47 results about "Homogeneous transformation matrix" patented technology

The invention discloses a time-varying precision customized fine self-healing method based on virtual-real homeomorphic evolution, and relates to the technical field of machine tool precision control, and the method comprises the steps: constructing a homogeneous transformation matrix according to the position relation of all parts of a machine tool, and obtaining an error unified mathematical model based on a small error theory; then, a measuring device is used for obtaining small errors of movement and rotation angles and reverse clearance errors of a translation shaft; and then constructing a virtual-real homeomorphic digital twin platform, and integrating the model and the error to realize virtual-real error homeomorphic evolution. Acquiring real-time sensing data, predicting and evaluating precision time variation in combination with a time sequence, and driving virtual-real synchronous evolution to generate a self-healing path; finally, positioning deviation is determined according to path start and end error changes and an error model, and the path is transmitted when a preset value is exceeded; and the time delay defect of traditional real-time compensation is relieved through advanced prediction / deduction. According to the method, unified error modeling of the multi-axis machine tool is achieved, the defect of reverse gap neglect is overcome, errors caused by compensation lag and blind compensation are solved, and the machining precision is guaranteed.

The invention discloses a transient signal detection and sorting method based on time-frequency image deep learning, and relates to the technical field of signal sorting. Based on a hypergraph model and core polymorphic sites, the hypergraph model is divided into a plurality of independent substructures by analyzing the distribution characteristics of hyperedge dynamic weights, independent modal analysis is performed on each substructure, and a transient signal detection and sorting result is obtained. Extracting a time-frequency distortion coefficient matrix and an interference response mode matrix; inputting the multi-modal data into a multi-modal network to generate a homogeneous transformation matrix; and based on the homogeneous transformation matrix, deriving attitude error parameters and translation error parameters, feeding back the attitude error parameters and the translation error parameters to a feature input layer and a decision layer of the multi-modal deep learning detection and sorting model, completing dynamic correction of model parameters, and detecting and sorting real-time signals again after model correction. According to the sorting method, the detection rate and sorting accuracy of transient signals are remarkably improved in real-time processing, and meanwhile, the false alarm and leak detection risks are reduced.

The application discloses a kind of wind turbine single blade installation process dynamic response analysis methods considering wind load action, comprising: according to the wind turbine blade installed and construction sea area, establish blade airfoil database and turbulent wind field database;When the position of lifting point and the position of tappet vertex are described, homogeneous transformation matrix is used to describe the motion of each mechanism of ship-mounted crane;When the position of lifting point is described, the position of tappet vertex is described, and the position of blade centroid in space is described by lifting point position, sling length and generalized coordinate;Wind load at each time point in the process of blade installation is obtained;The sling tension in the process of blade installation is obtained;The dynamics model of single blade installation system is established by using Lagrange method;The method can accurately analyze the coupling motion response between crane ship, ship-mounted crane, sling and blade in the installation process, and simultaneously by selecting generalized coordinate and modeling and analyzing the system based on energy method, the system modeling efficiency is effectively improved.

The invention discloses a five-axis numerical control machine tool machining error on-line compensation system based on deep learning, relates to the technical field of machine tool error compensation, and solves the problems that position correction difference is caused by neglecting a complex coupling relation between rotating shafts and linear shafts of different types of machine tools, and the error compensation accuracy is high. And deep learning models for machine tools with different requirement types are not designed, so that the model prediction precision is influenced. Determining the coupling relation of each axis error through the HTM homogeneous transformation matrix of the machine tool kinematic chain; aiming at kinematic chain structure differences of different types of machine tools, a differential correction strategy is designed. And constructing a zero drift time sequence model in combination with a historical drift trend term and a random error term predicted by the LSTM. Geometric error terms strongly related to machining errors are screened through grey correlation analysis, then the weight of the geometric error terms is quantified through random forest, the accuracy of key error recognition through a combinatorial algorithm is improved, and the model prediction precision is improved by training fusion models for machine tools with different requirement types.

A kinematics solving method of a cantilever type crushing device, comprising: establishing a link coordinate system of a three-link robot and a homogeneous transformation matrix of an end effector according to obtained DH parameters, and obtaining robot conversion equation sets according to link lengths of a boom, a stick and the end effector and motion pairs of each part; reading current driving space coordinates from displacement sensors of hydraulic cylinders; calculating current pose space coordinates by using the robot conversion equation sets, the link constraint equation sets and the current driving space coordinates; obtaining target pose space coordinates generated after the crushing device is moved to a target working position on the basis of the current pose space coordinates; and solving target driving space coordinates by using the robot conversion equation sets, the link constraint equation sets, the current and target pose space coordinates. The scheme can improve the control precision and motion rate of the cantilever type crushing device, and make the cantilever type crushing device motion more flexible.

This invention discloses a comprehensive error decoupling compensation method for a five-axis CNC polishing machine, comprising: 1. establishing homogeneous transformation matrices for the workpiece kinematic chain and tool kinematic chain of the five-axis polishing machine under ideal and error conditions; 2. establishing a comprehensive error transformation matrix between the coordinate systems of each kinematic pair of the five-axis polishing machine based on the homogeneous transformation matrix; 3. spatially decoupling the comprehensive error transformation matrix of the five-axis polishing machine based on the small error compensation motion assumption, and establishing a comprehensive error compensation model for the five-axis polishing machine to achieve comprehensive error compensation. This invention, through kinematic analysis of a five-axis polishing machine, uses the homogeneous coordinate transformation method to establish a comprehensive error transformation matrix between the coordinate systems of each kinematic pair of the machine tool, spatially decoupling the position and direction error compensation of each motion axis of the five-axis polishing machine, and establishing a comprehensive error compensation model for the five-axis polishing machine, providing a theoretical basis for real-time comprehensive error compensation of a five-axis CNC polishing machine.

The invention discloses a heavy-load high-precision mobile positioning robot, which is characterized in that a plane adjusting module is a 3-PRR parallel mechanism, has three degrees of freedom of X-direction translation, Y-direction translation and rotation around Z, and provides unconstrained vertical support and transverse guidance through a plurality of groups of bull eye bearings, a vision measurement module adopts a monocular vision measurement technology, and the measurement precision is high. And a hand-eye calibration matrix is combined to solve a pose error, accurate coupling with the 3-PRR parallel mechanism is realized, and pose deviation information is fed back to the 3-PRR parallel mechanism to complete accurate pose compensation. According to the method, a homogeneous transformation matrix of a camera coordinate system and a 3-PRR parallel mechanism static platform coordinate system is introduced, a quantized pose transformation relation is established, accurate calculation and compensation of AGV pose deviation are achieved, meanwhile, the standardized detection step of positioning precision is added, the compensation precision is quantitatively detected through a laser tracker, and the accuracy of AGV pose deviation is improved. And a theoretical basis and a quantitative index are provided for positioning precision verification.

The invention provides a synchronous control method for an underwater contact detection robot, and the method comprises the steps: constructing a first kinematical equation based on the multi-dimensional speed and pose of the robot, constructing a second kinematical equation based on the joint parameters of the mechanical arm and a homogeneous transformation matrix between the adjacent joints, and constructing a synchronous control system for the underwater contact detection robot. Fusing the first kinematic equation and the second kinematic equation to form an overall motion model; constructing a third-order time polynomial based on path boundary conditions of the end effector, and determining an end track of the end effector; and an inverse kinematics solving function containing a minimum norm item and a null space item is constructed through the overall Jacobian matrix, the inverse kinematics solving function is solved, and the moving speed and the joint angle of the robot at any moment are determined. According to the method, the robot and the mechanical arm can be synchronously controlled, and multi-target motion planning of joint limit obstacle avoidance and stable robot posture is considered while the precision of the end effector is ensured.

The application discloses a method for establishing and detecting a quick arbitrary shape bounding box of a mechanical arm and relates to the field of collision detection of the mechanical arm. The method comprises the following steps: obtaining an i-th coordinate system of an i-th rod in the mechanical arm, calculating a first homogeneous transformation matrix of two adjacent coordinate systems; calculating a second homogeneous transformation matrix between the coordinate system and a base coordinate system; calculating an origin of the i-th rod and obtaining orthogonal direction vectors of three axes in the coordinate system of the i-th rod; the i-th rod in the mechanical arm has n end points, the maximum distance in all distances of the n end points in the positive and negative directions of the orthogonal direction vectors is obtained; a first bounding box is obtained based on the maximum distance and the origin; when the mechanical arm moves, an updated second bounding box is obtained based on the second homogeneous transformation matrix and a homogeneous transformation matrix between the base coordinate system and a world coordinate system, and the application further discloses a collision detection method based on the updated bounding box, which greatly improves the calculation efficiency and meets the high-frequency real-time requirement.

The present invention makes it possible to obtain a highly accurate PET image in PET inspection without fixing a subject and while reducing a calculation cost. This image configuration device 1 acquires measurement data measured by a PET device 2 in time series, divides the measurement data into a plurality of frame data, generates an inverse-projection image from the frame data, generates a mask image in a frame by setting RoI by using segmentation from the inverse-projection image, derives the center of mass from the mask image, derives a main component vector of an inertia matrix obtained from the center of mass, configures a homogeneous transformation matrix composed of the center of mass and a rotation matrix, calculates the amount of change between the homogeneous transformation matrix in an initial frame and the homogeneous transformation matrix in an nth frame, and corrects a rotation matrix serving as a main component vector column component in accordance with continuity of motion so that the amount of change is minimized.

This invention discloses a spatiotemporal synchronous high-precision positioning method and system based on multi-sensor fusion, belonging to the field of positioning technology. The method includes the following steps: Step 1: Acquiring images from a visible light camera, a 3D point cloud coordinate image from a ToF depth camera, angular velocity and acceleration from an inertial measurement unit, and wireless signal strength from a wireless signal module; Step 2: Based on a pre-calibrated homogeneous transformation matrix, reprojecting the 3D point cloud coordinate image acquired by the ToF depth camera onto the image plane of the visible light camera to obtain spatially aligned coordinates; Step 3: Based on the signal strength indication received by the wireless signal module, calculating and correcting the distance observation value using a nonlinear ranging model to obtain the corrected distance observation value. This invention effectively solves the inherent defects of single-sensor positioning in complex environments through a complete spatiotemporal synchronization and multimodal data fusion framework.

The invention discloses a robot control method and device, electronic equipment and a storage medium, and the method comprises the steps: firstly building a reference workpiece coordinate system, and determining a first homogeneous transformation matrix of the reference workpiece coordinate system relative to a robot base coordinate system; based on the first homogeneous transformation matrix, determining a second homogeneous transformation matrix representing pose transformation of the current workpiece relative to the reference workpiece coordinate system; and finally, controlling the robot to move according to the target movement track under the robot base coordinate system. Determining a target motion track through a compensation coordinate system constructed by a first homogeneous transformation matrix and a second homogeneous transformation matrix representing pose transformation, and a reference motion track for a reference workpiece under a reference workpiece coordinate system, namely, performing overall coordinate system remapping on the original reference motion track through the compensation coordinate system, so as to obtain a target motion track; and pose compensation calculation does not need to be carried out on each motion point in the track independently, so that the real-time calculation burden is remarkably reduced, and the response speed and the operation efficiency of the system are improved.

A kind of fast hand-eye calibration method about multi-camera cooperative positioning, comprising: 1, mobile robot end three times and more, after each movement, detect calibration pattern with the same camera, record the position and pose of calibration pattern relative to camera after each movement and the position and pose of robot end relative to base;2, calculate the homogeneous transformation matrix of robot end relative to base coordinate system after each movement and the homogeneous transformation matrix of camera coordinate system relative to calibration pattern coordinate system after each movement;3, calculate the homogeneous transformation matrix of calibration pattern coordinate system relative to robot end coordinate system;4, calculate the homogeneous transformation matrix of each camera coordinate system relative to base coordinate system;5, calculate the final target point in base under the coordinates of multiple cameras, obtain the accurate position of target point, complete the position calibration of robot and multi-camera coordination.The present application has rapidity when carrying out robot hand-eye calibration task, and can significantly improve calibration efficiency.

The application belongs to the technical field of three-dimensional modeling, and particularly relates to a three-dimensional scanning modeling method based on kinematics cooperation and sub-group fuzzy ant colony, which comprises the following steps: based on the kinematics theory of multi-body system, a global coordinate system of a scanning system and a homogeneous transformation matrix of each motion axis are established; a depth-of-field constraint is constructed; for a workpiece to be measured, a dynamic edge profile of the workpiece is acquired through the scanning system, a rough visual shell model of the workpiece is constructed, the normal vector distribution of each point on the surface of the workpiece is calculated, and a probe task set is distributed; the probe task set is split into discrete scanning task strips and solved; according to the optimal scanning task strip sequence obtained by solving, the scanning system is used to collect data of the workpiece; an adaptive sampling strategy based on a dynamic chord height error is used for point cloud gridding processing, a bidirectional curve fitting method is used to generate a NURBS surface, and a three-dimensional model of the workpiece is output. The application can realize full-automatic and high-precision digital reconstruction of a complex surface.

The present application relates to the technical field of remote sensing, in particular to a forest point cloud registration method based on trunk position iteration. The present application makes full use of the natural complementarity of ULS and BLS data in obtaining vertical structure information of forest, converts the traditional discrete point set matching problem into the overlap optimization problem of continuous two-dimensional spatial distribution influence map; by introducing genetic algorithm to construct the spatial mapping relationship between non-homologous data and carry out global optimization, the interference of the horizontal offset of crown and trunk commonly existing in broad-leaved forest on the registration accuracy is fundamentally avoided. The present application can automatically obtain the global optimal solution and generate the homogeneous transformation matrix without laying artificial targets, finally realizes the high-precision rigid alignment of two sets of point clouds, has the advantages of high automation, strong noise-robustness and insensitivity to initial error, and can be widely applied in the fields of high-precision forest resource inventory, digital forestry construction and ecological environment monitoring.

This invention discloses a method for aligning the axis and spline during the flexible assembly process of a parallel platform. The method includes the following steps: S1, using a target ball to calibrate the end face of the low-voltage turbine shaft tooling and the end face of the compartment tooling to determine the reference coordinates of the end face of the low-voltage turbine shaft tooling and the end face of the compartment tooling; S2, establishing a predetermined distance between the bottom of the low-voltage turbine shaft and the top of the compartment, and using this position as the reference position; S3, using a laser tracker to measure the position of each target point at the reference position, moving the parallel platform to obtain the positions of the end face of the low-voltage turbine shaft tooling and the end face of the compartment tooling; establishing a low-voltage turbine shaft coordinate system {D} and a compartment coordinate system {C}; S4, correcting based on the actual measurement results to obtain the homogeneous transformation matrix between the low-voltage turbine shaft coordinate system {D} and the compartment coordinate system {C}, and adjusting the compartment axis according to the homogeneous transformation matrix; S5, using impedance control during the contact between the spline and the spline groove, rotating the compartment to align the spline inside the engine with the spline groove at the end of the low-voltage turbine shaft.

This invention discloses a combined measurement method consisting of a laser tracker and a binocular camera. The laser tracker measures the spatial coordinates of multiple target spheres, whose spatial distribution configurations have different lengths along all three axes. The coordinates of the measurement points are fitted into a spatial rectangular coordinate system to obtain the target sphere tool coordinate system. Coordinate axes with different directional accuracies are determined sequentially, with the X-axis representing the axis of highest accuracy. The homogeneous transformation matrix of the coordinate system is determined. A combined measurement system consisting of the laser tracker and the binocular camera is established, and error compensation is used within the combined measurement system to improve the overall system error and enhance the measurement system's accuracy. This improves the numerical stability of the coordinate system fitting, reducing uncertainty in the error aggregation stage from the source; it suppresses the leverage amplification effect of error in specific directions, controlling the growth trend of error during transmission. The two methods work together to achieve systematic suppression of error transmission throughout the entire process.

This application discloses a method, device, equipment, medium, and product for deformation monitoring of linear engineering components, relating to the field of equipment monitoring technology. The method includes acquiring the included angle between two planes collected by a displacement data measuring device; converting the two plane angles into a central angle and a direction angle in a three-dimensional spatial coordinate system; constructing a homogeneous transformation matrix for flexible segments using the central angle and direction angle of each flexible segment and the length of the flexible segment in the three-dimensional spatial coordinate system, and constructing a homogeneous transformation matrix for rigid segments using a fixed length; sequentially performing chain multiplication on the homogeneous transformation matrices of the flexible and rigid segments in a global coordinate system, and obtaining a spatial position model of each monitoring point in the global coordinate system through segment-by-segment coordinate recursion; and monitoring the displacement deformation of the linear engineering component based on the spatial position model of each monitoring point in the global coordinate system to obtain the monitoring results. This application can provide accurate and reliable data support for the maintenance of linear engineering components.

A method and system for precise spatial correction of rigid digital twins in power distribution networks based on point cloud mapping is proposed. This method accurately extracts the pose parameters of physical entities using RANSAC robust segmentation and least-squares refinement. From 3D point cloud data, the six-degree-of-freedom pose parameters (Pose_physical) of rigid equipment in the physical world are calculated. Digital twin inaccuracy diagnosis is performed based on six-degree-of-freedom deviation decomposition and safety regulations. The perceived "true value" from the physical world is compared with the "theoretical value" in the digital twin world to quantify spatial deviation and perform automated decision-making. Closed-loop correction of the digital twin model is achieved based on a homogeneous transformation matrix. The diagnosed deviation information is transformed into a mathematical transformation operator, which is then used for pose update, ultimately forming a closed loop. Through an integrated and automated process, precise perception of physical entities, inaccuracy diagnosis of the twin model, and full-process model correction are realized.

The invention provides a robot FKM kinematics modeling method, and aims to solve the problems of rotation and translation coupling, non-intuitive parameter significance, complex modeling and the like in the existing robot kinematics modeling process. The method comprises the following steps: establishing a joint coordinate system of the robot, and determining a transformation parameter of each joint and a homogeneous transformation matrix of an adjacent coordinate system; wherein the expression of the homogeneous transformation matrix has two forms according to different joint types, and the expression of a rotating joint is as shown in the specification, and the expression of a moving joint is as shown in the specification. A translation transformation matrix of the coordinate system relative to the coordinate system is in the formula; the rotation transformation matrix is a rotation transformation matrix rotating around the translated X axis; the forward kinematics model of the robot can be obtained by sequentially multiplying the homogeneous transformation matrixes of all the joints for the rotating joints as a rotation transformation matrix rotating around the rotated Z axis and for the moving joints as a translation matrix moving along the rotated Z axis. According to the method, basic transformation and joint variables of the coordinate system are decoupled, so that the modeling process is more visual, the parameter significance is clearer, and the method can be widely applied to the field of kinematics modeling and control of industrial robots and service robots.

The invention relates to the technical field of image processing, and particularly discloses a charging cover pose detection method based on machine vision and a storage medium, and the method comprises the steps: employing a monocular camera to respectively shoot pictures of a charging cover which is not marked with laser rays and a charging cover which is marked with laser rays, and recording the pictures as a first image and a second image; extracting laser rays according to the first image and the second image, and extracting at least three edge feature points of the charging cover from the laser rays; calculating a feature point cloud according to each edge feature point; matching the feature point cloud with a pre-obtained target point cloud to obtain a corresponding homogeneous transformation matrix; and determining pose parameters of the charging cover according to the homogeneous transformation matrix. According to the invention, active detection of the pose of the charging cover is realized by adopting a monocular camera and laser line marking mode, and meanwhile, the method has the core advantages of low cost, low hardware complexity and ambient light interference resistance.

The application discloses a control method and system for coking removal operation of a waste incinerator hearth, and relates to the technical field of waste incinerators. In the process of hoisting a frame into a waste incinerator, data of a laser ranging sensor and an inclination sensor are collected, height deviation data Δh measured by the laser ranging sensor and inclination sensor measured by the inclination sensor are obtained, and the height and posture of the hoisting frame inside the hearth are obtained. The height and posture of the hoisting frame are adjusted by controlling the lifting motor and the lifting mechanism arranged on the four corners of the hoisting frame. The technical advantage of the application is that a homogeneous transformation matrix of a mechanical hand space coordinate system relative to a hearth space coordinate system is established, so that the relationship between the target pose matrix of the crushing assembly in the hearth space coordinate system and the relative pose matrix of the mechanical hand end tool in the mechanical hand space coordinate system is obtained, the accurate motion amount of each motor is derived, and the coking removal efficiency and quality are ensured.

This invention relates to the field of solar power generation technology, and particularly to a control method for a dish concentrator based on an I3-RPS tracking mechanism. The control method includes: establishing a solar direction vector calculation model; establishing a multi-coordinate system to describe the motion of the dish concentrator, and deriving the homogeneous transformation matrix between the coordinate systems; obtaining the pose of the moving platform based on the solar direction vector, and establishing a mapping relationship between the length, velocity, and acceleration of the telescopic rod and the pose of the moving platform through inverse kinematics; establishing an inverse dynamics model based on the principle of virtual work; designing a hierarchical composite control strategy; at the top level, using a parallel synchronous architecture to coordinate the motion of the I3-RPS tracking mechanism; at the bottom level, designing an RBF-FSMC controller for the I3-RPS tracking mechanism, replacing the switching function with a saturation function, dynamically adjusting the saturation function gain and boundary layer thickness through fuzzy rules, and introducing a radial basis function neural network to approximate system modeling errors and external disturbances online. This control method exhibits high tracking accuracy and strong anti-interference capability.

The application discloses a positioning accuracy reliability-based industrial robot tolerance design method and system, and the method comprises the following steps: performing differential transformation processing on a homogeneous transformation matrix of an industrial robot connecting rod coordinate system, and constructing a positioning accuracy limit state function; establishing an inner and outer test table for industrial robot tolerance design; calculating the failure probability of the positioning accuracy of the industrial robot according to the inner and outer test table and the positioning accuracy limit state function; and sorting the importance of the kinematic parameter tolerance according to a signal-to-noise ratio calculation formula and the positioning accuracy failure probability, and guiding the design of the kinematic parameter tolerance scheme of the industrial robot. Through the use of the application, the kinematic parameter tolerance of each component of the industrial robot can be tightened and loosened, and the positioning accuracy of the industrial robot can be effectively improved under the same production conditions. The application can be widely applied to the technical field of industrial robot tolerance design as a positioning accuracy reliability-based industrial robot tolerance design method and system.

This invention provides a method and system for monitoring the deformation of slender marine structures, belonging to the field of marine engineering structure monitoring technology based on computer data processing. The invention first acquires measured strain using sparsely arranged sensors, and then generates a continuous curvature vector field that allows for stiffness steps through cross-sectional equivalent mapping and physical piecewise interpolation. Subsequently, based on the piecewise constant curvature theory, the structure is discretized, and the local geometric features of the infinitesimal elements are extracted and analyzed using a three-dimensional special Euclidean group. SE (3) Construct a local homogeneous transformation matrix in space; finally, combine the chain rule to recursively deduce the global pose and reconstruct the three-dimensional large deformation curve. This invention avoids the cumbersome modal parameter identification, strictly decouples spatial bending deformation, eliminates the geometric nonlinearity accumulation error caused by plane integration from the bottom layer, and breaks through the high-fidelity monitoring limitation of complex and slender marine structures such as variable cross-section towers and irregular blades with extremely low sensing cost.

A programmable RCM motion precision measurement method, the programmable RCM motion implementation device includes a surgical mechanical arm and an end effector mounted on the surgical mechanical arm; the end effector is used for carrying a surgical tool and providing operating power; a measuring device includes a binocular camera and a visual auxiliary marker point, and is used for collecting a homogeneous transformation matrix between the end effector and the binocular camera. The programmable RCM motion precision measurement method of the present application obtains the precision of the RCM point and the RCM constrained motion through optimal calculation by collecting the homogeneous transformation matrix of the marker coordinate system fixedly connected with the end effector relative to the camera coordinate system. The method of the present application provides an important evaluation basis for evaluating the programmable RCM motion algorithm.

The application discloses a time-varying precision customized fine self-recovery method based on virtual-real isomorphism evolution, relates to the technical field of machine tool precision control, and comprises the following steps: firstly, according to the positional relationship of each component of a machine tool, a homogeneous transformation matrix is constructed, and a unified mathematical model of errors is obtained based on a small error theory; secondly, a measuring device is used to obtain small errors of movement and rotation angle and reverse gap error of a translational axis; then, a virtual-real isomorphism digital twin platform is constructed, and a model and errors are integrated to realize virtual-real error isomorphism evolution; real-time sensing data is acquired, time series prediction is combined to evaluate precision time variation, a self-recovery path is generated by driving virtual-real synchronous evolution; finally, positioning deviation is determined according to error variation at the beginning and end of the path and the error model, and the path is transmitted when the error exceeds a preset value; in addition, the time lag defect of traditional real-time compensation is relieved through advanced prediction / deduction. The method realizes unified error modeling of a multi-axis machine tool, makes up for the defect of ignoring reverse gap, solves errors caused by compensation lag and blind compensation, and guarantees machining precision.