CN111580149B - Fuel assembly energy spectrum imaging method and device - Google Patents
Fuel assembly energy spectrum imaging method and device Download PDFInfo
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Abstract
The invention discloses a fuel assembly energy spectrum imaging method and a device, which comprises the steps of pre-establishing an energy spectrum nuclide identification prior model for a fuel assembly to be imaged; acquiring spontaneous gamma radiation energy spectrums of the fuel assemblies from different axial heights and different angles of the fuel assemblies to obtain a three-dimensional detection energy spectrum matrix; identifying spontaneous gamma rays of the fuel assembly according to the energy spectrum nuclide identification prior model, and extracting three-dimensional detection intensity matrixes of all the gamma rays with effective characteristic identification functions from the three-dimensional detection energy spectrum matrix; attenuation compensation is carried out on the three-dimensional detection intensity matrix of the extracted characteristic identification gamma rays; performing two-dimensional iterative inversion on each characteristic identification gamma ray after attenuation compensation to obtain two-dimensional inversion images with different axial heights; and integrating to obtain a three-dimensional image, and integrating and outputting three-dimensional image reconstruction results of all characteristic identification gamma rays. The invention can realize the accurate positioning of the fuel pellet and the cladding, the assembly wall, the imaging monitoring of the completeness, the swelling and other conditions of the fuel rod.
Description
Technical Field
The invention belongs to the technical field of radiation detection, and particularly relates to a fuel assembly energy spectrum imaging method and device.
Background
In the processes of monitoring the operating state of the nuclear fuel assembly of the reactor, retirement shearing treatment and the like, information such as integrity, swelling deformation, damage leakage and the like of fuel rods, cladding and assembly walls needs to be accurately positioned, for the cladding of the fuel rods of the reactor, the precision of the cladding is even required to be below a mm level, and accurate image inversion of relevant parts is particularly important.
In recent years, three-dimensional image reconstruction using gamma rays has been widely used in various fields such as nuclear medicine inspection, nuclear industry inspection, and the like. In terms of imaging, two types of algorithms are formed: the method comprises the steps of firstly, performing an analytic reconstruction algorithm based on the central slice theorem, wherein the analytic reconstruction algorithm is represented by Filtering Back Projection (FBP), ultra-short scanning, PI line reconstruction, FDK three-dimensional image reconstruction approximation, Katsevich algorithm and the like; the second is an iterative reconstruction algorithm represented by algebraic iteration (ART), joint algebraic reconstruction (SART), and statistical iteration (such as expectation maximum EM, minimum norm, maximum a posteriori probability algorithm MAP, etc.). In any algorithm, the internal structure and density information of the object are inverted based on the total ray intensity, and certain defects are present if material identification imaging is carried out on two material areas with similar radiation source intensity. In terms of accuracy, even mm or less is required for fuel rod cladding within a reactor fuel assembly.
Disclosure of Invention
The invention aims to provide a fuel assembly energy spectrum imaging method and a fuel assembly energy spectrum imaging device which can accurately position fuel pellets, fuel rod cladding and assembly walls in a nuclear fuel assembly.
In order to solve the problem, the technical scheme adopted by the invention is as follows:
a fuel assembly spectral imaging method comprising the steps of:
step 1: the method comprises the steps that an energy spectrum nuclide identification prior model is established in advance for a fuel assembly to be imaged, and the energy spectrum nuclide identification prior model provides a set of characteristic identification gamma rays for carrying out effective nuclide identification and distinguishing on a fuel rod fuel area, a fuel rod cladding and an assembly wall in the fuel assembly to be imaged;
step 2: scanning and acquiring detection energy spectrums of gamma radiation of the fuel assembly from different axial heights and different angles of the fuel assembly to obtain a three-dimensional detection energy spectrum matrix of spontaneous gamma radiation of the fuel assembly;
and step 3: according to an energy spectrum nuclide identification prior model, performing identification analysis on all gamma rays in a three-dimensional detection energy spectrum matrix of spontaneous gamma radiation of the fuel assembly, and according to an identification result, extracting a three-dimensional detection intensity matrix of all characteristic identification gamma rays which can perform an effective characteristic identification function on a fuel rod fuel area, a fuel rod cladding and an assembly wall in the fuel assembly to be imaged from the three-dimensional detection energy spectrum matrix;
and 4, step 4: performing attenuation compensation on the three-dimensional detection intensity matrix of each feature recognition gamma ray in all the extracted feature recognition gamma rays;
and 5: performing two-dimensional iterative inversion on each characteristic identification gamma ray subjected to attenuation compensation to obtain two-dimensional iterative inversion images at different axial heights;
step 6: and integrating the two-dimensional iterative inversion images of each characteristic identification gamma ray obtained at different axial heights to obtain the three-dimensional image reconstruction of each characteristic identification gamma ray.
And 7: and 6, repeating the step 6 to obtain three-dimensional image reconstruction results of all the characteristic identification gamma rays, and outputting the three-dimensional image reconstruction results of all the characteristic identification gamma rays.
Further, the method for establishing the prior model for the energy spectrum nuclide identification in the step 1 comprises the following steps:
step 1.1: performing corresponding combustion activation calculation on different structures of the fuel assembly to be imaged according to a combustion and activation equation, extracting the activity of the radioactive nuclide of a fuel rod fuel area, a fuel rod cladding and an assembly wall at a specific moment according to the calculation result of the combustion activation, and extracting the radioactive nuclide capable of generating gamma decay;
step 1.2: extracting the intensity of all characteristic gamma rays generated by each radioactive nuclide according to each extracted radioactive nuclide generating gamma decay and the activity thereof and combining the branch ratio of each gamma ray generated by each radioactive nuclide;
step 1.3: sequencing the intensities of all the extracted characteristic gamma rays according to the energy of the characteristic gamma rays from small to large to obtain spontaneous gamma decay characteristic spectrums of the fuel rod fuel area, the fuel rod cladding and the assembly wall at a specific moment;
step 1.4: screening out a group of characteristic identification gamma rays capable of carrying out effective nuclide identification and distinguishing on the fuel rod fuel area, the fuel rod cladding and the assembly wall of the fuel assembly according to the spontaneous gamma decay characteristic spectrums of the fuel rod fuel area, the fuel rod cladding and the assembly wall at the specific moment;
step 1.5: and obtaining an energy spectrum nuclide identification prior model according to the energy parameters of a group of characteristic identification gamma rays which are screened out and can be used for carrying out effective nuclide identification and discrimination.
Further, the spontaneous gamma decay profiles are screened in step 1.4 under the conditions that the energy of each characteristic identification gamma ray is greater than 200keV and the intensity is greater than 10 keV5Second, the radioactive mother nucleus half-life of its source is greater than 0.5 hour.
Further, the method for acquiring the spontaneous gamma radiation energy spectrum of the fuel rod fuel area, the fuel rod cladding and the assembly wall in the fuel assembly in the step 2 comprises the following steps: spontaneous gamma rays of the fuel assembly pass through a collimator containing a shielding body and then enter a photon detector with energy spectrum resolving power.
Further, the attenuation compensation method in step 4 is as follows:
and (3) identifying the three-dimensional detection matrix data of the gamma ray for each feature extracted in the step (3), and compensating the attenuation of the feature ray caused by the influence of the shielding body in the detection process based on the Lambert-beer law according to the shielding body in the detection process, the model geometry of the detector and the material parameters.
Further, the two-dimensional iterative inversion method in step 5 is as follows:
step 5.1: let i, j be two dimensions of the fuel assembly on the two-dimensional plane where the axial height h is located, i represent the radial distance, j represent the angle, identify the gamma ray for the kth feature, and record the result of attenuation compensation processing of the two-dimensional detection photon intensity of different angles under the axial height h as Pj,h,kBy presetting an initial distribution of gamma radiation intensity in the area to be imaged in a fuel assembly
Iterative inversion calculations were performed as follows:
wherein q is the number of iterations,
fij,h,krepresenting the photon intensity of the k type characteristic identification gamma ray under the radial distance i, the angle j and the axial height h;
Step 5.2: and 5.1, repeating the step 5.1, and performing the iterative inversion process on the kth characteristic identification gamma ray under different angles j until the difference of photon intensity distribution of the two times of iterative reconstruction images meets the preset precision requirement, thereby obtaining the two-dimensional imaging of the kth characteristic identification gamma ray under the axial height h.
Further, the accuracy requirement in step 5.2 is that the difference between the photon intensity distributions of the two iteratively reconstructed images is less than or equal to 0.1% of Pj,h,k/NjThe value of (c).
Further, in the step 6 of reconstructing the three-dimensional image, the gamma ray is identified for the k-th feature, if the scanning step length of the axial height of the fuel assembly in the three-dimensional detection energy spectrum matrix which scans and collects the spontaneous gamma radiation of the fuel assembly from different axial heights and different angles in the step 2 does not meet the preset imaging precision requirement, the scanning step length can be reduced or the axial height distribution in h is integrated according to the following formula when the two-dimensional iterative inversion image of each feature identification gamma ray obtained based on different axial heights is integrated1To h2The three-dimensional image between the two is subjected to interpolation processing,
wherein the content of the first and second substances,
respectively axial height h1、h2Two-dimensional iterative inversion of the k-th characteristic gamma ray of (1), fij,h,kIs axially between h1、h2A two-dimensional image with an axial height h in between.
Further, the invention also provides a fuel assembly energy spectrum imaging device, which comprises the following modules:
energy spectrum nuclide identification prior module: the system comprises a fuel assembly to be imaged, a nuclear species identification prior model, a characteristic identification gamma ray, a nuclear species identification prior model and a nuclear species identification prior model, wherein the fuel assembly to be imaged is pre-established with the nuclear species identification prior model, and the nuclear species identification prior model provides a group of characteristic identification gamma rays for carrying out effective nuclear species identification and distinguishing on a fuel rod fuel area, a fuel rod cladding and an assembly wall of the fuel assembly to be imaged;
the energy spectrum detection module: the system comprises a three-dimensional detection energy spectrum matrix, a data acquisition module and a data processing module, wherein the three-dimensional detection energy spectrum matrix is used for scanning and acquiring spontaneous gamma radiation energy spectrums of a fuel assembly from different axial heights and different angles of the fuel assembly to obtain a three-dimensional detection energy spectrum matrix of spontaneous gamma radiation of the fuel assembly;
the characteristic identification gamma ray extraction module: the system comprises a three-dimensional detection energy spectrum matrix, a prior model for identifying energy spectrum nuclides, a three-dimensional detection intensity matrix and a control module, wherein the three-dimensional detection energy spectrum matrix is used for identifying and analyzing all gamma rays in the three-dimensional detection energy spectrum matrix of spontaneous gamma radiation of the fuel assembly, and extracting all characteristic identification gamma rays with effective characteristic identification functions on a fuel rod fuel area, a fuel rod cladding and an assembly wall in the fuel assembly to be imaged according to an identification result;
an attenuation compensation module: attenuation compensation is carried out on the three-dimensional detection intensity matrix of each characteristic identification gamma ray in all the extracted characteristic identification gamma rays;
a two-dimensional iterative inversion module: the system is used for performing two-dimensional iterative inversion on each characteristic identification gamma ray subjected to attenuation compensation to obtain two-dimensional iterative inversion images with different axial heights;
a three-dimensional image reconstruction module: the method is used for integrating two-dimensional iterative inversion images of each characteristic identification gamma ray obtained based on different axial heights, and realizing three-dimensional image reconstruction of each characteristic identification gamma ray.
An image reconstruction output visualization module: the method is used for integrating and visually outputting the three-dimensional image reconstruction results of all the characteristic recognition gamma rays.
Further, the construction method of the energy spectrum nuclide identification prior module is as follows:
step 1.1: performing corresponding combustion activation calculation on different structures of the fuel assembly to be imaged according to a combustion and activation equation, extracting the activity of the radioactive nuclide of a fuel rod fuel area, a fuel rod cladding and an assembly wall at a specific moment according to the calculation result of the combustion activation, and extracting the radioactive nuclide capable of generating gamma decay;
step 1.2: extracting the intensity of all characteristic gamma rays generated by each radioactive nuclide according to each extracted radioactive nuclide generating gamma decay and the activity thereof and combining the branch ratio of each gamma ray generated by each radioactive nuclide;
step 1.3: sequencing the intensities of all the extracted characteristic gamma rays according to the energy of the characteristic gamma rays from small to large to obtain spontaneous gamma decay characteristic spectrums of the fuel rod fuel area, the fuel rod cladding and the assembly wall at a specific moment;
step 1.4: screening out a group of characteristic identification gamma rays capable of carrying out effective nuclide identification and distinguishing on the fuel rod fuel area, the fuel rod cladding and the assembly wall of the fuel assembly according to the spontaneous gamma decay characteristic spectrums of the fuel rod fuel area, the fuel rod cladding and the assembly wall at the specific moment;
step 1.5: and obtaining an energy spectrum nuclide identification prior model according to the energy parameters of a group of characteristic identification gamma rays which are screened out and can be used for carrying out effective nuclide identification and discrimination.
Compared with the prior art, the invention has the following beneficial effects:
the invention relates to a fuel assembly energy spectrum imaging method, which screens out a group of characteristic identification gamma rays capable of carrying out effective nuclide identification and distinguishing on a fuel rod fuel area, a fuel rod cladding and an assembly wall of a fuel assembly by analyzing spontaneous gamma decay characteristic spectrums of the fuel rod fuel area, the fuel rod cladding and the assembly wall of the fuel assembly to be imaged at a specific moment in advance; and then establishing an energy spectrum nuclide identification prior model according to a group of energy parameters of the characteristic identification gamma rays which are screened out and can be used for carrying out effective nuclide identification and differentiation. And then acquiring a three-dimensional detection energy spectrum matrix of spontaneous gamma radiation of the fuel assembly, identifying and analyzing all gamma rays in the three-dimensional detection energy spectrum matrix of the spontaneous gamma radiation of the fuel assembly according to an energy spectrum nuclide identification prior model, and finally identifying the gamma rays according to the identified characteristics to perform two-dimensional iterative image inversion and three-dimensional image reconstruction so as to obtain accurate positioning imaging of different components in the fuel assembly. The invention can realize the accurate positioning of the fuel pellet, the fuel rod cladding and the assembly wall in the fuel assembly, and the imaging monitoring of the integrity, swelling and other conditions of the fuel rod in the process of monitoring the operating state of the nuclear fuel assembly of the reactor, retired shearing treatment and the like.
Drawings
FIG. 1 is a schematic flow chart of a spectral imaging method according to the present invention;
FIG. 2 shows a specific embodiment using UO2As nuclear fuel loading, the spontaneous gamma radiation characteristic spectrum of a single fuel rod when the 5MW liquid lead bismuth cooling reactor is cooled for 1 month after being irradiated by LSMR; (a) is fuel rod fuel area, (b) is fuel rod cladding material;
FIG. 3 is a set of characteristic gamma rays that are effectively identifiable by a fuel rod cladding, a fuel rod fuel region of a 5MW LSMR fuel rod in an exemplary embodiment;
FIG. 4 is a spontaneous gamma radiation profile of a single fuel rod when loaded with Minor Actinides (MA) and Pu as nuclear fuel and cooled for 1 month after irradiation of a 1000MW liquid lead bismuth cooling accelerator driven subcritical reactor ADS-NWT, (a) being a fuel rod fuel region and (b) being a fuel rod cladding material in a specific example;
FIG. 5 is a set of characteristic gamma rays that may be effectively identified by the fuel rod cladding, the fuel rod fuel region of a 1000MWADS-NWT fuel rod in an embodiment;
FIG. 6 is a schematic diagram of the present invention for performing three-dimensional probing of fuel assemblies from different axial heights and different angles.
Detailed Description
Fig. 1 to 6 show an embodiment of the fuel assembly spectral imaging method of the present invention, as shown in fig. 1, comprising the following steps:
step 1: the method comprises the steps that an energy spectrum nuclide identification prior model is established in advance for a fuel assembly to be imaged, and the energy spectrum nuclide identification prior model provides a set of characteristic identification gamma rays for effective nuclide identification and distinguishing of a fuel rod fuel area, a fuel rod cladding and an assembly wall of the fuel assembly to be imaged;
each set of characteristic gamma rays includes spontaneous gamma rays of the fuel rod fuel region, fuel rod cladding and assembly walls in the fuel assembly. The invention idea of this embodiment is based on the characteristic gamma ray of radionuclide and can be used for nuclide identification and content identification, also called as "gene characteristic" or "nuclear fingerprint" of nuclear material, the radiation intensity of its spontaneous gamma ray is related to the number of atomic nuclei contained in the material, and the radioactive characteristic gamma ray is used for nuclide identification and analysis of the characteristic information of the material to be detected, and has been widely applied in the fields of nuclear material supervision, dangerous explosive identification and the like. For the fuel assembly, it is important that, because one fuel assembly includes different parts such as fuel rod fuel pellets, fuel rod cladding, and assembly wall, the spontaneous gamma radiation detection spectrum of the fuel assembly includes the spontaneous gamma rays of each part of material.
The method for establishing the prior model for the energy spectrum nuclide identification in the embodiment comprises the following steps:
step 1.1: performing corresponding combustion activation calculation on different structures of the fuel assembly to be imaged according to a combustion and activation equation, extracting the activity of the radioactive nuclide of a fuel rod fuel area, a fuel rod cladding and an assembly wall at a specific moment according to the calculation result of the combustion activation, and extracting the radioactive nuclide capable of generating gamma decay;
step 1.2: extracting the intensity of all characteristic gamma rays generated by each radioactive nuclide according to each extracted radioactive nuclide generating gamma decay and the activity thereof and combining the branch ratio of each gamma ray generated by each radioactive nuclide;
step 1.3: sequencing the intensities of all the extracted characteristic gamma rays according to the energy of the characteristic gamma rays from small to large to obtain spontaneous gamma decay characteristic spectrums of the fuel rod fuel area, the fuel rod cladding and the assembly wall at a specific moment;
step 1.4: screening out a group of characteristic identification gamma rays capable of carrying out effective nuclide identification and distinguishing on the fuel rod fuel area, the fuel rod cladding and the assembly wall of the fuel assembly according to the spontaneous gamma decay characteristic spectrums of the fuel rod fuel area, the fuel rod cladding and the assembly wall at the specific moment;
step 1.5: and obtaining an energy spectrum nuclide identification prior model according to the energy parameters of a group of characteristic identification gamma rays which are screened out and can be used for carrying out effective nuclide identification and discrimination.
The method comprises the steps of extracting radionuclides capable of generating gamma decay in a fuel rod fuel area, a fuel rod cladding and an assembly wall at a specific moment by pre-establishing a prior model for energy spectrum nuclide identification of a fuel assembly to be imaged and according to the combustion activation calculation of the fuel assembly to be imaged; then, based on the intensities of all the characteristic gamma rays generated by the radionuclides, a group of characteristic identification gamma rays capable of carrying out effective nuclide identification distinction on the fuel region of the fuel rod, the cladding of the fuel rod and the wall of the fuel assembly is screened. In this embodiment, the screening conditions are that the energy of each feature recognition gamma ray is greater than 200keV, and the intensity is greater than 105The radioactive mother nucleus half-life period of the source is more than 0.5 hour per second, and each gamma ray energy value extracted from the fuel rod fuel area, the fuel rod cladding and the assembly wall has resolvability. Specifically, as shown in tables 1 and 2:
table 1 each feature recognition gamma ray satisfies the conditions of energy and intensity
| Screening amount | Threshold value | Remarks for note |
| (Energy) | >200keV， | As large as possible |
| Strength of | >105Second/second | As large as possible |
Table 2 each feature recognition gamma ray branching ratio and half-life of corresponding radioactive mother nucleus satisfy conditions
| Screening amount | Threshold value | Remarks for note |
| Each feature identifies the branch ratio of the gamma ray | - | As large as possible |
| Corresponding to half life of radioactive mother nucleus | >0.5 hour | As large as possible |
In this embodiment, when screening each γ ray identified by an effective nuclide in a fuel rod fuel region of a fuel assembly, a fuel rod cladding, and an assembly wall, in order to make each energy value distinguishable, a plurality of characteristic γ rays with too close energy should be reduced as much as possible, and a γ ray energy parameter is identified by a set of finally determined characteristics, so as to establish an energy spectrum nuclide identification prior model.
FIG. 2 shows a diagram for a general UO2A spontaneous gamma radiation characteristic spectrum of a single fuel rod is obtained when a 5MW LSMR (laser induced magnetic resonance) small stack which is loaded as nuclear fuel and takes liquid lead bismuth as a coolant is irradiated and then cooled for 1 month; FIG. 2(a) is a fuel rod fuel region and FIG. 2(b) is a fuel rod cladding material; a set of characteristic gamma rays which are effective for identifying the fuel rod fuel region and the fuel rod cladding are shown in FIG. 3, wherein the characteristic gamma rays are respectively from the fuel rod fuel region237U、239Np and cladding of fuel rods54Mn、60Co and other nuclides, and selecting characteristic identification gamma rays as shown in a table 3:
TABLE 3 UO2Spectral imaging characteristic gamma ray selection of nuclear fuel loading and liquid lead bismuth cooling 5MW LSMR
FIG. 4 shows the spontaneous gamma radiation profile of a single fuel rod when cooled for 1 month after irradiation of a 1000MW liquid lead bismuth cooling accelerator driven subcritical reactor ADS-NWT stack with Minor Actinides (MA) and Pu as nuclear fuel, FIG. 4(a) is the fuel rod fuel region, and FIG. 4(b) is the fuel rod cladding material; a set of characteristic gamma rays which are effective for identifying the fuel rod fuel region and the fuel rod cladding are shown in FIG. 5, wherein the characteristic gamma rays are respectively from the fuel rod fuel region239Np、238Np、233Pa and cladding of fuel rods54Mn、59Fe、182Ta and other nuclides, and selecting the characteristic identification gamma rays as shown in the table 4:
TABLE 4 selection of gamma rays characteristic of spectral imaging of MA and Pu nuclear fuel loading, liquid lead bismuth cooling 1000MWADS-NWT stacks
Step 2: scanning and acquiring detection energy spectrums of gamma radiation of the fuel assembly from different axial heights and different angles of the fuel assembly to obtain a three-dimensional detection energy spectrum matrix of spontaneous gamma radiation of the fuel assembly; as shown in fig. 6, the acquisition method is: the spontaneous gamma-ray of the fuel assembly enters a photon detector with energy spectrum resolving power after passing through a collimator containing a shielding body, the collimator is used for shielding gamma-rays in other directions, the shielding body for protecting the detector under the high-radiation dose environment is arranged in front of the detector, and the spontaneous gamma-radiation energy spectrum of the fuel assembly is acquired through the detector.
And step 3: according to an energy spectrum nuclide identification prior model, performing identification analysis on all gamma rays in a three-dimensional detection energy spectrum matrix of spontaneous gamma radiation of the fuel assembly, and according to an identification result, extracting a three-dimensional detection intensity matrix of all characteristic identification gamma rays capable of performing an effective characteristic identification function on a fuel rod fuel area, a fuel rod cladding and an assembly wall in the fuel assembly to be imaged from the three-dimensional detection energy spectrum matrix;
and 4, step 4: attenuation compensation is carried out on the three-dimensional detection intensity matrix of each characteristic gamma ray in all the extracted characteristic identification gamma rays;
and (3) identifying the three-dimensional detection intensity matrix data of the gamma ray according to each feature extracted in the step (3), and compensating the attenuation of the feature ray caused by the influence of the shielding body in the detection process based on the Lambert-beer law by combining the shielding body in the detection process, the model geometry of the detector and the material parameters.
Lambert-beer law: i ═ I0e-μTWhere T is the shield thickness experienced by each characteristic ray reaching the detector in the detection direction, I0And I is the gamma ray photon intensity before and after entering the shielding body, and mu is the attenuation factor related to the shielding body material. And performing attenuation compensation on each ray before image inversion, and compensating characteristic ray attenuation caused by influence of a shielding body in the detection process.
And 5: performing two-dimensional iterative inversion on each characteristic identification gamma ray subjected to attenuation compensation to obtain two-dimensional iterative inversion images with different axial heights;
step 5.1:let i, j be two dimensions of the fuel assembly on the two-dimensional plane where the axial height h is located, i represent the radial distance, j represent the angle, identify the gamma ray for the kth feature, and record the result of attenuation compensation processing of the two-dimensional detection photon intensity of different angles under the axial height h as Pj,h,kBy presetting an initial distribution of gamma radiation intensity in the area to be imaged in a fuel assembly
Iterative inversion calculations were performed as follows:
wherein q is the number of iterations,
fij,h,krepresenting the photon intensity of the k type characteristic identification gamma ray under the radial distance i, the angle j and the axial height h;
Step 5.2: repeating the step 5.1, and identifying gamma rays through the kth features under different angles j through the iterative inversion process until the difference of photon intensity distribution of the two times of iterative reconstruction images meets the preset precision requirement, or judging iterative convergence according to the following formula:
wherein epsilon is a preset precision requirement.
The precision in this embodiment isCalculating P of the difference of photon intensity distribution of two times of iteration reconstruction image less than or equal to 0.1%j,h,k/NjA value of or epsilon less than or equal to 0.1% of Pj,h,kThe value is obtained.
This results in a two-dimensional image of the k-th feature recognition gamma ray at axial height h.
Step 6: and integrating the two-dimensional iterative inversion images of each characteristic identification gamma ray obtained at different axial heights to obtain the three-dimensional image reconstruction of each characteristic identification gamma ray. And for the k-th characteristic gamma ray, obtaining two-dimensional imaging matrixes at different axial heights h through the step 5.
When scanning a fuel assembly to be imaged, identifying gamma rays for the kth characteristic, if the three-dimensional detection energy spectrum matrix of spontaneous gamma radiation of the fuel assembly is scanned and collected from different axial heights and different angles of the fuel assembly in step 2, and if the scanning step length of the axial height does not meet the preset imaging precision requirement, reducing the scanning step length or integrating two-dimensional iterative inversion images of each characteristic identification gamma ray obtained based on different axial heights and distributing the axial heights in h according to the following formula1To h2The three-dimensional image between the two is subjected to interpolation processing,
wherein f isij,h1,k，fij,h2,kRespectively, axial height is respectively h1、h2Two-dimensional iterative inversion of the k-th characteristic gamma ray of (1), fij,h,kIs axially between h1、h2A two-dimensional image with an axial height h in between. The minimum precision of the current CT scan can be controlled to be 0.5mm, and when the scanning step length of the axial height is larger than the minimum precision of the current CT scan by 0.5mm, the step length of the axial scan can be reduced or the interpolation processing can be carried out according to the formula. When the axial scanning step length is equal to the minimum precision of 0.5mm of the current CT scanning, if the precision is higher for three-dimensional imaging, the interpolation processing can also be carried out according to the above formula.
And adjusting the step length of scanning acquisition on the axial height according to a preset precision requirement, or setting the step length to be 0.5mm as the minimum precision of the current CT scanning, performing interpolation processing according to the formula, and integrating two-dimensional plane images of all the axial heights to obtain three-dimensional image reconstruction of each feature recognition gamma ray.
And 7: and 6, repeating the step 6 to obtain three-dimensional image reconstruction results of all the characteristic identification gamma rays, and outputting the three-dimensional image reconstruction results of all the characteristic identification gamma rays.
And (4) identifying gamma rays for each characteristic which can be respectively identified by the fuel rod fuel area, the fuel rod cladding and the assembly wall in the fuel assembly, repeating the process of the step (7), completing the reconstruction of three-dimensional images of all the characteristic identification gamma rays, and performing visual output.
The invention relates to a fuel assembly energy spectrum imaging method, which screens out a group of characteristic identification gamma rays capable of carrying out effective nuclide identification and distinguishing on a fuel rod fuel area, a fuel rod cladding and an assembly wall of a fuel assembly by analyzing spontaneous gamma decay characteristic spectrums of the fuel rod fuel area, the fuel rod cladding and the assembly wall of the fuel assembly to be imaged at a specific moment in advance; and then establishing an energy spectrum nuclide identification prior model according to a group of energy parameters of the characteristic identification gamma rays which are screened out and can be used for carrying out effective nuclide identification and differentiation. And then acquiring a three-dimensional detection energy spectrum matrix of spontaneous gamma radiation of the fuel assembly, identifying and analyzing all gamma rays in the three-dimensional detection energy spectrum matrix of the spontaneous gamma radiation of the fuel assembly according to an energy spectrum nuclide identification prior model, and finally identifying the gamma rays according to the identified characteristics to perform two-dimensional iterative image inversion and three-dimensional image reconstruction so as to obtain accurate positioning imaging of different components in the fuel assembly. The invention can realize the accurate positioning of the fuel pellet, the fuel rod cladding and the assembly wall in the fuel assembly, and the imaging monitoring of the integrity, swelling and other conditions of the fuel rod in the process of monitoring the operating state of the nuclear fuel assembly of the reactor, retired shearing treatment and the like.
The invention also provides a fuel assembly energy spectrum imaging device, which comprises the following modules:
energy spectrum nuclide identification prior module: the system comprises a fuel assembly to be imaged, a nuclear species identification prior model, a characteristic identification gamma ray, a nuclear species identification prior model and a nuclear species identification prior model, wherein the fuel assembly to be imaged is pre-established with the nuclear species identification prior model, and the nuclear species identification prior model provides a group of characteristic identification gamma rays for carrying out effective nuclear species identification and distinguishing on a fuel rod fuel area, a fuel rod cladding and an assembly wall of the fuel assembly to be imaged;
the energy spectrum detection module: the system comprises a three-dimensional detection energy spectrum matrix, a data acquisition module and a data processing module, wherein the three-dimensional detection energy spectrum matrix is used for scanning and acquiring spontaneous gamma radiation energy spectrums of a fuel assembly from different axial heights and different angles of the fuel assembly to obtain a three-dimensional detection energy spectrum matrix of spontaneous gamma radiation of the fuel assembly;
the characteristic identification gamma ray extraction module: the system comprises a three-dimensional detection energy spectrum matrix, a prior model for identifying energy spectrum nuclides, a three-dimensional detection intensity matrix and a control module, wherein the three-dimensional detection energy spectrum matrix is used for identifying and analyzing all gamma rays in the three-dimensional detection energy spectrum matrix of spontaneous gamma radiation of the fuel assembly, and extracting all characteristic identification gamma rays with effective characteristic identification functions on a fuel rod fuel area, a fuel rod cladding and an assembly wall in the fuel assembly to be imaged according to an identification result;
an attenuation compensation module: the three-dimensional detection intensity matrix is used for performing attenuation compensation on the three-dimensional detection intensity matrix of each characteristic gamma ray in all the extracted characteristic identification gamma rays;
a two-dimensional iterative inversion module: the system is used for performing two-dimensional iterative inversion on each characteristic identification gamma ray subjected to attenuation compensation to obtain two-dimensional iterative inversion images with different axial heights;
a three-dimensional image reconstruction module: the method is used for integrating two-dimensional iterative inversion images of each characteristic identification gamma ray obtained based on different axial heights, and realizing three-dimensional image reconstruction of each characteristic identification gamma ray.
An image reconstruction output visualization module: the method is used for integrating and visually outputting the three-dimensional image reconstruction results of all the characteristic recognition gamma rays.
In this embodiment, the method for constructing the prior module for identifying the energy spectrum nuclide includes:
step 1.1: performing corresponding combustion activation calculation on different structures of the fuel assembly to be imaged according to a combustion and activation equation, extracting the activity of the radioactive nuclide of a fuel rod fuel area, a fuel rod cladding and an assembly wall at a specific moment according to the calculation result of the combustion activation, and extracting the radioactive nuclide capable of generating gamma decay;
step 1.2: extracting the intensity of all characteristic gamma rays generated by each radioactive nuclide according to each extracted radioactive nuclide generating gamma decay and the activity thereof and combining the branch ratio of each gamma ray generated by each radioactive nuclide;
step 1.3: sequencing the intensities of all the extracted characteristic gamma rays according to the energy of the characteristic gamma rays from small to large to obtain spontaneous gamma decay characteristic spectrums of the fuel rod fuel area, the fuel rod cladding and the assembly wall at a specific moment;
step 1.4: screening out a group of characteristic identification gamma rays capable of carrying out effective nuclide identification and distinguishing on the fuel rod fuel area, the fuel rod cladding and the assembly wall of the fuel assembly according to the spontaneous gamma decay characteristic spectrums of the fuel rod fuel area, the fuel rod cladding and the assembly wall at the specific moment;
step 1.5: and establishing an energy spectrum nuclide identification prior model according to the energy parameters of a group of characteristic identification gamma rays which are screened out and can be used for carrying out effective nuclide identification and discrimination.
The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above-mentioned embodiments, and all technical solutions belonging to the idea of the present invention belong to the protection scope of the present invention. It should be noted that modifications and embellishments within the scope of the invention may be made by those skilled in the art without departing from the principle of the invention.
Claims (8)
1. A fuel assembly spectral imaging method, comprising the steps of:
step 1: the method comprises the steps that an energy spectrum nuclide identification prior model is established in advance for a fuel assembly to be imaged, and the energy spectrum nuclide identification prior model provides a set of characteristic identification gamma rays for carrying out effective nuclide identification and distinguishing on a fuel rod fuel area, a fuel rod cladding and an assembly wall in the fuel assembly to be imaged;
step 2: scanning and acquiring spontaneous gamma radiation energy spectrums of the fuel assembly from different axial heights and different angles of the fuel assembly to obtain a three-dimensional detection energy spectrum matrix of spontaneous gamma radiation of the fuel assembly;
and step 3: according to an energy spectrum nuclide identification prior model, performing identification analysis on all gamma rays in a three-dimensional detection energy spectrum matrix of spontaneous gamma radiation of the fuel assembly, and according to an identification result, extracting a three-dimensional detection intensity matrix of all characteristic identification gamma rays capable of performing an effective characteristic identification function on a fuel rod fuel area, a fuel rod cladding and an assembly wall in the fuel assembly to be imaged from the three-dimensional detection energy spectrum matrix;
and 4, step 4: performing attenuation compensation on the three-dimensional detection intensity matrix of each feature recognition gamma ray in all the extracted feature recognition gamma rays;
and 5: performing two-dimensional iterative inversion on each characteristic identification gamma ray subjected to attenuation compensation to obtain two-dimensional iterative inversion images at different axial heights;
step 6: integrating two-dimensional iterative inversion images of each characteristic identification gamma ray obtained at different axial heights to obtain three-dimensional image reconstruction of each characteristic identification gamma ray;
and 7: repeating the step 6 to obtain three-dimensional image reconstruction results of all the characteristic identification gamma rays, and outputting the three-dimensional image reconstruction results of all the characteristic identification gamma rays;
the step 1 comprises the following steps:
step 1.1: performing corresponding combustion activation calculation on different structures of the fuel assembly to be imaged according to a combustion and activation equation, extracting the activity of the radioactive nuclide of a fuel rod fuel area, a fuel rod cladding and an assembly wall at a specific moment according to the calculation result of the combustion activation, and extracting the radioactive nuclide capable of generating gamma decay;
step 1.2: extracting the intensity of all characteristic gamma rays generated by each radioactive nuclide according to each extracted radioactive nuclide generating gamma decay and the activity thereof and combining the branch ratio of each gamma ray generated by each radioactive nuclide;
step 1.3: sequencing the intensities of all the extracted characteristic gamma rays according to the energy of the characteristic gamma rays from small to large to obtain spontaneous gamma decay characteristic spectrums of the fuel rod fuel area, the fuel rod cladding and the assembly wall at a specific moment;
step 1.4: screening out a group of characteristic identification gamma rays capable of carrying out effective nuclide identification and distinguishing on the fuel rod fuel area, the fuel rod cladding and the assembly wall of the fuel assembly according to the spontaneous gamma decay characteristic spectrums of the fuel rod fuel area, the fuel rod cladding and the assembly wall at the specific moment;
step 1.5: and obtaining an energy spectrum nuclide identification prior model according to the energy parameters of a group of characteristic identification gamma rays which are screened out and can be used for carrying out effective nuclide identification and discrimination.
2. The method of claim 1, wherein the spontaneous gamma decay profiles are screened in step 1.4 under conditions such that each signature-identifying gamma ray has an energy of greater than 200keV and an intensity of greater than 10 keV5Second, the radioactive mother nucleus half-life of its source is greater than 0.5 hour.
3. The method of claim 1, wherein the step 2 of acquiring spontaneous gamma radiation spectra of fuel rod fuel region, fuel rod cladding and assembly wall in the fuel assembly is by: spontaneous gamma rays of the fuel assembly pass through a collimator containing a shielding body and then enter a photon detector with energy spectrum resolving power.
4. The fuel assembly spectral imaging method of claim 1, wherein the attenuation compensation method in step 4 is:
and (3) identifying the three-dimensional detection matrix data of the gamma ray for each feature extracted in the step (3), and compensating the attenuation of the feature ray caused by the influence of the shielding body in the detection process based on the Lambert-beer law according to the shielding body in the detection process, the model geometry of the detector and the material parameters.
5. The method of claim 1, wherein the two-dimensional iterative inversion in step 5 is performed by:
step 5.1: let i, j be the axial height of the fuel assemblyh represents two dimensions on a two-dimensional plane, i represents a radial distance, j represents an angle, gamma rays are identified for the kth feature, and the result of attenuation compensation processing on the two-dimensional detection photon intensity of different angles under the axial height h is recorded as Pj,h,kBy presetting an initial distribution of gamma radiation intensity in the area to be imaged in a fuel assembly
Iterative inversion calculations were performed as follows:
wherein q is the number of iterations,
fij,h,krepresenting the photon intensity of the k type characteristic identification gamma ray under the radial distance i, the angle j and the axial height h;
step 5.2: and 5.1, repeating the step 5.1, and performing the iterative inversion process on the kth characteristic identification gamma ray under different angles j until the difference of photon intensity distribution of the two times of iterative reconstruction images meets the preset precision requirement, thereby obtaining the two-dimensional imaging of the kth characteristic identification gamma ray under the axial height h.
6. The method of claim 5, wherein the accuracy requirement is P for a difference between photon intensity distributions of two iteratively reconstructed images of less than or equal to 0.1%j,h,k/NjThe value of (c).
7. According to claim 5The method is characterized in that gamma rays are identified for the k-th feature in the process of reconstructing the three-dimensional image in the step 6, if the scanning step length of the axial height in the three-dimensional detection energy spectrum matrix which scans and collects the spontaneous gamma radiation of the fuel assembly from different axial heights and different angles in the step 2 does not meet the preset imaging precision requirement, the scanning step length is reduced or the axial height distribution h is integrated according to the following formula when the two-dimensional iterative inversion image of each feature identification gamma ray obtained based on different axial heights is integrated1To h2The three-dimensional image between the two is subjected to interpolation processing,
wherein the content of the first and second substances,
respectively, axial height is respectively h1、h2Two-dimensional iterative inversion of the k-th characteristic gamma ray of (1), fij,h,kIs axially between h1、h2A two-dimensional image with an axial height h in between.
8. A fuel assembly spectral imaging apparatus, characterized by: the system comprises the following modules:
energy spectrum nuclide identification prior module: the system comprises a fuel assembly to be imaged, a nuclear species identification prior model, a characteristic identification gamma ray, a nuclear species identification prior model and a nuclear species identification prior model, wherein the fuel assembly to be imaged is pre-established with the nuclear species identification prior model, and the nuclear species identification prior model provides a group of characteristic identification gamma rays for carrying out effective nuclear species identification and distinguishing on a fuel rod fuel area, a fuel rod cladding and an assembly wall of the fuel assembly to be imaged;
the energy spectrum detection module: the system comprises a three-dimensional detection energy spectrum matrix, a data acquisition module and a data processing module, wherein the three-dimensional detection energy spectrum matrix is used for scanning and acquiring spontaneous gamma radiation energy spectrums of a fuel assembly from different axial heights and different angles of the fuel assembly to obtain a three-dimensional detection energy spectrum matrix of spontaneous gamma radiation of the fuel assembly;
the characteristic identification gamma ray extraction module: the system comprises a three-dimensional detection energy spectrum matrix, a prior model for identifying energy spectrum nuclides, a three-dimensional detection intensity matrix and a control module, wherein the three-dimensional detection energy spectrum matrix is used for identifying and analyzing all gamma rays in the three-dimensional detection energy spectrum matrix of spontaneous gamma radiation of the fuel assembly, and extracting all characteristic identification gamma rays with effective characteristic identification functions on a fuel rod fuel area, a fuel rod cladding and an assembly wall in the fuel assembly to be imaged according to an identification result;
an attenuation compensation module: the three-dimensional detection intensity matrix is used for performing attenuation compensation on the three-dimensional detection intensity matrix of each characteristic gamma ray in all the extracted characteristic identification gamma rays;
a two-dimensional iterative inversion module: the system is used for performing two-dimensional iterative inversion on each characteristic identification gamma ray subjected to attenuation compensation to obtain two-dimensional iterative inversion images with different axial heights;
a three-dimensional image reconstruction module: the system is used for integrating two-dimensional iterative inversion images of each characteristic identification gamma ray obtained based on different axial heights to realize three-dimensional image reconstruction of each characteristic identification gamma ray;
an image reconstruction output visualization module: the three-dimensional image reconstruction result is used for integrating all the characteristic recognition gamma rays and visually outputting the three-dimensional image reconstruction result;
the construction method of the energy spectrum nuclide identification prior module comprises the following steps:
step 1.1: performing corresponding combustion activation calculation on different structures of the fuel assembly to be imaged according to a combustion and activation equation, extracting the activity of the radioactive nuclide of a fuel rod fuel area, a fuel rod cladding and an assembly wall at a specific moment according to the calculation result of the combustion activation, and extracting the radioactive nuclide capable of generating gamma decay;
step 1.2: extracting the intensity of all characteristic gamma rays generated by each radioactive nuclide according to each extracted radioactive nuclide generating gamma decay and the activity thereof and combining the branch ratio of each gamma ray generated by each radioactive nuclide;
step 1.3: sequencing the intensities of all the extracted characteristic gamma rays according to the energy of the characteristic gamma rays from small to large to obtain spontaneous gamma decay characteristic spectrums of the fuel rod fuel area, the fuel rod cladding and the assembly wall at a specific moment;
step 1.4: screening out a group of characteristic identification gamma rays capable of carrying out effective nuclide identification and distinguishing on the fuel rod fuel area, the fuel rod cladding and the assembly wall of the fuel assembly according to the spontaneous gamma decay characteristic spectrums of the fuel rod fuel area, the fuel rod cladding and the assembly wall at the specific moment;
step 1.5: and obtaining an energy spectrum nuclide identification prior model according to the energy parameters of a group of characteristic identification gamma rays which are screened out and can be used for carrying out effective nuclide identification and discrimination.
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