Patent Publication Number: US-10775166-B2

Title: Shape evaluation method and shape evaluation apparatus

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a U.S. National Stage Application of International Patent Application No. PCT/JP2016/053074, filed on Feb. 2, 2016, which claims priority to Japanese Application No. 2015-021309, filed on Feb. 5, 2015, which are hereby incorporated by reference in the present disclosure in its entirety. 
     FIELD OF THE INVENTION 
     The present invention relates to a shape evaluation method and a shape evaluation device of a target object. 
     BACKGROUND OF THE INVENTION 
     The quality of the surface of the workpiece is evaluated in a workpiece machined by a machine tool or the like. The quality of the surface affects not only the aesthetic appearance of the surface as seen by a person but also the design as seen by a person. For example, when the quality of the surface is poor, lines and patterns may be visible in undesired areas. In particular, when the object to be evaluated is a mold, the shape of the surface of the mold is transferred to many products manufactured. The shape of the surface of the mold is important, and it is preferable to increase the quality as seen by a person. The quality of such a surface can be evaluated by measuring the surface roughness or the like with a measuring instrument. 
     As a method for evaluating the quality of a surface, a method for evaluating the quality of the surface based on an image obtained by photographing the surface of the object is known. For example, there is known a method including photographing the surface of an object to generate image data, performing frequency analysis of a change in the brightness obtained from the image data, and performing evaluation based on a frequency component that can be visually recognized by a person (see Patent Literature 1 and Patent literature 2). 
     CITATIONS LIST 
     Patent Literature 
     [Patent literature 1] Japanese Unexamined Patent Publication No. H10-96696 
     [Patent literature 2] Japanese Unexamined Patent Publication No. 2011-185659 
     BRIEF SUMMARY OF THE INVENTION 
     In machining with a machine tool or the like, the surface may appear to be rough as seen by a person, although it is within the allowable range in the evaluation of the surface roughness or the like. Alternatively, unwanted polygonal lines or the like may appear in the processed workpiece, which may be greatly different from the desired design. On the contrary, although the surface roughness evaluation is out of the allowable range, the surface may look beautiful to the eyes of the person who sees the surface. Such quality as seen by a person is referred to as a surface quality. Evaluation of the surface quality may not match the evaluation of the surface roughness or the like of the conventional determination method. 
     According to the method described in Japanese Unexamined Patent Publication No. H10-96696 or the like, an actual product is photographed in order to obtain image data. Therefore, there is a problem that it may not be determined whether or not a visual problem occurs until a product to be evaluated is actually manufactured. In addition, the state of light at the time of photographing and the characteristics of the camera used for photographing affect the result of the evaluation of the surface, so that the evaluation result may not match with the visual evaluation made by a person when the person actually sees the product. 
     In particular, there is a problem that it may not be determined whether the shape is intentionally changed at the time of designing the product or the shape is changed due to error in the manufacturing process. For example, there is a problem that whether the shape is a corner portion (character line) intentionally formed by the design when the corner portion is formed in the product or whether the shape is a corner portion generated due to error in the manufacturing process may not be determined. 
     It is an object of the present invention to provide a shape evaluation method and a shape evaluation device capable of evaluating the quality of a surface of an object visually felt by a person. 
     A shape evaluation method according to the present invention is a shape evaluation method for evaluating a shape on a surface of the target object, including a step of storing design data having a design shape configured during designing of a target object, a step of storing evaluation target data having an evaluation target shape which is a target of evaluation of the target object, a shape error calculation step of calculating a shape error on the basis of the design shape and the evaluation target shape, a visible error detection step of detecting a visible shape error from the calculated shape error on the basis of the shape error calculated in the shape error calculation step and visual characteristic data defined in advance, and a step of identifying a position where a visible shape error occurs. 
     In the above invention, the shape error calculation step may include a step of calculating an error in a normal direction change rate serving as the shape error by subtracting the normal direction change rate of the design shape from the normal direction change rate of the evaluation target shape. 
     In the above invention, the visual characteristic data may include first visual characteristic data relating to a spatial frequency and second visual characteristic data relating to a magnitude of the error in a normal direction change rate, and the visible error detection step may include a step of removing a component of the spatial frequency that may not be seen from the error in the normal direction change rate on the basis of the first visual characteristic data, and a step of determining whether or not there is any error in the normal direction change rate that can be seen on the basis of the second visual characteristic data. 
     In the above invention, the first visual characteristic data may include a determination value of the spatial frequency that is set on the basis of a border where a change in a shape can be recognized when a person sees the first test object having the shape of which visual resolution is to be evaluated on the surface thereof, and the second visual characteristic data may include a determination value of the error in the normal direction change rate that is set on the basis of a border where a change in a shape can be recognized when a person sees the second test object having the shape of which visibility limitation of the normal direction change rate is to be evaluated on the surface thereof. 
     In the above invention, the first test object may have the shape of the surface having protrusions and recesses in a form of streaks of which interval gradually decreases, and the second test object may have a ridgeline of which normal direction changes on the surface thereof, and have such the shape that the normal direction change rate continuously changes at the ridgeline along a direction in which the ridgeline extends. 
     A shape evaluation device according to the present invention is the shape evaluation device evaluating a shape on a surface of a target object, and the shape evaluation device includes a design data storage part storing design data having a design shape configured during designing of the target object, an evaluation target data storage part storing evaluation target data having an evaluation target shape which is a target of evaluation of the target object, a shape error calculation part calculating a shape error on the basis of the design shape and the evaluation target shape, a visible error detection part detecting a visible shape error from the calculated shape error on the basis of the shape error calculated by the shape error calculation part and visual characteristic data defined in advance, and a position identifying part identifying a position where the visible shape error occurs. 
     In the above invention, the visual characteristic data may include first visual characteristic data relating to a spatial frequency and second visual characteristic data relating to a magnitude of a shape error, the shape error calculation part may be formed to calculate an error in a change rate of the shape, and the visible error detection part may include a spatial frequency processing part removing a component of the spatial frequency that may not be seen from the error in the change rate of the shape on the basis of the first visual characteristic data and an error determination part determining whether or not there is any error in the change rate of the shape that can be seen on the basis of the second visual characteristic data. 
     According to the present invention, a shape evaluation method and a shape evaluation device capable of evaluating the quality of a surface of an object visually felt by a person can be provided. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a block diagram of a shape evaluation device according to an embodiment. 
         FIG. 2  is a flowchart of a shape evaluation method according to the embodiment. 
         FIG. 3  is a schematic cross-sectional view illustrating a design shape and an evaluation target shape for which evaluation is made according to the embodiment. 
         FIG. 4  is an explanatory diagram illustrating a method for obtaining the angle in a normal direction from coordinate information. 
         FIG. 5  is a perspective view of first test object according to the embodiment. 
         FIG. 6  is a graph illustrating the interval of streaks with respect to a position in the Y axis of the first test object. 
         FIG. 7  is a graph illustrating the frequency of occurrence of observers with respect to a visibility limitation of an interval of streaks in the first test object. 
         FIG. 8  is a perspective view of second test object according to the embodiment. 
         FIG. 9  is a graph illustrating a relationship between a position in the X axis of the second test object and a normal direction change rate. 
         FIG. 10  is a graph illustrating the frequency of occurrence of observers with respect to a visibility limitation of the normal direction change rate in the second test object. 
         FIG. 11  is a graph illustrating a relationship between the position of the evaluation target shape and an error in the normal direction change rate. 
         FIG. 12  is a graph illustrating a relationship between the position of the evaluation target shape and the error in the normal direction change rate after the high frequency component is removed. 
         FIG. 13  is a block diagram of first processing system according to the embodiment. 
         FIG. 14  is a block diagram of second processing system according the an embodiment. 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     A shape evaluation method and a shape evaluation device according to an embodiment will be explained with reference to  FIG. 1  to  FIG. 14 .  FIG. 1  shows a block diagram of a shape evaluation device according to the present embodiment. In the present embodiment, an object to be evaluated is referred to as a target object. The shape evaluation device compares the shape of a processed target object with the shape of a target object in design. 
     The shape evaluation device  10  is a device that evaluates the shape of the surface of the target object. Examples of target objects to be evaluated include industrial products such as molds, mechanical parts, automobile bodies, or articles which need design. The shape evaluation device  10  is constituted by, for example, an arithmetic processing device including a CPU (Central Processing Unit), a RAM (Random Access Memory), and ROM (Read Only Memory) and the like connected to each other via a bus. 
     The shape evaluation device  10  according to the present embodiment receives design data  25  and evaluation target data  26 . The shape of the target object to be processed is determined with a CAD (Computer Aided Design) device and the like. A design shape which is a shape of a target object in design is defined in the design data  25 . 
     An evaluation target shape which is a shape of the target to be evaluated is defined in the evaluation target data  26 . The shape data of the processed target object can be employed as the evaluation target data  26 . For example, virtual shape data obtained by simulation simulating the processing procedure can be used as the evaluation target data  26 . Alternatively, the evaluation target data  26  may be shape data in which the shape of the surface obtained by actually processing the target object is set. 
     The design data  25  and the evaluation target data  26  can include a two-dimensional coordinate value relating to the shape of the surface or a three-dimensional coordinate value relating to the shape of the surface. Alternatively, the design data  25  and the evaluation target data  26  may include information about a normal vector relating to a shape of a surface or information about a normal direction change rate. In the present embodiment, coordinate data including two-dimensional coordinate values will be used and explained as an example of the design data  25  and the evaluation target data  26 . 
     The shape evaluation device  10  includes a data storage part  11  that stores the design data  25  and the evaluation target data  26 . The data storage part  11  functions as a design data storage part for storing the design data  25 . The data storage part  11  functions as an evaluation target data storage part for storing evaluation target data  26 . 
     The shape evaluation device  10  includes a shape error calculation part  12 . The shape error calculation part  12  calculates the error in the shape defined in the evaluation target data  26  with respect to the shape defined in the design data  25 . More specifically, the shape error calculation part  12  calculates a shape error which is an error between the design shape and the evaluation target shape. 
     The shape evaluation device  10  includes a visible error detection part  15 . The shape error calculated by shape error calculation part  12  is input to the visible error detection part  15 . The visible error detection part  15  detects a shape error that can be discriminated by a person, on the basis of the shape error calculated by the shape error calculation part  12  and visual characteristic data determined in advance. When the shape error is large, the observer can identify that the evaluation target shape is different from the design shape. However, when the shape error is small, the observer may not identify the difference. The visible error detection part  15  detects a shape error that affects vision from the shape error calculated by the shape error calculation part  12 . 
     The shape evaluation device  10  includes a position identifying part  18 . Information about the visible shape error that is detected by the visible error detection part  15  is inputted to the position identifying part  18 . The position identifying part  18  identifies the position where the visible shape error occurs in the target object. 
     The shape evaluation device  10  includes an output part  19 . A device configured to convey an evaluation result to a worker may be employed as the output part  19 . The output part  19  according to the present embodiment is a display part for displaying an evaluation result of a shape. When a visible shape error exists, the display part can display the position where the shape error in the target object exists. Alternatively, the output part  19  may be formed to send the evaluation result to another device. 
       FIG. 2  shows a flowchart of a shape evaluation method according to the present embodiment. The control illustrated in  FIG. 2  is performed by the shape evaluation device  10 . In this case, with reference to  FIG. 1  and  FIG. 2 , the error in the normal direction change rate is calculated as a shape error. When the error in the normal direction change rate is large, a person recognizes that the evaluation target shape is visually different from design shape. The error in the normal direction change rate preferably corresponds to the effect visually given when the observer sees the target object. 
     The shape error calculation part  12  performs a shape error calculation step for calculating a shape error which is an error between the design shape and the evaluation target shape. The shape error calculation part  12  includes a change rate calculation part  13  and a change rate error calculation part  14 . 
     In step  81 , the change rate calculation part  13  calculates the normal direction change rate at a certain point on the surface of the target object in each of the design shape and the evaluation target shape. In step  82 , the change rate error calculation part  14  calculates the error in the evaluation target shape with respect to the design shape on the basis of the normal direction change rate calculated by the change rate calculation part  13 . 
       FIG. 3  shows a schematic cross-sectional view for explaining the normal direction change rate in each of the design shape and the evaluation target shape. In the present embodiment, the design data  25  and the evaluation target data  26  include two-dimensional coordinate values. In the example as illustrated in  FIG. 3 , the target object  40  is sectioned in a plane parallel to the X axis and the Z axis. A normal vector can be set with predetermined interval on the surface of the target object  40 . The target object  40  is sectioned with every predetermined distance in a plane parallel to the X axis and the Z axis. The normal vectors are set with predetermined interval in each section plane so that the entire surface of the target object can be evaluated. 
     On the surface of the target object  40  of the design shape, a setting point  41   a  is set with interval defined in advance. On the surface of the target object  40  of the evaluation target shape, a setting point  41   b  is set with interval defined in advance. The positions of the setting points  41   b  respectively correspond to the positions of the setting points  41   a.    
     A normal vector n i  perpendicular to the inclination of the surface is set at the setting point  41   a  of the design shape. The normal vector n i  is a normal vector of the i-th setting point  41   a . An angle θ i  of the normal direction can be set for the normal vector n i . In this case, the angle with respect to the Z axis is set as the angle θ i  of the normal direction. A normal vector n ir  perpendicular to the inclination of the surface is set at the setting point  41   b  of the evaluation target shape. An angle θ ir  of the normal direction can also be set for the normal vector n ir . In this case, the angle with respect to the Z axis is set as the angle θ ir  of the normal direction. 
       FIG. 4  shows a schematic view illustrating a method for calculating an angle of the normal direction from coordinate data. A design shape is illustrated as an example on  FIG. 4 . The design shape according to the present embodiment is set by coordinate values. The coordinate values of the i-th setting point  42  and the (i+1)-th setting point  43  are already known. A vector a i  can be set on the basis of the coordinate values of these two setting points  42 ,  43 . The vector a i  is a vector from the setting point  42  to the setting point  43 . A vector perpendicular to the vector a i  can be set as the normal vector n 1 . The angle θ i  of the normal direction at this occasion can be calculated by the following equation (1). 
     
       
         
           
             
               
                 
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             θ i : angle of normal direction at the i-th setting point 
           
         
       
    
     As described above, the angle θ i  of the normal direction can be calculated for the i-th setting point of the design shape. According to similar method, the angle θ ir  of the normal direction can be calculated for the i-th setting point  41   b  of the evaluation target shape. 
     With reference to  FIG. 1  and  FIG. 2 , the change rate calculation part  13  calculates the normal direction change rates at the setting points  41   a ,  41   b . The normal direction change rate is a change rate of angle of the normal direction between two setting points adjacent to each other. For example, the normal direction change rate is a change rate between the angle θ i  of the normal direction and the angle θ 1+1  of the normal direction. The normal direction change rate can be calculated by the following equation (2). The following equation (2) represents the normal direction change rate at the i-th setting point  41   a  of the design shape. The normal direction change rate of evaluation target shape can also be calculated according to a similar method. 
     
       
         
           
             
               
                 
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     Subsequently, in step  82 , the change rate error calculation part  14  calculates the error in the normal direction change rate on the basis of the normal direction change rate of the design shape thus calculated and the normal direction change rate of the evaluation target shape. The error in the normal direction change rate can be calculated by subtracting the normal direction change rate of the design shape from the normal direction change rate of the evaluation target shape. The error in the normal direction change rate serving as the shape error can be calculated by the following equation (3). 
     
       
         
           
             
               
                 
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             θ i : angle of normal direction at the i-th setting point in design shape 
             θ ir : angle of normal direction at the i-th setting point in evaluation target shape 
             E i : error in normal direction change rate 
             x i : coordinate value at the i-th setting point in design shape 
             x ir : coordinate value at the i-th setting point in evaluation target shape 
           
         
       
    
     Subsequently, the visible error detection part  15  performs a visible error detection step for detecting a visible shape error from the calculated shape error. The visible error detection part  15  detects an error visible by a person on the basis of the shape error calculated in the shape error calculation step and visual characteristic data defined in advance. The visible error detection part  15  includes a spatial frequency processing part  16  and an error determination part  17 . The visual characteristic data includes first visual characteristic data on a spatial frequency and second visual characteristic data on the magnitude of an error in normal direction change rate. 
     In step  83 , the spatial frequency processing part  16  performs a step for removing a component of the spatial frequency that may not be recognized from the error in the normal direction change rate. When protrusions and recesses on the surface are finer, a person may not recognize the protrusions and recesses. In other words, when a spatial frequency of protrusions and recesses is high, a person may not distinguish protrusions and recesses appearing on the surface. Similarly, when the spatial frequency of a shape error increases, a person may not distinguish the difference in the evaluation target shape with respect to the design shape. The spatial frequency processing part  16  removes high spatial frequency components exceeding such visibility limitation. 
     In the step of conducting the processing of the spatial frequency, the first visual characteristic data is used. In the present embodiment, the first visual characteristic data is defined in advance by experiment. Hereinafter, the first visual characteristic data will be explained. First test object having a shape of which visual resolution is evaluated on its surface is used for setting of the first visual characteristic data. The first visual characteristic data includes a determination value of a spatial frequency that is set on the basis of a border for recognizing a change in the shape when a person sees the first test object. 
       FIG. 5  shows a perspective view of the first test object for setting the determination value of the spatial frequency. The first test object  31  is formed in a rectangular parallelepiped shape. In the first test object  31 , the surface is formed with a streak-like protrusions and recesses of which interval gradually decreases. Multiple recessed parts  32  are formed on the surface of the first test object  31  so as to extend in the X axis direction. The recessed part  32  has a cross sectional shape in an arc. The recessed parts  32  gradually become shallower toward the positive side in the Y axis direction as indicated by arrow  91 . 
     A streak  33  is formed between recessed parts  32  adjacent to each other. The multiple streaks  33  extend in the X axis direction. The multiple streaks  33  are formed so as to be parallel to each other. The interval between streaks  33  gradually becomes narrower toward the positive side in the Y axis direction as indicated by arrow  91 . 
     When the first test object  31  is formed, for example, a recessed part  32   a  is formed by moving a ball end mill in the direction indicated by arrow  92 . The same ball end mill is used in order to form recessed parts  32 . At this occasion, the depths of the recessed parts  32  gradually change. More specifically, the recessed parts  32  are formed by gradually changing the amount of pick feed when processing is performed with the ball end mill. 
       FIG. 6  is a graph illustrating a relationship between the interval of streaks and the position in the Y axis of the first test object. It is understood that as the position in the Y axis increases, the interval of streak  33  is narrower. In this example, the intervals of streaks  33  change in a manner of quadratic function. The spatial frequency is a frequency with regard to the length. As represented in the following equation (4), the spatial frequency can be defined as a reciprocal number of the length. 
     
       
         
           
             
               
                 
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     In the first test object  31 , the reciprocal number of the distance between the streaks  33  can be defined as a spatial frequency. In the first test object  31 , the spatial frequency increases toward the direction indicated by arrow  91 . 
     With reference to  FIG. 5  and  FIG. 6 , the first test object  31  is irradiated with light from various directions while the first test object  31  is covered with, for example, a white curtain, so that there is no reflection. Then, the observer observes the first test object  31  from immediately above the first test object  31 . The observer can recognize multiple streaks  33  in an area where the distance between the streaks  33  is large. However, when the distance between the streaks  33  decreases, it is impossible for the observer to recognize multiple streaks  33 . The point where the streaks  33  may not be recognized is a visual resolution by a person. 
     As described above, the first test object  31  has a shape of which visual resolution is to be evaluated. In the example illustrated in  FIG. 5  and  FIG. 6 , the pick feed amount is varied exponentially from 0.45 mm to 0.11 mm. In general, the visual resolution is expressed as a viewing angle. The viewing angle depends on the size of the target object and the distance between the target object and the viewpoint. Therefore, the interval between the streaks  33  can be defined on the basis of the distance where the product to be evaluated is observed. In this case, for reference, a visual acuity 1.0 corresponds to a viewing angle of 1/60 degrees in the visual resolution. 
     In the present embodiment, the observer observes the first test object from a distance defined in advance. The observer specifies the position in the Y axis where the observer may not see the pattern of the streaks  33  on the surface. With a measuring instrument, the position of this point in the Y axis is measured. Then, the distance between the streaks  33  is determined on the basis of the position in the Y axis. The spatial frequency of the visibility limitation of the observer can be determined on the basis of the distance between the streaks  33 . In the present embodiment, the spatial frequency of the visibility limitation is measured for each of multiple observers. Then, the average value of the spatial frequencies of the visibility limitations of multiple observers is calculated. This average value is set as the determination value of the spatial frequency. 
       FIG. 7  shows a graph of a result obtained by observing the first test object. The example as illustrated in  FIG. 7  represents an evaluation result when the first test object  31  is observed from the distance of 25 cm with a brightness in an ordinary office. The visual resolution varies depending on the observer. In the example as illustrated in  FIG. 7 , the average of the visual resolution is 0.27 mm, and the viewing angle is 0.07 degrees. More specifically, when the distance between the streaks  33  is 0.27 mm, this can be determined that many people may not distinguish the pattern of the streaks  33 . The spatial frequency of the visibility limitation at this occasion is 1/0.27 [1/mm], and this value is employed as the determination value of the spatial frequency. 
     In the present embodiment, the average value of multiple observers is adopted as the interval at which the pattern of streaks  33  disappear, but the embodiment is not limited to this, and the result of the observer can be processed statistically. For example, a margin may be taken into consideration, and interval obtained by adding a certain value to the average value of the measurement results of the observers may be employed. 
     The visual resolution can be quantitatively set by employing the first test object  31 . The visual resolution can be set in accordance with the type of the person who observes the target object. The visual resolution is determined by the refractive index of the eyeball and the size of the photoreceptor cell of the retina of the person. For this reason, it is thought that large individual differences are unlikely to occur. However, for example, the best easy-to-see focal length is different between near-sighted and far-sighted persons, and therefore, the visual resolution may be different when the target object arranged at the same distance is seen. 
     Therefore, for example, a visual resolution that is set by the child observers can be used for children&#39;s products, and a visual resolution that is set by the elderly observers can be used for the product used by the elderly people. As described above, a type of persons who actually observes the target object as the observer is selected, and the visual resolution is set, whereby the surface quality of actual products can be improved. 
     The visual resolution depends on the distance from the target object. Therefore, when the measurement is performed with the observers, it is preferable to perform the measurement at a distance corresponding to a distance where the actual product is seen by a person. 
     The first test object is not limited to this aspect, but any test object for setting the visual resolution can be employed. For example, the interval between streaks may be linearly changed in the Y axis direction. In the above first test object, the pattern of streaks are linearly formed in the plan view, but the embodiment is not limited to this, and the pattern of streaks are formed in curves in the plan view. 
     The first test object according to the present embodiment is formed with the ball end mill. When the tool diameter of the ball end mill is changed, the sectional shape of the recessed part changes. The inventors made multiple first test objects using multiple ball end mills with different tool diameters. During the period of making one first test object, the inventors used the same ball end mill without changing the ball end mill. As a result, it is understood that, even if the tool diameter of the ball end mill is different, the visual resolution of the observer is almost constant. 
     As illustrated in  FIG. 1 , based on the spatial frequency of the visibility limitation obtained as described above, the spatial frequency processing part  16  removes the spatial frequency component exceeding the visibility limitation from the error in the normal direction change rate. An example of a method for removing the component of the spatial frequency exceeding the visibility limitation includes using a publicly known filter such as low pass filter. Alternatively, the error in the normal direction change rate is transformed with Fourier transform, and the frequency component larger than the visibility limitation is removed from the result obtained through Fourier transform. Thereafter, the error in the normal direction change rate from which the component of the spatial frequency that may not be seen is removed can be obtained with inverse Fourier transform. 
     Alternatively, with respect to  FIG. 3 , a desired high frequency component can be removed by calculating the average value of the errors in the normal direction change rates while using multiple setting points before and after each of the setting points  41   b . The average value of the errors in the normal direction change rates at the setting points before and after the i-th setting point is adopted as the error in the normal direction change rate at the i-th setting point from which the high frequency component has been removed. The error in the normal direction change rate from which the high frequency component has been removed can be expressed by the following equation (5). 
     
       
         
           
             
               
                 
                   
                       
                   
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             E i : Error in the normal direction change rate at the i-th setting point 
             N: The number of (even number of) setting points for calculating average value 
             E ivis : Error in the normal direction change rate from which high frequency component has been removed 
           
         
       
    
     In this case, the number N of setting points for calculating the average value E ivis  can be calculated on the basis of the distance between setting points and the spatial frequency of the visibility limitation. The number N of setting points for calculating the average value E ivis  can be calculated according to the following equation (6). 
     
       
         
           
             
               
                 
                   [ 
                   
                     Formula 
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             f: Spatial frequency of visibility limitation 
             Δx: Distance between setting points 
             N: The number of setting points 
           
         
       
    
     As described above, the high frequency components beyond the visibility limitation can also be removed by calculating the moving average value of the errors in the normal direction change rates. Errors related to fine protrusions and recesses which may not be recognized by a person can be eliminated. 
     By the way, it is known that vision recognizes the contrast of the surface of the target object, i.e., the change in brightness. The brightness of the surface of the target object is determined by the relationship between the orientation of the surface, the light source, and the position of the viewpoint. The change of the brightness of the surface of the target object depends on the change in the normal direction of the surface. When the change in the normal direction is high, the change of the brightness of the surface of the target object is also great. Therefore, the contrast that the person can visually recognize, i.e., the change rate of the brightness, can be evaluated upon being replaced with the normal direction change rate. By quantifying the visibility limitation of the normal direction change rate of the surface of the target object, an evaluation can be performed to determine whether or not there is a visual problem on the surface. 
     With reference to  FIG. 1  and  FIG. 2 , in step  84 , the error determination part  17  performs a step of determining whether or not the visible error in the normal direction change rate is present on the basis of the second visual characteristic data. When the error in the normal direction change rate is greater than the determination value, a person recognizes that the evaluation target shape is different from the design shape. In other words, a person can determine that the evaluation target shape includes a part that is recognized as being different from the design shape. 
     The second visual characteristic data is data relating to the magnitude of the error in the normal direction change rate. In the present embodiment, the second visual characteristic data includes a determination value of the error in the normal direction change rate that is set on the basis of a border at which a person can recognize the change in the shape when the person sees the second test object. The second test object has, on the surface, a shape for which the visibility limitation of normal direction change rate is evaluated. 
       FIG. 8  shows a perspective view of the second test object for setting the second visual characteristic data. The second test object  35  is formed in a rectangular parallelepiped shape. The second test object  35  has a shape in which two planes intersect with each other. The second test object  35  has a ridgeline  36  extending in the Y axis direction that is formed when the two planes intersect with each other. In the ridgeline  36 , the direction in which the plane extends changes. The second test object  35  has such shape that the normal direction change rate of the ridgeline  36  continuously varies along the direction in which the ridgeline  36  extends. 
       FIG. 9  shows a graph of the normal direction change rate with respect to the position in the X axis near the ridgeline. The position of the top line of the ridgeline  36  in the X axis is zero.  FIG. 9  illustrates a graph passing through positions y a , y b  in the Y axis direction of the second test object  35 . For the second test object  35 , the cycle of the shape change is approximately 0.5 mm. With reference to  FIG. 8  and  FIG. 9 , the normal direction change rate increases as advanced toward the direction indicated by the arrow  93 . The position y a  in the Y axis is a position at one of the end faces of the second test object  35 , and the magnitude of the normal direction change rate is the highest at position y a . At the position y b  at the center of the second test object  35 , the normal direction change rate is smaller than that at the position y a . The position y c  in the Y axis is a position at the other of the end faces of the second test object  35 , and the normal direction change rate is zero at the position y c . As described above, one of the planes is formed such that the inclination of the plane gradually increases as advanced toward the direction indicated by the arrow  93 . In the present embodiment, the normal direction change rate is changed from 0 [rad/mm] to −0.013 [rad/mm] in an exponential manner. The state of the change of the normal direction change rate is not limited to this aspect, and, for example, the normal direction change rate may be changed linearly. 
     When the observer observes the second test object  35 , the observer can visually recognize the ridgeline  36  in a portion where the normal direction change rate is high. On the other hand, the observer may not visually recognize the ridgeline  36  in a portion where the normal direction change rate is low. The limitation where the observer can see the ridgeline  36  can be defined as the visibility limitation of the normal direction change rate. 
     The observer specifies the point where ridgeline  36  may not be seen. With a measuring instrument, the position of this point in the Y axis is measured. Then, the visibility limitation of the normal direction change rate can be set based on the position in the Y axis. In the present embodiment, for the second test object  35 , multiple observers observe the second test object  35 . Then, the average value of the visibility limitations of the normal direction change rates observed by multiple observers is employed as the determination value. 
       FIG. 10  shows a graph of the frequency of occurrence with respect to a visibility limitation of a normal direction change rate when multiple observers see the second target object. The example as illustrated in  FIG. 10  represents a case when the second test object  35  is observed from the distance of 25 cm with brightness in an ordinary office. The visibility limitation of the normal direction change rate involves some variation depending on observers. In the average value of the observes, the normal direction change rate is 0.0045[rad/mm]. In other words, when the normal direction change rate is 0.0045 [rad/mm], a lot of people may not recognize the ridgeline  36 . In the present embodiment, this value is set as the determination value of the error in the normal direction change rate. The method for setting the determination value of the error in the normal direction change rate is not limited to this aspect, and the determination value may be calculated statistically on the basis of the evaluation result of the observers. 
       FIG. 11  shows a graph of the error in the normal direction change rate calculated by the shape error calculation part. The horizontal axis is the position in the X axis, and a certain position is set as zero. It is understood that the error in the normal direction change rate greatly changes at each position. In other words, the error in the normal direction change rate includes a high frequency component. 
       FIG. 12  shows a graph of the error in the normal direction change rate from which the high frequency component is removed by the spatial frequency processing part. The graph is smoother and the high frequency component at each position has been removed in comparison to the graph of  FIG. 11 .  FIG. 12  describes a determination value LE of the error in the normal direction change rate. 
     As described above, when the error in the normal direction change rate of the target object is larger than the human-visible normal direction change rate, a person can recognize that the evaluation target shape is different from the design shape. For this reason, the visibility limitation of the normal direction change rate obtained with the second test object  35  can be used as the determination value LE of the shape error. In the example as illustrated in  FIG. 12 , the determination value LE of the error in the normal direction change rate is 0.0045 [rad/mm] (see  FIG. 10 ). 
     The part exceeding the determination value LE is a part that a person recognizes that the evaluation target shape differs from the design shape. For example, at the position x a , a person can judge that the evaluation target shape differs from the design shape. 
     With reference to  FIG. 1  and  FIG. 2 , in step  84 , the error determination part  17  determines whether or not the error in the normal direction change rate is more than the determination value. When the error in the normal direction change rate is equal to or less than the determination value in all the area in step  84 , the process proceeds to step  86 . In step  86 , the display part displays that there is no visible shape error. When the error in the normal direction change rate is more than the determination value in at least a part of the area in step  84 , the process proceeds to step  85 . 
     In step  85 , the position identifying part  18  identifies the position of the target object where the error in the normal direction change rate is more than the determination value. In the example illustrated in  FIG. 12 , the position x a  is identified. It can be determined that, at the position x a , a visual problem occurs with the shape. Subsequently, the process proceeds to step  86 . In step  86 , the display part displays that there is a visible shape error. The display part displays the position where visible shape error occurs. 
     The second visual characteristic data is preferably made on the basis of the user stratum who mainly use the actual products and the usage environment in the same way as the first visual characteristic data. These visual characteristic data can be made according to the type of a person who uses the product such as visual acuity and age. 
     The method for setting the determination value of the error in the normal direction change rate and the evaluation method during the evaluation can be set on the basis of the visual characteristic desired for the evaluation target shape, the usage state of actual products, and the like. For example, in the above embodiment, the average value of the measurement results of multiple observers is adopted as the determination value, but the embodiment is not limited to this, and a determination value including a margin for the average value may be used. 
     In the above embodiment, the position where the error in the normal direction change rate is more than the determination value is detected, but the embodiment is not limited to this, and, for example, the average value of the errors in the normal direction change rates in a section of several mm may be calculated, and when this average value is more than any other position, it may be determined that the problem is visible to people. Alternatively, when this average value is more than a determination value defined in advance, it may be determined that the problem is visible to people. Still alternatively, with regard to the error in the normal direction change rate, a contrast sensitivity curve including spatial frequency property of vision of a person may be used so as to determine that the problem is visible to people. After the error in the normal direction change rate is weighted with the spatial frequency, it may be determined as to whether or not the error in the normal direction change rate is more than a determination value, and when the error in the normal direction change rate is more than the determination value, it may be determined that the problem is visible to people. 
     In the above embodiment, the visibility limitation of normal direction change rate when the observer sees the second test object  35  is defined. By adopting this method, the visibility limitation of the normal direction change rate can be quantitatively determined. In addition, the second test object is made to have the same color, material, or surface roughness as the actual product, whereby the surface quality as seen by a person can be more accurately determined. Further, the same surface processing as the product is applied, whereby the surface quality can be more accurately determined. According to these methods, the effect caused by difference in the color and texture of the surface of the target object can also be taken into consideration. 
     The determination of the visibility limitation of the normal direction change rate is not limited to the method in which the observer actually sees the second test object. Alternatively, the visibility limitation of the normal direction change rate may be set by allowing the observer to see a picture of the second test object or a display device displaying an image obtained by photographing the second object with a camera. 
     In the above embodiment, the error in the normal direction change rate is determined after removing the high frequency component of the spatial frequency, but the step of removing the high frequency component of spatial frequency may not be performed. For example, when data calculated by a computer such as a simulator is used as evaluation target data, the high frequency component may not be expressed in some cases. In such a case, the step of removing the high frequency component of the spatial frequency may not be performed. 
     The shape evaluation method and the shape evaluation device according to the present embodiment can evaluate the quality of the surface of the target object that people feel visually. In addition, it can be determined whether a brightness change is caused by a shape change intentionally provided in design or a brightness change is caused by a shape error such as manufacturing error. Even if there is no actually produced product, the occurrence of visual problem can be evaluated. For example, as described later, it can be determined whether or not a visual problem occurs in the target object by using a result of processing simulation instead of a measurement result of a shape on a surface of a target object actually processed. 
     In addition, the shape evaluation method and the shape evaluation device according to the present embodiment can separately evaluate the visual resolution based on the spatial frequency and the visibility limitation of the contrast. 
     The visual characteristic data according to the present embodiment includes the first visual characteristic data and the second visual characteristic data. The evaluation accuracy of the surface quality can be improved by making the visual identification data on the basis of the result obtained when a person observes a test object. When the visual characteristic data is made on the basis of actual vision of a person, the evaluation according to the present invention can be matched well with the evaluation based on actual vision. For example, it can be determined whether or not a shape change is intentionally provided with a high degree of accuracy. 
     In the above embodiment, the error in the normal direction change rate is calculated using the normal direction data calculated from two-dimensional coordinate data, but the embodiment is not limited to this, and three-dimensional normal direction data may be used. In other words, in the above embodiment, the design data and the evaluation target data include two-dimensional coordinate information, but the embodiment is not limited to this, and three-dimensional coordinate information may be included. The three-dimensional normal direction change rate can be expressed by the following equation (7) and equation (8). 
     
       
         
           
             
               
                 
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     The design data and the evaluation target data may be not only data including a coordinate value and data including a normal direction but also STL (Standard Triangulated Language) data that can be used by CAD devices and the like. 
     In the present embodiment, the error in the normal direction change rate is calculated as a shape error, but the embodiment is not limited to this, and the shape error calculation part can calculate any shape error in an evaluation target shape with respect to a design shape. For example, with reference to  FIG. 3 , an error in an angle of the normal direction may be used as a shape error. The error in the angle of the normal direction can be calculated by the following equation (9).
 
[Formula 8]
 
 e   θ =θ ir −θ i   (9)
         e 0 : error in angle of normal direction       

     With reference to  FIG. 1 , in the present embodiment, the design data and the evaluation target data are stored in the data storage part, but the embodiment is not limited to this, and a normal direction change rate calculated on the basis of the design data and the evaluation target data may be stored in the data storage part. In this case, the change rate calculation part is provided before the data storage part. The error in the normal direction change rate may be stored in the data storage part. In this case, the shape error calculation part may be arranged before the data storage part. Any of these cases is mathematically equivalent. 
       FIG. 13  shows a block diagram of first processing system according to the present embodiment. The first processing system is provided with the shape evaluation device  10  explained above. In the first processing system, the shape of the workpiece is designed with a CAD (Computer Aided Design) device  51 . The CAD device  51  provides design data  52  of the workpiece to a CAM (Computer Aided Manufacturing) device  53 . The design data  52  of the workpiece is input into the shape evaluation device  10 . 
     The CAM device  53  generates an input numerical value data  54  for driving a numerically controlled machine tool based on the design data  52 . The input numerical value data  54  includes information about a path of the tool relative to the workpiece. An input parameter  57  such as a tool condition and a processing condition is input to the CAM device  53 . The tool condition includes a tool type, a tool diameter, an optimum cutting speed, and the like. The processing condition includes a pick feed amount, a feed speed, a rotation speed of the main shaft, and the like. 
     The first processing system includes a processing simulator  55 . The processing simulator  55  simulates the processing of the machine tool with a computer based on the input numerical value data  54  and the input parameter  57 . The input parameter  57  that is input into the processing simulator  55  includes a control parameter of the simulated machine tool and the like. The processing simulator  55  outputs a simulator output data  56  including information about the shape of the processed workpiece. The simulator output data  56  includes information about a coordinate value of the processed workpiece, information about normal direction, and the like. In the first processing system, the simulator output data  56  corresponds to the evaluation target data. The simulator output data  56  is input to the shape evaluation device  10 . 
     The shape evaluation device  10  determines whether or not visible shape error is included in the shape of the processed workpiece based on the design data  52  and the simulator output data  56 . When visible shape error is included, the worker can change the design of workpiece with the CAD device  51  on the basis of the evaluation result that is output by the output part  19 . Alternatively, the worker can change the input parameter  57  so that the shape of the processed workpiece does not include a visible shape error. 
     As described above, when a track of a tool corresponds to the shape of the surface in processing such as cutting with a numerically controlled machine tool, evaluation target data can be generated with a mathematical model simulating movement of a tool. 
     In the first processing system, the processed shape can be evaluated without performing any actual processing. Alternatively, before performing actual processing, the design shape can be changed and the input parameter can be changed so that any visible shape error is not included in the shaped of the processed workpiece. 
       FIG. 14  shows a block diagram of second processing system according to the present embodiment. The second processing system is different from the first processing system in that a numerically controlled machine tool  60  and a processing object measuring instrument  63  measuring the surface shape of the processing object (workpiece) processed with the machine tool  60  are provided. The input numerical value data  54  that is output by the CAM device  53  is input into the machine tool  60 . The control parameter  62  is input into the machine tool  60 . The control parameter  62  includes a time constant for acceleration and deceleration, backlash compensation, gain in the feedback control of the feed axis, and the like. The machine tool  60  can automatically process workpiece based on control parameter  62  and input numerical value data  54 . The machine tool  60  forms a processing object  61 . 
     The processing object measuring instrument  63  measures the surface shape of the processing object  61 . Examples of the processing object measuring instrument  63  include a roughness measurement device and a three-dimensional measurement device. Then, the processing object measuring instrument  63  generates measurement data  64  on the basis of the measurement result of the shape on the surface of the processing object  61 . The measurement data  64  includes information about a coordinate value, information about a normal direction, and the like. The measurement data  64  corresponds to the evaluation target data. The measurement data  64  is input into the shape evaluation device  10 . 
     The shape evaluation device  10  determines whether or not a visible shape error is included in the shape of the processing object  61  after machining based on the design data  52  and the measurement data  64 . When a visible shape error is included, the worker can change the design of workpiece in CAD device  51  on the basis of the evaluation result that is output by the output part  19 . Alternatively, the worker can change the control parameter  62  so that the shape of the processing object does not include any visible shape error. 
     As described above, the surface shape can also be evaluated quantitatively even when the evaluation target shape is the shape of the actual processing object. In addition, since the evaluation result is quantitatively indicated, it is easy to change the design of the workpiece and the control parameter  62 . 
     Alternatively, the movement track of the tool and the workpiece when the machine tool is driven can be measured while the workpiece is not arranged. The evaluation target data may be made on the basis of the measurement result of movement track. For example, the movement track of the table where the tool or the workpiece is arranged can be measured by a true circle measuring instrument including a ball bar, a grid encoder, a displacement meter, an accelerometer, or the like. The evaluation target data can be generated based on these measurement results. Alternatively, it may be possible to use information about the feedback control implemented in the control device of the machine tool and the like. 
     With this method, it is possible to drive the machine tool so as to perform actual processing. Alternatively, the measurement can be performed with a basic operation of a certain machine tool. The operation of the machine tool in actual processing may be estimated based on the measurement result of the basic operation, and the evaluation target data may be made on the basis of the estimated motion. Even in this method, it is possible to evaluate the surface shape of the processed workpiece without processing any actual workpiece. 
     The shape evaluation method and the shape evaluation device according to the present invention can be used for evaluation of a shape of a product which is to be evaluated through vision of a person. In addition, the shape evaluation method and the shape evaluation device can be used so as to set a shape tolerance during designing and determine a method for solving a problem when the visual problem occurs. 
     In each of the above-mentioned controls, the order of steps can be appropriately changed as long as the function and the action are not changed. The above embodiments can be appropriately combined. In each of the above figures, the same or equivalent parts are denoted with the same reference numerals. The above embodiments are illustrative and do not limit the invention. In the embodiment, changes in the embodiment described in the claims are included. 
     REFERENCE SIGNS LIST 
     
         
         
           
               10  shape evaluation device 
               11  data storage part 
               12  shape error calculation part 
               13  change rate calculation part 
               14  change rate error calculation part 
               15  visible error detection part 
               16  spatial frequency processing part 
               17  error determination part 
               18  position identifying part 
               19  output part 
               25  design data 
               26  evaluation target data 
               31  first test object 
               33  streak 
               35  second test object 
               36  ridgeline 
               40  target object 
               52  design data