A method and system for charged particle discrimination based on the signal waveform of a parallel-plate ionization chamber

Abstract

The application discloses a charged particle discrimination method and system based on a signal waveform of a parallel-plate ionization chamber, and belongs to the technical field of radiation detection. The charged particle discrimination method comprises the following steps: obtaining a current signal waveform generated by charged particles at an anode of a parallel-plate ionization chamber and extracting characteristic quantities; analyzing the relationship between the obtained characteristic quantities and particle energy and incident angle, and constructing particle identification parameters; according to the relationship between particle energy and range, the distribution characteristics of different particles are determined by using related identification parameters for plotting; and different particles are discriminated according to different distribution characteristics. The method utilizes the energy deposition characteristics of the particles, the constructed identification parameters weaken the influence of the particle incident angle on the particle discrimination, so that the p, D, T, 3 He, 4 He five kinds of particles can be accurately identified in a large angle range, and the efficiency of cross section measurement is improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of radiation detection, and particularly relates to a charged particle discrimination method and system based on a screen-grid ionization chamber signal waveform. BACKGROUND

[0002] With the deepening of particle physics and nuclear physics research, the acquisition of nuclear data puts forward new requirements for the identification technology of charged particles. In nuclear physics experiments, bombardment nuclear reactions are often accompanied by the generation of a large number of particle fragments. In order to study these particle fragments, they must first be discriminated. The discrimination of p, D, T, 3 He and 4 He charged particles is the basis and key to obtaining charged particle nuclear data. In the measurement of alpha particles and heavy charged particles, the screen-grid ionization chamber is a commonly used gas detector, which has the characteristics of high count rate, fast time response, good energy resolution, high detection efficiency, and the anode pulse amplitude being independent of the ionization position.

[0003] However, in recent years, although the application of the screen-grid ionization chamber has become more mature, its effect is still to distinguish the particles generated by known reactions. It cannot discriminate unknown p, D, T, 3 He or 4 He particles incident alone, thus greatly limiting the measurement efficiency of nuclear cross sections. SUMMARY

[0004] In order to overcome the above-mentioned shortcomings of the prior art, the purpose of the present application is to provide a charged particle discrimination method and system based on a screen-grid ionization chamber signal waveform, so as to solve the technical problem that the prior art cannot discriminate a plurality of unknown particles (such as p, D, T, 3 He or 4 He) incident alone.

[0005] In order to achieve the above-mentioned purpose, the present application adopts the following technical solutions:

[0006] The present application discloses a charged particle discrimination method based on a screen-grid ionization chamber current signal waveform, comprising:

[0007] obtaining a current signal waveform generated by a charged particle at an anode of a screen-grid ionization chamber and extracting a characteristic quantity;

[0008] constructing a particle identification parameter using the characteristic quantity;

[0009] plotting according to the identification parameter and determining the distribution characteristics of different particles;

[0010] discriminating the charged particles according to the distribution characteristics of different particles.

[0011] Preferably, the characteristic quantities include total integral of anode current signal, average slope of anode current signal rising edge, integral area of anode current signal when reaching peak, electron drift time from cathode to grid, and cathode-anode current signal start time difference.

[0012] Preferably, a particle identification parameter is constructed using the characteristic quantities, including:

[0013] An identification parameter Q is constructed, which is the total charge amount of particle deposition, obtained by calculating the total integral of anode current signal, reflecting the energy of incident particles;

[0014] An identification parameter k(t-Δt) / S is constructed, which eliminates the influence of angle and is considered to be only related to particle range R; wherein k is the average slope of anode current signal rising edge, t is the electron drift time from cathode to grid, Δt is the cathode-anode current signal start time difference, and S is the integral area of anode current signal when reaching peak.

[0015] The calculation formula of t is:

[0016]

[0017] In the formula, D is the distance from cathode to grid, v C is the electron drift velocity in the cathode region and the anode region.

[0018] Under the condition that the electric field intensity, gas composition and pressure in the detector are determined, v c can be considered as a constant value, and the experimental measurement method is as follows: a particle source parallel to the grid is arranged between the cathode and the grid, and the time difference of the signals generated by each incident particle in the cathode and the anode is measured, then v C can be obtained by the following formula:

[0019]

[0020] In the formula, D r is the vertical distance from the particle source to the grid, T2 is the time when the anode current signal starts, T1 is the time when the cathode current signal starts, i represents the i-th particle, and n is the total number of particles. In addition, it can also be obtained by querying a related database.

[0021] In addition, as an alternative, the characteristic quantity (t-Δt) can also be replaced by the anode current signal rising time t rise , especially when the projection distance of the particle range in the normal direction of the detector is less than the distance from the grid to the anode.

[0022] Further preferably, the distribution characteristics of different particles are determined according to the identification parameters, including:

[0023] Draw a k(t-Δt) / S-Q graph, which reflects the relationship between particle energy and range, and different particles show different bands.

[0024] Further preferably, the charged particle identification is performed according to the distribution characteristics of different particles, including: preferably using a quadratic polynomial (other functions can also be selected according to the situation) to fit different bands, and translating the fitted curve as a demarcation line to distinguish different particles.

[0025] Further preferably, for unknown incident particles, the identification parameters Q and k(t-Δt) / S are calculated through the signal waveform, and are reflected in the k(t-Δt) / S-Q graph, and the type of the particle is determined by the area where the point falls.

[0026] The application also discloses a charged particle identification system based on a screen-grid ionization chamber signal waveform, which realizes the above-mentioned charged particle identification method based on a screen-grid ionization chamber signal waveform.

[0027] The characteristic quantity extraction module is used for analyzing and generating characteristic quantities according to the signal waveform generated by the charged particle at the anode of the screen-grid ionization chamber.

[0028] The particle identification parameter construction module is used for constructing particle identification parameters according to the characteristic quantities.

[0029] The drawing module is used for drawing a graph according to the identification parameters and determining the distribution characteristics of different particles.

[0030] The charged particle identification module is used for identifying different particles according to the distribution characteristics of different particles in the graph.

[0031] Preferably, the signal acquisition module is further included, which is used for acquiring the signal waveform generated by the charged particle at the cathode and the anode of the detector through the screen-grid ionization chamber.

[0032] The application also discloses a computer device, which comprises a memory and a processor, the memory stores a computer program, and the processor realizes the steps of the above-mentioned charged particle identification method based on a screen-grid ionization chamber signal waveform when executing the computer program.

[0033] The application also discloses a computer readable storage medium, which stores a computer program, and the computer program realizes the steps of the above-mentioned charged particle identification method based on a screen-grid ionization chamber signal waveform when executed by a processor.

[0034] Compared with the prior art, the application has the following beneficial effects:

[0035] The charged particle identification method based on the screen grid ionization chamber disclosed in the present application is based on the working principle of the screen grid ionization chamber, the signal waveform generated by the charged particle at the anode of the detector is obtained, and the characteristic quantity is generated, the particle identification parameter is constructed according to the characteristic quantity, the energy deposition characteristics of the particle are utilized, the influence of the particle incident angle on the particle identification is weakened by the constructed identification parameter, and thus the p, D, T, 3 He, 4 He five kinds of particles can be accurately identified in a large incident angle range, and the efficiency of the cross section measurement is improved. Therefore, the present application can observe the distribution characteristics of different particle events by combining the advanced signal processing technology and the multi-parameter analysis, and thus the p, D, T, 3 He, 4 He five kinds of particles can be accurately identified in a large incident angle range, and the efficiency of the cross section measurement is improved. Therefore, the present application can observe the distribution characteristics of different particle events by combining the advanced signal processing technology and the multi-parameter analysis, and thus the p, D, T, 3 He, 4 He five kinds of particles can be accurately identified in a large incident angle range, and the efficiency of the cross section measurement is improved. Therefore, the present application can observe the distribution characteristics of different particle events by combining the advanced signal processing technology and the multi-parameter analysis, and thus the p, D, T, 3 He, 4 He five kinds of particles can be accurately identified in a large incident angle range, and the efficiency of the cross section measurement is improved. Therefore, the present application can observe the distribution characteristics of different particle events by combining the advanced signal processing technology and the multi-parameter analysis, and thus the p, D, T, BRIEF DESCRIPTION OF DRAWINGS

[0036] Figure 1 It is a flowchart of the charged particle identification method of the present application.

[0037] Figure 2 It is the relationship between the particle energy E and the charge Q.

[0038] Figure 3 It is the relationship between the particle incident angle and the signal rising edge slope.

[0039] Figure 4 It is the distribution of different incident particles in the k(t-Δt) / S-Q graph. DETAILED DESCRIPTION

[0040] In order to enable the personnel in the technical field to better understand the present application scheme, the technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by the personnel in the field without creative labor should belong to the protection scope of the present application.

[0041] It is to be understood that the terms "first", "second", and the like, used in the description and the claims of the application, as well as the above-described drawings, are used to distinguish between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the use of data so designated is not meant to limit, and will not serve to limit, the described embodiments of the application to only such values as are specifically recited. Further, the terms "include", "includes", and "including" and any variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, system, product, or apparatus that comprises a list of steps or elements does not necessarily comprise only those steps or elements that are literally recited, but can include other steps or elements not expressly listed or inherent to such process, method, product, or apparatus.

[0042] The application will be further described in detail below with reference to the accompanying drawings:

[0043] Referring to Figure 1 The charged particle discrimination method based on the signal waveform of the screen-grid ionization chamber comprises the following steps:

[0044] S1: obtaining the signal waveform generated by the charged particle at the anode of the screen-grid ionization chamber and extracting characteristic quantities;

[0045] S2: constructing a particle identification parameter by using the obtained characteristic quantities;

[0046] S3: drawing according to the identification parameter and determining the distribution characteristics of different particles;

[0047] S4: discriminating the particles according to the distribution characteristics of different particles.

[0048] Preferably, in step S1, the extracted characteristic quantities include: total integral of the anode current signal, average slope of the rising edge of the anode current signal, integral area of the anode current signal when reaching the peak, drift time of the electron from the cathode to the grid, and time difference between the start times of the cathode and anode current signals.

[0049] Preferably, in step S2, the particle identification parameter is constructed by using the obtained characteristic quantities, specifically including:

[0050] S21: constructing an identification parameter Q, which is the total charge amount deposited by the particle and reflects the energy of the incident particle, and can be obtained by integrating the anode current signal.

[0051] S22: constructing an identification parameter k(t-Δt) / S, which eliminates the influence of the angle and can be regarded as being related only to the particle range R. Wherein k is the average slope of the rising edge of the anode current signal, t is the drift time of the electron from the cathode to the grid, Δt is the time difference between the start times of the cathode and anode current signals, and S is the integral area of the anode current signal when reaching the peak.

[0052] Preferably, in step S3, a k(t-Δt) / SQ diagram is plotted, which reflects the relationship between particle energy and range, with different particles showing distinct different band distributions.

[0053] Preferably, in step S4, the method for identifying different particles includes: fitting different bands preferably with a quadratic polynomial (other functions may also be selected depending on the situation) as the dividing line for distinguishing different particles.

[0054] In one embodiment of the present invention, a method for identifying charged particles based on the signal waveform of a screen-grid ionization chamber is provided, specifically including:

[0055] S1: Acquire the signal waveform generated by charged particles at the anode of the grid ionization chamber and extract characteristic quantities. This waveform reflects the Bragg peak of the incident particle, that is, the energy deposition characteristics at the end of the particle track. Different particles have different Bragg peaks, so extracting the related characteristic quantities can achieve the effect of distinguishing different particles. The characteristic quantities include: the total integral Q of the anode current signal, the average slope k of the rising edge of the anode current signal, the integral area S when the anode current signal reaches its peak, the drift time t of the electron from the cathode to the grid, and the starting time difference Δt between the cathode and anode current signals. The obtained characteristic quantities are related to the incident particles and the design parameters of the detector.

[0056] S2: Construct particle recognition parameters using the obtained feature quantities. Q reflects the total charge deposited by charged particles within the detector, and is proportional to the particle's energy, such as... Figure 2 As shown; k is independent of the incident particle energy, only depends on the angle, and is proportional to 1 / cosθ, as... Figure 3 As shown, θ is the angle between the particle incident direction and the detector normal direction; S represents k0 when the particle is incident perpendicularly. Since the signal rise time is only related to the Bragg peak of the particle, S can be approximated as not changing with particle energy and angle, but only related to the type of incident particle; t and Δt are the drift time of the electron from the cathode to the grid, and the time difference between the start of the cathode and anode current signals, which can be expressed as:

[0057]

[0058] In the formula, D is the distance from the cathode to the grid, v C R represents the drift velocity of electrons in the cathode and anode regions, and R is the particle range.

[0059] Given a fixed electric field strength, gas composition, and pressure inside the detector, v c This can be considered a constant value. The experimental measurement method is as follows: a particle source parallel to the grid is set between the cathode and the grid. The time difference in signal generation at the cathode and anode is measured for each incident particle. Then v C It can be obtained from the following formula:

[0060]

[0061] where D r is the vertical distance from the source to the grid, T2 is the time at which the anode current signal begins, T1 is the time at which the cathode current signal begins, i represents the ith particle, and n is the total number of particles. Alternatively, the information can be obtained by querying a relevant database.

[0062] From equations (1.1) and (1.3), we have:

[0063]

[0064] The electron drift velocity is determined, so (t-Δt) is only related to the projected distance Rcosθ of the particle incident track. Alternatively, the characteristic quantity (t-Δt) can also be replaced by the rise time t rise of the anode current signal, especially when the projected distance of the particle range in the normal direction of the detector is less than the distance from the grid to the anode.

[0065] By constructing the identification parameter k(t-Δt) / S, the influence of the particle incident angle is eliminated, so that the parameter is only related to the particle range.

[0066] S3: Plotting according to the identification parameter and determining the distribution characteristics of different particles. The relationship between the energy and the range of different particles is different, and the identification parameter Q obtained in S2 is only related to the particle energy; k(t-Δt) / S is only related to the particle range. Draw the k(t-Δt) / S-Q image for all incident particles, and according to the different particle species, the corresponding points should be distributed near different curves, as shown in FIG. 2, because the energy deposition of particles is a random process, so the distribution of different particles presents different bands. Figure 4

[0067] S4: Particle identification according to the distribution characteristics of different particles. Preferably, a quadratic polynomial is used to fit the different particle bands, and the obtained curve is translated as the demarcation line of different particles. For unknown incident particles, the above identification parameters are calculated through the signal waveform, and reflected in the k(t-Δt) / S-Q image, so that the particle species can be determined by the area where the point falls. In this embodiment, the incident angle is within the range of 45°, and the correct rates of p, D, T, 3 He, 4 He identification are 82.26%, 53.60%, 49.23%, 76.08%, and 73.81%, respectively.

[0068] In another embodiment, the application also provides a charged particle identification system based on a screen-grid ionization chamber, which can implement the above-mentioned charged particle identification method, and comprises:​

[0069] A signal acquisition module is configured to acquire a signal waveform generated by a charged particle at a cathode and an anode of a detector through a parallel-plate ionization chamber.

[0070] A feature quantity extraction module is configured to analyze and generate a feature quantity according to the signal acquired by the signal acquisition module.

[0071] A particle identification parameter construction module is configured to construct a particle identification parameter according to the feature quantity.

[0072] A drawing module is configured to draw an image according to the identification parameter and observe a distribution characteristic of different particle events.

[0073] A particle identification module is configured to identify different particles according to the distribution characteristic of different particle events in the image.

[0074] In an embodiment, the present application provides a computer device, which comprises a processor and a memory, the memory is configured to store a computer program, the computer program comprises program instructions, and the processor implements the steps of the charged particle identification method when executing the computer program. The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor is the computing core and control core of the terminal, and is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions in the computer storage medium to implement a corresponding method flow or a corresponding function. The processor in the embodiment of the present application can be used to implement the steps of the charged particle identification method when the processor executes the computer program.

[0075] In another embodiment of the present application, the present application further provides a storage medium, specifically a computer readable storage medium, which is a memory device in a computer device, used for storing programs and data. The computer program in the embodiment is executed by a processor to implement the steps of the charged particle discrimination method described above. It can be understood that the computer readable storage medium herein can include an internal storage medium of the computer device, and of course can also include an extended storage medium supported by the computer device. The computer readable storage medium provides a storage space, which stores an operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space, and the instructions can be one or more computer programs (including program codes). It should be noted that the computer readable storage medium herein can be a high-speed RAM memory, or a non-volatile memory such as at least one disk memory. The one or more instructions stored in the computer readable storage medium can be loaded and executed by the processor to implement the corresponding steps of the steps of the charged particle discrimination method in the above embodiment.

[0076] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. In addition, the present application can take the form of a computer program product implemented on one or more computer usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage, etc.) containing computer usable program code.

[0077] The present application is described with reference to flowcharts and / or block diagrams of the methods, devices (systems), and computer program products of the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts 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, a special-purpose computer, an embedded processor, or other programmable data processing apparatus to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing apparatus produce a device that implements the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 an apparatus that implements the functions specified in one or more flows and / or blocks.

[0078] These computer program instructions can also be stored in a computer readable memory that can direct the computer or other programmable data processing apparatus to work in a specific manner, so that the instructions stored in the computer readable memory produce a manufactured product including instruction apparatus, which implements the functions specified in the flowcharts and / or block diagrams. Figure 1one or more processes and / or blocks Figure 1 the function specified in the one or more blocks.

[0079] These computer program instructions can also be loaded into a computer or other programmable data processing devices, so that a series of operational steps are performed on the computer or other programmable data processing devices to generate a computer implemented process, so that the instructions executed on the computer or other programmable data processing devices provide a process for implementing the flow Figure 1 one or more processes and / or blocks Figure 1 the function specified in the one or more blocks.

[0080] In summary, the method disclosed in the present application utilizes the energy deposition characteristics of particles, and the constructed identification parameters weaken the influence of particle incident angle on particle identification, so that p, D, T, 3 He, 4 He five kinds of particles, and improves the efficiency of cross section measurement.

[0081] The above is only to illustrate the technical idea of the present application, and cannot limit the protection scope of the present application, and any modification made according to the technical idea of the present application on the basis of the technical scheme falls within the protection scope of the claims of the present application.

Claims

1. A method of charged particle discrimination based on the waveform of a current signal from a parallel-plate ionization chamber, characterized by, The method comprises the following steps: acquiring a current signal waveform generated by a charged particle on an anode of a parallel-plate ionization chamber and extracting a characteristic quantity; constructing a particle identification parameter by using the characteristic quantity, which comprises: constructing an identification parameter Q, which is a total charge amount of particle deposition, and is obtained by calculating a total integral of the anode current signal, and reflects the energy of the incident particle; Constructing a recognition parameter which eliminates the influence of the angle and is considered to be related only to the particle range ; wherein k is the average slope of the rising edge of the anode current signal, t is the drift time of the electron from the cathode to the grid, Δt is the difference in the start time of the cathode and anode current signals, S is the integral area of the anode current signal up to the peak; t The calculation formula is: wherein D is the cathode-to-gate distance, is the electron drift velocity in the cathode and anode regions; The electric field intensity, gas composition and pressure inside the detector are determined, The experimental measurement method is as follows: a particle source parallel to the gate is arranged between the cathode and the gate, and the time difference of the signals generated by each incident particle at the cathode and the anode is measured. The following formula is obtained: wherein D r is the vertical distance from the particle source to the gate, T 2 is the time at which the anode current signal starts, T1 is the time at which the cathode current signal starts, i denotes the i particle, n is the total number of particles; In addition, Also available by querying relevant databases; Furthermore, when the projection distance of the particle range in the direction of the normal line of the detector is smaller than the distance from the grid to the anode, the characteristic quantity (t-Δt) can be obtained from the rising time of the anode current signal t rise instead drawing a graph according to the identification parameter and determining the distribution characteristics of different particles; identifying the charged particles according to the distribution characteristics of different particles.

2. The method of claim 1, wherein the method is based on a waveform of the current signal of the parallel-plate ionization chamber. The characteristic quantity comprises a total integral of the anode current signal, an average slope of a rising edge of the anode current signal, an integral area of the anode current signal at a peak, a drift time of an electron from a cathode to a gate, and a difference between the starting times of the cathode and anode current signals.

3. The method of claim 1, wherein the method is based on a waveform of the current signal of the parallel-plate ionization chamber. The method further comprises the following steps of: Plotting A Q-plot, which reflects the relationship between particle energy and range, shows different bands for different particles.

4. The method of claim 3, wherein the method is based on a waveform of the current signal of the parallel-plate ionization chamber. drawing a graph according to the identification parameter and determining the distribution characteristics of different particles, which comprises:

5. The method of claim 4, wherein the method is based on a waveform of the current signal of the parallel-plate ionization chamber. For unknown incident particles, the identification parameters Q and are calculated from their signal waveforms and The type of particle is determined by the region in the Q plot in which the point falls.

6. A charged particle discrimination system based on a screen ionization chamber signal waveform, characterized by, identifying the charged particles according to the distribution characteristics of different particles, which comprises: adopting a quadratic polynomial fitting for different bands, and translating the fitting curve as a demarcation line for distinguishing different particles. The method comprises the following steps of: a characteristic quantity extraction module, which is configured to analyze and generate a characteristic quantity according to a signal waveform generated by a charged particle on an anode of a parallel-plate ionization chamber; a particle identification parameter construction module, which is configured to construct a particle identification parameter according to the characteristic quantity; a drawing module, which is configured to draw a graph according to the identification parameter and determine the distribution characteristics of different particles; 7. A charged particle discrimination system based on a screen ionization chamber signal waveform according to claim 6, characterized in that, a charged particle identification module, which is configured to identify different particles according to the distribution characteristics of different particles in the graph.

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that, The method further comprises a signal acquisition module, which is configured to acquire a signal waveform generated by a charged particle on a cathode and an anode of a detector by using a parallel-plate ionization chamber.

9. A computer-readable storage medium storing a computer program, the computer program comprising instructions that, when executed by a computer, cause the computer to perform the method of any one of claims 1 to 8. The processor executes the computer program to implement the steps of the method for identifying charged particles based on a current signal waveform of a parallel-plate ionization chamber according to any one of claims 1 to 5. The computer program is executed by the processor to implement the steps of the method for identifying charged particles based on a current signal waveform of a parallel-plate ionization chamber according to any one of claims 1 to 5.

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