65 results about "Error coefficient" patented technology

The invention discloses an electric energy meter error prediction method and system based on big data analysis, and relates to the technical field of electric power measurement, and the method comprises the steps: firstly reading the device attribute, the voltage fluctuation threshold value and the power utilization load threshold value of a target electric energy meter, dividing parameters into a plurality of voltage fluctuation intervals and load proportion intervals, and constructing a plurality of power utilization scenes; thirdly, obtaining a sample training set based on the power big data by taking device attributes and power consumption scenes as constraints, and training through a BP neural network to obtain a plurality of error predictors; and finally, by establishing an error prediction model, inputting a real-time voltage fluctuation coefficient, an electricity load proportion and an environment factor, and outputting a prediction error coefficient of the electric energy meter. The technical problem that an existing electric energy meter is inaccurate in error prediction in a complex environment is solved, and the technical effect that metering of the electric energy meter is more accurate under different voltage fluctuation, environment conditions and load conditions is achieved.

The invention belongs to the technical field of phase control cabinet phase regulation and control, and particularly relates to a phase control cabinet regulation and control system and method based on multistage phase compensation. According to the method, the voltage waveform and the current waveform output by the phase control cabinet are preliminarily compensated so as to reduce the initial phase deviation, environmental parameters are matched with a pre-stored interference feature library, the type of an interference source can be identified, and the interference source is quantified as a thermal noise contribution value to calculate an interference intensity prediction value in a prediction window, so that the prediction accuracy is improved. And then providing data support for secondary compensation through a phase residual error output by an interference intensity predicted value, determining a compensation gain parameter according to a dynamic error coefficient during secondary compensation, performing secondary compensation on a voltage waveform and a current waveform to enable a phase deviation to be converged to a preset range, and according to the phase convergence information after secondary compensation, determining the interference intensity predicted value according to the phase convergence information after secondary compensation. And the sampling frequency and the compensation weight factor of the sensor array are reversely adjusted to form a closed-loop compensation control link, so that continuous optimization and improvement of the compensation process are realized.

The invention discloses a pressurized water reactor primary loop boron concentration prediction and control method and system, and the method comprises the steps: obtaining an original helium flow sequence of a pressurized water reactor primary loop, and obtaining M boron concentration IMF components IMF1,..., IMFM; the M boron concentration IMF components IMF1,..., IMFM are put into a trained LSTM model for prediction, predicted values Y1, Y2,..., YM of the IMF components are obtained, and error coefficients delta Y1, delta Y2,..., delta YM corresponding to the boron concentration IMF components are calculated according to the predicted values Y1, Y2,..., YM of the IMF components; and inputting error coefficients delta Y1, delta Y2,..., delta YM corresponding to each boron concentration IMF component into the trained DenseNet prediction model to obtain an optimal IMF component predicted value # imgabs0 # of the boron concentration signal sequence, based on a DEM-DAC algorithm, controlling the boron concentration of the pressurized water reactor primary loop according to the optimal IMF component predicted value # imgabs1 # of the boron concentration signal sequence, and calculating the boron concentration of the pressurized water reactor primary loop according to the optimal IMF component predicted value # imgabs0 # of the boron concentration signal sequence. The method and the system can solve the technical problems that the boron concentration fluctuation of the primary loop is large and the unit load regulation performance is poor during the reactor variable load operation period.

The invention provides an intelligent phase control vacuum circuit breaker health degree assessment method and device and a circuit breaker, and relates to the technical field of circuit breaker health assessment, and the method comprises the steps: carrying out the vacuum degree detection of an arc extinguish chamber in an intelligent phase control vacuum circuit breaker, and obtaining the vacuum degree; performing heating analysis on the vacuum circuit breaker according to the vacuum degree to obtain a heating parameter, and performing zero crossing point monitoring error analysis to obtain a zero crossing point error coefficient; according to the operation time parameter of the vacuum circuit breaker, mapping to obtain a mapping zero-crossing point error coefficient, calculating to obtain a zero-crossing deviation coefficient, and according to the zero-crossing deviation coefficient and an analysis deviation coefficient of heating analysis and zero-crossing point monitoring error analysis, carrying out confidence degree processing to obtain a zero-crossing confidence degree; and distributing a weight according to the zero-crossing confidence coefficient, and performing health degree calculation based on the vacuum degree and the zero-crossing point error coefficient to obtain the health degree of the vacuum circuit breaker. The technical problem of inaccurate health degree evaluation of the intelligent phase-controlled vacuum circuit breaker in the prior art is solved.

The invention discloses a control system of a processing machine tool and a control method of the control system, and particularly relates to the technical field of processing machine tool control. Obtaining a feedback error coefficient of each sub-interval according to the data transmission error coefficient, the electromagnetic interference coefficient and the voltage unavailable coefficient, screening out all abnormal coefficients according to the feedback error coefficients in all the sub-intervals, calculating standard deviations of all the abnormal coefficients, and comparing the standard deviations with a preset standard deviation value; and the operation state of the processing machine tool is controlled according to the comparison result, so that the processing information fed back to the system can be judged, whether the fed-back processing information is wrong or not is judged, and corresponding measures are taken in time, so that the system does not make wrong response, and the influence on the processing quality is reduced.

The invention belongs to the technical field of intelligent driving, and discloses a distributed driving vehicle trajectory tracking control method considering an energy consumption factor, and the method comprises the steps: obtaining a reference trajectory needing to be tracked, and constructing a trajectory tracking control model according to the reference trajectory; obtaining a front wheel rotation angle calculation formula and a rear wheel rotation angle calculation formula according to the trajectory tracking control model; delta f is equal to Kp1. E1 + Kd1. E2; delta r is equal to Kp2e1 + Kd2e2 + 1.5 * u2b; delta f is a front wheel turning angle, delta r is a rear wheel turning angle, Kp1 is a front wheel displacement error coefficient, Kd1 is a front wheel speed error coefficient, Kp2 is a rear wheel displacement error coefficient, Kd2 is a rear wheel speed error speed, e1 is a transverse displacement error, e2 is a transverse speed error, and u2b is a feedback quantity of the rear wheel turning angle; establishing a target function, and optimizing an array formed by the front wheel displacement error coefficient, the front wheel speed error coefficient, the rear wheel displacement error coefficient and the rear wheel speed error speed by taking the minimum target function as an optimization target to obtain an optimal array; and calculating according to the optimal array to obtain an optimal front wheel steering angle and an optimal rear wheel steering angle.

The invention discloses an abnormal current transformer error online evaluation method and system, and relates to the technical field of power transmission and distribution equipment state evaluation and online monitoring, and the method comprises the steps: calculating a current transformer standard error; drawing a standard error coefficient curve; calculating the actual error of the current transformer; when the actual error current is not equal to the standard error current under the same condition, calculating an error current correlation coefficient variable quantity under the current condition, and when the error current correlation coefficient variable quantity exceeds a threshold value set by the standard error coefficient curve, judging that the current transformer fluctuates; and when the current transformer is judged to have fluctuation, calculating the sum of the three-phase current of the current transformer, and when the sum of the three-phase current exceeds the threshold value of the sum of the three-phase current under the same condition, judging that the transformer is an abnormal transformer. According to the method, the problems that an existing operation current transformer error evaluation method is prone to being affected by the environment and poor in engineering adaptability are solved, and abnormity monitoring and warning of the current transformer are achieved.

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 method and a system for calibrating a jerk error term coefficient of a PIGA and a medium, belongs to the technical field of rocket launching, and aims to calibrate # imgabs0 # by exciting jerk error term output in a uniform acceleration stage of a centrifugal machine. PIGA output is used as observed quantity, and the calibration precision of the jerk error coefficient is simulated and analyzed. Analysis shows that in the specific application of rocket launching, the circular probability error CEP of a rocket drop point when the # imgabs 1 # is calibrated is two orders of magnitude smaller than the circular probability error CEP of a rocket drop point when the # imgabs 2 # is not calibrated, and the precision and practicability are improved.

The invention relates to a pressure gauge metering calibration method and system driven by error analysis, and relates to the field of pressure gauge metering calibration, and the method comprises the steps: carrying out the aging analysis of an elastic element according to the accumulated use time and loading and unloading records, and obtaining an aging analysis result; carrying out mechanical error analysis according to an aging analysis result to obtain a mechanical error coefficient, and carrying out lag error analysis to obtain a lag error coefficient; the method comprises the following steps: performing error correction by adopting mechanical and lag error coefficients to obtain a mechanical error value and a lag error value, compensating the lag error value according to a real-time loading and unloading record to obtain a compensated lag error value, and calibrating a metering result in combination with the mechanical error value. According to the invention, the technical problem that the accuracy and reliability of the measurement calibration result of the pressure gauge are insufficient due to the fact that the traditional method cannot accurately quantify the influence of the aging of the elastic element in the pressure gauge on the measurement error can be solved; and the accuracy, the stability and the reliability of the measurement calibration of the pressure gauge can be obviously improved.

The invention discloses a reactor control rod position control method and a related device, and the method comprises the steps: obtaining an original rod position sequence of a reactor control rod, decomposing the original rod position sequence, and obtaining M IMF components; inputting the M IMF components into a trained long short-term memory network model to obtain predicted values X1, X2,..., XM of the M IMF components, establishing an error evaluation index D-SMAPE according to the predicted values X1, X2,..., XM of the M IMF components and actual values thereof, and obtaining error coefficients delta Y1, delta Y2,..., delta YM corresponding to SWT-LMD subsequences; inputting the error coefficients delta Y1, delta Y2,..., and delta YM into a trained ResNet prediction model to obtain final IMF component prediction values Y1, Y2,..., and YM of the original rod position sequence; and controlling the control rod to act according to the final IMF component predicted values Y1, Y2,..., YM of the original rod position sequence. According to the method and the related device, the rod position of the reactor control rod can be accurately controlled.

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 present invention provides a method, device, storage medium and terminal for calculating the inclination angle of a near-bit, including: obtaining the past data of the near-bit, and establishing a correction model according to the past data; obtaining the initial measured inclination angle value of the near-bit at the current moment; obtaining the relevant parameter information of the near-bit at the current moment and the previous moment, and calculating the error coefficient of the inclination angle measuring tool according to the relevant parameter information at the current moment; calculating the current angle change ratio of the near-bit; inputting the relevant parameter information of the near-bit at the current moment and the previous moment into the correction model to obtain a primary output result and a secondary output result, and performing correction processing on the primary output result, the initial measured inclination angle value and the secondary output result according to the error coefficient and the angle change ratio to obtain the target inclination angle. Without changing the hardware conditions, the present invention effectively improves the accuracy of the inclination angle measurement result inside the near-bit.

The invention provides a power grid multi-energy data acquisition frequency control method considering a load prediction error, and belongs to the technical field of prediction control. The method comprises the steps of determining energy types of multiple energy sources of a research power grid, collecting original data of the energy sources according to energy characteristics of any energy type, and standardizing the original data to obtain standard power generation data; building a load prediction model, taking the standard power generation data of all energy types as the input of the load prediction model, and outputting a load prediction result; performing error analysis on the load prediction result and the actual load result to obtain an error coefficient of the corresponding energy type; based on a control algorithm, combining the error coefficient of the energy type and standard power generation data, and adjusting the collection frequency of the energy; and evaluating the frequency control result, and reversely optimizing the control algorithm and the load prediction model based on the evaluation result. And the load prediction precision and scheduling efficiency of the multi-energy power grid are improved.

The invention relates to the technical field of oil and gas reservoir engineering, in particular to a quantitative treatment method for a relative permeability curve. The method comprises the following steps: deriving a water content formula according to a relative permeability curve and a Darcy law; obtaining an oil content formula according to the obtained water content formula; s2, fitting oil production error coefficient parameters are introduced, and the corrected oil content is calculated in cooperation with the oil content formula obtained in the step S2 under the condition that the liquid production is not changed; determining the corrected water content according to the obtained corrected oil content, and establishing a relative permeability curve water phase permeability correction equation by combining the Darcy law; and S4, compiling a VBA relative permeability adjustment program according to an excel vba technology, and performing quantitative processing programming on the data calculated by the correction equation obtained in the step S4 through the adjustment program. According to the method provided by the invention, the relative permeability block is quantitatively adjusted by applying the method, and the working difficulty of historical fitting of traditional numerical simulation is solved.

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.

The invention discloses a thorium-based molten salt reactor primary loop molten salt flow prediction and control method and system, and the method comprises the steps: obtaining an original molten salt flow signal of each node in a thorium-based molten salt reactor primary loop, and obtaining a multi-scale molten salt flow component; inputting the multi-scale fused salt flow component into an LSTM network adaptive gating mechanism network model to obtain a fused salt flow initial prediction value of each node; obtaining an error coefficient of the fused salt flow based on D-SMAPE according to the initial predicted value of the fused salt flow of each node; the error coefficient of the fused salt flow is input into the trained ResNet prediction model, and an optimal fused salt flow prediction value is obtained; according to the optimal fused salt flow predicted value, the fused salt flow of the thorium-based fused salt reactor primary loop is controlled based on the DEM-DAC algorithm, and the method and system can solve the technical problems that during reactor variable-load operation, the fused salt flow fluctuation is large, and the unit load adjusting performance is poor.

The invention relates to the technical field of unmanned aerial vehicle control, in particular to an injector time calibration method, device and equipment and a medium, the method is applied to an MCU of an injector, and the method comprises the steps that whether a PPS IN signal exists or not is detected, and a detection result is obtained; based on a detection result, determining a timing condition; obtaining an error coefficient, wherein the error coefficient is a first time difference expanded by the equipment per second; based on the error coefficient and the timing condition, total error time needing to be compensated is calculated; and based on the total error time, a compensation mechanism is executed, so that the synchronization precision and the travel time precision can be improved.

The present application provides a health assessment method, device, and circuit breaker for an intelligent phase-controlled vacuum circuit breaker, and relates to the technical field of circuit breaker health assessment. The method comprises: performing vacuum detection on the arc extinguishing chamber in the intelligent phase-controlled vacuum circuit breaker to obtain the vacuum degree; performing a heat analysis of the vacuum circuit breaker based on the vacuum degree to obtain a heat parameter, performing a zero-crossing monitoring error analysis, and obtaining a zero-crossing error coefficient; mapping the zero-crossing error coefficient based on the operating time parameter of the vacuum circuit breaker, calculating a zero-crossing deviation coefficient, performing confidence processing based on the zero-crossing deviation coefficient and the analysis deviation coefficient of the heat analysis and the zero-crossing monitoring error analysis to obtain a zero-crossing confidence degree; assigning a weight based on the zero-crossing confidence degree, performing a health calculation based on the vacuum degree and the zero-crossing error coefficient, and obtaining the health degree of the vacuum circuit breaker. The method solves the technical problem of inaccurate health assessment of intelligent phase-controlled vacuum circuit breakers in the prior art.

The invention discloses a boiler combustion monitoring method and system based on multi-model joint simulation, and relates to the technical field of boiler monitoring, and the method comprises the steps: obtaining prediction output data of the same physical quantity of a CFD-AI model and a Modelica model, and calculating a precision difference coefficient; calculating a data scale coefficient according to the maximum value of the predicted output data; acquiring an error of data transmission of the same physical quantity between the CFD-AI model and the Modelica model, and calculating a parameter transmission error coefficient according to the error of data transmission; an error accumulation coefficient between the models is obtained according to the precision difference coefficient, the data scale coefficient and the parameter transfer error coefficient, the error accumulation coefficient is compared with a preset error accumulation coefficient threshold value, and the accuracy of boiler combustion data monitored according to simulation is judged according to a comparison result. Error accumulation of cooperative work between the CFD-AI model and the Modelica model can be judged, the reliability of a final simulation result is ensured, and boiler combustion monitoring data are accurate.

The present invention provides an online correction method and system for the error coefficient of a synchronous acquisition device, the method comprising: obtaining voltage values ​​collected by different channels of the synchronous acquisition device, constructing a multi-channel parallel measurement model of the same reference source, and establishing an error solution equation group of the error coefficient; obtaining the normal value, negative deviation and positive deviation distribution of the error coefficient of the voltage reference source based on the distribution law of the error coefficient of the synchronous acquisition device; traversing the values ​​of the error coefficient of the voltage reference source in each distribution interval, and obtaining the error coefficient joint distribution probability data set and the state category data set under the constraint of the parallel measurement model; based on the normal principle of the cluster subject and the maximum likelihood target, the optimal solution in the error coefficient joint distribution probability data set is screened, and the error coefficient corresponding to the optimal solution is obtained to perform online correction on the synchronous acquisition device. Through this scheme, the accuracy and reliability of the online correction of the error coefficient of the synchronous acquisition device can be guaranteed, and the accuracy of data acquisition of power equipment can be improved.

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.