sleeves a motor rotating shaft, the machine base is also provided with two groups of fixed frames, and the two groups of fixed frames are coaxially arranged. The axes of the two sets of fixing frames are horizontal, the top sides of the two sets of fixing frames are open, the motor rotating shaft is erected on the two sets of fixing frames, the detection ring is arranged between the two sets of fixing frames, multiple sets of detection pieces are arranged on the detection ring, the positions, close to the axis of the detection ring, of the detection pieces are movably attached to the outer surface of the motor rotating shaft, and the detection ring is rotationally arranged on the fixing machine base. And an adjusting piece for adjusting the angle of the detection ring is also arranged on the fixed machine base. The detection efficiency of the abrasion loss of the motor rotating shaft is simplified, the detection precision of the abrasion loss of the motor rotating shaft is improved, and therefore the normal service life of a subsequent motor can be conveniently judged.

Systems, methods, and computer program products are provided for disparate quantum computing (QC) detection. An example system includes QC detection data generation circuitry configured to generate a set of QC detection data. The example system further includes cryptographic circuitry configured to distort the set of QC detection data via a first PQC cryptographic technique, generate a pair of asymmetric cryptographic keys comprising a public cryptographic key and a private cryptographic key via a second PQC cryptographic technique, generate encrypted QC detection data from the distorted set of QC detection data based on the pair of asymmetric cryptographic keys, and destroy the private cryptographic key. The example system further includes data monitoring circuitry configured to monitor a set of data environments for electronic information related to the encrypted QC detection data.

The utility model belongs to the technical field of crack detection, and particularly relates to a road, bridge and tunnel crack detection device which comprises a detector main body, two groups of detection probes are mounted at the top of the detector main body; the middle part of the detection probe is fixedly connected with a sliding block; a plurality of groups of springs are fixedly connected to the inner wall of the bottom of the sliding block; the top of the spring is fixedly connected with a top plate; an adjusting rod is arranged at the top of the detection probe, and the two groups of sliding blocks are arranged on the inner wall of the adjusting rod in a sliding manner; a pressing plate is fixedly connected to the middle of the adjusting rod. By arranging the sliding block in the middle of the detection probe and by means of the straight adjusting rod, the levelness of the two groups of detection probes on the inner wall of the adjusting rod during working can be improved, the problem that the measurement effect is poor due to angle inclination between the two groups of detection probes is solved, and meanwhile the situation that it is difficult for a worker to operate a detector body screen with one hand is reduced. And the other hand is used for fixing the positions of the two groups of detection probes.

Data platforms described herein are configured to monitor a compute environment and to use machine learning models for managing security threat alerts for the compute environment. Such a data platform may identify, based on event data indicative of events occurring in the compute environment, a set of detected security threats present within the compute environment. Using a machine learning model trained based on previous event data indicative of events that occurred previously, the data platform may reduce the set of detected security threats to form a subset of prioritized security threats. The data platform may then provide security threat alerts for the compute environment in a manner that emphasizes alerts associated with prioritized security threats over alerts associated with other detected security threats of the set of detected security threats. Corresponding methods, systems, and products are also disclosed.

The invention relates to the technical field of blast pump detection, in particular to an air suspension blast pump convenient and rapid detection box device which comprises a test box body, a bottom plate, an eccentric wheel set, a switching mechanism, a transmission mechanism and a blast pump mounting mechanism, a box cover is rotatably hinged to the outer side of the test box body, and an operation plate is fixedly connected in the test box body; hydraulic rods are fixedly connected to the inner wall of the box cover. By integrating the test box body, the switchable eccentric wheel group and the sound insulation cover mechanism, multi-working-condition dynamic simulation and noise isolation are realized in single equipment, the problems of low detection efficiency, high cost and data deviation in the prior art are effectively solved, two groups of detection stations are arranged, a control group is conveniently provided, and the detection efficiency is improved. According to the air pump data detection device, the detected air pump data are more accurate and reliable, the detection devices are modularly combined in the test box body, the detection steps are more convenient, the detection efficiency is improved, and the use requirements of people are met.

Systems and methods of using sensor sets for detecting multiple tasks are disclosed. An example method includes receiving, via a first sensor of the shared sensor set, first data representative of visual intent and receiving, via a second sensor of the shared sensor set, second data representative of a hand input. The method includes determining, using a contrastively-trained model, third data that describes a relationship between the first data and the second data and determining, using a task-inferring model and the third data, a task to be performed at an XR system. The method further includes providing instructions for causing performance of the task at the XR system.

One variation of a method for predicting manufacturing defects includes: accessing a first set of inspection images of a first set of assembly units recorded by an optical inspection station over a first period of time; generating a first set of vectors representing features extracted from the first set of inspection images; grouping neighboring vectors in a multi-dimensional feature space into a set of vector groups; accessing a second inspection image of a second assembly recorded by the optical inspection station at a second time succeeding the first period of time; detecting a second set of features in the second inspection image; generating a second vector representing the second set of features in the multi-dimensional feature space; and, in response to the second vector deviating from the set of vector groups by more than a threshold difference, flagging the second assembly unit.

The utility model relates to the technical field of surface density detection, in particular to a surface density full-inspection detection mechanism, which comprises a plurality of groups of detection units distributed along the belt running direction of a detection material, and each group of detection units are arranged on the same straight line along the breadth direction of the detection material. Every two adjacent detection units in the breadth direction of a detection material are located on different straight lines respectively, the effective detection width of the multiple detection units covers the breadth of the detection material, the adjacent detection units are spliced, surface density full detection of any wide material can be achieved, meanwhile, every two adjacent detection units are not located on the same straight line, and the detection efficiency is improved. According to the method, the influence of ray crossing on the accuracy of surface density contour detection can be avoided, the ray fan beam angle of a single detection unit is small, large-angle oblique incidence is avoided, the radiation quantity difference of different positions on the long-strip-shaped light spots is small, and the whole breadth surface density detection effect is consistent.

A method for determining occupied positions in a space starts by receiving detections of object movement from a radar monitoring the space. Each detection is associated with a position in the space and a time point when the detection was made. The method accumulates detections that have a time point within a first time period of predefined duration, and identifies a set of clusters of detections in the space by analyzing similarity in position of the accumulated detections. Any cluster whose detections are temporally distributed within a proportion of the first time period which is below a predefined proportion threshold are then removed from the set of clusters. The positions in the space that correspond to the set of clusters are determined to be occupied during the first time period.

The invention provides a layout system integrating punching, cleaning and drying of a pcb, and relates to a layout system. Comprising a circulating material frame arranged on a table top, a feeding transition line connected to the starting end of the circulating material frame, a laser drilling part, a cleaning part and a first product conveying line, wherein the laser drilling part and the cleaning part are located on the two sides of the feeding transition line, and the first product conveying line is used for achieving pcb conveying and transferring among the laser drilling part, the feeding transition line and the cleaning part. At least one detection line is further arranged on the side, away from the feeding transition line, of the cleaning part, a detection table is installed on each detection line in a linear driving mode, when the detection tables move to one ends of the detection lines, the detection tables are used for driving the cleaned pcb to be photographed and detected by the detection camera, and when the detection tables move to the other ends of the detection lines, the detection tables are used for bearing the terminating end of the circulating material frame. According to the invention, the production operation of a plurality of pcb boards can be synchronously carried out in the production line, and the whole process production line is penetrated by only one group of clips, so that the layout is more reasonable, the uniformity can be ensured, and the production efficiency can be greatly improved.

The invention provides an intelligent detection method and system for medicine packaging defects, and relates to the technical field of intelligent detection, and the method comprises the steps: determining multi-source detection data and carrying out multi-view homologous mapping fitting, carrying out defect information retrieval and confidence verification, determining a defect knowledge graph, constructing a multi-layer Gaussian scale space, and carrying out data-driven modeling. The method comprises the following steps: generating an intelligent detection model, carrying out three-dimensional grid division, determining relative coordinates of grids, carrying out detection branch matching and concurrent processing in the intelligent detection model, determining multiple groups of detection data, carrying out position coupling integration, and determining a defect detection result. The technical problem of poor detection accuracy caused by limited recognition capability of defect detection on complex packages in the prior art can be solved, the processing and analysis capability on a large amount of complex data is enhanced by acquiring data from multiple perspectives and accurately positioning defect positions, and the detection accuracy is improved. The technical effect of improving the efficiency and accuracy of medicine packaging defect detection is achieved.