Surface Texture Measurement System

Abstract

To provide a surface property measurement system that measures the surface properties of a workpiece by improving responsiveness in an in-process of grinding.SOLUTION: A surface property measurement system S includes: detection devices 17, 17e that detect a displacement cause element, caused by displacement values in uneven height directions of uneven surfaces of detection targets W, MP, and output displacement cause data; and a surface property correction device 20. The surface property correction device 20 includes: a master data generation unit 21 that calculates frequency response data Df of MP data Sm indicating displacement cause data relating to a known periodic reference unevenness MPb of the master piece MP; and a correction unit 22 that corrects, by means of a frequency response characteristic of the MP data Sm, measurement data Sd indicating displacement cause data relating to a surface unevenness Wa of the workpiece W, thereby calculating a true displacement value of the surface unevenness Wa.SELECTED DRAWING: Figure 6

Description

[Technical field]

[0001] The present invention relates to a surface texture measurement system. [Background technology]

[0002] Conventionally, an automatic dimension measuring device is known, for example, as disclosed in Patent Document 1. This automatic dimension measuring device includes a control unit that performs a roundness analysis process. The control unit controls a grinding device so as to machine a workpiece to a fixed size based on measurement data measured by a measuring head, and also analyzes the roundness of the workpiece based on the measurement data measured by the measuring head. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2006-153897 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, when a conventional automatic dimension measuring device performs measurements, it is affected by the characteristic values, such as the characteristic frequency, of each component of the grinding device, and there is a risk that the accuracy of the measurement data may be impaired, particularly in the high frequency range. For this reason, the measurement data is generally filtered using a low-pass filter or the like before being output. However, when filtering the measurement data, a problem occurs in that the response is reduced due to the filtering.

[0005] The present invention has been made in view of the above-mentioned problems, and aims to provide a surface texture measuring system that measures the surface texture of a workpiece with improved responsiveness in the in-process grinding process. [Means for solving the problem]

[0006] One aspect of the present invention is a detection device that detects a displacement-induced element caused by a displacement value in a height direction of the unevenness at a detection position when the detection position is moved along an uneven surface of a detection object, and outputs displacement-induced data related to the displacement-induced element; a master data generating unit that acquires master piece displacement-induced data representing the displacement-induced data relating to the reference asperity output by the detection device using a master piece having a known periodic reference asperity as the detection object, and calculates a frequency response characteristic of the master piece displacement-induced data; a correction unit that acquires measured displacement-induced data representing the displacement-induced data relating to the surface unevenness on the surface of a workpiece ground by a grinding device using a grinding wheel as the detection object and that is output by the detection device, and corrects the measured displacement-induced data using the frequency response characteristic of the master piece displacement-induced data to calculate a true displacement value of the surface unevenness. 、 The frequency response characteristic is a transfer function that represents the relationship between input and output when virtual time series data related to true displacement values ​​derived from the shape of the reference unevenness is input and time series data related to displacement values ​​output by the detection device is output. , in surface texture measurement systems. Effect of the Invention

[0007] According to the surface texture measuring system, the master data generating unit calculates the frequency response characteristics of the master piece displacement-induced data of the master piece. Here, the master piece has a known periodic reference asperity. For example, when detecting the displacement value of the reference asperity height direction of the master piece by a detection device, the output data of the detection device is ideally data that matches the known periodic reference asperity. However, due to the influence of the eigenvalues ​​such as the eigenfrequency of each member constituting the grinding device, the output data of the detection device is actually data that does not match the reference asperity. For example, when the reference asperity is a sine wave, the actual output data of the detection device is not a sine wave, but a waveform whose amplitude and phase change depending on the frequency.

[0008] Therefore, as described above, the frequency response characteristic of the master piece displacement-induced data output by the detection device is calculated. In other words, the frequency response characteristic is an index showing how the displacement-induced data output by the detection device is affected by the amplitude and phase in which frequency band. Then, the correction unit corrects the measured displacement-induced data using the frequency response characteristic to calculate the true displacement value of the surface unevenness of the workpiece.

[0009] Even if the measured displacement-induced data output from the detection device when measuring the workpiece is affected by the eigenvalues ​​of each component of the grinding device, the measured displacement-induced data is corrected using the frequency response characteristics of the master piece, so that the corrected measured displacement-induced data can be data free of the effects of the eigenvalues. Therefore, the corrected measured displacement-induced data can be used to calculate the true displacement value of the surface unevenness of the workpiece.

[0010] Conventionally, low-pass filters attenuate components with frequencies higher than the cutoff frequency, so that the displacement value obtained by applying a low-pass filter does not include components in the high-frequency range. However, the above-described surface texture measurement system prevents the accuracy of the measured-displacement-induced data from being impaired in the high-frequency range. Furthermore, the surface texture measurement system can correct the measured-displacement-induced data by high-speed calculation without filtering, improving responsiveness. [Brief description of the drawings]

[0011] [Figure 1] FIG. 2 is a plan view showing the configuration of the grinding device. [Diagram 2] FIG. 4 is a diagram for explaining a detection device of the grinding apparatus. [Diagram 3] 4 is a flowchart showing a grinding process of the grinding device. [Figure 4] FIG. 13 is a diagram for explaining measurement of a master piece by a sizing device serving as an unevenness detection device. [Diagram 5] FIG. 1 is a block diagram showing a configuration of a surface texture measuring system. [Figure 6]FIG. 1 is a block diagram showing a configuration of a surface texture correction device according to a first embodiment. [Figure 7] FIG. 2 is a diagram illustrating a frequency response characteristic (transfer function). [Figure 8] FIG. 11 is a diagram showing the processing of a frequency response characteristic calculation unit constituting a master data generation unit of the surface texture correction device. [Figure 9] 1 is a graph showing frequency response data Df1, where (a) shows gain and (b) shows phase. [Figure 10] 13 is a graph showing frequency response data Df2 after fitting processing, where (a) shows gain and (b) shows phase. However, the data represented by each point is exaggerated, so the number of data points is reduced. [Figure 11] 1 is a graph showing frequency response data Df1 and a transfer function model Dm, where (a) shows gain and (b) shows phase. [Figure 12] FIG. 4 is a diagram showing the processing of a correction data generating unit constituting a correction unit of the surface texture correction device. [Figure 13] FIG. 11 is a block diagram showing the configuration of a surface texture correction device according to a second embodiment. [Figure 14] FIG. 13 is a diagram showing a sizing device equipped with an acceleration sensor as an unevenness detection device in the fifth embodiment. [Figure 15] FIG. 13 is a block diagram showing the configuration of a surface texture measuring system according to a sixth embodiment. [Figure 16] FIG. 11 is a diagram showing the processing of a frequency response characteristic calculation unit constituting a master data generation unit of the surface texture correction device. [Figure 17] FIG. 11 is a diagram showing a part of the processing of a correction data generating unit constituting a correction unit of the surface texture correction device. [Figure 18] FIG. 11 is a diagram showing a part of the processing of a correction data generating unit constituting a correction unit of the surface texture correction device. [Figure 19] FIG. 11 is a diagram showing a part of the processing of a correction data generating unit constituting a correction unit of the surface texture correction device. [Figure 20] 11 is a graph showing second frequency response data Df12, where (a) shows gain and (b) shows phase. [Figure 21] 11 is a graph showing second frequency response data Df22 after fitting processing, where (a) shows gain and (b) shows phase. However, the data represented by each point is exaggerated, so the number of data points is reduced. [Figure 22] 11 is a graph showing second frequency response data Df12 and a second transfer function model Dm12, where (a) shows gain and (b) shows phase. [Figure 23] 11 is a graph showing first frequency response data Df11 and a first transfer function model Dm11, where (a) shows gain and (b) shows phase. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] (Embodiment 1) 1. Overview of Surface Texture Measurement System S The surface texture measuring system S will be described below with reference to the drawings. As shown in Fig. 1, the surface texture measuring system S includes a grinding device 10 and a surface texture correcting device 20. The surface texture measuring system S of this embodiment also includes an image output device 30.

[0013] In the surface texture measuring system S of this embodiment, a sizing device 17 that functions as one of the unevenness detection devices provided in a grinding device 10 described later detects a displacement-causing element caused by a displacement value in the unevenness height direction at a detection position when the detection position is moved along the uneven surface of the detection object. Then, the sizing device 17 outputs displacement-causing data related to the displacement-causing element.

[0014] For example, the sizing device 17 as an unevenness detection device detects, as a detection object, a workpiece W that can be detected after or during grinding, and detects, as a displacement-causing element, a displacement value itself related to the surface unevenness Wa, which is the surface property of the workpiece W. Then, the sizing device 17 outputs displacement-causing data related to the displacement-causing element as a displacement value.

[0015] The displacement-induced data output by the sizing device 17 in the grinding device 10 is affected by the eigenvalues ​​(e.g., natural frequency, etc.) of the sizing device 17 and each of the machine elements (described below) constituting the grinding device 10. In particular, the displacement values ​​detected by the sizing device 17 in the high frequency range are easily affected by eigenvalues ​​such as the natural frequency, and as a result, the true displacement value cannot be obtained. For example, when the sizing device 17 detects the displacement value of the surface irregularities Wa of the workpiece W, the displacement-induced data (corresponding to the displacement data) output by the sizing device 17 indicates a value deviated from the true displacement value.

[0016] Therefore, in the surface texture measuring system S of this embodiment, the surface texture correcting device 20 corrects the displacement-related data output by the sizing device 17 of the grinding device 10 to a true displacement value and outputs the corrected data.

[0017] In order to perform the above-mentioned correction, the surface texture correction device 20 acquires master piece displacement-induced data representing displacement-induced data related to the reference asperity MPb, using a master piece MP (shown in FIG. 4) having a known periodic reference asperity MPb as a detection object by the sizing device 17. For example, the sizing device 17 detects the displacement value related to the reference asperity MPb itself, and the surface texture correction device 20 acquires master piece displacement-induced data related to the reference asperity MPb (corresponding to master piece displacement data) output by the sizing device 17. Then, the surface texture correction device 20 calculates the frequency response characteristics of the acquired master piece displacement data.

[0018] Furthermore, the surface texture correction device 20 corrects the measured displacement caused data for the surface unevenness Wa of the actual workpiece W output by the sizing device 17 using the frequency response characteristics of the calculated master piece displacement data. In this manner, the surface texture correction device 20 calculates the true displacement value of the surface unevenness Wa of the workpiece W. In this embodiment, the surface texture correction device 20 corrects the amplitude and phase of the measured displacement caused data. Then, the surface texture correction device 20 of this embodiment outputs the true displacement value represented by the corrected measured displacement caused data to the image output device 30.

[0019] Here, an example of a displacement-causing element detected by the sizing device 17 functioning as an unevenness detection device is the displacement value of the surface unevenness Wa on the surface of the workpiece W. In addition, the unevenness detection device can be, for example, an acceleration sensor provided in the sizing device 17. An example of a displacement-causing element detected by the acceleration sensor functioning as an unevenness detection device is the acceleration of vibrations generated in response to the surface unevenness Wa.

[0020] Furthermore, the sizing device 17 is capable of detecting the displacement value by directly or indirectly contacting the workpiece W, and is also capable of detecting the displacement value without (non-contacting) contacting the workpiece W. Furthermore, if the unevenness detection device is an acceleration sensor that detects the acceleration of vibration occurring in response to the surface unevenness Wa as a displacement-causing element, it is preferable that a member on which the acceleration sensor is provided is in contact with the workpiece W. In this embodiment, an example is shown in which the sizing device 17 detects the displacement value of the surface unevenness Wa on the surface of the workpiece W as the displacement value, and a case will be described in which the surface texture correction device 20 corrects the measured displacement-causing data representing the detected displacement value.

[0021] 2. Configuration of Grinding Apparatus 10 The configuration of the grinding device 10 will be described with reference to Figures 1 and 2. In this embodiment, the grinding device 10 is exemplified as a table traverse type grinding machine, but a wheelhead traverse type grinding machine can also be applied.

[0022] As shown in Fig. 1 and Fig. 2, the grinding machine 10 mainly includes a bed 11, a grinding wheel 12, a grinding wheel head 13, a headstock 14, a tailstock 15, a spindle table 16, and a sizing device 17. The workpiece W is a rotating body. For example, the workpiece W has a columnar or cylindrical portion as a portion to be ground. The workpiece W also has surface irregularities Wa along the circumferential direction on the outer or inner peripheral surface. The workpiece W is supported at both ends in the rotation axis direction by the headstock 14 and the tailstock 15 and rotates.

[0023] The grinding device 10 rotates the workpiece W and the grinding wheel 12, and grinds the workpiece W by bringing the grinding wheel 12 into contact with the outer peripheral surface of the workpiece W. The grinding wheel 12 is supported by a grinding wheel head 13 so as to be rotatable about an axis parallel to the Z axis. A grinding wheel head guide 11a is provided on the bed 11, and the grinding wheel head 13 is supported by the grinding wheel head guide 11a so as to be movable in the X axis direction. A rotational driving force is applied to the grinding wheel 12 from a grinding wheel rotation motor 12a, and the grinding wheel 12 rotates about the rotation axis. As the grinding wheel head 13 moves in the X axis direction, the grinding wheel 12 approaches the workpiece W placed at a distance in the X axis direction and grinds the workpiece W.

[0024] A spindle table guide 11b is fixed on the bed 11 at a position spaced from the wheel head guide 11a in the X-axis direction. The spindle table guide 11b supports a spindle table 16 so that it can move in the Z-axis direction. A headstock 14 and a tailstock 15 are disposed on the spindle table 16 so as to face each other in the Z-axis direction. Both ends of the workpiece W are rotatably supported by the headstock 14 and the tailstock 15, and the workpiece W is rotated by the rotational driving force applied from the spindle rotation motor 14a.

[0025] 2, the sizing device 17 includes a pair of contacts 17a which are contacting parts that come into contact with the surface of the workpiece W, and a pair of fingers 17b which support each of the pair of contacts 17a. The pair of contacts 17a are provided so as to come into contact with the outer surface of the workpiece W at two points on either side of the rotation center O which is the rotation axis of the workpiece W. The sizing device 17 functions as an outer diameter detection device which detects the outer diameter of the workpiece W by detecting the amount of mechanical displacement of the pair of contacts 17a while the workpiece W is rotated around the rotation axis.

[0026] The sizing device 17 is supported by an axial movement device 17c and is movable in the axial direction of the workpiece W, i.e., in the Z-axis direction. The movement of the sizing device 17 in the Z-axis direction is controlled by an axial movement control unit 17d. Note that the sizing device 17 is not limited to a device in which the contact 17a comes into contact with the surface of the workpiece W, and it is also possible to use, for example, a non-contact type laser sensor, an optical sensor, an eddy current sensor, or the like.

[0027] 3. Grinding method A grinding method using the grinding device 10 will be described with reference to FIG. 3. The grinding device 10 grinds the workpiece W through the steps shown in FIG. 3. The grinding steps are divided according to the difference in the grindstone feed speed, and are performed in the order of rough grinding step S1, fine grinding step S2, fine grinding step S3, and spark-out step S4. The grindstone feed speed in each step is rough grinding step S1>fine grinding step S2>fine grinding step S3>spark-out step S4. In the rough grinding step S1, the rough shape of the workpiece W is formed. In the subsequent fine grinding step S2 and fine grinding step S3, the grindstone feed speed is reduced while the surface shape of the workpiece W is adjusted. In the final spark-out step S4, the surface of the workpiece W is finished to complete the workpiece W.

[0028] Here, it is preferable that the surface texture measuring system S measures the surface texture of the workpiece W in the grinding process. The surface texture measuring system S measures the surface texture of the workpiece W in-process, which refers to the period from when the workpiece W is attached to the grinding device 10 to when it is removed from the grinding device 10, and also includes after the spark-out process S4. The surface texture measuring system S measures the surface texture of the workpiece W in a state in which the rotation of the workpiece W during grinding is maintained.

[0029] 4. Masterpiece MP The master piece MP used in the surface texture measuring system S will be described with reference to FIG. 4. The master piece MP is, for example, a rotating body formed in a disk shape, and has a reference irregularity MPb along the circumferential direction on its outer circumferential surface. However, the master piece MP may have a reference irregularity MPb on its inner circumferential surface. The reference irregularity MPb is a known periodic irregularity. In this embodiment, the reference irregularity MPb has a constant period and the same irregularity height. For example, the reference irregularity MPb has a sine wave shape when unfolded.

[0030] 5. Function as an unevenness detection device 2, circumferential surface irregularities Wa may be generated on the ground surface of the workpiece W. In this embodiment, the sizing device 17 functions as an irregularity detection device that detects the surface irregularities Wa as a surface property of the workpiece W, in addition to functioning as the outer diameter detection device described above.

[0031] In other words, the sizing device 17, which functions as an unevenness detection device, detects the displacement value itself in the unevenness height direction at the detection position as a displacement-attributing element when moving the detection position along the uneven surface of the workpiece W or master piece MP as a detection object. Then, the sizing device 17 outputs time-series data on the displacement value as displacement-attributing data.

[0032] As shown in Fig. 2, the workpiece W is rotated around the rotation axis while at least one contact 17a of the sizing device 17 is in contact with the outer peripheral surface of the workpiece W, which is a rotating body. This allows the detection position of the one contact 17a in contact to move along the circumferential surface irregularities Wa on the outer peripheral surface of the workpiece W. The sizing device 17 detects the mechanical displacement amount of the one contact 17a while the workpiece W is rotating, thereby detecting the displacement value in the irregularity height direction of the surface irregularities Wa, which are the surface properties of the workpiece W. The sizing device 17 outputs measured displacement data (corresponding to "measured displacement-induced data"), which is time-series data on the displacement value of the detected surface irregularities Wa.

[0033] As shown in Fig. 4, the master piece MP is rotated around the axis of rotation with at least one contact 17a of the sizing device 17 in contact with the outer peripheral surface of the master piece MP, which is a rotating body. This allows the detection position by the one contact 17a to move along the circumferential reference asperity MPb on the outer peripheral surface of the master piece MP. The sizing device 17 detects the mechanical displacement amount of the one contact 17a while the master piece MP is rotated, thereby detecting the displacement value of the reference asperity MPb of the master piece MP in the asperity height direction. The sizing device 17 outputs master piece displacement data (corresponding to "master piece displacement-induced data"), which is time-series data on the displacement value of the detected reference asperity MPb.

[0034] 6. Configuration of surface texture correction device 20 Next, the configuration of the surface texture correcting device 20 will be described with reference to Fig. 5 to Fig. 12. As shown in Fig. 5, the surface texture correcting device 20 mainly includes a master data generating unit 21 and a correcting unit 22.

[0035] The master data generating unit 21 uses the master piece MP having a known periodic reference asperity MPb as a detection object and calculates the frequency response characteristics of the master piece displacement data relating to the reference asperity MPb output by the sizing device 17. The correcting unit 22 uses the frequency response characteristics of the master piece displacement data calculated by the master data generating unit 21 to correct the displacement values ​​(measured displacement data) on the surface of the workpiece W measured by the sizing device 17, thereby calculating the true displacement values ​​of the surface asperity Wa.

[0036] 6-1. Master data generation unit 21 As shown in FIG. 6, the master data generating unit 21 mainly includes an MP data acquiring unit 41, a frequency response characteristic calculating unit 42, a fitting processing unit 43, and a transfer function model generating unit 44.

[0037] The MP data acquisition unit 41 acquires, as MP data Sm, master piece displacement data outputted when the sizing device 17 measures the periodic reference irregularity MPb at a predetermined sampling frequency, using the master piece MP supported and rotated by the headstock 14 and tailstock 15 of the grinding device 10 as a detection object. The MP data Sm is time-series data on the displacement value of the reference irregularity MPb in the circumferential direction of the master piece MP outputted by the sizing device 17 when the detection position by the sizing device 17 is moved along the reference irregularity MPb in the circumferential direction on the outer peripheral surface of the master piece MP. Here, as shown in FIG. 4, the master piece MP has a periodic reference irregularity MPb with a known amplitude and number of peaks formed in the circumferential direction. Note that the irregularities are exaggerated in FIG. 4, and the actual irregularity height is small.

[0038] The MP data Sm represents a displacement value of the reference irregularity MPb of the master piece MP measured in a frequency band that needs to be obtained in grinding the workpiece W. For this reason, the measurement of the reference irregularity MPb of the master piece MP by the sizing device 17 is performed as follows.

[0039] First, the spindle rotation speed range in the headstock 14 is calculated by dividing the required frequency band by the number of peaks of the master piece MP. Next, the rotation speed of the master piece MP supported by the headstock 14 and tailstock 15 is continuously changed at a constant rate of change within the spindle rotation speed range. In other words, the rotation speed of the master piece MP is swept. Then, while sweeping the rotation speed of the master piece MP, the sizing device 17 detects the displacement value of the reference asperity MPb in the circumferential direction of the master piece MP in the asperity height direction as a displacement-causing element. The sizing device 17 outputs time-series data relating to the displacement value as master piece displacement data.

[0040] The MP data Sm acquired by the MP data acquisition unit 41 is the master piece displacement data output by the sizing device 17. That is, the MP data Sm, which is the master piece displacement data representing the displacement value of the known reference asperity MPb in the circumferential direction of the master piece MP, is continuously output by the sizing device 17. The MP data acquisition unit 41 acquires the MP data Sm continuously output from the sizing device 17. The MP data acquisition unit 41 outputs the MP data Sm acquired from the sizing device 17 to the frequency response characteristic calculation unit 42.

[0041] The frequency response characteristic calculation unit 42 calculates the frequency response characteristic for the MP data Sm acquired by the MP data acquisition unit 41. The calculated frequency response characteristic is a transfer function that represents the relationship between input and output when virtual time series data relating to true displacement values ​​derived from the shape of the reference asperity MPb is input and time series data relating to displacement values ​​output by the sizing device 17 is output, as shown in Fig. 7 .

[0042] First, as shown in Fig. 8, the frequency response characteristic calculation unit 42 performs a Fourier transform on the MP data Sm (master piece displacement data) corresponding to the "output" data in Fig. 7 (step 42a). As a result, the frequency response characteristic calculation unit 42 generates data related to the displacement amplitude and displacement phase at each frequency of the MP data Sm. The generated data is data representing the displacement amplitude with respect to the frequency and the displacement phase with respect to the frequency.

[0043] Furthermore, the frequency response characteristic calculation unit 42 generates virtual time series data for true displacement values ​​defined by the sweep command when the rotation speed of the master piece MP is swept and the shape of the reference asperities MPb of the master piece MP. The virtual time series data for the true displacement values ​​corresponds to the "input" data in FIG. 7. As shown in FIG. 8, the frequency response characteristic calculation unit 42 performs a Fourier transform on the virtual time series data for the true displacement values ​​(true displacement data) (step 42b). As a result, the frequency response characteristic calculation unit 42 generates data for virtual displacement amplitude and virtual displacement phase in the virtual time series data for the true displacement values. The generated data is data representing the displacement amplitude with respect to frequency and the displacement phase with respect to frequency.

[0044] Then, the frequency response characteristic calculation unit 42 generates frequency response data Df1 representing frequency response characteristics including gain and phase by dividing the displacement amplitude and displacement phase in the MP data Sm that have been Fourier transformed by the true virtual displacement amplitude and true virtual displacement phase that have been Fourier transformed on the virtual time series data related to the true displacement value of the known master piece MP (step 42c). The generated frequency response data Df1 is data representing the gain with respect to the frequency and the phase with respect to the frequency. Here, since the frequency response data Df1 includes the gain and the phase, it can be expressed as a complex value.

[0045] As shown in FIG. 9(a), the gain of the generated frequency response data Df1 is data that changes according to the frequency of the horizontal axis. Also, as shown in FIG. 9(b), the phase of the generated frequency response data Df1 is data that changes according to the frequency of the horizontal axis. As shown in FIG. 9, the generated frequency response data Df1 has mostly suppressed gain and phase vibrations in the machining frequency range R1 required for measuring the surface quality of the workpiece W during grinding by the grinding device 10. On the other hand, in a frequency range larger than the machining frequency range R1, the influence of the eigenvalues ​​(eigenfrequency, etc.) of the components constituting the grinding device 10 is large, and the gain and phase vibrate greatly, resulting in so-called noise. The frequency response characteristic calculation unit 42 outputs the generated frequency response data Df1 to the fitting processing unit 43.

[0046] 6 again, the fitting processing unit 43 performs fitting processing using a polynomial function on the frequency response data Df1 generated by the frequency response characteristic calculation unit 42. In particular, the fitting processing unit 43 performs fitting processing using a polynomial function on complex values ​​including gain and phase, using the frequency response data Df1 related to gain and phase.

[0047] As shown in (a) and (b) of FIG. 10, the fitting processing unit 43 performs fitting processing to generate frequency response data Df2 after fitting processing for gain and phase. The frequency response data Df2 after fitting processing is discrete point group data for frequency. Here, the frequency response data Df2 after fitting processing is expressed as a complex value including gain and phase. Therefore, the frequency response data Df2 after fitting processing can also be expressed as data representing the gain with respect to frequency and the phase with respect to frequency.

[0048] More specifically, the fitting processing unit 43 first sets a designated frequency range R2 for performing the fitting process. Here, the designated frequency range R2 is set to a range narrower than the processing frequency range R1 as shown in (a) and (b) of Fig. 9, and is set as a frequency range from the lower limit frequency F1 of the frequency when the master piece MP is swept to the upper limit frequency F2 of the processing frequency range R1.

[0049] Then, the fitting processing unit 43 performs fitting processing using a polynomial function on the frequency response data Df1 within the specified frequency range R2 using a well-known method such as multiple regression analysis, multivariate analysis, or machine learning, thereby generating frequency response data Df2 after fitting processing.

[0050] Here, for frequencies equal to or higher than the upper limit frequency F2 of the specified frequency range R2, in other words, for a frequency range not used for measuring the surface properties of the workpiece W during grinding by the grinding device 10, the frequency response data Df1 vibrates due to the influence of the eigenvalue (natural frequency, etc.) of the grinding device 10. Also, for frequencies below the lower limit frequency F1 of the specified frequency range R2, since this is a frequency range that is not influenced by the eigenvalue (natural frequency, etc.) of the grinding device 10, it is highly likely that the gain will be approximately 1 and the phase will be approximately 0°, but the values ​​fluctuate due to noise.

[0051] Therefore, the fitting processing unit 43 performs fitting processing on the frequency response data Df1 within the specified frequency range R2. As a result, frequency response data Df2 within the specified frequency range R2 is generated, as shown in (a) and (b) of Figure 10. Then, the fitting processing unit 43 outputs the frequency response data Df2 after the fitting processing in the specified frequency range R2 to the transfer function model generation unit 44.

[0052] For frequencies less than the lower limit frequency F1 of the specified frequency range R2, the gain is 1 and the phase is 0°, so the frequency response data Df2 for the processing frequency range R1 may be generated by adding data less than the lower limit frequency F1 to the generated frequency response data Df2. In this case, the fitting processing unit 43 outputs the frequency response data Df2 for the processing frequency range R1 to the transfer function model generation unit 44.

[0053] The transfer function model generation unit 44 uses the frequency response data Df2 after fitting processing to generate a transfer function model Dm that represents the relationship between input and output when a waveform represented by a true displacement value obtained from the shape of the reference asperity MPb is input and the frequency response data Df2 after fitting processing is output, as shown in Fig. 7. The transfer function model Dm is a model expressed by Laplace transformation. Since the transfer function model Dm is a Laplace transformation model, it is a function expressed by the Laplace operator "s".

[0054] As described above, the frequency response data Df2 after the fitting process is discrete point group data with respect to frequency. Therefore, the transfer function model generation unit 44 generates a transfer function model Dm having a continuous relationship with respect to frequency by using the frequency response data Df2 after the fitting process, which is discrete point group data with respect to frequency.

[0055] As shown by the solid lines in (a) and (b) of FIG. 11, the transfer function model Dm corresponds to the frequency response data Df2 after the fitting process in (a) and (b) of FIG. 10 connected by a continuous line. The transfer function model Dm is a model that represents a frequency range from 0 Hz to, for example, infinity. The transfer function model Dm also represents a higher frequency range than the frequency response data Df2 after the fitting process. The transfer function model Dm can obtain the gain and phase at any frequency by inputting the frequency.

[0056] 6-2. Correction unit 22 As shown in FIG. 6, the correction unit 22 mainly includes a transfer function model reconversion unit 51, a measurement data acquisition unit 52, a correction data generation unit 53, and an output unit .

[0057] The transfer function model reconversion unit 51 uses the transfer function model Dm acquired from the transfer function model generation unit 44 of the master data generation unit 21 to reconvert into converted frequency response data Dfc corresponding to the frequency when the workpiece W is ground. The transfer function model reconversion unit 51 acquires, from the sizing device 17, the frequency when the workpiece W is ground, in other words, the sampling frequency Fs when the sizing device 17 measures the surface irregularities Wa of the workpiece W in grinding the workpiece W. Note that the sampling frequency Fs is not limited to being acquired from the sizing device 17, and can also be acquired, for example, from a control device (not shown) that controls the operation of the grinding device 10.

[0058] Then, the transfer function model reconversion unit 51 uses the transfer function model Dm to generate converted frequency response data Dfc for the reference roughness MPb so as to correspond to the acquired sampling frequency Fs. That is, the transfer function model reconversion unit 51 obtains converted frequency response data Dfc at the sampling frequency Fs by inputting the sampling frequency Fs to the transfer function model Dm. The generated converted frequency response data Dfc for the reference roughness MPb is data representing a gain with respect to the frequency and a phase with respect to the frequency. Here, the converted frequency response data Dfc for the reference roughness MPb includes a gain and a phase, and therefore can be expressed as a complex value. The transfer function model reconversion unit 51 outputs the generated converted frequency response data Dfc for the reference roughness MPb to the correction data generation unit 53.

[0059] The measurement data acquisition unit 52 acquires, as measurement data Sd, measurement displacement data representing the displacement values ​​of the circumferential surface irregularities Wa of the workpiece W outputted when the sizing device 17 measures the periodic surface irregularities Wa on the surface of the workpiece W, using the workpiece W supported and rotating by the headstock 14 and tailstock 15 of the grinding device 10 as the detection object. The measurement data Sd is time-series data relating to the displacement values ​​of the circumferential surface irregularities Wa of the workpiece W outputted by the sizing device 17 when the detection position by the sizing device 17 is moved along the circumferential surface irregularities Wa on the outer circumferential surface of the workpiece W.

[0060] Then, the measurement data acquisition unit 52 outputs the measurement data Sd acquired from the sizing device 17 to the correction data generation unit 53. Here, the measurement data Sd is measured under the same conditions as the MP data Sm, except that it is measured at a sampling frequency Fs different from the sampling frequency of the MP data Sm.

[0061] The correction data generation unit 53 calculates correction data Sr2 representing the true displacement value of the surface unevenness Wa by correcting the measurement data Sd (measured displacement data) using the converted frequency response data Dfc for the reference unevenness MPb obtained from the transfer function model reconversion unit 51 and the measurement data Sd obtained from the measurement data acquisition unit 52.

[0062] Specifically, as shown in Fig. 12, the correction data generating unit 53 performs a Fourier transform on the acquired measurement data Sd (measured displacement data) (step 53a). As a result, the correction data generating unit 53 generates data related to the displacement amplitude and displacement phase at each frequency of the measurement data Sd (measured displacement data). The generated data is data representing the displacement amplitude with respect to the frequency and the displacement phase with respect to the frequency.

[0063] The correction data generating unit 53 acquires the converted frequency response data Dfc for the reference unevenness MPb from the transfer function model reconversion unit 51 (step 53b). The converted frequency response data Dfc for the reference unevenness MPb is data representing the gain with respect to the frequency and the phase with respect to the frequency.

[0064] Then, the correction data generating unit 53 generates correction data Sr1 (corrected measurement data) by dividing the Fourier-transformed measurement data Sd (measurement displacement data) by the converted frequency response data Dfc for the reference irregularity MPb (step 53c). The correction data Sr1 is data representing the displacement amplitude with respect to the frequency and the displacement phase with respect to the frequency. The above-mentioned correction is performed only within the designated frequency range R2 or the machining frequency range R1, and data outside the designated frequency range R2 or the machining frequency range R1 is not used.

[0065] However, the predetermined sampling frequency during measurement of the master piece MP may differ from the sampling frequency Fs during measurement of the workpiece W. Here, the converted frequency response data Dfc for the reference asperity MPb is data reconverted from the transfer function model Dm using the sampling frequency Fs during measurement. Therefore, the Fourier-transformed measurement data Sd and the converted frequency response data Dfc for the reference asperity MPb are data that correspond in frequency. Since the Fourier-transformed measurement data Sd and the converted frequency response data Dfc for the reference asperity MPb are data that correspond in frequency, it is possible to divide the Fourier-transformed measurement data Sd by the converted frequency response data Dfc for the reference asperity MPb.

[0066] The correction data Sr1 calculated by dividing the Fourier-transformed measurement data Sd by the converted frequency response data Dfc for the reference asperity MPb has its displacement amplitude and displacement phase corrected. Therefore, the generated correction data Sr1 represents the true displacement value of the surface asperity Wa.

[0067] The correction data Sr1 is frequency response data that represents the displacement amplitude with respect to the frequency and the displacement phase with respect to the frequency. Therefore, the correction data generating unit 53 converts the correction data Sr1 into time series data by performing an inverse Fourier transform, and generates the converted correction data Sr2 (step 53d). The converted correction data Sr2 becomes data that represents the displacement value with respect to time. In this case, the correction data generating unit 53 can perform an inverse Fourier transform on the correction data Sr1 using the amplitude and phase of each frequency only within the processing frequency range R1.

[0068] The output unit 54 converts the correction data Sr2, which is generated by the correction data generating unit 53 and which represents the true displacement value of the surface irregularities Wa, into image output data and outputs it to the image output device 30.

[0069] The image output device 30 acquires the correction data Sr2 output from the correction unit 22, i.e., time-series data representing the displacement value of the surface unevenness Wa. The image output device 30 can then display, for example, on a display, the true displacement value of the surface unevenness Wa represented by the acquired correction data Sr2, or display a pass / fail result by comparing the true displacement value of the surface unevenness Wa with a reference value. The image output device 30 can also display a pass / fail result of the machining accuracy, such as the roundness, taking into account the surface unevenness Wa for a cylindrical or cylindrical workpiece W.

[0070] As can be understood from the above explanation, according to the surface texture measuring system S of this embodiment, the master data generation unit 21 acquires MP data Sm representing the master piece displacement data of the master piece MP, and calculates frequency response data Df1 regarding the reference asperity MPb representing the frequency response characteristics of the MP data Sm.

[0071] Here, the master piece MP has a known periodic reference asperity MPb. For example, when detecting the displacement value of the master piece MP in the reference asperity height direction by a sizing device 17 as an asperity detection device, the output data of the sizing device 17 is ideally data that matches the known periodic reference asperity MPb. However, due to the influence of the eigenvalues ​​such as the eigenfrequency of each member constituting the grinding device 10, the output data of the sizing device 17 is actually data that does not match the reference asperity MPb. For example, when the reference asperity MPb is a sine wave, the actual output data of the sizing device 17 is not a sine wave, but a waveform whose amplitude and phase change depending on the frequency.

[0072] Therefore, as described above, the frequency response data Df1 for the reference irregularity MPb, which represents the frequency response characteristics of the MP data Sm output by the sizing device 17, is calculated. In other words, the frequency response data Df1 is an index that represents how the displacement data output by the sizing device 17 is affected by the amplitude and phase in which frequency band. Then, the correction unit 22 corrects the measurement data Sd representing the measured displacement data using the frequency response data Df1, thereby making it possible to output the correction data Sr1 or the converted correction data Sr2 representing the true displacement value of the surface irregularity Wa of the workpiece W.

[0073] Even if the measurement data Sd output from the sizing device 17 when measuring the workpiece W is affected by the eigenvalues ​​of each member constituting the grinding device 10, the measurement data Sd is corrected using the frequency response data Df1 of the master piece MP, so the correction data Sr1, Sr2 representing the corrected true displacement value can be data that is free of the influence of the eigenvalues. Therefore, the true displacement value of the surface irregularities Wa of the workpiece W can be calculated using the correction data Sr1, Sr2 representing the corrected true displacement value.

[0074] Conventionally, low-pass filters attenuate components with frequencies higher than the cutoff frequency, so that the displacement value obtained by applying a low-pass filter does not include components in the high-frequency range. However, the above-described surface texture measurement system S prevents the accuracy of the measurement data Sd from being impaired in the high-frequency range. Furthermore, the surface texture measurement system S can correct the measurement data Sd by high-speed calculations such as Fourier transform without performing filter processing on the measurement data Sd, improving responsiveness.

[0075] In addition, by performing fitting processing using a polynomial function on the frequency response data Df1, frequency response data Df2 after fitting processing is generated, and the correction unit 22 generates the correction data Sr1 using the frequency response data Df2 after fitting processing. The frequency response data Df2 after fitting processing is data from which noise contained in the frequency response data Df1 has been removed. Therefore, the correction data Sr1 and Sr2 can be generated with high accuracy.

[0076] In this embodiment, the frequency response data Df2 after the fitting process is temporarily represented as a transfer function model Dm. Then, the correction unit 22 generates converted frequency response data Dfc for the reference irregularity MPb using the transfer function model Dm so as to correspond to the sampling frequency Fs when the measurement data Sd is measured. The correction unit 22 generates the correction data Sr1 using the generated converted frequency response data Dfc. This makes it possible to generate the correction data Sr1 even if the sampling frequency when the master piece MP is measured is different from the sampling frequency Fs when the workpiece W is measured.

[0077] (Embodiment 2) The surface texture correction device 20 of the second embodiment will be described with reference to Fig. 13. As in the first embodiment, the surface texture correction device 20 includes a master data generation unit 21 and a correction unit 22. This embodiment differs from the first embodiment in that the master data generation unit 21 does not include the transfer function model generation unit 44, and the correction unit 22 includes a frequency response characteristic interpolation processing unit 55 instead of the transfer function model reconversion unit 51.

[0078] Other configurations in this embodiment are the same as those in embodiment 1. Note that, among the reference symbols used in embodiment 2 and the following embodiments, those which are the same as those used in the previous embodiments represent the same components, etc. as those in the previous embodiments, unless otherwise specified.

[0079] In this embodiment, the frequency response characteristic interpolation processing unit 55 performs an interpolation process using the frequency response data Df2 after the fitting process to generate converted frequency response data Dfc corresponding to the frequency when the workpiece W is ground.

[0080] The frequency response characteristic interpolation processing unit 55 acquires the frequency when grinding the workpiece W, in other words, the sampling frequency Fs when the sizing device 17 measures the surface irregularities Wa of the workpiece W during grinding from the sizing device 17. Here, the sampling frequency when measuring the master piece MP is different from the sampling frequency Fs when measuring the workpiece W. Therefore, the frequency response data Df2 after the fitting process and the measurement data Sd after the Fourier transform do not correspond in frequency. Therefore, the correction data generation unit 53 cannot divide the measurement data Sd after the Fourier transform by the frequency response data Df2 after the fitting process.

[0081] Therefore, by performing an interpolation process on the frequency response data Df2 after the fitting process, the frequency response data Dfc after the interpolation is generated so that the frequency corresponds to the measurement data Sd after the Fourier transform. The interpolation process uses adjacent data to perform, for example, linear approximation. Therefore, this embodiment has the same effects as the first embodiment.

[0082] (Embodiment 3) When the predetermined sampling frequency when measuring the reference asperity MPb of the master piece MP is the same as the sampling frequency Fs when measuring the workpiece W, the transfer function model generating unit 44 and the transfer function model reconverting unit 51 in the first embodiment are not required. In this case, the frequency response data Df2 after fitting processing generated by the fitting processing unit 43 is output to the correction data generating unit 53. Therefore, this embodiment has the same effects as those of the first embodiment.

[0083] (Embodiment 4) When the predetermined sampling frequency when measuring the reference irregularity MPb of the master piece MP is the same as the sampling frequency Fs when measuring the workpiece W, the fitting processing unit 43, the transfer function model generating unit 44, and the transfer function model reconversion unit 51 in the first embodiment may not be included. In this case, the frequency response data Df1 generated by the frequency response characteristic calculating unit 42 is output to the correction data generating unit 53. This embodiment also has the same effects as the first embodiment. However, performing the fitting process provides higher accuracy.

[0084] (Embodiment 5) In the above-described embodiment, a sizing device 17 is used as an unevenness detection device, and displacement values ​​are detected as displacement-causing elements resulting from the displacement values ​​in the unevenness height direction of the surface unevenness Wa of the workpiece W and the reference unevenness MPb of the master piece MP, and time series data regarding the displacement values ​​is output as displacement-causing data regarding the displacement-causing elements.

[0085] However, as shown in Figure 14, the unevenness detection device is not limited to detecting displacement values ​​as displacement-causing elements, but can also be an acceleration sensor 17e that detects acceleration as a displacement-causing element related to the displacement values ​​in the unevenness height direction of the surface unevenness Wa of the workpiece W and the reference unevenness MPb of the master piece MP.

[0086] In this case, the acceleration sensor 17e as an unevenness detection device has a contact 17a that contacts the uneven surfaces Wa, MPb of the detection objects W, MP, and detects the acceleration of the contact 17a as a displacement-attributing element when the contact 17a is moved along the uneven surfaces Wa, MPb of the detection objects W, MP. Then, the acceleration sensor 17e as an unevenness detection device outputs time-series data on the detected acceleration as displacement-attributing data.

[0087] In this embodiment, since the data is related to acceleration, a process for converting the acceleration into a displacement value is required at the final stage of the process or during the process. For example, the correction data generating unit 53 generates the correction data related to the acceleration, and then performs an integration process to generate the correction data related to the displacement value of the surface irregularities Wa.

[0088] Furthermore, in the frequency response characteristic calculation unit 42 of the master data generation unit 21, an integration process is performed on the MP data Sm, which is time series data related to acceleration, to convert it into time series data related to displacement values, and then the processing described in the above embodiment is performed. Furthermore, in the correction data generation unit 53 of the correction unit 22, an integration process is performed on the measurement data Sd, which is time series data related to acceleration, to convert it into time series data related to displacement values, and then the processing described in the above embodiment is performed. In this way, the surface texture correction device 20 can obtain the true displacement value of the surface unevenness Wa of the workpiece W.

[0089] (Embodiment 6) A surface texture measuring system S of the sixth embodiment will be described with reference to Fig. 15 to Fig. 23. As shown in Fig. 15, the surface texture measuring system S includes a sizing device 17 serving as a displacement detection device, an acceleration sensor 17e serving as an acceleration detection device, a surface texture correction device 20, and an image output device 30.

[0090] The sizing device 17 has the same configuration as that of the above-mentioned embodiment 1. Therefore, when the sizing device 17 moves the detection position along the uneven surface of the detection object, it detects the displacement value in the unevenness height direction at the detection position as a displacement-attributing element. Then, the sizing device 17 outputs time-series data related to the detected displacement value as displacement data (displacement-attributing data).

[0091] The objects to be detected by the sizing device 17 are the master piece MP and the workpiece W. Therefore, when the master piece MP is the object to be detected, the sizing device 17 outputs time series data regarding the displacement values ​​of the reference asperity MPb of the master piece MP as first master piece displacement data. Also, when the workpiece W is the object to be detected, the sizing device 17 outputs time series data regarding the displacement values ​​of the surface asperity Wa of the workpiece W as first measured displacement data. The measurement method by the sizing device 17 is the same as in embodiment 1.

[0092] The acceleration sensor 17e is similar to that of the fifth embodiment, and detects the acceleration of the contact 17a of the sizing device 17 as a displacement-causing element, as shown in Fig. 14. That is, the acceleration sensor 17e detects the acceleration of the contact 17a as a displacement-causing element when the contact 17a, which is in contact with the uneven surface of the detection object, is moved along the uneven surface of the detection object. Then, the acceleration sensor 17e outputs time-series data related to the detected acceleration as acceleration data (displacement-causing data).

[0093] The objects to be detected by the acceleration sensor 17e are the master piece MP and the workpiece W, similar to the objects to be detected by the sizing device 17 as a displacement detection device. Therefore, when the master piece MP is the object to be detected, the acceleration sensor 17e outputs time series data related to the acceleration of the contact 17a contacting the reference asperity MPb of the master piece MP as master piece acceleration data. Also, when the workpiece W is the object to be detected, the acceleration sensor 17e outputs time series data related to the acceleration of the contact 17a contacting the surface asperity Wa of the workpiece W as measured acceleration data. The measurement method using the acceleration sensor 17e is performed simultaneously with the above measurement by the sizing device 17.

[0094] As in the first embodiment, the surface texture correction device 20 includes a master data generation unit 21 and a correction unit 22. The master data generation unit 21 and the correction unit 22 constituting the surface texture correction device 20 respectively acquire output data of the sizing device 17 and acquire output data of the acceleration sensor 17e.

[0095] As shown in FIG. 15, the master data generating unit 21 mainly includes an MP data acquiring unit 141, a frequency response characteristic calculating unit 142, a fitting processing unit 143, and a transfer function model generating unit 144.

[0096] The MP data acquisition unit 141 acquires first master piece displacement data (first MP displacement data) Sm11 output when the sizing device 17 measures the periodic reference irregularities MPb at a predetermined sampling frequency, with the master piece MP as the detection object. The first MP displacement data Sm11 is similar to the MP data Sm in embodiment 1. Furthermore, the MP data acquisition unit 141 acquires master piece acceleration data (MP acceleration data) Sm12 output from the acceleration sensor 17e, with the master piece MP as the detection object.

[0097] The frequency response characteristic calculation unit 142 calculates the frequency response characteristic of the first MP displacement data Sm11 and the frequency response characteristic of the MP acceleration data Sm12. The processing of the frequency response characteristic calculation unit 142 will be described with reference to FIG.

[0098] The frequency response characteristic calculation unit 142 performs a Fourier transform on the first MP displacement data Sm11 (step 142a). As a result, the frequency response characteristic calculation unit 142 generates data related to the displacement amplitude and displacement phase at each frequency of the first MP displacement data Sm11. The generated data is data representing the displacement amplitude with respect to the frequency and the displacement phase with respect to the frequency.

[0099] Furthermore, the frequency response characteristic calculation unit 142 generates virtual time series data for true displacement values ​​defined by the sweep command when the rotation speed of the master piece MP is swept and the shape of the reference asperities MPb of the master piece MP. The frequency response characteristic calculation unit 142 performs a Fourier transform on the virtual time series data for the true displacement values ​​(true displacement data) (step 142b). As a result, the frequency response characteristic calculation unit 142 generates data for virtual displacement amplitude and virtual displacement phase in the virtual time series data for the true displacement values. The generated data is data representing the displacement amplitude with respect to frequency and the displacement phase with respect to frequency.

[0100] Then, the frequency response characteristic calculation unit 142 generates first frequency response data Df11 representing a first frequency response characteristic including gain and phase by dividing the displacement amplitude and displacement phase in the first MP displacement data Sm11 obtained by Fourier transform by the true virtual displacement amplitude and true virtual displacement phase obtained by Fourier transforming the virtual time series data related to the true displacement value of the known master piece MP (step 142c). The generated first frequency response data Df11 is data representing the gain with respect to the frequency and the phase with respect to the frequency. Here, since the first frequency response data Df11 includes the gain and the phase, it can be expressed as a complex value.

[0101] The gain of the generated first frequency response data Df11 is data that changes according to the frequency on the horizontal axis, as shown in (a) of Fig. 9. Moreover, the phase of the generated first frequency response data Df11 is data that changes according to the frequency on the horizontal axis, as shown in (b) of Fig. 9.

[0102] The frequency response characteristic calculation unit 142 performs a Fourier transform on the MP acceleration data Sm12 (step 142d). As a result, the frequency response characteristic calculation unit 142 generates data related to the acceleration amplitude and acceleration phase at each frequency of the MP acceleration data Sm12. The generated data is data representing the acceleration amplitude with respect to the frequency and the acceleration phase with respect to the frequency.

[0103] The frequency response characteristic calculation unit 142 performs a displacement process on the Fourier transformed MP acceleration data Sm12 to generate second master piece displacement data (second MP displacement data) Sm13 (step 142e). The generated data represents the displacement amplitude with respect to the frequency and the displacement phase with respect to the frequency.

[0104] Then, the frequency response characteristic calculation unit 142 generates second frequency response data Df12 representing a second frequency response characteristic including gain and phase by dividing the displacement amplitude and displacement phase in the second MP displacement data Sm13 by the true virtual displacement amplitude and true virtual displacement phase obtained by performing a Fourier transform on the virtual time-series data related to the true displacement value of the known master piece MP (step 142f). The generated second frequency response data Df12 is data representing the gain with respect to the frequency and the phase with respect to the frequency. Here, since the second frequency response data Df12 includes the gain and the phase, it can be expressed as a complex value.

[0105] As shown in Fig. 20(a), the gain of the generated second frequency response data Df12 is data that changes according to the frequency on the horizontal axis, and as shown in Fig. 20(b), the phase of the generated second frequency response data Df12 is data that changes according to the frequency on the horizontal axis.

[0106] 20, in the generated second frequency response data Df12, the vibration of the gain and phase is generally suppressed in the second specified frequency range R11. On the other hand, in a frequency range larger than the second specified frequency range R11, the effect of the eigenvalues ​​(e.g., natural vibration frequency) of the components constituting the grinding device 10 is large, and the gain and phase vibrate greatly, resulting in so-called noise. In a frequency range smaller than the second specified frequency range R11, the effect of the eigenvalues ​​of the grinding device 10 is not present, so the gain is approximately 1 and the phase is approximately 0°, but the values ​​fluctuate due to noise.

[0107] As shown in FIGS. 15 and 16, the fitting processing unit 143 performs fitting processing on the first frequency response data Df11 and the second frequency response data Df12 generated by the frequency response characteristic calculation unit 142 using a polynomial function.

[0108] As shown in Fig. 16, the fitting processing unit 143 uses the first frequency response data Df11 related to gain and phase to perform fitting processing with a polynomial function for complex values ​​including gain and phase, thereby generating first frequency response data Df21 after fitting processing for gain and phase (step 143a). The first frequency response data Df21 after fitting processing is discrete point cloud data for frequency, as shown in (a) and (b) of Fig. 10. The generation of the first frequency response data Df21 after fitting processing is similar to the generation of the frequency response data Df2 after fitting processing in the first embodiment.

[0109] 16, the fitting processing unit 143 uses the second frequency response data Df12 for gain and phase to perform fitting processing with a polynomial function for complex values ​​including gain and phase to generate second frequency response data Df22 after fitting processing for gain and phase (step 143b). The second frequency response data Df22 after fitting processing is point cloud data that is discrete in frequency, as shown in (a) and (b) of FIG.

[0110] More specifically, the fitting processor 143 first sets a second specified frequency range R11 in which the fitting process is performed. Then, the fitting processor 143 performs the fitting process on the second frequency response data Df12 in the second specified frequency range R11. Then, as shown in (a) and (b) of FIG. 21, the second frequency response data Df22 in the second specified frequency range R11 is generated.

[0111] 15 and 16, the transfer function model generation unit 144 uses the first frequency response data Df21 after fitting processing to generate a first transfer function model Dm11 that represents the relationship between input and output when a waveform represented by a true displacement value obtained from the shape of the reference asperity MPb is input and the first frequency response data Df21 after fitting processing is output (step 144a). The first transfer function model Dm11 is a model expressed by Laplace transformation. Since the first transfer function model Dm11 is a Laplace transformation model, it is a function expressed by the Laplace operator "s".

[0112] As described above, the first frequency response data Df21 after the fitting process is point cloud data that is discrete in frequency. Therefore, the transfer function model generation unit 144 generates a first transfer function model Dm11 having a continuous relationship in frequency, using the first frequency response data Df21 after the fitting process that is point cloud data that is discrete in frequency.

[0113] As shown by the solid lines in (a) and (b) of FIG. 23, the first transfer function model Dm11 corresponds to the first frequency response data Df21 after the fitting process connected by a continuous line. The first transfer function model Dm11 is a model expressed for a frequency range from 0 Hz to, for example, infinity. The first transfer function model Dm11 also expresses a higher frequency range than the first frequency response data Df21 after the fitting process. The first transfer function model Dm11 can obtain the gain and phase at any frequency by inputting the frequency.

[0114] The transfer function model generation unit 144 further uses the second frequency response data Df22 after fitting processing to generate a second transfer function model Dm12 that represents the relationship between input and output when a waveform represented by a true displacement value obtained from the shape of the reference asperity MPb is input and the second frequency response data Df22 after fitting processing is output (step 144b). The second transfer function model Dm12 is a model expressed by Laplace transform. Since the second transfer function model Dm12 is a Laplace transform model, it is a function expressed by the Laplace operator "s".

[0115] As described above, the second frequency response data Df22 after the fitting process is point cloud data that is discrete in frequency. Therefore, the transfer function model generation unit 144 generates the second transfer function model Dm12 having a continuous relationship in frequency, using the second frequency response data Df22 after the fitting process, which is point cloud data that is discrete in frequency.

[0116] As shown by the solid lines in (a) and (b) of FIG. 22, the second transfer function model Dm12 corresponds to a continuous line connecting the second frequency response data Df22 after the fitting process in (a) and (b) of FIG. 21. The second transfer function model Dm12 is a model that represents a frequency range from 0 Hz to, for example, infinity. Furthermore, the second transfer function model Dm12 also represents a higher frequency range than the second frequency response data Df22 after the fitting process. The second transfer function model Dm12 can obtain the gain and phase at any frequency by inputting the frequency.

[0117] As shown in FIG. 15, the correction unit 22 mainly includes a transfer function model reconversion unit 151, a measurement data acquisition unit 152, a correction data generation unit 153, and an output unit 154.

[0118] The transfer function model reconversion unit 151 reconverts the first transfer function model Dm11 acquired from the transfer function model generation unit 144 of the master data generation unit 121 into first converted frequency response data Dfc11 corresponding to the frequency when the workpiece W is ground. Furthermore, the transfer function model reconversion unit 151 reconverts the first transfer function model Dm11 acquired from the transfer function model generation unit 144 of the master data generation unit 121 into second converted frequency response data Dfc12 corresponding to the frequency when the workpiece W is ground. The reconversion method is the same as in the first embodiment.

[0119] The measurement data acquiring unit 152 acquires first measured displacement data Sd11 output when the sizing device 17 measures the periodic reference irregularities MPb at a predetermined sampling frequency, with the workpiece W as the detection object. The first measured displacement data Sd11 is similar to the measurement data Sd in embodiment 1. Furthermore, the measurement data acquiring unit 152 acquires measured acceleration data Sd12 output from the acceleration sensor 17e, with the workpiece W as the detection object.

[0120] 17, the correction data generating unit 153 acquires the first measured displacement data Sd11 from the measurement data acquiring unit 152, and performs a Fourier transform on the acquired first measured displacement data Sd11 (step 153a). As a result, the correction data generating unit 153 generates data related to the displacement amplitude and displacement phase at each frequency of the first measured displacement data Sd11. The generated data is data representing the displacement amplitude with respect to the frequency, and the displacement phase with respect to the frequency.

[0121] The correction data generating unit 153 acquires the first converted frequency response data Dfc11 for the reference unevenness MPb from the transfer function model reconversion unit 151 (step 153b). Then, the correction data generating unit 153 divides the first measured displacement data Sd11 that has been Fourier transformed by the first converted frequency response data Dfc11 for the reference unevenness MPb to generate first corrected data Sr11 (corrected first measured displacement data) by correcting the first measured displacement data Sd11 (step 153c).

[0122] The first correction data Sr11 is data representing the true displacement value of the surface irregularities Wa. The first correction data Sr11 is data representing the displacement amplitude relative to the frequency and the displacement phase relative to the frequency. As shown in (a) and (b) of FIG. 23, the above-mentioned correction may be performed only within the first specified frequency range R2 (F1 to F2), may be performed only within the frequency range R1 (F3 to F20) including the first specified frequency range R2, or may be performed only within the first use frequency range R21 (F3 to F20). Here, the first use frequency range R21 is different from the first specified frequency range R2. In this embodiment, the first use frequency range R21 is a part of the frequency range R1 and is a range that is only partially common to the first specified frequency range R2.

[0123] 18, the correction data generating unit 153 acquires the measured acceleration data Sd12 from the measurement data acquiring unit 152, and performs a Fourier transform on the acquired measured acceleration data Sd12 (step 153d). As a result, the correction data generating unit 153 generates data related to the acceleration amplitude and acceleration phase at each frequency of the measured acceleration data Sd12. The generated data is data representing the acceleration amplitude with respect to the frequency, and the acceleration phase with respect to the frequency.

[0124] The correction data generator 153 performs a displacement process on the Fourier transformed measured acceleration data Sd12 to generate second measured displacement data Sd13 (step 153e). The generated data represents the displacement amplitude with respect to the frequency and the displacement phase with respect to the frequency.

[0125] The correction data generating unit 153 acquires the second converted frequency response data Dfc12 for the reference unevenness MPb from the transfer function model reconversion unit 151 (step 153f). Then, the correction data generating unit 153 divides the displaced second measured displacement data Sd13 by the second converted frequency response data Dfc12 for the reference unevenness MPb to generate second corrected data Sr12 (corrected second measured displacement data) by correcting the second measured displacement data Sd13 (step 153g).

[0126] The second correction data Sr12 is data representing the true displacement value of the surface irregularities Wa. Moreover, the second correction data Sr12 is data representing the displacement amplitude with respect to the frequency and the displacement phase with respect to the frequency. The above-mentioned correction may be performed only within the second specified frequency range R11 (F11 to F12) or only within the second use frequency range R22 (F20 to F12) as shown in (a) and (b) of FIG. 22. Here, the second use frequency range R22 is different from the second specified frequency range R11. In particular, the second use frequency range R22 is a part of the second specified frequency range R11. Furthermore, the second use frequency range R22 (F20 to F12) is a higher frequency range than the first use frequency range R21 (F3 to F20).

[0127] 19, when the first correction data Sr11 is data in the frequency range R1 (F3 to F2) or the first specified frequency range R2 (F1 to F2), the correction data generation unit 153 extracts a portion of the data to generate first correction data Sr11 in the first usable frequency range R21 (F3 to F20) (step 153h). When the first correction data Sr11 is data in the first usable frequency range R21 (F3 to F20), the correction data generation unit 153 acquires the first correction data Sr11 itself.

[0128] Furthermore, when the second correction data Sr12 is data in the second specified frequency range R11 (F11 to F12), the correction data generation unit 153 extracts a portion of the data to generate second correction data Sr12 in the second usable frequency range R22 (F20 to F12) (step 153i). When the second correction data Sr12 is data in the second usable frequency range R22 (F20 to F12), the correction data generation unit 153 acquires the second correction data Sr12 itself.

[0129] The correction data generating unit 153 generates the composite correction data Sr13 by combining the first correction data Sr11 in the first usable frequency range R21 (F3 to F20) and the second correction data Sr12 in the second usable frequency range R22 (F20 to F12) (step 153j). As described above, the first correction data Sr11 in the first usable frequency range R21 (F3 to F20) and the second correction data Sr12 in the second usable frequency range R22 (F20 to F12) are data separated into low-frequency data and high-frequency data with the frequency F20 as a boundary. Therefore, the composite correction data Sr13 is data in the frequency range F3 to F12. The composite correction data Sr13 is frequency response data that represents the displacement amplitude with respect to the frequency and the displacement phase with respect to the frequency.

[0130] Then, the correction data generator 153 converts the composite correction data Sr13 into time-series data by performing an inverse Fourier transform, thereby generating the converted composite correction data Sr14 (step 153k). The converted composite correction data Sr14 becomes data representing a displacement value with respect to time.

[0131] The output unit 154 converts the composite correction data Sr14, which is generated by the correction data generation unit 153 and indicates the true displacement value of the surface irregularities Wa, into image output data and outputs it to the image output device 30.

[0132] According to this embodiment, by using the displacement data detected by the sizing device 17 as a displacement detection device and the acceleration data detected by the acceleration sensor 17e as an acceleration detection device, data over a wide frequency range can be used.

[0133] In particular, the sizing device 17 as a displacement detection device is capable of highly accurate output on the low frequency side, while the acceleration sensor 17e as an acceleration detection device is capable of highly accurate output on the high frequency side. In this way, since each detection device has a different frequency range at which it can output with high accuracy, data over a wide frequency range can be used. Therefore, the true displacement value of the surface irregularities Wa of the workpiece W can be obtained with high accuracy.

[0134] (others) Furthermore, a linear gauge can be used instead of the sizing device 17. The linear gauge includes a contactor that contacts the workpiece W and an arm that supports the contactor, and detects the displacement of the surface of the workpiece W with the contactor in contact with the rotating workpiece W. Similarly to the sizing device 17, the linear gauge is supported by an axial direction moving device and can be moved in the axial direction of the workpiece W, i.e., in the Z direction. [Explanation of symbols]

[0135] 17...sizing device (detection device, displacement detection device), 17a...contactor, 17b...finger, 17e...acceleration sensor (detection device, acceleration detection device), 20...surface texture correction device, 21...master data generation unit, 22...correction unit, MP...master piece, MPb...reference unevenness, W...workpiece, Wa...surface unevenness, Sm...MP data (displacement-induced data, master piece displacement data), Sd...measurement data (displacement-induced data, measured displacement data), Sr11, Sr12...correction data, S...surface texture measurement system

Claims

1. a detection device that detects a displacement-induced element caused by a displacement value in a height direction of the unevenness at a detection position when the detection position is moved along an uneven surface of a detection object, and outputs displacement-induced data related to the displacement-induced element; a master data generating unit that acquires master piece displacement-induced data representing the displacement-induced data relating to the reference asperity output by the detection device using a master piece having a known periodic reference asperity as the detection object, and calculates a frequency response characteristic of the master piece displacement-induced data; a correction unit that acquires measured displacement-induced data representing the displacement-induced data relating to the surface unevenness on the surface of a workpiece ground by a grinding device using a grinding wheel as the detection object and outputted by the detection device, and calculates a true displacement value of the surface unevenness by correcting the measured displacement-induced data using the frequency response characteristic of the master piece displacement-induced data, A surface texture measurement system, wherein the frequency response characteristic is a transfer function that represents the relationship between input and output when virtual time series data regarding true displacement values ​​derived from the shape of the reference unevenness is used as input and time series data regarding displacement values ​​output by the detection device is used as output.

2. the detection device detects the displacement-causing element when moving the detection position along the uneven surface in a circumferential direction of the detection object by rotating the detection object, which is a rotating body, about a rotation axis; the master piece is a rotating body, and has the reference irregularities along a circumferential direction on an outer or inner peripheral surface, The surface texture measuring system according to claim 1 , wherein the workpiece is a rotating body, and the surface irregularities are provided along a circumferential direction on an outer circumferential surface or an inner circumferential surface.

3. The surface texture measurement system of claim 2, wherein the master data generation unit acquires the master piece displacement-induced data regarding the reference asperity output by the detection device when the detection device detects the displacement-induced element regarding the reference asperity while changing the rotational speed of the master piece, and calculates the frequency response characteristics of the master piece displacement-induced data.

4. the master data generating unit generates frequency response data representing the frequency response characteristics related to the reference unevenness by performing a Fourier transform on the master piece displacement caused data; The surface texture measurement system according to any one of claims 1 to 3, wherein the correction unit calculates a true displacement value of the surface unevenness by dividing the measured displacement-induced data that has been Fourier transformed by the frequency response data regarding the reference unevenness.

5. the master data generating unit performs a fitting process using a polynomial function using data in a specified frequency range in the frequency response data obtained by performing a Fourier transform on the master piece displacement caused data, thereby generating the frequency response data after the fitting process; The surface texture measuring system according to claim 4 , wherein the correction unit calculates a true displacement value of the surface unevenness by dividing the measured displacement caused data that has been Fourier transformed by the frequency response data regarding the reference unevenness after fitting processing.

6. the master data generating unit performs fitting processing by a polynomial function on complex values ​​including gain and phase using data in the specified frequency range in the frequency response data related to gain and phase, thereby generating the frequency response data after fitting processing related to gain and phase; The surface texture measurement system of claim 5, wherein the correction unit calculates a true displacement value of the surface unevenness by dividing the measured displacement caused data, which has been Fourier transformed in a complex value including gain and phase, by the frequency response data regarding the reference unevenness after fitting processing.

7. the master data generation unit uses the frequency response data after the fitting process to generate a transfer function model that represents a relationship between an input and an output when a waveform represented by a true displacement-causing element obtained from the shape of the reference unevenness is input and the frequency response data after the fitting process is output; The correction unit is generating transformed frequency response data for the reference asperity using the transfer function model to correspond to a sampling frequency at which the workpiece was ground; 7. The surface texture measuring system according to claim 5, further comprising: a measuring section for measuring the surface irregularity based on the measured displacement; a measuring section for measuring the surface irregularity based on the measured displacement;

8. The surface texture measurement system according to any one of claims 1 to 7, wherein the detection device detects the displacement value in the unevenness height direction at the detection position as the displacement-causing element when moving the detection position along the uneven surface of the detection object, and outputs time-series data regarding the displacement value as the displacement-causing data.

9. The surface texture measurement system according to any one of claims 1 to 7, wherein the detection device has a contactor that contacts the uneven surface of the object to be detected, detects the acceleration of the contactor as the displacement-causing element when the contactor is moved along the uneven surface of the object to be detected, and outputs time-series data relating to the acceleration as the displacement-causing data.

10. The detection device includes: a displacement detection device that detects, when a detection position is moved along the uneven surface of the detection object, a displacement value in an unevenness height direction at the detection position as the displacement-causing element, and outputs time-series data relating to the displacement value as the displacement-causing data; an acceleration detection device that detects acceleration of a contactor that comes into contact with the uneven surface of the detection object as the displacement-induced element when the contactor is moved along the uneven surface of the detection object, and outputs time-series data related to the acceleration as the displacement-induced data; Equipped with The master data generation unit acquiring time series data relating to the displacement value output by the displacement detection device using the master piece as the detection object as a first master piece displacement data, and calculating a first frequency response characteristic of the first master piece displacement data; obtaining time series data relating to the acceleration output by the acceleration detection device using the master piece as the detection object as master piece acceleration data, calculating second master piece displacement data by displacing the master piece acceleration data, and calculating a second frequency response characteristic of the second master piece displacement data; The correction unit is obtaining time series data relating to the displacement value output by the displacement detection device with the workpiece as the detection object as first measured displacement data; obtaining time series data relating to the acceleration outputted by the acceleration detection device as measured acceleration data, the workpiece being the detection object; Calculating second measured displacement data by displacing the measured acceleration data; correcting the first measured displacement data using the first frequency response characteristic; correcting the second measured displacement data using the second frequency response characteristic; Calculating a true displacement value of the surface asperity based on the corrected first measured displacement data and the corrected second measured displacement data; the first frequency response characteristic is a transfer function that represents a relationship between input and output when virtual time series data relating to a true displacement value derived from the shape of the reference asperity is input and the first master piece displacement data is output, The surface texture measurement system according to any one of claims 1 to 7, wherein the second frequency response characteristic is a transfer function that represents the relationship between input and output when virtual time series data relating to true displacement values ​​derived from the shape of the reference asperity is input and the second master piece displacement data is output.

11. The surface texture measurement system according to claim 10, wherein the correction unit calculates a true displacement value of the surface asperity based on the first measured displacement data after correction in a first frequency range used and the second measured displacement data after correction in a second frequency range used that is different from the first frequency range used.

12. The master data generation unit generating first frequency response data representing the first frequency response characteristic obtained by performing a Fourier transform on the first master piece displacement data; performing a fitting process using a polynomial function using data in a first specified frequency range in the first frequency response data to generate the first frequency response data after fitting process; generating second frequency response data representing the second frequency response characteristic obtained by performing a Fourier transform and displacing the master piece acceleration data; performing a fitting process using a polynomial function using data in a second specified frequency range in the second frequency response data to generate the second frequency response data after the fitting process; The correction unit is Calculating the corrected first measured displacement data by dividing the first measured displacement data that has been subjected to the Fourier transform by the first frequency response data that has been subjected to the fitting process; Calculating the corrected second measured displacement data by dividing the second measured displacement data that has been subjected to the Fourier transform by the second frequency response data that has been subjected to the fitting process; The surface texture measuring system according to claim 11 , further comprising a step of calculating a true displacement value of the surface asperity based on the corrected first measured displacement data and the corrected second measured displacement data.

13. the first use frequency range and the first designated frequency range are different, The surface texture measurement system of claim 12 , wherein the second operating frequency range and the second designated frequency range are different.

14. The surface texture measuring system according to any one of claims 1 to 13, wherein the detection device is provided in a sizing device that measures the outer diameter of the workpiece in the grinding device.

15. 15. The surface texture measuring system according to claim 1, wherein the correction section converts the true displacement value of the surface unevenness into image output data, and outputs the image output data to an image output device.

Images