JP2000161946A - Method and device for analyzing three-dimensional data - Google Patents

Abstract

PROBLEM TO BE SOLVED: To improve the analyzing efficiency of a method and device for analyz ing three-dimensional data by labeling the peaks and troughs of three- dimensional data at the same time. SOLUTION: The three-dimensional data of a work 14, obtained by means of a roughness measuring machine 10, are supplied to a personal computer 18. The computer 18 binarizes the three-dimensional data into black areas and white areas at a prescribed slice level. Then the computer 18 successively labels the black areas with positive integers, and at the same time, the white areas with negative integers. Since the computer 18 simultaneously labels the black areas corresponding to crests and white areas which correspond to troughs, processing efficiency can be improved.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for analyzing three-dimensional data, and more particularly to a method and an apparatus for analyzing peaks and valleys of a three-dimensional shape of a workpiece obtained by a roughness measuring instrument, a shape measuring instrument, or the like.

[0002]

2. Description of the Related Art Conventionally, there has been known a technique for detecting and correcting the surface roughness of a work with high accuracy. Usually, these analyzes are performed by calculating the arithmetic average roughness Ra, the maximum height Ry, and the load length ratio tp from a roughness curve obtained by scanning the work surface with a stylus.

FIG. 4 shows an example of a roughness curve and an average line of the roughness curve. In the figure, a roughness curve 50 is shown.
Is cut by an average line 52, a substantial part composed of a roughness curve 50 connecting the two adjacent points of the intersection and the average line 52 is a crest 54, and the roughness curve 50 is cut by an average line. The space formed by the roughness curve 50 connecting the two adjacent points of the intersection and the average line 52 is referred to as a valley 56. Then, when such a roughness curve 50 is obtained, a portion corresponding to the reference length L is extracted in the direction of the average line 52, and the absolute value of the deviation from the average line 52 to the roughness curve 50 of the extracted portion is summed. The arithmetic mean roughness Ra is obtained by averaging. That is,

(Equation 1) It is. Also, a reference length L is extracted from the roughness curve 50 in the direction of the average line 52, and the sum of the height Yp from the average line 52 to the highest peak and the depth Yv to the lowest valley bottom of the extracted portion is obtained. By obtaining, the maximum height Ry can be obtained. That is,

## EQU2 ## Ry = Yp + Yv. Further, a reference length L is extracted from the roughness curve 50 in the direction of the average line 52, and the roughness curve 50 of the extracted portion is cut at a cutting level parallel to the peak line (line passing through the highest elevation point in the peak). The load length ratio tp can be obtained by calculating the ratio of the sum (ηp) of the cut lengths obtained when cutting to the reference length. That is,

## EQU3 ## tp = ηp / L * 100. Ra and Ry mainly provide roughness information relating to the height of unevenness on the surface of a two-dimensional work, tp indicates a relationship between a peak portion and a valley portion, and shows wear resistance and slidability of an engine cylinder bore side surface and the like. It is used for evaluation (specify an arbitrary cutting level and determine the ratio of the contact area when wear progresses to that level).

[0004]

As described above, when calculating and analyzing evaluation parameters such as Ra, Ry, and tp based on a roughness curve, peaks and valleys of the roughness curve are removed. Need to be identified. However, in the conventional analysis method, first, only the peaks are identified, the cut area, the cut volume, the number of peaks, and the like are analyzed, and then the data is inverted and the same process is repeated to identify the valleys. And
Peaks and valleys could not be identified and analyzed at the same time. For example, in the case of a surface contact problem, when a peak contacts a partner's object and a valley holds lubricant, it is necessary to identify and analyze the peak and the valley at the same time. Such demands could not be met, and efficient analysis was not possible.

[0005] Hereinafter, labeling of peaks in a conventional analysis method (grouping and labeling such as numbers are given)
The processing will be described.

First, the three-dimensional data of the work surface obtained by the roughness measuring machine is cut at a predetermined height (average surface), and the data above the average surface is binarized to black, and the rest to white. FIG. 8 shows an example of the shape data binarized in this way. The hatched portions in the figure represent black. Note that, for convenience of explanation, the two-dimensional shape data array is given the first row, second row,.

Next, scanning is sequentially performed from the left of the first row of the two-dimensional array of shape data. If the data value is black, 1 is added to the data point and the connected element (this is called a black area). Assign a number. If the black data exists again after the white data, a number 2 is assigned to the black data. Hereinafter, numbers are sequentially assigned to the black areas in the same manner.

Next, scanning is sequentially performed from the left in the second row,
As in the line, successive numbers are assigned to the black area,
If the numbered black area is linked to the black area of the row before the numbering, the same number is assigned to the number assigned to the black area of the previous row. Therefore, FIG.
As shown in (a), numbers 1 and 2 are assigned to the black area in the second row scan, and numbers 3 and 4 are assigned to the black area in the third row scan. Even in the case shown in FIG.
As shown in (1), the black area 3 is connected to the black area 1 and the number 3 is changed to the number 1, and the black area 4 is connected to the black area 2 and the number 4 is changed to the number 2.

On the other hand, when one black area is connected to two or more different numbers in the scanning process, the smaller number in the previous row is used as the number of the black area, and the larger number is used as the number of the black area. Connection information indicating that the black region is connected to the smaller number is stored. For example, as shown in FIG. 10A, numbers 5 and 6 are assigned to the black area in the scanning of the fourth row (these are connected to the numbers 1 and 2 of the previous row, respectively, so that the numbers 1 and 2 are respectively connected). If the number 7 is assigned to the black area in the scanning of the fifth line, the number 7 (changed to number 1) and number 6 (changed to number 2) are assigned to the black area of number 7 Are connected to the two black areas, the same number as the smaller number 5 (changed to number 1) is assigned,
As a result, the result is as shown in FIG. And the number 2
For the black area of (No. 6 was initially assigned), connection information indicating that the black area is connected to the black area of No. 1 is stored.

The above processing is executed for all the rows, and finally, the number of the black area storing the connection information is changed to the number of the connection destination. This completes labeling for all peaks. By the way, in the case of FIG. 8, only the ridges finally numbered 1 exist, and when independent ridges exist separately, numbers 1 and 2 are assigned to these ridges. Will be. And
After the processing of the peaks is completed, the white and black data are inverted, and the same processing is repeated again to label the valleys. As described above, conventionally, the peaks and the valleys cannot be labeled at the same time, and it takes time to analyze the peaks and the valleys.

The present invention has been made in view of the above-mentioned problems of the prior art, and has as its object to collectively collect peaks and valleys in order to simultaneously analyze peaks and valleys of a roughness curve. An object of the present invention is to provide a method of identifying and assigning the same label to roughness data belonging to the same crest or valley so that they can be grouped.

[0012]

According to a first aspect of the present invention, there is provided a method for analyzing three-dimensional data corresponding to a surface shape of a three-dimensional work, comprising: A step of discriminating the three-dimensional data into peak data and valley data, grouping the peak data and sequentially assigning a label, and grouping the valley data to be different from the label of the peak. And a grouping step of sequentially assigning types of labels, wherein the peaks and the valleys are collectively labeled and grouped. Rather than assigning a label to a peak and then assigning a label to a valley, the processing can be speeded up by assigning labels to the peak and the valley in a lump. The peak label and the valley label can be distinguished by using different types of labels.

According to a second invention, in the first invention, in the grouping step, labels having different codes are used for the peak data and the valley data. By using labels with different codes, peaks and valleys can be easily distinguished while labeling the peaks and valleys collectively.

In a third aspect based on the first aspect, in the grouping step, a label is assigned by sequentially assigning a positive integer to the peak data, and a negative is assigned to the valley data. The label is assigned by sequentially assigning integers of. By labeling using a positive integer for the peak and a negative integer for the valley, the peak and the valley can be clearly distinguished, and the labeling process can be simplified by using the numbers.

In a fourth aspect based on the first aspect, the predetermined height threshold includes a threshold for the peak and a threshold for the valley. Rather than using a single value as the predetermined height threshold, by setting a threshold for determining a peak and a threshold for determining a valley individually, Crests and valleys can be reliably determined.

According to a fifth aspect of the present invention, there is provided an apparatus for analyzing three-dimensional data corresponding to a surface shape of a three-dimensional work,
Determining means for determining the three-dimensional data into peak data and valley data at a predetermined height threshold, and sequentially assigning a first type of label to a group of the peak data, Labeling means for sequentially applying a second type of label to a set, and calculating means for calculating characteristic parameters of the three-dimensional work using peak data and valley data labeled by the labeling means. It is characterized by.

[0017]

Embodiments of the present invention will be described below with reference to the drawings.

FIG. 1 shows the configuration of a three-dimensional data analysis system according to the present embodiment. This system is
Roughness measuring device 10 and personal computer 1 for analyzing data (roughness curve) obtained by roughness measuring device 10
8.

The roughness measuring apparatus 10 includes a work mounting table 12 provided on the measuring apparatus main body and a stylus 16 for scanning a surface of a work 14 mounted on the work mounting table 12. The work mounting table 12 is configured to be movable in the direction of the arrow in the figure, and the work 1 is held in a state where the stylus 16 touches the work surface.
The workpiece surface is scanned by moving 4 in the direction of the arrow. The three-dimensional data (roughness curved surface) obtained by scanning is output to the personal computer 18.

FIG. 2 shows how the stylus 16 scans the surface of the work 14. The direction in which the surface roughness appears largest on the surface of the work 14 (the direction of the arrow in the figure)
To obtain three-dimensional data. The direction in which the surface roughness appears most is, for example, a direction perpendicular to the cutter mark on the machined surface.

The personal computer 18 analyzes the three-dimensional data output from the roughness measuring device 10 and outputs the above-mentioned various parameters (Ra, Ry, tp, etc.). When these parameters are output, peaks and valleys of the three-dimensional data are simultaneously labeled to increase the efficiency of the subsequent processing. Hereinafter, the labeling process in the personal computer 18 will be described in detail.

FIG. 3 shows a flowchart of the labeling process executed by the personal computer 18. First, a slice level for determining a peak and a valley of three-dimensional data is set (S101). Usually, this slice level is set to the average plane. Then, the three-dimensional data is cut at the set slice level, and a region above the slice level is binarized into black and a region smaller than the slice level is binarized into white (S102). Instead of setting the slice level to the average plane as described above, it is also possible to use a slice level for a peak and a slice level for a valley individually, and (slice level for a peak)>
(Slice level for the valley).

FIG. 5 shows an example of three-dimensional data binarized using slice levels. For convenience of explanation, the shape data is the same as the shape data shown in FIG.

Next, the row number counter i is initialized to 1 (S103). The i-th row of the two-dimensional data array is scanned, and the number 1 (+1) is assigned to the black area and -1 is assigned to the white area. Attach. If black exists next to black and a black area appears again, the number 2 is assigned. If black exists next to white and white appears again, the number 2 is assigned ( S104). That is, a positive integer (first type) is sequentially assigned to the black area, and a negative integer (second type) is assigned sequentially to the white area.

FIG. 6 shows an example in which the first to third lines are numbered. In the first row, since all data is white, a number -1 is assigned to this white area. For the second row, the number 2 is assigned to the first white area that is scanned from the left, the number 1 is assigned to the next black area, the number 3 is assigned to the next white area, and the next black area is assigned. Number 2 is assigned to the area, and number-4 is assigned to the next white area. For the third row, a number -5 is assigned to the first white area that scans from the left, a number 3 is assigned to the next black area, and a number -6 is assigned to the next white area. The number 4 is assigned to the black area of No., and the number -7 is assigned to the next white area.

Then, if it is linked to the region of the (i-1) th row numbered before, that is, if it is a black region, (i
-1) It is determined whether the line is connected to the black region on the line or, if it is a white region, whether the line is connected to the white region on the line (i-1) (S
105) If it is linked, it is further determined whether or not it is linked to two or more different numbered areas (S106). If the area is linked to one area of the (i-1) th row to which a number has already been assigned, the number of the area is changed to the number of the (i-1) th row (S107).

Therefore, referring to the example of FIG. 6, the white area of the second row, number-2, is linked to the white area of the first row, number-1, so the number is changed from -2 to -1. Since the white area of number-3 is linked to the white area of number-1 in the first row, the number is changed from -3 to -1 and the white area of number-4 is the number in the first row. The number is changed from -4 to -1 because it is linked to the white area of -1.
The white area of the third line with the number -5 is the second area with the number -2.
The number is changed from -5 to -1 because it is linked to the white area (changed to number -1), and the white area of number -6 is changed to number -3 (changed to number -1) in the second row. Is changed from −6 to −1, and the white area with number −7 is the white area with number −4 (changed to number −1) on the second line. And the number is-
It is changed from 7 to -1. Regarding the black area of the third row, the black area of the number 3 is connected to the black area of the number 1 of the second row, so the number is changed from 3 to 1, and the black area of the number 4 is changed to 2 rows. Since it is linked to the black area of eye number 2, the number is changed from 4 to 2, resulting in a number as shown in FIG.

On the other hand, if the area is linked to the area having two or more different numbers in S106, the number is changed to the number having the smaller absolute value in the (i-1) th row (S108). Stores connection information indicating that the area is connected to the area with the smaller number in the memory (S109).

The above processing is repeated until the last line (S110, S111), and finally, the area having the connection information stored in the memory in S109 is changed to the smaller number (S112). As a result, peaks connected to each other are assigned the same number (positive integer) and grouped, and similarly, valleys connected to each other are assigned the same number (negative integer) and grouped. And
Labeling ends. After labeling is completed for all peak data and valley data, various characteristic parameters such as Ra, Ry, tp, the number of peaks, and the number of valleys are calculated using these labeling data, and the display device or the printer is used. Output to etc. It should be noted that a plurality of peaks can be identified from the label data by different numbers, and it is also possible to calculate a cut area and a cut volume for each peak by checking an area occupied by the same number. At this time, the peaks and valleys are labeled at the same time, and each peak and each valley can be identified. Therefore, the cutting area and the cutting volume (corresponding to the volume of the hole portion in the case of a valley) can be determined for each peak and each valley. It is possible to calculate and observe the shapes of peaks and valleys (so-called cut surface analysis). In this embodiment, the shape, area, and volume of these cut portions are also included in the characteristic parameters.

As described above, the labeling is performed on the black region (peak) and the labeling is also performed on the white region (valley). The unit can be identified.

The processing shown in FIG. 3 can be realized by installing the program in the personal computer 18 and sequentially executing the program. The program is supplied from an arbitrary storage medium (CD-ROM, FD, DVD, etc.). be able to.

In the present embodiment, labeling is performed by sequentially giving a positive integer to the peak and a negative integer to the valley.
It goes without saying that a negative integer may be given to the peak and a positive integer may be given to the valley, and other symbols (such as alphabets) may be used as labels instead of integers.

In this embodiment, the three-dimensional data has been described by taking the three-dimensional shape data of the work as an example.
The present invention can be applied to analysis of temperature distribution based on three data of X, Y, and t from four-dimensional data obtained by adding temperature data (t) to three-dimensional shape data (X, Y, Z). It is possible.

[0034]

As described above, according to the present invention,
The peaks and the valleys can be collectively identified and grouped, and the analysis of three-dimensional data can be performed efficiently.

[Brief description of the drawings]

FIG. 1 is a system configuration diagram of an embodiment.

FIG. 2 is an explanatory diagram showing a state of scanning by a stylus in the system of FIG. 1;

FIG. 3 is a processing flowchart of the embodiment.

FIG. 4 is a graph showing a roughness curve.

FIG. 5 is a data array diagram of three-dimensional data binarized at a slice level.

FIG. 6 is an explanatory diagram of labeling (1).

FIG. 7 is an explanatory view (2) of labeling.

FIG. 8 is an explanatory diagram of a data array of conventional three-dimensional data binarized at a slice level.

FIG. 9 is an explanatory view (part 1) of a conventional labeling.

FIG. 10 is an explanatory view (part 2) of a conventional labeling.

[Explanation of symbols]

10 roughness measuring machine, 12 work mounting table, 14 work, 16 stylus, 18 personal computer.

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Claims (5)

[Claims] 1. A method of analyzing three-dimensional data corresponding to a surface shape of a three-dimensional work, wherein a step of discriminating the three-dimensional data into peak data and valley data at a predetermined height threshold value. A grouping step of grouping the crest data and sequentially assigning a label, and grouping the trough data and sequentially assigning a different type of label to the crest label, A method for analyzing three-dimensional data, wherein a group and a valley are collectively labeled and grouped. 2. The method according to claim 1, wherein in the grouping step, labels of different codes are used for the peak data and the valley data. 3. The method according to claim 1, wherein, in the grouping step, a label is assigned by sequentially assigning a positive integer to the peak data, and a negative integer is assigned to the valley data sequentially. A method for analyzing three-dimensional data, wherein a label is given by giving the label. 4. The method of claim 1, wherein the predetermined height threshold comprises a threshold for the peak and a threshold for the valley.
How to analyze dimensional data. 5. An apparatus for analyzing three-dimensional data corresponding to a surface shape of a three-dimensional work, wherein a discriminating means for discriminating the three-dimensional data into peak data and valley data at a predetermined height threshold value. Labeling means for sequentially assigning a first type of label to the set of peak data and sequentially assigning a second type of label to the set of valley data; and a peak labeled by the labeling means. And a calculating means for calculating characteristic parameters of the three-dimensional work using the part data and the valley data.