Method for evaluating the uncertainty of in-process measurement of tool geometry parameters

Abstract

The application discloses a kind of cutter geometric parameter on-machine measurement uncertainty evaluation method, is built on-machine non-contact measurement system on five-axis numerical control tool grinder, realizes the efficient scanning of cutter geometric parameter by the linkage control of each axis;Then, adopt cylinder as standard piece to the pose of line laser sensor is calibrated, to ensure the reliability of measurement data;Finally, according to GUM standard, the main influencing factors of on-machine non-contact measurement system uncertainty, including repeatability error, workpiece installation error, calibration error and sensor resolution error are quantitatively analyzed, the combined standard uncertainty of measurement system is calculated, to establish the complete measurement uncertainty evaluation system.The method of the application can provide reliable guarantee for high-precision measurement of cutter geometric parameters, and provide quantitative basis for error traceability and system optimization, which has important theoretical significance and practical application value.

Description

Technical Field

[0001] This invention belongs to the field of measurement uncertainty assessment technology, specifically a method for assessing the uncertainty of in-machine measurement of tool geometric parameters. Background Technology

[0002] With the increasing demands for performance and reliability in high-end equipment in fields such as energy, automotive, and aerospace, the requirements for machining accuracy and surface quality of key components are also becoming increasingly stringent. As production tools for these critical components, complex cutting tools such as milling cutters, taps, and drills directly affect cutting performance and service life due to the precision of their numerous geometric parameters, thus impacting machining accuracy and production costs. Current research largely focuses on the structural optimization design of cutting tools, the development of cutting tool materials, and the rational selection of coatings. However, ensuring the precise and stable manufacturing of high-performance cutting tools with complex structural features remains a significant challenge that urgently needs to be addressed.

[0003] Tool geometry is typically a crucial consideration in the design process, directly impacting cutting efficiency, cutting quality, and tool life. However, due to installation deviations and manufacturing defects in machine tool motion axes, as well as machining errors during multi-axis simultaneous machining, tool errors are unavoidable. Traditional tool geometry measurement methods are mostly based on off-site contact measurements, which not only limit the measurable geometric parameters but also easily lead to secondary clamping errors, surface damage, changes in machining datum, and probe wear, failing to meet the demands for efficient, precise, and comprehensive tool parameter measurement.

[0004] To address this issue, in-machine non-contact scanning technology has been introduced into tool parameter measurement. It offers advantages such as high speed, high accuracy, and no need to disassemble the tool, enabling real-time measurement of tool geometry parameters directly on the machining equipment, thereby significantly improving production efficiency and reducing human error. Despite the significant advantages of non-contact measurement technology, the sources of uncertainty in its measurement results are complex and can be affected by environmental factors, equipment performance, clamping errors, and sensor calibration accuracy. Therefore, accurately assessing the uncertainty of in-machine non-contact measurement systems has become a key issue in ensuring the reliability of measurement results and improving manufacturing accuracy. Currently, most existing uncertainty assessment methods are designed for offline measurement systems or contact measurement equipment, lacking a systematic assessment method specifically for in-machine non-contact measurement systems. Summary of the Invention

[0005] In view of this, the purpose of this invention is to provide a method for evaluating the uncertainty of in-machine measurement of tool geometry parameters, which can provide a reliable guarantee for the high-precision measurement of tool geometry parameters and provide a quantitative basis for error tracing and system optimization.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A method for evaluating the uncertainty of in-machine measurement of tool geometry parameters includes the following steps:

[0008] Step 1: Setting up the machine-to-machine non-contact measurement system

[0009] A non-contact measurement system is built on a five-axis CNC machine tool. The cutting tool is mounted on the A-axis of the five-axis CNC machine tool, and a line laser sensor is mounted on the spindle of the five-axis CNC machine tool. The spindle is locked to prevent free rotation. The transmission chain path at the cutting tool end is: bed → Y-axis → C-axis → A-axis → cutting tool; the transmission chain path at the sensor end is: bed → Y-axis → X-axis → Z-axis → line laser sensor. The X-axis drives the line laser sensor for translational motion, and the A-axis drives the cutting tool for indexing or continuous rotational motion according to the tool's structural characteristics, thus performing non-contact measurement of the cutting tool.

[0010] Step 2: Sensor pose calibration

[0011] The pose of the line laser sensor relative to the Z-axis is calibrated to obtain the rotation matrix R and translation matrix T from the line laser sensor coordinate system to the Z-axis coordinate system;

[0012] Step 3: Evaluation of measurement uncertainty

[0013] The uncertainties in an in-machine non-contact measurement system include uncertainties u1 caused by measurement repeatability errors, u2 caused by workpiece installation errors, u3 caused by calibration errors, and u4 caused by sensor resolution; therefore, the combined standard uncertainty u is:

[0014]

[0015] Furthermore, in step two, the method for sensor pose calibration consists of the following steps:

[0016] 21) Obtain calibration data

[0017] Using a standard cylinder as a standard part, the standard part is mounted on the A-axis; the X-axis and Y-axis are controlled to move, so that the standard part is positioned in three or more different spatial positions; at each spatial position of the standard part, the cross-sectional contour data of the standard part is collected multiple times using a line laser sensor to obtain calibration data;

[0018] 22) Solve for the coordinates of the center of the cross section.

[0019] Due to installation errors, the intersection of the laser plane and the cylinder will form an elliptical cross section; the random sample consensus algorithm is used to fit the elliptical expression to obtain the coordinates of the cross section center;

[0020] 23) Establish coordinate transformation relationships

[0021] The transformation relationship between the line laser sensor coordinate system and the Z-axis coordinate system is expressed as follows:

[0022]

[0023] Where: (x si ,y si ,z si ) and (x zi ,y zi ,z zi () represents the coordinates of the center of the ellipse in the coordinate system of the online laser sensor and the coordinate system of the Z-axis, respectively;

[0024] 24) Solve for the rotation matrix R and the translation matrix T.

[0025] Furthermore, in step 24), the method for solving the rotation matrix R and the translation matrix T is as follows:

[0026] 241) Construct an antisymmetric matrix S consisting of three independent coefficients a, b, and c, and express the rotation matrix R as:

[0027] R = (I + S)(IS) -1

[0028] Where: I represents the identity matrix;

[0029] 242) Construct the i-th point pair using the coordinates of the ellipse center in the online laser sensor coordinate system and the Z-axis coordinate system for any i-th elliptical cross section; Substitute m pairs of point pairs into the transformation relationship between the online laser sensor coordinate system and the Z-axis coordinate system, and eliminate the translation matrix T by subtracting each pair to obtain a set of equations containing only coefficients a, b, and c; m is the number of calibration data.

[0030] 243) Solve for the coefficients a, b, and c using the least squares method to obtain the rotation matrix R;

[0031] 244) Substitute the obtained R back into the transformation relationship between the linear laser sensor coordinate system and the Z-axis coordinate system to calculate the translation matrix T.

[0032] Furthermore, in step three, the uncertainty u1 caused by repeatability error is:

[0033]

[0034] Wherein: S p is the assumed standard deviation of the measured parameter; m is the number of calibration data, i.e., the number of repeated measurements.

[0035] Furthermore, in step three, the uncertainty u2 caused by the workpiece installation error is:

[0036]

[0037] Where: e is the installation error; k2 is the error factor assuming the installation error follows a uniform distribution.

[0038] Furthermore, in step three, the method for solving the uncertainty u3 caused by the calibration error is as follows:

[0039] The uncertainty of each element of the rotation matrix R is given by the uncertainties u of a, b, and c. a u b and u c Characterized by the uncertainty propagation equation, it is expressed as:

[0040]

[0041] Where: f ij Let each element of the rotation matrix R be a function of parameters a, b, and c; r ij Let i be each element in the rotation matrix R; i and j represent the row and column, respectively.

[0042] The uncertainties u(t1), u(t2), and u(t3) of each element in the translation matrix T are expressed as:

[0043]

[0044] Where: m is the number of calibration data;

[0045] The coordinate uncertainty of each point in the tool coordinate system is approximately:

[0046]

[0047] The uncertainty u3 caused by calibration error is:

[0048]

[0049] Where: (x wi ,y wi ,z wi u(x) represents the coordinates of a point in the tool coordinate system; wi ), u(y) wi ) and u(z) wi ) represent the coordinate uncertainties of a point in the tool coordinate system on the X, Y, and Z axes, respectively; u(x zi ), u(y) zi ) and u(z) zi ) represent the coordinate uncertainties of a point in the Z-axis coordinate system on the X-axis, Y-axis, and Z-axis, respectively.

[0050] Furthermore, in step three, the uncertainty u4 caused by the sensor resolution is:

[0051]

[0052] Where: r x and r z represents the resolution of the line laser sensor in the X and Z axes, respectively; k4 is the resolution factor assuming the resolution follows a uniform distribution.

[0053] Furthermore, in step three, a confidence interval is introduced to obtain the expanded uncertainty:

[0054] U = k × u

[0055] Where: U is the expanded uncertainty; k is the confidence factor.

[0056] The beneficial effects of this invention are as follows:

[0057] The present invention discloses a method for evaluating the uncertainty of in-machine measurement of tool geometry parameters. An in-machine non-contact measurement system is built on a five-axis CNC tool grinder. Through the coordinated control of each axis, efficient scanning of tool geometry parameters is achieved. Then, a cylinder is used as a standard part to calibrate the pose of the line laser sensor to ensure the reliability of the measurement data. Finally, based on the "Guide to the expression of uncertainty in measurement (GUM)" standard, the main influencing factors of the uncertainty of the in-machine non-contact measurement system, including repeatability error, workpiece installation error, calibration error, and sensor resolution error, are quantitatively analyzed to calculate the combined standard uncertainty of the measurement system, thereby establishing a complete measurement uncertainty evaluation system. This invention provides a reliable guarantee for high-precision measurement of tool geometry parameters and provides a quantitative basis for error tracing and system optimization, possessing significant theoretical and practical application value. Attached Figure Description

[0058] To make the objectives, technical solutions, and beneficial effects of this invention clearer, the following figures are provided for illustration:

[0059] Figure 1 This is a schematic diagram of the structure of an on-machine non-contact measurement system;

[0060] Figure 2 A schematic diagram of pose calibration for mounting a line laser sensor;

[0061] Figure 3 This is a physical diagram of the in-machine non-contact measurement system;

[0062] Figure 4A physical diagram for sensor pose calibration. Detailed Implementation

[0063] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, so that those skilled in the art can better understand and implement the present invention. However, the embodiments described are not intended to limit the present invention.

[0064] The method for evaluating the uncertainty of in-machine measurement of tool geometry parameters in this embodiment includes the following steps.

[0065] Step 1: Setting up the machine-to-machine non-contact measurement system

[0066] A non-contact measurement system is built on a five-axis CNC machine tool. The tool is mounted on the A-axis of the five-axis CNC machine tool, and a line laser sensor is mounted on the spindle of the five-axis CNC machine tool. The spindle is locked to prevent free rotation. The transmission chain path at the tool end is: bed → Y-axis → C-axis → A-axis → tool; the transmission chain path at the sensor end is: bed → Y-axis → X-axis → Z-axis → line laser sensor. The X-axis drives the line laser sensor for translational motion, and the A-axis drives the tool for indexing or continuous rotational motion according to the tool's structural characteristics, thus performing non-contact measurement of the tool on the machine.

[0067] like Figure 1 As shown, this embodiment establishes an on-machine non-contact measurement system on a five-axis CNC tool grinder. This on-machine non-contact measurement system consists of a line laser sensor, a machine bed, a cutting tool, a worktable, three linear axes (X, Y, Z), and two rotary axes (A, C). The cutting tool end, starting from the machine bed, consists of the Y-axis, C-axis, A-axis, and workpiece in sequence; the sensor end, starting from the machine bed, consists of the Y-axis, X-axis, Z-axis, and the line laser sensor in sequence. The on-machine non-contact measurement system employs a multi-axis (multi-coordinate) linkage measurement method, wherein: O W -X W Y W Z W Indicates the workpiece coordinate system; O A -X A Y A Z A O X -X X Y X Z X O Y -X Y Y Y Z Y and O Z -X Z Y Z Z Z These represent the coordinate systems for the A-axis, X-axis, Y-axis, and Z-axis, respectively; O M -X M YM Z M Indicates the machine tool coordinate system; O S -X S Y S Z S This indicates a line laser measurement coordinate system. For installation, the sensor is mounted on the spindle end using a special fixture. During installation, ensure the mounting surface is parallel to the axis of the spindle mounting hole and lock the spindle to prevent free rotation. During measurement, the X-axis drives the sensor's translational motion, while the A-axis drives the measured component's indexing or continuous rotational motion according to the structural characteristics of the measured tool, thus achieving high-precision measurement.

[0068] Step 2: Sensor pose calibration

[0069] To ensure the accuracy of the measurement data, the pose of the line laser sensor relative to the Z-axis needs to be calibrated to obtain the line laser sensor coordinate system O. S -X S Y S Z S To the Z-axis coordinate system O Z -X Z Y Z Z Z The rotation matrix R and the translation matrix T.

[0070] In this embodiment, the steps for sensor pose calibration are as follows:

[0071] 21) Obtain calibration data

[0072] like Figure 2 As shown, this embodiment uses a high-precision cylinder as a standard part for calibration. The standard part is mounted on the A-axis; the X and Y axes are controlled to move, positioning the standard part in three or more different spatial locations, and its cross-sectional profile data is collected at each location. Furthermore, to ensure calibration accuracy, a line laser sensor is used to collect the cross-sectional profile data of the standard part multiple times at each spatial location, obtaining high-precision calibration data.

[0073] 22) Solve for the coordinates of the center of the cross section.

[0074] First, the measured cylindrical cross-section data is filtered to eliminate noise interference with data fitting. Due to installation errors, the intersection of the laser plane and the cylinder will form an elliptical cross-section; the Random Sample Consensus Algorithm (RANSAC) is used to fit the elliptical expression to obtain the coordinates of the cross-section center.

[0075] 23) Establish coordinate transformation relationships

[0076] Linear laser sensor coordinate system O S -X S Y S ZS To the Z-axis coordinate system O Z -X Z Y Z Z Z The conversion relationship between them is expressed as follows:

[0077]

[0078] Where: (x si ,y si ,z si ) and (x zi ,y zi ,z zi ) represent the coordinates of the ellipse center in the coordinate system of the online laser sensor and the Z-axis coordinate system, respectively. (x zi ,y zi ,z zi It can be calculated based on the machine tool coordinates, the line laser sensor dimensions, and the fixture dimensions.

[0079] 24) Solve for the rotation matrix R and the translation matrix T.

[0080] Specifically, this embodiment solves for the rotation matrix R and translation matrix T based on the Rodrigues matrix method. The method is as follows:

[0081] 241) Construct an antisymmetric matrix S consisting of three independent coefficients a, b, and c, and express the rotation matrix R as:

[0082] R = (I + S)(IS) -1

[0083] Where: I represents the identity matrix.

[0084] 242) Construct the i-th point pair using the coordinates of the center of the ellipse in the coordinate system of the online laser sensor and the Z-axis coordinate system for any i-th elliptical cross section; Substitute m pairs of point pairs into the transformation relationship between the online laser sensor coordinate system and the Z-axis coordinate system, and eliminate the translation matrix T by subtracting each pair to obtain a system of equations containing only coefficients a, b, and c; m is the number of calibration data.

[0085] 243) Solve for the coefficients a, b and c using the least squares method to obtain the rotation matrix R.

[0086] 244) Substitute the obtained R back into the transformation relationship between the linear laser sensor coordinate system and the Z-axis coordinate system to calculate the translation matrix T.

[0087] Step 3: Evaluation of measurement uncertainty

[0088] The uncertainty of in-machine non-contact measurement systems is analyzed according to the "Guide to the expression of uncertainty in measurement (GUM)". The sources of uncertainty in in-machine non-contact measurement systems include uncertainty u1 caused by measurement repeatability error, uncertainty u2 caused by workpiece installation error, uncertainty u3 caused by calibration error, and uncertainty u4 caused by sensor resolution.

[0089] (1) Uncertainty u1 caused by repeatability error

[0090] Assume the standard deviation of the measured parameter is S. p If the number of repeated measurements is n, then the uncertainty u1 caused by repeatability error is:

[0091]

[0092] Wherein: S p is the assumed standard deviation of the measured parameter; m is the number of calibration data, i.e., the number of repeated measurements.

[0093] (2) Uncertainty u2 caused by workpiece installation error

[0094] During workpiece installation, even with dial indicator calibration, installation errors e are inevitably introduced due to manual operation and low precision. When assessing measurement uncertainty, this error can be assumed to follow a uniform distribution with a coverage factor of k2. In this embodiment, the uncertainty u2 caused by the workpiece installation error is:

[0095]

[0096] Where: e is the installation error; k2 is the error factor assuming the installation error follows a uniform distribution.

[0097] (3) Uncertainty u3 caused by calibration error

[0098] In this embodiment, the method for solving the uncertainty u3 caused by the calibration error is as follows:

[0099] During sensor attitude calibration, the uncertainty of the rotation matrix R and translation vector T directly leads to measurement errors at coordinate points, thus affecting the accuracy of tool geometry calculations. To accurately assess the measurement uncertainty u3, a quantitative analysis of the coordinate point uncertainty caused by calibration errors is necessary. As shown in step two, each element of R can be represented as a function f of parameters a, b, and c. ij Therefore, the uncertainty of each element of the rotation matrix R is determined by the uncertainties u of a, b, and c. a u b and uc Characterized by the uncertainty propagation equation, it is expressed as:

[0100]

[0101] Where: f ij Let each element of the rotation matrix R be a function of parameters a, b, and c; r ij Let i be each element in the rotation matrix R; i and j represent the row and column, respectively.

[0102] The uncertainties u(t1), u(t2), and u(t3) of each element in the translation matrix T are expressed as:

[0103]

[0104] Where: m is the number of calibration data.

[0105] The uncertainties of each element of the rotation matrix R and the translation matrix T can be calculated using the process described above. Since O Z -X Z Y Z Z Z and O W -X W Y W Z W The transformations between them involve only translation transformations, so the propagation of transformation errors can be ignored. Therefore, the tool coordinate system O W -X W Y W Z W The coordinate uncertainty of each point in the middle is approximately:

[0106]

[0107] The uncertainty u3 caused by the calibration error is:

[0108]

[0109] Where: (x wi ,y wi ,z wi u(x) represents the coordinates of a point in the tool coordinate system; wi ), u(y wi ) and u(z) wi ) represent the coordinate uncertainties of a point in the tool coordinate system on the X, Y, and Z axes, respectively; u(x zi ), u(y) zi ) and u(z) zi ) represent the coordinate uncertainties of a point in the Z-axis coordinate system on the X-axis, Y-axis, and Z-axis, respectively.

[0110] (4) Uncertainty u4 caused by sensor resolution

[0111] The resolutions of the sensor in the X and Z axes are r, respectively. x and r z The error caused by resolution can be considered to follow a uniform distribution with a coverage factor of k4. Therefore, the uncertainty u4 caused by sensor resolution is:

[0112]

[0113] Where: r x and r z represents the resolution of the line laser sensor in the X and Z axes, respectively; k4 is the resolution factor assuming the resolution follows a uniform distribution.

[0114] (5) Combined standard uncertainty u

[0115] The combined standard uncertainty u is:

[0116]

[0117] Introducing confidence intervals, when the confidence interval is 95% and the coverage factor is k, we obtain the expanded uncertainty:

[0118] U = k × u

[0119] Where: U is the expanded uncertainty; k is the confidence factor.

[0120] The following detailed description, using specific examples, illustrates the detailed implementation of the method for evaluating the uncertainty of in-machine measurement of tool geometry parameters in this embodiment.

[0121] 1. On-machine non-contact measurement system setup

[0122] Referring to step one, set up the following on a five-axis CNC tool grinder: Figure 3 The in-machine non-contact measurement system shown.

[0123] 2. Sensor pose calibration

[0124] Referring to step two, the installation posture of the line laser sensor is calibrated, and eight sets of cross-sectional data at different positions of the standard component are collected. The rotation matrix R and translation matrix T can be solved using the least squares method. The calibration site diagram is shown below. Figure 4 As shown. The rotation matrix R and the translation matrix T are respectively:

[0125]

[0126] 3. Measurement uncertainty assessment

[0127] Referring to step three, the measurement uncertainty of the constructed in-machine non-contact measurement system is evaluated. This example uses the basic major diameter d of an M8 screw-tip tap as an example for uncertainty analysis. Ten repeated measurements were performed, and the average parameter value of d was 8.43 mm. Following step three, the calculated uncertainties u1 caused by repeatability error, u2 caused by workpiece installation error, u3 caused by calibration error, and u4 caused by sensor resolution are 3.2 μm, 1.4 μm, 1.1 μm, and 2.8 μm, respectively. The combined standard uncertainty u = 4.6 μm is then calculated, and with a coverage factor k of 2, the expanded uncertainty U is 9.2 μm.

[0128] Therefore, the basic major diameter d of the M8 screw-tip tap is expressed as (8.43±0.0092) mm, which meets the measurement requirements. Furthermore, the uncertainty caused by measurement repeatability and sensor resolution dominates this uncertainty, and accuracy can be improved by replacing it with a higher resolution sensor.

[0129] The above-described embodiments are merely preferred embodiments provided to fully illustrate the present invention, and the scope of protection of the present invention is not limited thereto. Equivalent substitutions or modifications made by those skilled in the art based on the present invention are all within the scope of protection of the present invention. The scope of protection of the present invention is defined by the claims.

Claims

1. A method for evaluating the uncertainty of in-machine measurement of tool geometry parameters, characterized in that: Includes the following steps: Step 1: Setting up the machine-to-machine non-contact measurement system A non-contact measurement system is built on a five-axis CNC machine tool. The cutting tool is mounted on the A-axis of the five-axis CNC machine tool, and a line laser sensor is mounted on the spindle of the five-axis CNC machine tool. The spindle is locked to prevent free rotation. The transmission chain path at the cutting tool end is: bed → Y-axis → C-axis → A-axis → cutting tool; the transmission chain path at the sensor end is: bed → Y-axis → X-axis → Z-axis → line laser sensor. The X-axis drives the line laser sensor for translational motion, and the A-axis drives the cutting tool for indexing or continuous rotational motion according to the tool's structural characteristics, thus performing non-contact measurement of the cutting tool. Step 2: Sensor pose calibration The pose of the line laser sensor relative to the Z-axis is calibrated to obtain the rotation matrix from the line laser sensor coordinate system to the Z-axis coordinate system. Translation matrix ; Step 3: Evaluation of measurement uncertainty Uncertainty sources in in-machine non-contact measurement systems include uncertainties caused by measurement repeatability errors. Uncertainty caused by workpiece installation error Uncertainty caused by calibration error Uncertainty caused by sensor resolution The combined standard uncertainty is... for: In step two, the method for sensor pose calibration consists of the following steps: 21) Obtain calibration data Using a standard cylinder as a standard part, the standard part is mounted on the A-axis; the X-axis and Y-axis are controlled to move, so that the standard part is positioned in three or more different spatial positions; at each spatial position of the standard part, the cross-sectional contour data of the standard part is collected multiple times using a line laser sensor to obtain calibration data; 22) Solve for the coordinates of the center of the cross section. Due to installation errors, the intersection of the laser plane and the cylinder will form an elliptical cross section; the random sample consensus algorithm is used to fit the elliptical expression to obtain the coordinates of the cross section center; 23) Establish coordinate transformation relationships The transformation relationship between the line laser sensor coordinate system and the Z-axis coordinate system is expressed as follows: in:( and They represent the first The coordinates of the ellipse center in the coordinate system of the online laser sensor with an elliptical cross-section and the Z-axis coordinate system; 24) Solve for the rotation matrix Translation matrix The method is as follows: 241) Construct a system with three independent coefficients , and Composed of antisymmetric matrices , rotate matrix Represented as: in: Represents the identity matrix; 242) with any number The coordinates of the ellipse center in the coordinate system of the online laser sensor with the elliptical cross-section and the Z-axis coordinate system are used to construct the coordinates of the ellipse center. One point pair; will Substituting the points into the transformation formula between the linear laser sensor coordinate system and the Z-axis coordinate system, the translation matrix is ​​eliminated by subtracting each pair of points. This yields results containing only coefficients. , and The system of equations; To determine the amount of calibration data; 243) Solving for coefficients using the least squares method , and The rotation matrix is ​​obtained. ; 244) The solution obtained Substituting the transformation equation between the linear laser sensor coordinate system and the Z-axis coordinate system back into the equation, the translation matrix is ​​calculated. .

2. The method for evaluating the uncertainty of in-machine measurement of tool geometry parameters according to claim 1, characterized in that: In step three, the uncertainty caused by repeatability error u 1 is: in: This is the assumed standard deviation of the measured parameter; The number of calibration data, i.e., the number of repeated measurements.

3. The method for evaluating the uncertainty of in-machine measurement of tool geometry parameters according to claim 1, characterized in that: In step three, the uncertainty caused by workpiece installation error u 2 is: in: This is due to installation error; This is the error factor assuming that the installation error follows a uniform distribution.

4. The method for evaluating the uncertainty of in-machine measurement of tool geometry parameters according to claim 1, characterized in that: In step three, the uncertainty caused by calibration error The solution method is as follows: Rotation matrix The uncertainty of each element is determined by , and uncertainty , and Characterized by the uncertainty propagation equation, it is expressed as: in: Rotation matrix Each element is represented as a parameter , and The function; Rotation matrix Each element in; and Representing rows and columns respectively; Translation matrix Uncertainty of each element , and Represented as: in: To determine the amount of calibration data; The coordinate uncertainty of each point in the tool coordinate system is approximately: The uncertainty caused by calibration error for: in: Represents the coordinates of a point in the tool coordinate system; , and These represent the coordinate uncertainties of a point in the tool coordinate system on the X, Y, and Z axes, respectively. , and These represent the coordinate uncertainties of a point in the Z-axis coordinate system on the X-axis, Y-axis, and Z-axis, respectively.

5. The method for evaluating the uncertainty of in-machine measurement of tool geometry parameters according to claim 1, characterized in that: In step three, the uncertainty caused by sensor resolution u 4 is: in: and These represent the resolution of the line laser sensor in the X and Z axes, respectively. This is the resolution factor assuming the resolution follows a uniform distribution.

6. The method for evaluating the uncertainty of in-machine measurement of tool geometry parameters according to claim 1, characterized in that: In step three, a confidence interval is introduced to obtain the expanded uncertainty: in: To expand the uncertainty; is the confidence factor.

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