27 results about "Error coefficient" patented technology

A calibration circuit for correcting timing errors introduced by a DAC in a signal path of an ADC, the calibration circuit comprising: an input subtraction module configured to subtract an estimated error from an output of the ADC and provide a corrected output; a filter module configured to approximate an error transfer function corresponding to the DAC timing errors; a correlation module configured to correlate the corrected output with an output from the filter module to extract an error term; an integrator module configured to integrate the error term to provide an updated error coefficient; and a correction module configured to correlate the updated error coefficient with the output from the filter module to provide the estimated error to the input subtraction module.

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.

This invention discloses a method for improving the accuracy of inertial guidance based on polynomial recursive least squares, comprising: constructing a guidance tool error model based on the difference between inertial guidance telemetry observations and a flight environment function, wherein the guidance tool error model satisfies a linear relationship; constructing a recursive formula based on polynomial recursive least squares based on the guidance tool error model; determining the estimated value of the guidance tool error coefficient at the current recursive time based on the difference between guidance telemetry observations at the current recursive time and the recursive formula of least squares, and using the estimated value of the guidance tool error coefficient to compensate for the guidance telemetry observations at the current recursive time. This invention can significantly improve estimation accuracy and efficiency, and has a wider range of applications and higher engineering value.

The invention belongs to the field of two-dimensional thrust vectoring nozzle control, and particularly relates to a cooperative control method and system for multiple control loops. The method comprises the following steps: step 1, determining a virtual saturation processing mode; step 2, determining a collaborative error processing mode, including acquiring displacement deviation of each execution mechanism; calculating a collaborative error coefficient of each execution mechanism according to the displacement deviation; superposing the control signal after the virtual saturation processing with the collaborative error coefficient; and step 3, realizing cooperative control of a plurality of control loops based on the virtual saturation processing mode and the cooperative error processing mode. According to the cooperative control method of the multiple control loops, the control current of the nozzle controller is corrected by using the cooperative error coefficient, the transition state matching among the multiple loops is adjusted, and meanwhile, the steady-state control quality is not influenced.

The invention discloses a noise and non-ideal calibration-based uncertainty hybrid propagation model construction method, which comprises the following steps of: determining two uncertainty sources of noise and a non-ideal calibration standard, namely the uncertainty of the noise and a self-defined value of the non-ideal calibration standard in a measurement system; determining an error model and a calibration method, measuring system noise according to a calibration standard required by the calibration method and spreading the system noise to a measurement value, and calculating uncertainty of a non-ideal calibration standard; jointly coupling the non-ideal calibration standard uncertainty and the measured value uncertainty caused by the noise to an error coefficient obtained by solving through an error model to obtain an error term; and re-coupling the synthetic uncertainty carried by the error term and the noise in the measurement of the to-be-measured device through an error model, and jointly transmitting to a final calibrated scattering parameter result.

The application provides a wheel hub motor MTPA control method, device, equipment and storage medium, and belongs to the motor control technical field, wherein the method comprises the following steps: constructing an MTPA calculation model; when a torque reference value changes, calculating an axle current reference value of a next control period through the MTPA calculation model; taking the next control period as a current control period, calculating a partial derivative error and an error coefficient of the current control period; comparing the error coefficient of the current control period with a preset limit value, when the error coefficient of the current control period is greater than the preset limit value, iteratively correcting the MTPA calculation model; and when the error coefficient of the current control period is less than or equal to the preset limit value, finally correcting the MTPA calculation model. The wheel hub motor MTPA control method, device, equipment and storage medium can improve the control precision of the motor and improve the dynamic performance.

The invention relates to the technical field of silicon controlled rectifier testing, in particular to a silicon controlled rectifier impact resistance testing method and system. The method comprises the following steps: acquiring a zero-crossing signal monitoring moment and a driving signal monitoring moment, acquiring delay duration controlled by a relay each time, and synchronously acquiring environment monitoring data at the monitoring moments; calculating a time extension error coefficient based on the delay duration, calculating an environment error coefficient based on the environment monitoring data, and forming a coefficient vector; collecting all coefficient vectors, calculating a time delay controllable coefficient of each time of relay control, constructing a two-dimensional sample space, and calculating error influence expressions corresponding to different time delays; carrying out statistical analysis on the error influence performance data of all the silicon controlled elements, and determining an error influence performance threshold value; and comparing the error influence performance at each monitoring moment with an error influence performance threshold value, and evaluating the impact resistance of the silicon controlled element. The accuracy of the impact resistance test result of the silicon controlled rectifier is remarkably improved.

The present application relates to thyristor testing technical field, specifically to a kind of thyristor impact resistance test method and system.The method includes the following steps: obtaining zero-crossing signal monitoring moment and driving signal monitoring moment, obtain the delay length of each relay control, and synchronously obtain the environmental monitoring data of monitoring moment;Based on the delay length calculation time extension error coefficient, based on environmental monitoring data calculation environmental error coefficient, and form coefficient vector;Collect all coefficient vectors, calculate the time delay controllable coefficient of each relay control, construct two-dimensional sample space, calculate the error influence performance corresponding to different time delay;Statistical analysis is carried out to the error influence performance data of all thyristor elements, and the threshold of error influence performance is determined;The error influence performance of each monitoring moment is compared with error influence performance threshold, and the impact resistance of thyristor element is evaluated.The present application realizes the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of the accuracy of

The invention discloses a heat pump air conditioning system with dynamic adjustment starting return difference control. The heat pump air conditioning system comprises a first temperature sensor, a compressor and a controller in communication connection with a reversing four-way valve, wherein the first temperature sensor is used for obtaining the temperature of an external heat source exchanging heat with a first heat exchanger; the controller comprises a temperature difference calculation unit used for obtaining the temperature of an external heat source, the set temperature of the external heat source and the communication state of the reversing four-way valve and calculating the actual temperature difference according to the communication state of the reversing four-way valve. The error acquisition unit is used for acquiring a first error, a second error and a third error; the return difference calculation unit is used for calculating a target return difference according to the initial return difference, the first error, the second error, the third error, the first error coefficient, the second error coefficient and the third error coefficient; and the system starting control unit is used for controlling the system to start according to the system starting times. Operation stability can be improved, and energy conservation, noise reduction and prolonging of the service life of equipment are both considered.

A kind of double-axis frame inertial navigation system error self-calibration and compensation method, under static base condition, in 8 frame angle position locking platform, acquisition accelerometer measurement value, calculate the specific force measurement value of inertial navigation system in each locking position platform coordinate system, and calculate the attitude matrix of inertial navigation system in each locking position platform coordinate system to local horizontal coordinate system, obtain the acceleration of inertial navigation system in each locking position local horizontal coordinate system, as error observation quantity.Using total least squares algorithm to obtain the residual of error coefficient, correct the estimated value of measured parameter, carry out iterative calculation until meeting iteration convergence criterion, obtain the self-calibration result of each error coefficient;Through the self-calibration and compensation of error coefficient, the influence of shaft system non-orthogonal error on the attitude measurement precision of double-axis frame inertial navigation system carrier or base can be improved.

The present application relates to the technical field of machine intelligence, in particular to a control method of a multi-station manipulator for stamping of a washing machine shell, which constructs a synchronization error matrix to determine an error transmission station sequence and a disturbance source station by using a station cooperative calibration experiment; in the working process of the station manipulator, the end load error coefficient of each station is determined, and the cumulative error weight of each station is determined in combination with the sequence number difference of each station and the disturbance source station in the error transmission station sequence; based on the cumulative error weight and the real-time position error of the manipulator of the disturbance source station, and in combination with the synchronization error matrix, the cumulative error amount of each station is determined; finally, according to the real-time position error and the cumulative error amount of the manipulator of each station, the error compensation value of each station is determined and compensation control is performed. The present application improves the accuracy of manipulator error compensation by determining the cumulative error amount of each station.

This invention discloses a method for processing error data of smart energy meters based on edge computing, belonging to the technical field of error data processing methods. The invention includes: S1, calculating the mean and standard deviation of the total energy increment sequence within a sliding window, defining a first-order autoregressive hysteresis correction term, setting an adaptive threshold, defining the state machine system state, and finding the computer increment sequence during inactive periods by constructing an inactive period criterion; S2, storing the filtered effective data increments, calculating the energy increment of each sub-meter, defining a continuous zero increment detection function, collecting effective rearranged data points by setting the meter failure detection window and parameters, and constructing an observation matrix X and an observation vector Y; S3, using an improved genetic optimization algorithm framework, calculating eigenvalues ​​and condition numbers, and iteratively obtaining optimal and distinct individuals; S4, determining the optimal regularization parameters using the L-curve method, and calculating the error coefficients of each energy meter using improved Tikhonov regularization.

The application discloses a circulating error improved wind speed prediction super-capacity energy storage grid-connected method and related products, and belongs to the technical field of wind power generation. The method is characterized in that: the original wind speed sequence of a wind farm is obtained and is divided into a training set and a test set; a prediction model is inputted with the training set to obtain a predicted value, and an error coefficient is calculated accordingly; the original wind speed sequence is corrected by using the error coefficient, a wind speed correction sequence and a first-order residual sequence are generated, and the residual sequence is iteratively corrected until the residual error coefficient is less than a preset value; the wind speed correction sequence and all-order residual sequences are inputted into the prediction model to be superimposed to obtain a final wind speed prediction value; and finally, the prediction value is used to determine the shortage of the super-capacity energy storage system, and a charging and discharging plan is formulated to realize efficient dispatching of the power grid. The application continuously optimizes the wind speed prediction result through the circulating error correction mechanism, and provides a reliable basis for accurate grid-connected dispatching of the super-capacity energy storage system.

A self-calibration method for frame non-orthogonality error and accelerometer error in a dual-axis frame inertial system is proposed. Under static base conditions, the platform is locked at 10 frame angular positions, accelerometer measurements are collected, and the specific force measurement of the inertial system in the platform coordinate system at each locked position is calculated. The attitude matrix of the inertial system from the platform coordinate system to the local horizontal coordinate system at each locked position is also calculated, yielding the acceleration of the inertial system in the local horizontal coordinate system at each locked position, which is used as the error observation. The residuals of the error coefficients are calculated using a total least squares algorithm, and the estimated values ​​of the measured parameters are corrected. Iterative calculations are performed until the iterative convergence criterion is met, obtaining the self-calibration results for each error coefficient. Through the self-calibration and compensation of the error coefficients, the accuracy of attitude measurement of the dual-axis frame inertial system carrier or base affected by the non-orthogonality error of the axis system can be improved.

The invention provides a direct current buck converter constant value steady-state error convergence control method and device. The method comprises the following steps: acquiring the input voltage, the output voltage and the inductive current of each stage of direct current buck converter; setting a corresponding output voltage target value, an error coefficient and a convergence factor; calculating an error function of each stage according to a difference value between an output voltage target value and an actual output voltage in combination with an error coefficient; carrying out convergence operation on the error function to enable the error function to converge in finite time; calculating an actual voltage gain according to the result of the convergence operation in combination with the dynamic change of the input voltage and the inductive current; and comparing the actual voltage gain serving as a modulation signal with a carrier wave to generate a pulse width modulation signal, and driving a power switch tube of the direct-current buck converter with the corresponding series. Based on the method, the invention further provides a control device. According to the invention, the change of the output voltage of the DC buck converter in the error convergence approximation process can be dynamically compensated, and a good control effect is realized.

The invention discloses a multi-task cooperative intelligent progress management method based on artificial intelligence, and relates to the technical field of bridge engineering data management and analysis. The method comprises the following steps: carrying out the first adjustment of the bridge measurement radar; performing bridge engineering intelligent progress first management; carrying out second adjustment on the bridge measurement radar; performing bridge engineering intelligent progress second management; and self-updating the intelligent progress management model of the bridge engineering. According to the invention, single radar parameter evaluation is carried out and then error coefficient calculation and first adjustment are carried out; performing radar composite influence evaluation, model correction and second adjustment; and finally, model self-updating is retrained through actual and target time error data, so that the effect of improving the robustness of collaborative progress management in bridge construction is achieved, and the problem of insufficient robustness of collaborative progress management in bridge construction in the prior art is solved.

The invention provides a current sampling error compensation method, system and device, a medium and a program product, and the method comprises the steps: extracting an extra current harmonic wave from a sampling current of a motor through a constructed combined complex filter, and reconstructing a sampling error coefficient according to the current harmonic wave; and compensating the sampling current according to the sampling error coefficient so as to eliminate the influence of the sampling error. According to the method, the combined complex filter is constructed, the extra current harmonic is extracted from the sampling current, the sampling error coefficient is reconstructed according to the extracted harmonic component, the error is compensated, extra hardware is not needed, extra injection signals are not needed, the reconstructed sampling error coefficient changes in real time, and the error compensation precision is improved. The change of sampling errors along with time caused by temperature excursion is avoided, the loss of the motor is reduced, the overall working efficiency of a motor control system is improved, and the service life of the motor is prolonged.

This invention discloses a method for improving the accuracy of inertial guidance based on the least squares method, comprising: constructing a recursive formula for the least squares method according to the guidance tool error model; and applying the difference y between k-dimensional guidance telemetry observations at the current recursive time in real time. n+ 1. Combining the recursive formula of the least squares method, the estimated value of the guidance tool error coefficient at the current recursive time is determined. This estimated value is then used to compensate for the k-dimensional guidance telemetry observations at the current recursive time. The specific method for constructing the recursive formula of the least squares method includes: determining the value of the constant p. When the constant p is used as the iteration number, the recursive formula of the least squares method is an iterative recursive least squares recursive formula; when the constant p is used as the order, the recursive formula of the least squares method is a polynomial recursive least squares recursive formula. This invention can significantly improve the estimation accuracy and has a wider range of applications and higher engineering value.

This invention discloses a method and related apparatus for controlling the positions of reactor control rods, comprising: acquiring the original position sequence of the reactor control rods; decomposing the original position sequence to obtain M IMF components; and inputting the M IMF components into a trained Long Short-Term Memory (LSTM) network model to obtain predicted values ​​X1, X2, ..., X... of the M IMF components. M Based on the predicted values ​​X1, X2, ..., X of the M IMF components M An error evaluation index, D-SMAPE, is established with its actual value to obtain the error coefficients ΔY1, ΔY2, ..., ΔY corresponding to the SWT-LMD subsequence. M The error coefficients ΔY1, ΔY2, ..., ΔY M The inputs are fed into the trained ResNet prediction model to obtain the final IMF component prediction values ​​Y1, Y2, ..., Y of the original bar sequence. M Based on the final IMF component prediction values ​​Y1, Y2, ..., Y of the original bar sequence M The method and related devices for controlling the movement of control rods can accurately control the position of reactor control rods.

The invention provides a CVT error calculation method based on ALS-MLE and a medium, relates to the technical field of electric power measurement, and aims to solve the problem that the voltage measurement precision is affected by a ratio difference error and an angle difference error due to the fact that a CVT in an electric power system generates unsteady-state characteristics due to temperature, humidity and load changes. According to the method, a mixed algorithm combining ALS and MLE is adopted, and the method is used for online monitoring and CVT error calculation. The method comprises the following steps: firstly, collecting secondary end voltage measurement data of the CVT at a plurality of time points, and analyzing amplitude and phase information; on the basis of a log-likelihood function, maximum likelihood function estimation is utilized, iterative optimization is carried out in combination with ALS, and CVT error parameters are solved; and finally, the amplitude and the phase error of the CVT are corrected simultaneously according to the solving result to adapt to the dynamic error change in the operation of the CVT. According to the method, the error coefficient in the capacitor voltage transformer can be effectively estimated, and the error is corrected, so that the accuracy of on-line monitoring of the voltage value is improved.

This invention relates to the field of electric drive system design and development for new energy vehicles, specifically to a method for testing and analyzing the dynamic stiffness of electric drive assembly mounts and the accuracy of simulation. The method involves standardized frequency response testing of the electric drive assembly mounts, identification of minimum dynamic stiffness, and the construction of a dynamic simulation model consistent with the test boundaries to extract the minimum dynamic stiffness on the simulation side. Then, it sequentially performs frequency and amplitude error analysis of the minimum dynamic stiffness points in the tests and simulations, as well as average dynamic stiffness error analysis. Finally, it comprehensively calculates accuracy performance coefficients based on multi-dimensional error coefficients and establishes a scoring system to achieve a quantitative evaluation of the test and simulation accuracy. This method solves the technical problems in existing technologies where evaluating the dynamic stiffness of electric drive assembly mounts requires multiple physical impact tests, which are resource-intensive, time-consuming, and lack a systematic and quantitative analysis method for testing and quantifying the accuracy of mount dynamic stiffness, thus failing to utilize the preliminary analysis results to guide subsequent mount design and development.

The invention provides a coal feeder weight intelligent conveying method and system based on environment self-adaption and dynamic verification, and relates to the technical field of thermal power plant coal feeder verification. S1, belt operation state parameters, weighing basic parameters and environment interference parameters are synchronously collected through sensor assemblies deployed on the A / B side of a coal feeder; carrying out anti-interference preprocessing by adopting a Kalman filtering algorithm, and outputting an effective parameter set P; and S2, dynamically adjusting the operation state of the weight conveying device according to the effective parameter set P, and obtaining the coordinates of the weight and the belt weigher through visual positioning. Through the cooperation of the above structures, compared with the existing method, the method has the following beneficial effects that the forgetting factor and the error coefficient of the RLS algorithm are dynamically adjusted by adopting environmental parameters, dynamic errors caused by belt speed and acceleration fluctuation are compensated in real time, and the influence of belt dynamic fluctuation and environmental interference on the verification precision can be effectively overcome.

The application discloses a simulation test method, device, equipment, medium and product, the method comprises the following steps: pre-training the error coefficient determination module based on the theoretical database, the general simulation database and the general measured database, and determining the general model under the general simulation topology; simulating the specific signal based on the general model to obtain specific simulation data; post-training the general error coefficient determination module according to the specific simulation data and the measured data under the specific signal, determining the scene-based error coefficient corresponding to the specific signal and the scene-based compensation reference parameter, and taking the mature model; receiving the actual simulation demand, calling the mature model based on the scene-based error coefficient and the scene-based compensation reference parameter corresponding to the actual simulation demand, simulating and compensating the error of the actual simulation demand, and obtaining the compensated simulation result. The compensation parameters corresponding to different scenes are determined through training, different signal scenes are accurately adapted, and the accuracy of the simulation result is improved.

The invention relates to the technical field of digital multimeter systems, in particular to a high-precision digital multimeter system based on man-machine interaction, which comprises a primary error analysis module, a secondary error analysis module and a computer module, the first-level error analysis module calculates a first-level error function according to the first-level error coefficient, obtains first-level error information according to the first-level error function and transmits the first-level error information to the computer module; the second-level error analysis module calculates a second-level error function according to the second-level error coefficient, obtains second-level error information according to the second-level error function and transmits the second-level error information to the computer module; and the computer module transmits the first-level error information and the second-level error information to the client. The information with larger or smaller first-level errors and second-level errors can be obtained, and technicians in the field can make corresponding adjustment according to the information, so that the detection precision of the digital multimeter system is improved.

This invention provides a CVT error calculation method and medium based on ALS-MLE, belonging to the field of power measurement technology. It aims to solve the problem of voltage measurement accuracy being affected by the non-steady-state characteristics of CVTs in power systems caused by temperature, humidity, and load changes, resulting in ratio and angle difference errors. This invention employs a hybrid algorithm combining ALS and MLE for online monitoring and calculation of CVT errors. First, secondary terminal voltage measurement data of the CVT at multiple time points are collected, and the amplitude and phase information are analyzed. Based on the log-likelihood function, maximum likelihood function estimation is used, combined with iterative optimization using ALS to solve for the CVT error parameters. Finally, based on the solution results, the amplitude and phase errors of the CVT are simultaneously corrected to adapt to dynamic error changes during operation. This invention can effectively estimate the error coefficients in capacitive voltage transformers and correct errors, thereby improving the accuracy of online voltage monitoring.

The embodiment of the application discloses a hemispherical resonator gyro error force compensation method and device. The method comprises the following steps: in the force balance mode, using electrostatic driving force, electrostatic feedback force, quasi-orthogonal control force and virtual Coriolis force, completing self-excitation of the gyro error; according to the proportional relationship between the electrostatic driving force and the electrostatic feedback force, obtaining the HRG error evolution model of the sensitive angular velocity information, obtaining the rate HRG scale factor and the zero bias error parameter; according to the relationship between the scale factor and the zero bias error parameter and the non-equal damping error coefficient, obtaining the non-equal damping error coefficient; according to the non-equal damping error coefficient, generating electrostatic compensation force through the self-excitation control module, and acting on the x x-axis and y-axis directions, completing the gyro error force compensation. The application solves the problem that the existing gyro needs to be recalibrated before each use and the test environment and the actual use environment are different, which seriously affects the gyro reaction speed and leads to low gyro angular velocity output precision, and achieves the technical effect of improving the gyro angular velocity output precision.

The invention discloses a numerical simulation and machine learning combined rolling model establishment method, which relates to the field of metal rolling, and comprises the following specific steps of: constructing a numerical simulation model in a rolling production process and a rolling process parameter data set containing each rolling process parameter group, further obtaining the size simulation value of the rolled piece after rolling and the rolling force simulation value of the rolling mill corresponding to each rolling process parameter group; obtaining a real value of a rolled piece size after rolling and a real value of a rolling force of a rolling mill corresponding to each rolling process parameter group, further obtaining an error coefficient corresponding to each rolling process parameter group, and carrying out normalization processing to form a sample set taking a single rolling process parameter group and the corresponding error coefficient as samples; and training a pre-constructed support vector regression model by using the sample set to obtain a rolling model. According to the rolling model obtained through the method, errors generated during simulation can be eliminated, and the size of a rolled piece and the rolling force of the rolling mill can be rapidly and accurately predicted.