Neutron energy spectrum measurement method and device based on characteristic gamma energy response

Abstract

The invention relates to the field of neutron energy spectrum measurement, and provides a neutron energy spectrum measurement method and device based on characteristic gamma energy response, and the method comprises the steps: obtaining a counting rate and a corresponding energy response; discretizing continuous energy into a plurality of energy groups, and establishing a linear equation set by using an energy response function; carrying out iterative solution on the linear equation set to obtain a neutron energy spectrum; a neutron dose equivalent conversion factor can be expressed as linear superposition of an energy response function, and a contribution weight coefficient is obtained by adopting a weighted least square method; and calculating a first neutron dose equivalent rate based on the contribution weight coefficient and the counting rate, calculating a second neutron dose equivalent rate based on the neutron energy spectrum and the neutron dose equivalent conversion factor, carrying out comparison verification on the first neutron dose equivalent rate and the second neutron dose equivalent rate, and outputting the neutron energy spectrum as a final measurement result when the comparison verification is passed. On the basis of the single detector, the purpose of online real-time measurement of the neutron energy spectrum is achieved, and the accuracy and the reliability of a measurement result are improved.

Description

Technical Field

[0001] This invention relates to the field of neutron energy spectrum measurement, and more particularly to a method and apparatus for neutron energy spectrum measurement based on characteristic γ energy response. Background Technology

[0002] Neutrons are one of the main objects of nuclear radiation detection and radiodoscopy research. Neutrons of different energies interact with biological tissues in different ways, and the resulting radiation biological effects are also significantly different. The neutron dose rate corresponding to a unit neutron fluence rate varies greatly with neutron energy, and can differ by up to nearly a hundred times. Therefore, the neutron energy spectrum is of vital importance for neutron dose rate measurement and neutron radiation protection.

[0003] Among existing technologies, the Bonner multi-sphere neutron spectrometer is the most widely used, possessing advantages such as isotropic energy response and high response sensitivity. However, the Bonner multi-sphere spectrometer requires multiple polyethylene moderator spheres of different sizes, necessitating the replacement of each moderator sphere for multiple measurements. The entire measurement process typically takes several hours or even longer, and the equipment is bulky and complex to operate, making it unsuitable for applications requiring high real-time performance and portability, such as online monitoring and emergency response of nuclear facilities. Summary of the Invention

[0004] In view of this, the present invention proposes a neutron energy spectrum measurement method and device based on characteristic γ energy response, which solves the problems of existing Bonner multisphere spectrometers being large in size and weight, only usable for offline measurement, and having long measurement time and complicated operation.

[0005] The technical solution of the present invention is implemented as follows: On the one hand, the present invention provides a neutron energy spectrum measurement device based on characteristic γ energy response. The device is a spherical detection structure, including a scintillator detector, an inner layer of polyethylene, a middle layer of boron-containing polyethylene, and an outer layer of polyethylene.

[0006] The scintillator detector is located at the center of the neutron energy spectrum measuring device and is used to detect thermal neutrons and gamma rays.

[0007] On the other hand, the present invention provides a neutron energy spectrum measurement method based on characteristic γ energy response, comprising the following steps:

[0008] A lithium-6 scintillator detector was used to measure the neutron field under test. Neutrons and gamma rays were distinguished by the difference in pulse shape and amplitude, and the neutron count rate and characteristic gamma ray count rate were obtained.

[0009] The neutron energy response function and characteristic gamma-ray energy response function for different monoenergetic neutrons within a preset energy range were obtained by Monte Carlo simulation calculation.

[0010] Based on the principle of integral equations, continuous energy is discretized into multiple energy groups. Using the neutron energy response function and the characteristic gamma-ray energy response function, a system of linear equations is established with the neutron flux density of each energy group as unknowns and the neutron count rate and energy response as knowns.

[0011] The linear equations are solved iteratively using the nonnegative constraint least squares method to obtain the neutron energy spectrum. The nonnegative constraint least squares method sets nonnegativity constraints, smoothness constraints, and prior information constraints.

[0012] The neutron dose equivalent conversion factor is obtained by weighted least squares method. The neutron dose equivalent conversion factor is represented by the linear superposition of neutron energy response function and characteristic gamma-ray energy response function.

[0013] The first neutron dose equivalent rate is calculated based on the contribution weight coefficient, the neutron count rate, and the characteristic gamma ray count rate. The second neutron dose equivalent rate is calculated based on the neutron energy spectrum and the neutron dose equivalent conversion factor. The first neutron dose equivalent rate and the second neutron dose equivalent rate are compared and verified. When the comparison and verification pass, the neutron energy spectrum is output as the final measurement result.

[0014] Based on the above technical solutions, preferably, the step of obtaining the neutron energy response function and characteristic gamma-ray energy response function for different monoenergetic neutron incidents within a preset energy range through Monte Carlo simulation calculations includes:

[0015] By establishing a simulation model of the neutron energy spectrum detection device, the Monte Carlo method is used to simulate the energy response of the scintillator detector to neutrons and the energy response to characteristic gamma rays under different monoenergetic neutron incident spherical neutron energy spectrum detection device conditions, so as to obtain the neutron energy response function and the characteristic gamma ray energy response function.

[0016] Based on the above technical solutions, preferably, the process of constructing the characteristic gamma-ray energy response function includes:

[0017] Characteristic gamma-ray energies are generated by the interaction of neutrons with polyethylene and boron-containing polyethylene. The transport and deposition process of characteristic gamma rays in a scintillator detector is simulated using the Monte Carlo method. The gamma energy spectrum of the scintillator detector is recorded, characteristic gamma energy peaks are identified, the peak areas of different characteristic energy peaks are statistically analyzed, and the corresponding count rates are calculated to obtain the characteristic gamma energy response.

[0018] Based on the above technical solutions, preferably, the neutron dose equivalent conversion factor is obtained by weighted least squares method, and the neutron dose equivalent conversion factor is represented by the linear superposition of the neutron energy response function and the characteristic gamma-ray energy response function, including:

[0019] By querying the ICRP-74 report, the neutron dose equivalent conversion factor corresponding to different neutron energies is obtained. Based on the neutron energy response function and the characteristic gamma-ray energy response function, they are linearly combined according to a preset weight ratio to represent the neutron dose equivalent conversion factor corresponding to each energy point.

[0020] Based on the theory of relative error minimization, the weighted least squares method is used to fit the neutron dose equivalent conversion factor to obtain the contribution weight coefficient.

[0021] Based on the above technical solution, preferably, the non-negativity-constrained least squares method is used to iteratively solve the linear equation system to obtain the neutron energy spectrum. The non-negativity-constrained least squares method includes non-negativity constraints, smoothness constraints, and prior information constraints, including:

[0022] Based on the linear equations, the neutron flux rate density of each energy group is solved using the non-negative constraint least squares method. During the solution process, non-negative constraints and smoothness constraints are introduced to suppress fluctuations and negative values ​​in the inversion results.

[0023] The constraints are combined with the observation data to form a weighted objective function, and the weighted objective function is iteratively optimized to obtain the optimal neutron energy spectrum distribution.

[0024] Based on the above technical solutions, preferably, the solution process of the non-negative constrained least squares method includes:

[0025] The lower bound of the neutron flux rate density for each energy group is set to zero, and a constraint matrix including nonnegativity constraints is constructed.

[0026] Smoothness constraints are constructed by introducing differential quadratic terms between the neutron flux rate densities of each energy group into the weighted objective function;

[0027] Based on prior information, weighting coefficients are set for the neutron flux rate density of some energy groups to construct prior information constraints.

[0028] Using an iterative optimization algorithm, the constraint strength and weight factors are dynamically adjusted in each iteration until the objective function converges to the optimum.

[0029] Based on the above technical solutions, preferably, the step of using a lithium-6 scintillator detector to measure the neutron field under test, distinguishing neutrons and gamma rays by differences in pulse shape and amplitude, and obtaining the neutron count rate and characteristic gamma ray count rate includes:

[0030] The scintillation pulse signals generated in the neutron field under test are collected and analyzed to obtain the pulse shape and amplitude characteristics;

[0031] Neutron signals and characteristic gamma-ray signals are identified and distinguished based on pulse shape and amplitude characteristics, and the neutron count rate and characteristic gamma-ray count rate are calculated separately.

[0032] Based on the above technical solutions, preferably, the step of identifying and distinguishing neutron signals and characteristic gamma-ray signals according to pulse shape and amplitude characteristics, and separately calculating the neutron count rate and characteristic gamma-ray count rate, includes:

[0033] Pulse shape discrimination technology is used to identify neutron signals and characteristic gamma-ray signals by setting a discrimination threshold based on the difference in the integral ratio of the fast and slow components of the scintillator output pulse under different particle excitation in the pulse shape and amplitude characteristics. The identified signals are then included in the neutron count rate and gamma response, respectively, and the characteristic gamma rays are identified in the gamma energy spectrum and the characteristic gamma-ray count rate is measured.

[0034] Based on the above technical solutions, preferably, the step of discretizing continuous energy into multiple energy groups based on the principle of integral equations, and establishing a system of linear equations with neutron fluence density of each energy group as unknowns and neutron count rate and energy response as knowns using the neutron energy response function and characteristic gamma-ray energy response function, includes:

[0035] The continuous energy within the preset energy range is discretized into several energy groups, and a set of unknown neutron flux rate density for each energy group is constructed.

[0036] The neutron count rate and characteristic gamma-ray count rate are obtained using the neutron energy spectrum detection device. The neutron energy response function and characteristic gamma-ray energy response function are calculated using the Monte Carlo simulation method, and a system of linear equations is established with the neutron count rate, characteristic gamma-ray count rate and energy response as known values.

[0037] The neutron energy spectrum measurement method and apparatus based on characteristic γ energy response of the present invention have the following advantages over the prior art:

[0038] (1) By using a single lithium-6 scintillator detector to simultaneously acquire neutron signals and characteristic gamma-ray signals, neutron and gamma-ray energy response functions are established based on Monte Carlo simulation, and neutron energy spectrum is rapidly measured by combining non-negative constraint least squares inversion algorithm. A dual neutron dose equivalent rate verification mechanism is established, which effectively improves the accuracy and reliability of neutron energy spectrum measurement results and realizes online real-time measurement with a single detector.

[0039] (2) By establishing a simulation model of the neutron energy spectrum measurement device, the neutron energy response function and the characteristic γ-ray energy response function were obtained by using the Monte Carlo method. The deposition process of γ-rays generated by the interaction between neutrons of different energies and the slowing absorption material was accurately simulated in the detector, and the γ-ray energy spectrum was obtained. By identifying the characteristic γ-ray energy peak, the neutron and characteristic γ-ray energy response functions that reflect the real physical characteristics of the detector were obtained. The response matrix obtained by simulation provides the physical basis for the neutron energy spectrum inversion algorithm, ensuring the accuracy of the neutron energy spectrum measurement results, avoiding the complicated experimental calibration process, and improving the efficiency and accuracy of energy response acquisition.

[0040] (3) By linearly combining the neutron energy response function and the characteristic γ-ray energy response function, a composite response function for each energy point is established. The weighted least squares method is used to optimize and fit the neutron dose equivalent conversion factor, and the optimal contribution weight coefficients of the neutron signal and the characteristic γ-ray signal are obtained. The weight adaptive optimization of the dual signals is realized, and the accuracy of the neutron dose equivalent rate calculation is improved. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 This is a schematic diagram of a neutron energy spectrum measurement device based on characteristic γ energy response according to the present invention;

[0043] Figure 2 This is a flowchart of a neutron energy spectrum measurement method based on characteristic γ energy response according to the present invention. Detailed Implementation

[0044] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0045] Please see Figure 1 The present invention discloses a neutron energy spectrum measurement device based on characteristic γ energy response, characterized in that the device is a spherical detection structure, comprising a scintillator detector, an inner layer of polyethylene, a middle layer of boron-containing polyethylene, and an outer layer of polyethylene.

[0046] The scintillator detector is located at the center of the neutron energy spectrum measuring device and is used to detect thermal neutrons and gamma rays;

[0047] In one specific embodiment, the neutron energy spectrum measuring device adopts a spherical detection structure to achieve isotropic neutron energy response; the central detector of the neutron energy spectrum measuring device is a scintillator detector that can detect both thermal neutrons and gamma rays; the central detector is surrounded by two layers of polyethylene moderation layers, with an absorption layer in between the two polyethylene moderation spheres. The absorption layer is made of uniformly perforated boron-containing polyethylene or cadmium layer to achieve neutron dose equivalent detection.

[0048] This embodiment optimizes the detector structure by optimizing the structure of the neutron spectrometer from three dimensions: polyethylene thickness, boron-containing polyethylene thickness, and boron content (boron doping ratio and perforation area).

[0049] The optimization principle is to achieve the best match between the neutron dose rate energy response and the neutron fluence-neutron surrounding dose equivalent conversion coefficient curve in ICRP74 as a function of energy. The optimization steps include: First, prioritizing the optimization of the moderator size, which affects the detection efficiency of both fast and slow neutrons, ensuring the detection efficiency of fast neutrons, and optimizing the peak region matching of the conversion coefficient curve; second, optimizing the thickness of the boron-containing polyethylene, optimizing the valley region matching of the conversion coefficient curve; finally, optimizing the boron content and the perforation area, optimizing the plateau region matching of the conversion coefficient curve.

[0050] The scintillator employs pulse signal amplitude and shape discrimination techniques for dual-ray detection of neutrons and gamma rays. Energy spectrum measurements are performed on the discriminated gamma rays to identify gamma energy peaks with different characteristics. The peak areas of these peaks are then statistically analyzed to calculate the corresponding count rate response. The count rate response is then used to detect the discriminated neutrons.

[0051] In one specific embodiment, the measurement principle of the neutron energy spectrum measuring device based on characteristic γ energy response is as follows:

[0052] The novel scintillation crystal contains or is doped with 6 Li element, through neutron capture reaction 6 Li(n,T)α can generate a deposition energy of 4.78 MeV to excite scintillators to emit light. A photomultiplier tube converts the weak light signal from the scintillator into an electrical signal. A preamplifier performs IU conversion on the electrical signal, and the main amplifier filters, amplifies, and shapes the output signal. The signal processing unit converts the pulse signal into a spectral signal, and simultaneously uses differences in pulse amplitude and pulse shape to distinguish between neutron and gamma rays. This enables novel scintillator crystals (such as NaIL scintillators and CLYC scintillators) to simultaneously detect gamma rays and neutron rays.

[0053] When neutrons of different energies are incident, the amount of thermal neutrons varies after being moderated and absorbed by polyethylene and boron-containing polyethylene, resulting in different responses. The responses also differ between boron-containing polyethylene and polyethylene containing neutrons. 10 B, H, and C nuclides react with neutrons to produce characteristic gamma rays with energies of 477 keV, 2.2 MeV, and 4.43 MeV, respectively. The characteristic gamma ray response curves and neutron response curves detected by the scintillator are different depending on the incident neutron energy.

[0054] Using the Monte Carlo simulation method, a probabilistic statistical "nondeterministic method," a probabilistic model of actual irradiation by a neutron spectrometer is constructed. This model simulates the case of monoenergetic neutrons incident on the neutron spectrometer with energies ranging from thermal neutrons to 20 MeV. One neutron energy response curve and three energy response curves based on characteristic gamma rays can be obtained.

[0055] Energy response directly affects the accuracy of neutron energy spectrum measurement. To improve the difference between the γ energy response curves of different characteristics of scintillators and thus enhance the curve fitting effect, the structures of the moderator and absorber in the structure were optimized.

[0056] The structure of the neutron spectrometer was optimized from three dimensions: polyethylene thickness, boron-containing polyethylene thickness, and boron content. This maximized the differences between the three energy response curves based on characteristic gamma rays and the neutron energy response curves, providing as much prior information as possible for neutron energy spectrum interpretation and thus improving the accuracy of the interpretation.

[0057] The first neutron dose equivalent rate was calculated by forward calculation of the neutron energy spectrum obtained by "single-channel spectral analysis" and compared with the second neutron dose rate calculated by "multi-channel spectral analysis" to further complete the supplementary verification of neutron energy spectrum analysis, and further improve the calculation accuracy of the few-channel spectral analysis.

[0058] Please see Figure 2 This invention provides a neutron energy spectrum measurement method based on characteristic γ energy response, comprising the following steps:

[0059] A lithium-6 scintillator detector was used to measure the neutron field under test. Neutrons and gamma rays were distinguished by the difference in pulse shape and amplitude, and the neutron count rate and characteristic gamma ray count rate were obtained.

[0060] The neutron energy response function and characteristic gamma-ray energy response function for different monoenergetic neutrons within a preset energy range were obtained by Monte Carlo simulation calculation.

[0061] Based on the principle of integral equations, continuous energy is discretized into multiple energy groups. Using the neutron energy response function and the characteristic gamma-ray energy response function, a system of linear equations is established with the neutron flux density of each energy group as unknowns and the neutron count rate and energy response as knowns.

[0062] The linear equations are solved iteratively using the nonnegative constraint least squares method to obtain the neutron energy spectrum. The nonnegative constraint least squares method sets nonnegativity constraints, smoothness constraints, and prior information constraints.

[0063] The neutron dose equivalent conversion factor is obtained by weighted least squares method. The neutron dose equivalent conversion factor is represented by the linear superposition of neutron energy response function and characteristic gamma-ray energy response function.

[0064] The first neutron dose equivalent rate is calculated based on the contribution weight coefficient, the neutron count rate, and the characteristic gamma ray count rate. The second neutron dose equivalent rate is calculated based on the neutron energy spectrum and the neutron dose equivalent conversion factor. The first neutron dose equivalent rate and the second neutron dose equivalent rate are compared and verified. When the comparison and verification pass, the neutron energy spectrum is output as the final measurement result.

[0065] Specifically, this embodiment employs a single lithium-6 scintillator detector to simultaneously acquire neutron signals and characteristic gamma-ray signals. Based on Monte Carlo simulation, neutron and gamma-ray energy response functions are established. Combined with a non-negative constraint least squares inversion algorithm, the neutron energy spectrum is rapidly measured, and a dual neutron dose equivalent rate verification mechanism is established. This effectively improves the accuracy and reliability of neutron energy spectrum measurement results and enables online real-time measurement with a single detector.

[0066] The method employs a lithium-6 scintillator detector to measure the neutron field under test, distinguishing neutrons and gamma rays by differences in pulse shape and amplitude, and obtaining the neutron count rate and characteristic gamma ray count rate, including:

[0067] The scintillation pulse signals generated in the neutron field under test are collected and analyzed to obtain the pulse shape and amplitude characteristics;

[0068] In one specific embodiment, the acquisition and analysis of the scintillation pulse signal generated in the neutron field under test to obtain pulse shape and amplitude characteristics includes:

[0069] The electrical signals generated by the scintillator detector are digitally processed and subjected to waveform time window integration analysis using a data acquisition system. By extracting the integration ratio of the fast and slow components of the pulse and the peak amplitude information, the pulse shape and amplitude characteristics are obtained.

[0070] Neutron signals and characteristic gamma-ray signals are identified and distinguished based on pulse shape and amplitude characteristics, and the neutron count rate and characteristic gamma-ray count rate are calculated separately.

[0071] In one specific embodiment, the step of identifying and distinguishing neutron signals and characteristic gamma-ray signals based on pulse shape and amplitude characteristics, and separately calculating the neutron count rate and characteristic gamma-ray count rate, includes:

[0072] Pulse shape discrimination technology is used to identify neutron signals and characteristic gamma-ray signals by setting a discrimination threshold based on the difference in the integral ratio of the fast and slow components of the scintillator output pulse under different particle excitation in the pulse shape and amplitude characteristics. The identified signals are then included in the neutron count rate and gamma response, respectively, and the characteristic gamma rays are identified in the gamma energy spectrum and the characteristic gamma-ray count rate is measured.

[0073] Specifically, this embodiment extracts the integration ratio of the fast and slow components and the peak amplitude information of the pulse through digital processing and waveform time window integration analysis. By employing pulse shape discrimination technology, based on the difference in the integration ratio of the fast and slow components of the scintillator output pulse under neutron and gamma-ray excitation, it achieves effective identification and differentiation of the two signals. This embodiment accurately counts the neutron count rate and characteristic gamma-ray count rate by setting discrimination thresholds, providing an experimental data foundation for the establishment of neutron and gamma response functions and energy spectrum inversion, ensuring the signal processing accuracy and data quality of neutron energy spectrum measurement.

[0074] The process of obtaining the neutron energy response function and characteristic gamma-ray energy response function for different monoenergetic neutron incidents within a preset energy range through Monte Carlo simulation calculations includes:

[0075] By establishing a simulation model of the neutron energy spectrum measurement device, the Monte Carlo method is used to simulate the energy response of the scintillator detector to neutrons and the energy response to characteristic gamma rays under different monoenergetic neutron incident neutron energy spectrum measurement device conditions, so as to obtain the neutron energy response function and the characteristic gamma ray energy response function.

[0076] The process of constructing the characteristic gamma-ray energy response function includes:

[0077] Characteristic gamma-ray energies are generated by the interaction of neutrons with polyethylene and boron-containing polyethylene. The transport and deposition process of characteristic gamma rays in a scintillator detector is simulated using the Monte Carlo method. The gamma energy spectrum of the scintillator detector is recorded, characteristic gamma energy peaks are identified, the peak areas of different characteristic energy peaks are statistically analyzed, and the corresponding count rates are calculated to obtain the characteristic gamma energy response.

[0078] Specifically, this embodiment establishes a simulation model of the neutron energy spectrum measurement device and uses the Monte Carlo method to obtain the neutron energy response function and the characteristic gamma-ray energy response function, respectively. It accurately simulates the transport and deposition process of the characteristic gamma rays generated by the interaction in the scintillator detector, and obtains the energy response function matrix that reflects the real physical characteristics of the detector. The response function obtained from the simulation provides a physical basis for the neutron energy spectrum inversion algorithm, ensuring the accuracy of the neutron energy spectrum measurement results, avoiding the complicated experimental calibration process, and improving the efficiency and accuracy of the response function acquisition.

[0079] The method, based on the principle of integral equations, discretizes continuous energy into multiple energy groups. Using the neutron energy response function and the characteristic gamma-ray energy response function, a system of linear equations is established with the neutron fluence rate density of each energy group as unknowns and the neutron count rate and energy response as knowns. This system includes:

[0080] The continuous energy within the preset energy range is discretized into several energy groups, and a set of unknown neutron flux rate density for each energy group is constructed.

[0081] In one specific embodiment, discretizing the continuous energy within the preset energy range into several energy groups and constructing a set of unknown neutron fluence rate densities for each energy group includes:

[0082] The preset energy range is divided into several energy groups according to the set energy interval, and each energy group corresponds to a neutron flux density unknown, thus constructing the set of neutron flux density unknowns.

[0083] Using the neutron energy response function and the characteristic gamma-ray energy response function, the theoretical response of each energy group is calculated, and a system of linear equations is established with the neutron count rate, the characteristic gamma-ray count rate, and the energy response as known values.

[0084] In one specific embodiment, since the neutron spectrometer detection device can only acquire a series of count rates and cannot acquire the neutron energy spectrum, it can be linked together through the energy response based on the principle of integral equations. The calculation formula of the principle of integral equations is as follows:

[0085]

[0086] Among them, M j R represents the count rate of the j-th signal, including the neutron count rate and the characteristic gamma-ray count rate; j (E)) is the response function of the j-th signal to the neutron energy E, including the neutron energy response function and the characteristic gamma-ray energy response function; denoted as denoted as neutron flux rate density for each continuous energy group; E is the neutron energy; dE is the differential element of neutron energy; and m is the total number of signal channels.

[0087] Considering that energy can be discretized in practice, continuous energy is discretized into multiple energy groups. Using the neutron energy response function and the characteristic gamma-ray energy response function, a system of linear equations is established with the neutron fluence rate density of each energy group as unknowns and the neutron count rate and the characteristic gamma-ray count rate as knowns. That is, equation (1) is approximated as n discrete energy groups. The specific calculation formula is as follows:

[0088]

[0089] Among them, M jThe counting rate of the j-th signal; R ij Let be the response of the j-th signal to the i-th energy group, i.e., the elements in the response matrix; Let be the neutron flux density of the i-th energy group, i.e., the neutron flux density of each energy group.

[0090] It should be noted that in this embodiment, m = 4 (including one neutron response curve and three characteristic gamma-ray response curves), while n is generally tens or even hundreds. Therefore, this invention is a problem of "few-channel spectrum solving", which usually requires mathematical processing methods combined with certain constraints to find a unique optimal solution that infinitely approximates the real situation.

[0091] In one specific embodiment, the step of using the neutron energy response function and the characteristic gamma-ray energy response function to calculate the theoretical response of each energy group and establish a system of linear equations with the neutron count rate and the characteristic gamma-ray count rate as known values ​​includes:

[0092] For each energy group, the neutron energy response and characteristic gamma-ray energy response at each energy point are determined by point-by-point simulation or interpolation, a response matrix is ​​constructed, and the linear equation system is established.

[0093] Specifically, this embodiment discretizes continuous energy into multiple energy groups, establishing a set of unknown neutron flux rate densities. By employing point-by-point simulation or interpolation, the neutron energy response and characteristic gamma-ray energy response of each energy group are determined, constructing a complete response matrix. This embodiment achieves an efficient mapping from continuous energy to discrete energy groups, providing a structured foundation of linear equations for solving non-negative constrained least squares methods. Through energy group partitioning and response matrix construction, the computational complexity of energy spectrum inversion is significantly simplified, solution efficiency is improved, and the accuracy of the theoretical responses of each energy group is ensured.

[0094] The non-negativity-constrained least squares method is used to iteratively solve the linear equation system to obtain the neutron energy spectrum. The non-negativity-constrained least squares method includes non-negativity constraints, smoothness constraints, and prior information constraints, including:

[0095] Based on the linear equations, the neutron flux rate density of each energy group is solved by the non-negative constraint least squares method. During the solution process, non-negative constraints and smoothness constraints are introduced to suppress fluctuations and negative values ​​in the inversion results, and to improve the physical interpretability of the energy spectrum solution through regularization.

[0096] By combining constraints with observational data to form a weighted objective function, and iteratively optimizing the weighted objective function, the optimal neutron energy spectrum distribution is obtained, thereby improving the inversion accuracy and stability while satisfying physical constraints.

[0097] The solution process of the non-negativity constrained least squares method includes:

[0098] The lower bound of the neutron flux rate density for each energy group is set to zero, and a constraint matrix including nonnegativity constraints is constructed.

[0099] By introducing a differential quadratic form term between the neutron flux rate densities of each energy group into the weighted objective function, a smoothness constraint is constructed to achieve smooth modulation of the energy spectrum solution, thereby preventing unreasonable and drastic fluctuations in the inverted energy spectrum.

[0100] Weighting coefficients are set for the neutron flux rate density of some energy groups based on prior information to construct prior information constraints and improve the reliability of the inversion results.

[0101] Using an iterative optimization algorithm, the constraint strength and weight factor are dynamically adjusted in each iteration until the objective function converges to the optimum, so that the final neutron energy spectrum not only conforms to the measured count rate, but also has physical rationality and expected smoothness.

[0102] In one specific embodiment, in order to obtain a physically reasonable and mathematically stable solution, it is necessary to introduce various constraints, including physical constraints and prior information constraints, wherein:

[0103] The physical constraints include: nonnegativity constraint, the neutron flux density must be physically nonnegative; and smoothness constraint, the neutron flux density variation between adjacent energy groups should not be too drastic, and the energy spectrum should exhibit continuous and smooth characteristics.

[0104] Specifically, this embodiment achieves comprehensive optimization and control of the energy spectrum inversion process through a multi-constraint mechanism using the non-negativity-constrained least squares method. By setting non-negativity constraints, non-physical negative solutions are avoided; by introducing smoothness constraints, drastic fluctuations in the inversion results are suppressed; and by combining prior information constraints, the reliability of the solution is improved. An iterative optimization algorithm that dynamically adjusts the constraint strength and weighting factors ensures that the inversion results satisfy both the experimental count rate and maintain physical rationality. This embodiment significantly improves the accuracy and stability of neutron energy spectrum inversion, ensuring the physical interpretability and smoothness of the neutron energy spectrum measurement results.

[0105] The neutron dose equivalent conversion factor is obtained by applying a weighted least squares method. The neutron dose equivalent conversion factor is represented by a linear superposition of the neutron energy response function and the characteristic gamma-ray energy response function, including:

[0106] The neutron dose equivalent conversion factor for each energy level can be queried through the ICRP-74 report. Based on the neutron energy response function and the characteristic gamma-ray energy response function, they are linearly combined according to a preset weight ratio to represent the neutron dose equivalent conversion factor corresponding to each energy point.

[0107] Based on the theory of relative error minimization, and by using the weighted least squares method to fit the neutron dose equivalent conversion factor, the contribution weight coefficient is obtained.

[0108] It should be noted that the neutron dose equivalent rate is calculated using the conversion factor h between the neutron energy spectrum and the neutron ambient dose equivalent. * (E) The integral over the energy range of the neutron radiation field allows for the verification of the neutron energy spectrum once the neutron dose equivalent rate is calculated. This is achieved by using the neutron dose equivalent conversion factor h. * (E) is represented by m energy response functions R. j The linear combination of (E) is specifically calculated as follows:

[0109]

[0110] Among them, h * (E) is the neutron dose equivalent conversion factor; k j The weighting coefficients for the j-th signal to be solved are R. j (E) is the response function of the j-th signal to the neutron energy E; m is the total number of signal channels.

[0111] The formula for calculating the weighted objective function is:

[0112] Q(K)=e T We; (4)

[0113] e = H - KR; (5)

[0114] Where Q(K) is the weighted objective function, e is the error vector, W is the weight matrix, which is the diagonal matrix of the reciprocal of the square of H, H is the neutron dose equivalent conversion factor vector corresponding to different energies, K is the contribution weight coefficient vector to be solved, and R is the energy response matrix.

[0115] The gradient calculation formula for the weighted objective function with respect to the contribution weight coefficient is as follows:

[0116]

[0117] in, Let K be the gradient of the weighted objective function with respect to K.

[0118] The contribution weight coefficient K WLS The formula for calculation is:

[0119] K WLS =(R T WR) -1 R T WH; (7)

[0120] Specifically, this embodiment establishes a composite response function for each energy point by linearly combining the neutron energy response function and the characteristic gamma-ray energy response function. The weighted least squares method is used to optimize and fit the neutron dose equivalent conversion factor to obtain the optimal contribution weight coefficients of the neutron signal and the characteristic gamma-ray signal. This achieves adaptive optimization of the weights of the two signals and improves the accuracy of dose equivalent rate calculation.

[0121] The process involves calculating a first neutron dose equivalent rate based on the contribution weighting coefficient, the neutron count rate, and the characteristic gamma-ray count rate; calculating a second neutron dose equivalent rate based on the neutron energy spectrum and the neutron dose equivalent conversion factor; comparing and verifying the first and second neutron dose equivalent rates; and outputting the neutron energy spectrum as the final measurement result when the comparison and verification pass.

[0122] The contribution weighting coefficient is multiplied by the neutron count rate to obtain the neutron signal contribution, the contribution weighting coefficient is multiplied by the characteristic gamma ray count rate to obtain the characteristic gamma ray signal contribution, and the neutron signal contribution and the characteristic gamma ray signal contribution are added to obtain the first neutron dose equivalent rate.

[0123] Calculate the relative deviation between the first neutron dose equivalent rate and the second neutron dose equivalent rate, and determine whether the relative deviation is within a preset threshold range. If the relative deviation is within the preset threshold range, the measurement result is determined to be valid.

[0124] Based on equation (3), the corresponding first neutron dose equivalent rate can be expressed as multiple count rates M j The linear combination, specifically calculated as follows:

[0125]

[0126] in, M represents the first neutron dose equivalent rate. j Let be the measured count rate of the j-th signal.

[0127] k j Using the optimal contribution weight coefficient K WLS The specific calculation formula is shown in formula (7).

[0128] The formula for calculating the second neutron dose equivalent rate is:

[0129]

[0130] in, E represents the second neutron dose equivalent rate. max E is the maximum value of the preset energy range. min This is the minimum value within the preset energy range; For continuous neutron flux rate densities of each energy group, in equation (9), represents the neutron energy spectrum; h * (E) is the neutron dose equivalent conversion factor.

[0131] Specifically, this embodiment calculates the neutron signal contribution and the characteristic gamma-ray signal contribution by multiplying the contribution weight coefficient by the measured count rate, and then adds them together to obtain the first neutron dose equivalent rate. A dual verification mechanism is achieved by calculating the relative deviation between the first neutron dose equivalent rate and the second neutron dose equivalent rate obtained based on the neutron energy spectrum. This embodiment judges the validity of the measurement results by setting a preset threshold range, effectively identifying and eliminating abnormal neutron energy spectrum measurement data, thus improving the reliability of the neutron energy spectrum measurement results.

[0132] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A neutron energy spectrum measurement device based on characteristic γ energy response, characterized in that, The device is a spherical detection structure, including a scintillator detector, an inner layer of polyethylene, a middle layer of boron-containing polyethylene, and an outer layer of polyethylene. The scintillator detector is located at the center of the neutron energy spectrum measuring device and is used to detect thermal neutrons and gamma rays.

2. A neutron energy spectrum measurement method based on characteristic gamma energy response, implemented based on the neutron energy spectrum measurement device based on characteristic gamma energy response as described in claim 1, characterized in that, Includes the following steps: A lithium-6 scintillator detector was used to measure the neutron field under test. Neutrons and gamma rays were distinguished by the difference in pulse shape and amplitude, and the neutron count rate and characteristic gamma ray count rate were obtained. The neutron energy response function and characteristic gamma-ray energy response function for different monoenergetic neutrons within a preset energy range were obtained by Monte Carlo simulation calculation. Based on the principle of integral equations, continuous energy is discretized into multiple energy groups. Using the neutron energy response function and the characteristic gamma-ray energy response function, a system of linear equations is established with the neutron flux density of each energy group as unknowns and the neutron count rate and energy response as knowns. The linear equations are solved iteratively using the nonnegative constraint least squares method to obtain the neutron energy spectrum. The nonnegative constraint least squares method sets nonnegativity constraints, smoothness constraints, and prior information constraints. The neutron dose equivalent conversion factor is obtained by weighted least squares method. The neutron dose equivalent conversion factor is represented by the linear superposition of the neutron energy response function and the characteristic gamma-ray energy response function. The first neutron dose equivalent rate is calculated based on the contribution weight coefficient, the neutron count rate, and the characteristic gamma ray count rate. The second neutron dose equivalent rate is calculated based on the neutron energy spectrum and the neutron dose equivalent conversion factor. The first neutron dose equivalent rate and the second neutron dose equivalent rate are compared and verified. When the comparison and verification pass, the neutron energy spectrum is output as the final measurement result.

3. The neutron energy spectrum measurement method based on characteristic γ energy response as described in claim 2, characterized in that, The process of obtaining the neutron energy response function and characteristic gamma-ray energy response function for different monoenergetic neutron incidents within a preset energy range through Monte Carlo simulation calculations includes: By establishing a simulation model of the neutron energy spectrum detection device, the Monte Carlo method is used to simulate the energy response of the scintillator detector to neutrons and the energy response to characteristic gamma rays under different monoenergetic neutron incident spherical neutron energy spectrum detection device conditions, so as to obtain the neutron energy response function and the characteristic gamma ray energy response function.

4. The neutron energy spectrum measurement method based on characteristic γ energy response as described in claim 3, characterized in that, The process of constructing the characteristic gamma-ray energy response function includes: The Monte Carlo method was used to simulate the transport and deposition process of characteristic gamma rays in a scintillator detector. The gamma energy spectrum of the scintillator detector was recorded, characteristic gamma energy peaks were identified, the peak areas of different characteristic energy peaks were counted, the corresponding count rates were calculated, and the characteristic gamma energy response was obtained.

5. The neutron energy spectrum measurement method based on characteristic γ energy response as described in claim 2, characterized in that, The neutron dose equivalent conversion factor is obtained by weighted least squares method, and the contribution weight coefficient is represented by the linear superposition of the neutron energy response function and the characteristic gamma-ray energy response function, including: By querying the ICRP-74 report, the neutron dose equivalent conversion factor corresponding to different neutron energies is obtained. Based on the neutron energy response function and the characteristic gamma-ray energy response function, they are linearly combined according to a preset weight ratio to represent the neutron dose equivalent conversion factor corresponding to each energy point. Based on the theory of relative error minimization, the weighted least squares method is used to fit the neutron dose equivalent conversion factor to obtain the contribution weight coefficient.

6. The neutron energy spectrum measurement method based on characteristic γ energy response as described in claim 2, characterized in that, The non-negativity-constrained least squares method is used to iteratively solve the linear equation system to obtain the neutron energy spectrum. The non-negativity-constrained least squares method includes non-negativity constraints, smoothness constraints, and prior information constraints, including: Based on the linear equations, the neutron flux rate density of each energy group is solved using the non-negative constraint least squares method. During the solution process, non-negative constraints and smoothness constraints are introduced to suppress fluctuations and negative values ​​in the inversion results. The constraints are combined with the observation data to form a weighted objective function, and the weighted objective function is iteratively optimized to obtain the optimal neutron energy spectrum distribution.

7. The neutron energy spectrum measurement method based on characteristic γ energy response as described in claim 6, characterized in that, The solution process of the non-negativity constrained least squares method includes: The lower bound of the neutron flux rate density for each energy group is set to zero, and a constraint matrix including nonnegativity constraints is constructed. Smoothness constraints are constructed by introducing a difference quadratic form term between the neutron flux rate densities of each energy group into the weighted objective function; Based on prior information, weighting coefficients are set for the neutron flux rate density of some energy groups to construct prior information constraints. Using an iterative optimization algorithm, the constraint strength and weight factors are dynamically adjusted in each iteration until the objective function converges to the optimum.

8. The neutron energy spectrum measurement method based on characteristic γ energy response as described in claim 2, characterized in that, The method employs a lithium-6 scintillator detector to measure the neutron field under test, distinguishing neutrons and gamma rays by differences in pulse shape and amplitude, and obtaining the neutron count rate and characteristic gamma ray count rate, including: The scintillation pulse signal generated in the neutron field under test is acquired and analyzed to obtain the pulse shape and amplitude characteristics; Neutron signals and characteristic gamma-ray signals are identified and distinguished based on pulse shape and amplitude characteristics, and the neutron count rate and characteristic gamma-ray count rate are calculated separately.

9. The neutron energy spectrum measurement method based on characteristic γ energy response as described in claim 8, characterized in that, The process of identifying and distinguishing neutron signals and characteristic gamma-ray signals based on pulse shape and amplitude characteristics, and separately calculating the neutron count rate and characteristic gamma-ray count rate, includes: Pulse shape discrimination technology is used to identify neutron signals and characteristic gamma-ray signals by setting a discrimination threshold based on the difference in the integral ratio of the fast and slow components of the scintillator output pulse under different particle excitation in the pulse shape and amplitude characteristics. The identified signals are then included in the neutron count rate and gamma response, respectively, and the characteristic gamma rays are identified in the gamma energy spectrum and the characteristic gamma-ray count rate is measured.

10. The neutron energy spectrum measurement method based on characteristic γ energy response as described in claim 2, characterized in that, The method, based on the principle of integral equations, discretizes continuous energy into multiple energy groups. Using the neutron energy response function and the characteristic gamma-ray energy response function, a system of linear equations is established with the neutron fluence rate density of each energy group as unknowns and the neutron count rate and energy response as knowns. This system includes: The continuous energy within the preset energy range is discretized into several energy groups, and a set of unknown neutron flux rate density for each energy group is constructed. The neutron count rate and characteristic gamma-ray count rate are obtained using the neutron energy spectrum detection device. The neutron energy response function and characteristic gamma-ray energy response function are calculated using the Monte Carlo simulation method, and a system of linear equations is established with the neutron count rate, characteristic gamma-ray count rate and energy response as known values.

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