244 results about "Calibration instructions" patented technology

The invention relates to the technical field of online calibration, in particular to a multi-parameter fusion intelligent electric energy meter online calibration method and system, and the method comprises the following steps: collecting voltage waveforms, current harmonics and active power data, dividing windows, calculating a covariance matrix, and generating a feature set; a power factor curvature extreme value and a temperature inflection point offset are analyzed to generate an interference identifier, current density distribution and a voltage distortion spectrum are jointly analyzed to extract a harmonic energy ratio to generate a feature vector, and phase compensation is performed on a pulse sequence to generate a calibration instruction set. According to the method, the covariance matrix is constructed by synchronously collecting voltage and current power parameters, the abnormal mark section is generated by combining the temperature change and the covariance difference value, the environment disturbance and the real deviation are effectively distinguished, and the temperature hysteresis effect is identified through the power factor curvature extreme value and the temperature inflection point offset. And combining current density and voltage distortion spectrum analysis to extract a fundamental wave and harmonic wave energy ratio, establishing a composite calibration reference, and dynamically adjusting a pulse duty ratio to realize harmonic wave energy compensation.

The invention discloses a lithium battery diaphragm whole-process production data transmission optimization method and system, and particularly relates to the technical field of data transmission. Sensor data of a lithium battery diaphragm whole process is collected through a sensor array, the sensor data is extracted to obtain actual process parameters, and the actual process parameters are compared with preset process parameters; outputting the abnormal data; based on a space-time topological structure of a sensor, calculating space-time-function coupling weights among abnormal data, constructing a structural coupling matrix, identifying error clustering candidate bodies, and extracting space-time distribution characteristics and abnormal combination modes of the error clustering candidate bodies; performing structural classification on the error clustering candidate bodies by utilizing a preset rule engine, and outputting a deviation report; and outputting a sensor calibration instruction and a process fine tuning instruction based on the deviation report, thereby solving the problems that the deviation source is difficult to accurately identify, the key abnormal data transmission is not timely and the false alarm rate is high.

The invention discloses a digital twinning progress tracking and risk pre-control method for hydraulic engineering construction, and relates to the field of hydraulic engineering construction, and the method comprises the steps: obtaining mechanical positioning, material entering and environment monitoring data through a multi-source sensing terminal, and generating a time-space aligned construction situation data set; a progress weight template is activated based on the construction stage identifier, and a dynamic weight vector is generated in combination with the environment data; comparing the construction situation data with the reference model to calculate a comprehensive progress deviation index; when the index exceeds the limit, constructing a resource topological relation graph to generate an elastic scheduling instruction; outputting a derivative risk probability through the risk conduction model and generating an optimized scheduling instruction set; triggering a calibration instruction to feed back a correction parameter according to the execution data; by establishing a three-level calibration mechanism linked with the construction progress, the risk change and the environmental disturbance, layered accurate adjustment of data acquisition, environmental factors and model parameters is realized.

The invention relates to an intelligent control method, system and device for an automobile seat and a medium, and belongs to the field of automobile seat adjustment control. The intelligent control method comprises the steps that a control instruction data packet from a mobile terminal is received and converted into a vehicle CAN bus protocol data frame; analyzing an operation mode identifier in a vehicle CAN bus protocol data frame, and matching a corresponding target attitude parameter set; based on the real-time temperature data in the vehicle, dynamic compensation calculation is executed on the target attitude parameter set, and an after-compensation execution instruction set is generated; a motor control signal is sent to a seat executing mechanism; calculating a deviation value between the feedback signal data and the compensated execution instruction set, and if any deviation value exceeds a preset deviation threshold value, generating a mechanism calibration instruction; and acquiring final execution state data of the seat execution mechanism, and feeding back the final execution state data to the mobile terminal. Intelligent seat adjustment based on real-time feedback can be achieved, and it is ensured that a driver obtains the best comfortable experience in different scenes.

The invention discloses a measuring instrument automatic calibration method and system based on big data, and the method comprises the steps: obtaining the multi-dimensional operation data of a measuring instrument in real time through a sensor, and covering the equipment state and environment parameters; processing the data to generate an operation data set, and extracting a fluctuation characteristic value of the quantitative state change by adopting time sequence analysis; when the fluctuation characteristic value exceeds a preset threshold value, triggering depth characteristic decomposition to obtain deviation distribution information; on the basis of the information and in combination with historical records, the optimal calibration opportunity is judged through a machine learning model; and a calibration instruction is automatically generated and issued to the instrument control module to execute calibration. According to the method, the defects that traditional calibration depends on manpower and is not accurate in time are overcome, intelligent and automatic calibration based on the real state is achieved, the calibration precision and efficiency are remarkably improved, and the adaptability and robustness of the system in the complex environment are enhanced.

The invention belongs to the field of virtual image display, particularly relates to a spherical reflection cavity virtual calibration method based on a neural radiation field, and aims to solve the problems that micron-level deviation is difficult to accurately capture due to interference of a high-reflection surface, and an executable correction instruction cannot be generated by fusing process constraints. The method comprises the following steps: deploying image acquisition equipment around a cavity to synchronously capture a multi-view optical image sequence; inputting a neural radiation field model, reconstructing a three-dimensional geometric structure and optical properties through a volume rendering technology, and dynamically optimizing and fitting reflection characteristics and curvature changes of a carbon fiber material; extracting spherical radius, local curvature and boundary contour parameters, and comparing the parameters with design specifications point by point to generate a deviation distribution diagram; generating a multi-level calibration instruction set based on the deviation distribution diagram in combination with the laying layer tolerance and the assembly clearance; and outputting an instruction to the manufacturing system to execute physical adjustment, and re-collecting the image to verify the calibration effect until the acceptance index is met. According to the invention, the deviation capturing precision is improved, and a correction instruction can be generated.

The invention relates to a state of charge calibration method and device, a battery management system and a storage medium. The method comprises the following steps: determining equivalent cycle times of battery charging and discharging; under the condition that the equivalent cycle number is greater than a preset number threshold, sending a charge state calibration request; and receiving a state-of-charge calibration instruction returned based on the state-of-charge calibration request, and performing state-of-charge calibration processing on the energy storage battery according to the state-of-charge calibration instruction. By adopting the method and the device, the judgment accuracy of the calibration opportunity can be improved, and the accumulated error of the SOC is within an acceptable range.

The invention relates to the technical field of production state management, in particular to an LCD display screen production state collaborative management method based on the industrial internet, which comprises the following steps of: acquiring execution cycles and response delays of multiple devices, performing aggregation analysis, generating a rhythm synchronization parameter table, performing time sequence alignment to calculate time sequence offset and generating a time sequence calibration instruction; the method comprises the following steps of: analyzing current power and cycle deviation to form an equipment coupling trend, monitoring a scheduling rhythm correction execution sequence, dynamically estimating delay and optimizing a production state management cooperative control result, realizing cooperative measurement and difference identification through multi-equipment rhythm normalization aggregation, and improving state response precision and synchronization consistency through time sequence alignment; load coupling analysis balances energy consumption distribution and rhythm, whole-line scheduling correction realizes production rhythm balance and continuous operation, the resource utilization rate and the production efficiency are improved, process waiting and energy consumption fluctuation are reduced, and the system cooperation and self-adaptive regulation and control capability is enhanced.

The invention relates to an automatic printing calibration method and system combining vision and AI and a storage medium, a multi-mode sensing unit integrated on a printing head assembly synchronously collects two-dimensional images, three-dimensional shapes and working spacing data of a printing area in real time, and data fusion is carried out by using a model based on a neural radiation field; generating a high-fidelity multi-dimensional digital mapping; carrying out defect identification and positioning by adopting a pre-trained convolutional neural network CNN model, and predicting an optimal adjustment parameter according to the defect information and the historical sequence through a long short-term memory network LSTM model; the edge calculation and control unit is combined with a material characteristic database to generate a hierarchical calibration instruction in a millisecond level, adopts fuzzy PID self-optimization control to dynamically set PID control parameters, and is combined with feed-forward compensation of the inertial measurement unit to perform accurate, smooth and robust control on an execution mechanism, so that the accuracy of calibration is improved. And full-automatic, high-precision and real-time online calibration of the printing process in a complex industrial environment is realized.

The invention discloses a dynamic calibration control method for the detection precision of a non-standard automatic testing fixture, and particularly relates to the field of industrial automation and control, which comprises the following steps of: constructing a real-time dynamic error field model of the testing fixture; a distributed optical fiber sensing network and a miniature laser interferometer cooperatively collect real-time detection data and spatial-temporal variation errors under a multi-physics coupling effect, a precision degradation track is predicted based on spatial-temporal variation error data, a pre-compensation signal is generated, and a self-adaptive Kalman filtering algorithm is adopted to generate a precision compensation parameter. Environment temperature, vibration and electromagnetic interference data are monitored in real time, environment disturbance data are generated, a hybrid controller combining nonlinear model predictive control and reinforcement learning is adopted, multi-source data are fused, a calibration instruction is generated through multi-target optimization, and an execution mechanism is driven to achieve online dynamic calibration. And digital threads and transfer learning are integrated to realize full-life-cycle data closed-loop management and continuous optimization.

The invention provides a production equipment state real-time analysis method and system based on edge calculation, and relates to the technical field of information, and the method comprises the steps: analyzing the dynamic change trend of a light beam central axis according to the offset trajectory of the light beam central axis, and determining the spatial distribution characteristics of the light beam axis through the dynamic change trend of the light beam central axis in combination with an LED array arrangement SIC mode; if the adjustment angle in the lens calibration instruction set exceeds a preset angle threshold, dynamically adjusting the position of the optical axis of the lens according to the offset amplitude and direction of the optical axis, compensating the offset of the light beam axis in real time, and obtaining a calibrated optical axis parameter; according to the color temperature distribution uniformity, determining a target lens position through a lens position adjustment attribute; according to the calibrated optical axis parameters and color temperature distribution uniformity, stable light beam center axis distribution is determined, spectrum consistency is determined, and a performance evaluation data set is obtained through comprehensive evaluation.

The invention relates to the technical field of medical big data analysis, and discloses a hospital medical record data anomaly analysis method based on big data. According to the method, multi-source medical record data including diagnosis and treatment event records, nursing operation sequences and patient sign monitoring streams in a hospital information system are collected, and structured reforming is carried out. And constructing a medical record element interaction graph based on the reformed data, and detecting an abnormal state conduction path between the data elements through the graph model. And performing hierarchical traceability calculation according to the detected conduction path, positioning an abnormal source and generating a positioning report, and finally outputting a calibration instruction set according to the report. According to the method, the abnormal conduction chain is systematically identified from the correlation perspective, and the root source of the abnormality can be automatically and accurately traced, so that the logicality and the positioning accuracy of the medical record data abnormality analysis are improved.

The invention relates to the technical field of power system energy storage optimization, and discloses a terminal micro-grid energy storage optimization configuration method and system and a computer readable storage medium. Comprising the steps of generating load demand probability distribution and a new energy output confidence interval through deep learning and Bayesian probability modeling based on historical load and new energy monitoring data, extracting boundary parameters and mapping the boundary parameters into a quantum state initial solution set, and generating a quantum coding instruction set; a quantum algorithm population is initialized, a non-dominated solution set sequence is generated through quantum gate evolution operation, and a Pareto leading edge output optimization configuration scheme is screened; verifying feasibility in combination with local voltage data, and generating an executable control instruction set after fine tuning of capacity-position weight; and driving the energy storage unit to execute charging and discharging operation, collecting operation data, updating model parameters, finally separating probability weights and quantum deviations, adjusting a Bayesian model and resetting quantum gate parameters to generate a calibration instruction set. According to the invention, the energy storage configuration efficiency and precision can be obviously improved.

The invention discloses a high-precision zero magnetic flux compensation method, which comprises the following steps of: acquiring a detected current signal, and generating a magnetic field detection interface structure after noise reduction, frequency band extraction and magnetic sensitive configuration processing; performing magnetic field analysis, feature matching and resource optimization based on the data to generate efficient compensation parameters; final compensation output is generated through interference identification, compensation recombination and power adaptation; generating a calibration trigger mark through standard value comparison, stability evaluation and threshold judgment; and finally, forming a closed-loop calibration instruction set through type identification, strength calculation and time sequence arrangement, and completing parameter updating and verification. According to the invention, the precision and stability of current measurement are significantly improved, the interference of a complex environment is effectively suppressed, and the characteristics of strong adaptability and low power consumption are achieved.

The invention discloses a direct current motor control and automatic detection system and method, the system comprises an upper computer, a lower computer and a CAN bus communication unit, the upper computer comprises a calibration module, a position control module, a self-inspection module and a communication interface, and the calibration module is used for initiating an automatic calibration instruction and receiving and displaying a calibration result; the position control module is used for generating a target position instruction and receiving and dynamically displaying the real-time position of the motor; the self-checking module is used for initiating a one-key self-checking instruction and displaying a self-checking result; the lower computer comprises a main control chip, the main control chip is provided with an H-bridge driving circuit and an encoder acquisition circuit, the H-bridge driving circuit is used for driving the direct current motor to rotate forwards and backwards, and the encoder acquisition circuit is used for acquiring motor position signals; the CAN bus communication unit is connected with the communication interface of the upper computer and the main control chip of the lower computer through the USB to CAN module; according to the invention, faults can be automatically detected in the production and use processes of the DC motor, and the efficiency of production personnel and the product quality are improved.

The invention provides a multi-target adaptive optical tracking method and system for an unmanned intelligent turntable. The method comprises the following steps: acquiring a video stream and turntable attitude data on an unmanned intelligent turntable; carrying out scene understanding operation on the video stream, fusing the dynamic attention area and extracting spatial distribution information of a plurality of moving targets in a rotary table coordinate system; calculating an optical deformation parameter of the liquid lens, and driving the liquid lens to execute non-uniform optical curved surface adjustment, so that a focus area simultaneously covers a plurality of spatially dispersed moving targets; receiving distance data fed back by the distance measuring equipment, carrying out cross validation on the distance data and actual optical parameters of the adjusted liquid lens, and generating a cooperative calibration instruction when the deviation exceeds the tolerance; and synchronously updating the dynamic region of interest identification logic of scene understanding and an optical deformation parameter calculation strategy according to the instruction. According to the invention, the stability and spatial positioning precision of multi-moving-target tracking in a wide-area complex scene are improved.

The invention belongs to the technical field of calibration test, and provides a calibration test system and calibration test equipment, and the calibration test system comprises the calibration test equipment, control equipment and a plurality of to-be-calibrated test products. The calibration test equipment is connected with the control equipment and the plurality of to-be-calibrated test products, and is configured to execute the following steps: responding to a received calibration instruction issued by the control equipment, performing calibration test on the plurality of to-be-calibrated test products at the same time, and respectively obtaining a calibration result corresponding to each to-be-calibrated test product; and the control equipment is configured to execute the following steps: when the calibration result corresponding to each to-be-calibrated test product uploaded by the calibration test equipment is received, displaying the calibration result corresponding to each to-be-calibrated test product in the user interaction interface.

The invention relates to the technical field of sensor calibration, and discloses a calibration method and device for a vehicle camera, a vehicle and calibration equipment. The calibration equipment comprises a movable robot and a calibration plate arranged on the movable robot. The calibration method comprises the steps that a calibration instruction for a target camera is sent to calibration equipment, so that a movable robot drives a calibration plate to move according to a target calibration track corresponding to the target camera; in the moving process of the movable robot, image data collected by the target camera for the calibration plate, three-dimensional point cloud data collected by a laser radar carried by the vehicle and vehicle attitude data collected by an inertial measurement unit carried by the vehicle are obtained; calculating and determining internal and external parameters of the target camera according to the image data, the three-dimensional point cloud data and the vehicle attitude data; and storing the internal and external parameters as calibration parameters of the target camera to an electronic control unit of the vehicle. According to the invention, the calibration efficiency and precision of the vehicle camera can be improved.

The invention provides an ice water accumulation body permeability coefficient dynamic calibration method which comprises the following steps: responding to a dynamic calibration instruction, analyzing an identification code, calling an environment parameter set and generating a permeability characteristic spectrum; selecting a calibration time period for storage; after verification is triggered, a verification parameter group is generated, real-time response data is received, a calibration result is output after interference filtering, correction, adjustment, feature extraction and similarity calculation, and the permeability coefficient is corrected if verification is passed. According to the invention, the permeability coefficient of the ice water accumulation body can be accurately calibrated in real time, the accuracy of glacier melt water seepage characteristic analysis is improved, and the reliability of glacier engineering and environment monitoring is enhanced.

The invention provides an amplitude-phase regulator debugging method and device, an upper computer and a storage medium, and belongs to the technical field of automatic control. The method comprises the steps that a zero calibration instruction is issued to an amplitude-phase regulator; sequentially issuing a plurality of first set attenuation values to the amplitude-phase regulator, and drawing a first curve fluctuation diagram of the attenuator in the to-be-tested frequency band based on a plurality of first actually measured attenuation values returned by the test instrument; sequentially issuing a plurality of first set phase shift values to the amplitude-phase regulator, and drawing a second curve fluctuation diagram of the phase shifter in the to-be-tested frequency band based on a plurality of first actually measured phase shift values returned by the test instrument; selecting a curve fluctuation graph with a relatively large fluctuation degree value as a target curve graph, and performing frequency band division based on the target curve graph to obtain a plurality of sub-frequency bands to be measured; and in each sub-frequency band to be tested, debugging the attenuator and the phase shifter respectively. According to the amplitude-phase regulator debugging method and device, the upper computer and the storage medium provided by the invention, the debugging efficiency of the amplitude-phase regulator can be improved, and the debugging difficulty can be reduced.

The invention provides an on-line intelligent calibration method and system for electrical parameters of a chip, and relates to the technical field of parameter calibration, and the method comprises the steps: carrying out the physical state sensing of a target chip, and obtaining multi-mode state data; real-time working scene recognition is carried out; calling a historical time sequence state sequence; performing electrical parameter dynamic deviation prediction, and outputting a target parameter prediction deviation value; based on the time sequence violation event and the voltage overrun event, performing dynamic weighted accumulation to obtain an abnormal accumulation factor; performing a multi-objective optimization decision, and generating a dynamic calibration instruction; and mapping the parameters into hardware configuration parameters of an adjustable circuit module in the target chip, and carrying out on-line real-time calibration on the electrical parameters. The technical problems that in the prior art, chip electrical parameter calibration mostly depends on static testing during factory leaving, electrical parameter changes of the chip in different working stages, especially in the long-term operation process are neglected, and performance loss and reliability reduction of the chip in operation are caused are solved.

The invention relates to the technical field of optical cross connection device calibration, and discloses an FAU array self-calibration collimation and low-crosstalk coupling system for an OCS. According to the system, optical axis deviation, light spot parameters and inter-unit crosstalk data of each unit are acquired in real time through a distributed optical sensing array. And the light path state mapping module constructs a dynamic topological mapping graph according to the data, and globally represents the array coupling state. The self-adaptive calibration module calculates calibration requirements and generates an original instruction, and the crosstalk suppression coordination module analyzes the estimated influence of instruction adjustment on crosstalk of adjacent units, restrains the instruction which may deteriorate the crosstalk, and generates an optimized calibration instruction. And the collaborative execution module drives the micro actuator to complete submicron-level pose adjustment according to the final instruction. According to the system, active collaborative optimization of alignment precision and crosstalk suppression in the calibration process is realized, and the overall performance and stability of the system are improved.

The invention belongs to the technical field of industrial Internet of Things, and particularly discloses an industrial Internet of Things-based energy consumption detection method, system and device and a medium, and the method comprises the steps: carrying out the time sequence alignment of a power curve, a current waveform and voltage stability data collected by a multi-source sensor according to a timestamp marking technology, and obtaining a time sequence synchronization data set; analyzing current waveform frequency domain characteristics in the time sequence synchronization data set based on fast Fourier transform, judging whether an abnormal frequency component caused by electromagnetic interference exists or not, and obtaining interference source equipment; according to the interference source equipment, the transmission sequence of the real-time calibration instruction is adjusted through a priority scheduling algorithm, and an optimized instruction sequence is obtained; according to the optimization instruction sequence, updating power distribution parameters of the parallel equipment through an incremental data fusion method; the objective of the invention is to solve the problem of inaccurate energy efficiency evaluation caused by electromagnetic interference, voltage fluctuation and energy consumption deviation during cooperative operation of multiple devices in an industrial scene.

The invention discloses a control instruction rate matching method of a distributed controller-driver, and relates to the technical field of distributed control, and the method comprises the steps: carrying out instruction frequency detection through employing a clock source of the driver, and obtaining a frequency error value of a controller instruction; performing interpolation caching processing on the controller instruction based on the frequency error value of the controller instruction to obtain frequency error information of instruction caching; and performing dynamic period adjustment according to the frequency error value of the controller instruction and the frequency error information of the instruction cache, and obtaining a control instruction rate matching result. Frequency detection and dynamic period adjustment are independently completed through the driver, a controller does not need to participate in clock calibration, the communication bandwidth is prevented from being occupied by a calibration instruction, and the system communication efficiency is remarkably improved; and in combination with interpolation cache processing, clock skew can be compensated in real time, the instruction frequency error is controlled within an extremely low range, the system fluctuation risk is effectively reduced, a communication protocol does not need to be modified, and the method is completely compatible with an existing hardware architecture.

The invention discloses an electric power real-time dynamic carbon factor metering and monitoring system, which belongs to the technical field of electric power systems, and comprises a data acquisition module used for acquiring multi-source data of a power generation side, a power grid side and a user side of an electric power system in real time, verifying the multi-source data, generating high-frequency data streams, and transmitting the high-frequency data streams to a data processing module; the high-frequency data stream comprises renewable energy output fluctuation data, load change data and power grid topological structure data; the dynamic calculation module is used for generating time-sharing and partitioned dynamic carbon factors based on the high-frequency data stream; the monitoring feedback module is used for generating a carbon flow path track based on the dynamic carbon factors and generating a calibration instruction set in combination with deviation records in the historical dynamic carbon factors; and the optimization output module is used for recalculating the dynamic carbon factor based on the calibration instruction set and the real-time multi-source data, and outputting the optimized dynamic carbon factor of the time-sharing partition to an external carbon accounting system. According to the method, the problem that the traditional annual average factor cannot reflect the space-time dynamism is solved by calculating the carbon factor of the time-sharing partition.

The invention provides a temperature calibration method, device and equipment for a wireless sensing terminal and a storage medium, and the method comprises the steps: testing the wireless sensing terminal under a preset temperature condition, collecting external temperature data and sensor output data, and obtaining a test data set; according to the test data set, carrying out modeling processing on sensor output data to obtain a temperature hysteresis error; establishing a calibration model containing an undetermined coefficient according to the temperature hysteresis error and the external temperature change rate, and solving the undetermined coefficient to obtain a calibration coefficient; and when a temperature calibration instruction is received, performing compensation operation on the sensor output data according to the calibration coefficient and the real-time measured external temperature change rate to obtain calibrated sensor output data. According to the method, the correlation model between the temperature hysteresis error and the external temperature change rate is established, effective compensation of the hysteresis error caused by dynamic temperature change is achieved, additional hardware does not need to be added, and system complexity and cost are reduced.

This invention belongs to the field of virtual image display, specifically relating to a virtual calibration method for spherical reflective cavities based on neural radiation fields. It aims to solve the problems of difficulty in accurately capturing micron-level deviations due to interference from highly reflective surfaces and the inability to integrate process constraints to generate executable correction instructions. The invention includes: simultaneously capturing multi-view optical image sequences by deploying image acquisition devices around the cavity; inputting a neural radiation field model, reconstructing the three-dimensional geometric structure and optical properties using volume rendering technology, and dynamically optimizing the fitting of carbon fiber material's reflectivity and curvature changes; extracting spherical radius, local curvature, and boundary contour parameters, and comparing them point-by-point with design specifications to generate a deviation distribution map; generating a multi-level calibration instruction set based on the deviation distribution map combined with layup tolerance and assembly gaps; outputting instructions to the manufacturing system to perform physical adjustments, re-acquiring images to verify the calibration effect, until acceptance criteria are met. This invention improves deviation capture accuracy and can generate correction instructions.

The present application relates to the technical field of gas sensor calibration, and particularly relates to an intelligent calibration method for a methane sensor in a coal mine, which comprises the following steps: establishing a near-field session and obtaining a permeation tube metrological certificate parameter and a calibration instruction set; obtaining a zero point data set and a sealing score in a closed microcavity, generating a standard concentration trajectory according to the metrological certificate, and collecting a standard section data set; forming original collected data according to joint target optimization of a temperature time profile and an H-infinity norm information matrix; implementing robust deconvolution and variational Bayesian inference based on a first-order inertial dynamic model to obtain a set of robust point estimation parameters, a posterior distribution and a combined uncertainty; calculating a Wasserstein barycenter on a section adjacency graph and solving a one-norm uniform optimization release correction parameter set to realize traceable, robust and section-consistent online correction and re-calibration triggering.

The present application relates to production management technical field, especially to a kind of FPC flexible circuit board intelligent production management system based on image recognition.The method includes the following steps: by positioning acquisition module, FPC is fixed and original detection image is obtained;By curvature calibration module, edge offset is identified and board body pose calibration instruction is generated to complete rectification;Subsequently, regional resampling module carries out local high-precision collection to pad, circuit and mounting area to form structured detection data;Finally, quality evaluation module extracts detection field to generate production quality result and record to storage system, realize automatic detection calibration and quality tracking process.The present application drives automatic positioning calibration by image recognition, regional high-precision detection and quality data closed-loop management, realizes the high-precision alignment of flexible circuit board production process, adaptive detection and intelligent quality control, to significantly improve production efficiency and yield.

The application discloses a kind of geometric error calibration method, device, multi-axis motion system and storage medium, it is related to multi-axis motion system technical field, method includes: according to user operation instruction manual calibration, obtains the initial corresponding relationship between the mechanical coordinate system of multi-axis motion system and the calibration coordinate system of calibration plate;According to initial corresponding relationship, target acquisition point based on calibration plate and the target pose of visual camera, determine corresponding target calibration point on mechanical coordinate system;According to target calibration point generation automatic calibration instruction;According to automatic calibration instruction, control visual camera and target calibration point carry out point operation, obtain the final corresponding relationship between mechanical coordinate system and calibration coordinate system.The application solves the problem that the geometric error calibration of existing multi-axis motion system is lower in efficiency, realizes the effect that multi-axis motion system is geometrically error calibrated automatically, quickly and efficiently.