A method for reconstructing distribution of indoor gamma radiation sources

Abstract

The application relates to an indoor gamma radioactive source distribution reconstruction method, which comprises the following steps: quickly scanning and measuring a target room by adopting a dose rate field measuring device to obtain a gamma dose rate field and a point cloud model of the target room; filtering the point cloud model and exporting the coordinates of each point in the processed model; calculating the back projection weight of each measuring point in the gamma dose rate field to each point in the point cloud model; calculating the back projection value of the measured gamma dose rate field to each point in the filtered point cloud model; and attaching the back projection value to the corresponding point in the point cloud model after mapping the back projection value into color, so as to obtain a point cloud model capable of reflecting the gamma radioactive source distribution. According to the method disclosed in the application, the approximate distribution of the radioactive source in the scene can be quickly and preliminarily calculated by using the measured gamma dose rate field, which is used as prior knowledge for subsequent detailed radioactive source characterization work, and has practical application value.

Description

Technical Field

[0001] This invention belongs to the field of radioactivity characterization, and specifically relates to a method for reconstructing the distribution of indoor gamma radiation sources. Background Technology

[0002] Nuclear facility decommissioning takes place in the final stage of the operational lifecycle of nuclear facilities (nuclear power plants, nuclear fuel cycle facilities, medical accelerators, etc.). Its ultimate goal is to remove all components of the facility, manage the generated radioactive waste, and release the site for new uses. Nuclear decommissioning is a massive, multidisciplinary project that includes a range of tasks such as radiological characterization, decontamination, dismantling, waste disposal, and cost estimation.

[0003] Radiographic characterization (determining the quantity, type, and distribution of radionuclides) plays a unique and crucial role in nuclear decommissioning because its output forms the basis for other decommissioning procedures. For example, appropriate decontamination and dismantling technologies need to be selected based on the type, activity, and distribution of radionuclides, and the resulting radioactive waste needs to be classified and managed according to its activity and half-life. Obtaining comprehensive and reliable information on radioactive sources is a prerequisite for the smooth implementation of nuclear facility decommissioning.

[0004] In existing technologies, in-situ gamma spectroscopy and gamma cameras are commonly used to characterize radioactive sources within nuclear facilities. In-situ gamma spectroscopy involves using a collimated gamma spectrometer to acquire gamma spectra of the region of interest, then combining this with the geometric features between the radioactive source and the detector to calculate the activity of the source. However, collimated gamma spectrometers have a small field of view, making it difficult to reconstruct radioactive sources throughout the entire room. Therefore, in practice, the location of gamma sources is mainly achieved by overlaying the imaging results from a gamma camera with scene images or models. However, gamma camera image acquisition takes a long time, typically several hours, resulting in low efficiency in reconstructing the distribution of gamma sources. Summary of the Invention

[0005] To address the shortcomings of existing technologies, the present invention aims to provide a method for reconstructing the distribution of indoor gamma radiation sources. This method can quickly and preliminarily calculate the approximate distribution of radiation sources in a scene using the measured gamma dose rate field, thus serving as prior knowledge for subsequent detailed characterization of radiation sources and having practical application value.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is: a method for reconstructing the distribution of indoor gamma radiation sources, the method comprising the following steps:

[0007] a. The target room is rapidly scanned and measured using a dose rate field measurement device to obtain the γ dose rate field and point cloud model of the target room;

[0008] b. Filter the point cloud model and export the coordinates of each point in the processed model;

[0009] c. Calculate the back projection weight from each measurement point in the γ dose rate field to each point in the point cloud model;

[0010] d. Calculate the back projection value of each point in the filtered point cloud model of the measured γ dose rate field;

[0011] e. Map the back-projected values ​​into colors and attach them to the points in the corresponding point cloud model to obtain a point cloud model that reflects the distribution of the γ-ray source.

[0012] Furthermore, the dose rate field measurement device in step a includes a SLAM system and a γ dose rate meter. The SLAM system performs a moving scan model of the target room to obtain a point cloud model of the room. At the same time, the SLAM system outputs the spatial position of the device in real time and combines it with the dose rate output by the γ dose rate meter to achieve rapid measurement of the γ dose rate field.

[0013] Furthermore, the SLAM system's mobile scanning range needs to cover the region of interest within the room, i.e., the high-probability radiation source area.

[0014] Furthermore, the high-probability radioactive source region includes typical radioactive structures within a nuclear facility.

[0015] Furthermore, the typical radioactive structure includes pipes and waste bins.

[0016] Furthermore, in step b, noise points in the point cloud model are removed by filtering and the number of points in the point cloud model is reduced to reduce the computational load. The PCD format file of the point cloud model is parsed to export the three-dimensional coordinates of each point in the point cloud model.

[0017] Furthermore, the formula for calculating the back projection weight from the measurement point to the model point in step c is as follows:

[0018]

[0019] In the formula, B is the cumulative factor, which is related to distance, shielding, and gamma particle energy; e -μt This is the attenuation term, related to particle energy and shielding; d ij The distance from measurement point i to model point j is calculated from the three-dimensional coordinates of the two points; F(E) is the conversion factor from flux rate to dose rate, which is related to particle energy.

[0020] Furthermore, the formula for calculating the back projection value in step d is as follows:

[0021] S=W·D (2)

[0022] In the formula, S is a matrix composed of the back projection values ​​of all points in the point cloud model, and W is the back projection weight w. ijThe matrix formed by these measurements, where D is the matrix composed of all dose rate measurements.

[0023] Furthermore, in step e, the back-projection values ​​are mapped into colors using RGB color mapping and then attached to the points in the corresponding point cloud model. The intensity of the color mapped from the back-projection values ​​reflects the probability of the presence of a radiation source.

[0024] Furthermore, in step e, the back-projected values ​​are mapped into colors using RGB color mapping and then appended to the points in the corresponding point cloud model. One form of the RGB color mapping formula is as follows:

[0025]

[0026] In the formula r j g j b j Let represent the RGB value of the j-th model point, and C be a constant scaling factor.

[0027] Furthermore, under the aforementioned color mapping formula, the deeper the red, the higher the probability of the presence of a gamma radiation source.

[0028] Furthermore, the color mapping formula is not unique; its purpose is to reflect the probability of the presence of a radioactive source by utilizing the magnitude of the back projection value corresponding to the color.

[0029] The beneficial technical effects of this invention are as follows: The indoor gamma radiation source distribution reconstruction method disclosed in this invention overcomes the problem of low efficiency of the mainstream gamma camera method in the prior art. It can quickly measure data using a dose rate field measurement device without relying on prior knowledge, and quickly and comprehensively reconstruct the distribution of gamma radiation sources in the scene, which greatly improves the reconstruction efficiency.

[0030] Furthermore, it provides a point cloud model of the scene and directly displays the reconstructed γ-ray source distribution through the color distribution of the point cloud model, which is more vivid and intuitive than the reconstruction results obtained by existing technologies. Attached Figure Description

[0031] Figure 1 This is a flowchart illustrating an indoor gamma radiation source distribution reconstruction method according to an embodiment of the present invention;

[0032] Figure 2 This is a schematic diagram of the structure of a rapid γ dose rate field measurement device according to an embodiment of the present invention;

[0033] Figure 3 This is a schematic diagram illustrating the working process of the rapid γ dose rate field measurement device according to an embodiment of the present invention;

[0034] Figure 4 This is a schematic diagram of point cloud model filtering shown in an embodiment of the present invention;

[0035] Figure 5 This is a schematic diagram illustrating the results of reconstructing the distribution of indoor gamma-ray sources using an embodiment of the present invention.

[0036] Among them: 201-SLAM system, 202-dose rate meter, 301-dose rate field, 302-pipeline, 303-waste bin. Detailed Implementation

[0037] The present invention will now be further described with reference to the accompanying drawings and specific embodiments.

[0038] Example 1

[0039] like Figure 1 As shown in the figure, an embodiment of the present invention provides a method for reconstructing the distribution of indoor gamma radiation sources, the method comprising the following steps:

[0040] a. The target room is rapidly scanned and measured using a dose rate field measurement device to obtain the γ dose rate field and point cloud model of the target room;

[0041] b. Filter the point cloud model and export the coordinates of each point in the processed model;

[0042] c. Calculate the back projection weight from each measurement point in the γ dose rate field to each point in the point cloud model;

[0043] d. Calculate the back projection value of each point in the filtered point cloud model of the measured γ dose rate field;

[0044] e. Map the back-projected values ​​into colors and attach them to the points in the corresponding point cloud model to obtain a point cloud model that reflects the distribution of the γ-ray source.

[0045] like Figure 2 As shown, the dose rate field measurement device in step a includes a SLAM (simultaneous localization and mapping) system 201 and a gamma dose rate meter 202. The SLAM system 201 uses an RGBD camera or a 3D LiDAR to perform a moving scan and model of the target room, obtaining a point cloud model of the room. Simultaneously, the SLAM system 201 outputs the spatial position of the device in real time, combined with the dose rate output by the gamma dose rate meter, to achieve rapid measurement of the gamma dose rate field 301. It should be noted that, as... Figure 3 As shown, during the moving scan process, it is necessary to acquire a model of the entire room as much as possible, especially in areas where radioactive sources are likely to exist, such as pipe 302 and waste bin 303.

[0046] The purpose of filtering the point cloud model in step b includes removing noise points from the model and reducing the number of points in the point cloud model to reduce computational load. For example... Figure 4 As shown, the number of points in the filtered point cloud model is reduced, but it still reflects the real scene well. The 3D coordinates of each point in the point cloud model are exported by parsing the PCD format file of the point cloud model.

[0047] The formula for calculating the back projection weights from the measurement points to the model points in step c is as follows:

[0048]

[0049] In the formula, B is the cumulative factor, which is related to distance, shielding, and gamma particle energy; e -μt This is the attenuation term, related to particle energy and shielding; d ij The distance from measurement point i to model point j is calculated from the three-dimensional coordinates of the two points; F(E) is the conversion factor from fluence rate to dose rate, which is related to particle energy. Since only the dose rate field and point cloud model are available data, the effects of particle energy and shielding are generally not considered in practice, so the back projection weights are simplified as follows:

[0050]

[0051] The formula for calculating the back projection value in step d is as follows:

[0052] S = W·D

[0053] In the formula, S is a matrix composed of the back projection values ​​of all points in the point cloud model, and W is the back projection weight w. ij The matrix formed by these measurements, where D is the matrix composed of all dose rate measurements.

[0054] In step e, the color of each point is changed according to the color mapped by the back projection value of each point in the point cloud model to obtain a new point cloud map. The intensity of the color mapped by the back projection value reflects the probability of the presence of a radiation source.

[0055] like Figure 5 As shown, the color distribution in the new point cloud map reflects the distribution of the gamma radiation source. The RGB color mapping formula is as follows:

[0056]

[0057] In the formula r j g j b jLet be the RGB value of the j-th model point, and C be a constant scaling factor. The mapping result is that the deeper the red, the higher the probability of the presence of a gamma radiation source. In this embodiment of the invention, only the mapping method corresponding to the above color mapping formula is used as an example for illustration. In fact, it is not limited to this, and other mapping methods can achieve the same effect. The color mapping formula is not unique. Its purpose is to reflect the probability of the presence of a radiation source by using the magnitude of the back projection value corresponding to the color depth, so as to more clearly and intuitively understand the probability of the presence of a radiation source.

[0058] As can be seen from the above embodiments, the indoor gamma-ray source distribution reconstruction method disclosed in this invention can quickly reconstruct the distribution of indoor gamma-ray sources, and can be used to achieve the preliminary location of gamma-ray sources or radioactive materials in the nuclear facility operation site.

[0059] The method described in this invention is not limited to the embodiments described in the specific implementation. Other implementation methods derived by those skilled in the art based on the technical solution of this invention also fall within the scope of technical innovation of this invention.

Claims

1. A method for reconstructing the distribution of an indoor gamma radiation source, the method comprising the following steps: a. The target room is rapidly scanned and measured using a dose rate field measurement device to obtain the γ dose rate field and point cloud model of the target room; b. Filter the point cloud model and export the coordinates of each point in the processed model; c. Calculate the back projection weight from each measurement point in the γ dose rate field to each point in the point cloud model; d. Calculate the back projection value of each point in the filtered point cloud model of the measured γ dose rate field; e. Map the back-projection values ​​into colors and then attach them to the points in the corresponding point cloud model to obtain a point cloud model that can reflect the distribution of the γ-ray source. The dose rate field measurement device mentioned in step a includes a SLAM system and a γ dose rate meter. The SLAM system performs a moving scan model of the target room to obtain a point cloud model of the room. At the same time, the SLAM system outputs the spatial position of the device in real time and combines it with the dose rate output in real time by the γ dose rate meter to achieve rapid measurement of the γ dose rate field. The formula for calculating the back projection weights from the measurement points to the model points in step c is as follows: In the formula This is a cumulative factor, related to distance, shielding, and gamma particle energy; This is a decay term, related to particle energy and shielding. For measurement points To model point The distance between the two points is calculated from their three-dimensional coordinates. This is the conversion factor from infusion rate to dose rate, and it is related to particle energy.

2. The method for reconstructing the distribution of indoor gamma radiation sources as described in claim 1, characterized in that: The SLAM system's mobile scanning range needs to cover the region of interest within the room, which is an area with a high probability of containing a radiation source.

3. The method for reconstructing the distribution of indoor gamma radiation sources as described in claim 2, characterized in that: The region of interest contains typical radioactive structures within a nuclear facility, including pipes and waste bins.

4. The method for reconstructing the distribution of indoor gamma radiation sources as described in claim 1, characterized in that: In step b, noise points in the point cloud model are removed by filtering and the number of points in the point cloud model is reduced to reduce the amount of computation. The PCD format file of the point cloud model is parsed to export the three-dimensional coordinates of each point in the point cloud model.

5. The method for reconstructing the distribution of indoor gamma radiation sources as described in claim 1, characterized in that: The formula for calculating the back projection value in step d is as follows: In the formula Let be the matrix consisting of the back projection values ​​of all points in the point cloud model. Back projection weights The matrix formed A matrix consisting of all dose rate measurements.

6. The method for reconstructing the distribution of indoor gamma radiation sources as described in claim 1, characterized in that: In step e, the back-projection values ​​are mapped into colors using RGB color mapping and then attached to the points in the corresponding point cloud model. The intensity of the color mapped from the back-projection values ​​reflects the probability of the presence of a radiation source.

7. The method for reconstructing the distribution of indoor gamma radiation sources as described in claim 6, characterized in that: In step e, the back-projected values ​​are mapped into colors using RGB color mapping and then appended to the points in the corresponding point cloud model. One form of the RGB color mapping formula is as follows: In the formula For the first RGB values ​​of each model point It is a constant scaling factor.

8. The method for reconstructing the distribution of an indoor gamma radiation source as described in claim 7, characterized in that: The deeper the red color in the mapping result, the higher the probability of the presence of a gamma radiation source.

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