CN113721286B - Positron annihilation life spectrometer for pulse discrimination by using support vector machine - Google Patents
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- G01T—MEASUREMENT OF NUCLEAR OR X-RADIATION
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Abstract
The invention relates to a positron annihilation life spectrometer for pulse discrimination by using a support vector machine, which comprises the following components: a learning training device and a positron annihilation lifetime measurement device; the learning training device comprises a first detector module, a first data acquisition module and a processing terminal; the first detector module includes a scintillator and a photomultiplier tube; the first data acquisition module is used for digitally sampling the detector pulse to digitize the analog signal so that the analog signal 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 wrong 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 verifying 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 for pulse discrimination by using a support vector machine and a method thereof.
Background
Positron annihilation spectroscopy is widely used in research in material science. The positron is annihilated with an electron in the sample after the processes of slowing down and the like. The annihilation-generated gamma photons can reflect information such as electron density within the material. Positrons are easily captured by defects inside the material and are therefore currently the most sensitive material defect probes. The annihilation lifetime of positrons can reflect the electron concentration of annihilation positions, and further corresponding structural information can be acquired. Positron life spectroscopy is used as a nondestructive and sensitive material defect characterization means, and has unique advantages in the field of material science.
In positron lifetime measurement, 22Na was used as a positron source. 22Na releases a gamma photon of about 1.28MeV energy while undergoing positron decay, which can be considered the initiation signal for positron lifetime. Annihilation of a positron with an electron converts the annihilation into a pair of annihilation photons having energies of 0.511MeV, which are considered to be end-of-positron life signals. And measuring the time difference between the end signal and the start signal to obtain the positron life, and counting the positron life to obtain a positron life spectrum.
Conventional positron life spectrometers consist of a scintillator, a photomultiplier tube (PMT), a high voltage, constant ratio timing discriminator (CFDD), a time delay, a time-to-amplitude converter (TAC), a multichannel analyzer (MCA), and a computer. As shown in fig. 1, the two scintillation detectors respectively measure a start signal and a stop signal as a start detector and a stop detector. The signals are converted into time signals after being subjected to amplitude discrimination and timing by a constant ratio timing discriminator, the time difference of the two time signals is converted into pulse signals with amplitude linearly related to time by a time amplitude converter, and the pulse signals are acquired by a multi-channel analyzer and transmitted to a computer for analysis, so that the final positron annihilation life spectrum can be obtained.
The traditional life spectrum only carries out simple amplitude discrimination on the pulse, and distortion pulse caused by external interference cannot be discriminated, so that the life spectrum result can be influenced by fitting parameters, and the measurement precision is difficult to guarantee.
Disclosure of Invention
In order to solve the technical problems, the invention provides the positron annihilation life spectrometer for pulse discrimination by using a support vector machine, and the positron annihilation life spectrometer for pulse discrimination by using the support vector machine effectively improves the discrimination efficiency of the spectrometer on error 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 screening using a support vector machine, comprising: a learning training device and a positron annihilation lifetime measurement device;
the learning training device comprises a first detector module, a first data acquisition module and a processing terminal;
the first detector module includes a scintillator and a photomultiplier tube;
the first data acquisition module is used for digitally sampling the detector pulse to digitize the analog signal so that the analog signal 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 a correct case, a wrong case and a case which cannot be distinguished; wherein the correct case and the wrong case form a training set for subsequent training; the support vector machine training module performs learning training on the training set samples 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;
the positron life measuring device comprises an initial 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.
Further, the scintillator is selected from barium fluoride crystal, lanthanum bromide crystal, lutetium yttrium silicate crystal or plastic scintillator; the detector module receives the decay gamma photons and positron annihilation gamma photons generated by the 22Na radioactive source and converts the decay gamma photons and the positron annihilation gamma photons into electric pulse signals.
Further, in the positron lifetime measurement device:
the initial detector is used for detecting 1.28MeV gamma photons generated by decay of the radioactive source, and the structure of the initial detector is the same as that of a first detector module in the learning and training device;
the ending detector is used for detecting 0.511MeV gamma photons generated by positron annihilation, and the structure is the same as that of 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 the subsequent module;
the digital timing module is used for extracting time information of starting and stopping the pulse data of the detector;
classification model unit: for classifying the detector pulses as either correct or incorrect;
the coincidence logic unit is used for carrying out coincidence judgment on time on the starting signal and the ending signal marked as the correct instance and calculating the time difference between the starting signal and the ending signal which meet the time condition;
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 lifetime is provided, comprising the steps of:
step 1, measuring gamma photons generated by a 22Na radioactive source by using a single detector module, wherein 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, dividing the pulse data into correct cases, wrong cases and cases which cannot be distinguished, and learning and training by using a support vector machine algorithm to obtain a classifying model; and verifying the model by using the collected and classified offline data;
step 2, during 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, and two detector modules are arranged at right angles; one detector module is used as an initial detector for measuring 1.28MeV gamma photons generated by decay of a radioactive source, and the other detector is used as an end detector for measuring 0.511MeV gamma photons generated by positron annihilation;
step 3, the pulses of the two paths of detectors are simultaneously input to a data acquisition card of the 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 are classified by a classification model unit and marked as correct cases and error cases, and meanwhile, the time is calculated by a digital timing module; and inputting data into the coincidence logic unit, and when the time difference of the two paths of signals is smaller than 100ns and is the correct case, counting the time difference of the coincidence case to obtain a positron life spectrum for the group of coincidence cases.
The beneficial effects are that:
(1) According to the method, the classified waveforms are learned and trained by using a support vector machine algorithm in machine learning, unknown samples are classified, distorted pulses can be effectively screened, the measurement result is not easily influenced by fitting parameters, and the result confidence is improved.
(2) The detector pulse is directly sampled by using the data acquisition equipment, data is transmitted to the computer and is processed by using software, the hardware structure is greatly simplified, and the modularized software design concept is adopted, so that the detector pulse detector is convenient to upgrade and maintain.
Drawings
FIG. 1 is a conventional positron life spectrometer;
FIG. 2 is a learning training device of the present invention;
FIG. 3 is a positron life measuring device of the present invention;
FIG. 4 is a schematic representation of one embodiment of the present invention;
FIG. 5 is a classification sample;
fig. 6 is a schematic diagram of measurement results.
Detailed Description
The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, but not all embodiments, and all other embodiments obtained by those skilled in the art without the inventive effort based on the embodiments of the present invention are within the scope of protection of the present invention.
The invention relates to a positron annihilation life spectrometer for pulse discrimination by using a support vector machine, which comprises the following components: a learning training device and a positron annihilation lifetime measuring device.
As shown in fig. 2, the learning training device comprises a first detector module, a first data acquisition module and a processing terminal;
the first detector module includes a scintillator and a photomultiplier tube; the scintillator can be barium fluoride crystal, lanthanum bromide crystal, lutetium yttrium 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 the photons into electrical pulse signals.
The first data acquisition module is used for digitally sampling the detector pulse to digitize the analog signal so that the analog signal 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 a correct case, a wrong case and a case which cannot be distinguished; wherein the correct case and the wrong case form a training set for subsequent training; the support vector machine training module performs learning training on the training set samples 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;
according to one embodiment of the invention, the impulse signals of the detector in the positron life spectrometer are screened and classified by using a support vector machine algorithm, so that error cases are screened out, and the precision of experimental results is improved.
As shown in fig. 3, the positron life measuring device comprises 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 the radioactive source, and the structure of the initial detector is the same as that of a detector module in the learning training device.
The end detector is used for detecting 0.511MeV gamma photons generated by positron annihilation, and has the same structure as the start detector.
The data processing module is used for converting the detector pulse data into a data format which can be used by the subsequent modules.
The digital timing module is used for extracting time information of starting and stopping the pulse data of the detector.
Classification model unit: the detector pulses are classified and marked as either correct or incorrect.
The coincidence logic unit is used for carrying out coincidence judgment on time on the start signal and the end signal marked as correct cases, and calculating the time difference between the start signal and the end signal which meet the time condition.
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, the positron annihilation lifetime spectrometer utilizes two cylindrical lanthanum bromide crystals with the diameter of 25 mm and the height of 15 mm and two photomultiplier tubes, data are collected through a digital acquisition card, the data are processed through a computer terminal, and screening of a support vector machine is completed, so that a correct positron annihilation lifetime spectrum is obtained, as shown in fig. 4.
Firstly, gamma photons generated by a 22Na radioactive source are measured by using a single detector module, lanthanum bromide crystals in a first detector module are in coupling contact with a photomultiplier tube through silicone oil, and pulse data are collected by a digital collection card in a first data collection module and transmitted to a computer for storage. The pulse data is processed and classified to separate the pulse data into correct cases, incorrect cases and cases that cannot be distinguished, as shown in fig. 5. And 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 validating the model using the collected and categorized offline data.
In positron annihilation life experiment measurement, a radiation source and a sample form a sandwich structure, the radiation source is positioned between two samples to be measured, and two detector modules are arranged at right angles, so that compared with linear arrangement, the influence caused by stacking signals of two photons of 0.511MeV and 1.28MeV can be greatly reduced. One detector module served as the initial detector and measured 1.28MeV gamma photons generated by the decay of the radioactive source, and the other detector served as the final detector and measured 0.511MeV gamma photons generated by positron annihilation.
The two paths of detector module pulses are simultaneously input to the data acquisition card through the coaxial cable, and the data acquisition card acquires data and then transmits the data to the computer for processing. The detector pulse data is classified by the classification model, marked as correct cases and incorrect cases, and the time is calculated by the timing module. The data is input to the coincidence logic unit, and is a group of coincidence cases when the time difference between the two paths of signals is less than 100ns and the two paths of signals are the correct cases. The time difference according to the case is statistically processed to obtain a positron life spectrum, as shown in fig. 6.
While the foregoing has been described in relation to illustrative embodiments thereof, so as 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 is to be construed as limited to the spirit and scope of the invention as defined and defined by the appended claims, as long as various changes are apparent to those skilled in the art, all within the scope of which the invention is defined 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 measurement device;
the learning training device comprises a first detector module, a first data acquisition module and a processing terminal;
the first detector module includes a scintillator and a photomultiplier tube;
the first data acquisition module is used for digitally sampling the detector pulse to digitize the analog signal so that the analog signal 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 a correct case, a wrong case and a case which cannot be distinguished; wherein the correct case and the wrong case form a training set for subsequent training; the support vector machine training module performs learning training on the training set samples 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;
the positron life measuring device comprises an initial 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.
2. The positron annihilation lifetime spectrometer for pulse screening using a support vector machine of claim 1, wherein:
the scintillator is selected from barium fluoride crystal, lanthanum bromide crystal, lutetium yttrium silicate crystal or plastic scintillator; the detector module receives the decay gamma photons and positron annihilation gamma photons generated by the 22Na radioactive source and converts the decay gamma photons and the positron annihilation gamma photons into electric pulse signals.
3. The positron annihilation lifetime spectrometer for pulse discrimination using a support vector machine of claim 1, wherein the positron lifetime measurement device comprises:
the initial detector is used for detecting 1.28MeV gamma photons generated by decay of the radioactive source, and the structure of the initial detector is the same as that of a first detector module in the learning and training device;
the ending detector is used for detecting 0.511MeV gamma photons generated by positron annihilation, and the structure is the same as that of 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 the subsequent module;
the digital timing module is used for extracting time information of starting and stopping the pulse data of the detector;
classification model unit: for classifying the detector pulses as either correct or incorrect;
the coincidence logic unit is used for carrying out coincidence judgment on time on the starting signal and the ending signal marked as the correct instance and calculating the time difference between the starting signal and the ending signal which meet the time condition;
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 of discriminating positron annihilation lifetime using the positron annihilation lifetime spectrometer of any one of claims 1-3, comprising:
step 1, measuring gamma photons generated by a 22Na radioactive source by using a single detector module, wherein lanthanum bromide crystals in the detector module are in coupling contact with a photomultiplier through silicone oil, and pulse data are acquired by a digital acquisition card of a first data acquisition module and transmitted to a computer for storage; processing and classifying the pulse data by using a data processing and classifying module, dividing the pulse data into correct cases, wrong cases and cases which cannot be distinguished, and learning and training by using a support vector machine algorithm to obtain a classifying model; and verifying the model by using the collected and classified offline data;
step 2, during 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, and two detector modules are arranged at right angles; one detector module is used as an initial detector for measuring 1.28MeV gamma photons generated by decay of a radioactive source, and the other detector is used as an end detector for measuring 0.511MeV gamma photons generated by positron annihilation;
step 3, the pulses of the two paths of detectors are simultaneously input to a data acquisition card of the 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 are classified by a classification model unit and marked as correct cases and error cases, and meanwhile, the time is calculated by a digital timing module; and inputting data into the coincidence logic unit, and when the time difference of the two paths of signals is smaller than 100ns and is the correct case, counting the time difference of the coincidence case to obtain a positron life spectrum for the group of coincidence cases.
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