Shape evaluation apparatus and shape evaluation program

Abstract

To provide a shape evaluation device and a shape evaluation program capable of evaluating the likelihood of each measurement data by using each measurement data.SOLUTION: The shape evaluation device includes a reference curve calculation unit, a deviation amount calculation unit, a deviation amount aggregation unit, and an output control unit. The reference curve calculation unit calculates data of a reference curve representing a parametrically represented contour from a plurality of pieces of measurement data representing the same contour of a measurement target. The deviation amount calculation unit calculates a deviation amount of each piece of measurement data based on the data of the reference curve. The deviation amount aggregation unit calculates a variation in the deviation amount for each section of the reference curve. The output control unit outputs the variation in the deviation amount.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The embodiments relate to a shape evaluation device and a shape evaluation program. [Background technology]

[0002] One method of processing measurement data is to compare the measurement data with known data. For example, in parts manufacturing, the shape of a manufactured part is measured and the measurement data is compared with correct shape data, such as design data, to evaluate whether the part is manufactured with high precision. This evaluation is performed on the assumption that the correct shape data is known. In other words, if the correct shape data is not known, it is difficult to perform an evaluation by comparing the measurement data with the correct shape data. One method of evaluating measurement data when correct shape data does not exist is to compare multiple measurement data of the same shape. Using this method, it is possible to estimate the correct shape data from measurement data, for example, in reverse engineering. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 6363436 Summary of the Invention [Problem to be solved by the invention]

[0004] When comparing measurement data, the ability to evaluate whether each piece of measurement data is trustworthy from the measurement data alone leads to a highly reliable evaluation.There is a need for a framework that can evaluate whether each piece of measurement data is trustworthy from the measurement data alone.

[0005] The embodiments provide a shape evaluation device and a shape evaluation program that can evaluate the likelihood of each piece of measurement data using the measurement data. [Means for solving the problem]

[0006] A shape evaluation device according to one embodiment includes a reference curve calculation unit, a deviation calculation unit, a deviation counting unit, and an output control unit. The reference curve calculation unit calculates reference curve data representing a parametrically expressed contour from a plurality of measurement data representing the same contour of the measurement object. The deviation calculation unit calculates deviations of each measurement data based on the reference curve data. The deviation counting unit calculates deviation variations for each section of the reference curve. The output control unit outputs the deviation variations. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 is a diagram illustrating an example of a configuration of a measurement system according to an embodiment. [Figure 2] FIG. 2 is a block diagram illustrating an example of the configuration of the control device. [Figure 3] FIG. 3 is a diagram illustrating an example of a hardware configuration of the control device. [Figure 4] FIG. 4 is a flowchart showing the operation of the measurement system. [Figure 5] FIG. 5 is a flowchart showing an example of a process for calculating a reference curve. [Figure 6A] FIG. 6A is a diagram for explaining the calculation process of the reference curve. [Figure 6B] FIG. 6B is a diagram for explaining the calculation process of the reference curve. [Figure 7] FIG. 7 is a flowchart showing an example of a process for calculating the amount of deviation. [Figure 8] FIG. 8 is a diagram showing the Frenet frame for the j-th point P. [Figure 9] FIG. 9 is a flowchart showing an example of a process for tallying the deviation amounts. [Figure 10]FIG. 10 is a diagram for explaining the process of tallying the deviation amounts. [Figure 11] FIG. 11 is a diagram showing an example of a display on the display device in the embodiment. [Figure 12] FIG. 12 is a diagram for explaining the first modification. [Figure 13] FIG. 13 is a flowchart showing the process of tallying the deviation amounts in the second modification. [Figure 14] FIG. 14 is a diagram showing an example of a display on a display device in the second modification. [Figure 15] FIG. 15 is a diagram showing an example of the configuration of a measurement system according to the fourth modification of the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0008] Hereinafter, an embodiment will be described with reference to the drawings. FIG. 1 is a diagram showing an example of the configuration of a measurement system according to an embodiment. As shown in FIG. 1, the measurement system 1 has a measurement device 10 and a control device 20. The control device 20 is configured to be able to communicate with a display device 30. The communication between the control device 20 and the display device 30 may be wireless or wired.

[0009] The measuring device 10 is a shape measuring device configured to measure information related to the three-dimensional shape of a measurement object O. The measurement object O is, for example, a machined part (workpiece). The measuring device 10 is, for example, a CMM. For example, the measuring device 10 may be a gantry-type CMM equipped with a probe 11, a probe receiving portion 12, a z-axis movement mechanism 13, an x-axis movement mechanism 14, a y-axis movement mechanism 15, and a stage 16. Here, a machine coordinate system is defined for the measuring device 10. The x-axis of the machine coordinate system is an axis parallel to the horizontal direction of the stage 16. The y-axis of the machine coordinate system is an axis parallel to the vertical direction of the stage 16. The z-axis of the machine coordinate system is an axis parallel to the thickness direction of the stage 16.

[0010] The probe 11 has a ball-shaped contactor at its tip, which comes into contact with the measurement object O and generates a signal. The contactor may be made of ruby, ceramic, or the like. The probe 11 is held by a probe receiving part 12. The probe receiving part 12 holds the probe 11 so that when the contactor of the probe 11 comes into contact with the measurement object O, the contactor can move to follow the shape of the measurement object O. The probe receiving part 12 is attached to a z-axis movement mechanism 13.

[0011] The z-axis moving mechanism 13 is attached to the x-axis moving mechanism 14 so as to be able to move the probe receiving portion 12 in the z-axis direction. The x-axis moving mechanism 14 holds the z-axis moving mechanism 13 so as to be able to move the z-axis moving mechanism 13 in the z-axis direction, and is attached to the y-axis moving mechanism 15 so as to be able to move in the x-axis direction. The y-axis moving mechanism 15 is gate-shaped so as to be able to move the x-axis moving mechanism 14 in the x-axis direction, and is attached to the stage 16 so as to be able to move in the y-axis direction.

[0012] The stage 16 has a flat plate shape and holds the y-axis moving mechanism 15 so that the y-axis moving mechanism 15 can move in the y-axis direction. The measurement object O is placed on the stage 16.

[0013] The control device 20 controls the z-axis movement mechanism 13, the x-axis movement mechanism 14, and the y-axis movement mechanism 15 to move the probe 11 so as to follow the shape of the measurement object O. The control device 20 also processes a signal obtained from the probe 11 when the probe 11 comes into contact with the measurement object O, and generates contour data representing the cross-sectional shape of the measurement object O. Furthermore, the control device 20 functions as a shape evaluation device, comparing the contour data with each other to evaluate each contour data. The control device 20 also displays various information on the display device 30.

[0014] The display device 30 is a display device such as a liquid crystal display or an organic EL display. The display device 30 displays various images based on data transferred from the control device 20. For example, the display device 30 displays the evaluation results of the measured contour data.

[0015] 2 is a block diagram showing an example of the configuration of the control device 20. The control device 20 is a computer such as a personal computer or a tablet terminal, and includes a drive control unit 21, a contour data generation unit 22, a database 23, a reference curve calculation unit 24, a deviation amount calculation unit 25, a deviation amount calculation unit 26, and a display control unit 27.

[0016] The drive control unit 21 controls the z-axis movement mechanism 13, the x-axis movement mechanism 14, and the y-axis movement mechanism 15 to move the probe 11 so as to follow the shape of the object O to be measured.

[0017] The contour data generator 22 generates contour data of the measurement object O from signals obtained via the probe 11. The contour data is point cloud data along the contour of the measurement object O, based on signals output from the probe 11 when the probe 11 is moved, for example, so as to trace the circumferential direction of the measurement object O. The point cloud data may be composed of three-dimensional information corresponding to the xyz coordinates of the probe 11. By performing multiple measurements while changing the z coordinate of the probe 11, multiple contour data representing the three-dimensional shape of the measurement object O are generated. Here, the multiple contour data in this embodiment are data obtained by measuring multiple locations on the same contour shape of the measurement object O that have different z coordinates. Therefore, the multiple contour data usually approximately match.

[0018] The database 23 is a database for storing the contour data generated by the contour data generating unit 22 as measurement data 231 .

[0019] The reference curve calculation unit 24 selects one of the measurement data 231 and calculates curve shape data of the reference curve based on the selected measurement data. The reference curve is a curve that serves as a reference for data comparison and follows the contour shape of the object to be measured. The curve shape data of the reference curve includes data of each point on the reference curve expressed parametrically, a tangent vector of each point on the reference curve, and a normal vector of each point on the reference curve. The data of each point on the reference curve expressed parametrically is a representation of the coordinates of each point on the reference curve as a function of the arc length parameter s. The arc length parameter s is defined by the cumulative distance along the curve from the starting point of the curve. In an embodiment, the coordinates of a point p(s) on the reference curve can be expressed as p(s) = (x(s), y(s)) using the arc length parameter s. The tangent vector of each point on the reference curve is a vector that represents the direction in which the point advances on the reference curve. The tangent vector t(s) is defined by the first-order differential of p(s) shown in the following equation (1). The normal vector of each point on the reference curve is a vector perpendicular to the tangent vector. The normal vector n(s) is defined as a vector in the direction obtained by rotating t(s) shown in the following equation (2) 90 degrees counterclockwise around p(s).

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[0020] The deviation amount calculation unit 25 calculates the amount of deviation of each measurement data with respect to the reference curve. The deviation amount can be a component in the normal direction of the Frenet frame between each point of each measurement data and the nearest point on the reference curve.

[0021] The deviation amount collecting unit 26 evaluates the measurement data by collecting the deviation amounts, and calculates statistical values ​​that represent the variation in the deviation amounts, such as the average value and standard deviation of the deviation amounts.

[0022] The display control unit 27 is an output control unit that displays the evaluation results obtained by the deviation amount counting unit 26 on the display device 30. For example, the display control unit 27 displays a visualized deviation amount of each measurement data with respect to the reference curve.

[0023] Fig. 3 is a diagram showing an example of the hardware configuration of the control device 20. The control device 20 may be various types of terminal devices such as a personal computer (PC) or a tablet terminal. As shown in Fig. 3, the control device 20 has, as hardware, a processor 201, a ROM 202, a RAM 203, a storage 204, an input interface 205, and a communication device 206.

[0024] The processor 201 controls the overall operation of the measurement system 1. The processor 201 operates as a drive control unit 21, a contour data generating unit 22, a reference curve calculating unit 24, a deviation amount calculating unit 25, a deviation amount tallying unit 26, and a display control unit 27, for example, by executing a program stored in the storage 204. The processor 201 is, for example, a central processing unit (CPU). The processor 201 may be a micro-processing unit (MPU), a graphics processing unit (GPU), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or the like. The processor 201 may be a single CPU or the like, or multiple CPUs or the like.

[0025] The ROM (Read Only Memory) 202 is a non-volatile memory. The ROM 202 stores a startup program and the like for the measurement system 1. The RAM (Random Access Memory) 203 is a volatile memory. The RAM 203 is used as a working memory for processing in the processor 201, for example.

[0026] The storage 204 is, for example, a storage such as a hard disk drive or a solid state drive. The storage 204 stores various programs, such as a measurement program, that are executed by the processor 201. The storage 204 can also store measurement data 231 as a database 23.

[0027] The input interface 205 includes input devices such as a touch panel, a keyboard, a mouse, etc. When an input device of the input interface 205 is operated, a signal corresponding to the operation content is input to the processor 201. The processor 201 performs various processes according to this signal.

[0028] The communication device 206 is a communication device that enables the control device 20 to communicate with external devices such as the measuring device 10 and the display device 30. The communication device 206 may be a communication device for wired communication or a communication device for wireless communication.

[0029] Next, a description will be given of the operation of the measurement system 1 in this embodiment. Fig. 4 is a flowchart showing the operation of the measurement system 1. The processing in Fig. 4 is executed by the processor 201.

[0030] In step S1, the processor 201 performs measurement of the measurement object O. Specifically, the processor 201 controls the z-axis movement mechanism 13, the x-axis movement mechanism 14, and the y-axis movement mechanism 15 of the measurement device 10 to perform scanning measurement in which the probe 11 moves so as to scan the outer periphery of the measurement object O, thereby acquiring contour data representing the cross-sectional shape of the measurement object O. The processor 201 performs scanning measurement multiple times while changing the height relative to the measurement object O, i.e., the z coordinate, to acquire multiple pieces of contour data representing the three-dimensional shape of the measurement object O. The processor 201 stores each acquired piece of contour data in the database 23 as measurement data 231. After the measurement is completed, the process proceeds to step S2.

[0031] In step S2, the processor 201 performs preprocessing on the measurement data 231 stored in the database 23. The preprocessing may include processing such as aligning the measurement data, cutting out only the portion necessary for comparison between the measurement data, etc. After the preprocessing is completed, the process proceeds to step S3.

[0032] In step S3, the processor 201 calculates a reference curve. After the reference curve is calculated, the process proceeds to step S4. The reference curve calculation process will be described below. Fig. 5 is a flowchart showing an example of the reference curve calculation process.

[0033] In step S101, the processor 201 extracts one piece of measurement data from the measurement data 231 stored in the database 23. The measurement data to be extracted may be any data. For example, the measurement data to be extracted may be determined randomly. Alternatively, the measurement data to be extracted may be specified by the user. FIG. 6A is a diagram showing an example of measurement data D.

[0034] In step S102, the processor 201 initializes a parameter k, which indicates a point of measurement data for which an arc length parameter is to be calculated, to 1. The processor 201 also initializes an arc length parameter list, which is set in the RAM 203, for example, and which stores the arc length parameter s.

[0035] In step S103, the processor 201 adds 0, which is the value of the starting point s0 of the reference curve, to the arc length parameter list.

[0036] In step S104, the processor 201 p Determine whether it is less than N p is the number of extracted measurement data points. In step S104, k is p If it is determined that k is less than N, the process proceeds to step S105. p If it is determined that it is not less than 100, the process proceeds to step S107.

[0037] In step S105, the processor 201 calculates a discrete approximation s of the cumulative distance from the starting point p0, which is given by the following equation (3): k , and calculate the discrete approximation of the calculated cumulative distance s k The kth arc length parameter p kHere, p in Eq. (3) is added to the arc length parameter list. j is the value of the x and y coordinate data of the jth (1≦j≦k) point in the measurement data.

number

[0038] In step S106, the processor 201 increments k by 1. After that, the process returns to step S104.

[0039] In step S104, k is N p If it is determined that the parameter s is not less than 0, in step S107, the processor 201 initializes a parameter s representing the arc length parameter of the base curve to be calculated to 0. The processor 201 also initializes a coordinate list that is set in the RAM 203, for example, and that stores the coordinates of the base curve.

[0040] In step S108, the processor 201 determines whether s is s Np Determine whether it is equal to or less than s Np is point N p In step S108, s is the value of the arc length parameter s at s Np If it is determined that s is equal to or smaller than s, the process proceeds to step S109. Np If it is determined that the value is not equal to or less than the predetermined value, the process proceeds to step S114.

[0041] In step S109, the processor 201 initializes a parameter k to zero.

[0042] In step S110, the processor 201 determines whether s is s k In step S110, it is determined whether s exceeds s k If it is determined that s does not exceed s, the process proceeds to step S111. k If it is determined that the difference is greater than the threshold value, the process proceeds to step S112.

[0043] In step S111, the processor 201 increments k by 1. After that, the process returns to step S110.

[0044] In step S110, s is k In step S112, if it is determined that the cumulative distance from the starting point p0 on the reference curve is greater than s, the processor 201 calculates the coordinates of the point p(s) on the reference curve based on the following formula (4) and adds the calculated coordinates of the point p(s) to the coordinate list. As shown in FIG. 6B, formula (4) calculates the coordinates of the point on the reference curve whose cumulative distance from the starting point p0 is s by adding the coordinates of the point p of the adjacent measurement data to the coordinate list. k and point p k+1 This is an equation expressed by linear interpolation using the coordinates of

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[0045] In step S113, the processor 201 adds Δs to s. Then, the process returns to step S108. Δs may be a predetermined fixed value or may be specified by the user.

[0046] In step S108, s is Np If it is determined that the coordinates are not equal to or less than the above, in step S114, the processor 201 stores the coordinate list in the RAM 203, for example.

[0047] In step S115, the processor 201 calculates the normal vector and the tangent vector at each point from the data of each point of the base curve parametrically expressed by the arc length parameters. Then, the processor 201 stores the data of each point of the parametrically expressed base curve, the tangent vector, and the normal vector in, for example, the RAM 203 as curve shape data of the base curve. Thereafter, the processing in FIG. 5 ends.

[0048] The reference curve may be calculated by any method, for example, by fitting a non-uniform rational B-spline (NURBS) curve or the like to smoothly connect the measurement data points.

[0049] Returning now to the description of Fig. 4, in step S4 after the calculation of the reference curve, the processor 201 calculates the amount of deviation. After the amount of deviation is calculated, the process proceeds to step S5. The calculation process of the amount of deviation will be described below. Fig. 7 is a flowchart showing an example of the calculation process of the amount of deviation.

[0050] In step S201, the processor 201 reads the curve shape data of the reference curve from the RAM 203, for example.

[0051] In step S202, the processor 201 initializes a parameter i, which indicates the number of data items to be processed for calculating the amount of deviation, to zero.

[0052] In step S203, the processor 201 determines whether i is less than N. N is the number of pieces of measurement data 231. Here, N may or may not be a number that includes the measurement data used to calculate the reference curve. If it is determined in step S203 that i is less than N, the process proceeds to step S204. If it is determined in step S203 that i is not less than N, the process of FIG. 7 ends.

[0053] In step S204, the processor 201 reads the i-th measurement data from the measurement data 231 stored in the database 23. Note that the measurement data for i=0 may be measurement data extracted for calculating the reference curve, or may be other measurement data.

[0054] In step S205, the processor 201 initializes a list of deviation amounts that stores deviation amounts for the i-th measurement data.p Get.

[0055] In step S206, the processor 201 initializes to 0 a parameter j that indicates a point for which the amount of deviation is to be calculated.

[0056] In step S207, the processor 201 p In step S207, it is determined whether j is less than N. p If it is determined that j is less than N, the process proceeds to step S208. p If it is determined that it is not less than 100, the process proceeds to step S212.

[0057] In step S208, the processor 201 obtains the closest point on the reference curve as viewed from the jth point of the ith measurement data. The closest point is, for example, the point that is the shortest distance from the normal to the jth point.

[0058] In step S209, the processor 201 transforms the coordinates of the j-th point into the Frenet frame. The Frenet frame is defined by the t-axis and the n-axis, with the nearest point on the base curve as viewed from the j-th point as the origin. FIG. 8 shows the Frenet frame for the j-th point P. In FIG. 8, the nearest point on the base curve as viewed from the j-th point P is the point s=s0 on the base curve. Therefore, the Frenet frame for the j-th point is a coordinate system having the point s=s0 on the base curve as the origin, the t-axis parallel to the tangent vector t(s0) at s=s0, and the n-axis parallel to the normal vector n(s0) at s=s0. When the coordinates of point P are expressed in the Frenet frame, as shown in Figure 8, the deviation δ(s0) between the j-th point P and the point s = s0 on the base curve is the signed distance between the j-th point P and the point s = s0 on the base curve, i.e., the value of the normal direction component of the coordinates of the j-th point P.

[0059] In step S210, the processor 201 adds the value of the normal direction component of the j-th coordinate expressed in the Frenet frame as the deviation amount data to the j-th position in the deviation amount list.

[0060] In step S211, the processor 201 increments j by 1. After that, the process returns to step S207.

[0061] In step S207, j is set to N p If it is determined that the deviation amount is not less than the predetermined value, in step S212, the processor 201 stores the deviation amount list in, for example, the database 23 as a deviation amount list for the i-th measurement data.

[0062] In step S213, the processor 201 increments i by 1. After that, the process returns to step S203.

[0063] Now, returning to the explanation of Fig. 4, in step S5 after calculating the deviation amounts, processor 201 counts up the deviation amounts. After counting up the deviation amounts, the process proceeds to step S6. The counting process of the deviation amounts will be explained below. Fig. 9 is a flowchart showing an example of the counting process of the deviation amounts.

[0064] In step S301, the processor 201 reads the curve shape data of the reference curve from the RAM 203, for example.

[0065] In step S302, the processor 201 divides the arc length parameter s into intervals of Δs. The intervals of Δs are intervals that are parallel to the tangent vector t and have a length of Δs. The length of the intervals Δs may be a predetermined fixed value or may be specified by the user.

[0066] In step S303, the processor 201 initializes to 0 a parameter j that indicates a point that is the target of deviation amount aggregation.

[0067] In step S304, the processor 201 p In step S304, it is determined whether j is less than N. pIf it is determined that j is less than N, the process proceeds to step S305. p If it is determined that it is not less than 100, the processing of FIG. 9 ends.

[0068] In step S305, the processor 201 reads data on the amount of deviation of the j-th point of each measurement data from, for example, the database 23.

[0069] In step S306, the processor 201 calculates the average value and standard deviation of the deviations. Then, the processor 201 stores the calculated average value and standard deviation of the deviations in the j-th position of the array of evaluation results. For example, in the calculation for point S0 on the base curve S shown in FIG. 10, the processor 201 calculates the average value and standard deviation of the 0-th deviation δ(S0) of the measurement data D1, D2, D3, D4, and D5. The processor 201 performs similar calculations for the other points on the base curve S. Here, the average value and standard deviation are calculated, but other statistical values ​​such as the median and variance may be calculated instead of or in addition to this. As shown in FIG. 10, the comparison of the deviations is performed using the Frenet frame reference, so that the deviations between corresponding points of each measurement data can be appropriately evaluated.

[0070] In step S307, the processor 201 increments j by 1. After that, the process returns to step S304.

[0071] Returning now to the description of Fig. 4, after tallying up the deviation amounts, the processor 201 causes the display device 30 to display the evaluation results of the measurement data. After the display is complete, the processing of Fig. 4 ends. Here, instead of or in addition to displaying the evaluation results of the measurement data on the display device 30, the processor 201 may execute various output processes, such as transmitting the evaluation results of the measurement data to a server (not shown).

[0072] FIG. 11 is a diagram showing an example of a display on the display device 30. An example display screen 300 displays an image 301 in which, for example, a base curve (Base Contour in FIG. 11) is superimposed with a curve of the average value of each measurement data (Mean Contour in FIG. 11). The curve of the average value of the measurement data can be said to represent the most likely contour shape of the measurement object O represented by the measurement data. Furthermore, a distribution of the standard deviation (Uncertainty 1σ in FIG. 11) is superimposed on the image 301. In FIG. 11, the standard deviation is superimposed after being multiplied by 25. The magnification of the standard deviation can be specified, for example, by the user.

[0073] Here, on the display screen 300 as an example, when a portion of the image 301 is designated by the user, an enlarged image 302 of that portion can be displayed. The enlarged image 302 also has a distribution of twice the standard deviation (Uncertainty 2σ in FIG. 11) superimposed thereon. The enlarged image 302 also has a distribution of the median (Median Contour in FIG. 11) superimposed thereon. The superimposition of the 2σ distribution and the median distribution may be omitted.

[0074] Furthermore, the exemplary display screen 300 may display an indication 303 of the upper and lower limits of the range of the arc length parameter of the area displayed in the enlarged image 302 and the interval division width Δs of the arc length parameter s. By displaying the range of the arc length parameter, the user can recognize the position of the area displayed in the enlarged image 302 measured from the start point of the curve. Furthermore, by displaying the interval division width Δs of the arc length parameter s, the user can recognize the granularity at which the deviation amounts are compared.

[0075] As described above, according to the embodiment, one piece of measurement data is extracted from a plurality of pieces of measurement data corresponding to a plurality of contour shapes of the measurement object O as data for calculating a reference curve that serves as a basis for comparing the measurement data. Then, based on this extracted measurement data, curve shape data of the reference curve, including a parametric expression of the curve, is calculated. Then, the amount of deviation of each piece of measurement data is calculated based on the reference curve, and a statistical value of the amount of deviation is calculated as an evaluation result of the measurement data.

[0076] Here, the measurement data for calculating the reference curve is randomly extracted or specified by the user. Therefore, unlike design data, the measurement data extracted in the embodiment for calculating the reference curve is not necessarily highly reliable. However, in such cases, the deviation between the reference curve and the average value becomes large, and the standard deviation value also becomes large. That is, in the embodiment, the likelihood of the measurement data for calculating the reference curve can also be evaluated. In this manner, in the embodiment, the likelihood of each measurement data can be evaluated using the respective measurement data. Note that if the likelihood of the measurement data for calculating the reference curve is determined to be low, for example, the average curve may be used as the reference curve for future deviation calculations and deviation aggregation. Alternatively, different measurement data may be extracted and the reference curve may be calculated again.

[0077] Furthermore, in the embodiment, the deviation amount is evaluated for each section Δs of the reference curve, thereby enabling the local likelihood of the measurement data to be evaluated.

[0078] (Variation 1) A modified example of the embodiment will be described. In the embodiment, the measurement data is treated as being plausible to a certain extent before the deviation amounts are tallied. In reality, outliers may occur in the measurement data. In order to calculate an appropriate deviation amount, it is desirable to exclude such outliers.

[0079] Therefore, when the processor 201 calculates the average value and standard deviation of the deviation amount in step S306 of FIG. 9, the deviation amount data of point p0 of the measurement data where the deviation amount exceeds the threshold value may be excluded from the calculation of the average value and standard deviation as an outlier, as shown in FIG. 12.

[0080] (Variation 2) In the embodiment, the deviation amount between the reference curve and each measurement data is compared. Alternatively, a detailed deviation amount between the reference curve and specific measurement data may be compared. Fig. 13 is a flowchart showing the deviation amount calculation process of the second modification.

[0081] In step S401, the processor 201 reads the curve shape data of the reference curve from, for example, the RAM.

[0082] In step S402, the processor 201 reads specific measurement data from, for example, the storage 204. The specific measurement data can be specified by, for example, a user.

[0083] In step S403, the processor 201 divides the arc length parameter s into intervals of Δs. The processor 201 also divides the number of intervals N s is stored in the RAM 203, for example.

[0084] In step S404, the processor 201 initializes to 0 a parameter i that indicates a section for which deviation amounts are to be tallied.

[0085] In step S405, the processor 201 s In step S405, it is determined whether i is less than N. s If it is determined that i is less than N, the process proceeds to step S406. s If it is determined that it is not less than 1 / 2, the processing of FIG. 13 ends.

[0086] In step S406, the processor 201 calculates a standard score representing the likelihood of specific measurement data for the i-th section. Then, the processor 201 stores the calculated standard score in the i-th position of the array of the evaluation results of the measurement data. The standard score is, for example, a z score Z shown in the following formula (5): i Here, δ in Eq. (5) can be i is the value of the deviation amount data in section i. μ i is the mean value in interval i. σ i is the standard deviation in interval i.

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[0087] In step S407, the processor 201 increments i by 1. After that, the process returns to step S405.

[0088] FIG. 14 is a diagram showing an example of a display on the display device 30 in Modification 2. In one example of the display screen 300, each point of specific measurement data is enlarged and displayed in addition to the enlarged image 302 of the display screen 300 shown in FIG. 11. Here, points 302a whose absolute value of the z-score is within the threshold, i.e., points with high likelihood, are displayed as white points, for example. On the other hand, points 302b whose absolute value of the z-score exceeds the threshold, i.e., points with low likelihood, are displayed as black points, for example. By displaying each point of the measurement data in a different color according to the z-score in this way, the user can intuitively recognize which positions of the specific measurement data were likely to be measured and which positions were not likely to be measured.

[0089] In the example of Fig. 13, it is assumed that the deviation amount from the reference curve for specific measurement data has been calculated in advance. In contrast, the process of Fig. 13 can also be applied to new measurement data for which the deviation amount has not been calculated. In this case, the deviation amount calculation process shown in steps S204-S211 of Fig. 7 may be performed on the new measurement data.

[0090] 14, the measurement data points are color-coded as black or white according to the z-score. The color coding is not limited to black or white. For example, various other methods of emphasis other than color coding may be used, such as varying the color density of the measurement data, varying the brightness, or blinking according to the z-score.

[0091] (Variation 3) In the above-described embodiment, the reference curve is calculated from one piece of measurement data. However, the reference curve may be calculated from a plurality of pieces of measurement data. For example, the reference curve may be calculated from the average value of the plurality of pieces of measurement data.

[0092] (Variation 4) In the embodiment, the measurement device 10 is a CMM in which the probe 11 is movable in three-axis directions. However, the technology of the embodiment can be applied to various shape measurement devices other than a CMM in which the probe 11 is movable in three-axis directions.

[0093] 15 is a diagram showing another example of the configuration of the measurement system 1. The measurement system 1 has a measurement device 40 and a control device 20. The control device 20 is configured to be able to communicate with the display device 30.

[0094] Similar to the measuring apparatus 10, the measuring apparatus 40 is a shape measuring apparatus configured to measure information related to the three-dimensional shape of the measurement object O. Here, the measuring apparatus 40 in FIG. 15 is, for example, a roundness measuring apparatus, and includes, for example, a probe 41, a probe receiving portion 42, a support member 43, a z-axis moving mechanism 44, a support member 45, a rotary table 46, and a stage 47. Here, similar to the measuring apparatus 10, a machine coordinate system is defined for the measuring apparatus 40. The x-axis of the machine coordinate system for the measuring apparatus 40 is an axis parallel to the horizontal direction of the stage 47. The y-axis of the machine coordinate system is an axis parallel to the vertical direction of the stage 47. The z-axis of the machine coordinate system is an axis parallel to the thickness direction of the stage 47.

[0095] Like probe 11, probe 41 has a ball-shaped contactor at its tip, which comes into contact with the measurement object O and generates a signal. Probe 41 is held by probe receiving part 42. Probe receiving part 42 holds probe 41 so that when the contactor of probe 41 comes into contact with the measurement object O, the contactor can move in accordance with the shape of the measurement object O. Probe receiving part 42 is supported by support member 43. Support member 43 extends in the x-axis direction and supports probe receiving part 42 so that it is fixed. Support member 43 is attached to z-axis movement mechanism 44.

[0096] The z-axis moving mechanism 44 is attached to the support member 45 so as to be able to move the support member 43 in the z-axis direction. The support member 45 holds the z-axis moving mechanism 44 so as to be able to move the z-axis moving mechanism 44 in the z-axis direction, and is fixed by the stage 47.

[0097] The rotary table 46 is attached to a stage 47 so that it can rotate about a rotation axis A that is parallel to the z-axis, and so that the contact of the probe 41 can come into contact with the measurement object O placed on the rotary table 46. The stage 47 is flat and holds the support member 43 and the rotary table.

[0098] The control device 20 rotates the turntable 46 in the θ direction around the axis A. The measurement object O placed on the turntable 46 also rotates in the θ direction. At this time, the contact of the probe 41 comes into contact with the measurement object O so as to trace the circumferential direction of the measurement object O. The contour data generation unit 22 of the control device 20 can generate contour data of the measurement object O similar to that of the measurement device 10 from the signal obtained via the probe 41.

[0099] (Other variations) Although several embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be embodied in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, and are also included in the scope of the invention and its equivalents as defined in the claims. [Explanation of symbols]

[0100] 1 Measurement system, 10 Measurement device, 11 Probe, 12 Probe receiving part, 13 Z-axis movement mechanism, 14 X-axis movement mechanism, 15 Y-axis movement mechanism, 16 Stage, 20 Control device, 21 Drive control part, 22 Contour data generation part, 23 Database, 24 Reference curve calculation part, 25 Deviation amount calculation part, 26 Deviation amount collection part, 27 Display control part, 30 Display device, 40 Measurement device, 41 Probe, 42 Probe receiving part, 43 Support member, 44 Z-axis movement mechanism, 45 Support member, 46 Rotary table, 47 Stage, 201 Processor, 202 ROM, 203 RAM, 204 Storage, 205 Input interface, 206 Communication device.

Claims

1. a reference curve calculation unit that calculates data of a reference curve that represents a parametrically expressed contour from a plurality of measurement data that represent the same contour of the measurement object; a deviation amount calculation unit that calculates a deviation amount of each of the measurement data with respect to the data of the reference curve; a deviation amount calculation unit that calculates the deviation amount variation for each section of the reference curve; an output control unit that outputs the deviation amount variation; A shape evaluation device comprising:

2. the deviation amount tallying unit calculates data representing a most likely contour of the measurement object represented by the plurality of measurement data based on the deviation amount; The output control unit further outputs data representing the most likely contour of the measurement object. The shape evaluation device according to claim 1 .

3. the deviation amount tallying unit calculates the likelihood of the specific measurement data based on the deviation amount of the specific measurement data from the reference curve for each section of the reference curve and a distribution of deviation amounts of other measurement data. The shape evaluation device according to claim 1 .

4. the deviation amount tallying unit calculates the variation of the deviation amounts by excluding outliers from the deviation amounts. The shape evaluation device according to claim 1 .

5. the output control unit displays the deviation amount variation on a display device. The shape evaluation device according to claim 1 .

6. calculating, from a plurality of measurement data representing the same contour of the measurement object, data of a reference curve representing the contour in a parametric representation; calculating a deviation amount of each of the measurement data based on the data of the reference curve; calculating the variation in the amount of deviation for each section of the reference curve; outputting the deviation amount variation; A shape evaluation program for causing a processor to execute the above.

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