Nuclear species alarm method, system and electronic device

Abstract

The application discloses a kind of nuclide alarm method, system and electronic equipment, it is related to radioactive nuclide identification alarm field, method includes: obtaining the nuclear detection event sequence information of ray detector;According to the time information of current detection ray and last detection ray, the time interval of current detection ray is calculated;According to the time interval of current detection ray, bayesian factor is calculated;According to bayesian factor and the prior probability of full spectrum time interval, posterior probability is calculated;According to posterior probability, statistical decision is made to determine whether there is radioactive nuclide.The application makes statistical decision according to the time correlation statistics of the signal of the ray entering the detector to alarm whether there is radioactive nuclide, without requiring energy, set the value range of time interval on decision function, not directly given a preset time interval parameter, greatly improve the universality of method, can more quickly and accurately determine and alarm whether there is radioactive nuclide.

Description

Technical Field

[0001] This invention relates to the field of radionuclide identification and alarm, and in particular to a radionuclide alarm method, system and electronic equipment. Background Technology

[0002] According to the IAEA's ITDB database, there are currently over 4,000 recorded cases of illicit trafficking, sale, and malicious use of radioactive materials. For the detection of illicit transport of radioactive materials in special scenarios such as airports, ports, and nuclear radiation emergencies, the transit time for personnel and goods is typically only a few seconds at most. Therefore, the required radionuclide alarm algorithms must possess characteristics such as small sample size, fast identification speed, and high identification accuracy.

[0003] For the detection and alarm of illegal transportation of radioactive materials in special scenarios such as airports, ports, and nuclear radiation emergencies, the characteristics of non-static measurement, short detection time, and weak detected signals present new demands on measurement technology:

[0004] 1- The measurable time is short, typically in the sub-second to tens of seconds range;

[0005] 2. High data reliability is required. At a high level of confidence, high alarm efficiency and accuracy are required, while false alarm rate and missed alarm rate should be as low as possible.

[0006] Currently, common radionuclide alarm methods are based on gamma-ray spectral analysis and characteristic peak matching techniques. The algorithms mainly include background subtraction, filtering and smoothing, and peak finding. These methods statistically analyze the characteristic gamma rays emitted by radioactive materials by assuming a Gaussian distribution of the full-energy peak shape and matching peak positions, thus achieving qualitative and quantitative judgment of the radioactive material. However, this method requires collecting a sufficient number of photons to reduce the statistical fluctuations of the characteristic peaks, thus placing certain requirements on detection time and the intensity of radionuclide emission. Furthermore, accurately distinguishing and identifying characteristic gamma rays requires a certain level of energy resolution from the detector. In addition, there are also detectors with low energy resolution, such as those based on plastic scintillators, which measure the particle count rate of the scintillator. However, their identification methods mainly rely on classical statistical theory, resulting in a high detection threshold and poor sensitivity (generally requiring a detection threshold 2-5 times higher than the background count level). Summary of the Invention

[0007] The purpose of this invention is to provide a radionuclide alarm method, system, and electronic device that can more quickly and accurately determine and alarm on the presence of radioactive nuclides.

[0008] To achieve the above objectives, the present invention provides the following solution:

[0009] In a first aspect, this application provides a method for detecting radionuclides, the method comprising:

[0010] Obtain nuclear detection event sequence information from the X-ray detector;

[0011] The time interval of the current detection ray is calculated based on the time information of the current detection ray and the time information of the previous detection ray.

[0012] The Bayes factor is calculated based on the current time interval of the detected rays, the time interval probability density function under the null hypothesis, and the time interval probability density function under the alternative hypothesis; the null hypothesis refers to the assumption that no radioactive nuclide exists; the alternative hypothesis refers to the assumption that a radioactive nuclide exists.

[0013] Calculate the posterior probabilities under the null and alternative hypotheses based on the Bayesian factor and the prior probabilities of the full-spectrum time interval under the null and alternative hypotheses, respectively.

[0014] Statistical decision-making is made based on the comparison between the posterior probability under the null hypothesis and the alarm threshold to determine whether a radionuclide exists.

[0015] Secondly, this application provides a radionuclide alarm system, the system comprising:

[0016] The X-ray energy time information acquisition module is used to acquire the nuclear detection event sequence information of the X-ray detector;

[0017] The time interval calculation module is used to calculate the time interval of the current detection ray based on the time information of the current detection ray and the time information of the previous detection ray.

[0018] The Bayesian factor calculation module is used to calculate the Bayesian factor based on the current time interval of the detected ray, the time interval probability density function under the null hypothesis, and the time interval probability density function under the alternative hypothesis; the null hypothesis refers to the assumption that no radioactive nuclide exists; the alternative hypothesis refers to the assumption that a radioactive nuclide exists.

[0019] The posterior probability calculation module is used to calculate the posterior probability under the null hypothesis and the alternative hypothesis based on the Bayes factor and the prior probability of the full spectrum time interval under the null hypothesis and the alternative hypothesis, respectively.

[0020] The nuclide discrimination module is used to make statistical decisions based on the comparison between the posterior probability under the null hypothesis and the alarm threshold to determine whether a radioactive nuclide exists.

[0021] Thirdly, this application provides an electronic device, including a memory and a processor, wherein the memory is used to store a computer program, and the processor runs the computer program to cause the electronic device to perform a nuclide alarm method as described in any of the above claims.

[0022] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0023] This invention provides a radionuclide alarm method, system, and electronic device. Within the full spectrum of the detector, statistical decisions are made based on the time-related statistics of the X-ray signals entering the detector. Based on the statistical decision results, an alarm can be quickly triggered to indicate the presence or absence of a radionuclide. No energy requirements are necessary. Instead of directly specifying a pre-defined time interval parameter, the decision function sets a range of time interval values, greatly improving the method's versatility. It achieves high detection sensitivity and a low detection limit, enabling faster determination and alarm of the presence of radionuclides. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments 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.

[0025] Figure 1 This is a schematic flowchart of a radionuclide alarm method provided in Embodiment 1 of the present invention;

[0026] Figure 2 The energy spectrum and timing diagram of the background provided in Embodiment 1 of the present invention;

[0027] Figure 3 This is a graph showing the change of the alarm decision function based on the background provided in Embodiment 1 of the present invention;

[0028] Figure 4 Provided for Embodiment 1 of the present invention 137 Cs energy spectrum and time series plot;

[0029] Figure 5 Provided for Embodiment 1 of the present invention 137 A schematic diagram illustrating the changing trend of the alarm decision function of Cs;

[0030] Figure 6 This is a block diagram of a nuclide alarm system provided in Embodiment 2 of the present invention. Detailed Implementation

[0031] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] The purpose of this invention is to provide a radionuclide alarm method, system, and electronic device. Based on a gamma-ray spectrometer measurement system that can detect gamma rays and output gamma-ray energy and time information, combined with the method of this invention, it enables rapid and accurate identification of the presence of radioactive nuclides.

[0033] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0034] Example 1

[0035] When gamma rays are incident on the sensitive volume of the gamma ray detector in the measurement system, the measurement system outputs the energy and time data pair (ε, t) of the ray to the host computer. Based on the nuclide rapid alarm algorithm provided by the present invention, the host computer calculates the decision function and completes statistical inference based on the energy and time data pair (ε, t) of the incident ray, and makes an effective inference on the presence or absence of radioactive nuclides.

[0036] like Figure 1 As shown, this embodiment provides specific steps for a rapid nuclide alarm method based on energy and time data pairs (ε, t):

[0037] S1: Obtain the nuclear detection event sequence information of the radiation detector, that is, obtain the energy-time information of the radiation detected by the detector.

[0038] S2: Calculate the time interval of the current detection ray based on the time information of the current detection ray and the time information of the previous detection ray.

[0039] When the detector detects a ray, it outputs the ray's energy-time information ξ. (0) =(ε (0) ,τ (0) Then, the formula for calculating the time interval Δt is:

[0040] Δt (0) =τ (0) -τ (-1) ;

[0041] Where, τ (0) τ is the measurement time of the current probe ray. (-1) The measurement time of the previous probe ray (τ when the system inputs the first probe ray).(-1) The value is 0).

[0042] S3: Calculate the Bayesian factor based on the current time interval of the detected rays, the time interval probability density function under the null hypothesis, and the time interval probability density function under the alternative hypothesis; the null hypothesis refers to the assumption that no radioactive nuclide exists; the alternative hypothesis refers to the assumption that a radioactive nuclide exists.

[0043] The expression for calculating the Bayesian factor is as follows:

[0044]

[0045] In the formula, It is based on the current detection ray time interval Δt (0) Calculated Bayesian factor; g0(Δt) (0) |τ0) and g1(Δt) (0) |τ1) represents the time interval probability density function under the null hypothesis M0 and the alternative hypothesis M1, respectively.

[0046]

[0047] Where τ0 and τ1 are the mathematical expectations of the time interval under the null hypothesis and the alternative hypothesis, respectively; and τ bkg These are the background count rate and the expected value of the time interval, respectively, and they are reciprocals of each other; τ min It is the lower limit of detection sensitivity η under the original assumption. min Relevant parameters, lower limit of detection sensitivity η min Defined as the minimum signal-to-noise ratio η required to make an effective judgment and meet certain detection performance under active conditions, the signal-to-noise ratio is the ratio of the net count rate to the background count rate. h1(τ1) is the probability density function under the alternative hypothesis. Where C is related to (τ) min ,τ bkg The normalization coefficients related to this.

[0048] The construction of the probability density function for the time interval between the null and alternative hypotheses is one of the key points that needs to be protected in this invention. In this embodiment, regarding the hypothesis of the presence of a radionuclide, the presence of the radionuclide is determined based on the difference between the time interval of the full spectrum following an exponential distribution and the time interval of the background. The probability density of the time interval in this invention is not limited to the exponential distribution in the example of this invention, and the specific probability density distribution can be determined according to the actual use scenario.

[0049] S4: Calculate the posterior probabilities under the null and alternative hypotheses based on the Bayesian factor and the prior probabilities of the full-spectrum time interval under the null and alternative hypotheses, respectively.

[0050] The expression for the prior probability density function θ(τ) of the full-spectrum time interval is:

[0051]

[0052] Here, θ0 and θ1 are the prior probabilities of the full-spectrum time interval under the null and alternative hypotheses, respectively, with θ0 + θ1 = 1. The "τ" without any subscript represents a parameter without specific meaning, that is, the parameter of the exponential distribution of time intervals in a more common sense (without any restrictions).

[0053] The construction of the prior probability of the time-related statistics in this invention is one of the key points that needs to be protected in this case. In this case, the prior probability density function can be either an information-free prior probability density function or a conjugate prior probability density function, and is not limited to the information-free prior probability density function mentioned above in this invention; at the same time, the initial value of the prior probability can be determined according to the actual situation. In addition, the selection of the range of values ​​for the time interval in the prior probability is related to the background conditions and the detector type, and is set according to the specific circumstances.

[0054] The decision function (i.e., posterior probability) can be constructed in two ways: one is to obtain the decision function based on the prior probability and the sample probability density function; the other is to first calculate the Bayes factor based on the sample probability density function, and then jointly construct the decision function based on the aforementioned prior probability and Bayes factor. The Bayes factor, as an intermediate parameter, may not participate in the actual construction process. In this invention, the calculation of the decision function is divided into two steps: 1- calculate the Bayes factor, 2- calculate the decision function. The phrase "may not participate in the construction process" means that the above two steps can be combined into one step, which is the first construction path described above.

[0055] Whether calculated based on prior probabilities and Bayesian factors, or directly based on prior information and sample information, the construction of the decision function is one of the key points that this invention aims to protect. The first construction method, directly constructing the decision function based on prior information and sample information, has the following formula:

[0056]

[0057] The second construction method: The expression for the posterior probability obtained by jointly constructing the prior probability and the Bayes factor is as follows:

[0058]

[0059] in, and These are the posterior probabilities calculated based on the current time interval of the detected rays under the null and alternative hypotheses, respectively, which are the decision functions for making the decision.

[0060] S5: Update the prior probabilities of the full-spectrum time interval under the null and alternative hypotheses based on the posterior probabilities under the null and alternative hypotheses.

[0061] S6: Make a statistical decision based on the comparison between the posterior probability under the null hypothesis and the alarm threshold to determine whether a radionuclide exists.

[0062] Step S6 specifically includes:

[0063] (1) The posterior probability under the null hypothesis Greater than the alarm upper limit threshold If the decision is made, then the radioactive nuclide is deemed to be absent.

[0064] (2) The posterior probability under the null hypothesis Less than the alarm lower threshold If the system detects a radioactive nuclide, it will determine that the radioactive nuclide is present and issue an alarm.

[0065] (3) The posterior probability under the null hypothesis Greater than the alarm lower limit threshold And less than the alarm upper limit threshold If the next ray is detected, the detector continues to detect the next ray. When the next ray is detected, the detector obtains the energy-time information of the ray currently being detected by the ray detector by obtaining the nuclear detection event sequence information through step S1, and returns to the step "Calculate the time interval of the current ray based on the time information of the current ray and the time information of the previous ray".

[0066] The threshold is determined by the probability of committing a Type I error α (i.e., rejecting M0 when the M0 hypothesis is true, also known as the false alarm rate) and the probability of committing a Type II error β (i.e., accepting M0 when the M1 hypothesis is true, also known as the false alarm rate).

[0067]

[0068] The method for constructing a threshold judgment during statistical inference of time-related statistics in this invention is one of the key points that needs to be protected in this case. In conventional Bayesian methods, the relative magnitude of the posterior probabilities of the null and alternative hypotheses (with upper and lower thresholds both at 0.5) is generally chosen. When making statistical decisions, if the posterior probabilities of the null and alternative hypotheses are close, there is a high probability of making an incorrect decision. In this case, the decision functions for time intervals are all set with different upper and lower thresholds. Furthermore, the introduction of decision thresholds for the two types of decisions (supporting the null hypothesis and supporting the alternative hypothesis) is a key point of protection in this invention. The specific value of the threshold can be determined based on the actual application scenario.

[0069] In this embodiment, instead of directly assigning a fixed value to the time interval parameter, a range of values ​​is set based on the prior probability, greatly improving the universality of the method. Furthermore, the presence or absence of a nuclide can be determined simply by measuring the time interval, providing a faster and more effective alarm for the presence of radioactive nuclides compared to the energy spectrum analysis-characteristic peak matching method, thus offering higher determination efficiency. The nuclide alarm method of this invention can be used with various types of detectors, including but not limited to scintillator detectors, semiconductor detectors, and detectors with energy resolution capabilities, as well as detectors without energy resolution capabilities such as plastic scintillators and Geiger tubes.

[0070] The following sections will use the background and... 137 The method provided in this embodiment is illustrated using Cs as an example.

[0071] A 1.5-inch lanthanum bromide detection system was used to collect background data and calibrate the background count rate of the entire spectrum. and the background count rate within 46 ROI regions

[0072] Since the prior probability is unbiased, the initial value of the prior probability is set to (0.5, 0.5). The initial values ​​of the prior probabilities of the null and alternative hypotheses can be determined according to the actual situation, including but not limited to the parameter (0.5, 0.5) in the example of this invention; the lower limit of the detection sensitivity of this method is set to 10%, and τ min =85%·τ bkg ; Set α = β = 0.2, the upper and lower thresholds for decision-making are:

[0073] (I) Background alarm method procedure:

[0074] The detector detected the first ray, with time and energy information of (0.045657025, 44) / (time / second, energy / channel address).

[0075] The time interval Δt is calculated from steps S1 and S2. (0) =0.0457

[0076] The Bayes factor is calculated in step S3:

[0077] The decision function is calculated in step S4:

[0078] The prior probability is updated in step S5: θ0 = 0.5367.

[0079] The decision is made in step S6: because the decision function has Therefore, no decision was made, and we continued to wait for the arrival of the next ray.

[0080] A total of 10 were measured and identified in the examples of the background. 4 One X-ray particle, taking approximately 166 seconds, the energy spectrum and timing diagram are as follows. Figure 2 As shown in the figure, the algorithm made a valid identification (decided as background) at 6.62 seconds (389 ray samples). The change of the decision function over time is shown in the figure. Figure 3 As shown, the experiment was repeated 100 times, with a false alarm rate of less than 13%, which was better than expected (expected to be 20%).

[0081] (two) 137 Cs(9.22*10 3 B q Alarm procedure for (source-detector front face distance 35cm) (equivalent dose rate approximately 5.52nGy / h):

[0082] The detector detected the first ray, with time and energy information of (0.030928838, 161) / (time / second, energy / channel address).

[0083] The time interval Δt is calculated from steps S1 and S2. (0) =0.0309.

[0084] The Bayes factor is calculated in step S3:

[0085] The decision function is calculated in step S4:

[0086] The prior probability is updated in step S5: θ0 = 0.5188.

[0087] The decision is made in step S6: because the decision function has Therefore, no decision was made, and we continued to wait for the arrival of the next ray.

[0088] After the arrival of the next ray, steps S1-S4 are repeated based on the time and energy information of the ray to calculate the decision function; then step S5 is repeated based on the decision function to make a decision on whether the radionuclide exists.

[0089] 137 A total of 10 were measured and identified in the Cs instance. 4 The total number of X-ray particles was 154 seconds, with a full-spectrum count rate of 64.14 s. -1 Energy spectrum and time series diagram as follows Figure 4 As shown, the nuclide alarm algorithm made a valid identification (determined the presence of a radioactive nuclide) in 4.20 seconds (276 radiation samples). The change of the decision function over time is shown in the graph. Figure 5 As shown. The experiment was repeated 100 times, and the alarm rate was higher than 97%, which was better than expected (expected to be 80%).

[0090] The two examples show that even with an extremely low signal-to-noise ratio (1 / 85% ≈ 1.18), the recognition speed can reach 4.2 seconds and the alarm accuracy rate is higher than 97%. This demonstrates that in practical applications, it can achieve fast and accurate recognition efficiency and results.

[0091] Example 2

[0092] like Figure 6 As shown, this embodiment provides a radionuclide alarm system, the system comprising:

[0093] The X-ray energy-time information acquisition module 100 is used to acquire the energy-time information of the X-ray currently being detected by the X-ray detector.

[0094] The time interval calculation module 200 is used to calculate the time interval of the current detection ray based on the time information of the current detection ray and the time information of the previous detection ray.

[0095] The Bayesian factor calculation module 300 is used to calculate the Bayesian factor based on the current time interval of the detected ray, the time interval probability density function under the null hypothesis, and the time interval probability density function under the alternative hypothesis; the null hypothesis refers to the assumption that no radioactive nuclide exists; the alternative hypothesis refers to the assumption that a radioactive nuclide exists.

[0096] The Bayesian factor is calculated as follows:

[0097]

[0098] in, τ1∈(τ min ,τ bkg );

[0099] In the formula, It is based on the current detection ray time interval Δt (0) Calculated Bayesian factor; g0(Δt) (0) |τ0) and g1(Δt) (0) |τ1) represents the probability density function of the time interval under the null and alternative hypotheses, respectively; τ0 and τ1 represent the mathematical expectations of the time interval under the null and alternative hypotheses, respectively; h1(τ1) is the probability density function under the alternative hypothesis. and τ bkg These are the base count rate and the expected value of the time interval, respectively; τ min It is the lower limit of detection sensitivity η under the original assumption. min The relevant parameters.

[0100] The posterior probability calculation module 400 is used to calculate the posterior probability under the null hypothesis and the alternative hypothesis based on the Bayes factor and the prior probability of the full-spectrum time interval under the null hypothesis and the alternative hypothesis, respectively.

[0101] The expression for the posterior probability is:

[0102]

[0103] in, and θ0 and θ1 are the posterior probabilities calculated based on the time interval of the current detected ray under the null and alternative hypotheses, respectively; θ0 and θ1 are the prior probabilities of the full-spectrum time interval under the null and alternative hypotheses, respectively.

[0104] The nuclide discrimination module 500 is used to make statistical decisions based on the comparison between the posterior probability under the null hypothesis and the alarm threshold to determine whether a radioactive nuclide exists.

[0105] Specifically, the nuclide discrimination module includes:

[0106] The first discrimination unit is used to output that there are no radioactive nuclides in the current detection ray when the posterior probability under the original assumption is greater than the alarm upper limit threshold.

[0107] The second discrimination unit is used to output that there is a radioactive nuclide in the current detection ray and to issue an alarm when the posterior probability under the original assumption is less than the lower alarm threshold.

[0108] The third discrimination unit is used to make no decision and continue to detect the next ray when the posterior probability under the original assumption is greater than the lower alarm threshold and less than the upper alarm threshold. When the next ray is detected, the energy-time information of the ray detector is obtained by the ray energy-time information acquisition module 100, and the unit returns to the execution of the step "calculate the time interval of the current ray based on the time information of the current ray and the time information of the previous ray" in the time interval calculation module 200.

[0109] The update unit is used to update the prior probability of the full-spectrum time interval under the null hypothesis and the alternative hypothesis based on the posterior probability under the null hypothesis and the alternative hypothesis after the first, second or third discrimination unit makes a decision.

[0110] Example 3

[0111] This embodiment provides an electronic device, including a memory and a processor. The memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to perform a nuclide alarm method according to Embodiment 1.

[0112] Alternatively, the aforementioned electronic device may be a server.

[0113] In addition, embodiments of the present invention also provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements a nuclide alarm method of embodiment 1.

[0114] Embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0115] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1A device that provides the functions specified in one or more boxes.

[0116] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0117] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0118] Each embodiment in this specification focuses on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be found in the method section.

[0119] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for detecting radionuclides, characterized in that, The method includes: Obtain nuclear detection event sequence information from the X-ray detector; The time interval of the current detection ray is calculated based on the time information of the current detection ray and the time information of the previous detection ray. The Bayes factor is calculated based on the current time interval of the detected rays, the time interval probability density function under the null hypothesis, and the time interval probability density function under the alternative hypothesis; the null hypothesis refers to the assumption that no radioactive nuclide exists; the alternative hypothesis refers to the assumption that a radioactive nuclide exists. Calculate the posterior probabilities under the null and alternative hypotheses based on the Bayesian factor and the prior probabilities of the full-spectrum time interval under the null and alternative hypotheses, respectively. Statistical decision-making is made based on the comparison between the posterior probability under the null hypothesis and the alarm threshold to determine whether a radionuclide exists. The Bayesian factor is calculated as follows: ； in, ; ; In the formula, It is based on the current time interval of the detected rays. Calculated Bayesian factor; and These are the time interval probability density functions under the null hypothesis and the alternative hypothesis, respectively. and These are the mathematical expectations of the time interval under the null and alternative hypotheses, respectively. For the probability density function under the alternative assumptions, ; and These are the background count rate and the expected value of the time interval, respectively. This is related to determining the lower limit of detection sensitivity under the null hypothesis. η min Relevant parameters; The expression for the posterior probability is: in, and These are the posterior probabilities calculated based on the time interval of the current detected rays under the null hypothesis and the alternative hypothesis, respectively. and These are the prior probabilities of the full-spectrum time interval under the null hypothesis and the alternative hypothesis, respectively.

2. The radionuclide alarm method according to claim 1, characterized in that, Statistical decision-making is performed based on the comparison between the posterior probability under the null hypothesis and the alarm threshold to determine the presence of radioactive nuclides. Specifically, this includes: When the posterior probability under the null hypothesis is greater than the upper alarm threshold, the decision is made that no radioactive nuclide exists. When the posterior probability under the null hypothesis is less than the alarm lower limit threshold, the decision is made to determine that a radioactive nuclide is present, and an alarm is issued. If the posterior probability under the original assumption is greater than the lower alarm threshold and less than the upper alarm threshold, no decision is made and the next ray is detected. When the next ray is detected, the energy-time information of the ray currently being detected by the ray detector is obtained, and the process returns to the step "Calculate the time interval of the current ray based on the time information of the current ray and the time information of the previous ray". After the decision-making process is completed, the prior probabilities of the full-spectrum time interval under the null and alternative hypotheses are updated based on the posterior probabilities under the null and alternative hypotheses.

3. A radionuclide alarm system, characterized in that, The system includes: The X-ray energy time information acquisition module is used to acquire the nuclear detection event sequence information of the X-ray detector; The time interval calculation module is used to calculate the time interval of the current detection ray based on the time information of the current detection ray and the time information of the previous detection ray. The Bayesian factor calculation module is used to calculate the Bayesian factor based on the current time interval of the detected ray, the time interval probability density function under the null hypothesis, and the time interval probability density function under the alternative hypothesis; the null hypothesis refers to the assumption that no radioactive nuclide exists; the alternative hypothesis refers to the assumption that a radioactive nuclide exists. The Bayesian factor is calculated as follows: ； in, ; ; In the formula, It is based on the current time interval of the detected rays. Calculated Bayesian factor; and These are the time interval probability density functions under the null hypothesis and the alternative hypothesis, respectively. and These are the mathematical expectations of the time interval under the null and alternative hypotheses, respectively. For the probability density function under the alternative assumptions, ; and These are the background count rate and the expected value of the time interval, respectively. This is related to determining the lower limit of detection sensitivity under the null hypothesis. η min Relevant parameters; The posterior probability calculation module is used to calculate the posterior probability under the null hypothesis and the alternative hypothesis based on the Bayes factor and the prior probability of the full spectrum time interval under the null hypothesis and the alternative hypothesis, respectively. The expression for the posterior probability is: ； in, and These are the posterior probabilities calculated based on the time interval of the current detected rays under the null hypothesis and the alternative hypothesis, respectively. and These are the prior probabilities of the full-spectrum time interval under the null hypothesis and the alternative hypothesis, respectively. The nuclide discrimination module is used to make statistical decisions based on the comparison between the posterior probability under the null hypothesis and the alarm threshold to determine whether a radioactive nuclide exists.

4. A radionuclide alarm system according to claim 3, characterized in that, The nuclide discrimination module specifically includes: The first discrimination unit is used to output the result that no radioactive nuclide exists when the posterior probability under the null hypothesis is greater than the alarm upper limit threshold. The second discrimination unit is used to output the presence of radioactive nuclides and issue an alarm when the posterior probability under the null hypothesis is less than the alarm lower limit threshold. The third discrimination unit is used to make no decision and continue to detect the next ray when the posterior probability under the original assumption is greater than the lower alarm threshold and less than the upper alarm threshold. When the next ray is detected, the energy-time information of the ray detector is obtained by the ray energy-time information acquisition module, and the unit returns to the execution of the step "calculate the time interval of the current ray based on the time information of the current ray and the time information of the previous ray" in the time interval calculation module. The update unit is used to update the prior probability of the full-spectrum time interval under the null hypothesis and the alternative hypothesis based on the posterior probability under the null hypothesis and the alternative hypothesis after the first, second or third discrimination unit makes a decision.

5. An electronic device, comprising a memory and a processor, characterized in that, The memory is used to store computer programs, and the processor runs the computer programs to cause the electronic device to perform a nuclide alarm method according to any one of claims 1 to 2.

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