210 results about "Linearity error" patented technology

The invention relates to a temperature drift compensation method for a pressure instrument, and belongs to the technical field of pressure instruments, and the method comprises the following steps: obtaining output signal values of a pressure sensor at different temperature points, and building a temperature-output signal data set; constructing a polynomial fitting model as a temperature drift compensation model, fitting a temperature coefficient through a least square method, and storing the coefficient into an instrument memory; original values of temperature and pressure are collected in real time and substituted into the model to calculate a compensated pressure value. The method also supports various strategies such as temperature sensor calibration, nonlinear error compensation, Kalman filtering noise reduction, dynamic temperature change rate compensation and neural network compensation, and has self-calibration and remote updating functions. According to the invention, the measurement precision and stability of the pressure instrument in a variable-temperature environment are significantly improved, and the method is suitable for high-precision industrial measurement and intelligent monitoring scenes of the Internet of Things.

The invention relates to the technical field of precise motion control, in particular to an XY motion platform positioning error compensation system and method, which extracts spatial-temporal characteristics through multi-modal data fusion and normalization processing in combination with a neural network hybrid model, and dynamically manages time sequence errors by using a forgetting gate, an input gate and an output gate. And a compensation parameter is updated by adopting an online adaptive training mechanism of error source classification. The problems that in the prior art, due to mechanical abrasion and thermal deformation of an encoder, precision is attenuated, nonlinear errors are difficult to process through a PID algorithm, pure vision positioning is prone to interference and complex in calibration, and an online learning mechanism is lacked can be effectively solved, the positioning comprehensive error is reduced to the micron order, the anti-interference robustness and the real-time compensation capacity of a system are improved, and the system reliability is improved. And the positioning precision and the production efficiency are obviously improved.

The invention relates to the technical field of adaptive filtering, discloses a variable-step robust adaptive filter and a filter network, and aims to solve the technical problem that a traditional adaptive filter cannot effectively consider convergence speed, steady-state precision and impulse noise interference resistance. A non-linear error factor is introduced, large errors caused by impulse noise are effectively suppressed through a generalized function form of the non-linear error factor, and the robustness of the filtering process is remarkably improved; meanwhile, a variable step length mechanism is provided, the theoretically optimal candidate step length is calculated on line by minimizing the mean square deviation of the next moment, and a self-adaptive target variable step length is generated through truncation and time smoothing processing, so that dynamic balance is realized between rapid convergence and low-steady-state maladjustment. According to the invention, the filter is expanded to the distributed network, each node follows a diffusion strategy of first updating and then combining, and global information sharing and performance collaborative optimization are realized by using a combined coefficient.

The invention discloses a nonlinear error compensation device and compensation method for a five-axis machine tool, in the device, an X-axis compensation assembly is fixed on a bottom fixing plate, a Y-axis compensation assembly is fixed on an X-axis sliding block of the X-axis compensation assembly, and the X-axis sliding block can drive the Y-axis compensation assembly to linearly move back and forth in the X-axis direction; the Z-axis compensation assembly is fixed to a Y-axis sliding block of the Y-axis compensation assembly, and the Y-axis sliding block can drive the Z-axis compensation assembly to linearly move back and forth in the Y-axis direction. The workbench is fixed to a Z-axis sliding block of the Z-axis compensation assembly, and the Z-axis sliding block can drive the workbench to linearly move back and forth in the Z-axis direction. According to the technical scheme, movement of the workbench in three directions is achieved, compensation of nonlinear errors is achieved, post-processing software and a built-in kinematics model do not need to be modified, calculation of nonlinear error compensation is simplified, the machining precision of the five-axis machine tool is improved, and production efficiency is improved.

The invention discloses an unmanned aerial vehicle navigation method, device and equipment and a storage medium, and the method constructs an LIEKF algorithm on a world coordinate system (local coordinate system), enables the value to be small, and guarantees the stability of a linear error kinematics matrix and an observation matrix. A left invariant error on a matrix Lie group is defined under a world coordinate system, and the error is kept unchanged on a left group. According to the method, state quantities such as attitude, position and speed and errors are defined in a group space, and a linear state space model independent of the state is deduced through multiplication closure of the Lie group and affine characteristics between Lie algebra and corresponding nonlinear error quantities constructed by the multiplication closure and the Lie algebra. Because the redefined speed error and position error both comprise attitude items, the real error can be represented more accurately.

The invention belongs to the technical field of sensor data fusion, and particularly relates to a DNN-EKF-based multi-sensor heterogeneous data fusion method, a DNN-EKF-based multi-sensor heterogeneous data fusion program, equipment and a storage medium. The method comprises the following steps: predicting a current carrier pose and noise covariance matrix according to a last multi-sensor heterogeneous data fusion result based on an EKF model; for each sensor, pre-training a DNN model, and obtaining a nonlinear error compensation item according to a residual error between carrier pose prediction and observation data of each sensor; and filtering observation data of each sensor by adopting extended Kalman filtering, and balancing a nonlinear error compensation item and an extended Kalman filtering result by adopting a learning weight. According to the method, through combination of DNN and extended Kalman filtering, IMU, VO and GPS heterogeneous data can be effectively fused, the problem of non-uniform data time of different sensors is solved, sensor noise can be dynamically adjusted, and the accuracy of a data fusion result is improved.

The invention belongs to the technical field of detection, and discloses a nonlinear error correction method based on error change trend partition calibration for an eddy current displacement sensor. The method comprises the steps of firstly analyzing a corresponding relation between a displacement value and output voltage, and drawing an output characteristic curve of a sensor; distinguishing an error change trend according to a local extreme value, carrying out interval partitioning on an error change curve, training each partition, constructing a partition training set, constructing a correction model covering the full range of the sensor, and realizing error correction of high-precision measurement of the eddy current displacement sensor; and finally, the measured displacement value is obtained through the linear relation between the output voltage and the displacement value. According to the method, the linearity error, the sensitivity error, the return stroke error and the zero drift error after correction are greatly reduced, and the method is simple, easy to operate and high in real-time performance. Through reasonable segmentation, the complexity of curve fitting is reduced, the correction efficiency of the non-linear error of the eddy current sensor is improved, and the measurement precision is improved.

The invention discloses a non-linear error correction method for an electromagnetic flowmeter based on machine learning. The non-linear error correction method comprises the steps that 1, original monitoring data, working condition parameters and a reference calibration flow value of the electromagnetic flowmeter are collected; 2, performing data preprocessing to obtain a standard feature vector sequence and an original error sequence; 3, performing cycle and trend error feature modeling on the standard feature vector sequence through an improved TimeMixer network; 4, taking the original error sequence as a supervision label, and calculating a joint loss function; 5, designing a double-stage error correction strategy to carry out trend correction and period correction, and generating a corrected flow value sequence; 6, executing physical consistency constraint on the corrected flow value sequence to generate a credible corrected flow value sequence; and step 7, updating the improved TimeMixer network and the credible correction flow value sequence. According to the invention, the measurement precision and the operation stability of the electromagnetic flowmeter under non-linear interference are improved.

The invention relates to a 3D camera galvanometer module motion nonlinear error calibration method, and the method comprises the steps: determining a target galvanometer delay parameter enabling the center position of the reciprocating motion of a galvanometer motor to be aligned under the preset initial camera exposure time and initial galvanometer motion time, and adjusting the stepping modification camera exposure time and galvanometer motion time, the corresponding relation between camera exposure time and galvanometer delay parameters is obtained, the lightening time of the laser at different positions is determined with the minimum nonlinear error of reciprocating motion of the galvanometer motor as the target under different camera exposure time and galvanometer motion time, and the laser is controlled according to the lightening time. And laser compensation parameters when the galvanometer motor operates to different positions at different galvanometer movement speeds are obtained. According to the application, the problem of inaccurate imaging caused by nonlinear errors existing in positive and negative motion of galvanometer structured light projection in related technologies is solved, and the nonlinear errors existing in the positive and negative motion are eliminated through the galvanometer delay parameter and the laser compensation parameter.

The present invention provides an underground mining settlement monitoring method and system that integrates time series and spatiotemporal deformation, and the method includes the following steps: generating an InSAR interference pattern stack based on existing mining area SAR images; obtaining a mining area predicted settlement model and an unwrapped interference pattern stack by a MA-PU assisted model phase unwrapping method based on the InSAR interference pattern stack; removing linear errors and reference points from the unwrapped interference pattern stack; performing pixel classification on the processed unwrapped interference pattern stack, and filling the unwrapped interference pattern stack from the spatial relationship and time relationship of the pixel points based on the pixel type; performing singular value decomposition on the filled unwrapped interference pattern stack to obtain the time deformation sequence of the settlement surface; and completing underground mining settlement monitoring that integrates the time series and spatiotemporal deformation based on the time deformation sequence. The present invention provides more comprehensive deformation data for mining area monitoring.

The invention relates to the technical field of motor control, and discloses a dead-beat predictive current control method of a permanent magnet synchronous motor, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: establishing a current state equation of the three-phase permanent magnet synchronous motor when motor parameters are mismatched; according to a current state equation of the three-phase permanent magnet synchronous motor when the motor parameters are mismatched, determining a d-q axis current estimated by the extended state observer and total disturbance on a current loop, and calculating to obtain a compensation voltage; applying linear active disturbance rejection control to a speed ring, and outputting a linear error feedback control law by the speed ring; based on a linear error feedback control law and d-q axis current estimated by an extended state observer, applying an improved dead-beat predictive current control mode to a current loop to obtain an iterative voltage; and taking the sum of the iteration voltage and the compensation voltage as a reference voltage. By adopting the method, various interferences in a speed loop and a current loop can be effectively relieved, and the robustness of a control system is improved.

The invention provides a front-end readout electronics circuit for a silicon PIN detector. The front-end readout electronics circuit solves the technical problems that an existing front-end readout circuit cannot meet the requirements for quick response, dynamic adjustment of the dynamic range and small nonlinearity error. The charge sensitive amplifier comprises a charge sensitive amplifier and a forming module connected with the charge sensitive amplifier, and the charge sensitive amplifier receives an analog charge signal of the silicon PIN detector and converts the analog charge signal into an analog voltage signal according to a certain gain; the gain is controlled by a feedback capacitor which is dynamically controlled by a register; the reset module is connected in parallel to two ends of the charge sensitive amplifier and is used for releasing the accumulated charge quantity of the charge sensitive amplifier; the forming module performs filtering forming on the analog voltage signal to obtain a Gaussian-like waveform; the forming module comprises a fast forming unit and a slow forming unit, and the fast forming unit is sequentially connected with a comparator and a digital-to-analog converter; the slow forming unit is sequentially connected with the sampling hold circuit, the digital control center module and the analog-to-digital converter. The method can be widely applied to the technical field of particle detection.

The invention discloses a permanent magnet synchronous motor inverter nonlinear error compensation method, which comprises the following steps of: inputting an input capacitor of an insulated gate bipolar transistor (IGBT) and an output capacitor of the insulated gate bipolar transistor (IGBT) into a voltage error mathematical model; estimating a first coefficient, a second coefficient, a third coefficient and a fourth coefficient in the voltage error mathematical model by using an algorithm of a linear neural network; the first coefficient, the second coefficient, the third coefficient and the fourth coefficient in the voltage error mathematical model obtained through estimation are input into the voltage error mathematical model, and the nonlinear voltage error of the permanent magnet synchronous motor inverter is obtained through output of the voltage error mathematical model. According to the invention, the dead zone effect, the switch tube turn-on delay, the switch tube turn-off delay, the switch tube and diode turn-on voltage drop and the stray capacitance effect are comprehensively considered, an accurate voltage error mathematical model is established, and accurate voltage compensation can be realized.

The invention discloses an analog quantity detection system with a protection circuit, and relates to the analog quantity detection system with the protection circuit, which comprises a detection circuit connected with an analog signal through a wiring terminal, the protection circuit and an MCU (Microprogrammed Control Unit), compared with a detection system of a traditional operational amplifier, the instrument amplifier is adopted for detection, and the detection system has the advantages of being ultrahigh in input impedance, extremely good in CMRR, low in input offset, low in output impedance and capable of amplifying signals under common-mode voltage. The circuit also has the functions of high common-mode rejection ratio, low noise, low linear error, low offset voltage and offset voltage drift, and low input bias current and offset current error, and by arranging an AD input clamping protection circuit, when the system has a fault and the voltage suddenly rises, the clamping function is realized by using the unilateral conductivity of a diode, and the phenomenon that the voltage of a sampling port is larger than 5V is prevented. And the ADC port of the MCU is damaged.

The invention provides a multi-baseline InSAR residual phase error correction method and system based on flat ground prior information, and the method comprises the steps: selecting a large flat ground region and a small flat ground region for the terrain prior knowledge of a research region, constructing a residual linear phase model, removing the residual linear error phase of a multi-baseline InSAR interferometric phase, and carrying out the correction of the multi-baseline InSAR residual phase error. The function of improving the phase error accuracy and the correction speed of the multi-baseline InSAR is achieved. According to the method, the correction precision of the interference phase of the multi-baseline InSAR after flat ground removal is improved, the phase error correction precision under the condition of small baselines is high, and the terrain reconstruction precision of the multi-baseline InSAR is high; and a reliable data basis is provided for accurate reconstruction of the multi-baseline InSAR terrain. According to the method, the speed of the error phase correction process is high, and the consumption of computing resources and the hardware cost of the system are reduced.

The invention discloses a grooving positioning system based on a paperboard digital intelligent grooving machine, relates to the technical field of grooving machine positioning adjustment, and solves the technical problems of insufficient transverse deviation adjustment precision and incomplete longitudinal deviation compensation. Proportional, integral and differential parameters of the incremental PID are dynamically adapted according to the deviation, compared with a fixed parameter PID, the adjustment response time is shortened, the overshoot is controlled within + / -0.01 mm, the transverse positioning precision is improved, and the high-precision grooving requirement is met. A total error model of a linear error and a periodic error is established through a laser interferometer for encoder error calibration. And in combination with a PLC position-compensation amount comparison table, encoder positioning errors are reduced, dynamic environment compensation fits a paperboard stretching model through a humidity sensor, an equipment thermal deformation model is established through a temperature sensor, temperature and humidity influences are comprehensively compensated, and the longitudinal positioning precision fluctuation range is narrowed.

The invention provides an acquired data error compensation method for a small-sized thermohaline instrument, belongs to the technical field of electrical digital data processing, and realizes accurate error compensation by constructing a multi-stage neural network tree structure. According to the method, firstly, errors are classified into system errors, random errors and environment interference errors, and second-level and third-level subdivision is carried out to form a complete error classification system; based on the classification system, an optimal path selection function is adopted to dynamically determine a compensation strategy, and corresponding models are selected from a pre-trained miniature neural network library to form a compensation chain. All compensation model structures are subjected to optimization design, different network structures and parameter configurations are adopted for linear errors, nonlinear errors, noise errors, fluctuation errors, temperature errors and salinity mutual interference errors, the total parameter number is controlled to be at a low level, and efficient operation on small equipment is ensured. The technical problem that in the prior art, a small-sized salt thermometer is insufficient in measurement precision under the condition of low energy consumption is solved.

The invention discloses a clock synchronization frequency modulation continuous terahertz frequency sweep source nonlinear error elimination system, which comprises two clock synchronization receiving and transmitting heterogenous frequency modulation continuous terahertz system error elimination architecture designs, and realizes reference signal generation by using double-source frequency mixing and single-source difference frequency respectively. The two architectures both select 10MHz as the frequency of a reference signal and an intermediate frequency signal, adopt the same 100MHz constant-temperature crystal oscillator as a reference clock of the frequency-modulated continuous wave frequency source, and provide local oscillators for the reference signal and the intermediate frequency signal; and the intermediate frequency signal and the reference signal are subjected to frequency mixing, so that the obtained difference frequency signal has the characteristic that a clock synchronization error, a modulation nonlinear error and the like are eliminated, and the difference frequency signal can be used for terahertz in-situ nondestructive testing and imaging after IQ demodulation. The invention provides an implementation method for a low-frequency aperiodic intermediate-frequency time domain signal required by a frequency spectrum type terahertz in-situ nondestructive testing and imaging technology.

The invention discloses a super-large-scale in-memory computing core circuit for solving an IR-Drop problem, belongs to the field of microelectronic technology and artificial intelligence, and determines that precision reduction caused by line resistance is an approximately linear error by analyzing an intrinsic physical equation of a line resistance network. Through the analysis of an approximate analysis formula, the linear error is only related to the parameters of the line resistance network. This means that different input voltage vectors produce an approximately linear error of the same column output current. Therefore, through collaborative design of devices, layout and circuits, line resistance of rows and columns is adjusted so as to maximize linearization of errors, and the errors are eliminated through adjacent differential pair read-out design and sampling resistance trimming; meanwhile, a fully differential ADC is designed by combining an adjacent differential readout circuit, and isolation sampling of current and error compensation of line resistance are achieved.

The invention discloses a nano-scale displacement real-time compensation measurement method and system based on double-frequency laser interference, and belongs to the technical field of precision measurement. In order to solve the problems that three error sources of environmental drift, periodic nonlinear error and dynamic vibration are mutually coupled and have high real-time requirements in dual-frequency laser interference measurement, a multi-source error unified state space model including measured displacement, an air refractive index parameter, a nonlinear error parameter and a vibration disturbance quantity is constructed. A high-dimensional state vector is divided into a displacement-refractive index group and a nonlinear parameter group by adopting an extended Kalman filter of a grouping updating strategy, the displacement-refractive index group and the nonlinear parameter group are alternately updated in an assembly line parallel mode, nonlinear parameters are identified in real time in combination with an online recursive least square algorithm, and the state of the filter is corrected through a state coupling injection mechanism. Real-time compensation with the end-to-end delay smaller than 80 microseconds is achieved, the displacement measurement residual error is controlled within + / -0.3 nm under the composite disturbance condition, and the method is suitable for precise assembly of intelligent glasses optical assemblies.

The invention belongs to the field of electric energy meters, particularly relates to an automatic compensation calibration method for electric energy metering errors of an electric energy meter, and aims to solve the technical problems that a CORDIC algorithm is difficult to give consideration to efficiency and precision and an existing compensation method is difficult to correct multi-dimensional nonlinear errors under wide temperature and wide flow. Outputting an uncorrected x-axis component and a final accumulated phase angle, wherein the improved CORDIC iterative operation comprises M times of coarse rotation iteration and P times of fine rotation iteration; s2, performing amplitude correction on the uncorrected x-axis component to obtain a corrected instantaneous current amplitude; and S3, performing reconstruction by using the corrected instantaneous current amplitude and the final accumulated phase angle to obtain a corrected instantaneous current value, multiplying the corrected instantaneous current value by the instantaneous voltage value to obtain instantaneous active power, and performing accumulated integration on the instantaneous active power to obtain a compensated and calibrated electric energy value. According to the invention, high-precision metering performance of the electric energy meter in a wide current range and a wide temperature change range can be ensured.

The invention belongs to the technical field of unit valve monitoring optimization, and discloses a unit valve flow monitoring optimization method and system based on data mining, and the method comprises the steps: obtaining the operation data in the operation process of a unit valve, constructing a flow model based on the structural characteristics of the valve and the flow state of fluid, and carrying out the recognition of the flow state of the fluid based on a characteristic through-flow area recognition method; analyzing the linearity of the flow in the valve; based on a data mining clustering algorithm, performing data extraction on a linearity analysis result, and clustering valve flow characteristics according to different modes; a valve flow characteristic curve is divided into a plurality of sections, independent linearity optimization is carried out on each section, the linear error of each section is analyzed, and a key area of valve performance optimization is identified. According to the method, the flow model is accurately constructed by combining the structural characteristics of the valve and the flow state of the fluid, and the linearity of the flow is analyzed by adopting a characteristic through-flow area identification method, so that the precision and the response capability in the valve adjusting process are effectively improved.

The invention discloses an error compensation method of an analog-to-digital converter, a digital device and a controller, and the method comprises the steps: obtaining a to-be-compensated digital quantity and two reference digital quantities, the to-be-compensated digital quantity is obtained through the conversion of an analog signal through the analog-to-digital converter, and the reference digital quantities are obtained through the conversion of a reference signal through the analog-to-digital converter; obtaining a linear error based on the plurality of sampling values of each reference digital quantity under the condition that the reference digital quantity is within a preset effective range; and compensating the digital quantity to be compensated according to the linear error to obtain a compensated digital quantity. According to the invention, the accuracy in the ADC analog-to-digital conversion process can be effectively improved.

The present invention relates to an orthogonal correction network, method and device for an angle sensor. The correction network includes: a first bypass correction network for providing a first preset correction value and a second bypass correction network for providing a second preset correction value; a first multiplier for performing a multiplication operation on a detection value of a first axis of a misaligned orthogonal coordinate and the first preset correction value to obtain a first coordinate correction detection value; a second multiplier for performing a multiplication operation on the detection value of the first axis and the second preset correction value to obtain an intermediate correction value; and an adder for performing an addition operation on a detection value of a second axis and the intermediate correction value to obtain a second coordinate correction detection value. The correction network of the present invention can completely eliminate the non-orthogonal distortion caused by a non-orthogonal sensing element array, and only two multipliers and one adder are provided, with a simple structure, small calculation amount and easy implementation. In addition, the method and device can be applied to multiple groups of sensing elements, and stable angle detection can be realized through model and coordinate conversion to eliminate non-linear errors.

The invention provides an angle calculation method and system based on a triaxial accelerometer, and relates to the technical field of inertial navigation, and the method comprises the steps: obtaining an acceleration signal and preprocessing the acceleration signal to obtain an effective acceleration component, constructing a nonlinear error feature vector, carrying out the real-time parameter identification through a recursive least square method, and building a nonlinear error compensation model. And performing dynamic correction by adopting a self-adaptive sliding time window, and finally calculating a pitch angle and a roll angle. The non-linear error of the accelerometer can be effectively inhibited, the angle calculation precision is improved, and the method has the characteristics of good real-time performance and strong adaptability.

The invention provides an exposure apparatus, an exposure method, and an alignment method. In an exposure device provided with a stage or the like, proper alignment is performed in consideration of a linear error generated along with movement of the stage. An exposure device (10) is provided with a pair of calibration scales (62, 64) on which reference marks (CM) facing each other in an X direction (main scanning direction) are disposed, and the reference marks (CM) facing each other are imaged by an alignment camera (80) while a stage (50) moves. The amount of linear error in the amount of movement of the stage (50) is detected on the basis of the amount of misalignment of the reference mark (CM) in the captured image. Then, scale correction processing is performed on the exposure data in accordance with the calculated linear error amount.

The invention discloses a millimeter wave beam tracking method, a computer readable storage medium and node equipment, and belongs to the technical field of wireless communication, and the method comprises the steps: constructing a beam pointing error interval at an initial moment; at the next moment, predicting the interval through a state transition equation; acquiring a channel observation value under the current beam pointing based on a channel model; carrying out shrinkage processing on the predicted error interval; and estimating a beam pointing angle according to the contracted interval, and transmitting the interval as priori information to the next moment so as to repeat the steps. A computer program for executing the method is stored in the computer readable storage medium. The node equipment comprises at least one processor, a memory and a bus, wherein the memory stores a program for executing the method. According to the method, the tracking performance in a nonlinear and non-Gaussian scene can be kept under the condition that the calculation load is not increased, and the method is suitable for the conditions of uncertain and incomplete channel state information introduced by multipath, analog-to-digital conversion quantization, hardware nonlinear errors and the like.

The invention discloses an aperture error and non-linear cooperative calibration circuit and method for a pipeline ADC, and relates to the technical field of mixed signal integrated circuits, the circuit comprises a pipeline ADC basic circuit and a calibration circuit integrated with the pipeline ADC basic circuit, and the calibration circuit comprises an aperture error calibration module and a non-linear error calibration module. And the aperture error calibration module dynamically adjusts the sampling clock phase of the first-stage Sub-ADC by counting a post-stage output code value histogram and combining an SAR logic feedback mechanism so as to compensate the sampling moment deviation between the first-stage Sub-ADC and the MDAC. The nonlinear error calibration module extracts errors by injecting pseudo-random jitter and utilizing double-threshold window crossing statistics, and after EWMA smooth filtering is carried out, a polynomial compensation coefficient is updated in a self-adaptive mode through an LMS algorithm, and harmonic distortion is restrained. According to the method, the linearity under high-speed and high-bandwidth application is remarkably improved, and the method has good robustness for PVT fluctuation.

The present application discloses a torque correction method, a torque correction device, a robot, and a storage medium. The torque correction method includes: obtaining a zero-bias error of a torque sensor; collecting a sampled voltage of the torque sensor under an external force using a sampling module; calculating a first torque based on the bias voltage, amplification factor, sensitivity, range, and sampling voltage of the sampling module; correcting the first torque based on the zero-bias error to obtain a second torque; determining a target correction coefficient of the torque sensor based on the second torque; and correcting the second torque based on the target correction coefficient to obtain a third torque. This method implements linear error correction of the first torque based on zero-bias correction of the first torque collected by the torque sensor, thereby improving the measurement accuracy of the torque measured by the torque sensor.

This invention provides a rapid detection method for critical linear errors of linear axes in CNC machine tools. The method is used to solve for critical linear errors of linear axes in CNC machine tools, including positioning errors and straightness errors. Based on the measurement function of a ballbar, this method ignores angular errors and does not consider the influence of other errors. Detection is performed under two designed circular trajectories. The critical linear errors are expressed and fitted using polynomials, and the coefficients are solved using the least squares method. This method can effectively and quickly obtain the positioning and straightness errors of the linear axis, which is of great significance for improving machine tool accuracy and increasing production efficiency.