430 results about "Calibration algorithm" patented technology

The invention relates to the technical field of computer vision and three-dimensional reconstruction, and discloses an exhibition hall three-dimensional modeling intelligent optimization system based on multi-modal data fusion, and the system comprises a data collection module which is configured to synchronously obtain laser radar point cloud data, a multispectral image sequence and inertial measurement unit data; the preprocessing module is used for receiving the output of the data acquisition module, aligning a multi-source sensor coordinate system through a space-time calibration algorithm, and separating a static scene from a dynamic interference element by using a dynamic segmentation network; and the multi-modal fusion module is used for receiving the preprocessed data and carrying out adaptive weighted fusion on the geometric features of the laser radar and the visual texture features through a cross-modal attention mechanism. According to the invention, through multi-modal data fusion and a dynamic scene adaptive mechanism, the modeling precision and the real-time updating capability in a complex exhibition hall environment are significantly improved.

The invention discloses a railway intelligent construction site safety penetration type management messenger platform which comprises a multi-modal data fusion processing module, an edge computing node cluster module, a three-dimensional visual penetration type management interface module, an intelligent early warning and emergency response module, a self-adaptive network transmission module and the like. Real-time cleaning, alignment and correlation analysis are realized by using a dynamic data calibration algorithm, and a data island is broken; the edge computing node cluster carries out localization preprocessing and the like on data in a key area, so that the load of a central server is reduced; the three-dimensional visual interface is based on a digital twinborn construction model, supports drilling type viewing and realizes three-dimensional monitoring; the intelligent early warning system adopts a reinforcement learning model to automatically trigger multi-channel early warning; and the adaptive network transmission module dynamically switches communication modes to ensure low-delay transmission of key data. The platform realizes real-time acquisition and integration of construction site data and reduces manual intervention.

The invention discloses a high-precision current detection circuit calibration system, and belongs to the technical field of current detection circuit calibration. Comprising a shunt resistor, a Hall sensor array, a chopping amplifier, a low-noise operational amplifier, a temperature sensor, an ADC acquisition unit, an RC low-pass filter, a signal conditioning unit, a main control unit, an environmental parameter adaptive compensation module and a gain adaptive adjustment module. After an original signal is obtained from a multi-channel sensor, a dynamic error model is constructed in combination with temperature data, a long-term imbalance trend is extracted by using a moving average or median filtering algorithm, and real-time compensation is performed through a pre-calibrated temperature-drift function, so that the system maintenance period is remarkably prolonged.

The invention relates to the technical field of intelligent war game deduction, in particular to an intelligent war game deduction simulation system based on a digital twin fusion large model. Comprising a digital twin modeling unit which adopts a dynamic precision adaptive modeling mechanism; a large model decision unit; a deduction execution unit; and a dynamic interaction unit. A dynamic precision self-adaptive modeling mechanism is adopted by the digital twin modeling unit, the model precision can be dynamically switched on demand, the detail simulation demand and the computing resource consumption are balanced, and meanwhile, the sub-second-level dynamic synchronization of a virtual model and a war game deduction scene is realized through a time sequence calibration algorithm; and space confrontation, time sequence decision and rule triggering features are fused through the multi-modal feature analysis module, and the Wargame rule verification module is combined to embed entity performance boundaries and scene rule constraints, so that compliance confrontation decision parameters conforming to Wargame deduction logic can be generated, and the problem of insufficient model precision adaptation and decision constraints is solved.

The invention relates to the technical field of time synchronization, and discloses a hybrid time service method based on Beidou satellite navigation and a TSN, which comprises the following steps: acquiring network topology structure information and historical time service error data of each synchronization node in a target distributed system, and constructing a dynamic time delay state set for jitter identification; based on the dynamic time delay state set, a current global time reference is extracted through a time calibration algorithm, a time difference reference vector sequence is generated, and initial synchronization adjustment is carried out on the TSN main node; constructing an inter-node clock convergence function curve according to the slave node response stability, and judging whether the synchronous network is in a low jitter interval or not based on the time offset rate and the time drift trend change; in combination with the node time state after directional offset suppression, a multi-channel redundant time synchronization mechanism in a time window is applied, a weight adjustment coefficient is extracted, and an unbalanced calibration factor is introduced; and according to a regression correction result, evaluating a time service stability index in real time. The method has the advantage of improving the time service stability.

The invention relates to the technical field of image correction, in particular to a correction method and system for a low-distortion image of a panoramic camera. The method comprises the following steps: based on a second-hand vehicle scene acquisition demand, acquiring a panoramic image and executing basic preprocessing to obtain a preprocessed panoramic image; calling a lens distortion coefficient, analyzing a corresponding distortion parameter in combination with a checkerboard calibration algorithm, and generating a polar region distortion distribution diagram; carrying out segmentation and grid reconstruction on a polar region of the preprocessed panoramic image, and executing distortion elimination and geometric reduction to obtain a preliminary correction image; fine tuning is carried out on the pixel position of the preliminary correction image, color fault and edge dislocation of a multi-lens splicing seam are eliminated, and an optimized correction image is obtained; executing second-hand car scene customized enhancement processing on the optimized correction image to obtain an enhanced correction image; and automatically checking the enhanced correction image, and outputting a low-distortion final correction image. According to the invention, the correction efficiency of the panoramic low-distortion image of the second-hand vehicle can be improved.

The invention discloses a visual perception and dynamic anti-collision intelligent closed-loop control method for a central control mechanical arm in a vehicle, and the method comprises the steps: S1, loading an improved YOLOv11 network detection model, and reading a video stream of a camera; s2, preprocessing each frame of image in the video stream, inputting the preprocessed image into the model, and performing target identification; s3, inputting an identification result into a dynamic safe area collision model, and performing coordinate conversion through a hand-eye calibration algorithm; calculating a relative position and a motion trend in combination with depth sensor data, and judging a risk level to generate a corresponding protection instruction; and S4, executing a hierarchical control strategy according to the risk level, updating the action track of the mechanical arm, and returning to the step S1 through a closed-loop feedback mechanism to adjust the safety threshold and the control parameters to form a complete'perception-decision-execution-optimization 'autonomous evolution closed loop. According to the method, the visual perception robustness and the target detection precision under the complex illumination condition are improved, and real-time dynamic anti-collision response and millisecond-level rapid obstacle avoidance are realized.

The invention relates to the field of vegetation index monitoring, and discloses a method for monitoring solanum roselle based on a multi-spectral index change rate of an unmanned aerial vehicle, which comprises the following steps: acquiring multi-spectral image data of a target area under a continuous time sequence; extracting NDVI, GNDVI and red edge vegetation index change layers from the reconstructed time sequence multispectral image by adopting a self-adaptive spectrum calibration algorithm to obtain a vegetation index change rate initial map; the method aims at the spectrum confusion problem of the eggplant at different growth stages and peripheral plants in change rate expression. Carrying out deep fusion on the initial vegetation index change rate map and the growth fluctuation contour model, constructing a change rate anomaly response factor map layer, and outputting suspected distribution candidate regions of the solanum aureocauda var. Aureocauda var. Aureocauda; and combining the change rate evolution trend of the historical extension path with a neighborhood growth consistency index, and dynamically generating a high-confidence identification map of the solanum aureum. The method has the advantage of improving the change rate discrimination precision.

The invention discloses a pressure injury risk early warning method and equipment, and relates to the technical field of medical monitoring instruments. The pressure sensor array layout can be self-adaptive to the body shape of a patient, a key osseous process part is covered, no monitoring dead angle is ensured, a temperature compensation mechanism is built in, environmental interference is reduced, the measurement precision is improved, an abnormal pressure threshold value can be dynamically set based on individual medical record data, data verification is performed before early warning is triggered, false alarm is avoided, and the array structure is light, thin and flexible. The mask is comfortable to fit skin, supports long-term wearing and is easy to disinfect and maintain; environment temperature and humidity parameters and pressure data are subjected to fusion analysis, the influence of a high-temperature and high-humidity environment on skin microcirculation can be recognized, the risk of pressure sores can be evaluated in an auxiliary mode, a calibration algorithm is built in a sensor, environment fluctuation interference is reduced, and data reliability is ensured; and the early warning unit comprises sound-light alarm equipment which supports a multi-stage alarm mode and is used for triggering an early warning signal and pushing information when the risk index exceeds a threshold value, so that the early warning timeliness is ensured and the false alarm risk is reduced.

The invention discloses a current and voltage signal synchronous correction and output method and system, and relates to the technical field of power system analysis and control. Compared with a previous current and voltage signal correction method, the method solves the problems that traditional multi-channel signal acquisition depends on conventional clock control, and synchronization precision is insufficient; a conventional sampling circuit is weak in anti-interference capability. The problem that an existing scheme lacks efficient error prediction and dynamic optimization capability is solved. Through a multi-channel FPGA clock synchronization and double-differential sampling technology, complete acquisition of high-frequency transient characteristics of voltage and current signals is ensured; a dynamic calibration algorithm and multi-stage composite filtering are combined, so that common-mode interference and non-linear errors are effectively suppressed; and finally, through optical fiber isolation output and intelligent feedback control, signal full-link synchronous correction is realized, the electric energy metering error can be reduced, the fault positioning precision is improved, the characteristics of high precision, strong anti-interference and low energy consumption are realized, and a reliable data reference is provided for intelligent power grid and new energy grid connection.

The embodiment of the invention provides an optical measurement method and system based on camera calibration and a distortion model, and a medium. The method comprises the following steps: shooting a plurality of calibration images and distortion measurement images at different angles and positions based on a three-dimensional calibration workpiece; analyzing the calibration image and the distortion measurement image based on a calibration algorithm to obtain camera parameters and a distortion model; obtaining a to-be-measured object image based on the calibrated camera, and extracting features of the to-be-measured object image; performing distortion correction on the image features of the to-be-measured object based on a distortion model to obtain corrected image features of the to-be-measured object; performing three-dimensional reconstruction on the corrected image features of the to-be-measured object to obtain a measurement image, and analyzing parameter information of the to-be-measured object based on the measurement image to obtain a measurement result; parameter calibration and distortion correction are carried out on the camera, so that the distortion error is reduced, and the measurement precision is improved.

The invention discloses a visual tracking image acquisition method and device, electronic equipment and a readable storage medium, relates to the technical field of robot inspection, and accurately establishes a mapping relation between an actual image coordinate and a camera coordinate through a camera checkerboard calibration algorithm to obtain an internal reference matrix and a distortion coefficient. A shooting holder is controlled to collect a large-range image containing an inspection target, and a visual tracking algorithm is used to identify the contour of the target. And calculating a target magnification factor and a holder fine tuning parameter based on the contour coordinate data, the internal reference matrix and the distortion coefficient. And rotating the holder according to the fine tuning parameters, accurately positioning the inspection target to the center of the global image, and executing image magnification operation according to the target magnification times to complete target image acquisition. Through cooperation of calibration data support, algorithm contour recognition and parameter driving adjustment, the collection effect of a target image is not affected by repeated positioning precision of the robot, it is ensured that the collected target image is centered and clearly amplified, and a high-quality image basis is provided for subsequent detection.

The invention discloses a structure three-dimensional displacement monitoring method and device based on a monocular camera and a concentric annulus, and relates to the field of computer vision and structure health monitoring, a concentric annulus target is fixed at a to-be-monitored structure monitoring point, and the monocular camera carries out positioning and lens parameter adjustment; shooting a checkerboard image and calibrating the checkerboard image by adopting a camera calibration algorithm to obtain a distortion parameter and an internal reference matrix; collecting a video sequence containing a structure displacement process of the target; image distortion correction is carried out based on the distortion parameters and the internal reference matrix, a target is identified through a target detection algorithm, and target parameters are calculated through least square circle fitting; realizing multi-target tracking by a target point topology identification algorithm based on Y-X threshold sorting; calculating scale factors according to target parameters and actual physical sizes, and calculating in-plane orthogonal direction displacement and out-of-plane displacement to form three-dimensional displacement information of the structure; according to the invention, the monocular camera is adopted to realize the accurate measurement of the three-dimensional displacement of the structure and reduce the complexity and calibration difficulty of the system.

The invention discloses a liquid hydrogen container heat leakage prediction and boost characteristic detection method and system. The method comprises the following steps: establishing a three-dimensional heat flow field model of a liquid hydrogen container; calculating the heat flow density of a gas-liquid interface based on the three-dimensional heat flow field model so as to adjust the liquid hydrogen evaporation capacity; total heat leakage is obtained through finite element simulation and experimental data collaborative calibration; calculating a static evaporation rate according to the total heat leakage; establishing a nonlinear mapping model of the static evaporation rate and the boost rate through a response surface regression method; the wall temperature distribution of the liquid hydrogen container is monitored in real time, thermophysical parameters are calibrated through the LSTM neural network by adopting a dynamic calibration algorithm, and the output result of the three-dimensional heat flow field model is corrected. By establishing a three-dimensional heat flow field model of the liquid hydrogen container, determining a nonlinear response relationship between the evaporation rate and the pressure rising rate of the liquid hydrogen container, and constructing a cloud-edge collaborative detection system, the heat leakage performance of the liquid hydrogen container is accurately predicted, and efficient pressure rising rate detection is realized.

The invention relates to the technical field of display, in particular to a Mini LED backlight module intelligent control system and method of a distributed driving architecture, and the system comprises a processor unit, an LED driving chip, a Mini LED module and a sensor. The processor unit converts an RGB color space into a backlight brightness signal in an XYZ tristimulus value form based on a topological mapping theory; the LED driving chip receives the signal, controls the light intensity of the Mini LED module, and executes verification and compensation based on a Bayesian inference framework; the Mini LED modules are arranged in a distributed architecture, receive the brightness signal and output backlight brightness; a sensor collects backlight brightness signals of an RGB color space to form closed-loop feedback, a calibration coefficient matrix is generated through a polynomial fitting calibration algorithm optimized through matrix decomposition, and high-precision and high-reliability backlight control is achieved in combination with adaptive parameter adjustment and a dynamic compensation mechanism.

The invention discloses an in-service precision intelligent diagnosis and calibration industrial robot system and a diagnosis and calibration method. The system comprises a parameter acquisition module, a fault diagnosis engine module, a collaborative calibration algorithm module, a laser tracking calibration module, an execution calibration module and a result feedback module. According to the method, joint, tail end, load and environment parameters of the robot are collected through the parameter collection module and transmitted to the fault diagnosis engine module, and features are extracted and faults are classified through a specific technology; the collaborative calibration algorithm module calculates a calibration compensation amount in combination with the fault parameters, and the laser tracking calibration module tracks and measures the motion trail of the robot in real time; the execution calibration module adjusts controller parameters to complete calibration, and the result feedback module compares the parameters and adjusts the acquisition frequency and type. According to the system and the method, in-service real-time diagnosis and calibration of the robot are realized, the fault diagnosis accuracy and the calibration precision stability are improved, the production interruption is reduced, the flexible production requirement is met, and the operation precision and the production efficiency of the robot are guaranteed.

The invention relates to an energy storage power station SOC automatic calibration and inter-cluster dynamic balance cooperative control method. The method comprises the following steps: acquiring charge state parameters of a sodium ion supercapacitor cluster group preset in an energy storage power station; calculating a corresponding charge change rate based on the charge state parameters to judge whether calibration is abnormal or not; when the calibration is abnormal, the working modes of the cluster group are divided according to the charge state parameters, and a calibration period is set for each working mode; a local equilibrium buffer is additionally arranged on a preset management end of the energy storage power station, a previous calibration value is allowed to be returned within a preset time period, and the returning frequency of the previous calibration value is recorded; and when the return frequency of the previous calibration value is greater than the preset frequency, sending a calibration refresh request to the management end of the energy storage power station, shortening the calibration period, forcibly obtaining the latest SOC value, filling the missing estimated value, optimizing the operation efficiency of the energy storage power station through an adaptive calibration algorithm and hierarchical equalization, reducing redundant operations, and improving the reliability of the energy storage power station. Missing data is compensated through historical data trends, and the safety and reliability of the system are improved.

The invention discloses a live-action three-dimensional modeling error dynamic compensation method based on multi-source heterogeneous sensor fusion in the field of computer vision and surveying and mapping engineering. The method comprises the following steps: step S101, multi-source data acquisition: synchronously acquiring laser radar point cloud data, RGB-D camera depth images and unmanned aerial vehicle image data; step S102, space-time alignment: carrying out space-time alignment on the multi-sensor data by using an improved joint calibration algorithm, and constructing a unified coordinate system; and step S103, feature extraction and matching: extracting feature points of the data of each sensor, and performing feature matching through a multi-scale descriptor. According to the method, dynamic error compensation and multi-source data deep fusion are carried out, the bottlenecks of a traditional modeling method in precision, adaptability and efficiency are broken through, a high-precision and extensible three-dimensional modeling solution is provided for the fields of intelligent transportation, industrial quality inspection, forestry investigation and the like, and remarkable economic benefits and social benefits are achieved.

The invention provides an industrial graph construction method and system based on scene type marketing, and relates to the technical field of industrial graph construction, and the method comprises the steps: processing a media text through a BERT pre-training model to generate a text data set, processing scene data through a space-time calibration algorithm to generate a behavior data set, and summarizing to generate an unstructured marketing data set. Generating a multi-modal marketing scene data set in combination with the structured marketing data set; processing the multi-modal data set by adopting a stream-batch integrated framework and an entity disambiguation technology, and constructing a four-dimensional data lake; constructing a three-dimensional feature library and training a marketing scene weight model; a data lake is mapped to a graph database, an industrial chain topological structure is formed, node relation strength is adjusted based on a weight model, node implicit features are learned through a GraphSAGE algorithm, and a scene-sensitive industrial graph topological structure is generated, so that industrial entity relations in different marketing scenes can be reflected in real time, and the marketing efficiency is improved. And the accuracy of the industrial map in marketing decision making is improved.

The invention relates to the technical field of computer vision, and discloses a Monte Carlo tree search-based camera lens assembly focusing calibration algorithm and system, and the algorithm comprises the steps: constructing a three-dimensional search space comprising a focus position, a horizontal inclination angle and a vertical inclination angle, and combining a high-contrast cross wire test pattern to generate a local definition matrix; calculating an initial inclination angle based on the matrix to construct a root node of the Monte Carlo tree; according to the algorithm, an optimal search path is dynamically selected by applying an upper confidence bound strategy, child nodes are expanded in a three-dimensional space, physical adjustment is executed, and optimal three-dimensional configuration parameters are finally determined based on node scores through back propagation iterative optimization. The method breaks through a traditional one-dimensional search framework, effectively avoids a pseudo peak trap caused by inclination of a lens-sensor axis, improves the calibration precision and efficiency of the full-view-field definition of the camera, and achieves the precise positioning of a global optimal solution under a complex assembly tolerance.

The invention relates to the technical field of electric power energy storage battery replacement, in particular to a dynamic positioning unmanned energy storage battery replacement system, which comprises a dynamic positioning module, a power conversion module, a power conversion module, a power conversion module, a power conversion module, a power conversion module, a power conversion module, a power conversion module and a power conversion module, the self-adaptive battery grabbing unit monitors battery deformation based on positioning data and feedback of a six-dimensional force sensor, adjusts grabbing parameters according to the type of the battery, drives a mechanical arm to conduct force-position hybrid control, and adopts a graded force control strategy to adjust the claw distance and the locking force in a self-adaptive mode. The intelligent storage scheduling center dynamically generates a battery replacement instruction through a demand prediction model based on the battery health degree, the load demand and the battery replacement priority; the dynamic fault-tolerant unit monitors battery replacement abnormity and triggers an emergency strategy; and the block chain evidence storage unit writes the key information into an alliance chain, and operation traceability and equipment state right confirmation are carried out. Therefore, the problems of low positioning precision, poor compatibility and the like in the prior art are solved.

The invention relates to a double-robot automatic calibration method based on self-adaptive point location planning in a restricted space, and belongs to the technical field of double-robot calibration, and the method comprises the steps: building a three-dimensional simulation model of a double-robot operation space on an Rviz platform based on an ROS architecture; a collision detection module is used for randomly generating a calibration point composed of collision-free double-robot joint angle vectors; when the robot is driven to move, data of the motion capture camera and positive kinematics Cartesian coordinates of the double robots are synchronously collected, a calibration result is obtained through optimization of a least square method by adopting a hand-eye calibration algorithm, and the effectiveness of the calibration result is judged through the average value of data calibration precision until calibration of the double robots is completed. Simulation modeling, collision detection and a hand-eye calibration technology are fused, a complex calibration problem is converted into a virtual environment parameter optimization process through a self-adaptive sampling strategy and a data synchronous acquisition mechanism, calibration robustness and precision are remarkably improved, and guarantee is provided for high-precision cooperative control of double robots.

The embodiment of the invention provides a high-precision machine vision calibration method and system based on multi-modal feature fusion and a medium, and the method comprises the steps: collecting calibration plate shooting based on a multi-modal sensor, and obtaining a multi-modal calibration plate image and point cloud information; extracting multi-modal image features based on the multi-modal calibration plate image, and extracting point cloud features based on the point cloud information; carrying out fusion processing on the multi-modal image features and the point cloud features based on a multi-modal fusion network; performing initial calibration on the multi-modal sensor based on a calibration algorithm, inputting the fusion feature vector into the calibration algorithm, calculating a re-projection error and a point cloud matching error, and performing optimization adjustment on an initial calibration parameter to obtain a calibration result; through multi-modal feature fusion processing, the relation between image features and point cloud features is obtained, the representation ability of the features is enhanced, a re-projection error and a point cloud matching error are analyzed based on a calibration algorithm, calibration parameters are dynamically adjusted, and the calibration precision is improved.

The present application relates to the technical field of intelligent war game, in particular to an intelligent war game simulation system based on digital twin fusion large model, which comprises a digital twin modeling unit, a large model decision unit, a deduction execution unit and a dynamic interaction unit. The digital twin modeling unit adopts a dynamic precision adaptive modeling mechanism, which can realize dynamic switching of model precision on demand, balance the demand for detailed simulation and the consumption of computing resources, and realize sub-second dynamic synchronization of virtual models and war game scenes through a timing calibration algorithm. Through the multi-modal feature analysis module, spatial adversarial, timing decision and rule trigger features are fused, and the entity performance boundary and scene rule constraint are embedded in the war game rule verification module, which can generate compliant adversarial decision parameters in line with the logic of war game, solving the problem of insufficient model precision adaptation and decision constraint.

The invention discloses an aircraft remote control delay compensation response method and system, and the method comprises the steps: obtaining airborne data, and constructing a multi-source data set; calculating bidirectional transmission delay based on a bidirectional delay estimation algorithm, and calculating initial total delay; the initial total delay is dynamically calibrated by using a self-adaptive delay calibration algorithm, the confidence coefficient is evaluated, and the delay precision is improved; deducing a flight state in a delay time period by adopting a delay deduction hybrid model, and dynamically adjusting parameters along with load; according to the deduction result and the original instruction, generating a compensation instruction containing constraints by using a model prediction control algorithm; and executing the instruction after onboard verification, comparing the actual state with the expected state, and feeding back a deviation value to optimize the weight of the next-round model so as to form a closed-loop lifting mechanism. According to the method, the problems of incomplete delay composition analysis, poor environmental adaptability, lack of constraint collaboration of compensation instructions, no closed-loop optimization mechanism and the like in the existing aircraft remote control delay compensation are solved.

The invention discloses a matrix type temperature detection system and method based on temperature-sensitive diodes, the problems of complex wiring and large temperature drift of a traditional multi-node temperature measurement system are solved through M * N matrix layout, row and column time-sharing gating and constant current driving technologies, the system adopts an independent column constant current source to ensure the measurement consistency, and a high-precision ADC and a dynamic calibration algorithm are combined, so that the measurement accuracy is improved. And the precision of + / -0.2 DEG C is realized within the range of 50-150 DEG C. The method is particularly suitable for high-density temperature measurement scenes such as battery thermal management, electronic equipment overheating monitoring and the like.

The invention relates to a bridge intelligent sensing support, a bridge early warning system and a bridge early warning method.The system comprises the steps that displacement monitoring data are obtained through real-time monitoring of a monitoring sensing module, and the displacement monitoring data comprise circumferential strain data and vertical displacement data; the side end operation module is used for correcting the displacement monitoring data in a time dimension and a space dimension based on a preset self-adaptive calibration algorithm; the cloud inversion algorithm and early warning module is used for calculating a stress state inversion result of each bridge intelligent sensing support and a bridge global displacement result based on a neural network inversion algorithm according to the corrected displacement monitoring data; when the stress state inversion result and / or the bridge global displacement result exceed / exceeds a preset safety threshold value, early warning information is triggered. The space and durability limitation of traditional external monitoring is solved, the consistency of displacement monitoring data and the actual stress state of the support is guaranteed through structural integration, and reliable technical support is provided for health monitoring of the bridge support.

The invention discloses a multichannel electronic component test system based on an adaptive calibration algorithm, and the system comprises the following modules: a signal collection and preprocessing module which is used for collecting channel signals and carrying out the standardization processing; the linear regression calibration module is used for calculating an offset parameter and a gain parameter and outputting an initial channel calibration parameter; the decoupling adaptive calibration module is used for generating an adaptive calibration parameter set; the signal correction module is used for correcting the standardized signal sequence; the feature extraction module is used for generating a multi-dimensional feature vector; the improved TimeMIL model module is used for performing time slice division, multi-scale attention coding, causal driven and prototype alignment aggregation and uncertainty quantization constraint on the multi-dimensional feature vector; and the result generation module is used for generating the electronic component performance index and the abnormity judgment result. According to the invention, the combination of multichannel signal adaptive calibration and intelligent discrimination is realized, and the precision and robustness of electronic component testing are improved.

The invention discloses a small signal output and automatic calibration system and method special for power secondary equipment. The system comprises a voltage acquisition loop, a current acquisition loop, an analog switch switching loop, an ADC sampling loop, an acquisition channel calibration module and a calibration parameter calculation module. According to the invention, the internal resistor of the DAC is combined with the operational amplifier to acquire the output current of the current acquisition loop, so that the use of external elements is avoided; meanwhile, voltage and current signals are combined and sent to the ADC sampling loop through the analog switch switching loop, calibration parameters are automatically calculated in combination with a calibration algorithm, the output precision is ensured, the influence of switch network on-resistance errors and external element drift is eliminated, and synchronous monitoring and automatic calibration are achieved.

The present invention discloses a fully wireless ocular surface pressure monitoring system based on a multi-frequency phase-shift decoupling self-calibration algorithm, relating to the technical field of intelligent ophthalmic detection. The system comprises a wearable three-layer contact lens, wherein the outer layer is embedded with a capacitive eyelid pressure sensor and a first spiral coil, and the inner layer is embedded with a piezoresistive intraocular pressure sensor and a second spiral coil, which are respectively tuned to different center frequencies to modulate pressure changes into radio frequency signals. Externally powered receiving glasses or eye masks comprise a multi-frequency transmitting coil, a rectifier circuit and a receiving coil, which supply energy to the sensing structure in the contact lens and sense and obtain a composite signal formed by spatial superposition, which is transmitted to a processing circuit and then sent to a mobile computing terminal. The terminal performs multi-frequency decoupling, sparse matrix separation and temporal self-calibration processing to generate calibration curves of eyelid pressure and intraocular pressure, thereby realizing real-time perception of dual parameters in the eyes-closed state. The system has the advantages of compact structure, high signal separation accuracy and high degree of wirelessness.