400 results about "Compensation algorithm" patented technology

The invention relates to a concrete temperature-stress two-parameter cooperative monitoring and early warning method and system, and belongs to the technical field of concrete structure health monitoring, and the method comprises the steps: activating a composite sensor network disposed at a preset position of a concrete structure, and executing a sensor self-calibration mode; the method comprises the following steps: synchronously acquiring temperature and stress original monitoring data of each node, processing based on an altitude air pressure compensation algorithm, and outputting a temperature gradient field matrix and a stress tensor sequence with aligned time domains; the method comprises the following steps: separately calculating a thermal stress component and an effective stress component, performing integral calculation on hydration reactivity, generating a multi-dimensional feature vector set, inputting a pre-constructed prediction model, executing time sequence evolution prediction, calculating a crack probability value, performing environment correction in combination with real-time environment parameters, outputting a risk level identifier, and matching a preset regulation and control strategy. And generating an equipment control instruction set and executing corresponding regulation and control actions. According to the invention, the accuracy and timeliness of crack risk prediction can be improved.

The invention discloses a force control joint torque self-correction method based on digital twinborn mapping, which comprises the following steps of: acquiring and preprocessing multi-source operation data of a force control joint to generate a standardized input data set; establishing a three-layer digital twinning mapping model to realize physical, simulation and cognitive layer mapping; a bias load device is arranged, and angle, torque, current and temperature signals are collected; space-time tensor compensation is executed on the simulated twinborn layer, and a dynamic compensation value is generated; bootstrap consistency correction is executed on the cognitive twin layer, and comprehensive correction parameters are fused; and inputting comprehensive parameters to adjust a simulation layer structure, outputting a correction torque and performing closed-loop updating. By constructing the three-layer digital twinning mapping model and introducing the torque compensation algorithm, torque dynamic error identification, adaptive compensation and real-time self-correction of the force control joint under complex working conditions are realized, and the measurement precision and the system stability are improved.

The invention relates to the technical field of computers, and discloses a multi-mode audio and video synchronous processing method and system based on a distributed architecture. The method comprises the following steps: generating a unique logic sequence identifier consisting of a device code, a media type and a frame number for each frame of audio and video data; distributing the frame carrying the identifier to a distributed node for processing and adding a local timestamp; and the sink node reconstructs an original frame sequence according to the identifier, calculates a synchronous offset by combining high-precision clock calibration, and realizes dynamic reordering and output through a double-buffer structure and a self-adaptive drift compensation algorithm. The system comprises a source end acquisition module, an identifier generation module, a task scheduling module, a distributed processing cluster module, a convergence synchronization module and a synchronous output module. According to the scheme, the system effectively guarantees the audio and video synchronization precision in a high-concurrency heterogeneous environment, the synchronization error is controlled within 20 milliseconds, and the playing quality and the user experience of scenes such as live broadcast and cloud games are remarkably improved.

The invention discloses an embedded motor torque ripple real-time compensation system based on deep learning, and relates to the technical field of motor control and artificial intelligence crossing, the system comprises a hardware data acquisition module, a signal feature extraction module, a deep learning compensation model module, an embedded real-time compensation module and a compensation effect verification module; a motor position and a current signal are acquired in real time through the hardware data acquisition module, dynamic analysis and multi-dimensional feature construction are performed on torque ripple related features by combining the signal feature extraction module, and the deep learning compensation model module learns a fluctuation rule in historical data by using a space-time sequence model to generate a high-precision compensation current. The model adapts to an embedded environment through lightweight design, real-time deployment and dynamic optimization of a compensation algorithm are achieved, compared with traditional PID control, the scheme can adapt to changes of motor operation conditions, the influence of torque fluctuation on system stability is reduced, and the smoothness and efficiency of motor operation are improved.

The invention discloses a low-drift laser scanning control method and system based on dynamic error compensation, relates to the technical field of laser scanning control, and aims to solve the drift problem in the laser scanning process and improve the scanning precision. The system comprises a system initialization and calibration module, a data acquisition and storage module, an error modeling module, a route planning and correction module and a real-time compensation and closed-loop optimization module, wherein the error modeling module and the route planning and correction module are key modules. The error modeling module comprises a key route screening unit and a data preprocessing unit, and is responsible for constructing a space-time joint error correction model; the route planning and correction module comprises an initial route generation unit, an error prediction unit and the like, and dynamic correction of a pre-planned route is achieved. According to the system, real-time compensation and closed-loop optimization are achieved through cooperation of all the modules in combination with a dynamic error compensation algorithm, scanning drift is effectively reduced, low-drift and high-precision laser scanning is guaranteed, and meanwhile follow-up scanning precision is optimized.

The invention belongs to the technical field of intelligent robots and environment perception, and particularly relates to a multi-mode autonomous positioning and inspection method and system for a hazardous chemical substance warehouse environment. According to the method, robust continuous positioning in a high-pollution characteristic environment is realized through combination of a layered confidence scheduling mechanism, an observation judgment mechanism and a time sequence clustering compensation algorithm; through path local reconstruction based on task semantics, the inspection system has task understanding and autonomous adjustment capabilities and adapts to multiple types of inspection tasks; the autonomous sustainable operation capability of the system in continuous inspection is improved through energy consumption and risk double-constraint control; a multi-mode degradation identification and self-healing mechanism ensures long-term stable operation of the sensor, and manual intervention is reduced; the whole inspection system can realize all-weather and unattended multi-mode autonomous inspection in a dangerous chemical warehouse scene, and provides stable mobile platform support for subsequent dangerous symptom identification and automatic early warning.

The invention discloses a UPA pressure automatic compensation system and method for mask substrate polishing. The UPA pressure automatic compensation system comprises a pressure execution module, a distributed sensing feedback network and an intelligent control unit. Wherein the pressure execution module is used for directly polishing a mask base plate and comprises a force application shaft, a polishing head, an air source, a UPA air bag and an electric proportional valve, the distributed sensing feedback network comprises an air path pressure sensor and a tail end contact pressure sensor, and the intelligent control unit receives a collection signal of the distributed sensing feedback network and sends the collection signal to the polishing head. On the basis of a current process formula and process parameter coupling model, a data fusion algorithm, a feed-forward compensation algorithm and a fuzzy PID algorithm are operated to obtain a feed-forward compensation amount and a fuzzy PID output amount, the feed-forward compensation amount and the fuzzy PID output amount are superposed, a total control voltage is generated and output to an electric proportional valve, and then the input air pressure of a UPA air bag is adjusted. Therefore, closed-loop control over the polishing pressure of the mask substrate is achieved. Through multi-sensor data fusion, fuzzy PID self-adaptive control and intelligent feed-forward compensation based on a process parameter coupling model, real-time, accurate and constant control of the polishing pressure is realized, so that the surface precision and yield of the mask substrate are improved.

The invention discloses a multi-modal data fusion method in electric power overhaul, which comprises the following steps of: firstly, respectively acquiring long-sequence video data and audio data in an electric power overhaul process, and constructing a window-level multi-modal data fusion model; secondly, performing time window division and coarse alignment on the long-sequence video data and audio data by the window-level multi-modal data fusion model, generating a frame-level quality score, and performing fine alignment on multi-modal characteristic data in a time window by adopting a segmented time sequence alignment and compensation algorithm; and calculating a window-level quality score, a window-level weak supervision label and a confidence coefficient, and finally performing multi-modal fusion according to the multi-modal feature data after fine alignment and the window-level weak supervision label to generate a window-level semantic representation as a model output. According to the method, accurate time alignment of video and audio data and consistent fusion of multi-modal semantic features are realized, and more reliable alignment data and semantic input are provided for subsequent target recognition.

The invention discloses a control method and equipment of a glue spraying system and a storage medium, and relates to the technical field of automatic spraying, the method comprises the following steps: obtaining a distance parameter from a nozzle to the surface of a workpiece at the cut-off position of the nth time step and spraying area image data of the nth time step, and generating a workpiece curvature feature and a spraying state feature; the spraying state characteristics, the workpiece curvature characteristics and the material type of the area corresponding to the (n + 1) th time step are substituted into a compensation algorithm, and difference parameter values are generated; and generating and executing a target control parameter of the (n + 1) th time step according to the difference parameter value and the initial control parameter. According to the method, the change of the surface of the workpiece is monitored in real time, the spraying parameters are automatically adjusted according to the change, the technical problem that the thickness of a coating is not uniform is solved, and the spraying quality and efficiency are improved.

The invention provides a centralized heating method and system based on room temperature feedback regulation, and the method comprises the steps: collecting and verifying real-time room temperature data, and generating a room temperature feedback signal; the signals are transmitted to a central control unit for sequential processing, and a temperature-time two-dimensional data matrix is generated; a preset dynamic compensation algorithm is used for calculating a heat demand correction value of each heat supply pipe network key node; the heat supply pipeline flow is dynamically adjusted according to the correction value; and verifying the effect through a closed-loop feedback mechanism and optimizing algorithm parameters. According to the method, a network is constructed to realize multi-node synchronous acquisition and verification, and heat distribution heterogeneity and fluctuation characteristics are captured in combination with matrix processing and interpolation completion. Compared with a traditional single-point sensor, according to the scheme, through two-dimensional mapping and anomaly detection, the adjustment response time is shortened to the sampling period level, the temperature deviation calculation precision is improved to + / -0.1 DEG C level, the overheating-underheating alternating phenomenon is solved, and accurate dynamic matching of the heat demand correction value is achieved.

The invention discloses an AGV-six-degree-of-freedom mechanical arm operating system and method based on double-vision fusion, the system comprises a control system and a six-degree-of-freedom mechanical arm, and the control system comprises a master control unit, a slave control unit and a dynamic error compensation module; the method comprises the steps of AGV autonomous navigation and material transfer, cross-station accurate docking and dynamic error compensation, high-precision biological medicine operation under double-vision fusion guidance, and material recovery and circulation. According to the invention, through dual-vision dynamic fusion of eyes outside the hand and eyes on the hand, adaptive switching from global coarse positioning to local fine positioning is realized; due to the integrated design of the AGV and the six-degree-of-freedom mechanical arm, the operation flexibility is greatly improved; an extended Kalman filtering dynamic error compensation algorithm is innovatively adopted, so that the comprehensive error of the AGV, the mechanical arm and the visual system can be corrected in real time; and by combining with a double-layer distributed control architecture, the system realizes multi-task intelligent scheduling and modular collaboration.

The invention discloses an MMC intelligent setting and cooperative control method and system based on deep reinforcement learning, and relates to the technical field of power transmission system regulation and control, and the method comprises the steps: obtaining the current operation state data of a converter in a power transmission system, the current operation state data comprising a system frequency, a frequency reference value, a frequency deviation and a frequency change rate; establishing a third-order active closed-loop small signal transfer function based on an active transient feedback compensation algorithm, and decoupling a damping coefficient and a primary frequency modulation coefficient in VSG control through the third-order active closed-loop small signal transfer function; inputting the current operation state data into the trained DDPG intelligent agent for processing, and obtaining an optimization result of the virtual inertia; the optimized virtual inertia is applied to a rotational inertia control link of VSG control, and self-adaptive adjustment of the virtual inertia is carried out through the trained DDPG intelligent agent; the problem that control parameters of a traditional virtual synchronous generator VSG are fixed and are difficult to adapt to system operation state changes is solved.

The invention discloses a dynamic self-adaptive precision switching method for a voice recognition NPU, and aims to solve the core problems that precision and energy efficiency of an end-side voice recognition NPU in multiple scenes cannot be considered at the same time, fixed-precision hardware resources are seriously wasted, software switching efficiency is low, and errors are accumulated. A hardware architecture of a 4 * 4 reconfigurable MAC subunit array and a switch matrix is constructed, and a task-driven adaptive scheduling mechanism, an operation period synchronous control technology (single-period hardware reconfiguration is realized by utilizing idle gap latch configuration) and a direction-sensitive error compensation algorithm (historical data interpolation extension or correction truncation) are combined; hardware-level dynamic lossless switching of the MAC unit between 8bit / 16bit / 32bit precision is realized, so that different voice tasks achieve the highest necessary computing power with the lowest necessary power consumption, no data is lost in the switching process, and finally, the energy efficiency rigidity of a fixed-precision framework is oppositely converted into the precision on-demand supply capability capable of being deployed in an engineering manner.

The invention relates to the technical field of power distribution Internet of Things, in particular to a power distribution Internet of Things networking method and system capable of sensing multiple energy flow states. According to the method, an acquisition strategy configuration file is generated by acquiring electric-thermal-hydrogen energy flow characteristic data, SDN channel configuration parameters are generated based on time-sensitive level mapping processing and SDN controller interface calling, and a space-time compensation coefficient matrix is constructed through transmission delay data acquisition and sliding compensation algorithm operation. GIS equipment coordinate data is combined to carry out topological relation analysis and multi-energy flow data alignment operation to form a space-time alignment data flow, an energy flow coupling analysis report and a system optimization suggestion item are generated through coupling feature extraction and coupling degree calculation, and finally closed-loop optimization updating of an acquisition strategy file is realized. The space-time accurate alignment and coupling relation dynamic analysis of the multi-energy flow data are realized, and the sensing precision and the regulation and control efficiency of the power distribution Internet of Things on the electric-thermal-hydrogen multi-energy flow cooperative operation are improved.

The invention relates to the technical field of mine environmental protection, and discloses a gravel aggregate mine carbon emission real-time monitoring and metering method, which comprises the following steps: S1, multi-source sensing, including mining blasting monitoring, ore transportation monitoring and aggregate processing monitoring; s2, edge calculation, including data preprocessing, dynamic compensation calculation and local storage and communication; in the dynamic compensation calculation, the CO2 concentration is output and corrected in real time through a dynamic compensation algorithm, and the dynamic compensation algorithm comprises particulate matter dust drop, temperature and humidity deviation and vibration compensation; and S3, cloud platform processing is carried out, block chain evidence storage, carbon sink deduction calculation and early warning control are carried out, and the carbon sink deduction calculation is vegetation carbon sink absorption amount calculation deduction and waste rock recycling carbon emission reduction calculation deduction according to satellite data. The edge calculation layer adopts a dynamic compensation algorithm, temperature and humidity, vibration and particulate matter compensation items are fused in real time, and the hysteresis bottleneck of accounting is solved; a satellite-ground fusion deduction mechanism is adopted to construct a judicial-level trusted data chain.

The invention relates to the technical field of digital manufacturing and precision machining, and discloses a part machining method and system based on inspection planning and feature driving, and the method comprises the steps: reading a full three-dimensional model, analyzing a tolerance mark, instantiating the tolerance mark into a procedure inspection item node, and building a persistent reference; identifying geometric features and matching the geometric features with the inspection items to generate a to-be-tested feature set; measuring point distribution is calculated in a self-adaptive mode according to the feature types, and a collision-free measuring path is generated; converting the path into a numerical control code containing a radius compensation algorithm and embedding the numerical control code into a machining program; after the numerical control center executes measurement, abnormal data calculation deviation is eliminated, and a compensation value is written into a register to correct parameters. By establishing full three-dimensional model data association and applying curvature adaptive sampling and statistical data cleaning strategies, data faults of design and detection are eliminated, the problem of environmental noise interference is solved, and the precision control level of complex feature processing is improved.

The invention discloses a multi-channel multi-color-temperature intelligent light source system for consistency calibration of a camera module and an optimization method, and the calibration system generates PWM signals through an STM32F103ZET6 main control unit of a light source controller to control the light output of each group of cold and warm LEDs so as to provide a stable and adjustable illumination environment; measuring reference brightness and chromaticity parameters of cold light and warm light of each group of LEDs, setting a target brightness value and a color temperature value, and converting the target brightness value and the color temperature value into target chromaticity coordinates; the initial PWM duty ratio of the cold and warm light LED is calculated, a piecewise polynomial nonlinear compensation algorithm is adopted to correct the duty ratio, and the LED is driven to output mixed light meeting the target brightness and color temperature; collecting a large amount of brightness and color temperature data by cyclically and gradually adjusting the duty ratio, and generating an error thermodynamic diagram; and the compensation model coefficient is optimized and updated according to error analysis, so that the light source output keeps high-precision consistency in a full range. Compared with the prior art, the method has the advantages that the brightness and color temperature consistency of the light source can be automatically calibrated and continuously optimized, the accuracy and stability of OTP burning calibration of the camera module are greatly improved, and the production test efficiency and the product imaging quality are improved.

The invention discloses a wind turbine generator voiceprint self-adaptive detection method, system and device and a storage medium, and belongs to the technical field of wind power, and the method comprises the steps: collecting a voiceprint signal, raindrop diameter, environment humidity, environment temperature and atmospheric pressure of a wind turbine generator in real time through a sensor array; temperature and humidity coupling correction parameters are calculated based on the environment humidity, and real-time air density is obtained through correction according to an air density correction formula by means of the environment humidity, the environment temperature and the atmospheric pressure; constructing a rain intensity noise spectrum mapping model based on the raindrop diameter and the real-time air density in combination with a raindrop vertical fragmentation merging effect compensation algorithm; performing rain noise suppression on the voiceprint signal of the wind turbine generator by adopting a depth spectrum subtraction algorithm in combination with the rain intensity noise spectrum mapping model and the dynamic suppression factor to obtain a clean voiceprint signal; and matching the clean voiceprint signal with a preset wind turbine generator fault voiceprint feature library to complete wind turbine generator voiceprint adaptive detection.

The invention discloses a concrete permeability multi-parameter comprehensive detection system and an evaluation method. The system comprises a data acquisition module, a data processing module, a comprehensive evaluation module and a man-machine interaction module, and synchronous acquisition and calibration of multiple parameters such as electric flux, a chloride ion diffusion coefficient, water absorption and an air permeability coefficient are realized through a unified synchronous trigger mechanism and an environment compensation algorithm; carrying out intelligent processing on the data by utilizing an improved data cleaning, multi-level and multi-modal feature extraction and fusion strategy; and finally, through dynamic fusion of fuzzy comprehensive evaluation, grey correlation analysis and a machine learning classification model, outputting a quantitative grade evaluation result of the concrete permeability. The method can comprehensively and accurately evaluate the permeability of the concrete, remarkably improves the detection precision and efficiency, adapts to a complex environment and a long-term aging process, and provides a scientific basis for durability evaluation and maintenance of a concrete structure.

The invention discloses a rotary machine dynamic balance optimization method based on an attitude performance correlation model, and relates to the technical field of rotary machine dynamic balance optimization. Comprising the following steps: S1, synchronously collecting rotor vibration signals and temperature field data through temperature and vibration sensors, carrying out real-time calibration on structure parameters, substituting a temperature compensation algorithm to calculate interference components, and outputting pure vibration deviation data subjected to temperature compensation; the structural parameters comprise a rotor thermal expansion coefficient, a bearing radial clearance temperature attenuation coefficient and inherent or dynamic characteristic parameters related to material properties, geometric dimensions and connection states of the rotary machinery. The method has the advantages that through deep combination of vibration and temperature, a temperature-frequency spectrum-amplitude three-dimensional coupling traceability matrix is constructed; multi-feature matching is achieved through a fusion algorithm, temperature-dominated vibration sources and mechanical-dominated vibration sources can be clearly distinguished, and the accuracy of the dynamic balance optimization direction is guaranteed.

The invention discloses a relay fault detection circuit, method and system applied to an energy storage system, and relates to the technical field of electrical control, and the method comprises the following steps: resistance dynamic compensation, coil fault analysis, contact fault analysis, mechanical performance analysis and comprehensive fault risk assessment. The comprehensive performance of the relay is analyzed through a comprehensive evaluation algorithm in combination with a coil aging coefficient, a contact health index H and a mechanical degradation index, a comprehensive fault index is obtained, the overall performance condition of the relay is judged according to the comprehensive fault index, and corresponding measures are taken. According to the method, the temperature fluctuation interference is eliminated, the accuracy of contact resistance detection is improved, the mechanical fault of the relay can be found in time through coil aging analysis, contact health evaluation and mechanical performance evaluation algorithms in combination with compensated data, multi-dimensional fault detection is realized, misjudgment and missed judgment are effectively reduced, and the fault judgment accuracy of the relay is remarkably improved.

The invention relates to a loose-leaf notebook inner page hole site processing self-adaptive positioning method and system and electronic equipment, and the method comprises the steps: obtaining the morphological feature information of the edge of a to-be-processed paper pile, and determining a datum reference line and an actual edge contour curve according to the morphological feature information; and based on a deviation mapping model, determining a pose deviation vector according to the datum reference line and the actual edge contour curve, generating a positioning adjustment instruction according to the pose deviation vector by utilizing a self-adaptive compensation algorithm, and driving a positioning mechanism to carry out pose correction on the to-be-processed paper pile. And aligning the hole site machining center with the actual edge profile curve. Accurate sensing and self-adaptive compensation of the shape of the edge of the inner page of the loose-leaf notebook are achieved, the problem that traditional mechanical positioning is poor in adaptability is effectively solved, high precision and high quality of hole site machining are guaranteed, and the yield is increased.

The invention discloses a feed processing load management method based on a staged strategy gradient algorithm, and relates to the technical field of industrial automation control, and the method comprises the steps: collecting a feed processing dynamic state set, and obtaining a standardized decision input vector through preprocessing; based on the standardized decision input vector, dynamically adjusting equipment parameters through a two-factor cooperative compensation algorithm, and obtaining an equipment control instruction; executing an equipment control instruction, and generating an efficiency feedback data packet by monitoring equipment energy consumption change and output material granularity in real time; a load management decision model is constructed, and optimization strategy parameters are obtained by combining the efficiency feedback data packet and adopting a staged strategy gradient algorithm; and updating the load management decision model based on the optimization strategy parameters, and generating a closed loop verification report through load management verification. According to the method, the load management decision model is constructed through a quantum annealing mechanism, the local optimal limitation of traditional reinforcement learning is broken through, and global optimization efficiency jump is realized.

The application relates to the technical field of building surveying and mapping, and provides an old building digital surveying and mapping system and method based on air-ground cooperative point cloud fusion, which comprises the following steps: blind area detection is performed on spatiotemporal fusion data scanned by a unmanned aerial vehicle device and a ground robot, and a dynamic master-slave mechanism is started when there is a blind area view angle in top point cloud data / bottom point cloud data; wherein the dynamic master-slave mechanism takes a point cloud data corresponding device with a blind area as a slave device, takes a point cloud data corresponding device without a blind area as a master device, controls the slave device to perform point cloud filling, determines blind area compensation data, and generates target spatiotemporal fusion data loaded to a visual interface after the blind area compensation data is fused to the spatiotemporal fusion data. Through a dynamic master-slave control mechanism, a multi-dimensional synchronization strategy and an intelligent compensation algorithm driven by building features, a closed loop working flow from data acquisition to quality verification is constructed.

The invention discloses a quantitative test method and system for a peak locked-rotor torque of a robot joint module, and relates to the technical field of robot joint performance evaluation, and the method comprises the steps: extracting a torque time-calendar curve of the joint module, defining the peak locked-rotor torque as a controlled low-frequency fatigue loading process, and building a mapping model of a torque amplitude and a failure cycle index; constructing a test system, and performing torque-current static calibration; embedding a specific excitation function in a current loop of the servo driver; the bus voltage and rotating speed change rate is monitored in real time, and the voltage and current impact at the unloading moment is inhibited by adopting a back electromotive force compensation algorithm and combining an energy consumption discharge loop; and repeatedly loading until the structure is damaged, recording the number of cycles, and drawing a peak torque-life curve as a basis for predicting the life of the whole machine. According to the method, quantitative association of the peak locked-rotor torque and the fatigue life is realized, quantitative evaluation from a static index to a dynamic life is realized, a basis is provided for life prediction of the whole robot, and the test precision is improved.

The invention discloses a toilet paper embossing online monitoring method based on machine vision, and relates to the technical field of product monitoring. The method comprises the following steps: presetting a plurality of detection bits, acquiring multi-modal data, and extracting multi-source characteristic parameters; calculating a comprehensive damage index of each detection position through a weighted fusion algorithm based on the multi-source characteristic parameters, establishing a damage evaluation system according to the comprehensive damage indexes, and executing a repair strategy according to an evaluation result; an embossing roller is divided into a plurality of independent control subareas in the axial direction, and each subarea is provided with an independent pressure adjusting device. Obtaining a pressure compensation value of each partition through a partition pressure fusion compensation algorithm based on the partition basis weight data and the comprehensive damage index; and the pressure compensation value is sent to each subarea pressure adjusting device, and dynamic subarea adjustment of the embossing pressure is achieved.

The invention discloses an automatic temperature compensation system and method for an ultrasonic transducer, and the method comprises the steps: carrying out the timely collection of the temperature through a temperature detection module, and carrying out the temperature error compensation of a pressure measurement result based on an environment temperature parameter; according to error characteristics of the digital temperature sensor, a characteristic threshold value is obtained based on a temperature compensation algorithm of an RBP neural network with nonlinear fitting capability and generalization capability, and then nonlinear error compensation in a temperature measuring range is completed by using the characteristic threshold value. The transition time of ultrasonic waves in a pipeline under any temperature and zero pressure serves as a training target value of an artificial neural network, drifting of the transition time at the zero pressure position is compared after training, the receiving waveform of the temperature change to the frequency mutation of the ultrasonic transducer under the zero pressure is calculated, the zero pressure position is locked, and the temperature change of the ultrasonic transducer is calculated. The frequency with the strongest signal is found out, the optimal working frequency of the ultrasonic transducer at the temperature is obtained, and temperature compensation of ultrasonic transit time is automatically completed through a temperature compensation module; according to the invention, the temperature compensation performance is reliable, the phenomenon of pressure drift caused by zero pressure ultrasonic transit time drift can be effectively avoided, and the final measurement error is effectively reduced.

The invention belongs to the technical field of vehicle-mounted display, and relates to a vehicle-mounted display screen touch abnormity recovery method and system, and the method comprises the following steps: dividing a virtual sensing area, and building a mapping table; the method comprises the following steps: periodically collecting original capacitance data of a normal area, synchronously obtaining communication quality and environment state messages, and aligning to form a multi-dimensional data stream; identifying an abnormal region, dynamically adjusting a threshold value in combination with an environment state for rechecking, determining a fault type, and generating an abnormal judgment signal; generating a targeted recovery instruction packet according to the fault type; sending to a controller for execution, updating the mapping table and activating a neighborhood interpolation compensation algorithm; monitoring a touch track in real time, calculating a simulation coordinate by using data interpolation of an adjacent normal area when entering a fault area, and integrating the simulation coordinate with a real coordinate to form a continuous touch coordinate flow; according to the invention, the problems of whole screen interruption caused by inaccurate fault positioning, unnecessary reset caused by environment interference misjudgment and influence on system availability due to long overall reset time in the prior art are solved.

The invention provides an intelligent obstacle avoidance and path planning method based on a ship, and relates to the technical field of intelligent control of small leisure ships. S1, the state and surrounding environment information of the ship are obtained through a multi-sensor group deployed on the ship, and a distortion compensation algorithm combining Kalman filtering with a sea condition coefficient is adopted; outputting the compensated obstacle information, sea condition parameters and ship task types; s2, the local end uploads the compensated obstacle information and the sea condition parameters output in the step S1 to a server end, the server end introduces sea condition correction factors to construct a CPA model, collision risk indexes are calculated through the CPA model, and the path conflict probability between ship pairs in the water area is predicted according to a path conflict probability calculation formula. According to the invention, accurate risk judgment can be ensured through collision risk correction, and multi-ship ordered avoidance is realized through scenarized priority, so that the problems of path conflict, low decision-making efficiency and increased navigation risk caused by lack of collaboration in a multi-ship environment are solved.

The application provides a sideband compensation acceleration method, an acceleration device, a computing device and a storage medium. The sideband compensation acceleration method comprises the following steps: obtaining sideband data; adaptively setting a candidate concurrency parameter and determining an optimal concurrency parameter P; dividing the sideband data into a plurality of vectors according to the determined optimal concurrency parameter P; performing parallelization calculation on each divided vector and judging whether each vector matches; and updating the sideband data according to the matching state of the plurality of vectors. Through the sideband compensation acceleration method of the application, sideband compensation data can be calculated in parallel based on an adaptive compensation algorithm, and the coding efficiency is improved.