CN113721286A - Positron annihilation life spectrometer for pulse discrimination by using support vector machine - Google Patents
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Abstract
The invention relates to a positron annihilation lifetime spectrometer for pulse discrimination by using a support vector machine, which comprises: a learning training device and a positron annihilation lifetime measuring device; the learning training device comprises a first detector module, a first data acquisition module and a processing terminal; the first detector module comprises a scintillator and a photomultiplier tube; the first data acquisition module performs digital sampling on the detector pulse, so that an analog signal is digitized and can be subjected to subsequent digital processing; the processing terminal comprises a data processing and classifying module and a support vector machine training module, wherein the data processing and classifying module processes and classifies the detector pulse data acquired by the data acquisition module; the correct cases and the error cases form a training set for subsequent training; and (3) learning and training the training set sample by using a support vector machine algorithm to obtain a classification model and verify the reliability of the classification model, wherein the classification model is used for a positron annihilation life measuring device.
Description
Technical Field
The invention relates to the field of positron annihilation life, in particular to a positron annihilation life spectrometer and a method thereof for pulse discrimination by using a support vector machine.
Background
Positron annihilation spectroscopy is widely used in the research of material science. The positron annihilates with electrons in the sample after processes such as moderation. The gamma photons generated by annihilation can reflect information such as electron density inside the material. Positrons are easily captured by defects inside the material and are therefore the most sensitive material defect probes at present. The annihilation lifetime of the positron can reflect the electron concentration at the annihilation position, and further corresponding structural information can be acquired. Positron lifetime spectroscopy has unique advantages in the field of material science as a nondestructive and sensitive material defect characterization means.
In positron lifetime measurements, 22Na was used as the positron source. The decay of the positron with 22Na releases a gamma photon of about 1.28MeV, which is considered to be the initial signal of positron lifetime. The positron annihilates with an electron and is converted into a pair of annihilation photons of 0.511MeV, which are considered to be the end-of-life signal of the positron. The time difference between the ending signal and the starting signal is measured to obtain the positron lifetime, and the positron lifetime spectrum can be obtained by counting the positron lifetime.
A conventional positron life spectrometer consists of a scintillator, a photomultiplier tube (PMT), a high-voltage, constant-ratio, timed discriminator (CFDD), a time delay, a time-to-amplitude converter (TAC), a multichannel analyzer (MCA), and a computer. As shown in fig. 1, two scintillation detectors are used as the start detector and the end detector to measure the start signal and the end signal, respectively. The signal is converted into a time signal after amplitude discrimination and timing by a constant ratio timing discriminator, the time difference of the two time signals is converted into a pulse signal with the amplitude linearly related to the time by a time amplitude converter, and the pulse signal is collected by a multichannel analyzer and transmitted to a computer for analysis to obtain a final positron annihilation life spectrum.
The traditional life spectrum only simply discriminates the amplitude of the pulse, and can not discriminate the distorted pulse caused by external interference, so that the life spectrum result is influenced by the fitting parameters, and the measurement precision is difficult to guarantee.
Disclosure of Invention
In order to solve the technical problems, the invention provides a positron annihilation lifetime spectrometer for pulse discrimination by using a support vector machine, which is used for pulse discrimination, effectively improves the discrimination efficiency of the spectrometer on wrong pulses and improves the measurement precision of the spectrometer.
The technical scheme of the invention is as follows: a positron annihilation lifetime spectrometer for pulse discrimination using a support vector machine, comprising: a learning training device and a positron annihilation lifetime measuring device;
the learning training device comprises a first detector module, a first data acquisition module and a processing terminal;
the first detector module comprises a scintillator and a photomultiplier tube;
the first data acquisition module performs digital sampling on the detector pulse, so that an analog signal is digitized and can be subjected to subsequent digital processing;
the processing terminal comprises a data processing and classifying module and a support vector machine training module, wherein the data processing and classifying module processes and classifies the detector pulse data acquired by the data acquisition module into three types of samples, namely correct cases, error cases and cases which cannot be distinguished; wherein the correct case and the incorrect case form a training set for subsequent training; the support vector machine training module performs learning training on a training set sample by using a support vector machine algorithm to obtain a classification model and verify the reliability of the classification model, and the classification model is used for a positron annihilation life measuring device;
the positron life measuring device comprises an initial detector, a termination detector, a second data acquisition module, a data processing module, a digital timing unit, a classification model unit, a coincidence unit and a data analysis module.
Further, the scintillator is selected from barium fluoride crystal, lanthanum bromide crystal, yttrium lutetium silicate crystal or plastic scintillator; the detector module receives decay gamma photons and positron annihilation gamma photons generated by the 22Na radiation source and converts the decay gamma photons and the positron annihilation gamma photons into electrical pulse signals.
Further, in the positron lifetime measuring apparatus:
the initial detector is used for detecting 1.28MeV gamma photons generated by decay of a radioactive source, and the structure of the initial detector is the same as that of a first detector module in the learning training device;
the termination detector is used for detecting 0.511MeV gamma photons generated by positron annihilation and has the same structure as the starting detector;
the data processing module is used for converting the pulse data of the detector into a data format which can be used by a subsequent module;
the digital timing module is used for extracting the time information of the pulse data of the start detector and the stop detector;
a classification model unit: the detector pulse classification system is used for classifying the detector pulse and marking the detector pulse as a correct case or an error case;
the coincidence logic unit is used for judging coincidence in time of the starting signal and the ending signal marked as the correct case, and calculating the time difference between the starting signal and the ending signal which accord with the time condition;
and the data analysis module is used for counting the time difference between the starting signal and the ending signal and drawing a life spectrum.
According to another aspect of the present invention, a method for discriminating positron annihilation lifetimes is provided, comprising the steps of:
step 1, a single detector module is used for measuring gamma photons generated by a 22Na radioactive source, a scintillator in the detector module is in coupling contact with a photomultiplier through silicone oil, and a digital acquisition card of a first data acquisition module acquires pulse data and transmits the pulse data to a computer for storage; processing and classifying the pulse data by using a data processing and classifying module, and classifying the pulse data into correct cases, wrong cases and cases which cannot be distinguished by using a support vector machine algorithm to learn and train so as to obtain a classification model; verifying the model by using the acquired and classified off-line data;
step 2, when positron annihilation life experiment measurement is carried out, a radioactive source and a sample form a sandwich structure, the radioactive source is positioned between two samples to be measured, and two detector modules are arranged in a right angle; one detector module is used as an initial detector for measuring gamma photons of 1.28MeV generated by decay of a radioactive source, and the other detector module is used as a termination detector for measuring gamma photons of 0.511MeV generated by positron annihilation;
step 3, the pulses of the two detectors are simultaneously input into a data acquisition card of a second data acquisition module through a coaxial cable, and the data acquisition card acquires data and then transmits the data to a computer for processing; the pulse data of the detector is classified by a classification model unit, is marked as a correct case and an error case, and meanwhile, the time is calculated by a digital timing module; and inputting the data into a coincidence logic unit, and when the time difference of the two paths of signals is smaller than 100ns and is the correct case, forming a group of coincidence cases, and performing statistical processing on the time difference of the coincidence cases to obtain a positron life spectrum.
Has the advantages that:
(1) the method utilizes a support vector machine algorithm in machine learning to perform learning training on the classified waveforms and classify unknown samples, so that distorted pulses can be effectively discriminated, the measurement result is not easily influenced by fitting parameters, and the result confidence is improved.
(2) The data acquisition equipment is used for directly sampling the detector pulse, data are transmitted to the computer and processed by software, the hardware structure is greatly simplified, and the modularized software design concept is adopted, so that the upgrading and maintenance are convenient.
Drawings
FIG. 1 is a conventional positron lifetime spectrometer;
FIG. 2 is a learning training apparatus of the present invention;
FIG. 3 is a positron lifetime measuring apparatus of the present invention;
FIG. 4 is a schematic view of an embodiment of the present invention;
FIG. 5 is a classification sample;
fig. 6 is a graph showing the measurement results.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, rather than all embodiments, and all other embodiments obtained by a person skilled in the art based on the embodiments of the present invention belong to the protection scope of the present invention without creative efforts.
The invention relates to a positron annihilation lifetime spectrometer for pulse discrimination by using a support vector machine, which comprises: a learning training device and a positron annihilation lifetime measuring device.
As shown in fig. 2, the learning and training device includes a first detector module, a first data acquisition module, and a processing terminal;
the first detector module comprises a scintillator and a photomultiplier tube; the scintillator can be selected from barium fluoride crystal, lanthanum bromide crystal, yttrium lutetium silicate crystal or plastic scintillator. The first detector module receives decay gamma photons and positron annihilation gamma photons generated by the 22Na radiation source and converts them into electrical pulse signals.
The first data acquisition module performs digital sampling on the detector pulse, so that an analog signal is digitized and can be subjected to subsequent digital processing;
the processing terminal comprises a data processing and classifying module and a support vector machine training module, wherein the data processing and classifying module processes and classifies the detector pulse data acquired by the data acquisition module into three types of samples, namely correct cases, error cases and cases which cannot be distinguished; wherein the correct case and the incorrect case form a training set for subsequent training; the support vector machine training module performs learning training on a training set sample by using a support vector machine algorithm to obtain a classification model and verify the reliability of the classification model, and the classification model is used for a positron annihilation life measuring device;
according to one embodiment of the invention, the pulse signals of the detector in the positive electron lifetime spectrometer are screened and classified by using a support vector machine algorithm, so that error cases are screened out, and the precision of the experimental result is improved.
As shown in fig. 3, the positron lifetime measuring apparatus includes a start detector, an end detector, a second data acquisition module, a data processing module, a digital timing unit, a classification model unit, a coincidence unit, and a data analysis module.
The initial detector is used for detecting 1.28MeV gamma photons generated by decay of a radioactive source, and the structure of the initial detector is the same as that of a detector module in the learning training device.
The stop detector is used to detect the 0.511MeV gamma photons produced by positron annihilation and is structurally identical to the start detector.
The data processing module is used for converting the detector pulse data into a data format which can be used by a subsequent module.
The digital timing module is used for extracting the time information of the pulse data of the start detector and the end detector.
A classification model unit: the detector pulses are classified and marked as either correct or false.
The coincidence logic unit is used for judging coincidence in time of the starting signal and the ending signal marked as the correct case, and calculating the time difference between the starting signal and the ending signal which accord with the time condition.
And the data analysis module is used for counting the time difference between the starting signal and the ending signal and drawing a life spectrum.
According to one embodiment of the invention, a positron annihilation lifetime spectrometer acquires data by using two cylindrical lanthanum bromide crystals with the diameter of 25 mm and the height of 15 mm and two photomultiplier tubes through a digital acquisition card, processes the data by a computer terminal and finishes screening by a support vector machine to obtain a correct positron annihilation lifetime spectrum, as shown in fig. 4.
Firstly, gamma photons generated by a 22Na radioactive source are measured by using a single detector module, a lanthanum bromide crystal in the first detector module is in coupling contact with a photomultiplier through silicone oil, and a digital acquisition card in the first data acquisition module acquires pulse data and transmits the pulse data to a computer for storage. The pulse data is processed and classified into correct cases, error cases and unrecognizable cases, as shown in fig. 5. And (3) taking 30 groups of correct cases and 100 groups of error cases as training sets, and learning and training by using a support vector machine algorithm to obtain a classification model. And the model is verified using the collected and classified offline data.
In positron annihilation life experiment measurement, a radioactive source and a sample form a sandwich structure, the radioactive source is positioned between two samples to be measured, two detector modules are placed at a right angle, and compared with the linear placement, the influence caused by the stacked signals of two photons, namely 0.511MeV and 1.28MeV, can be greatly reduced. One detector module serves as a start detector for measuring 1.28MeV gamma photons from decay of the radiation source, and the other detector serves as an end detector for measuring 0.511MeV gamma photons from positron annihilation.
The two paths of detector module pulses are simultaneously input to a data acquisition card through a coaxial cable, and the data acquisition card acquires data and then transmits the data to a computer for processing. The detector pulse data is classified by the classification model, marked as correct cases and error cases, and the time is calculated by the timing module. The data is input into the coincidence logic unit, and when the time difference of the two paths of signals is less than 100ns and is the correct case, the two paths of signals form a group of coincidence cases. The time difference corresponding to the case is statistically processed to obtain a positron lifetime spectrum, as shown in fig. 6.
Although illustrative embodiments of the present invention have been described above to facilitate the understanding of the present invention by those skilled in the art, it should be understood that the present invention is not limited to the scope of the embodiments, but various changes may be apparent to those skilled in the art, and it is intended that all inventive concepts utilizing the inventive concepts set forth herein be protected without departing from the spirit and scope of the present invention as defined and limited by the appended claims.
Claims (4)
1. A positron annihilation lifetime spectrometer for pulse discrimination using a support vector machine, comprising: a learning training device and a positron annihilation lifetime measuring device;
the learning training device comprises a first detector module, a first data acquisition module and a processing terminal;
the first detector module comprises a scintillator and a photomultiplier tube;
the first data acquisition module performs digital sampling on the detector pulse, so that an analog signal is digitized and can be subjected to subsequent digital processing;
the processing terminal comprises a data processing and classifying module and a support vector machine training module, wherein the data processing and classifying module processes and classifies the detector pulse data acquired by the data acquisition module into three types of samples, namely correct cases, error cases and cases which cannot be distinguished; wherein the correct case and the incorrect case form a training set for subsequent training; the support vector machine training module performs learning training on a training set sample by using a support vector machine algorithm to obtain a classification model and verify the reliability of the classification model, and the classification model is used for a positron annihilation life measuring device;
the positron life measuring device comprises an initial detector, a termination detector, a second data acquisition module, a data processing module, a digital timing unit, a classification model unit, a coincidence unit and a data analysis module.
2. The positron annihilation lifetime spectrometer of claim 1 for pulse discrimination using a support vector machine, wherein:
the scintillator is selected from barium fluoride crystal, lanthanum bromide crystal, yttrium lutetium silicate crystal or plastic scintillator; the detector module receives decay gamma photons and positron annihilation gamma photons generated by the 22Na radiation source and converts the decay gamma photons and the positron annihilation gamma photons into electrical pulse signals.
3. The positron annihilation lifetime spectrometer for pulse discrimination using a support vector machine as defined in claim 1, wherein said positron lifetime measurement device comprises:
the initial detector is used for detecting 1.28MeV gamma photons generated by decay of a radioactive source, and the structure of the initial detector is the same as that of a first detector module in the learning training device;
the termination detector is used for detecting 0.511MeV gamma photons generated by positron annihilation and has the same structure as the starting detector;
the data processing module is used for converting the pulse data of the detector into a data format which can be used by a subsequent module;
the digital timing module is used for extracting the time information of the pulse data of the start detector and the stop detector;
a classification model unit: the detector pulse classification system is used for classifying the detector pulse and marking the detector pulse as a correct case or an error case;
the coincidence logic unit is used for judging coincidence in time of the starting signal and the ending signal marked as the correct case, and calculating the time difference between the starting signal and the ending signal which accord with the time condition;
and the data analysis module is used for counting the time difference between the starting signal and the ending signal and drawing a life spectrum.
4. A method for discriminating positron annihilation lifetimes using a positron annihilation lifetime spectrometer of any of claims 1-3, comprising:
step 1, a single detector module is used for measuring gamma photons generated by a 22Na radioactive source, a lanthanum bromide crystal in the detector module is in coupling contact with a photomultiplier through silicone oil, and a digital acquisition card of a first data acquisition module acquires pulse data and transmits the pulse data to a computer for storage; processing and classifying the pulse data by using a data processing and classifying module, and classifying the pulse data into correct cases, wrong cases and cases which cannot be distinguished by using a support vector machine algorithm to learn and train so as to obtain a classification model; verifying the model by using the acquired and classified off-line data;
step 2, when positron annihilation life experiment measurement is carried out, a radioactive source and a sample form a sandwich structure, the radioactive source is positioned between two samples to be measured, and two detector modules are arranged in a right angle; one detector module is used as an initial detector for measuring gamma photons of 1.28MeV generated by decay of a radioactive source, and the other detector module is used as a termination detector for measuring gamma photons of 0.511MeV generated by positron annihilation;
step 3, the pulses of the two detectors are simultaneously input into a data acquisition card of a second data acquisition module through a coaxial cable, and the data acquisition card acquires data and then transmits the data to a computer for processing; the pulse data of the detector is classified by a classification model unit, is marked as a correct case and an error case, and meanwhile, the time is calculated by a digital timing module; and inputting the data into a coincidence logic unit, and when the time difference of the two paths of signals is smaller than 100ns and is the correct case, forming a group of coincidence cases, and performing statistical processing on the time difference of the coincidence cases to obtain a positron life spectrum.
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