Radiation detection method and device

Abstract

The invention discloses a radiation detection method and device, and belongs to the technical field of nuclear radiation measurement. According to the radiation detection method, pulse signals output by a plurality of photomultipliers can be converted into digital signals; multiple paths of first signals can be processed to extract pulse amplitude information, first integral processing is performed on the pulse amplitude information to determine a first integral value, and second integral processing is performed on the pulse amplitude information to obtain a second integral value; generating a two-dimensional distribution diagram according to the first integral value, the second integral value and the pulse amplitude information; and classifying the data points in the two-dimensional distribution diagram based on the identification curve so as to distinguish at least two particle types. According to the invention, the charge integration method is adopted to discriminate multiple particles, the waveform is subjected to two kinds of integration processing to obtain the first integration value and the second integration value, the peak value of the waveform is extracted, the integration mode is adopted to extract the characteristics of the whole waveform, the waveform acquisition error is reduced, and the particle separation precision is improved.

Description

Technical Field

[0001] This application relates to the field of nuclear radiation measurement technology, and in particular to radiation detection methods and devices. Background Technology

[0002] With the development of nuclear radiation detection technology, radiation detection methods have been widely used in environmental monitoring, nuclear safety, and medical diagnosis. In the field of radiation detection, the differentiation between alpha and beta particles is a key technology, crucial for accurately assessing the nature and intensity of radiation sources. A technical bottleneck in traditional single-parameter detection is the cross-interference between alpha and beta particle signals. Because the high ionization density generated by alpha particles in scintillation fluid induces slow-decaying fluorescence, while beta particles trigger fast-decaying components, traditional integration methods are prone to spectral overlap.

[0003] Currently, liquid scintillation counting is one of the commonly used methods in the field of radiation detection. Liquid scintillation spectrometers are used to measure the activity of radionuclides emitting alpha (α) and have confirmed that α- and β-emitting radionuclides produce different pulse shapes at the anode of a photomultiplier tube (PMT), allowing for their differentiation. Pulse shape discrimination techniques are quite mature and widely used to exclude gamma background in neutron spectra and to isolate fission events during liquid scintillation counting. These counts are commonly referred to as pulse shape discrimination (PSD), pulse shape analysis (PSA), or pulse decay analysis (PDA) in the literature of different equipment manufacturers. Because pulse shape discrimination techniques can be divided into many types, they have different names, but all techniques are based on electronic circuits that measure pulse decay time.

[0004] Application publication number CN117647831A discloses an αβ particle counting method and system based on a liquid scintillation counter. The invention is characterized by constructing three-dimensional separation spectra of standard α-nuclides, standard β-nuclides, and α / β mixed samples, respectively. The three-dimensional separation spectra of the α / β mixed sample are compared with those of the standard α-nuclides and standard β-nuclides to obtain the number of α particles and β particles in the mixed sample. Specifically, the construction process of the three-dimensional separation spectra includes: inputting the sample into a liquid scintillation counter and sampling each output pulse signal; calculating the maximum amplitude of each pulse signal based on the amplitude corresponding to each sampling point using a pulse amplitude analysis algorithm; calculating the slow signal energy ratio of each pulse signal based on the maximum amplitude and the amplitude at time t; and constructing a three-dimensional separation map of the sample based on the maximum amplitude, slow signal energy ratio, and particle count of each pulse signal.

[0005] However, the main drawbacks of the above-mentioned αβ particle counting method and system based on liquid scintillation counter are as follows: the calculation uses two points (the point of maximum amplitude and the point of time t) in the signal waveform as the sole basis for calculating the proportion of the slow component of the waveform. This will cause the calculation results to fluctuate greatly due to factors such as pulse amplitude, amplitude selection method, and signal noise, thus affecting the accuracy of αβ separation; the method uses a three-dimensional graph as the basis for separation, which will increase the computational burden on the computer and the complexity of separation.

[0006] In summary, existing liquid scintillation counters (LSCs) distinguish between α and β particles through energy resolution. However, due to the partial overlap in their energy ranges and the fact that the light output of α particles is only 1 / 10 that of β particles, traditional two-dimensional energy spectra (such as energy-count spectra) are insufficient to effectively separate α / β signals in mixed samples. Furthermore, traditional methods rely on analog circuits for pulse zero-crossing analysis, but the overlap of multiple pulse signals within a short period can lead to counting errors, and analog circuit debugging is complex and costly.

[0007] Therefore, there is an urgent need for a radiation detection method and device that can improve the accuracy of α / β particle separation and reduce computational complexity. Summary of the Invention

[0008] To address the technical bottleneck of cross-interference between α and β particle signals in traditional liquid scintillation counters, this application provides a radiation detection method and apparatus designed to improve the separation accuracy of α and β signals and reduce the computational burden on computers.

[0009] This application provides a radiation detection method, including:

[0010] The pulse signals output from at least two photomultiplier tubes are converted into digital signals, wherein the digital signals include at least two first signals;

[0011] At least two of the first signals are processed to extract pulse amplitude information, the pulse amplitude information is subjected to a first integration process to determine a first integration value, and the pulse amplitude information is subjected to a second integration process to obtain a second integration value.

[0012] A two-dimensional distribution map is generated based on the first integral value, the second integral value, and the pulse amplitude information;

[0013] The data points in the two-dimensional distribution map are classified based on the discrimination curve to distinguish at least two particle types.

[0014] Optionally, the conversion of the pulse signals output by at least two photomultiplier tubes into digital signals includes:

[0015] The pulse signals output from at least two of the photomultiplier tubes are respectively subjected to voltage reduction processing to obtain low-voltage signals;

[0016] The low-voltage signal is amplified to obtain a voltage signal;

[0017] The voltage signal is converted into the digital signal.

[0018] Optionally, the step of processing at least two of the first signals to extract pulse amplitude information, performing a first integration process on the pulse amplitude information to determine a first integral value, and performing a second integration process on the pulse amplitude information to obtain a second integral value includes:

[0019] Filter at least two of the first signals respectively;

[0020] Identify whether all the first signals after filtering meet preset conditions;

[0021] All the filtered first signals that meet the preset conditions are summed to extract pulse amplitude information;

[0022] The pulse amplitude information is subjected to a first integral processing to determine a first integral value, wherein the first integral processing interval is the pulse length interval between the start time of a preset period and the pulse peak time.

[0023] The pulse amplitude information is subjected to a second integral processing to obtain a second integral value, wherein the second integral processing interval is the pulse length interval corresponding to a preset period duration.

[0024] Optionally, the preset condition is that the pulse arrival times of all the first signals are consistent.

[0025] Optionally, generating a two-dimensional distribution map based on the first integral value, the second integral value, and the pulse amplitude information includes:

[0026] Calculate the integration ratio based on the first integral value and the second integral value;

[0027] The two-dimensional distribution map is generated based on the pulse amplitude information and the integral ratio.

[0028] Optionally, the step of classifying data points in the two-dimensional distribution map based on the discrimination curve to distinguish at least two particle types further includes: obtaining the discrimination curve;

[0029] The discrimination curve includes:

[0030] Obtain pulse shape discrimination spectra of at least two standard particles respectively;

[0031] The pulse shape discrimination spectra of all the standard particles are merged to generate a fitting graph;

[0032] In the fitting graph, a separation curve is fitted based on the crosstalk ratio between each standard particle, and the separation curve is used as the identification curve.

[0033] Optional, also includes:

[0034] The cross-channel ratio of each particle is calculated based on the discrimination curve in the two-dimensional distribution map.

[0035] This application provides a radiation detection device, comprising:

[0036] A conversion unit is used to convert the pulse signals output by at least two photomultiplier tubes into digital signals, wherein the digital signals include at least two first signals;

[0037] The processing unit is configured to process at least two of the first signals to extract pulse amplitude information, perform a first integration process on the pulse amplitude information to determine a first integration value, and perform a second integration process on the pulse amplitude information to obtain a second integration value.

[0038] A generation unit is configured to generate a two-dimensional distribution map based on the first integral value, the second integral value, and the pulse amplitude information;

[0039] A classification unit is used to classify data points in the two-dimensional distribution map based on a discrimination curve to distinguish at least two particle types.

[0040] Optionally, the conversion unit includes:

[0041] A step-down module is used to step down the pulse signals output by at least two of the photomultiplier tubes to obtain low-voltage signals.

[0042] An amplification module is used to amplify the low-voltage signal to obtain a voltage signal;

[0043] A conversion module is used to convert the voltage signal into the digital signal.

[0044] Optionally, the processing unit includes:

[0045] A filtering module is used to filter at least two of the first signals respectively;

[0046] The judgment module is used to identify whether all the first signals after filtering meet preset conditions;

[0047] The processing module is used to sum all the first signals that have been filtered and meet the preset conditions, and extract pulse amplitude information.

[0048] The first integration module is used to perform a first integration process on the pulse amplitude information to determine a first integration value. The first integration processing interval is the pulse length interval between the start time of a preset period and the pulse peak time.

[0049] The second integration module is used to perform a second integration process on the pulse amplitude information to obtain a second integration value. The second integration processing interval is the pulse length interval corresponding to a preset period duration.

[0050] The beneficial effects of the above technical solution are as follows:

[0051] This radiation detection method converts pulse signals output from multiple photomultiplier tubes into digital signals. It processes multiple first signals to extract pulse amplitude information, performs a first integration process on the pulse amplitude information to determine a first integral value, and performs a second integration process on the pulse amplitude information to obtain a second integral value. A two-dimensional distribution map is generated based on the first integral value, the second integral value, and the pulse amplitude information. Data points in the two-dimensional distribution map are classified based on a discrimination curve to distinguish at least two particle types. This application uses a charge integration method to distinguish multiple particles, performing two integration processes on the waveform to obtain the first and second integral values, extracting the peak value of the waveform, and using an integration method to extract the features of the entire waveform. This reduces waveform acquisition errors and improves particle separation accuracy, preventing large deviations in results due to sudden fluctuations at a single point, effectively averaging errors across multiple pulse points. By using multi-point piecewise linear fitting for particle separation and displaying the distribution map, the computational burden on the computer and the complexity of the separation are reduced. Attached Figure Description

[0052] One or more embodiments are illustrated by way of example with reference numerals in the accompanying drawings. These illustrations do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the figures in the drawings are not to be limited by scale.

[0053] Figure 1 This is a flowchart of one embodiment of the radiation detection method described in Example 1;

[0054] Figure 2 This is a schematic diagram of the pulse discrimination principle.

[0055] Figure 3 This is a schematic diagram of one embodiment of the two-dimensional distribution map described in this application;

[0056] Figure 4 This is a flowchart of one embodiment of the radiation detection method described in Example 2;

[0057] Figure 5This is a block diagram of one embodiment of the radiation detection device described in this application;

[0058] Figure 6 This is a block diagram of one embodiment of the conversion unit described in this application;

[0059] Figure 7 This is a block diagram of one embodiment of the processing unit described in this application. Detailed Implementation

[0060] The advantages of this application are further illustrated below with reference to the accompanying drawings and specific embodiments.

[0061] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0062] The terminology used in this disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The singular forms “a,” “the,” and “the” as used in this disclosure and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any and all possible combinations of one or more of the associated listed items.

[0063] It should be understood that although the terms first, second, third, etc., may be used in this disclosure to describe various information, such information should not be limited to these terms. These terms are used only to distinguish information of the same type from one another. For example, without departing from the scope of this disclosure, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."

[0064] In the description of this application, it should be understood that the numerical labels before the steps do not indicate the order of the steps, but are only used to facilitate the description of this application and to distinguish each step, and therefore should not be construed as a limitation of this application.

[0065] The radiation detection method of this application is applicable to fields such as nuclear radiation monitoring, medical imaging, and scientific research. The method converts pulse signals output from multiple photomultiplier tubes into digital signals; it processes multiple first signals to extract pulse amplitude information, performs a first integration process on the pulse amplitude information to determine a first integral value, and performs a second integration process on the pulse amplitude information to obtain a second integral value; it generates a two-dimensional distribution map based on the first integral value, the second integral value, and the pulse amplitude information; and it classifies the data points in the two-dimensional distribution map based on a discrimination curve to distinguish at least two particle types. This application uses a charge integration method to distinguish multiple particles, performs two integration processes on the waveform to obtain the first and second integral values, extracts the peak value of the waveform, and uses an integration method to extract the features of the entire waveform, reducing waveform acquisition errors and improving particle separation accuracy. It avoids large deviations in results due to sudden fluctuations at a single point, effectively averaging the errors of multiple pulse points. By using a multi-point piecewise linear fitting method for particle separation and employing a two-dimensional distribution map for display, it reduces the computational burden on the computer and the complexity of separation.

[0066] Example 1

[0067] See Figure 1 This embodiment provides a radiation detection method that can effectively distinguish different types of radiation particles, including the following steps:

[0068] S1. Convert the pulse signals output by at least two photomultiplier tubes into digital signals, wherein the digital signals include at least two first signals;

[0069] Further, step S1 includes: performing voltage reduction processing on the pulse signals output by at least two of the photomultiplier tubes to obtain low-voltage signals; performing amplification processing on the low-voltage signals to obtain voltage signals; and converting the voltage signals into digital signals.

[0070] In this embodiment, the current pulse signal output by the photomultiplier tube is converted from fluorescent photons generated by the scintillator when excited by particles. Its waveform characteristics (rise / decay time) carry particle type information (such as neutrons, gamma particles, alpha particles, beta particles, etc.). In step S1, the pulse signal output by the photomultiplier tube (approximately kilovolts) can be stepped down to a low-voltage signal (e.g., 0-5V) using a voltage divider to adapt it to subsequent circuits for signal processing. The weak low-voltage signal is amplified into a voltage signal (e.g., mV → V) by a preamplifier; the analog pulse model is converted into a digital signal by an analog-to-digital converter.

[0071] S2. Process at least two of the first signals to extract pulse amplitude information, perform a first integration process on the pulse amplitude information to determine a first integral value, and perform a second integration process on the pulse amplitude information to obtain a second integral value;

[0072] Further, step S2 may include: filtering at least two of the first signals respectively; identifying whether all the filtered first signals meet a preset condition; summing all the filtered first signals that meet the preset condition to extract pulse amplitude information; performing a first integration process on the pulse amplitude information to determine a first integral value, wherein the first integration processing interval is the pulse length interval from the start time of a preset period to the pulse peak time; and performing a second integration process on the pulse amplitude information to obtain a second integral value, wherein the second integration processing interval is the pulse length interval corresponding to the preset period duration.

[0073] In this embodiment, the preset condition is that the pulse arrival times of all the first signals are consistent. When the pulse arrival times of multiple signals are detected to be consistent, these signals are considered to originate from the same radiation event, and the pulse amplitude information is extracted for subsequent processing.

[0074] In step S2, a filter can be used to first filter the first signal to suppress high-frequency noise (electromagnetic interference) and low-frequency drift (baseline fluctuation); asynchronous signals are filtered out by preset conditions to obtain at least two first signals with the same pulse arrival time; the amplitudes of the obtained multiple signals are added point by point according to time points to improve the signal-to-noise ratio of the total pulse amplitude and extract the pulse amplitude information. Two different integration processes are performed on the pulse amplitude information to obtain a first integral value and a second integral value.

[0075] It should be noted that the first integration process is a fast component integration (narrow window), and the second integration process is a slow component integration (wide window).

[0076] Taking alpha and beta particles as examples, the main difference between their nuclear pulse signals lies in the speed of the falling edge of the nuclear signal. Based on this characteristic, the charge integration method can be used to distinguish between alpha and beta nuclides. (See also...) Figure 2As shown in the figure, the horizontal axis represents time, the vertical axis represents amplitude, and the trigger threshold represents the point at which the pulse signal arrives and ends. The delay before burst (QS1) indicates the length of the waveform that needs to be retained before triggering. QS1 filters out interference from white noise signals and is typically set to a threshold higher than the noise amplitude. The real signal is only triggered and recorded after reaching this threshold. This delay setting ensures that the complete real signal is recorded, including both the signal after triggering and the segment of signal before reaching the threshold. The short gate (QS2) indicates the length of the fast component integration. QS2 is typically the time between the start of the pulse waveform and the peak value. In practical applications, it can be fine-tuned manually based on the separation effect. The long gate (Qa) indicates the length of the long slow component integration. The length of Qa includes the entire waveform and the delay portion. In practical applications, it can also be fine-tuned manually based on the separation effect.

[0077] In step S2, the waveform is integrated in the short gate and long gate intervals respectively to obtain the first integral value Qs_cnt and the second integral value Qa_cnt. At the same time, the peak value of the waveform, i.e. the pulse amplitude information, is extracted.

[0078] S3. Generate a two-dimensional distribution map based on the first integral value, the second integral value, and the pulse amplitude information;

[0079] Further, step S3 may include: calculating an integration ratio based on the first integration value and the second integration value; and generating the two-dimensional distribution map according to the pulse amplitude information and the integration ratio.

[0080] It should be noted that in step S3, the first integral value and the second integral value can also be calculated by multiplication, addition, subtraction, or other methods instead of calculating the integral ratio between the first integral value and the second integral value.

[0081] In step S3, to avoid decimals in the calculation results, after receiving the first integral value Qs_cnt, the second integral value Qa_cnt, and the peak value, the value of Qs_cnt×1000 / Qa_cnt is calculated as the PSD value of the pulse. Based on the peak value of the pulse, the position corresponding to a single pulse is generated in a two-dimensional coordinate system, thereby completing multi-point statistics and obtaining a two-dimensional distribution map. The horizontal axis of the map is peak, and the vertical axis is psd.

[0082] It should be noted that a two-dimensional distribution map can be a two-dimensional heat map, with different colors representing the count rate, to more intuitively show the distribution.

[0083] S4. Classify the data points in the two-dimensional distribution map based on the discrimination curve to distinguish at least two particle types.

[0084] In this embodiment, the method may further include the following steps before performing step S4:

[0085] A. Obtain the discrimination curve;

[0086] Further, step A may include: acquiring pulse shape discrimination spectra of at least two standard particles respectively; merging the pulse shape discrimination spectra of all the standard particles to generate a fitting graph; fitting a separation curve in the fitting graph according to the crosstalk ratio between each standard particle, and using the separation curve as the discrimination curve.

[0087] As an example, and not a limitation, the process of obtaining the discrimination curves using alpha and beta particles is as follows:

[0088] Two pulse shape discrimination spectra (PSDs) of standard particle α and standard particle β are obtained separately. The two PSDs are merged to generate a composite image. The channel ratio of α to β and the channel ratio of β to α are calculated. Based on a preset rule, a discrimination curve is generated in the composite image. The preset rule is that the channel ratio of α to β is close to and reaches the optimal value of β to α.

[0089] See Figure 3 As shown, specifically, taking a dividing line based on 15 points as an example, this dividing line is the separation standard curve for standard particles α and β. The crossover ratio is calculated by using the referenced standard curve as the boundary; the count above the standard curve is the β count, and the count below the standard curve is the α count. The crossover ratio of α to β is: β count / (α count + β count); similarly, the crossover ratio of β to α is: α count / (α count + β count). Based on the calculated crossover ratios of α to β and β to α, and using preset rules, the standard curve is adjusted to obtain the discrimination curve.

[0090] This embodiment can effectively distinguish different types of radiation particles, such as alpha particles, beta particles, and gamma rays.

[0091] In this embodiment, the radiation detection method can convert the pulse signals output by multiple photomultiplier tubes into digital signals; it can process multiple first signals to extract pulse amplitude information, perform a first integration process on the pulse amplitude information to determine a first integral value, and perform a second integration process on the pulse amplitude information to obtain a second integral value; it generates a two-dimensional distribution map based on the first integral value, the second integral value, and the pulse amplitude information; and it classifies the data points in the two-dimensional distribution map based on the discrimination curve to distinguish at least two particle types. This application uses the charge integration method to distinguish multiple particles, performs two integration processes on the waveform to obtain the first integral value and the second integral value, extracts the peak value of the waveform, and uses the integration method to extract the features of the entire waveform, reducing the error of waveform acquisition and improving the accuracy of particle separation. It avoids large deviations in results due to sudden fluctuations at a certain point, which is equivalent to averaging the error of multiple pulse points; by using a multi-point piecewise linear fitting method for particle separation and using a two-dimensional distribution map for display, it reduces the computational burden of the computer and the complexity of separation.

[0092] In this embodiment, the radiation detection method generates a two-dimensional graph based on the integral ratio of the fast component integral and the slow component integral of the entire pulse and the pulse amplitude, which is better than the existing three-dimensional graph. This application uses an integral method instead of selecting two points, which can extract the features of the entire waveform compared with the prior art. It will not cause a large deviation in the result due to a sudden fluctuation at a certain point, which is equivalent to averaging the error of multiple points of the pulse.

[0093] Example 2

[0094] See Figure 4 As shown, a radiation detection method includes the following steps:

[0095] S1. Convert the pulse signals output by at least two photomultiplier tubes into digital signals;

[0096] S2. Process at least two of the first signals to extract pulse amplitude information, perform a first integration process on the pulse amplitude information to determine a first integral value, and perform a second integration process on the pulse amplitude information to obtain a second integral value;

[0097] S3. Generate a two-dimensional distribution map based on the first integral value, the second integral value, and the pulse amplitude information;

[0098] S4. Classify the data points in the two-dimensional distribution map based on the discrimination curve to distinguish at least two particle types;

[0099] S5. Calculate the cross-channel ratio of each particle based on the discrimination curve in the two-dimensional distribution map.

[0100] Crossover ratio refers to the proportion of different types of particles that are confused with each other during the classification process. By calculating the crossover ratio, the accuracy and reliability of particle classification can be evaluated.

[0101] Existing technologies lack effective methods for calculating crosstalk ratios, making it impossible to accurately assess the interference levels between different particle types, thus affecting the accuracy and reliability of radiation detection. This application's radiation detection method provides a more intuitive way to calculate and display crosstalk ratios, significantly improving the accuracy of crosstalk ratio calculations for alpha and beta particle separation techniques under various acidity conditions. This embodiment can accurately distinguish different types of radiation particles, improving the accuracy and efficiency of radiation detection. This method is particularly suitable for scenarios requiring simultaneous detection of multiple radiation types, such as nuclear radiation monitoring, medical imaging, and scientific research.

[0102] Example 3

[0103] See Figure 5 As shown, a radiation detection device 1 includes: a conversion unit 11, a processing unit 12, a generation unit 13, and a classification unit 14.

[0104] The conversion unit 11 is used to convert the pulse signals output by at least two photomultiplier tubes into digital signals, wherein the digital signals include at least two first signals;

[0105] Further, see Figure 6 The conversion unit 11 shown includes: a step-down module 111, an amplification module 112, and a conversion module 113.

[0106] The step-down module 111 is used to step down the pulse signals output by at least two of the photomultiplier tubes to obtain low-voltage signals.

[0107] Amplification module 112 is used to amplify the low-voltage signal to obtain a voltage signal;

[0108] The conversion module 113 is used to convert the voltage signal into the digital signal.

[0109] In this embodiment, the current pulse signal output by the photomultiplier tube is converted from fluorescent photons generated by the scintillator when excited by particles. Its waveform characteristics (rise / decay time) carry particle type information (such as neutrons, gamma particles, alpha particles, beta particles, etc.). The step-down module 111 can be a voltage divider, which steps down the pulse signal output by the photomultiplier tube (approximately kilovolts) to a low-voltage signal (e.g., 0-5V) to adapt to subsequent circuits for signal processing. The amplification module 112 can be a preamplifier, which amplifies the weak low-voltage signal to a voltage signal (e.g., mV → V). The conversion module 113 can be an analog-to-digital converter, which converts the analog pulse model into a digital signal.

[0110] Processing unit 12 is configured to process at least two of the first signals to extract pulse amplitude information, perform a first integration process on the pulse amplitude information to determine a first integration value, and perform a second integration process on the pulse amplitude information to obtain a second integration value.

[0111] Further, see Figure 7 The processing unit 12 shown includes: a filtering module 121, a judgment module 122, a processing module 123, a first integration module 124, and a second integration module 125.

[0112] Filtering module 121 is used to filter at least two of the first signals respectively;

[0113] The judgment module 122 is used to identify whether all the first signals after filtering meet the preset conditions;

[0114] Processing module 123 is used to sum all the first signals that have been filtered and meet the preset conditions, and extract pulse amplitude information;

[0115] The first integration module 124 is used to perform a first integration process on the pulse amplitude information to determine a first integration value. The first integration processing interval is the pulse length interval between the start time of a preset period and the pulse peak time.

[0116] The second integration module 125 is used to perform a second integration process on the pulse amplitude information to obtain a second integration value, wherein the second integration processing interval is a pulse length interval corresponding to a preset period duration.

[0117] In this embodiment, the preset condition is that the pulse arrival times of all the first signals are consistent. When the pulse arrival times of multiple signals are detected to be consistent, these signals are considered to originate from the same radiation event, and the pulse amplitude information is extracted for subsequent processing.

[0118] The filtering module 121 can employ a filter to first filter the first signal, suppressing high-frequency noise (electromagnetic interference) and low-frequency drift (baseline fluctuation). The judgment module 122 filters out asynchronous signals based on preset conditions, obtaining at least two first signals with consistent pulse arrival times. The processing module 123 adds the amplitudes of the acquired multiple signals point by point according to time points to improve the signal-to-noise ratio of the total pulse amplitude and extract pulse amplitude information. The first integration module 124 and the second integration module 125 perform two different integration processes on the pulse amplitude information to obtain a first integration value and a second integration value.

[0119] It should be noted that the first integration process is a fast component integration (narrow window), and the second integration process is a slow component integration (wide window).

[0120] The generation unit 13 is used to generate a two-dimensional distribution map based on the first integral value, the second integral value and the pulse amplitude information;

[0121] Furthermore, the generation unit 13 calculates the integration ratio based on the first integration value and the second integration value; and generates the two-dimensional distribution map according to the pulse amplitude information and the integration ratio.

[0122] It should be noted that in the generation unit 13, the first integral value and the second integral value can also be calculated by multiplication, addition, subtraction, etc., instead of calculating the integral ratio between the first integral value and the second integral value.

[0123] The classification unit 14 is used to classify data points in the two-dimensional distribution map based on the discrimination curve to distinguish at least two particle types.

[0124] In this embodiment, the conversion unit 11 in the radiation detection device 1 can convert the pulse signals output by multiple photomultiplier tubes into digital signals; the processing unit 12 processes the multiple first signals to extract pulse amplitude information, performs a first integration process on the pulse amplitude information to determine a first integration value, and performs a second integration process on the pulse amplitude information to obtain a second integration value; the generation unit 13 generates a two-dimensional distribution map based on the first integration value, the second integration value, and the pulse amplitude information; and the classification unit 14 classifies the data points in the two-dimensional distribution map based on the discrimination curve to distinguish at least two particle types. This application uses the charge integration method to distinguish multiple particles, performs two integration processes on the waveform to obtain the first integration value and the second integration value, and extracts the peak value of the waveform. The integration method is used to extract the features of the entire waveform, reducing the error of waveform acquisition and improving the accuracy of particle separation. It avoids large deviations in results due to sudden fluctuations at a certain point, which is equivalent to averaging the error of multiple pulse points. By using a multi-point piecewise linear fitting method for particle separation and using a two-dimensional distribution map for display, the computational burden of the computer and the complexity of separation are reduced.

[0125] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A radiation detection method, characterized in that, include: The pulse signals output from at least two photomultiplier tubes are converted into digital signals, wherein the digital signals include at least two first signals; At least two of the first signals are processed to extract pulse amplitude information, the pulse amplitude information is subjected to a first integration process to determine a first integration value, and the pulse amplitude information is subjected to a second integration process to obtain a second integration value. A two-dimensional distribution map is generated based on the first integral value, the second integral value, and the pulse amplitude information; The data points in the two-dimensional distribution map are classified based on the discrimination curve to distinguish at least two particle types.

2. The radiation detection method according to claim 1, characterized in that, The process of converting the pulse signals output by at least two photomultiplier tubes into digital signals includes: The pulse signals output from at least two of the photomultiplier tubes are respectively subjected to voltage reduction processing to obtain low-voltage signals; The low-voltage signal is amplified to obtain a voltage signal; The voltage signal is converted into the digital signal.

3. The radiation detection method according to claim 1, characterized in that, The step of processing at least two of the first signals to extract pulse amplitude information, performing a first integration process on the pulse amplitude information to determine a first integral value, and performing a second integration process on the pulse amplitude information to obtain a second integral value includes: Filter at least two of the first signals respectively; Identify whether all the first signals after filtering meet preset conditions; All the filtered first signals that meet the preset conditions are summed to extract pulse amplitude information; The pulse amplitude information is subjected to a first integral processing to determine a first integral value, wherein the first integral processing interval is the pulse length interval between the start time of a preset period and the pulse peak time. The pulse amplitude information is subjected to a second integral processing to obtain a second integral value, wherein the second integral processing interval is the pulse length interval corresponding to a preset period duration.

4. The radiation detection method according to claim 3, characterized in that, The preset condition is that the pulse arrival time of all the first signals is consistent.

5. The radiation detection method according to claim 1, characterized in that, The step of generating a two-dimensional distribution map based on the first integral value, the second integral value, and the pulse amplitude information includes: Calculate the integration ratio based on the first integral value and the second integral value; The two-dimensional distribution map is generated based on the pulse amplitude information and the integral ratio.

6. The radiation detection method according to claim 1, characterized in that, The step of classifying data points in the two-dimensional distribution map based on the discrimination curve to distinguish at least two particle types also includes: obtaining the discrimination curve; The discrimination curve includes: Obtain pulse shape discrimination spectra of at least two standard particles respectively; The pulse shape discrimination spectra of all the standard particles are merged to generate a fitting graph; In the fitting graph, a separation curve is fitted based on the crosstalk ratio between each standard particle, and the separation curve is used as the identification curve.

7. The radiation detection method according to claim 1 or 6, characterized in that, Also includes: The cross-channel ratio of each particle is calculated based on the discrimination curve in the two-dimensional distribution map.

8. A radiation detection device, characterized in that, include: A conversion unit is used to convert the pulse signals output by at least two photomultiplier tubes into digital signals, wherein the digital signals include at least two first signals; The processing unit is configured to process at least two of the first signals to extract pulse amplitude information, perform a first integration process on the pulse amplitude information to determine a first integration value, and perform a second integration process on the pulse amplitude information to obtain a second integration value. A generation unit is configured to generate a two-dimensional distribution map based on the first integral value, the second integral value, and the pulse amplitude information; A classification unit is used to classify data points in the two-dimensional distribution map based on a discrimination curve to distinguish at least two particle types.

9. The radiation detection device according to claim 8, characterized in that, The conversion unit includes: A step-down module is used to step down the pulse signals output by at least two of the photomultiplier tubes to obtain low-voltage signals. An amplification module is used to amplify the low-voltage signal to obtain a voltage signal; A conversion module is used to convert the voltage signal into the digital signal.

10. The radiation detection device according to claim 8, characterized in that, The processing unit includes: A filtering module is used to filter at least two of the first signals respectively; The judgment module is used to identify whether all the first signals after filtering meet preset conditions; The processing module is used to sum all the first signals that have been filtered and meet the preset conditions, and extract pulse amplitude information. The first integration module is used to perform a first integration process on the pulse amplitude information to determine a first integration value. The first integration processing interval is the pulse length interval between the start time of a preset period and the pulse peak time. The second integration module is used to perform a second integration process on the pulse amplitude information to obtain a second integration value. The second integration processing interval is the pulse length interval corresponding to a preset period duration.

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