752 results about "Signal response" patented technology

The invention relates to the technical field of grinding wheel monitoring, in particular to a centerless grinding machine full-life-cycle grinding wheel state monitoring system and method.According to the centerless grinding machine full-life-cycle grinding wheel state monitoring system and method, through combined difference extraction of a main shaft current mean value fluctuation ratio and a power gradient continuous variation value and assisted by transverse comparison of periodic response intervals, effective recognition of time period boundaries of working condition states is achieved; according to the method, operation stage division does not depend on static threshold judgment any more, a track trend is established through linkage judgment of an amplitude kick point and a slope extreme value, a dynamic evolution path of signal response is clearer, the identification resolution of abnormal changes and local deviation trends is improved, response synchronous identification of parameter state changes is achieved, and the identification accuracy is improved. In multi-signal collaborative analysis, directivity comparison between a temperature rise mutation fragment and a current residual error response is carried out, so that the consistency analysis capability of response logic between different monitoring paths is enhanced, and the real-time performance, stability and anti-interference capability of state identification are improved.

A wearable device configured to monitor physiological parameters of a wearer can include: a physiological parameter measurement sensor configured to monitor a plurality of physiological parameters; a hardware processor; a display in communication with the processor; and a band configured to secure the physiological parameter measurement sensor on a wrist of the wearer. In some implementations, the hardware processor is configured to: obtain a first plurality of signals from the physiological parameter measurement sensor when the band is secured on the wrist at a first tightness; determine a signal quality responsive to the first plurality of signals; and output an indication on the display to adjust tightness of the band with respect to the wrist from the first tightness to a second tightness based on the determined signal quality.

The invention relates to the technical field of water quality pollution detection, in particular to a water quality pollution rapid detection method driven by a quantum sensing technology. A quantum sensor array is deployed in a water area to be detected, and quantum signal response data of the water area is collected; constructing a pollutant quantum recognition model, and inputting quantum signal response data into the model to obtain an initial predicted value of pollutant concentration; generating an initial detection parameter of the quantum detection instrument based on the initial predicted value, executing primary pollution detection by the instrument according to the parameter, and collecting primary deviation data of an actual detection value and an expected detection value; determining a detection error according to the deviation data, further correcting the initial detection parameter, and generating an optimized detection parameter; and finally, the instrument performs secondary pollution detection based on the optimized detection parameters. According to the method, complex water sample pretreatment is not needed, water quality pollution detection can be rapidly and accurately completed, detection requirements of different water areas are met, and the detection efficiency and accuracy are improved.

The invention discloses a brain deep nerve stimulation method and system based on adaptive adjustment, and relates to the technical field of brain deep nerve regulation, and the method comprises the steps: collecting a local field potential signal of a brain deep target region of a target patient, and extracting a beta frequency band power spectrum density and a gamma frequency band phase synchronization index as neural activity characteristic parameters; determining an individual baseline value and a preset threshold value based on historical data, and outputting a stimulation adjustment trigger signal when the beta frequency band power spectral density exceeds the individual baseline value and the gamma frequency band phase synchronization index is lower than the preset threshold value; in response to the trigger signal, calculating an optimal stimulation parameter combination through a gradient descent optimization algorithm and executing nerve regulation; and monitoring the signal change after regulation and control, calculating a relative change rate and updating a threshold value. Through a two-parameter joint judgment mechanism and a threshold updating strategy, individualized adaptive adjustment of stimulation parameters is realized, and the stimulation accuracy and the treatment effect are improved.

The invention relates to an unmanned aerial vehicle inspection method and system based on an overhead transmission line, and the method comprises the steps: S1, generating an unmanned aerial vehicle three-dimensional space coordinate signal, and outputting a position correction signal based on a tower topology database; s2, in response to the position correction signal, controlling a multispectral sensing module to synchronously acquire a visible light image signal, an infrared temperature signal and a laser radar point cloud signal of the line; s3, inputting the visible light image signal into a defect identification model to generate a first defect feature signal; s4, fusing the first defect characteristic signal and the second defect characteristic signal to form a cross-modal diagnosis signal, and triggering a defect classification decision signal; and S5, classifying decision signals and cross-modal diagnosis signals according to defects. According to the air quality intelligent monitoring method and system based on sensing data feedback, the problems of inaccuracy in routing inspection positioning, defect missing detection and insufficient endurance in a complex environment can be solved.

The invention discloses a cross-channel marketing automation method and system based on real-time behavior triggering. The method comprises the following steps: capturing a user behavior event flow in real time through a front-end acquisition unit; performing real-time mode matching on the event stream by utilizing a complex event processing engine, and generating a marketing trigger signal when a preset rule is matched; dynamically selecting an optimal channel for the user based on a real-time scoring model in response to the signal; the marketing content is sent to the selected channel through the unified execution module; and finally, tracking user feedback and updating model parameters and user preferences in real time to form closed-loop optimization. The corresponding system comprises a front-end data acquisition module, a streaming event processing module, a real-time intelligent decision-making module, a multi-channel execution module and a closed-loop optimization module which are used for implementing the steps. According to the method, millisecond-level intention perception, cost and experience optimal channel intelligent decision and data-driven adaptive optimization closed loop are realized, and the problems of delayed response, extensive channel and lack of self-adaption of traditional marketing are solved.

The invention relates to the technical field of debugging systems, in particular to an adaptive debugging system and method for touch screen FW parameters, and the system comprises a signal acquisition module, a trend triggering module, a temperature compensation calculation module, a window generation module and a parameter output module. According to the invention, the edge of the driving voltage is carefully collected, the sliding difference algorithm is introduced to filter out high-frequency noise, meanwhile, real-time sampling of environment temperature and baseline capacitance adjustment are combined, the influence of external variables on signals can be dynamically corrected, and accurate judgment of capacitance fluctuation is improved by utilizing periodic delay deviation and regression trend analysis. By means of main frequency feature extraction and zero crossing point sudden change detection, threshold setting can be refined, self-adaptive window expansion can be achieved, touch signal response is kept sensitive and consistent all the time, adjustment and optimization can still be automatically completed even under the condition that the temperature changes frequently or signal interference is complex, parameter drift and debugging failure are effectively prevented, and user experience is improved. And the parameter automatic matching efficiency and the finished product consistency in batch production are improved.

A tool for movement sequence analysis utilizing printed circuits. The tool determines a workflow sequence based, at least in part, on one or more printed circuits within a printed organic component. The tool activates the workflow sequence utilizing applied external stimuli on the one or more printed circuits. Responsive to activating the workflow sequence, the tool analyzes a signal response from the one or more printed circuits. The tool generates one or more printing recommendations based, at least in part, on the signal response analysis.

The invention relates to the field of display, and discloses a short-circuit protection circuit, an array substrate, a display device and a short-circuit protection method.The short-circuit protection circuit is used for an OLED device and comprises the steps that an information sensing module obtains the actual working current of the OLED device and real-time parameters related to the working state of the OLED device; the dynamic expectation calculation module calculates the dynamic expectation working current n of the OLED device according to the real-time parameters and a preset OLED electrical characteristic model; the decision module synthesizes the actual current, the expected current and the current change rate / fluctuation amplitude to generate a risk judgment signal; and the response control module executes protection operation according to the judgment signal. According to the OLED short-circuit protection method, the accuracy, the sensitivity and the intelligent management level of OLED short-circuit protection are remarkably improved through the technology of dynamically calculating the expected current and carrying out decision making and parameter self-adaptive adjustment by fusing the actual current time sequence characteristics.

The invention relates to the technical field of electronic connector performance monitoring, in particular to a connector performance detection method, and aims to solve the problem that a method for realizing performance early warning through dynamic correlation analysis of vibration signals and contact resistance in the prior art is not suitable for an L-shaped pin connector without a sheath. According to the method, micro-strain signals and contact resistance signals are synchronously collected, analysis time periods are divided in combination with plugging events, the plastic deformation accumulation degree and signal response delay characteristics are quantitatively evaluated, performance degradation coefficients are generated through fusion, and trend analysis is carried out; the problem that the relevance between the mechanical deformation and the electrical performance cannot be quantitatively evaluated in the prior art is effectively solved, and the method has the advantages of realizing early warning, improving the monitoring accuracy and reducing the maintenance cost.

A wireless device may receive one or more radio resource control (RRC) messages comprising one or more configuration parameters. The one or more configuration parameters may comprise (i) a sounding reference signal (SRS) resource indicator (SRI), for a configured uplink grant, indicating an SRI-physical uplink shared channel (PUSCH) power control parameter set and (ii) a pathloss reference signal update parameter enabling an activation command to update pathloss reference signals of an uplink channel. In response to the one or more configuration parameters comprising the pathloss reference signal update parameter, the wireless device may determine a transmission power for a transport block of the configured uplink grant based on a pathloss reference signal mapped to the SRI-PUSCH power control parameter set. The wireless device may transmit the transport block with the transmission power.

The invention discloses a fault signal dual-mode output method of a magnetic latching relay, particularly relates to the technical field of relay control, and is used for solving the problem of low mode switching efficiency caused by an existing physical jumper mechanism. The current mechanical state of the relay is detected by receiving a remote dual-mode switching instruction; applying a driving voltage sequence corresponding to the target mode according to the state; based on the iron core residual magnetism intensity and the dynamic margin of a target mode nominal value, judging and generating a driving enabling or degaussing trigger signal; when a driving enable signal is responded, the lag time difference between the voltage rising edge and the magnetic flux jump starting point is captured in real time, and the eddy current loss characterization quantity is generated by combining the product integration of the current differential and the temperature rise; adjusting the rising slope and the duty ratio of the driving voltage sequence according to the lag time difference and the over-limit condition of the eddy-current loss characterization quantity; and finally, the matching between an execution result and a target mode identifier is verified by controlling a coil current response waveform, and the continuous holding mode and the instantaneous pulse mode are remotely and reliably switched.

The invention relates to the technical field of infrared measurement, in particular to an intelligent calibration method and system for temperature measurement of an infrared sensor, and the method comprises the steps: enabling an infrared camera to align with a blackbody radiation source to form a calibration scene, collecting the output of a plurality of groups of pixels under different radiation temperatures and different internal part temperature states, fitting a temperature signal response model containing an exponential term and a bias term according to least square to obtain amplitude, exponential, temperature offset and output bias parameters; during measurement, a thermal image containing a target object and two reference blackbody sources is obtained, and parameters such as emissivity, environment equivalent radiation temperature, transmission medium and optical transmission, camera temperature and the like are synchronously obtained; performing non-uniformity and offset correction and abnormal pixel replacement on the thermal image; the initial temperature is inverted based on radiation transfer decomposition and compensation of internal radiation of the camera; and carrying out statistical averaging on the temperatures of the two blackbody reference regions to obtain a double-point correction coefficient, and outputting correction temperature or temperature distribution. According to the method, the problems that temperature inversion model parameters are difficult to adaptively update along with working conditions and on-site temperature measurement errors are difficult to effectively suppress when an existing infrared sensor array is in a long-distance non-contact temperature measurement scene can be solved.

The invention discloses a fast data protection method and device for SSD abnormal power failure, equipment and a medium, and relates to the field of SSDs, and the method comprises the steps: monitoring a power supply voltage, and generating an interrupt signal when the power supply voltage is lower than a preset threshold value; in response to the interrupt signal, turning off a power supply of a preset non-data path hardware module through the SSD controller; stopping scheduling all operation commands for the NAND flash memory through the SSD firmware, and emptying a data path in an NAND flash memory controller; writing the user data in the host write cache and the command information corresponding to the user data into a special physical address block reserved in the SSD in advance; after the SSD is powered on again, the address mapping table is recovered by scanning the write-in point in the NAND flash memory, the backup data and the command information in the special physical address block are read, and the backup data are written into the user data area according to the command information. According to the method, the key data backup time during abnormal power failure is shortened, the capacity requirement for the standby capacitor is reduced, and the problem that the cost is increased due to the fact that the backup time is too long is effectively solved.

The present invention relates to the technical fields of human-computer interaction and brain informatics, and in particular to a closed-loop neurofeedback method and device based on haptic memory electroencephalogram signal conditioning. The method comprises: collecting electroencephalogram signals of a subject, and performing real-time online data preprocessing; designing a haptic memory stimulation task, activating the haptic memory of the subject, and recording a corresponding electroencephalogram signal response; performing feature extraction and analysis on a corresponding electroencephalogram signal to obtain an electroencephalogram feature related to haptic memory; and on the basis of a haptic memory electroencephalogram feature signal, designing a closed-loop neurofeedback system, the closed-loop neurofeedback system monitoring the electroencephalogram signals of the subject in real time, performing real-time stimulation on the basis of a preset haptic stimulation task, and recording a corresponding electroencephalogram response. In the technical solution of the present invention, the haptic memory electroencephalogram feature signal is combined with the closed-loop neurofeedback system, thus providing new ideas and methods for the diagnosis and treatment of haptic memory-related diseases.

The invention relates to the technical field of big data, in particular to a personalized recommendation method and device based on structure and behavior layering and a medium, and the method comprises the steps: extracting global features and graph structure information of interaction data of a user and an article; modeling a personalized portrait of the user, and generating a filter coefficient; carrying out hierarchical coefficient fusion, and executing mixed spectral domain atlas filtering to obtain a personalized atlas filtering score; obtaining a basic recommendation score through multi-source score fusion, and executing dynamic score modulation to obtain a final recommendation score; and generating a recommendation list based on the final recommendation score, and returning the recommendation list to the user. According to the method, through layered and two-dimensional personalized modeling, a recommendation engine can dynamically adjust the signal response of each user in a low frequency-high frequency and global-personalized spectral domain, so that the diversity, novelty and interpretability of a recommendation result are remarkably improved while the recommendation precision is ensured.

The invention relates to the technical field of defect detection of image recognition, and particularly discloses a mobile phone card holder processing defect detection method and system based on image recognition, and the method comprises the steps: collecting multiple frames of time sequence images, and carrying out the sub-pixel-level space-time registration, thereby eliminating the influence of mechanical vibration and displacement deviation; calculating an optical flow field, extracting a local strain tensor, an optical flow vorticity and a motion consistency entropy, and constructing a time-varying feature matrix; carrying out frequency domain decomposition and motion amplification on the characteristic matrix, and enhancing micro defect signal response; the dynamic time domain features and the static image features are fused, and a defect detection model based on deep learning is established; and finally generating a defect probability cloud picture, and outputting defect types and positions in combination with a dynamic threshold mechanism, so that high-precision and high-efficiency automatic detection of the small defects of the mobile phone card tray is realized, and the method has good stability and adaptability.

The invention discloses a gesture interaction method and device, a ring and a storage medium, and relates to the technical field of intelligent wearable device.The method comprises the steps that a hand motion data stream of a user is collected in real time through an inertial measurement unit of the intelligent ring, and an electromyographic signal data stream of the user is collected in real time through an electromyographic sensor of the intelligent ring; when the signal feature of the electromyographic signal data flow meets a preset activation condition and the track starting section of the hand motion data flow and the electromyographic signal data flow meet a synchronism condition in time sequence, a gesture interaction signal is triggered; and in response to the gesture interaction signal, executing an interaction operation. The identification accuracy of the user interaction intention in the office scene can be improved.

An embodiment of the disclosure provides a system for recommending at least one product to a user device. The system is configured to: (a) receive N product descriptions, each product description in the N product descriptions including an image; (b) extract, for each image in the N product descriptions, a plurality of features including machine-understandable visual parameters; (c) arrange a subset of the N product descriptions relative to a surface in a grid-like manner according to the machine-understandable visual parameters; (d) providing, to the user device, the grid-like arrangement of the subset of the N product descriptions; (e) receive, from the user device, signals indicating an interaction relative to the surface; (f) in response to the signals, rearrange the subset of the N product descriptions relative to the surface; and (g) send, to the user device, the rearranged subset of the N product descriptions.

The invention discloses a multi-mode anti-interference communication method and system based on lip language recognition, and belongs to the technical field of communication equipment. The method comprises the following steps: acquiring a face lip video stream and an audio signal; in response to the conventional mode trigger signal, feature extraction is performed on the lip video stream and the audio signal, and extraction results are fused to generate a fused feature vector; performing voice enhancement on the fusion feature vector in combination with lip motion information, and outputting an audio enhancement signal; and in response to the silent communication mode trigger signal, performing lip language recognition based on the face lip video stream to obtain a lip language recognition text, and converting the lip language recognition text into voice. Clear and stable communication in an ultra-strong noise environment can be realized by combining two types of modal information, and the problem that the communication quality is influenced by an existing high-noise environment and the requirement for mobile silent communication in a special scene are solved.

The embodiment of the invention provides a transformer no-load closing angle control method, electronic equipment, a storage medium and a program product. The method comprises the following steps: periodically sampling three-phase voltages at a power supply side of a transformer, and determining a zero crossing moment when the phase voltage is changed from a negative value to a positive value according to respective sampling data for each phase in the three phases; based on the zero point moment of each phase, a preset switching-on angle and the total delay required from the switching-on instruction sending to the actual conduction of the main circuit, the target moments at which the switching-on instructions of the three phases should be sent out are calculated respectively, and corresponding switching-on trigger signals are output at the target moments of the phases respectively; and in response to the closing trigger signal of each phase, combined switch circuits arranged in the three-phase line are respectively driven, and each group of combined switch circuit comprises an MOS (Metal Oxide Semiconductor) tube and a dry reed relay which are connected in parallel, so that the MOS tube is conducted to establish an initial current path.

The invention discloses a carbon nanosensor with a gradient pore structure and a preparation method and application thereof. The carbon nanosensor comprises a sensing base layer, a sensing layer and a flexible electrode, the sensing layer is located between the sensing base layer and the flexible electrode; the sensing layer is prepared by mixing at least two of a zero-dimensional conductive nano-material, a one-dimensional conductive nano-material, a two-dimensional conductive nano-material and a three-dimensional conductive nano-material with a surfactant; the sensing base layer is prepared from a high-molecular polymer, and the pore structure of the sensing base layer is sequentially increased along the direction far away from the sensing layer to form a gradually-changed gradient pore structure. According to the invention, the defects of signal response lag, large measurement error, long-term performance degradation and the like of a traditional sensor can be overcome, high-sensitivity, high-precision and high-stability collaborative sensing of the material structure state under complex working conditions is realized, and a breakthrough technical scheme is provided for the field of structure health monitoring.

A method and apparatus for non-terrestrial network (NTN) coverage extension is provided. A user equipment (UE) transmits an indication of UE capability for physical uplink control channel (PUCCH) repetitions of a fourth message (Msg4) hybrid automatic repeat request-acknowledgement (HARQ-ACK) transmission in a random access channel (RACH) procedure to a network node of the NTN. The UE determines a trigger for PUCCH repetitions of the Msg4 HARQ-ACK transmission during the RACH procedure. In response to the trigger, the UE transmits one or more Msg4 HARQ-ACK repetitions from the UE to the network node.

The invention discloses a photovoltaic power station fault alarm and operation and maintenance task automatic distribution method based on air-ground cooperation, and belongs to the technical field of photovoltaic operation and maintenance management and intelligent scheduling, and the method comprises the steps: obtaining an equipment dynamic importance score, and executing differential data collection to generate an abnormal trigger signal; responding to the signal, controlling the unmanned aerial vehicle to collect air data, and generating a precise positioning request when an abnormality occurs; acquiring centimeter-level precision ground data through the ground operation and maintenance unit; fusing the air data and the ground data to generate a fused fault feature packet; performing fault diagnosis based on the feature packet, and generating alarm information; and automatically generating an operation and maintenance task based on the alarm information, calculating an optimal distribution scheme through a multi-constraint optimization algorithm in combination with a real-time resource state, and distributing the operation and maintenance task to a corresponding operation and maintenance resource. According to the invention, land-air multi-mode data collaboration and intelligent optimization scheduling are adopted, high-precision positioning and automatic distribution of faults can be realized, and the operation and maintenance efficiency and the resource utilization rate of the photovoltaic power station are improved.

The invention discloses a data mining method and system based on artificial intelligence driving. The method comprises the steps that S1, an original data stream is received, and heterogeneous data feature signals are generated; s2, inputting the heterogeneous data characteristic signal into a dynamic quality sensing module, generating a quality evaluation feedback signal and a purification trigger signal, and outputting a cleaned optimized characteristic signal; s3, in response to the optimization feature signal, synchronously outputting a classification label signal, a clustering correlation signal and an abnormal scoring signal; s4, generating an interpretability enhancement signal based on the mode recognition control signal, and generating a semantic interpretation signal aligned with the business rule; s5, the semantic interpretation signal is received, a closed-loop optimization instruction signal is generated, the feature extraction strategy and the model hyper-parameters are dynamically adjusted through the reinforcement learning agent, and a self-adaptive iterative mining link is formed. According to the data mining method and system based on artificial intelligence driving, the problems of heterogeneous data fusion distortion, poor dynamic environment adaptability and untrusted model decision can be solved.

The invention relates to the technical field of precision shell contour metering, and discloses an online metering method for a precision shell contour, and the method comprises the steps: obtaining an original sampling point cloud and a feature point group of a to-be-measured workpiece in a conveying state; resolving a real-time pose matrix of the to-be-measured workpiece relative to a preset measurement reference by using a spatial topology constraint relationship of the feature point groups; carrying out differential processing on a real-time pose matrix in the sampling sequence, and synthesizing an instantaneous motion vector corresponding to a sampling moment; in combination with a signal response time delay constant of the sampling system, phase compensation is carried out on a motion displacement deviator induced by signal conversion delay, and a corrected sampling point cloud is generated; according to the method, the geometric distortion of the point cloud generated by response delay of the sensor is solved, the problem of instantaneous drift of the measurement reference in an unsteady state conveying state is solved, and the contour reduction precision in a complex working condition is improved.

The invention belongs to the field of quantum computing, and particularly relates to a distortion correction optimization method and device for a quantum measurement and control link. The method comprises the following steps: determining a digital filter for distortion correction or a pre-distortion waveform output by the digital filter and used for compensating distortion based on a target parameter value of a target system function fusing quantum measurement and control link signal response characteristics; acquiring an output signal of the quantum measurement and control link provided with the digital filter; and in response to the condition that the output signal does not reach the preset standard, updating the target parameter value or the pre-distortion waveform, and returning to execute the step of acquiring the output signal of the quantum measurement and control link provided with the digital filter until the output signal reaches the preset standard. According to the invention, distortion correction of the quantum measurement and control link can be effectively realized.

Approaches for initiating a human takeover by a virtual artificially intelligent (AI) agent. A predetermined indication is used as a signal for initiating the human takeover across a variety of contexts. Responsive to detecting the predetermined indication, a human operator is automatically notified to take over the conversation and the AI system is prepared for transferring control to a human operator.

The invention relates to the technical field of financial science and technology and artificial intelligence cross fusion, in particular to a financial format file processing method and device based on a large language model, and the method comprises the steps: receiving a file uploading or generating instruction, responding to the uploading instruction, carrying out format recognition and integrity verification, storing, and generating a ready signal; and in response to the generation instruction, constructing a cue word containing financial scene parameters, calling a large language model to generate content and generating a signal. And extracting a text through an adaptive analyzer based on the signal, filtering redundancy, converting into a standard JSON format, and driving a large language model to proofreading in combination with a special prompt word in the financial field to generate a compliant text. And after converting into a structured HTML intermediate representation and checking, analyzing an HTML matching template, filling placeholders, mapping into a Word format of a financial specification, and outputting a file which conforms to the business specification through special checking. Full-process automation is achieved, efficiency is improved, compliance risks are reduced, and the method is suitable for multiple scenes.