CN115656238B - Micro-region XRF element analysis and multidimensional imaging method and system - Google Patents
Micro-region XRF element analysis and multidimensional imaging method and system Download PDFInfo
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Abstract
The invention discloses a micro-region XRF element analysis and multidimensional imaging method and a system. The system comprises a multi-dimensional motion device, a profile information acquisition device and a micro-region XRF, wherein the multi-dimensional motion device is used for carrying and driving the profile information acquisition device and the micro-region XRF to perform multi-dimensional motion; the profile information acquisition device is used for scanning the profile of the object to be detected under the drive of the multi-dimensional movement device, acquiring the profile information of the object to be detected and sending the profile information to the multi-dimensional movement device; the micro-region XRF is used for moving to the corresponding working position of each scanning point along the scanning track under the drive of the multi-dimensional movement device, carrying out X-ray irradiation on the object to be detected, acquiring an X-ray fluorescence spectrum emitted by the object to be detected and sending the X-ray fluorescence spectrum to the data analysis and display system; the multi-dimensional motion device determines the working position and the scanning track of the micro-region XRF relative to each scanning point on the object to be detected according to the contour information; and the data analysis and display system is used for displaying the spectrum in real time and analyzing elements.
Description
Technical Field
The invention relates to a micro-region X-ray fluorescence (XRF) element analysis and multidimensional imaging method and a system, which are particularly suitable for carrying out high-precision micro-region XRF element analysis and multidimensional imaging on curved surface samples with various forms in an open scene.
The invention also relates to a scanning track generation method and a three-dimensional visualization method of surface element distribution. The scanning track generation method can be used for generating sample scanning point position and direction data, and the three-dimensional visualization method of the surface element distribution can be used for three-dimensional display of the surface element distribution in the scanning area.
Background
The currently known micro-region XRF mainly comprises an X-ray source, a multi-capillary X-ray lens and an X-ray detector, wherein X-rays emitted by the X-ray source are converged on the surface of an object through the multi-capillary X-ray lens, and an X-ray fluorescence spectrum emitted by the surface of the object is acquired by using the X-ray detector, so that element type and content information of the detection point are obtained. Further, the micro-area X-ray fluorescence spectrometer is used for scanning on the surface of the object, so that the distribution information of each element component on the surface of the object can be obtained.
The micro-area X-ray fluorescence spectrometer M6 JETSTTREAM developed by BRUKER company is loaded on mutually perpendicular round rods with threads, and the micro-area X-ray fluorescence spectrometer can freely move in a two-dimensional plane by rotating the round rods. The product acquires color information and two-dimensional position information of the surface of an object by using an optical camera, designs a scanning path and acquires the distribution condition of each element on the surface of the object.
In the prior art, an optical camera is adopted to only acquire two-dimensional position information of a sample, and a micro-area X-ray fluorescence spectrometer can only move in a two-dimensional plane, so that when a curved surface (or uneven surface) sample is scanned, the focal point of X-rays cannot be kept on the surface of the sample under the influence of the space position and the angle of the curved surface direction, and the photon number recorded by a detector is also related to the angular distribution of characteristic X-rays, so that the counting of each scanning point has deviation caused by space inconsistency (inconsistent position of the focal point of the X-rays, inconsistent space position and direction of the detector for each scanning point on the curved surface sample), and thus the element distribution and content information of the surface of the sample cannot be accurately acquired.
Disclosure of Invention
The invention provides a method and a system for high-precision micro-area XRF element analysis and multidimensional imaging, which are applicable to curved surface (or uneven surface) samples. The invention adopts an open system structure, can adapt to various complex external environments, is convenient for placing samples with different sizes and shapes, and reduces the shape limitation of scannable samples. For curved (or uneven) samples, the system can obtain photon counting information with good spatial consistency, and surface element composition and distribution information.
The invention consists of a multidimensional motion device, a contour information acquisition device, a micro-region XRF and a data analysis and display system, as shown in figure 1. The multi-dimensional motion device is used for carrying the profile information acquisition device and the micro-region XRF to carry out multi-dimensional motion, and can be a device capable of carrying out multi-dimensional translation and rotation, such as a mechanical arm or a multi-axis displacement table; the profile information acquisition device is used for acquiring profile information of the surface of an object and can be a depth camera, a laser displacement sensor and the like; the micro-region XRF comprises an X-ray source, a multi-capillary lens (used for generating high-brightness and tiny focal spot excitation X-rays) and a particle detector (usually a silicon drift detector used for recording characteristic spectrum of the surface of a sample), wherein the multi-capillary lens and the detector form a certain included angle to form a typical energy dispersion micro-region XRF; the data analysis and display system is used for real-time display and element analysis of characteristic spectra and three-dimensional visualization of element distribution on the surface of a sample.
The invention also provides a scanning track generation method which is used for converting the acquired profile information into the scanning track information which can be used for the multidimensional movement device to analyze.
The method comprises the following steps: intercepting profile data, intercepting data downsampling, removing outliers in downsampled data, upsampling to supplement incomplete data, removing redundant outliers, downsampling to generate scanning point data, calculating a normal vector of a curved surface, and converting a coordinate system and a direction angle of the scanning point.
The invention also comprises a three-dimensional visualization method of the surface element distribution, wherein the three-dimensional visualization of the surface element distribution is used for three-dimensional imaging of the surface element distribution of a curved surface (surface unevenness) sample, and can realize custom element display and characterization.
The technical scheme of the invention is as follows:
the micro-area XRF element analysis and multidimensional imaging system is characterized by comprising a multidimensional movement device, a profile information acquisition device, a micro-area XRF and a data analysis and display system;
the multi-dimensional motion device is used for carrying and driving the profile information acquisition device and the micro-region XRF to perform multi-dimensional motion;
the contour information acquisition device is used for scanning the contour of the object to be detected under the drive of the multi-dimensional motion device, acquiring the contour information of the object to be detected and sending the contour information to the multi-dimensional motion device;
the micro-region XRF is used for moving to a working position corresponding to each scanning point along a scanning track under the drive of the multi-dimensional movement device, carrying out X-ray irradiation on the object to be detected, acquiring an X-ray fluorescence spectrum emitted by the object to be detected and sending the X-ray fluorescence spectrum to the data analysis and display system; the multi-dimensional motion device determines the working position and the scanning track of the micro-region XRF relative to each scanning point on the object to be detected according to the contour information;
the data analysis and display system is used for displaying the X-ray fluorescence spectrum in real time and analyzing elements to obtain the element type and content information of each scanning point.
Further, the multi-dimensional motion device is a mechanical arm or a multi-axis displacement table; the profile information acquisition device is a depth camera or a laser displacement sensor; the domain XRF is an energy dispersive domain XRF.
Further, the micro-area XRF comprises an X-ray exciter for generating a high brightness and tiny focal spot, and an excitation-ray detector.
Further, the object to be detected is a curved object.
A micro-area XRF elemental analysis and multi-dimensional imaging method, comprising the steps of:
1) The multi-dimensional motion device drives the mounted contour information acquisition device to scan the contour of the object to be detected, and contour information of the object to be detected is acquired;
2) The multi-dimensional motion device determines the working position and the scanning track of the carried micro-area XRF relative to each scanning point on the object to be detected according to the contour information;
3) The multi-dimensional motion device moves the micro-region XRF to the working position corresponding to each scanning point according to the scanning track, performs X-ray irradiation on the object to be detected, acquires an X-ray fluorescence spectrum emitted by the object to be detected, and sends the X-ray fluorescence spectrum to a data analysis and display system;
4) And the data analysis and display system displays the X-ray fluorescence spectrum in real time and performs element analysis to obtain element type and content information of each scanning point.
Further, the method for determining the working position and the scanning track of the carried micro-region XRF relative to each scanning point on the object to be detected by the multi-dimensional motion device according to the contour information comprises the following steps:
21 The multi-dimensional motion device intercepts required contour data from the contour information according to a scanning area selected by a user on the contour information;
22 The multi-dimensional motion device samples the intercepted profile data;
23 The multi-dimensional motion device samples the sampling result in the step 22) according to the sampling interval set by a user to generate scanning points; calculating the normal vector of the surface of the object to be detected at each scanning point;
24 The multi-dimensional motion device converts the three-dimensional position coordinates of each scanning point and the normal vector at the corresponding surface into a scanning track for controlling the micro-region XRF to move.
Further, the sampling method in step 22) is as follows: firstly, the intercepted contour data is divided into three-dimensional volume elements with specified size, and all data points in each three-dimensional volume element are replaced by mass center data points of the three-dimensional volume element; the outliers are then removed and the supplemental incomplete data points are upsampled, and then the outliers are removed again.
Further, the method for converting the three-dimensional position coordinates of each scanning point and the normal vector on the corresponding surface of each scanning point into the scanning track for controlling the movement of the micro-area XRF by the multi-dimensional movement device comprises the following steps: the multi-dimensional motion device moves the position coordinates (x 0 ,y 0 ,z 0 ) T is represented by formula (x, y, z) T ＝C·(x 0 ,y 0 ,z 0 ) T Converting the coordinate point into a coordinate point (x, y, z) on a scanning track which can be read by a multi-dimensional motion device, wherein C is a coordinate transformation matrix; normal to the scan pointQuantity (n) x ,n y ,n z ) The angle information (O, A, T) of coordinate points (x, y, z) on a scanning track which can be read by the multi-dimensional motion device is converted into the angle information (O, A, T) of the coordinate points (x, y, z) on the scanning track which can be read by the multi-dimensional motion device; wherein, the liquid crystal display device comprises a liquid crystal display device,
t= - (180-O); then generating a motion track according to the position coordinates (x, y, z) and the angle information (O, A, T) corresponding to each scanning point; and confirming the motion trail information according to the set safe scanning rule, deleting unsafe points and generating the scanning trail.
Further, the method for displaying the X-ray fluorescence spectrum in real time and analyzing elements by the data analysis and display system comprises the following steps:
31 Directly adding the counts of all points of each energy channel in the X-ray fluorescence spectrum in the scanning area to obtain a sum spectrum containing the types of elements in the whole scanning area; peak searching and element matching are carried out on the spectrum, and main element types of the constituent substances in the scanning area are identified;
32 Extracting and combining the maximum count of each energy channel in the X-ray fluorescence spectrum to obtain a maximum spectrum; carrying out peak searching and element matching on the maximum spectrum, and identifying elements existing on the surface of the object;
33 In the X-ray fluorescence spectrum acquired by each scanning point, carrying out Gaussian fitting on the identified element spectrum peak, and calculating the spectrum peak area in the half-width range to obtain the content of various elements of each scanning point;
34 Combining the spectral peak area of each element at each scanning point with the position information of the corresponding scanning point, and converting the combined spectral peak area of each element into a three-dimensional RGB point cloud file to obtain a three-dimensional element distribution image of the surface of the object to be detected.
The invention has the following advantages:
according to the invention, the optimal spatial position and direction of the micro-region XRF are obtained through the acquisition and processing of the object surface profile information, the accurate scanning of the surface of a curved surface (or surface unevenness) sample is realized through a multi-dimensional motion device (including but not limited to a mechanical arm), the problem of spatial inconsistency (inconsistent X-ray focal position and inconsistent detector spatial position and direction for each scanning point on the curved surface sample) in the existing XRF scanning technology is solved, and the focal position and detector position of X-rays are in the same calibration position for each scanning point. The invention improves the accuracy of the composition and distribution measurement of the surface elements of the curved surface (or uneven surface) sample, and can adapt to various scanning scenes.
The scanning track generation method can realize effective sampling and processing of the position information of the surface of the curved surface (or uneven surface) sample, and prevent incomplete or wrong scanning points from being generated due to the acquisition error of the contour acquisition device.
The three-dimensional visualization method for the surface element distribution can enable the generated three-dimensional surface element distribution image to have good corresponding relation with the sample object, and can select the elements to be displayed and adjust the color intensity of each element in a self-defined way, thereby greatly facilitating the observation and analysis of operators.
Drawings
Fig. 1 is a schematic diagram of a system architecture.
FIG. 2 is an effect diagram of a scan trajectory generation method;
(a) original image, (b) first downsampling, (c) first removal of discrete points, (d) upsampling result, (e) second removal of discrete points, (f) second downsampling.
FIG. 3 is a diagram of a data analysis and display system.
FIG. 4 is a schematic diagram of spectroscopic analysis;
(a) And a spectral plot, (b) a maximum spectral plot.
Fig. 5 is a system workflow diagram.
Detailed Description
The invention is described in further detail below with reference to the accompanying drawings.
FIG. 5 is a system workflow diagram of the invention, with specific steps comprising:
the first step: acquiring profile information
1. The user performs the operations of system connection, zero setting, preparation and the like of the multi-dimensional motion device (including but not limited to a mechanical arm) on an interface of application software (operation software of the system: including the functions of controlling the work of various devices in the system, realizing data analysis, display and the like).
2. Parameters for profile information collection (including, but not limited to, exposure time, light brightness, collection height, etc. for the present system) are set by the user at the application software interface;
3. the multi-dimensional motion device carries an object surface profile acquisition device (including but not limited to a depth camera, a laser displacement sensor and the like) to move to a calibration position according to set parameters so as to scan the profile of the scanned object;
4. contour information of the object (including but not limited to three-dimensional space coordinates of the surface of the object, normal vectors, optical images and the like) is transmitted to application software for processing after being acquired;
and a second step of: as shown in FIG. 2, a scan trajectory is generated
1. The user interactively selects a scanning area of interest in application software, and sets single sampling time and sampling interval;
2. intercepting required profile information data according to selected scan area image parameters (including but not limited to a start point/end point X coordinate, a start point/end point Y coordinate);
3. the application software can sample, integrate and optimize the scanning points through an internal data point sampling algorithm and generate scanning point information (comprising three-dimensional position coordinates of space and normal vector data of the surface), and the specific steps are as follows:
A. downsampling the profile information data to reduce the amount of data;
the principle of downsampling is to divide a three-dimensional space into three-dimensional volume elements of a specified size, and replace all data points within the volume elements with corresponding centroid data points. The number of data points is greatly reduced, and the subsequent point cloud processing time is saved.
B. Removing outliers;
the principle of outlier removal is to calculate the average distance between a point and a data point in a specified range nearby, and to delete data points greater than the critical distance compared to the specified critical distance. As shown in the box in fig. 2 (c), removing outliers can effectively remove noisy data points that deviate from the scan surface, avoiding being mistaken for real data points during upsampling.
C. Upsampling supplemental incomplete data points;
the principle of upsampling is to perform polynomial fitting of a curved surface according to data points in the neighborhood, and then perform interpolation according to specified parameters to construct new point cloud data. The up-sampling can fill the point cloud data loss caused by the reasons of the change of the reflectivity of the surface of the object, and the like, as shown in a circle of fig. 2 (d), the up-sampling can effectively fill the incomplete data points.
D. Removing outliers again;
the outlier removal is again performed, as shown by the square box in fig. 2 (e), to avoid the generation of noisy data points off the object surface by the upsampling in step C.
E. Downsampling to generate scanning points;
the purpose of the second downsampling is to grid the point cloud data according to the specified spacing, so that scanning and data analysis are facilitated.
F. Calculating the normal vector of the curved surface at the scanning point;
the method for generating the normal vector of the point cloud is to fit a curved surface by using data points in the neighborhood, calculate a tangent plane of the curved surface at the target data point, and calculate the normal vector at the target data point according to the tangent plane.
4. Converting the three-dimensional position coordinates of the scanning points and the normal vector data of the surface into motion track information (including but not limited to mechanical arm motion position coordinates and rotation angle parameters) under a multi-dimensional motion device coordinate system;
the track information readable by the multi-dimensional motion device includes position coordinates (x, y, z) and angle information (O, a, T). Through calibration and correction, a position coordinate transformation formula can be calculated:
(x,y,z) T ＝C·(x 0 ,y 0 ,z 0 ) T
(x 0 ,y 0 ,z 0 ) T is the position coordinates in the laboratory coordinate system (the coordinate system of the contour acquisition device). C is a coordinate transformation matrix.
Normal vector in laboratory coordinate system (n x ,n y ,n z ) The angle information (O, A, T) under the coordinate system of the motion device is converted, and the formula can be deduced:
|A|＝arccos(n z )
T＝-(180-O)
5. and confirming the motion trail information according to the safety scanning rule of the multidimensional motion device, and deleting unsafe points.
By the scanning track generation method, the complete scanning track covering the scanning area can be obtained.
And a third step of: motion and scanning
1. After confirming that the scanning point is correct, the user transmits the scanning point information to the multidimensional movement device through an application program interface;
2. the multi-dimensional movement device analyzes the scanning point information, sequentially moves to each position point according to the transmission sequence, deflects to the corresponding space angle direction, and keeps the distance and the included angle between the receiving end of the detector and the surface of the object unchanged, so that the counting accuracy is improved;
3. after the multi-dimensional motion device analyzes the scanning point information, a user sends a scanning ready instruction to the multi-dimensional motion device through application software;
4. the multi-dimensional movement device receives a scanning ready instruction and then immediately moves the initial position of a scanning point to prepare for scanning;
5. after the multidimensional movement device moves to a ready position, a user selects 'point-by-point scanning' or 'continuous scanning' through application software, and sends an instruction for starting acquisition to a movement acquisition system;
6. the motion acquisition system comprises a multi-dimensional motion device, a detector device and a real-time spectrum display system, when the motion acquisition system receives an instruction for starting acquisition, the multi-dimensional motion device sequentially moves to each scanning point, and stays at each scanning point according to single acquisition time set by a user, during the period, the detector records the number of photons entering a detection sensitive area, and transmits scanning data of each point to application software, and a spectrogram of the scanning point is displayed in real time in an application software window and is stored locally in real time;
7. and the whole acquisition process is completed until the last scanning point is acquired.
Fourth step: data processing and analysis
The data processing modules of the system are shown in fig. 3, and are mainly divided into: spectroscopic analysis and three-dimensional visualization of surface element distribution.
1) Spectral analysis:
the spectral analysis is to obtain information such as the composition and distribution of the element components on the surface of the material through the spectral data of each scanning point. The spectral data is photon counts of the detector in a series of energy channels. Spectral analysis in the system comprises sum spectral analysis, maximum spectral analysis and single-point element quantitative analysis. Three different analytical methods were used to obtain different material composition information, respectively.
a. And spectral analysis: the spectral data of all scan points are summed, i.e. the counts of the corresponding energy channels in the spectra of all scan points are added. Thus, the sum spectrum of all the scanning points can be obtained. By peak finding and element matching of the spectrum, the user can learn the main element types of the composition substances in the scanning area;
b. maximum spectral analysis: and counting the corresponding energy channels in the spectrums of all the scanning points to obtain the maximum value, and combining the energy channels with the maximum counts into the maximum spectrums. By carrying out peak searching and element matching on the maximum spectrum, a user can know the element types which cannot be distinguished in the sum spectrum and are only locally dominant;
c. single point elemental quantitative analysis: in the spectrum of each scanning point, gaussian fitting is carried out on the identified element spectrum peak, the spectrum peak area in the half-width range is calculated, the content of various elements in each scanning point is obtained, and the spectrum analysis result is shown in figure 4.
2) Three-dimensional visualization of surface element distribution:
the system can realize three-dimensional visualization of the distribution of the surface elements of the curved surface sample. By means of the point cloud data structure, component content images corresponding to all scanning points of the sample can be restored without distortion, so that good correspondence can be formed with the sample, and comparison and analysis of a user are facilitated.
a. The specific element distribution shows: counting the characteristic peak intensities of the specific elements at all scanning points; the maximum and minimum characteristic peak intensities of the element in all scanning points are counted; mapping the element intensities of all the scanning points to the same scale through maximum and minimum normalization; each specific element is endowed with a specific RGB color value, and corresponding brightness is matched according to the intensity of each scanning point; and carrying out point cloud matching on the position information, RGB value and brightness of each scanning point, and generating a three-dimensional point cloud image with specific element content distribution.
b. The mixed surface element distribution shows: respectively counting the characteristic peak intensity of each element at all scanning points; carrying out maximum and minimum normalization processing on the intensity values according to the flow; matching brightness values according to the processed intensity values, and giving specific RGB values; and (3) carrying out position point matching on the three-dimensional point cloud image of each element, carrying out weighted summation on the RBG value and the brightness value, and enabling an operator to automatically adjust the brightness of each element according to analysis requirements to generate a three-dimensional point cloud fusion image with various element contents and distribution information.
Although specific embodiments of the invention have been disclosed for illustrative purposes, it will be appreciated by those skilled in the art that the invention may be implemented with the help of a variety of examples: various alternatives, variations and modifications are possible without departing from the spirit and scope of the invention and the appended claims. Therefore, it is intended that the invention not be limited to the particular embodiment disclosed as the best mode contemplated for carrying out this invention, but that the invention will have the scope indicated by the scope of the appended claims.
Claims (8)
1. The micro-area XRF element analysis and multidimensional imaging system is characterized by comprising a multidimensional movement device, a profile information acquisition device, a micro-area XRF and a data analysis and display system;
the multi-dimensional motion device is used for carrying and driving the profile information acquisition device and the micro-region XRF to perform multi-dimensional motion;
the contour information acquisition device is used for scanning the contour of the object to be detected under the drive of the multi-dimensional motion device, acquiring the contour information of the object to be detected and sending the contour information to the multi-dimensional motion device;
the micro-region XRF is used for moving to a working position corresponding to each scanning point along a scanning track under the drive of the multi-dimensional movement device, carrying out X-ray irradiation on the object to be detected, acquiring an X-ray fluorescence spectrum emitted by the object to be detected and sending the X-ray fluorescence spectrum to the data analysis and display system; the multi-dimensional motion device determines the working position and the scanning track of the micro-region XRF relative to each scanning point on the object to be detected according to the contour information;
the data analysis and display system is used for displaying the X-ray fluorescence spectrum in real time and analyzing elements to obtain element type and content information of each scanning point;
the method for determining the working position and the scanning track of the carried micro-region XRF relative to each scanning point on the object to be detected by the multi-dimensional motion device according to the contour information comprises the following steps: 21 The multi-dimensional motion device intercepts required contour data from the contour information according to a scanning area selected by a user on the contour information; 22 The multi-dimensional motion device samples the intercepted profile data; 23 The multi-dimensional motion device samples the sampling result in the step 22) according to the sampling interval set by a user to generate scanning points; calculating the normal vector of the surface of the object to be detected at each scanning point; 24 The multi-dimensional motion device converts the three-dimensional position coordinates of each scanning point and the normal vector on the corresponding surface into a scanning track for controlling the micro-region XRF to move;
the multi-dimensional motion device coordinates and corresponds the three-dimensional position of each scanning point to a tableThe method for converting the normal vector at the surface into the scanning track for controlling the movement of the micro-area XRF by the multi-dimensional movement device comprises the following steps: the multi-dimensional motion device moves the position coordinates (x 0 ,y 0 ,z 0 ) T By the formula (x, y, z) T ＝C·(x 0 ,y 0 ,z 0 ) T Converting the coordinate point into a coordinate point (x, y, z) on a scanning track which can be read by a multi-dimensional motion device, wherein C is a coordinate transformation matrix; the normal vector (n x ,n y ,n z ) The angle information (O, A, T) of coordinate points (x, y, z) on a scanning track which can be read by the multi-dimensional motion device is converted into the angle information (O, A, T) of the coordinate points (x, y, z) on the scanning track which can be read by the multi-dimensional motion device; wherein |a|=arccos (n z )，
T= - (180-O); then generating a motion track according to the position coordinates (x, y, z) and the angle information (O, A, T) corresponding to each scanning point; and confirming the motion trail information according to the set safe scanning rule, deleting unsafe points and generating the scanning trail.
2. The system of claim 1, wherein the multi-dimensional motion device is a robotic arm or a multi-axis displacement table; the profile information acquisition device is a depth camera or a laser displacement sensor; the domain XRF is an energy dispersive domain XRF.
3. The system of claim 1, wherein the micro-XRF comprises an X-ray exciter for producing a high intensity and tiny focal spot, and an excitation-ray detector.
4. The system of claim 1, wherein the object to be inspected is a curved object.
5. A micro-area XRF elemental analysis and multi-dimensional imaging method, comprising the steps of:
1) The multi-dimensional motion device drives the mounted contour information acquisition device to scan the contour of the object to be detected, and contour information of the object to be detected is acquired;
2) The multi-dimensional motion device determines the working position and the scanning track of the carried micro-area XRF relative to each scanning point on the object to be detected according to the contour information; wherein, the liquid crystal display device comprises a liquid crystal display device,
the method for determining the working position and the scanning track of the carried micro-region XRF relative to each scanning point on the object to be detected by the multi-dimensional motion device according to the contour information comprises the following steps: 21 The multi-dimensional motion device intercepts required contour data from the contour information according to a scanning area selected by a user on the contour information; 22 The multi-dimensional motion device samples the intercepted profile data; 23 The multi-dimensional motion device samples the sampling result in the step 22) according to the sampling interval set by a user to generate scanning points; calculating the normal vector of the surface of the object to be detected at each scanning point; 24 The multi-dimensional motion device converts the three-dimensional position coordinates of each scanning point and the normal vector on the corresponding surface into a scanning track for controlling the micro-region XRF to move;
the method for converting the three-dimensional position coordinates of each scanning point and the normal vector at the corresponding surface into the scanning track of the micro-area XRF movement controlled by the multi-dimensional movement device comprises the following steps: the multi-dimensional motion device moves the position coordinates (x 0 ,y 0 ,z 0 ) T By the formula (x, y, z) T ＝C·(x 0 ,y 0 ,z 0 ) T Converting the coordinate point into a coordinate point (x, y, z) on a scanning track which can be read by a multi-dimensional motion device, wherein C is a coordinate transformation matrix; the normal vector (n x ,n y ,n z ) The angle information (O, A, T) of coordinate points (x, y, z) on a scanning track which can be read by the multi-dimensional motion device is converted into the angle information (O, A, T) of the coordinate points (x, y, z) on the scanning track which can be read by the multi-dimensional motion device; wherein |a|=arccos (n z )，
T= - (180-O); then generating a motion track according to the position coordinates (x, y, z) and the angle information (O, A, T) corresponding to each scanning point; according to the set security scanning rule pairConfirming the motion trail information, deleting unsafe points and generating the scanning trail;
3) The multi-dimensional motion device moves the micro-region XRF to the working position corresponding to each scanning point according to the scanning track, performs X-ray irradiation on the object to be detected, acquires an X-ray fluorescence spectrum emitted by the object to be detected, and sends the X-ray fluorescence spectrum to a data analysis and display system;
4) And the data analysis and display system displays the X-ray fluorescence spectrum in real time and performs element analysis to obtain element type and content information of each scanning point.
6. The method according to claim 5, wherein the sampling method in step 22) is: firstly, the intercepted contour data is divided into three-dimensional volume elements with specified size, and all data points in each three-dimensional volume element are replaced by mass center data points of the three-dimensional volume element; the outliers are then removed and the supplemental incomplete data points are upsampled, and then the outliers are removed again.
7. The method of claim 5, wherein the method of real-time display and elemental analysis of the X-ray fluorescence spectrum by the data analysis and display system is:
31 Directly adding the counts of all points of each energy channel in the X-ray fluorescence spectrum in the scanning area to obtain a sum spectrum containing the types of elements in the whole scanning area; peak searching and element matching are carried out on the spectrum, and main element types of the constituent substances in the scanning area are identified;
32 Extracting and combining the maximum count of each energy channel in the X-ray fluorescence spectrum to obtain a maximum spectrum; carrying out peak searching and element matching on the maximum spectrum, and identifying elements existing on the surface of the object;
33 In the X-ray fluorescence spectrum acquired by each scanning point, carrying out Gaussian fitting on the identified element spectrum peak, and calculating the spectrum peak area in the half-width range to obtain the content of various elements of each scanning point;
34 Combining the spectral peak area of each element at each scanning point with the position information of the corresponding scanning point, and converting the combined spectral peak area of each element into a three-dimensional RGB point cloud file to obtain a three-dimensional element distribution image of the surface of the object to be detected.
8. The method of claim 5 or 6, wherein the profile information includes, but is not limited to, three-dimensional spatial coordinates, normal vectors and optical images of the surface of the object to be inspected; the object to be detected is a curved object; the multi-dimensional motion device is a mechanical arm or a multi-axis displacement table; the profile information acquisition device is a depth camera or a laser displacement sensor; the domain XRF is an energy dispersive domain XRF.
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