225 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 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 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 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 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 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 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.

This invention discloses a three-dimensional quantification method for transmission line defects based on RGB-D point clouds and PointNet++, aiming to solve the technical problem that traditional two-dimensional visual inspection can only qualitatively identify defects and cannot achieve accurate quantification of physical parameters. The method includes constructing a dual-modal data acquisition framework of RGB texture and dense point cloud, achieving pixel-level spatiotemporal alignment through an online calibration algorithm for heterogeneous sensors; building a semantic segmentation model based on PointNet++ to accurately segment key components of the transmission line; and establishing a differential analysis mechanism between the standard equipment 3D model and the measured point cloud model to automatically calculate key parameters such as icing thickness, hardware corrosion volume, and insulator damage area. This invention breaks through the limitations of traditional two-dimensional visual qualitative identification, realizing a leap from visual inspection to physical quantification of defects, filling the gap in three-dimensional quantitative assessment in the industry, and providing accurate data support for the digital operation and maintenance of transmission lines.

This invention relates to the field of new energy cable management technology, specifically to an intelligent management method and system for new energy cables based on the Internet of Things (IoT). The system includes: an array of sensors deployed on the new energy cable itself and at monitoring points along the cable line to continuously collect real-time operational status data such as cable sheath temperature, conductor current load, joint vibration amplitude, and ambient air humidity; the data is transmitted to an edge computing node for preprocessing and standardization to form a cable health data package; this data package is then input into an improved fault probability prediction algorithm based on a historical fault database and an environmental stress evolution model to calculate the instantaneous probability values ​​of different levels of faults in each monitoring section at a specific time in the future; adaptive inspections are triggered based on these probability values, generating intelligent work orders that are sent to a mobile inspection terminal; and the algorithm parameters are calibrated using the returned on-site verification results. This method can accurately predict fault risks, rationally allocate inspection resources, continuously optimize algorithm accuracy, and ensure the safe and stable operation of new energy cables.

The invention discloses a foreground calibration method for relieving capacitor mismatch in an SAR ADC, and relates to the field of microelectronics and solid-state electronics, in particular to the field of high-precision SAR ADCs. According to the invention, an additional DAC is not introduced or an original DAC array structure is not modified, a complex calibration algorithm is not needed, all calibration modules are integrated in a chip, and the method is suitable for full-integration application. According to the technology, the linearity of the SAR ADC can be improved, and then the DNL / INL of the ADC is improved. The SAR ADC high-order capacitor array is sequenced and recoded, so that error accumulation caused by capacitor mismatch can be avoided, and small INL can be realized.

According to the multi-level wind turbine generator cooperative reliability rating system, method and device and the storage medium, the system comprises a domain self-adaptive processing sub-module, a digital twin working condition label calibrates a local gradient through an MMD algorithm, a domain self-adaptive calibration algorithm of federal transfer learning is adopted, and the local gradient of the digital twin working condition label is calibrated; a virtual fault sample generated by digital twinning is combined with real monitoring data, a mixed data set covering all working conditions is constructed, a model can still learn corresponding fault features under the condition that no real extreme fault data exists, a safety aggregation module carries out cross-domain adaptation processing on local gradients through a domain self-adaptation gradient processing formula, and the safety aggregation module carries out cross-domain adaptation processing on the local gradients through the domain self-adaptation gradient processing formula. The method comprises the following steps of: calculating an aggregation weight according to a block chain-federated security aggregation formula, generating block chain evidence hash according to the aggregation weight, fusing real-time real data and digital twin virtual data, reducing interference of a single data source, and greatly improving reliability rating accuracy.

This invention relates to the field of thickness measurement technology, and discloses an online thickness measurement method and system for hot-rolled alloy plates. The method includes: acquiring measurement data of the hot-rolled alloy plate to be measured; preprocessing the measurement data to obtain standardized data; performing calibration calculations on the standardized data using a calibration algorithm based on a dynamic benchmark and two-segment mapping to determine the basic thickness data of the hot-rolled alloy plate to be measured; extracting features from the standardized data using deep learning to generate global fusion features; performing error compensation calculations based on the global fusion features and standardized data to determine the error compensation factor; and correcting the basic thickness data based on the error compensation factor to determine the accurate thickness measurement data of the hot-rolled alloy plate to be measured. This invention integrates a physical mechanism model with a data-driven model, overcoming the limitations of a single model and improving the accuracy, stability, and adaptability of thickness measurement in complex and dynamic hot-rolling environments.

The invention discloses a cultural performance content-based dance beauty effect adaptive adjustment method and system, and the method comprises the steps: collecting stage environment parameters through a stage environment perception intelligent coupling model, building a matrix, obtaining the limb dynamic data of a performance person through a performance limb dynamic feature mapping model, and extracting feature parameters; calling a sound field and light collaborative calibration algorithm, and preliminarily calibrating sound field and light equipment parameters in combination with the limb dynamic characteristic parameters; inputting the environment parameter matrix and the initial calibration parameter set into a multi-mode dance artistic effect analysis platform, constructing an evaluation index system and calculating a real-time numerical value; and dynamically correcting equipment parameters and generating multiple groups of operation parameters according to the evaluation numerical value and the dance beauty effect self-adaptive adjustment parameters, and transmitting the parameters to a control terminal to complete configuration, so that the dance beauty effect self-adaptive adjustment is realized. According to the method, the integrating degree with the performance content is improved, and the viewing experience is optimized.

This invention provides a data fusion method for multi-parameter environmental sensor chips based on artificial intelligence, belonging to the field of agricultural product growth environment monitoring technology. This invention constructs a continuous data sequence using a multi-parameter environmental sensor chip, evaluates and preprocesses the data quality using anomaly jump matrices and interference anomaly matrices, constructs a multi-dimensional fusion algorithm to calculate convergence, stability, and disorder indices to quantify the data fusion state, and employs an adaptive calibration algorithm combined with jump compensation and anomaly compensation matrices to dynamically compensate for sensor baseline drift and sensitivity attenuation in real time. The number of attention approximation features is dynamically adjusted through a feature adjustment function, ultimately achieving classification prediction and quality assessment of agricultural product growth environment. This invention solves the technical problem that baseline drift and sensitivity attenuation in multi-parameter environmental sensors significantly reduce data fusion accuracy over time during long-term operation.