23 results about "Static error" patented technology

The invention discloses a PMSLM adaptive optimization harmonic current suppression method based on a multi-rotating coordinate system. According to the method, high-precision extraction of target harmonic waves is realized through a multi-rotating reference coordinate system and a complex coefficient filter; an adaptive moment estimation algorithm (AdamW) with weight attenuation is used to quickly solve an optimal harmonic reference current; and harmonic compensation voltage is output by combining the zero static error characteristic of the proportional resonance PR controller, so that the harmonic current is effectively suppressed. The harmonic current of the permanent magnet synchronous linear motor is quickly and effectively suppressed through a harmonic injection method adopting a multi-rotation reference coordinate system, a complex coefficient filter and an AdamW optimization algorithm. The inherent defects of large phase lag and slow dynamic response when a low-pass filter is used in a traditional harmonic current injection method can be effectively overcome by adopting a complex coefficient filter for current extraction; and an AdamW optimization algorithm is adopted to suppress overfitting through a weight attenuation strategy, and an optimal solution is efficiently and stably obtained.

The invention discloses a gyro accelerometer dynamic error modeling and calibration method considering angular motion of a base, and belongs to the field of dynamics and control. The implementation method comprises the following steps: establishing kinematics and dynamics equations of the PIGA under the triaxial angular motion of the base, and deducing a complete error model comprising a static error term, a dynamic error term and a nonlinear error term; constructing a kinetic equation including inertia tensor, a moment balance equation and servo loop influence; quantitatively analyzing the influence of the angular motion parameters of the base on PIGA output errors; based on three-axis turntable experimental design, dynamic response of each axis of the PIGA is excited through single-axis, double-axis and three-axis angular velocity input, and error model coefficients are separated and calibrated; error model parameters are calibrated by adopting a mode of combining a least square method and other data fitting algorithms; angular velocity and angular acceleration terms are separated based on direction cosine matrix transformation, and error coefficient aliasing is avoided; dynamic response data are fitted through a least square method, and all error coefficients are calibrated at a time.

The application discloses a kind of super-long part bending front feeding positioning device and method, belong to metal sheet precision forming manufacturing field, method is through high-precision measurement acquisition feeding platform surface full field data, constructs and bending mould center line alignment digitization platform surface model, and generates height constant equal to mould center line global reference line and static platform compensation mapping function.In feeding process, the trajectory deviation of the part bottom surface relative to the reference line is detected in real time using a non-contact displacement sensor array, the static compensation value is combined with feedforward-feedback composite control to drive the active leveling mechanism for vertical adjustment, and the static error and dynamic disturbance of the platform are simultaneously offset.The system continuously monitors the actual trajectory and triggers the instant adjustment mechanism when the deviation exceeds the limit.The application solves the problem of error accumulation in super-long part feeding by establishing a global unified reference, integrating static pre-compensation and dynamic closed-loop control, and constructing multiple verification, achieving high-precision positioning.

This invention discloses a method, device, and medium for error prediction and self-repair in low-code applications, belonging to the field of low-code platform technology. It addresses the technical problems of existing low-code platforms, which rely heavily on manual testing, are prone to lag, have blind spots, and are difficult for non-professional developers to diagnose deep-seated logical errors. The method includes: classifying and configuring business scenarios in the low-code platform, collecting and obtaining scenario constraint data; performing error prediction detection on the low-code data at both dynamic and static levels to obtain dynamic and static error results; performing error prediction detection on the low-code data at the machine learning prediction layer to obtain machine learning layer error prediction results; classifying and repairing both dynamic / static error results and machine learning layer error prediction results to obtain repair result information; and blocking high-risk error results to obtain blocking result information; thereby completing error prediction and self-repair in the low-code application.

The invention relates to the technical field of loading control, and discloses an LQG control method and system for an integral configuration link, and the method comprises the steps: obtaining an actual measurement output vector, an expected output vector and a system state observation vector of a loading control system in a current control period, and constructing an integral type performance index functional; obtaining an augmented state space model and an augmented state estimation vector according to an original state space equation, a process noise covariance matrix, a measurement noise covariance matrix and a system state observation vector of the loading control system; based on the augmented state space model and the integral type performance index functional, establishing an extended Riccati differential equation to obtain an optimal feedback gain matrix; and performing linear feedback operation on the augmented state estimation vector based on the optimal feedback gain matrix, generating a control instruction of a loading control system, and realizing zero-static-error optimal tracking, independent and accurate setting of multi-channel integral intensity, adaptive optimization of controller parameters and robust stable operation under uncertainty.

The invention discloses a method and a device for predicting the fatigue life of a low-temperature container. The method comprises the following steps: constructing a geometric model of a to-be-predicted low-temperature container; performing mesh generation on the geometric model, and performing finite element analysis and fluid mechanics calculation on the meshed model to obtain a multi-physical field simulation model of the low-temperature container; performing short-term real-time correction on model parameters of the simulation model based on the real-time data of the low-temperature container so as to eliminate static errors of the simulation model; in response to the fact that the static error of the simulation model exceeds a preset value, training a pre-constructed machine learning model based on the historical data of the low-temperature container to obtain the dynamic deviation of the simulation model; based on the dynamic deviation, correcting the simulation model after short-term and real-time correction to obtain a digital twinborn model of the low-temperature container; and predicting fatigue damage and residual life of the low-temperature container based on the digital twin model. According to the invention, the fatigue damage and residual life of the low-temperature container can be accurately predicted.

The application provides a kind of permanent magnet synchronous motor deadbeat prediction control method based on super-spiral sliding mode extended observer, which first designs a sliding mode observer based on super-spiral theory to estimate unknown disturbances such as parameter perturbation, then designs an extended state observer to estimate disturbances twice, and compensates the estimated values of the two disturbances to the predicted current and output voltage, respectively, to achieve high-precision and robust current control and improve the dynamic and static performance of the control system. Compared with traditional deadbeat prediction control, the application has the advantages of high robustness, low parameter sensitivity, good dynamic performance and no static error.

This invention discloses a high-precision nine-position autonomous calibration method for an inertial platform, belonging to the field of inertial navigation technology. Specifically, it includes the following steps: S1: analyzing the installation error of the gyroscope; S2: analyzing the installation error of the accelerometer; S3: constructing a static error model of the inertial platform system; S4: based on the static error model of the inertial platform system in step S3, constructing a nine-position mathematical model for error coefficient calibration; S5: performing calibration calculations on the nine-position mathematical model for error coefficient calibration in step S4. Based on the characteristics of inertial platform installation errors, this invention analyzes the error model of the platform system considering installation errors, and the proposed calibration method can calibrate both the platform error coefficients and installation errors. Experimental verification shows that this calibration method has good stability and repeatability, and can relax the installation requirements of inertial instruments, ensuring the stability of installation accuracy and improving the accuracy of inertial instruments.

The present application relates to the technical field of electric digital data processing, and discloses a data processing method of multi-source error fusion, comprising: acquiring geometric static error, non-uniform temperature field distribution and strain load mixed data containing thermal stress characteristics of a large controlled system; thermal elastic compensation modeling is used to calculate thermal deformation compensation and map thermal induced pseudo-tension component; the component is used to decouple and separate strain load mixed data, and extract net mechanical load component; according to the dynamic distribution weight of each data compensation component observation variance, a multi-dimensional matrix fusion is used to generate a comprehensive error state vector; a physical logic threshold is compared, and a space deviation control instruction is outputted; the present application decouples thermal induced interference at the level of electric digital signal, cuts off the coupling parasitic link between temperature characteristics and strain characteristics, avoids data space collinearity interference, suppresses control instruction oscillation, and improves the deviation hedging stability and real-time processing efficiency of a large controlled system.

The invention relates to a mold closing mechanism dynamic geometric error modeling method, system and device and a storage medium. The modeling method disclosed by the invention comprises the following steps: identifying key geometric features and key rigidity features of the mold closing mechanism; solving an initial static error of a movable template based on the key geometric features; based on the parameterized virtual prototype, taking the initial static error as a geometric initial pose of a movable template, and introducing a nonlinear contact force model and an equivalent stiffness model to construct a parameterized multi-body dynamic model; and calculating and extracting dynamic error and mold clamping force data based on the parameterized multi-body dynamics model, and constructing a collaborative explicit function model of the dynamic error and the mold clamping force. Compared with the prior art, the method has the advantages that the influence of the nonlinear dynamic effect excited by the gap of the kinematic pair on error analysis can be evaluated, the kinematic precision and the mechanical property are subjected to collaborative analysis, and the geometric error of the mold closing mechanism under the working conditions of high-speed operation and mold locking is quantified.

The invention discloses a feeding and positioning device and method before bending of ultra-long parts, and belongs to the field of precise forming and manufacturing of metal plates. According to the method, full-field-domain data of a feeding table top are collected through high-precision measurement, and a digital table top model aligned with the center line of a bending mold is constructed; and generating a global datum reference line and a static table top compensation mapping function of which the height is constantly equal to the center line of the mold. In the feeding process, the track deviation of the bottom face of a part relative to a datum line is detected in real time through a non-contact displacement sensor array, the active leveling mechanism is driven to conduct vertical adjustment through feedforward-feedback composite control by combining a static compensation value, and static errors and dynamic disturbance of the table top are synchronously counteracted. And the system continuously monitors the actual track, and triggers an immediate adjustment mechanism when deviation exceeds the limit. According to the method, the global unified reference is established, static pre-compensation and dynamic closed-loop control are fused, multi-stage verification is constructed, the problem of error accumulation in the ultra-long part feeding process is solved, and high-precision positioning is achieved.

The invention relates to a dynamic error compensation method for multi-degree-of-freedom plastic forming equipment based on process data, which comprises the following steps of: S1, determining 6-PSS / 3-SPS kinematic configuration of a heavy-load parallel machine tool, and analyzing a kinematic model of the 6-PSS / 3-SPS kinematic configuration; s2, distributed force and motion measurement is carried out on the heavy-load parallel machine tool; s3, the expected position of the driving sliding block is corrected in real time; s4, using a machine learning method to establish a mapping relationship between the process parameters and the processing errors, and optimizing the process parameters; and S5, the machining precision of the heavy-load parallel machine tool is improved by combining an online dynamic error compensation method and an offline static error compensation method. Machining errors caused by geometric errors, insufficient rigidity and dynamic loads can be effectively reduced, and therefore the machining precision, stability and production efficiency of a machine tool are remarkably improved.

This invention discloses a power distribution error correction method for energy storage in parallel operation, relating to the field of energy storage device power control technology. First, initial power allocation is performed based on the device's state of charge. Then, a dynamic grouping and cyclic redistribution mechanism handles excess power to ensure the safe operation of each device. Next, error correction is performed by comparing the actual and target total power. Based on fluctuation monitoring, dynamic or static error thresholds are intelligently switched to achieve a balance between high precision and stability. This invention solves the problem of uneven power distribution through dynamic grouping and cyclic redistribution mechanisms, improving system safety and output capacity. Combined with dual-threshold correction and variance monitoring, it intelligently balances precision and stability, eliminating errors while reducing equipment losses, thereby improving overall operating efficiency and lifespan.

The invention relates to a metering traceability method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: obtaining measurement values of a plurality of measurement parameters corresponding to each measured component of the aero-engine, wherein the measurement values comprise a first measurement value of each measured component in a static state and a second measurement value of each measured component in an operation state; for each measured component, determining static error data corresponding to the measured component according to the first measurement value and a preset multi-stage reference measurement set, and determining dynamic difference data corresponding to the measured component according to the first measurement value and the second measurement value; and according to the static error data, the dynamic difference data and a preset vertical and horizontal nested network, determining a metering traceability result of the tested component. By adopting the method, the accuracy of the metering traceability result can be improved when the civil aero-engine is in the running state.

The application relates to a metrological traceability method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: obtaining measurement values of a plurality of measurement parameters corresponding to each measured component of an aero-engine, the measurement values comprising first measurement values of each measured component in a static state and second measurement values of each measured component in a running state; for each measured component, determining static error data corresponding to the measured component according to the first measurement values and a plurality of preset reference measurement sets, and determining dynamic difference data corresponding to the measured component according to the first measurement values and the second measurement values; and determining a metrological traceability result of the measured component according to the static error data, the dynamic difference data and a preset longitudinal and transverse nested network. The method can improve the accuracy of the metrological traceability result when the civil aero-engine is in a running state.

The invention provides a geometric-gravity error integrated calibration method of a large gantry machine tool. The method comprises the steps that a geometric error model of the gantry machine tool is established based on the multi-body system kinematics theory and rigid body kinematics analysis, and the geometric error model is used for describing geometric error sources of all motion axes and the transmission relation of the geometric error sources; establishing a gravity deformation error model of the gantry machine tool based on mechanical analysis and a potential energy method; coupling the geometric error model with the gravity deformation error model to obtain a rigid-flexible coupled integrated geometric-gravity error model; measuring static error parameters of each motion axis of the machine tool, and substituting the static error parameters into the integrated geometry-gravity error model to obtain geometric error parameters without influence of gravity error factors; and on the basis of the integrated geometry-gravity error model and the geometric error parameters with the influence of the gravity error factor eliminated, the error compensation amount of each movement position point of the gantry machine tool is calculated, and the gantry machine tool is calibrated on the basis of the error compensation amount of each movement position point.

The application discloses a controller parameter setting method and system for a quad-rotor unmanned aerial vehicle in a forward flight mode, the method comprising the following steps: S1, frequency domain identification is performed on the quad-rotor unmanned aerial vehicle in the forward flight mode, and a forward flight dynamics model of the quad-rotor unmanned aerial vehicle is obtained; and S2, based on the forward flight dynamics model, pole placement analytical method is used to set parameters of an attitude control cascade PID controller. The method provided by the application has the advantages that in terms of time domain response, control instruction tracking is smooth, there is no static error and oscillation phenomenon, and the response speed is relatively fast, and the rising time is about 0.3s; in terms of frequency domain response, the system is stable in convergence, the open loop amplitude margin and the phase margin are sufficient, the relative stability is relatively strong, and the method has certain robustness.

The invention discloses a novel phase-locked loop implementation method and a motor rotating speed estimation and control method and system, and the method comprises the steps: exploring that a d-axis component and a q-axis component of a back electromotive force observation value have uniqueness at a phase angle solution of a maximum value and a minimum value in a range of [0, 2pi) through a constructed back electromotive force observation value model of a synchronous rotation reference system; designing a phase angle cost function, namely taking the maximum value or the minimum value of the d-axis component or the q-axis component of the back electromotive force observation value as the phase angle cost function; and then dividing the phase angles from 0 to 2pi into a finite number of discrete phase angle sets, then evaluating all the discrete phase angles through an iterative algorithm and a phase angle cost function, and finally obtaining a phase angle with the minimum static error as an optimal phase angle. In conclusion, the phase angle and the rotating speed of the permanent magnet motor can be accurately estimated, a PI controller of a traditional phase-locked loop can be avoided, the complex parameter setting process is reduced, the dynamic response performance is improved, and the calculation burden is reduced.

The invention discloses a linear encoder precision compensation system and method based on error table compensation, and the system comprises a module pedestal, the module pedestal is provided with a multi-read-head linear magnetic encoder and a rotor sliding along the module pedestal, the rotor is provided with a magnetic scale cooperating with the multi-read-head linear magnetic encoder, and the magnetic scale is provided with a plurality of error tables. A high-precision reference measurement system is arranged on the module base and the rotor in a matched manner; the calibration data acquisition unit is used for synchronously acquiring position output information of the multi-read-head linear magnetic encoder and the high-precision reference measurement system; and the calibration module is used for controlling the rotor to move, calculating a position error and generating a static error compensation table. The system is high in cost benefit, the precision of magnetic drive module products produced in a large scale can be permanently improved only by adding a set of reusable reference measurement system in a factory leaving link, and the situation that each module is equipped with an expensive high-precision grating ruler is avoided.

The invention discloses a wind turbine generator yaw error identification and correction method and system based on a graph attention network and embedded decoupling, belongs to the technical field of wind turbine generator control, and solves the problem of how to design a method and system for automatically and synchronously decoupling high-precision static errors and dynamic errors from mixed historical data. The problem of accurate yaw correction under all working conditions is solved. The method comprises the steps of collecting historical data of a wind turbine generator, and performing preprocessing; constructing a heterogeneous double-branch deep neural network model, wherein the heterogeneous double-branch deep neural network model comprises a graph attention network module and a learnable embedding module; training the heterogeneous double-branch deep neural network model by adopting a loss function; and performing one-time static compensation on the wind turbine generator, performing real-time dynamic error compensation by adopting a graph attention network module, and optimizing yaw control. The method is suitable for wind turbine generator error identification and correction scenes.

The application discloses a rudder state recognition method, device and equipment and a storage medium, and is applied to the field of rudders. The method comprises the following steps: acquiring a rudder position feedback signal Vf1 through a sampling frequency f1, and determining a jitter state according to the rudder position feedback signal Vf1; acquiring a rudder position feedback signal Vf2 and a rudder position control signal Vg2 through a sampling frequency f2, and determining a static error state according to the rudder position feedback signal Vf2 and the rudder position control signal Vg2; and determining a rudder state according to the jitter state and the static error state. The application judges various states of the rudder from multiple aspects, so that a more real and reliable rudder state is obtained, the rudder can be better controlled subsequently, and the rudder can quickly and stably respond to control information.

The application discloses a motor control method and device, a compressor and a storage medium, wherein the method comprises the following steps: obtaining a d-axis flux linkage observation value and a q-axis flux linkage observation value; filtering out harmonics of the d-axis flux linkage observation value and the q-axis flux linkage observation value respectively based on a first complex filter set to obtain a d-axis flux linkage and a q-axis flux linkage; obtaining an observed angular velocity and an observed angle of the motor according to the d-axis flux linkage and the q-axis flux linkage; performing non-static error following on the observed angle of the motor based on a second complex filter set to obtain a current angle of the motor, and obtaining a current angular velocity of the motor according to the current angle of the motor; and controlling the motor according to the current angle of the motor and the current angular velocity of the motor. Thus, harmful harmonics in the observed flux linkage are filtered out, and a non-static error following is performed on a one-frequency fluctuation component of the compressor speed and the position angle signal except for a direct current component, so that the stability requirement and the accuracy requirement of the position observer when driving a high-pole-number and low-lamination-thickness compressor are met.

This invention relates to a method, system, device, and storage medium for modeling dynamic geometric errors of a mold clamping mechanism. The modeling method disclosed in this invention includes the following steps: identifying key geometric and stiffness features of the mold clamping mechanism; solving for the initial static error of the moving template based on the key geometric features; using a parametric virtual prototype, taking the initial static error as the initial geometric pose of the moving template, and introducing a nonlinear contact force model and an equivalent stiffness model to construct a parametric multibody dynamics model; calculating and extracting dynamic error and mold clamping force data based on the parametric multibody dynamics model, and constructing a collaborative explicit function model of dynamic error and mold clamping force. Compared with existing technologies, the advantages of this invention are: it can evaluate the impact of nonlinear dynamic effects induced by the clearance of the kinematic pairs on error analysis, and perform collaborative analysis of motion accuracy and mechanical performance, quantifying the geometric error of the mold clamping mechanism under high-speed operation and mold-locking conditions.