CN114037705A - Metal fracture fatigue source detection method and system based on moire lines - Google Patents
Metal fracture fatigue source detection method and system based on moire lines Download PDFInfo
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Abstract
The invention relates to the field of image processing, in particular to a method and a system for detecting the position of a metal fatigue source according to an image. The method comprises the following steps: extracting a fracture area and a central point of the part; processing the extracted fracture area image of the part, and establishing a central coordinate system by taking the central point as an origin; calculating the change condition of the pixel values in all directions of the central point of the area to obtain a pulse graph of the pixel value change, calculating the mean square difference value of a peripheral density sequence according to a pulse curve oscillogram, dividing the area type of the fracture area of the part, determining the boundary point of a fatigue expansion area and a transient fracture area, fitting the boundary point to obtain a scallop line, determining the moving track of the scallop line, and obtaining the final intersection position of the scallop line and the edge of the part as the position of the fatigue source. According to the method, the shell line in the fracture is searched for according to the gray value fluctuation condition in the fracture area, the shell line can be found more accurately, and the condition that the fatigue source detection effect is poor due to the fact that the shell line in the fracture is not clear can be effectively avoided.
Description
Technical Field
The invention relates to the field of image processing, in particular to a method and a system for detecting a metal fracture fatigue source based on a moire line.
Background
The fracture of the part records the whole process from the initiation and the propagation of the crack to the fracture, and through morphological analysis of the fracture, some basic problems of the part fracture can be obtained, such as fracture cause, fracture mode, crack propagation trend and the like, and the finding of the fatigue source position of the fracture area is the basis of the whole analysis. Most of existing methods for searching for the position of the fatigue source are manual detection, and detection is carried out by experienced workers, or a texture detection method is used for analyzing a shell line in a fracture, so that the position of the fatigue source is searched for according to the method, but the method is limited in detection of the condition that the shell line in the fracture is clear, and poor in detection effect of the position of the fatigue source under the condition that the shell line is not clear.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides the metal fracture fatigue source detection method and system based on the shell lines, which can accurately find the shell lines in the fracture area and accurately position the fatigue source position through the determined shell lines.
In order to achieve the purpose, the invention adopts the following technical scheme, namely a method and a system for detecting a metal fracture fatigue source based on a moire line.
The implementation of the method comprises the following steps:
s1: extracting the central point of the fracture region image of the part, performing binarization image processing on the extracted region image, and establishing a coordinate system by taking the central point of the region image as an origin;
s2: taking the central point of the region image as an origin, extending and generating rays in all directions in a radial manner, obtaining a pixel pulse curve graph for ray pairs in all directions according to pixel values on the generated rays, calculating the peripheral density of each pulse in the pixel pulse curve graph, obtaining a peripheral density sequence according to the peripheral density of each pulse in the pixel pulse curve graph, and obtaining the mean square error of the peripheral density sequence by using the peripheral density sequence;
judging the areas through which the rays pass in each direction according to the mean square error of the peripheral density sequence; the passing area is a fatigue expansion area or a transient interruption area or a common area passing through the fatigue expansion area and the transient interruption area simultaneously;
dividing pixel points on rays passing through the common region into fatigue expansion regions or instantaneous interruption regions, and determining demarcation points on rays in all directions according to the division result;
fitting the obtained demarcation points on the rays in each direction to obtain a shell line;
s3: extracting two edge rays passing through the common area, and finding out a median line of an included angle formed by the two rays, wherein the obtained median line is the motion track of the Bayes line;
and (4) moving the shell line in parallel along the motion track to the direction of the fatigue expansion area, and determining the position of the fatigue source of the fracture area of the part.
The binarization processing of the area image is to sharpen and enhance the area of the area image and to binarize the sharpened and enhanced image.
The method for obtaining the peripheral intensity sequence of the pulse curve of the pixel values on the directional ray is as follows:
extracting the abscissa of the starting point and the ending point of the waveform in a rectangular pulse curve on rays in each direction in a pixel pulse curve graph, calculating the concentration of each pulse and two adjacent pulses to obtain the peripheral concentration of each pulse, wherein the calculation formula is as follows:
in the formula:
representing the peripheral concentration of the pulse;
is the waveform width of the pulse;
the pixel distance between the waveform and the end point of the adjacent waveform on the left side;
the pixel distance between the waveform and the starting point of the adjacent waveform on the right side;
and according to the calculated peripheral density of all the pulses on the pulse curve, combining the peripheral density of each pulse according to the pulse sequence on the pulse curve to obtain the peripheral density sequence of the pulse curve.
The step of dividing the region types passed by the rays in each direction is as follows:
the mean square error value of the peripheral dense sequence of the pulse curve is calculated by the following formula:
in the formula:
is the mean square error of the surrounding intensity sequences,
for the data in the peripheral intensity sequence,
representing the position of the data in the perimeter intensity sequence,
is the average of the data in the surrounding intensity sequence,
is a pulse curve and
the number of the intersection points of the axes;
setting a mean square error threshold value of a peripheral dense sequence of a pulse curve, and dividing the region type of a part fracture region according to the set threshold value:
in the formula:
a region-indicating mark is shown which indicates,
the degree of an included angle formed by each direction ray and the horizontal axis of the coordinate system is expressed;
Further, a method for determining a demarcation point on a ray in each direction comprises the following steps:
firstly, extracting the peripheral density of all pixel points on the directional ray, respectively comparing with the average value of the peripheral density sequence, and determining the type of the region to which the pixel points belong;
then marking all pixel points on the directional ray, and marking the pixel points belonging to the fatigue expansion area
Marking of pixel points belonging to a transient interruption zone
；
And then comparing the marking values of the pixel points at two adjacent sides of all the pixel points in the direction, and when the marking values of the pixel points at two sides of the pixel point are different, the pixel point is a demarcation point in the direction.
The method for determining the position of the fatigue source comprises the following steps:
extracting two edge rays passing through the common region, finding out a median line of an included angle formed by the two edge rays, wherein the median line is a motion track of the shell line, horizontally moving the shell line along the motion track to the fatigue expansion region, and when the shell line is moved to be intersected with only one pixel point of the region image, the pixel point is the position of the fatigue source.
The system comprises the following modules: the device comprises an image processing module, a shell line fitting module and a fatigue source determining module;
the image acquisition module is used for acquiring RGB image information of part fracture and extracting a part fracture area.
And the image processing module is used for carrying out sharpening processing and binarization processing on the fracture area image and providing image detail information for determining the position of the fatigue source.
And the scallop line fitting module is used for determining regional boundary points of the instantaneous fracture region and the fatigue expansion region from the detail information, and then fitting all the boundary points to obtain the scallop lines.
And the fatigue source determining module is used for determining the final position of the fatigue source according to the fitted beta line and the region type.
The invention has the beneficial effects that: the shell line can be more accurately found out through the fluctuation condition of the gray value in the fracture area, and the condition that the fatigue source is inaccurately detected due to the unclear shell line in the fracture can be effectively avoided.
1. The method and the device have the advantages that the image of the fracture area of the part is sharpened, enhanced and binarized, the detail information of the image is highlighted, and the fatigue expansion area and the instantaneous fracture area in the fracture area of the part can be determined more clearly.
2. Through the fatigue expansion area and the instantaneous interruption area which are judged, the scallop lines obtained by the least square method fitting of the boundary points are more accurate, so that the movement locus of the scallop lines is more accurate, and the accuracy of the position of the fatigue source is improved.
Drawings
FIG. 1 is a schematic flow diagram of the present invention.
Fig. 2 is a schematic view of a metal fracture in the present embodiment.
Fig. 3 is a schematic diagram of the embodiment after the sharpening of the metal fracture is enhanced.
Fig. 4 is a schematic diagram of the center coordinate system in the present embodiment.
Fig. 5 is a schematic view of rays in each direction in the present embodiment.
Fig. 6 is a graph of the pixel pulse in this embodiment.
Fig. 7 is a schematic view of the peripheral density in the present embodiment.
Fig. 8 is a block diagram of a system in the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and examples.
In the description of the present invention, it is to be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of description and simplicity of description, and do not indicate or imply that the referenced devices or elements must have a particular orientation, be constructed and operated in a particular orientation, and thus, are not to be construed as limiting the present invention.
The terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature; in the description of the present invention, "a plurality" means two or more unless otherwise specified.
Example 1
The method mainly aims to utilize an image processing technology to search the shell line according to the difference of the roughness of a transient fracture area and the roughness of a fatigue expansion area, and judge the unclear fracture fatigue source position;
the following description is made with reference to the examples and fig. 1:
the method comprises the following steps: extracting a part fracture area from the obtained RGB image by using the enclosure frame; sharpening and enhancing the extracted region, and establishing a central coordinate system;
the DNN can realize target detection automatically, but when the accuracy result is related, the DNN accuracy is limited, and labeling of the lines of the shell and the fatigue source needs to be performed by professional personnel, and the operation is complex. And the section is identified only by using the form of the bounding box, so that the labeling is simple, and the DNN result is reliable.
Only DNN is used to detect the slices and not to identify more other information.
The invention uses DNN neural network to carry out target detection on the fracture in the image by using an Encoder-Decoder-Bbox structure, and the specific process is as follows:
1. the network adopts an Encoder-Decoder form, and firstly encodes and then decodes the image. The input of the network is an image and the output is the center of the bounding box.
2. The network takes the image with the detected target as input, firstly decodes, namely uses convolution and pooling operation to extract spatial domain characteristics in the image in the process of downsampling the image, and the output of the encoder is the extracted characteristic vector.
3. The input of the decoder is the output characteristic vector of the encoder, and the decoder returns the central point of the target corresponding bounding box in the image after up-sampling. The output of the decoder is the output of the network.
4. The data set used for training the network is an image with a part fracture;
5. the label of the image is an enclosure frame corresponding to the fracture of the part, and comprises a central point coordinate of the enclosure frame, wherein the central point is marked in the image in a hot spot mode, namely the mark is corresponding to the mark
After the coordinates are obtained, a corresponding hot spot is obtained by blurring the coordinates using a gaussian kernel.
6, the Loss function is a mean square error Loss function;
at this point, extracting the fracture area of the part shown in fig. 2, and acquiring the central point of the area, which is recorded as
。
Using the extracted region
The gradient sharpening of the operator is enhanced, the details in the fracture area are highlighted, then the binarization is carried out, and the obtained result is shown in figure 3.
The gray gradient of the projection positions in the instantaneous interruption area is changed greatly, and the positions are converted into white pixel points after the operation; the fatigue expansion area is smooth, the gradient change of the gray scale is small, and most of the area is converted into black background pixel points.
The image is sharpened and enhanced and binarized, so that the detail information of the fracture area image can be obtained more clearly, and the boundary point between the fatigue expansion area and the instantaneous fracture area can be obtained more accurately when the area type in the area image is analyzed.
To be provided with
As the origin, the horizontal direction to the right is the positive X-axis direction, and the vertical direction is the positive Y-axis direction, a central coordinate system is established, as shown in fig. 4.
Step two: calculating the change condition of the pixel values in all directions of the central point of the area, determining the boundary position of the instantaneous interruption area and the expansion area, and fitting the boundary points according to the boundary position to obtain a shell line;
in the embodiment, the boundary point of the transient interruption area and the fatigue expansion area is found through the change condition of the pixel values in each direction of the central point of the section, so that the shell line is fitted. According to the relative position of the instantaneous fracture area and the fatigue expansion area, moving a shell line to the fatigue expansion area, and finally, taking the position intersected with the fracture edge as the position of a fatigue source, wherein the specific process is as follows:
a) obtaining a pixel pulse curve graph of the central point in each direction according to the gray value in each direction;
b) calculating the pulse peripheral density
Searching a region boundary point;
c) and fitting the boundary points according to all the obtained boundary points to obtain a shell line, and determining the relative positions of the fatigue expansion area and the instantaneous fracture area.
The following is an expanded description of the above process:
corresponding to the step a), obtaining a pixel pulse curve graph of the central point in each direction according to the pixel values in each direction;
1. at the center point
As a starting point, in a range of one circle around the central point, every time an included angle formed by the central point and the positive direction of the X axis is 1 °,2 °, … 360 ° and the central point of the region image is used as an origin point, the rays are generated by extending in each direction in a radial manner, and the rays generated in each direction are as shown in fig. 5;
2. and fitting each pixel point and pixel value thereof obtained by each ray into a pixel pulse curve graph which starts from an original point, takes the central point of the area image as the original point, extends and generates the ray in each direction in a radial mode, and obtains the ray pair in each direction according to the pixel value on the generated ray.
Since the extracted fracture area is binarized in the processing of the pair of data in the step, the pixel values of the pixel points in the area are only black and white, namely, in a certain direction, starting from a central point, the pixel values jump between 0 and 255 along with the increase of the number of pixels, and are in a rectangular pulse curve shape as shown in fig. 6;
the pixel point corresponding to the pixel value of 255 is a white pixel point in the sharpened image, and the pixel point corresponding to the pixel value of 0 is a background pixel point.
Corresponding to the step b), calculating the proportion of background pixels in the midpoint range of two adjacent waveform intervals, judging the type of the region where the pixel points are located, and searching region boundary points;
and (3) logical level: the instantaneous interruption region has more and dense white pixels, so that the width of the waveform in the instantaneous interruption region is larger and the distance between the waveforms is smaller, and the specific expression is that the peripheral concentration of the pulse is larger, namely the ratio of the width of the pulse to the distance between two adjacent pulses is larger; the fatigue expansion area has fewer and sparse white pixels, so the waveform width of the fatigue expansion area is smaller and the distance between the waveforms is larger, and the specific expression is that the peripheral concentration of the pulse is smaller, namely the value of the ratio of the width of the pulse to the distance between two adjacent pulses is smaller; the waveform pitch of a curve on a direction ray passing through the common region (namely a region passing through the fatigue expansion region and the instantaneous interruption region simultaneously) is shown as sparse first and then dense or dense first and then sparse;
the specific steps of the part are as follows:
1. respectively recording the abscissa of the starting point and the ending point of the pulse curve waveform of the pixel values on the rays in each direction obtained in the step a), and obtaining the abscissa as
Of the pixel pulse profile of (1), wherein
Is an integer and
is taken as
(co)
One waveform) as shown in fig. 7.
2. Calculating the peripheral concentration of the pulse
The abscissa of the starting point and the end point of the waveform to be calculated is set as
Then the horizontal coordinates of the starting point and the ending point of the waveform on the left and right sides are respectively
The calculation formula is as follows:
as shown in fig. 7, wherein
Is wave-shaped in width, i.e.
；
The pixel distance of the waveform from the end of the left adjacent waveform, i.e.
；
The pixel distance of the start of the waveform from the right-hand adjacent waveform, i.e.
；
It should be noted that when the waveform is the first waveform, i.e. the first waveform
When the temperature of the water is higher than the set temperature,
(ii) a When the waveform is the last waveform, i.e.
When the temperature of the water is higher than the set temperature,
；
arranging all the obtained peripheral densities according to the sequence of the pulses in the pulse curve, and integrating to obtain a peripheral density sequence of the pulse curve:
；
by calculating the peripheral density of each pulse according to the pulse curve on each direction ray, the change condition of the gray level of the pixel points on the direction ray can be reflected more clearly, and the demarcation point on the direction ray can be determined more accurately.
3. The mean square error of the peripheral density sequence is obtained by calculation
The consistency of the pulse peripheral density in the direction is judged, so that the area of the fracture area of the part is divided;
the mean square error of the surrounding intensity sequence is calculated by the formula:
in the formula:
is the mean square error of the surrounding intensity sequences,
for the data in the peripheral intensity sequence,
representing the position of the data in the perimeter intensity sequence,
is the average of the data in the surrounding intensity sequence,
is a pulse curve and
the number of intersections of the axes.
According to the priori knowledge, when the pixel points in a certain direction are all located in a transient interruption area or a fatigue expansion area, the pixel points are
The degree of change of the mean square error is small, so that the mean square error is small; when the pixel point in the direction passes through the transient interruption region and the fatigue expansion region, the pixel point in the direction passes through the transient interruption region and the fatigue expansion region
There is a large variation in the entire region, so the resulting mean square error is large, and thus the region types can be distinguished.
Setting a mean square error threshold value of the peripheral density sequence, wherein the empirical value is 0.3; setting region marks in various directions
The judgment criteria are as follows:
in the formula:
a region-indicating mark is shown which indicates,
representing the angle of each direction.
4. Determining demarcation points on the rays in all directions:
to is directed at
In case of (1), for
The peripheral intensity of all pulses in the sequence is respectively equal to
The average values of the data in the sequence are compared and
the pixel points of (a) consider the waveform to be located in the fatigue extension region, and mark the starting point and the end point of the waveform
(ii) a Will be provided with
The pixel points consider the waveform to be positioned in the transient interruption area, and marks of the starting point and the end point of the waveform
(ii) a After all the waveforms are judged, traversing the pulse sequence and comparing the pixel points
Marking of two-sided pixel points
I.e. by
And
when the two are different (the exclusive or value is 1), the dividing point is the first point from the central point in the direction
Each pixel point records the coordinates of the demarcation point; and repeating the step, traversing all direction rays in the regional image, and recording to obtain demarcation points on all direction rays.
5. Corresponding to the step c), fitting the boundary points according to the recorded boundary points on the rays in each direction to obtain a shell line;
and performing curve fitting on all the demarcation points obtained in the last step by using least square fitting, so that as many demarcation points as possible fall on the curve.
Step three: determining the motion trail of the shell lines according to the obtained shell lines, and further determining the position of the fatigue source;
and according to the obtained shell line, extracting two edge rays which simultaneously pass through a common area of the fatigue expansion area and the instantaneous interruption area to obtain a median line of an included angle formed by the two rays, wherein the median line is the motion track of the shell line.
The fatigue expansion zone is formed firstly when the part is broken from the fatigue source, and the scallop line has the fatigue characteristic and only exists in the fatigue expansion zone, so that the position of the fatigue source can be obtained by moving the obtained scallop line to the fatigue expansion zone, and therefore, the moving direction of the scallop line is always moved to the fatigue expansion zone.
And (4) moving the shell line in parallel to the fatigue expansion region along the motion track, wherein the position of the shell line which is finally intersected with the edge of the part (when only one intersected pixel point is provided) is the position of the fatigue source.
As shown in FIG. 8, the invention provides a fatigue source detection system for metal fracture based on a moire line, which comprises the following modules: the device comprises an image acquisition module, an image processing module, a shell line fitting module and a fatigue source determining module.
The image acquisition module is used for acquiring RGB image information of part fracture and extracting a part fracture area.
And the image processing module is used for carrying out sharpening processing and binarization processing on the fracture area image and providing image detail information for determining the position of the fatigue source.
And the scallop line fitting module is used for extracting pixel point information from the detail information and determining that the pixel points on the ray in each direction belong to a fatigue expansion area or a transient interruption area, so that the boundary points of the transient interruption area and the fatigue expansion area on the ray in the direction are determined, and all the obtained boundary points are fitted to obtain the scallop line.
And the fatigue source determining module is used for acquiring the moving direction of the shell lines according to the fitted shell lines and the region types, horizontally moving the shell lines to the moving direction of the shell lines and determining the final position of the fatigue source.
The above examples are merely illustrative of the present invention and do not constitute the scope of the present invention.
Claims (7)
1. A method for detecting a metal fracture fatigue source based on a moire line is characterized by comprising the following steps:
s1: extracting the central point of the fracture region image of the part, performing binarization image processing on the extracted region image, and establishing a coordinate system by taking the central point of the region image as an origin;
s2: taking the central point of the region image as an origin, extending and generating rays in all directions in a radial manner, obtaining a pixel pulse curve graph for ray pairs in all directions according to pixel values on the generated rays, calculating the peripheral density of each pulse in the pixel pulse curve graph, obtaining a peripheral density sequence according to the peripheral density of each pulse in the pixel pulse curve graph, and obtaining the mean square error of the peripheral density sequence by using the peripheral density sequence;
judging the areas through which the rays pass in each direction according to the mean square error of the peripheral density sequence; the passing area is a fatigue expansion area or a transient interruption area or a common area passing through the fatigue expansion area and the transient interruption area simultaneously;
dividing pixel points on rays passing through the common region into fatigue expansion regions or instantaneous interruption regions, and determining demarcation points on rays in all directions according to the division result;
fitting the obtained demarcation points on the rays in each direction to obtain a shell line;
s3: extracting two edge rays passing through the common area, and finding out a median line of an included angle formed by the two rays, wherein the obtained median line is the motion track of the Bayes line;
and (4) moving the shell line in parallel along the motion track to the fatigue expansion area to determine the fatigue source position of the fracture area of the part.
2. The method for detecting the fatigue source of the metal fracture based on the moire lines as claimed in claim 1, wherein the method for performing binarization processing on the area image comprises the following steps: firstly, sharpening enhancement is carried out on the region image region, and then binarization processing is carried out on the sharpened and enhanced image.
3. The method for detecting the metal fracture fatigue source based on the moire lines as claimed in claim 1, wherein the method for obtaining the peripheral intensity sequence of the pulse curve is as follows:
extracting the abscissa of the starting point and the ending point of the waveform in a rectangular pulse curve on rays in each direction in a pixel pulse curve graph, calculating the concentration of each pulse and two adjacent pulses to obtain the peripheral concentration of each pulse, wherein the calculation formula is as follows:
in the formula:
representing the peripheral concentration of the pulse;
is the waveform width of the pulse;
the pixel distance between the waveform and the end point of the adjacent waveform on the left side;
the pixel distance between the waveform and the starting point of the adjacent waveform on the right side;
and according to the calculated peripheral density of all the pulses on the pulse curve, combining the peripheral density of each pulse according to the pulse sequence on the pulse curve to obtain the peripheral density sequence of the pulse curve.
4. The method for detecting the metal fracture fatigue source based on the moire lines as claimed in claim 1, wherein the step of dividing the region types passed by the rays in each direction is as follows:
the mean square error value of the peripheral dense sequence of the pulse curve is calculated by the following formula:
in the formula:
is the mean square error of the surrounding intensity sequences,
for the data in the peripheral intensity sequence,
representing the position of the data in the perimeter intensity sequence,
is the average of the data in the surrounding intensity sequence,
is a pulse curve and
the number of the intersection points of the axes;
setting a mean square error threshold value of a peripheral dense sequence of a pulse curve, and dividing the region type of a part fracture region according to the set threshold value:
in the formula:
a region-indicating mark is shown which indicates,
the degree of an included angle formed by each direction ray and the horizontal axis of the coordinate system is expressed;
5. The method for detecting the metal fracture fatigue source based on the moire lines as claimed in claim 1, is characterized in that the method for determining the demarcation point on the ray in each direction comprises the following steps:
extracting the peripheral density of all pixel points on the directional ray, and respectively comparing the peripheral density with the average value of the peripheral density sequence to determine the type of the region to which the pixel points belong;
marking all pixel points on the directional ray, and marking the pixel points belonging to the fatigue expansion area
Marking of pixel points belonging to a transient interruption zone
；
And comparing the marking values of the pixel points at the two adjacent sides of all the pixel points in the direction, and when the marking values of the pixel points at the two sides of the pixel point are different, the pixel point is a demarcation point in the direction.
6. The method for detecting the fatigue source of the metal fracture based on the scallop lines as claimed in claim 1, wherein the method for determining the position of the fatigue source comprises the following steps:
and horizontally moving a motion track formed by the shell line along a median line of an included angle formed by the two edge rays to the direction of the fatigue expansion area, and when the motion track is moved to the state that only one pixel point of the shell line and the area image is intersected, determining the pixel point as the position of the fatigue source.
7. A metal fracture fatigue source detection system based on a moire line is characterized by comprising the following modules: the device comprises an image processing module, a shell line fitting module and a fatigue source determining module;
the image acquisition module is used for acquiring RGB image information of part fracture and extracting a part fracture area;
the image processing module is used for carrying out sharpening enhancement processing and binarization processing on the fracture area image and providing image detail information for determining the position of the fatigue source;
the shell line fitting module is used for determining a region boundary point of a transient interruption region and a fatigue expansion region from detail information;
and the fatigue source determining module is used for determining the final position of the fatigue source according to the fitted beta line and the region type.
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