242 results about "Calibration algorithm" patented technology

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 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 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 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 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 embodiment of the invention provides a communication optical cable route detection method and system based on digital twinning, and the method comprises the steps: obtaining the position information of a mark in a communication optical cable, and integrating the multi-source information based on a differential space-time calibration algorithm; constructing a digital twinborn model comprising a base layer, a dynamic layer and an interaction layer; in the base layer, a composite base framework including a spatial topological relation, an environmental constraint boundary and a physical property reference is formed; in the dynamic layer, a knowledge graph and a rule engine are introduced, semantic analysis is carried out on dynamic data, meanwhile, an association reasoning model of the dynamic data and environment characteristics of the basic layer is constructed, when data exception is detected, potential association of the exception and the environment characteristics is mined, and the sensitivity of the model to different data is dynamically adjusted based on a reasoning result; in the interaction layer, an operation and maintenance scene feature library is constructed, and a scene self-adaption and pre-feedback mechanism is introduced. According to the detection method provided by the invention, the detection accuracy of the communication optical cable route in a complex environment is remarkably improved.

The invention discloses a PH electrode intelligent calibration method and system based on a self-adaptive calibration algorithm, and relates to the technical field of intelligent calibration control, and the method comprises the steps: carrying out the preprocessing of an original potential signal of an electrode, and obtaining a standardized potential; constructing a two-channel Gaussian process model, and outputting a calibrated pH value and uncertainty in real time; inputting a reinforcement learning decision network, automatically selecting an execution action according to a comprehensive reward function of a prediction error and resource consumption, and obtaining a new sample increment; and the new sample increment is updated to the Gaussian process and reinforcement learning model, and data-driven closed-loop adaptive calibration is completed. According to the method, the calibration pH value and the uncertainty thereof are output in real time through the two-channel Gaussian process model, and automatic balance is performed between prediction errors and resource consumption in combination with the reinforcement learning decision network, so that lag and waste of fixed period calibration are avoided, reagent, energy consumption and manual maintenance cost are remarkably reduced, and the overall operation efficiency of the system is improved.

The invention discloses a human body protection active suspension system control method, device and equipment and a storage medium, and the method comprises the steps: collecting vibration acceleration data of a vehicle body and an unsprung in real time after a human body protection function of a current vehicle is activated; converting the vibration acceleration into a vertical vibration frequency, and judging whether the vertical vibration frequency exceeds a preset vertical threshold value or not; when the vertical vibration frequency exceeds a preset vertical threshold value, the current of the active actuator is adjusted; the vehicle body vibration frequency can be effectively prevented from falling below the safety limit value, health risks caused by continuous exposure of pregnant women and other special groups to high-frequency vibration are avoided, it is ensured that the vibration environment in the driving process meets the human body tolerance standard, transmission of road surface vibration excitation is reduced through a calibration algorithm, the vehicle body vibration frequency is improved, and the driving safety is improved. The protection on the human body is enhanced, the human body is prevented from being exposed in a high-frequency vibration environment for a long time, and the control speed and efficiency of the active suspension system are improved.

The invention discloses a glucometer high-precision detection method based on a dynamic calibration algorithm and a glucometer, and relates to the field of blood glucose detection.The method comprises the steps that modal decomposition is conducted on a blood glucose current signal, the blood glucose current signal is decomposed into a plurality of frequency components, and an effective physiological component and an interference component are separated from the frequency components; performing time sequence feature extraction on the effective physiological component to obtain feature parameters at multiple moments, and performing correlation analysis on the feature parameters at the multiple moments, the environment temperature and the tissue impedance parameter to obtain a fusion feature vector; inputting the fusion feature vector into a parameter calibration model, and outputting a preliminary blood glucose value; a temperature correction coefficient is calculated according to the deviation between the environment temperature and the preset reference temperature, the initial blood glucose value is dynamically adjusted according to the temperature correction coefficient, and a final blood glucose detection value is obtained. By implementing the method, the detection accuracy of the glucometer can be improved.

The application relates to the technical field of time synchronization, and discloses a mixed time service method based on Beidou satellite navigation and 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 a TSN master node; according to the response stability of a slave node, a clock convergence function curve between nodes is constructed, whether the synchronization network is in a low jitter interval is judged based on time offset rate and time drift trend change; in combination with the node time state after directional offset suppression, a multi-channel redundant time adjustment mechanism in a time window is applied, a weight adjustment coefficient is extracted, and a non-uniform calibration factor is introduced; and according to a regression correction result, a time service stability index is evaluated in real time. The application has the advantages of improving time service stability.

The invention discloses an outdoor power equipment temperature abnormity monitoring method, device and equipment, and the method comprises the steps: carrying out the calibration processing of power equipment temperature data collected based on a dynamic collection frequency through employing a preset calibration algorithm, and obtaining the calibration temperature data; performing temperature anomaly analysis according to the calibration temperature data based on the temperature threshold, the trend threshold, the mutation mechanism and the baseline standard, and generating an anomaly analysis data packet; sending the abnormal analysis data packet to a relay gateway according to a spread spectrum technology and a check retransmission mechanism, so that the relay gateway performs data aggregation and protocol conversion processing based on an abnormal priority to obtain a transmission data packet; and triggering different temperature early warning mechanisms through the cloud platform according to the abnormality level in the received transmission data packet to realize temperature abnormality early warning. The technical problems of lack of timeliness, accuracy and remote control capability of monitoring due to lack of timeliness, weak data acquisition anti-interference capability and easy loss in the data transmission process in the prior art can be solved.

The invention discloses a marine engine manufacturing full-process decision prediction method combined with machine learning, and relates to the technical field of marine engine manufacturing and testing. The method solves the problems of model prediction deviation, confidence coefficient imbalance, response lag and the like caused by difference between a bench test and a sea test environment in key working condition feature statistical distribution, selects an adversarial domain adaptation or confidence calibration algorithm for model training, constructs a prediction model based on a deep neural network, and improves the prediction accuracy. Through adversarial optimization or post-processing calibration of the feature extraction network, the main task prediction sub-network and the domain discrimination sub-network, the generalization ability and confidence reliability of the model are improved, the model is deployed in a sea test environment and verified in real time, and closed-loop decision control is executed based on a model prediction result by calculating an error index of a predicted value and a measured value. Through data layer alignment, model layer adaptation, verification layer verification and execution layer control, the prediction accuracy and operation safety of the marine engine in the sea test stage are remarkably improved.

The invention discloses an infusion monitoring and automatic blocking device and method. The device comprises a blocking mechanism, a monitoring module and a control module. The blocking mechanism controls the first abutting piece and the second abutting piece to be close to each other through the driving piece so as to clamp the infusion tube. The monitoring module adopts a double-sensor scheme of an upper sensor and a lower sensor and is used for monitoring liquid drop pulse and liquid level height. And the control module operates a weighted average data fusion algorithm based on confidence, and calculates the actual dripping speed after fusion. According to the device, the accuracy and reliability of infusion state monitoring are improved through a dynamic calibration algorithm and data fusion. The control module can accurately identify three main risk states, namely dripping speed and flow abnormity, infusion completion and pipeline gas abnormity. When it is judged that the infusion tube flow channel is abnormal, the control module drives the blocking mechanism to rapidly block the infusion tube flow channel, a double confirmation mechanism is arranged to provide safety redundancy, a safety closed loop of'detection-decision-execution 'is formed, and the safety and management efficiency of clinical infusion are improved.

The invention relates to a target positioning method based on radar photoelectric linkage guidance, and belongs to the technical field of edge-sea-air defense three-dimensional management and control of multi-source sensor fusion. According to the method, a dynamic calibration mechanism is provided, a real-time timestamp alignment and navigational speed calibration algorithm is introduced on the basis of traditional calibration, and radar measurement errors and coordinate conversion errors are effectively weakened; through an SAMURAI tracking algorithm of improved Kalman filtering, stable target tracking under shielding, appearance change and similar target interference is realized, and identity and position consistency is kept; the three-dimensional-to-two-dimensional projection conversion is adopted, the calculation precision of the pitch angle and the azimuth angle is improved, and the influence of radar latitude and longitude errors is reduced. Compared with an existing method, the method has the advantages that the precision and stability of joint positioning of the perimeter target in a complex environment are remarkably improved, the problem of target tracking jump is effectively solved, and the method has wide application prospects in scenes such as boundary security and protection and marine monitoring.

The invention discloses an inclinometer calibration method for oil exploration, and relates to the technical field of oil exploration. Comprising the steps of S1, setting up a calibration environment and fixing an inclinometer, S2, collecting data of a multi-attitude sensor, S3, calculating compensation parameters by a calibration algorithm module, S4, writing and preliminarily verifying the compensation parameters, S5, calibrating the adaptability of a temperature and humidity environment, S6, tracking and calibrating long-term stability, S7, compensating and calibrating magnetic field interference, S8, calibrating the precision of a data acquisition module, and S9, calibrating and accepting system joint debugging. Through the steps S1, S2 and S3, a basic calibration system with a stable environment, comprehensive data and accurate calculation is constructed, and the basic measurement accuracy of the inclinometer is remarkably improved; through the steps S5, S7 and S9, a scenarized calibration closed loop of environmental adaptation, interference resistance and actual combat verification is formed, so that the inclinometer can keep stable precision in a temperature zone of-20 DEG C to 60 DEG C, a wet zone of 30% RH-90% RH and a magnetic field interference environment, and the adaptability and reliability of the inclinometer in an actual exploration scene are greatly improved.

The invention relates to a digital-intelligent automatic point alignment and full information verification method based on a power distribution terminal tester, which comprises the following steps of: acquiring electrical quantity signals and operating parameters of a terminal through the tester, and establishing communication connection through a digital-intelligent point alignment module; starting a three-remote check matrix model to perform matrix check on telemetering, remote signaling and remote control functions, calling an FFT harmonic synthesis telemetering calibration algorithm to dynamically calibrate a deviation value, introducing an abnormal attribution model based on a Bayesian network to perform probability reasoning on abnormal data, generating a report containing abnormal information and calibration suggestions, and uploading the report. The method improves the verification efficiency and overcomes the problem that the existing mode is tedious; checking accuracy is improved, and the problem that measurement deviation is difficult to correct is solved; abnormality processing capability is enhanced, defects of insufficient attribution capability are made up, stable operation of the power distribution terminal is guaranteed, and support is provided for power grid safety.

The invention discloses a color consistency calibration system for AMOLED flexible display, which relates to the field of display and comprises a deformation sensing module, a color acquisition module, an aging state sensing and dynamic compensation module, a user personalized color gamut adaptation module, a data fusion processing module, a self-adaptive calibration algorithm module, a calibration execution module and a real-time feedback verification module. According to the AMOLED flexible display color consistency calibration system, screen body stress and deformation data are captured through deformation perception, the pixel attenuation state is monitored through aging perception, a personalized module adapts to user color preference, partition integrated calibration parameters are generated through data fusion and a self-adaptive algorithm, a closed loop is formed through calibration execution and real-time feedback, and the color consistency of the AMOLED flexible display is calibrated. According to the AMOLED flexible screen color consistency calibration method, the defects that deformation-aging composite drift is ignored and personalized adaptation is lacked in the prior art are overcome, full-scene and full-life-cycle color consistency calibration of the AMOLED flexible screen is achieved, accuracy and user experience are considered, and the AMOLED flexible screen color consistency calibration method is suitable for various flexible display terminals such as folding screens and curled screens.

The invention provides a photoelectric solar irradiance meter self-calibration device for outdoor monitoring and a calibration method, and belongs to the technical field of photovoltaic monitoring. The device comprises a sky imager, a solar irradiance meter for monitoring, a standard solar irradiance meter, a sealed darkroom, a three-dimensional adjusting bracket and a waterproof sealed box, wherein a dual-channel temperature collector, a dual-channel voltage collector and a control, data processing and storage module are integrated in the waterproof sealed box. The sealed darkroom normally protects the standard irradiance meter to prevent the standard irradiance meter from aging and dust deposition; the dual-channel collector synchronously collects temperature and voltage of a standard solar irradiance meter for monitoring, and supports a calibration algorithm to realize dynamic updating of sensitivity; the three-dimensional adjusting bracket ensures that the device is parallel to the mounting plane of the photovoltaic module, and the angle response matching degree is improved; the sky imager judges the calibration weather condition to guarantee the effectiveness of the calibration environment; the control module realizes automation of a self-calibration process, adapts to an outdoor long-term monitoring scene, and realizes continuous and accurate measurement of photovoltaic solar irradiance.

The invention discloses a multi-scene high-precision positioning method based on near ultrasound, and relates to the technical field of positioning, and the method comprises the steps: obtaining deployment parameters and environment reference parameters, and constructing a standardized reference database; deploying a near ultrasonic base station and a positioning terminal, and cooperatively collecting a near ultrasonic signal and a Beidou signal; performing targeted cleaning and standardization processing on the near ultrasonic signal and the Beidou signal; extracting features of the cleaned near ultrasonic signal and the Beidou signal, and performing fusion positioning calculation to obtain a positioning result; a positioning result is corrected through a self-calibration algorithm and an AI deep optimization model, and multi-dimensional positioning feedback is realized; and outputting a multi-dimensional positioning result. In actual use, an AI-driven scene algorithm is adopted for positioning optimization, indoor and outdoor centimeter-level seamless positioning is achieved, the method is adaptive to complex scenes such as strong electromagnetism, strong noise and multi-reflection, the deployment cost is remarkably reduced, and 1D, 2D and 3D positioning results are accurately output according to service requirements.

The application discloses a kind of steel rail crawling fast measurement method and device based on multi-camera cooperative measurement, it is related to railway track detection technical field, method includes the multiple crawling identification modules of equidistance setting in the track area to be measured, each crawling identification module includes two groups of symmetrically arranged rail displacement identification fixed on rail waist;Two groups of symmetrically arranged sleeper reference identification fixed on the top surface of rail sleeper;Positioning mark fixed on the way side fixed building;Device includes the synchronous trigger control module of control image acquisition module;Image acquisition module includes multiple area array cameras of image synchronous acquisition, the multiple area array cameras are transmitted to data processing module with the image information collected;Data processing module prestore calibration algorithm and displacement calculation;Solve the problem of low precision, poor efficiency, difficult to synchronously acquire rail and sleeper displacement data, insufficient adaptability in the existing rail crawling measurement, and realize automatic, fast, high-precision crawling quantity monitoring.

The application discloses a kind of big data-based wisdom campus traffic management system and method, and the application relates to wisdom campus management technical field, the present application is by collecting RFID card reader data, monitoring video data, timetable data, and the calibration number is generated by the monitoring data calibration algorithm driven by timetable, based on decision tree and the split strategy of compound rank is constructed risk grading model, by input real-time calibration number, timetable number, time period type, RFID coverage, historical congestion frequency, weather condition, output corresponding risk level, and according to real-time risk level, corresponding measures are taken, the specific reason of generating this risk can also be analyzed.The present application can dynamically adjust risk level, significantly reduce misjudgment and omission, realize fine risk control.

The invention discloses a vehicle door unlocking control method, electronic equipment and a program product, and the method comprises the steps: when a vehicle collides, collecting a collision signal of the vehicle, and transmitting the collision signal to an airbag controller; the airbag controller generates at least three types of unlocking judgment signals based on a calibration algorithm and the vehicle operation parameters; when any kind of unlocking judgment signal meets the corresponding sending condition, the air bag controller sends a corresponding vehicle door unlocking signal to the vehicle body domain controller; after the vehicle body domain controller receives the vehicle door unlocking signal, an unlocking instruction is sent to the door lock controller; and the door lock controller controls the door lock module to execute an automobile door unlocking action. The three types of unlocking judgment signals are set to correspond to different collision judgment strategies respectively, automatic unlocking of the vehicle door can be triggered in different collision scenes, and therefore the applicability and accuracy of vehicle door unlocking control are ensured.

The utility model discloses a high accuracy temperature detection circuit, it includes signal conditioning module, clock synchronization module and sectional type quantization module. Sectional type quantization module starts through the rising edge of external periodic signal, the falling edge of internal signal ends, ensures that the quantization result is accurate, optionally, contains multiple quantization channels and control unit, adjusts the switch state through delay inversion circuit accurately, and optimizes quantization process. The present application can reduce the power consumption, simplify the manufacturing process, improve real -time and the flexibility of the scope of application, reduce the dependence on complex calibration algorithm simultaneously, provide brand -new solution for high accuracy temperature detection.

The invention relates to the technical field of computer vision and natural language processing, in particular to a barrier-free drama-oriented real-time sign language-subtitle-voice three-dimensional synchronous generation system. Comprising a multi-mode drama content collection module, a drama semantic and emotion deep analysis module, a three-dimensional emotional content generation module, a millisecond-level synchronous calibration module, a personalized demand adaptation module, a multi-terminal output module and a feedback iteration module which are linked in sequence. The multi-mode drama content acquisition module supports offline theaters and online live broadcast / recorded broadcast scenes and can acquire line audios, actor performance data and scene auxiliary data, the deep binding of role personalization, plot emotion, scene atmosphere and barrier-free content is realized for the first time, the pain points of'action stiffness and emotion missing 'of a general system are solved, and the system has the advantages of being high in practicability and high in practicability. The sign language / voice / subtitle drama adaptation degree is improved to 95% or above, the overall time delay is controlled within 100 ms through a synchronous calibration algorithm and is far lower than the standard of 200 ms in the industry, and the drama continuity is guaranteed.

The application discloses a time-to-digital converter based on pulse stretching. The time-to-digital converter structure combines frequency multiplication delay locked loop, pulse stretching circuit and calibration circuit, guarantees high resolution, effectively increases the range of the time-to-digital converter, and can reduce the influence of PVT. The calibration circuit has simple structure, low calibration cost, and is suitable for the calibration of the pulse stretching circuit. In addition, the calibration algorithm for the static phase error of the frequency multiplication delay locked loop only needs to increase a 1bit counter, the additional circuit cost is very small, and the influence of the static phase error of the frequency multiplication delay locked loop can be overcome.

This invention relates to a method, system, and medium for measuring the spatial parameters of a monocular target object based on a 2D camera. The method includes: acquiring a calibration board image and an original distorted image captured by the 2D camera; calibrating the calibration board image using a calibration algorithm to obtain calibration parameters; correcting the original distorted image using the calibration parameters to obtain a corrected image; performing target detection; and outputting the external contour and target contour feature points of the target object; classifying the target contour feature points into upper boundary feature points and lower boundary feature points; calculating the relative distance between the target object and the 2D camera based on the lower boundary feature points and the calibration parameters; and performing curve fitting on the upper and lower boundary feature points and the lower boundary feature points, respectively, and calculating the actual height of the target object based on the calibration parameters. Compared with existing technologies, this invention has advantages such as improved measurement accuracy and adaptability to complex boundary targets.

The application discloses an industrial robot calibration device and method based on a structured light system and a hemispherical target. The application takes a double target fixed at both ends of a rigid ruler and composed of at least three precise standard hemispheres as a calibration reference, combines a structured light three-dimensional measurement technology, constructs a double-constraint calibration algorithm based on fixed distances and fixed relative postures, and realizes calibration of kinematic parameters of an industrial robot. Through a low-cost structured light system and a standardized double-hemispherical target reference element, high-precision standards required by calibration of the industrial robot are met, the calibration operation threshold and equipment cost are greatly reduced, and stable and reliable constraint conditions are provided for identification of kinematic parameters of the industrial robot.