CN112945125B - Non-contact tire rolling deformation characteristic test method - Google Patents
Non-contact tire rolling deformation characteristic test method Download PDFInfo
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- CN112945125B CN112945125B CN202110326786.6A CN202110326786A CN112945125B CN 112945125 B CN112945125 B CN 112945125B CN 202110326786 A CN202110326786 A CN 202110326786A CN 112945125 B CN112945125 B CN 112945125B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/16—Measuring arrangements characterised by the use of optical techniques for measuring the deformation in a solid, e.g. optical strain gauge
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
Abstract
The invention discloses a non-contact tire rolling deformation characteristic test method, which comprises the following steps: step 1: preparing a test tire; step 2: preparing an experiment site; step 3: calibrating the length of the cross reference ruler; step 4: setting and adjusting a high-speed camera; step 5: calibrating a high-speed camera; step 6: collecting data; step 7: converting data; step 8: pre-analyzing data; step 9: image matching: the graph acquired by the test piece in the undeformed state is called a reference image, the graph acquired by each deformed state is called a deformed graph, the discretized recording is carried out on the deformation process in the test process, and the image matching is carried out on the data of each deformation time point. According to the experimental result, the tire strain concentration position can be reflected, and the data curves of the key points and the hub points are drawn, so that the purpose of analyzing the tire and the automobile performance is achieved.
Description
Technical Field
The invention relates to the technical field of detection of automobile tires, in particular to a non-contact tire rolling deformation characteristic test method.
Background
In the bearing process of an automobile, the tires can deform under stress when passing through different barriers, the traditional strain gauge can only analyze deformation of a single point, and the tires are large and are fussy to arrange, and can not meet the requirement of full-field strain measurement.
Disclosure of Invention
In view of the above problems, the present invention is directed to a non-contact tire rolling deformation characteristic test method, which can realize full-field tire deformation measurement.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
a non-contact tire rolling deformation characteristic test method comprises the following steps:
step 1: preparing a test tire;
step 2: preparing an experiment site;
step 3: calibrating the length of the cross reference ruler;
step 4: setting and adjusting a high-speed camera;
step 5: calibrating a high-speed camera;
step 6: collecting data;
step 7: converting data;
step 8: pre-analyzing data;
step 9: image matching
The graph acquired by the test piece in the undeformed state is called a reference image, the graph acquired by each deformed state is called a deformed graph, the discretized recording is carried out on the deformation process in the test process, and the image matching is carried out on the data of each deformation time point.
Preferably, in the step 1, the tire surface is whitened by white paint, a speckle pattern is prepared on the tire surface by using a bushing, black paint and a marker pen, and a mark point is attached at the center of the hub.
Preferably, in the step 3, the cross ruler is placed on the ground, the coding mark points and the reference ruler are laid, the cross ruler is shot from multiple angles by using a photogrammetric camera, all relevant target points are calculated, three-dimensional coordinates of the mark points and the object feature points stuck in the digital pictures are automatically calculated, data calculation is completed, and calibration of the cross ruler is achieved.
Preferably, in the step 4, in the high-speed camera control software, the resolution 1280×800 pixels of the camera are set, the cross ruler is placed at the measuring position, the focal length and aperture of the camera are adjusted, and the sharpness and the uniform brightness of the two-phase image are ensured.
Preferably, in the step 5, the accurate distance between two pairs of identification points on the identification board is set as a scale, the cross scale is placed under the standard measurement distance, the image data of the identification board under eight different directions are sequentially collected by using two high-speed cameras, the three-dimensional coordinates of the identification points are identified, and the internal and external parameters of the high-speed cameras are obtained by adopting a planar template eight-step method calculation.
Preferably, in the step 6, in the high-speed camera control software, the camera acquisition frame frequency is set to 4000fps, the shutter is set to 100us, the post-trigger mode is selected, and Capture is clicked for the two high-speed cameras respectively, so that the cameras are in a waiting trigger state; after preparation is completed, the automobile engine is started, when the tire completely passes through the obstacle, the record of data is triggered by clicking, and then the data acquisition is completed through the obstacles of different specifications under the same tire pressure; after the tire pressure is changed, the data acquisition is completed through barriers of different specifications again.
Preferably, in the step 7, all the collected data are converted into a picture format.
Preferably, in step 8 above, the speckle field is framed, i.e., the 3/4 circle data is truncated.
Preferably, in the step 9, the image matching specifically includes the following steps:
step 901: the image coordinates of the center point P of the image reference sub-area before deformation are (x, y), the image coordinates of the center point P ' of the corresponding target sub-area after deformation are (x ', y '), so that the position and shape change of the reference sub-area in the deformation process is obtained, and the displacement and strain of an object at the position of the sub-area point can be obtained by comparing the position and shape change of the same sub-area between the two states before and after deformation;
step 902: the coordinate change of any point on the surface of the object can be expressed as the combination of the coordinate change caused by displacement and deformation, and then the following mapping function exists:
wherein u represents the displacement of the center point P' of the target subarea relative to the center point P of the reference subarea in the X direction; v represents the displacement of the center point P' of the target subarea relative to the center point P of the reference subarea in the Y direction;representing a displacement gradient of the target subregion relative to the reference subregion;
step 903: and evaluating the similarity between the reference subarea and the target subarea, and expressing the similarity degree between the reference subarea and the target subarea by adopting a correlation coefficient, wherein the correlation coefficient formula is specifically expressed as follows:
wherein: f (x, y) -gray values at any point in the reference subregion; g (x+u, y+v) -gray values of corresponding points of any point in the reference subregion in the deformed image; p-related parameter vector, depending on the mapping function used; r is (r) 0 And r 1 The two parameters are used for compensating gray scale linear deviation in the reference subarea and the target subarea;
the least square iteration method is adopted to calculate the correlation coefficient C SSD The extremum of (2) to complete image matching, and further obtain corresponding displacement and strain.
The beneficial effects of the invention are as follows: the invention provides a non-contact tire rolling deformation testing method based on high-speed photography and speckle analysis, which is characterized in that a counterweight is added to a vehicle in consideration of actual conditions, a roadblock is simulated, full-field deformation analysis is carried out on a tire when the tire passes through the roadblock, non-contact full-field strain measurement on the tire rolling process is realized, a tire strain concentration position can be reflected according to experimental results, and a data curve of key points and hub points is drawn, so that the purpose of analyzing the performances of the tire and the vehicle is achieved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is an image of a left and right high speed camera adjusted; (a) a left high speed camera; (b) a right high speed camera;
FIG. 2 is a high-speed camera calibration result;
FIG. 3 is a schematic diagram of a speckle domain;
FIG. 4 is a schematic diagram of digital image correlation;
FIG. 5 is a strain field when not in contact with an obstacle; (a) A selected strain analysis zone when the tire is not in contact with an obstacle; (b) The tire is subjected to the calculation of the invention and does not contact with obstacle strain;
FIG. 6 is a strain field at contact barrier; (a) A selected strain analysis area after the tire falls from the obstacle and contacts the iron plate; (b) The tire strain condition calculated by the invention is obtained after the tire falls from an obstacle and contacts with the iron plate;
FIG. 7 is a graph of a point strain analysis in a deformation region; (a) analyzing the marker points for the selected tire deformations; (b) A strain curve for the selected marker point during tire rolling over the obstacle;
FIG. 8 is a graph of hub point displacement analysis.
Detailed Description
In order to enable those skilled in the art to better understand the technical solution of the present invention, the technical solution of the present invention is further described below with reference to the accompanying drawings and examples.
The invention specifically provides a non-contact tire rolling deformation characteristic test method, which comprises the following steps:
step 1: test tire preparation
The surface of the tire is sprayed with white paint, a speckle pattern is prepared on the surface of the tire by using a bushing, black paint and a marker pen, and a mark point is stuck at the center of the hub.
Step 2: experiment site preparation
And (3) erecting a high-speed camera and an LED light source according to the measurement distance (3500 mm) and the camera distance (1500 mm), and determining an experiment site.
Step 3: calibrating cross-reference bar length
The method comprises the steps of placing a cross ruler on the ground, arranging coding mark points and a reference ruler, shooting the cross ruler from multiple angles by using a photogrammetry camera, calculating all relevant target points, automatically calculating three-dimensional coordinates of the mark points and object characteristic points stuck in the digital pictures, completing data calculation, and realizing calibration of the cross ruler.
Step 4: high speed camera setup and adjustment
In the high-speed camera control software, the resolution 1280 x 800 pixels of the camera are set, a cross ruler is arranged at a measuring position, the focal length and the aperture of the high-speed camera are adjusted, and the sharpness and the uniform brightness of images of the two high-speed cameras are ensured, as shown in fig. 1.
Step 5: high speed camera calibration
The accurate distance between two pairs of identification points on the identification plate is set as a scale, a cross ruler is placed under the standard measurement distance, the image data of the identification plate under eight different directions are sequentially collected by two high-speed cameras, the three-dimensional coordinates of the identification points are identified, and the internal and external parameters of the high-speed cameras are obtained by adopting a planar template eight-step method calculation. The calibration of the high-speed camera is a precondition of system calculation, and only the internal and external parameters of the camera are obtained, three-dimensional data of the object point can be accurately obtained, as shown in fig. 2.
Step 6: data acquisition
Arranging a vehicle in place, setting the camera acquisition frame frequency to 4000fps, setting the shutter to 100us in high-speed camera control software, selecting a 'post trigger' mode (namely saving all previous data when the camera is triggered), and clicking Capture for the two cameras respectively to enable the cameras to be in a waiting trigger state.
After preparation is completed, the automobile engine is started, and when the tire completely passes through the obstacle, clicking triggers the recording of completion data. Taking this process as an example, under the same tire pressure, the data acquisition is completed through barriers of different specifications respectively; after the tire pressure is changed, the data acquisition is completed through barriers of different specifications again, and the tire pressure sensor can be used for analyzing the tire deformation characteristics under the conditions of different tire pressures, bearing and roadblocks.
Step 7: data conversion
Because the data collected by high-speed photography are all in the format of video, all the data need to be converted into a picture format, and subsequent calculation is facilitated.
Step 8: data pre-analysis
And selecting a speckle domain (according to the specificity of the experiment, intercepting data of 3/4 circle and avoiding influence caused by a line and an iron beam) by a frame, as shown in figure 3.
Step 9: image matching
The images acquired by the test piece in the undeformed state are generally referred to as "reference images", and the images acquired in the respective deformed states are generally referred to as "deformed images". In the deformation detection process, discretizing the deformation process, and performing image correlation matching on the data of each deformation time point.
As shown in fig. 4, the image coordinates of the center point P of the reference subregion of the image before deformation are (x, y); searching a target subarea corresponding to the speckle gray information in the subarea as a characteristic template in the deformed image, wherein the image coordinate of the central point P ' of the deformed corresponding target subarea is (x ', y '); thus, the position and shape change of the reference subarea in the deformation process is obtained, and the displacement and strain of the object at the subarea point position can be obtained by comparing the position and shape change of the same subarea between the two states before and after the deformation. Taking deformation such as rigid body translation, rotation, expansion and contraction, torsion and the like into consideration when the object is deformed under the force, the coordinate change of any point on the surface of the object can be expressed as the combination of the coordinate change caused by displacement and deformation. Then, there is the following mapping function:
wherein: u represents the displacement of the center point P' of the target subarea relative to the center point P of the reference subarea in the X direction; v represents the displacement of the center point P' of the target subarea relative to the center point P of the reference subarea in the Y direction;representing the displacement gradient of the target subregion relative to the reference subregion.
In order to evaluate the similarity between the reference subregion and the target subregion, a mathematical measure, i.e., a correlation coefficient, reflecting the degree of similarity between the reference subregion and the target subregion is required. And obtaining the extreme value (maximum or minimum value) of the correlation coefficient through a correlation search algorithm, so that the matching of the images can be realized.
The zero-mean normalized cross-correlation coefficient and the zero-mean normalized minimum distance sum-of-squares coefficient are insensitive to gray level linear changes of the image subregion due to normalization processing of the reference subregion and the target subregion before searching, and have strong anti-interference capability, but the expression is very complex, so that an improved minimum distance sum-of-squares coefficient is introduced, and a linear light intensity change model is introduced:
wherein: f (x, y) -gray values at any point in the reference subregion; g (x+u, y+v) -gray values of corresponding points of any point in the reference subregion in the deformed image; p-related parameter vector, depending on the mapping function used; r is (r) 0 And r 1 The two parameters are used to compensate for gray scale linear deviations in the reference sub-region and the target sub-region.
The least square iteration method is adopted to calculate the correlation coefficient C SSD The extremum of (2) to complete image matching, and further obtain corresponding displacement and strain.
Examples
As shown in fig. 5 (a) and 5 (b), the strain area of the tire is shown green and the strain value is within 0.5% when the tire is not in contact with an obstacle; as shown in fig. 6 (a), when the tire is in contact with a failure, the strain value is 5.65% due to the increased load bearing of the tire, and the strain area is shown in red (corresponding to the scale in the figure); as shown in fig. 6 (b), after falling from the obstacle and contacting with the iron plate, the tire and the iron plate exhibit a vibration process, the strain value is remarkably increased to 5.1% as compared with the initial state, and the entire tire bottom is concentrated to be red. As shown in fig. 7 (a) and 7 (b), a point is selected for the strain concentration region, and a curve is drawn to reflect the change in the maximum principal strain with state (time) when the tire passes an obstacle. The mark point attached to the hub has obvious effect, the displacement information of the mark point can be obtained through analysis, and a corresponding curve is drawn, as shown in fig. 8.
According to the invention, under the condition of a large view field, the deformation of the tire can be monitored by means of high-speed photography and three-dimensional digital image related technologies, the strain concentration part of the tire can be reflected according to experimental results, and the data curves of key points and hub points are drawn, so that the purpose of analyzing the performances of the tire and the automobile is achieved, and the accuracy and the stability of the digital image technology are further verified.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made without departing from the spirit and scope of the invention, which is defined in the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (1)
1. The non-contact tire rolling deformation characteristic testing method is characterized by testing based on high-speed photography and speckle analysis, and specifically comprises the following steps of:
step 1: preparing a test tire; white spraying paint is used for spraying white on the surface of the test tire, a speckle pattern is prepared on the surface of the test tire by using a bushing, black spraying paint and a marker pen, and a mark point is stuck at the center of the hub;
step 2: preparing an experimental field and simulating a roadblock;
step 3: calibrating the length of the cross reference ruler;
placing the cross reference ruler on the ground, pasting and arranging coding mark points on the cross reference ruler, shooting the cross reference ruler from multiple angles by using a photogrammetry camera, automatically calculating three-dimensional coordinates of the coding mark points pasted in the digital pictures and characteristic points of the cross reference ruler, completing data calculation, and realizing calibration of the cross reference ruler;
step 4: setting and adjusting a high-speed camera; setting the resolution ratio 1280 x 800 pixels of the high-speed camera, placing a cross reference ruler at a measuring position, adjusting the focal length and the aperture of the high-speed camera, and ensuring the definition and the uniform brightness of images of the two high-speed cameras;
step 5: calibrating a high-speed camera;
step 6: collecting data;
setting the acquisition frame frequency of the high-speed camera to 4000fps, setting the shutter to 100us, selecting a post-trigger mode, and clicking Capture for the two high-speed cameras respectively to enable the high-speed cameras to be in a waiting trigger state; after preparation is completed, starting an automobile engine, clicking to trigger to complete data recording when a test tire completely passes through the roadblock, and then respectively passing through roadblocks of different specifications under the same tire pressure to complete data acquisition; after the tire pressure is changed, the data acquisition is completed through roadblocks of different specifications again;
step 7: converting data; all the acquired data are converted into a picture format;
step 8: pre-analyzing data; selecting a speckle domain by a frame, and intercepting data of a 3/4 circle;
step 9: matching images;
the method comprises the steps of (1) taking an image acquired by a test tire in an undeformed state as a reference image, taking the image acquired by each deformed state as a deformed image, performing discretization recording on a deformation process in a test process, and performing image matching on data of each deformation time point;
the image matching specifically comprises the following steps:
step 901: the image coordinates of the center point P of the image reference sub-area before deformation are (x, y), the image coordinates of the center point P ' of the corresponding target sub-area after deformation are (x ', y '), so that the position and shape change of the reference sub-area in the deformation process is obtained, and the displacement and strain of the test tire at the position of the sub-area point can be obtained by comparing the position and shape change of the same sub-area between the two states before and after deformation;
step 902: based on rigid body translation, rotation, expansion and torsion deformation when the test tire is deformed under the stress, the coordinate change of any point on the surface of the test tire can be expressed as the combination of the coordinate change caused by displacement and deformation, and the following mapping functions exist:
wherein u represents the displacement of the center point P' of the target subarea relative to the center point P of the reference subarea in the X direction; v represents the displacement of the center point P' of the target subarea relative to the center point P of the reference subarea in the Y direction;representing a displacement gradient of the target subregion relative to the reference subregion;
step 903: and evaluating the similarity between the reference subarea and the target subarea, and expressing the similarity degree between the reference subarea and the target subarea by adopting a correlation coefficient, wherein the correlation coefficient formula is specifically expressed as follows:
wherein: f (x) i ，y j ) Gray value of any point in reference sub-zone；g(x′ i ，y′ j ) -gray values of corresponding points of any point in the reference subregion in the target subregion; r is (r) 0 And r 1 The two parameters are used for compensating gray scale linear deviation in the reference subarea and the target subarea;
the least square iteration method is adopted to calculate the correlation coefficient C SSD The extremum of (2) to complete image matching, and further obtain corresponding displacement and strain.
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Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201203420Y (en) * | 2008-05-23 | 2009-03-04 | 韩斯超 | Digital close view photogrammetric system |
| JP2009139268A (en) * | 2007-12-07 | 2009-06-25 | Yokohama Rubber Co Ltd:The | Tire wheel tread measurement apparatus |
| CN101694373A (en) * | 2009-10-23 | 2010-04-14 | 北京航空航天大学 | Antenna deformation measuring method |
| DE102010011124A1 (en) * | 2010-03-11 | 2011-12-15 | Andreas Stadlmeier | System for optimum tire pressure control in vehicles, has compact and functional design structure with compressed air generation mechanism and energy supply mechanism |
| CN102507589A (en) * | 2011-10-11 | 2012-06-20 | 无锡翼龙航空设备有限公司 | Laser speckle inspection method for aircraft tire |
| JP2012242290A (en) * | 2011-05-20 | 2012-12-10 | Nippon Yusoki Co Ltd | Detection device and detection method for detecting deformation state of tire in travelling vehicle |
| KR20130054547A (en) * | 2011-11-17 | 2013-05-27 | 한국타이어월드와이드 주식회사 | Dynamic displacement measuring apparatus of tire tread |
| CN105928467A (en) * | 2016-06-01 | 2016-09-07 | 北京卫星环境工程研究所 | Test system for deformation measurement of large spacecraft structure under vacuum and low-temperature environment |
| CN106091966A (en) * | 2016-06-01 | 2016-11-09 | 北京卫星环境工程研究所 | Thermal deformation measurement method under vacuum low-temperature environment |
| CN108716891A (en) * | 2018-04-28 | 2018-10-30 | 河南理工大学 | A kind of underworkings surrouding rock deformation quickly accurately monitors system and its monitoring method |
| CN108759699A (en) * | 2018-03-27 | 2018-11-06 | 西安交通大学 | A kind of measurement method and system of big visual field masonry structure material three-dimensional whole field deformation |
| CN108871223A (en) * | 2018-08-22 | 2018-11-23 | 西安空间无线电技术研究所 | A kind of satellite antenna thermal deformation automatic measurement system and method |
| CN109696133A (en) * | 2017-10-24 | 2019-04-30 | 柯尼卡美能达株式会社 | Squeegee action device for calculating and its method and overload detection system |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101484504B1 (en) * | 2013-04-17 | 2015-01-20 | 장철환 | Active contact pressure measuring module and Tire testing equipment thereby |
-
2021
- 2021-03-26 CN CN202110326786.6A patent/CN112945125B/en active Active
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2009139268A (en) * | 2007-12-07 | 2009-06-25 | Yokohama Rubber Co Ltd:The | Tire wheel tread measurement apparatus |
| CN201203420Y (en) * | 2008-05-23 | 2009-03-04 | 韩斯超 | Digital close view photogrammetric system |
| CN101694373A (en) * | 2009-10-23 | 2010-04-14 | 北京航空航天大学 | Antenna deformation measuring method |
| DE102010011124A1 (en) * | 2010-03-11 | 2011-12-15 | Andreas Stadlmeier | System for optimum tire pressure control in vehicles, has compact and functional design structure with compressed air generation mechanism and energy supply mechanism |
| JP2012242290A (en) * | 2011-05-20 | 2012-12-10 | Nippon Yusoki Co Ltd | Detection device and detection method for detecting deformation state of tire in travelling vehicle |
| CN102507589A (en) * | 2011-10-11 | 2012-06-20 | 无锡翼龙航空设备有限公司 | Laser speckle inspection method for aircraft tire |
| KR20130054547A (en) * | 2011-11-17 | 2013-05-27 | 한국타이어월드와이드 주식회사 | Dynamic displacement measuring apparatus of tire tread |
| CN105928467A (en) * | 2016-06-01 | 2016-09-07 | 北京卫星环境工程研究所 | Test system for deformation measurement of large spacecraft structure under vacuum and low-temperature environment |
| CN106091966A (en) * | 2016-06-01 | 2016-11-09 | 北京卫星环境工程研究所 | Thermal deformation measurement method under vacuum low-temperature environment |
| CN109696133A (en) * | 2017-10-24 | 2019-04-30 | 柯尼卡美能达株式会社 | Squeegee action device for calculating and its method and overload detection system |
| CN108759699A (en) * | 2018-03-27 | 2018-11-06 | 西安交通大学 | A kind of measurement method and system of big visual field masonry structure material three-dimensional whole field deformation |
| CN108716891A (en) * | 2018-04-28 | 2018-10-30 | 河南理工大学 | A kind of underworkings surrouding rock deformation quickly accurately monitors system and its monitoring method |
| CN108871223A (en) * | 2018-08-22 | 2018-11-23 | 西安空间无线电技术研究所 | A kind of satellite antenna thermal deformation automatic measurement system and method |
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|---|---|
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