Stable spectrum method and electronic device for nuclear energy spectrum

Abstract

The application provides a nuclear energy spectrum stabilization method and an electronic device. The nuclear energy spectrum stabilization method comprises the following steps: determining channel address characteristic values corresponding to channel addresses in an energy spectrum diagram; determining a target reference source characteristic peak according to the channel address characteristic values; determining a reference position with the maximum slope in a falling edge region on the right side of the target reference source characteristic peak; determining a center position of the target reference source characteristic peak according to a predetermined proportion coefficient and the reference position; the predetermined proportion coefficient is the ratio of a reference distance to a half-height width; the reference distance is the distance between the center position of the reference source characteristic peak and the reference position; and the energy spectrum diagram is corrected based on the center position of the target reference source characteristic peak to obtain a stabilized energy spectrum. The technical scheme of the application can accurately determine the center position of the target reference source characteristic peak, avoid the influence of statistical fluctuations and the interference of characteristic peaks of other radioactive nuclides, and ensure the stability of the stabilized spectrum result.

Description

Technical Field

[0001] This application relates to the field of nuclear radiation monitoring technology, and in particular to a method for stabilizing the nuclear energy spectrum and an electronic device. Background Technology

[0002] In related technologies, the process of stabilizing the nuclear energy spectrum first requires identifying the characteristic peak of potassium-40 (K-40) in the natural background. Then, the peak position of this characteristic peak is adjusted to the desired channel address, and a pre-calibrated energy curve is used to map the energy of other channels. A key reason why traditional stabilization methods use the characteristic peak of K-40 as a reference peak is that the energy of K-40's characteristic peak is higher than that of most artificial radionuclides. However, due to limitations in detector resolution, the characteristic peak energies of some nuclides are close to the K-40 characteristic peak energy. The broadened characteristic peak will interfere with the left half of the K-40 characteristic peak, making it difficult to accurately locate the K-40 characteristic peak position using traditional stabilization methods. Summary of the Invention

[0003] This application provides a method and electronic device for stabilizing nuclear energy spectrum to solve the problems existing in related technologies. The technical solution is as follows:

[0004] In a first aspect, embodiments of this application provide a method for stabilizing a nuclear energy spectrum, comprising: determining the address characteristic value corresponding to each address in the energy spectrum; determining a target reference source characteristic peak based on multiple address characteristic values; determining the reference position with the largest slope in the right-side falling edge region of the target reference source characteristic peak; determining the center position of the target reference source characteristic peak based on a predetermined scaling factor and the reference position; wherein the predetermined scaling factor is the ratio of the reference distance to the full width at half maximum (FWHM); the reference distance is the distance between the center position of the reference source characteristic peak and the reference position; and correcting the energy spectrum based on the center position of the target reference source characteristic peak to obtain a stable energy spectrum.

[0005] In one implementation, determining the reference position with the largest slope in the right-side falling edge region of the target reference source characteristic peak includes: calculating the original count derivative value corresponding to each channel address in the right-side falling edge region of the target reference source characteristic peak; smoothing the original count derivative value to obtain the mean count derivative value corresponding to each channel address; and determining the position corresponding to the maximum value among the mean count derivative values ​​as the reference position with the largest slope.

[0006] In one embodiment, calculating the original count derivative value corresponding to each trace address in the falling edge region to the right of the target reference source feature peak includes: calculating a first count value located at a predetermined distance to the left of the target trace address and a second count value located at a predetermined distance to the right of the target trace address in the falling edge region to the right of the target reference source feature peak; wherein the predetermined distance is determined based on the half-width at half-maximum (WHM) of the trace address; and determining the original count derivative value corresponding to the target trace address based on the first count value and the second count value.

[0007] In one embodiment, the original count derivative value is smoothed to obtain the mean count derivative value corresponding to each road address, including: calculating the total number of road addresses within the preset road address range of the target road address and the sum of the original count derivative values; wherein, the preset road address range is the range between a predetermined distance to the left of the target road address and a predetermined distance to the right of the target road address; and determining the mean count derivative value corresponding to the target road address based on the total number of road addresses within the preset road address range and the sum of the original count derivative values.

[0008] In one embodiment, determining a target reference source feature peak based on multiple address feature values ​​includes: determining a local maximum value among the multiple address feature values; determining the feature peak corresponding to the local maximum value that is greater than a preset threshold as a pre-selected reference source feature peak; and determining the target reference source feature peak among the pre-selected reference source feature peaks.

[0009] In one embodiment, determining a target reference source characteristic peak from pre-selected reference source characteristic peaks includes: determining the count rate of the pre-selected reference source characteristic peaks; determining the pre-selected reference source characteristic peaks whose count rates are within a preset count rate range as candidate reference source characteristic peaks; and determining the candidate reference source characteristic peak closest to the reference source characteristic peak after the previous spectral stabilization adjustment as the target reference source characteristic peak.

[0010] In one implementation, determining the address feature value corresponding to each address in the energy spectrum includes: determining the count value corresponding to each address in the energy spectrum; and performing convolution calculation with the count value corresponding to each address using a symmetric window function to obtain the address feature value corresponding to each address.

[0011] Secondly, embodiments of this application provide an electronic device, including a memory, a processor, and a computer program stored in the memory, wherein the processor implements any of the methods of embodiments of this application when executing the computer program.

[0012] Thirdly, embodiments of this application provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the method of any one of the embodiments of this application.

[0013] Fourthly, embodiments of this application provide a computer program product, including a computer program, which, when executed by a processor, implements any of the methods described in the embodiments of this application.

[0014] The advantages or beneficial effects of the above technical solution include at least the following: by determining the reference position with the largest slope in the right-side falling edge region of the target reference source characteristic peak, and accurately determining the center position of the target reference source characteristic peak according to the predetermined scaling factor and the reference position, the influence of statistical fluctuations and interference from the characteristic peaks of other radionuclides are avoided, thus ensuring the stability of the stable spectrum results.

[0015] The above overview is for illustrative purposes only and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features of this application will become readily apparent from the accompanying drawings and the following detailed description. Attached Figure Description

[0016] In the accompanying drawings, unless otherwise specified, the same reference numerals throughout the various drawings denote the same or similar parts or elements. These drawings are not necessarily drawn to scale. It should be understood that these drawings depict only some embodiments disclosed in this application and should not be construed as limiting the scope of this application.

[0017] Figure 1 The figure shows an example of the application of spectral stabilization methods in related technologies;

[0018] Figure 2 A schematic diagram showing the characteristic peaks of lanthanum (La) and K-40 in related technologies is shown;

[0019] Figure 3 A schematic flowchart of a method for stabilizing the nuclear energy spectrum according to an embodiment of this application is shown.

[0020] Figure 4 A block diagram of an electronic device according to an embodiment of this application is shown. Detailed Implementation

[0021] In the following description, only certain exemplary embodiments are briefly described. As those skilled in the art will recognize, the described embodiments can be modified in various ways without departing from the spirit or scope of this application. Therefore, the drawings and description are considered to be exemplary in nature and not restrictive.

[0022] Figure 1 The diagram illustrates an application example of spectral stabilization methods in related technologies. Among them, Figure 1 (a) is the energy spectrum of Co-60. Figure 1 Image (b) shows the peak finding results. Combined with... Figure 1In the process of stabilizing the nuclear energy spectrum, the first step is to find the characteristic peak of K-40 in the natural background (such as...). Figure 1 (As indicated by the arrow in (b)). Then, the peak position of the characteristic peak is adjusted to the channel address expected by the user, and the energy of other channels is mapped using a pre-calibrated energy curve. However, due to the limitation of the detector's resolution, the characteristic peak energy of some nuclides is close to the characteristic peak energy of K-40. The broadened characteristic peak will interfere with the K-40 characteristic peak, making it difficult to accurately locate the peak position of the K-40 characteristic peak.

[0023] Taking the energy spectrum of a lanthanum bromide (Labr3) detector as an example, the Labr3 detector carries the weakly radioactive nuclide lanthanum (La). Figure 2 This diagram illustrates the La characteristic peak and the K-40 characteristic peak in related technologies. (For example...) Figure 2 As shown, the blue arrow points to the left of the characteristic peak of La, and the green arrow points to the characteristic peak of K-40. The energies of the characteristic peaks of La and K-40 are similar. Therefore, the characteristic peak of La significantly interferes with the calculation of the center address of the characteristic peak of K-40, resulting in errors in the calculated center address of the K-40 characteristic peak.

[0024] The activity composition of the radionuclide La in different Labr3 detectors varies considerably, and the activity of K-40 also differs under different measurement environments. Even under the same environment, due to the influence of statistical fluctuations, the superposition of the two characteristic peaks (i.e., the characteristic peak of La and the characteristic peak of K-40) still exhibits multiple different forms. Therefore, regardless of the calculation algorithm used (such as the maximum value method, the first derivative method, the multi-derivative method, the centroid method, the symmetric zero-area method, the Gaussian fitting method, etc.), it is impossible to accurately calculate the peak position of the K-40 characteristic peak.

[0025] For other scintillator detectors (such as sodium iodide (NaI) detectors), although they do not carry their own radioactive nuclides, the detectors have poor resolution and large half-width at half-maximum (FWHM) of their characteristic peaks. They are also subject to interference from the characteristic peaks of other external radioactive nuclides (such as the 1332 KeV characteristic peak of Co-60 and the 1408 KeV characteristic peak of Europium-152 (Eu-152)).

[0026] Figure 3 A schematic flowchart illustrating a method for stabilizing the nuclear energy spectrum according to an embodiment of this application is shown. Figure 3 As shown, the spectral stabilization method for this nuclear energy spectrum includes:

[0027] Step S301: Determine the characteristic values ​​of each channel address in the energy spectrum;

[0028] Step S302: Determine the target reference source characteristic peak based on multiple road address characteristic values.

[0029] For example, the path address characteristic value S i This can be understood as the local characteristic intensity of the energy spectrum data at address i, reflecting the signal variation characteristics of address i and its neighboring region, and can be used to identify characteristic peaks. Each address has a corresponding address characteristic value, and the target reference source characteristic peak can be determined based on the multiple address characteristic values ​​corresponding to multiple addresses.

[0030] For example, if the reference source can be the natural radionuclide K-40, then the characteristic peak of the reference source is the characteristic peak of K-40.

[0031] Step S303: Determine the reference position with the largest slope in the right-side falling edge region of the target reference source characteristic peak.

[0032] The peak of the characteristic peak corresponds to the highest signal count, making its statistical fluctuations relatively significant and its position highly susceptible to noise. In the right-side falling edge region, the signal strength is lower than at the peak, resulting in less relative noise influence. Furthermore, the location of the steepest slope is determined by the geometric changes in the signal, rather than simply the magnitude of the count, making the reference position less affected by statistical fluctuations. Therefore, compared to the peak position or the left half of the characteristic peak, the location with the steepest slope in the right-side falling edge region is more stable.

[0033] Among them, statistical fluctuations refer to signal fluctuations caused by the random emission of radioactive source particles and the uncertainty of the detector (such as counting noise).

[0034] Step S304: Determine the center position of the target reference source characteristic peak according to the predetermined scaling factor and reference position;

[0035] Step S305: Based on the center position of the characteristic peak of the target reference source, the energy spectrum is corrected to obtain a stable energy spectrum.

[0036] Wherein, the predetermined scaling factor ratio is the reference distance d. k40-edge The ratio of the full width at half maximum (FWHM) to the height of the object. Reference distance d k40-edge The center position d of the characteristic peak of the reference source k40 With reference position d edge The distance between them. Therefore, the reference distance d k40-edge This is the product of a predetermined scaling factor (ratio) and the full width at half maximum (FWHM). The FWHM is the product of the detector's resolution and the energy corresponding to the current channel address. This is calculated after determining the reference distance d. k40-edge Then, the reference position d can be calculated. edge Distance d from the reference k40-edge The difference between the peaks yields the center position d of the target reference source characteristic peak. k40 For example, the predetermined scaling factor ratio can be a calibration parameter of the detector.

[0037] According to the nuclear energy spectrum stabilization method of the embodiments of this application, the reference position with the largest slope in the right-side falling edge region of the target reference source characteristic peak is determined, and the center position of the target reference source characteristic peak is accurately determined according to a predetermined scaling factor and the reference position, so as to avoid the influence of statistical fluctuations and the interference of characteristic peaks of other radionuclides, and ensure the stability of the stabilization result.

[0038] In one embodiment, determining the reference position with the largest slope in the right-side falling edge region of the target reference source characteristic peak in step S303 may include: calculating the original count derivative value corresponding to each channel address in the right-side falling edge region of the target reference source characteristic peak; smoothing the original count derivative value to obtain the mean count derivative value corresponding to each channel address; and determining the position corresponding to the maximum value among the mean count derivative values ​​as the reference position with the largest slope.

[0039] It should be noted that the aforementioned "count derivative value" can be understood as the derivative value of the count value, used to represent the rate of change of the count value. In this application, the "count derivative value" is an absolute value.

[0040] In this embodiment, by smoothing the original count derivative values, the mean count derivative values ​​corresponding to each track address are obtained. This reduces the error caused by statistical fluctuations, thereby reducing noise and local fluctuations, and making the obtained reference position more stable and reliable.

[0041] In one implementation, calculating the original count derivative value corresponding to each trace address in the falling edge region to the right of the target reference source feature peak may include: calculating a first count value located at a predetermined distance to the left of the target trace address and a second count value located at a predetermined distance to the right of the target trace address in the falling edge region to the right of the target reference source feature peak; wherein the predetermined distance is determined based on the half-width at half-maximum (WHM) of the trace address; and determining the original count derivative value corresponding to the target trace address based on the first count value and the second count value.

[0042] For example, the half-width at half-height (FWHM) can be an integer multiple of a predetermined distance. Using the predetermined distance as... Let's take an example. The predetermined distance to the left of target address i is... The first count value at the predetermined distance to the left of target address i is The predetermined distance to the right of the target address i is The second count value at the predetermined distance to the right of target address i is The original count derivative value corresponding to target address i

[0043] In one example, in the region of the falling edge to the right of the target reference source characteristic peak, partial address i and count value y iThe relationships are shown in Table 1:

[0044] Table 1

[0045] Daozhi i <![CDATA[Count value y i > 12 600 13 550 14 400 15 250 16 100

[0046] For example, with a half-width at half-maximum (FWHM) of 3, the predetermined distance is 1. When calculating the original count derivative value corresponding to address 13, the target address i is 13. The predetermined distance to the left of target address 13 is 13-1=12, i.e., address 12. The first count value y at the predetermined distance to the left of target address 13 is... 12 The value is 600. The predetermined distance to the right of target address 13 is 13 + 1 = 14, which is address 14. The second count value y at the predetermined distance to the right of target address 13 is... 14 The value is 400. The original count derivative value corresponding to target address 13. Similarly, the original count derivative value corresponding to each address in the falling edge region to the right of the target reference source characteristic peak can be calculated.

[0047] In this embodiment, the original count derivative value corresponding to each track address can be effectively determined, and the original count derivative value corresponding to each track address can be smoothed to obtain the mean count derivative value corresponding to each track address, thereby determining the reference position with the largest slope.

[0048] In one embodiment, smoothing the original count derivative value to obtain the mean count derivative value corresponding to each road address may include: calculating the total number of road addresses within a preset road address range of the target road address and the sum of the original count derivative values; wherein, the preset road address range is the range between a predetermined distance to the left and a predetermined distance to the right of the target road address; and determining the mean count derivative value corresponding to the target road address based on the total number of road addresses within the preset road address range and the sum of the original count derivative values.

[0049] For example, with a predetermined distance as Let's take an example. The predetermined distance to the left of target address i is... The predetermined distance to the right of the target address i is The preset address range is (Including endpoint values). The total number of addresses within the preset address range is: The sum of the original count derivative values ​​within the preset address range is The mean count derivative value corresponding to target address i

[0050] In one example, in the region of the falling edge to the right of the target reference source characteristic peak, part of the address i and the original count derivative value are... The relationships are shown in Table 2:

[0051] Table 2

[0052]

[0053] For example, with a half-width at half-maximum (FWHM) of 6, the predetermined distance is 2. When calculating the mean count derivative value corresponding to address 14, the target address i is 14. The predetermined distance to the left of target address 14 is 14-2=12, i.e., address 12. The predetermined distance to the right of target address 14 is 14+2=16, i.e., address 16. The preset address range is address 12 to address 16 (including endpoint values). The total number of addresses within the preset address range is 5.

[0054] The mean count derivative value f corresponding to target address 14 avg-14 =100 / 5=20. Similarly, the mean count derivative value corresponding to each trace address in the descending region to the right of the target reference source characteristic peak can be calculated. The position corresponding to the maximum value among the mean count derivative values ​​is determined as the reference position with the largest slope.

[0055] In this embodiment, the original count derivative values ​​within the preset track address range of the target track address can be mean filtered, which can effectively reduce the error caused by statistical fluctuations, reduce noise and local fluctuations, and make the obtained reference position more stable and reliable.

[0056] In one embodiment, in step S302, determining the target reference source feature peak based on multiple address feature values ​​may include: determining the local maximum value among the multiple address feature values; determining the feature peak corresponding to the local maximum value that is greater than a preset threshold as a pre-selected reference source feature peak; and determining the target reference source feature peak among the pre-selected reference source feature peaks.

[0057] The local maximum can be understood as the maximum value within a local range, which is greater than the characteristic value of the corresponding road address of the adjacent road address. For example, in S i >S i-1 And S i >S i+1 In the case of S i It is a local maximum.

[0058] In one example, partial address i and address characteristic S i The relationships are shown in Table 3:

[0059] Table 3

[0060] Daozhi i <![CDATA[Road address eigenvalue S i > 1 5 2 10 3 8 4 12 5 7

[0061] For example, referring to Table 3, the address characteristic value S2 corresponding to address 2 is 10, S2 > S1 and S2 > S3, therefore, address characteristic value S2 is a local maximum. The address characteristic value S4 corresponding to address 4 is 12, S4 > S3 and S4 > S5, therefore, address characteristic value S4 is also a local maximum. Similarly, all local maximums in the energy spectrum can be identified. Then, from all local maximums, those greater than a preset threshold are selected and identified as pre-selected reference source characteristic peaks. For example, when the preset threshold is 9, both address characteristic values ​​S2 and S4 are identified as pre-selected reference source characteristic peaks; when the preset threshold is 11, only address characteristic value S4 is identified as a pre-selected reference source characteristic peak; when the preset threshold is 13, neither address characteristic values ​​S2 nor S4 are identified as pre-selected reference source characteristic peaks. Finally, the target reference source characteristic peak is determined from the pre-selected reference source characteristic peaks.

[0062] In this embodiment, by determining the feature peaks corresponding to local maximum values ​​greater than a preset threshold as pre-selected reference source feature peaks, insignificant local maximum values ​​can be effectively filtered out, and significant feature peaks can be retained as pre-selected reference source feature peaks. Finally, the target reference source feature peak is determined from the pre-selected reference source feature peaks.

[0063] In one embodiment, determining a target reference source characteristic peak from pre-selected reference source characteristic peaks includes: determining the count rate of the pre-selected reference source characteristic peaks; determining the pre-selected reference source characteristic peaks whose count rates are within a preset count rate range as candidate reference source characteristic peaks; and determining the candidate reference source characteristic peak closest to the reference source characteristic peak after the previous spectral stabilization adjustment as the target reference source characteristic peak.

[0064] For example, the count rate doserate of the preselected reference source characteristic peak can be calculated using the following formula: Among them, y i is the count value of the peak region address i; FWHM is the half-width at half-maximum. The sum of all count values ​​within the peak region; t is the data acquisition time. The preset count rate range can be 0.3Dose to 3Dose (inclusive of endpoint values). Here, Dose is the standard count rate of the detector in passive spectral stabilization mode, which can be obtained by measurement during detector power-on calibration. After determining the candidate reference source characteristic peaks, the distance between each candidate reference source characteristic peak and the reference source characteristic peak recorded after the previous spectral stabilization adjustment can be calculated, and the candidate reference source characteristic peak with the closest distance can be determined as the target reference source characteristic peak.

[0065] In this embodiment, by determining the pre-selected reference source characteristic peaks whose count rates are within a preset count rate range as candidate reference source characteristic peaks, pre-selected reference source characteristic peaks with excessively low or high intensities can be excluded, avoiding the influence of noise or background fluctuations and interference caused by other types of radionuclides. By determining the candidate reference source characteristic peak closest to the reference source characteristic peak after the previous spectral stabilization adjustment as the target reference source characteristic peak, the characteristic peak with the smallest deviation from historical reference source characteristic peaks can be selected from the candidate reference source characteristic peaks as the target reference source characteristic peak, improving the positioning accuracy of the target reference source characteristic peak.

[0066] In one embodiment, determining the address feature value corresponding to each address in the energy spectrum in step S301 may include: determining the count value corresponding to each address in the energy spectrum; and performing convolution calculation with the count value corresponding to each address using a symmetric window function to obtain the address feature value corresponding to each address.

[0067] For example, the symmetric window function C j A symmetric window function with a total area of ​​zero, i.e., a symmetric window function C. j satisfy: This eliminates the contribution of background signals, thereby enhancing the ability to identify characteristic peaks. The prototype of the window function can be a Gaussian function, such as a Gaussian function with a height of 1 and a half-width at half-maximum (WWHM) equal to the detector's WWHM. Symmetric window function C j satisfy: Where σ = FWHM / 2.355 is the standard deviation of the Gaussian function; FWHM is the full width at half maximum (FWHM) corresponding to channel address i. The convolution calculation formula satisfies: in, It is a weighted sum of the symmetric window function and the count values; To normalize the weighted sum and reduce the impact of noise, a symmetric window function C is used. j The formulas and convolution formulas can be used to calculate the feature values ​​of each channel address.

[0068] In this embodiment, the characteristic values ​​of each tunnel address can be obtained by the symmetric zero-area method, thereby enabling the determination of the target reference source characteristic peak based on multiple tunnel address characteristic values.

[0069] As an implementation of the above methods, this application also provides a nuclear energy spectrum stabilization device, which may include: an eigenvalue determination module for determining the eigenvalue corresponding to each channel in the energy spectrum; a characteristic peak determination module for determining the characteristic peak of a target reference source based on multiple channel eigenvalues; a reference position determination module for determining the reference position with the largest slope in the right-side falling edge region of the characteristic peak of the target reference source; a center position determination module for determining the center position of the characteristic peak of the target reference source based on a predetermined scaling factor and the reference position; wherein the predetermined scaling factor is the ratio of the reference distance to the full width at half maximum (FWHM); the reference distance is the distance between the center position of the characteristic peak of the reference source and the reference position; and a correction module for correcting the energy spectrum based on the center position of the characteristic peak of the target reference source to obtain a stable energy spectrum.

[0070] In one embodiment, the reference position determination module includes: a calculation submodule, used to calculate the original count derivative value corresponding to each channel address in the falling edge region to the right of the characteristic peak of the target reference source; a processing submodule, used to smooth the original count derivative value to obtain the mean count derivative value corresponding to each channel address; and a position determination submodule, used to determine the position corresponding to the maximum value among the mean count derivative values ​​as the reference position with the largest slope.

[0071] In one implementation, the calculation submodule is further configured to: calculate a first count value located at a predetermined distance to the left of the target address and a second count value located at a predetermined distance to the right of the target address in the region of the falling edge to the right of the characteristic peak of the target reference source; wherein the predetermined distance is determined based on the half-width at half-maximum corresponding to the address; and determine the original count derivative value corresponding to the target address based on the first count value and the second count value.

[0072] In one embodiment, the processing submodule is further configured to: calculate the total number of road addresses within the preset road address range of the target road address and the sum of the original count derivative values; wherein, the preset road address range is the range between a predetermined distance to the left of the target road address and a predetermined distance to the right of the target road address; and determine the mean count derivative value corresponding to the target road address based on the sum of the total number of road addresses within the preset road address range and the original count derivative values.

[0073] In one embodiment, the feature peak determination module includes: a maximum value determination submodule, used to determine the local maximum value among multiple channel address feature values; a pre-selected feature peak determination submodule, used to determine the feature peak corresponding to the local maximum value that is greater than a preset threshold as a pre-selected reference source feature peak; and a target feature peak determination submodule, used to determine the target reference source feature peak among the pre-selected reference source feature peaks.

[0074] In one implementation, the target characteristic peak determination submodule is further configured to: determine the count rate of the pre-selected reference source characteristic peaks; determine the pre-selected reference source characteristic peaks whose count rates are within a preset count rate range as candidate reference source characteristic peaks; and determine the candidate reference source characteristic peak closest to the reference source characteristic peak after the previous spectral stabilization adjustment as the target reference source characteristic peak.

[0075] In one implementation, the feature value determination module is further configured to: determine the count value corresponding to each channel address in the energy spectrum; and perform convolution calculation with the count value corresponding to each channel address using a symmetric window function to obtain the channel address feature value corresponding to each channel address.

[0076] The functions of each module in the device of this embodiment can be found in the corresponding descriptions in the above methods, and will not be repeated here.

[0077] According to embodiments of this application, this application also provides an electronic device, a computer-readable storage medium, and a computer program product.

[0078] Figure 4 A structural block diagram of an electronic device according to an embodiment of the present invention is shown. Figure 4 As shown, the electronic device includes a memory 410 and a processor 420. The memory 410 stores a computer program that can run on the processor 420. When the processor 420 executes the computer program, it implements the radiation source localization method in the above embodiments. The number of memories 410 and processors 420 can be one or more.

[0079] The electronic device also includes:

[0080] The communication interface 430 is used to communicate with external devices and perform data exchange and transmission.

[0081] If the memory 410, processor 420, and communication interface 430 are implemented independently, they can be interconnected via a bus to communicate with each other. This bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. This bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 4 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0082] Optionally, in a specific implementation, if the memory 410, processor 420 and communication interface 430 are integrated on a single chip, the memory 410, processor 420 and communication interface 430 can communicate with each other through an internal interface.

[0083] This invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method provided in this application.

[0084] This application also provides a chip, which includes a processor for calling and executing instructions stored in a memory, causing a communication device on which the chip is installed to perform the method provided in this application.

[0085] This application also provides a chip, including: an input interface, an output interface, a processor, and a memory. The input interface, output interface, processor, and memory are connected through an internal connection path. The processor is used to execute code in the memory. When the code is executed, the processor is used to execute the method provided in the application embodiment.

[0086] It should be understood that the aforementioned processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. General-purpose processors can be microprocessors or any conventional processor. It is worth noting that the processor can be a processor supporting Advanced Reduced Instruction Set Computing (RISC) machines (ARM) architecture.

[0087] Further, optionally, the aforementioned memory may include read-only memory and random access memory, and may also include non-volatile random access memory. The memory may be volatile or non-volatile, or may include both. Non-volatile memory may include read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory may include random access memory (RAM), which serves as an external cache. By way of example, but not limitation, many forms of RAM are available. Examples include static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0088] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to this application is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another.

[0089] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of those different embodiments or examples.

[0090] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "a plurality of" means two or more, unless otherwise explicitly specified.

[0091] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process. Furthermore, the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functionality involved.

[0092] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus or device (such as a computer-based system, a processor-included system or other system that can fetch and execute instructions from, an instruction execution system, apparatus or device).

[0093] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. All or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware, the program being stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiments.

[0094] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. This storage medium can be a read-only memory, a disk, or an optical disk, etc.

[0095] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various variations or substitutions within the technical scope disclosed in this application, and these should all be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method of deconvolving a nuclear spectrum, characterized by, The method comprises the following steps: determining channel address characteristic values corresponding to each channel address in a spectrum diagram; determining a target reference source characteristic peak according to a plurality of channel address characteristic values; determining a reference position with the maximum slope in a falling edge region on the right side of the target reference source characteristic peak; determining a center position of the target reference source characteristic peak according to a predetermined proportion coefficient and the reference position; wherein the predetermined proportion coefficient is the ratio of a reference distance to a half-height width; the reference distance is the distance between the center position of the reference source characteristic peak and the reference position; correcting the spectrum diagram based on the center position of the target reference source characteristic peak to obtain a stable spectrum; determining a reference position with the maximum slope in a falling edge region on the right side of the target reference source characteristic peak comprises: calculating original count derivative values corresponding to each channel address in the falling edge region on the right side of the target reference source characteristic peak; performing smoothing processing on the original count derivative values to obtain mean count derivative values corresponding to each channel address; determining the position corresponding to the maximum value in the mean count derivative values as the reference position with the maximum slope; calculating original count derivative values corresponding to each channel address in the falling edge region on the right side of the target reference source characteristic peak comprises: calculating a first count value located at a predetermined distance on the left side of a target channel address and a second count value located at a predetermined distance on the right side of the target channel address in the falling edge region on the right side of the target reference source characteristic peak; wherein the predetermined distances are determined based on the half-height widths corresponding to the channel addresses; determining original count derivative values corresponding to the target channel address according to the first count value and the second count value; performing smoothing processing on the original count derivative values to obtain mean count derivative values corresponding to each channel address comprises: calculating the total number of channel addresses and the sum of original count derivative values within a preset channel address range of a target channel address; wherein the preset channel address range is the range between the predetermined distance on the left side of the target channel address and the predetermined distance on the right side of the target channel address; determining the mean count derivative value corresponding to the target channel address according to the total number of channel addresses within the preset channel address range and the sum of original count derivative values.

2. The method of claim 1, wherein, determining a target reference source characteristic peak according to a plurality of channel address characteristic values comprises: determining local maximum values in the plurality of channel address characteristic values; determining a characteristic peak corresponding to a local maximum value greater than a preset threshold as a preselected reference source characteristic peak; determining a target reference source characteristic peak in the preselected reference source characteristic peak.

3. The method of claim 2, wherein, determining a target reference source characteristic peak in the preselected reference source characteristic peak comprises: determining a count rate of the preselected reference source characteristic peak; determining a preselected reference source characteristic peak with a count rate within a preset count rate range as a candidate reference source characteristic peak; determining a candidate reference source characteristic peak closest to the reference source characteristic peak after the last stable spectrum adjustment as the target reference source characteristic peak.

4. The method according to any one of claims 1 to 3, characterized in that, determining channel address characteristic values corresponding to each channel address in a spectrum diagram comprises: determining count values corresponding to each channel address in the spectrum diagram; performing convolution calculation on the count values corresponding to each channel address by using a symmetric window function to obtain channel address characteristic values corresponding to each channel address.

5. An electronic device comprising: a processor, and a memory storing a program, the program comprising instructions which, when executed by the processor, cause the processor to perform the method according to any one of claims 1 to 4.

6. A computer-readable storage medium having stored therein a computer program, which, when executed by a processor, implements the method according to any one of claims 1 to 4.

7. A computer program product comprising a computer program for causing a computer to perform the method according to any one of claims 1 to 4 when the computer program is executed by a processor of the computer.

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