WO2024057514A1 - 放射能分析装置及び放射能分析方法 - Google Patents

放射能分析装置及び放射能分析方法 Download PDF

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Publication number
WO2024057514A1
WO2024057514A1 PCT/JP2022/034696 JP2022034696W WO2024057514A1 WO 2024057514 A1 WO2024057514 A1 WO 2024057514A1 JP 2022034696 W JP2022034696 W JP 2022034696W WO 2024057514 A1 WO2024057514 A1 WO 2024057514A1
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radiation
signal
inverse problem
radioactivity
problem calculation
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French (fr)
Japanese (ja)
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理 笹野
真照 林
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Mitsubishi Electric Corp
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Mitsubishi Electric Corp
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01T—MEASUREMENT OF NUCLEAR OR X-RADIATION
    • G01T1/00—Measuring X-radiation, gamma radiation, corpuscular radiation, or cosmic radiation
    • G01T1/16—Measuring radiation intensity
    • G01T1/167—Measuring radioactive content of objects, e.g. contamination
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E30/00—Energy generation of nuclear origin
    • Y02E30/30—Nuclear fission reactors

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  • the present disclosure relates to a radioactivity analysis device and a radioactivity analysis method.
  • a radiation detector measures the energy distribution of radiation emitted from the measurement target, and based on the measurement results, the radionuclide that is the radioactive substance contained in the measurement target is determined. identification and calculation of the radioactivity intensity [Bq (becquerel)] of the radionuclide.
  • Non-Patent Document 1 describes a mathematical method for calculating the energy spectrum of incident radiation using a response function of a radiation detector based on the output wave height distribution (i.e., pulse height distribution) of a pulse signal output from a radiation detector. It explains the unfolding method. Furthermore, Patent Document 1 describes a method of improving the accuracy of estimation results by increasing the number of response functions used in inverse problem calculations.
  • the radioactivity analysis method described above has a problem in that the accuracy of radioactivity analysis is low when the measurement target contains radionuclides that emit multiple types of radiation.
  • the present disclosure has been made to solve the above problems, and aims to provide a radioactivity analysis device and a radioactivity analysis method that have high accuracy in radioactivity analysis.
  • the radioactivity analyzer of the present disclosure includes a radiation detection unit that detects radiation emitted from a measurement target and outputs a first signal based on the radiation, and indicates the type of the radiation based on the first signal.
  • a radiation line type determination unit that determines the radiation line type and outputs a second signal including information indicating the radiation line type;
  • an inverse problem calculation algorithm selection unit that selects an inverse problem calculation algorithm based on the inverse problem calculation algorithm; and an inverse problem calculation using the selected inverse problem calculation algorithm and a response function of the radiation detection unit stored in advance in a storage device.
  • the method further includes an inverse problem calculation unit that identifies a radionuclide included in the measurement target and calculates the radioactivity intensity of the radionuclide from the first signal and the second signal.
  • the radioactivity analysis method of the present disclosure is a method executed by a computer, in which the first signal is output from a radiation detection unit that detects radiation emitted from a measurement target and outputs a first signal based on the radiation. a step of determining a radiation line type indicating the type of radiation based on the first signal and outputting a second signal including information indicating the radiation line type, and storing the information in advance in a storage device.
  • radioactivity analysis device and radioactivity analysis method of the present disclosure highly accurate radioactivity analysis can be performed.
  • FIG. 1 is a block diagram schematically showing the configuration of a radioactivity analyzer according to Embodiment 1.
  • FIG. FIG. 3 is a diagram showing the wave height (that is, energy) distribution of pulse signals output from the detector of the radiation detection unit for each radiation line type indicating the type of radiation.
  • 1 is a diagram showing a hardware configuration of a radioactivity analyzer according to Embodiment 1.
  • FIG. 3 is a flowchart showing a radioactivity analysis method according to Embodiment 1.
  • FIG. FIG. 2 is a block diagram schematically showing the configuration of a radioactivity analyzer according to Embodiment 2.
  • FIG. FIG. 3 is a block diagram schematically showing the configuration of a radioactivity analyzer according to Embodiment 3.
  • FIG. 3 is a diagram showing the rise and decay characteristics of the amplitude of a pulse signal output from a detector of a radiation detection unit for each type of radiation line.
  • FIG. 3 is a block diagram schematically showing the configuration of a radioactivity analyzer according to Embodiment 4.
  • FIG. (A) to (C) are schematic diagrams showing trajectory shapes in a detector of a radiation detection unit for each radiation line type.
  • FIG. 3 is a block diagram schematically showing the configuration of a radioactivity analyzer according to Embodiment 5.
  • FIG. FIG. 3 is a diagram showing the relationship between the brightness value and the spread of a locus shape in a position detection type detector of a radiation detection unit.
  • FIG. 1 is a block diagram schematically showing the configuration of a radioactivity analyzer 1 according to the first embodiment.
  • the radioactivity analyzer 1 detects radiation emitted from a measurement target (also referred to as “measurement material” or “measurement object”) 70, and outputs a first signal D1 based on the detected radiation. section 10, and an information processing section that identifies radioactive substances (also referred to as “radionuclides” or “nuclides”) contained in the measurement target 70 and calculates the radioactivity intensity [Bq (Becquerel)] of the radionuclides. 1a.
  • the information processing unit 1a is, for example, a computer serving as an information processing device, and is capable of implementing the radioactivity analysis method according to the first embodiment.
  • the information processing section 1a of the radioactivity analyzer 1 includes a radiation line type determination section 20, an inverse problem calculation algorithm selection section 30, and an inverse problem calculation section 50.
  • the inverse problem calculation algorithm selection unit 30 selects the radiation radiation indicated by the second signal D2 from a plurality of inverse problem calculation algorithms (for example, stored as the inverse problem calculation algorithm database 31) stored in advance in the storage device.
  • the inverse problem calculation algorithm is selected based on the radiation line type indicating the type.
  • the inverse problem calculation unit 50 performs inverse problem calculation using the selected inverse problem calculation algorithm and the response function of the radiation detection unit 10 that is stored in advance in the storage device (for example, stored as the response function database 41).
  • the radionuclide contained in the measurement target 70 is identified and the radioactivity intensity [Bq] of the radionuclide is calculated from the first signal D1 and the second signal D2.
  • the inverse problem calculation section 50 identifies each of the plurality of radionuclides and determines the radioactivity strength [Bq (becquerel)] of each of the plurality of radionuclides. ] can be calculated.
  • the inverse problem calculation unit 50 calculates the radiation intensity (for example, radiation fluence (flux) [1/(cm 2 ⁇ s)]) may be calculated.
  • the calculated radioactivity may be expressed as radioactivity concentration [Bq/g] (or [Bq/cm 3 ], etc.), which is the intensity of radioactivity per unit weight (or unit volume) of the measurement target 70. good.
  • the storage device in which the inverse problem calculation algorithm database (also referred to as "inverse problem calculation algorithm DB") 31 is stored and the storage device in which the response function database (also referred to as "response function DB") 41 is stored are as follows. They may be the same device or different devices.
  • the storage device in which the inverse problem calculation algorithm DB 31 is stored and the storage device in which the response function DB 41 is stored may be part of the radioactivity analysis device 1, but may be other devices that can communicate with the radioactivity analysis device 1. It may be part of a device (eg, a computer on a network).
  • the radioactivity analyzer 1 is connected to a display unit 60 as an information output device that presents the calculation results of the inverse problem calculation unit 50 to the user.
  • the display section 60 may be a part of the radioactivity analyzer 1.
  • the display unit 60 is, for example, a display device such as a liquid crystal display that displays images.
  • another information output device for example, a printer, etc. may be provided.
  • the radiation detection unit 10 includes a detector 11 that detects radiation emitted from a measurement target 70, an amplifier 12 that amplifies the output pulse output from the detector 11, and a waveform that shapes the output pulse output from the amplifier 12. It has a shaper 13 and a pulse height analysis section 14 that generates a pulse height distribution of output pulses output from the waveform shaper 13.
  • the detector 11 has a function of outputting signal strength (for example, pulse amplitude) according to the energy given to the detector by radiation.
  • Examples of the detector 11 that are widely used include a scintillation detector that combines a scintillator crystal and a photomultiplier, a scintillation detector that combines a scintillator crystal and a semiconductor photodetector, a semiconductor detector, or a gas detector. etc. are known.
  • the semiconductor detector is, for example, a germanium semiconductor detector.
  • a gas detector detects the number of electrons (i.e., a value proportional to the amount of energy loss of the charged particles) produced by the collision of charged particles with electrons in the gas molecules as radiation passing through the gas in the container. This is a detector that measures .
  • Gas detectors include Geiger-Mueller (GM) counters and detectors filled with gas and using an ionization chamber.
  • the amplifier 12 is a circuit that has a function of amplifying the amplitude of the output pulse, which is the signal output from the detector 11.
  • the amplifier 12 is used to amplify the output pulse to a signal strength (for example, a sufficiently large pulse amplitude) sufficient for detection by the pulse height analysis section 14 and the radiation type determination section 20 at the subsequent stage. If the output of the detector 11 is sufficiently large, there is no need to provide the amplifier 12.
  • the waveform shaper 13 is a circuit that has the function of removing noise from the signal output from the amplifier 12 or the detector 11 and adjusting the amplification factor.
  • the waveform shaper 13 is formed of an analog circuit, it is generally configured by combining an integrating circuit and a differentiating circuit.
  • the waveform shaper 13 removes noise and adjusts the amplification factor, and forms the output pulse into a waveform that allows the pulse height analysis section 14 to easily detect the pulse height.
  • the waveform shaper 13 When the waveform shaper 13 is formed by a digital circuit, it digitally converts the signal output from the previous stage by analog-to-digital conversion, removes noise and adjusts the amplification factor by a digital filter, and converts the signal into a digital waveform-shaped signal. Perform pulse processing.
  • the pulse height analyzer 14 creates a frequency distribution of the peak values of the output pulses output from the waveform shaper 13 or a frequency distribution of the time widths of the output pulses.
  • the pulse height analyzer 14 acquires the wave height of the output pulse by combining a circuit that holds the peak value of the output pulse and analog-to-digital conversion.
  • the wave height of the output pulse is obtained by combining a circuit that converts the rise and fall times of the output pulse into voltage and analog-to-digital conversion.
  • the pulse height analyzer 14 obtains the wave height of the output pulse from the amplitude or time width of the output pulse processed by the digital filter.
  • the pulse height analysis unit 14 creates a frequency distribution from the wave heights of the acquired output pulses.
  • FIG. 2 is a diagram showing the wave height (that is, energy) distribution of the pulse signal output from the radiation detection unit 10 for each radiation line type.
  • the measured wave height distribution may be converted into an energy distribution.
  • the radiation type is one or more of ⁇ rays, ⁇ rays, and ⁇ rays.
  • the radiation type determining unit 20 has a function of detecting the type of radiation (that is, the radiation type) emitted from the measurement object 70 from the pulse height distribution or energy distribution obtained by the pulse height analysis unit 14.
  • alpha rays ( ⁇ rays) detected by the radiation detection unit 10 are generally emitted from alpha ray emitting nuclides and have energy of 4 MeV or more.
  • plutonium-238 ( 238 Pu) emits ⁇ -rays with an energy of 5.50 MeV and ⁇ -rays with an energy of 5.46 MeV.
  • Plutonium-239 ( 239 Pu) emits ⁇ -rays with an energy of 5.16 MeV.
  • Americium-241 ( 241 Am) emits ⁇ -rays with an energy of 5.49 MeV.
  • Curium-244 ( 244 Cm) emits alpha rays with an energy of 5.95 MeV.
  • ⁇ rays having high energy are detected by the detector 11 so that a pulse height distribution is formed in the high energy region, as shown by the solid line in FIG.
  • the energy of the alpha rays emitted from the measurement object 70 has an asymmetrical peak structure due to energy loss in the air, but exhibits a characteristic in which a peak structure appears on the wave height distribution.
  • the radiation type determination unit 20 can determine whether the measurement target 70 contains an ⁇ -ray emitting nuclide.
  • gamma rays ( ⁇ rays) emitted from radionuclides generally have energy specific to the nuclide, and the wave height distribution of ⁇ rays has a peak structure close to a normal distribution. It has a continuous component that reflects the process of losing energy due to scattering inside or around the detector 11.
  • the energy of gamma rays of general radionuclides is 3 MeV or less, which is lower than the peak of the pulse height distribution of alpha rays.
  • thallium (Tl) emits gamma rays with an energy of 2.6 MeV.
  • Yttrium (Y) emits gamma rays with an energy of 1.8 MeV.
  • Cobalt-60 ( 60 Co) emits two gamma rays with energies of 1.3 MeV and 1.1 MeV.
  • the energy of ⁇ -rays emitted from ⁇ -ray-emitting nuclides is lower than the energy of ⁇ -rays emitted from ⁇ -ray-emitting nuclides, and the shape of the peak structure is also different (it has a steep peak structure and a continuous component). Therefore, the radiation type determining unit 20 can determine whether the measurement target 70 contains a gamma-ray emitting nuclide from the pulse height distribution.
  • Beta rays ( ⁇ rays) emitted from radionuclides are emitted during the process of beta decay, which is a type of radioactive decay of atomic nuclei.
  • beta decay electrons (ie, beta rays) and antielectron neutrinos are released.
  • beta decay the electron and antielectron neutrino share energy, so the pulse height distribution of the ⁇ ray, which is the energy of the emitted electron (i.e. ⁇ ray), is as shown by the dashed line in Figure 2. , a continuous distribution.
  • the pulse height distribution of ⁇ -rays depends on the structure of the detector 11, a peak structure appears in a low energy region, but unlike ⁇ -rays and ⁇ -rays, it does not have a peak structure in a specific energy region. Similar to the pulse height distribution of gamma rays, the pulse height distribution of ⁇ rays is a continuous distribution in the low energy region. Furthermore, in the low energy region, the pulse height distribution of ⁇ rays is larger than the pulse height distribution of ⁇ rays. Since the shape of the wave height distribution of ⁇ -rays is different from that of other radiation types, the radiation type determining unit 20 can determine whether the measurement target 70 contains a ⁇ -ray emitting nuclide from the wave height distribution.
  • the characteristics of each radiation line type in the wave height distribution can be detected, for example, by analytically detecting the above characteristics, by verifying the degree of agreement with a previously assumed wave height distribution, or by detecting the characteristics of each radiation line type based on a previously assumed wave height distribution. This can be achieved by either a method of determining the radiation line type by machine learning or a method of learning to determine the radiation line type by unsupervised machine learning.
  • the wave height distribution assumed in advance can be created by calculating the wave height distribution under various conditions. The calculation of the wave height distribution includes, for example, calculation based on radiation behavior analysis.
  • the function of performing detection using the pulse height distribution of the pulse height analysis unit 14 may be performed by the radiation type determination unit 20. In that case, it is possible not to include the pulse height analysis section 14.
  • the radiation type output from the detector 11 by determining the radiation type output from the detector 11 and selecting an inverse problem calculation algorithm to be used according to the detected radiation type, it is possible to detect a plurality of radiation types in the measurement object 70. Even if it is included, it is possible to determine the radioactivity intensity of each radiation type.
  • the characteristics of each radiation line type in the wave height distribution can be detected, for example, by analytically detecting the above characteristics, by verifying the degree of agreement with a previously assumed wave height distribution, or by detecting the characteristics of each radiation line type based on a previously assumed wave height distribution. This can be achieved by learning to determine radiation line types using machine learning or unsupervised machine learning.
  • the wave height distribution assumed in advance can be created by calculating the wave height distribution under various conditions. The calculation of the wave height distribution includes, for example, calculation based on radiation behavior analysis.
  • the inverse problem calculation unit 50 identifies the radionuclide included in the measurement target 70 from the wave height distribution and calculates the radioactivity intensity [Bq] of the radionuclide.
  • the radioactivity strength [Bq] may be expressed as radioactivity concentration.
  • the nuclide of the radionuclide contained in the measurement object 70, the radioactivity intensity [Bq] of the radionuclide, and the radioactivity concentration are known, and the measurement is performed in a state where the wave height distribution is obtained as a forward problem. be done.
  • R(E) is a response function
  • S(E) is the intensity of radioactivity (or radioactivity concentration) for each energy of the measurement target 70.
  • algorithms for performing inverse problem calculations include inverse matrix calculation, pseudo-inverse matrix calculation, deconvolution, deconvolution, and successive approximation.
  • the response function can be prepared by using, for example, a method such as radiation behavior analysis that can perform calculations that reflect the physical process of radiation.
  • M(E) and S(E) can be created by using radiation behavior analysis in the same manner as above.
  • S(E) and M(E ) can also be used to solve inverse problem operations.
  • ⁇ Inverse problem calculation algorithm selection unit 30> Next, the inverse problem calculation algorithm selection unit 30 will be explained. A plurality of inverse problem calculation algorithms that can perform inverse problem calculations as described above are prepared in advance. In some cases, it may not be possible to obtain a solution due to the nature of the matrix that is the response function R(E). The response function R(E) differs depending on the radiation type.
  • the ⁇ -ray response function R(E) is shown below as equation (2).
  • the following response function R(E) is represented by a matrix whose diagonal elements have values greater than zero.
  • the ⁇ -ray response function R(E) is shown below as equation (3).
  • the response function R(E) below is represented by a matrix whose diagonal elements are zero.
  • an analytical calculation algorithm such as an inverse matrix calculation, a pseudo-inverse matrix calculation, or a successive approximation method can be used.
  • the response function for a radiation type that is attenuated in the air, such as ⁇ -rays is a matrix that does not have diagonal components, as shown in equation (3).
  • the response function is represented by a matrix without diagonal elements, an inverse matrix operation cannot be used because an inverse matrix does not exist.
  • pseudo-inverse matrix calculations may have problems with calculation accuracy, such as the existence of solutions that are less than or equal to 0.
  • the response function can be created using the estimated spectrum from the assumed radionuclide.
  • the condition is that the response function is not a square matrix, and there is no inverse matrix, so inverse problem calculation using a network using machine learning may be able to estimate the optimal result rather than analytical inverse problem calculation.
  • the inverse problem calculation algorithm selection unit 30 optimally selects one or more calculation algorithms based on the detected radiation line type so that the solution converges or the calculation speed becomes faster.
  • the inverse problem calculation algorithm DB 31 stores a plurality of calculation algorithms that can be used in the inverse problem calculation unit 50 as described above.
  • the response function database 41 has parameters of a response matrix or machine learning network structure used for inverse problem calculation.
  • matrices such as equations (2) and (3) are held. Further, it may have information regarding a network for performing inverse problem calculation using machine learning, which is a method other than analytical calculation.
  • FIG. 3 is a diagram showing an example of the hardware configuration of the radioactivity analyzer 1 according to the first embodiment.
  • the hardware configuration of FIG. 3 is also applied to the radioactivity analyzers according to the second to fifth embodiments.
  • the radioactivity analyzer 1 includes a radiation detection section 10 and an information processing section 1a.
  • the information processing unit 1a includes a processor 101 such as a CPU (Central Processing Unit), a memory 102 that is a volatile storage device, and a nonvolatile storage device 103 such as a hard disk drive (HDD) or a solid state drive (SSD). have.
  • the memory 102 is, for example, a semiconductor memory such as a RAM (Random Access Memory).
  • the storage device 103 may store the database shown in FIG.
  • Each function of the information processing unit 1a is realized by, for example, a processing circuit.
  • the processing circuitry may be dedicated hardware or may be a processor 101 executing a program stored in memory 102.
  • the processor 101 may be any one of a processing device, an arithmetic device, a microprocessor, a microcomputer, and a DSP (Digital Signal Processor).
  • the processing circuit is dedicated hardware, the processing circuit is, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Arra), etc. y ), or a combination of any of these.
  • ASIC Application Specific Integrated Circuit
  • FPGA Field-Programmable Gate Arra
  • the radioactivity analysis program executed by the information processing unit 1a is realized by software, firmware, or a combination of software and firmware.
  • the radioactivity analysis program is installed in the information processing unit 1a via a network or from a recording medium.
  • Software and firmware are written as programs and stored in memory 102.
  • the processor 101 can realize the functions of each section shown in FIG. 1 by reading and executing the display control program stored in the memory 102.
  • the information processing unit 1a may be partially realized by dedicated hardware and partially realized by software or firmware. In this way, the processing circuit can implement each of the above-mentioned functions using hardware, software, firmware, or any combination thereof.
  • FIG. 4 is a flowchart showing the radioactivity analysis method according to the first embodiment.
  • This radioactivity analysis method is executed by a computer serving as the information processing section 1a.
  • This radioactivity analysis method includes a step S1 of receiving a first signal D1 from a radiation detection section 10 that detects radiation emitted from a measurement target 70 and outputs a first signal D1 based on the radiation; A step S2 of determining a radiation line type indicating the type of radiation based on the information and outputting a second signal D2 including information indicating the radiation line type, and a step S2 of determining a radiation line type indicating the type of radiation based on Step S3 of selecting an inverse problem calculation algorithm based on the radiation type, and executing the inverse problem calculation using the selected inverse problem calculation algorithm and the response function of the radiation detection unit 10 stored in advance in the storage device.
  • the method includes a step S4 of identifying a radionuclide included in the measurement target 70 and calculating the radioactivity intensity of the radionuclide from the first signal D1 and the second signal D2. . Further, in step S4, the intensity of radiation (for example, the fluence of radiation) may be calculated.
  • the intensity of radiation for example, the fluence of radiation
  • FIG. 5 is a block diagram schematically showing the configuration of the radioactivity analyzer 2 according to the second embodiment.
  • components that are the same as or correspond to those shown in FIG. 1 are given the same reference numerals as those shown in FIG.
  • the radioactivity analysis device 2 according to the second embodiment differs from the radioactivity analysis device 1 according to the first embodiment in that the information processing section 2a includes a response function selection section 40.
  • the radioactivity analyzer 2 includes a radiation detection unit 10 that detects radiation emitted from a measurement target 70 and outputs a first signal D1 based on the detected radiation, and a radioactivity detector 10 that detects radiation emitted from a measurement target 70 and outputs a first signal D1 based on the detected radiation. It has an information processing unit 2a that specifies the nuclide and calculates the radioactivity strength [Bq] of the radionuclide.
  • the information processing unit 2a is, for example, a computer, and is capable of implementing the radioactivity analysis method according to the second embodiment.
  • a plurality of response functions are stored in advance in a storage device (for example, the storage device 103 in FIG. 3) as the response function DB 41.
  • the response function selection unit 40 selects a response function to be used from a plurality of response functions stored in the response function DB 41 based on the second signal D2 indicating the radiation type determined by the radiation type determination unit 20. select.
  • the inverse problem calculation unit 50 performs the first inverse problem calculation by using the inverse problem calculation algorithm selected by the inverse problem calculation algorithm selection unit 30 and the response function selected by the response function selection unit 40.
  • the radionuclide contained in the measurement target 70 is identified and the radioactivity intensity [Bq] of the radionuclide is calculated from the signal D1 and the second signal D2. Further, the inverse problem calculation unit 50 may calculate the intensity of radiation from the first signal D1 and the second signal D2 by performing an inverse problem calculation.
  • a suitable inverse problem calculation algorithm is selected from a plurality of inverse problem calculation algorithms, and a suitable inverse problem calculation algorithm is selected from a plurality of response functions.
  • the second embodiment is the same as the first embodiment.
  • FIG. 6 is a block diagram schematically showing the configuration of the radioactivity analyzer 3 according to the third embodiment.
  • the radioactivity analyzer 3 according to the third embodiment has a radiation detection unit 10b including a waveform discriminator 15 that discriminates a detection signal for each type of radiation detected by the detector 11 and outputs a discrimination signal. This is different from the radioactivity analyzer 1 according to the first embodiment.
  • the waveform discriminator 15 is a circuit that allows the pulse shapes of the output of the detector 11 and the output signal output from the amplifier 12 to differ depending on the type of radiation line.
  • the radiation line type determining unit 20b determines the radiation line type based on the first signal D1 including the discrimination signal, and outputs a second signal D2 including information indicating the determined radiation line type.
  • the radioactivity analyzer 3 includes a radiation detection unit 10b that detects radiation emitted from the measurement target 70 and outputs a first signal D1 including a discrimination signal indicating the wave height distribution of the radiation, It has an information processing unit 3a that specifies the nuclide and calculates the radioactivity strength [Bq] of the radionuclide.
  • the information processing unit 3a is, for example, a computer, and is capable of implementing the radioactivity analysis method according to the third embodiment.
  • FIG. 7 is a diagram showing the rise and attenuation characteristics of the amplitude of the pulse signal output from the detector 11 of the radiation detection section 10b for each radiation line type.
  • a semiconductor is used as the substance that interacts with radiation in the detector 11
  • electrons and holes are generated inside the semiconductor by the passage of radiation, but the mobility of electrons and the mobility of holes are different. is different.
  • the pulse rises in a gentle shape see Figure 7). (indicated by a solid line).
  • the waveform discriminator 15 can detect a specific radiation line type with high accuracy by discriminating the radiation line type using such a difference in waveform shape.
  • the inverse problem calculation unit 50 solves the first problem by executing the inverse problem calculation using the inverse problem calculation algorithm selected by the inverse problem calculation algorithm selection unit 30 and the response function. From the signal D1 and the second signal D2, the radionuclide contained in the measurement target 70 is identified and the radioactivity intensity [Bq] of the radionuclide is calculated. Further, the inverse problem calculation unit 50 may calculate the intensity of radiation from the first signal D1 and the second signal D2 by performing an inverse problem calculation.
  • the radioactivity analysis device 3 and the radioactivity analysis method according to the third embodiment by selecting and using a suitable inverse problem calculation algorithm from a plurality of inverse problem calculation algorithms, It is possible to improve the accuracy of problem calculations.
  • the waveform discriminator 15 determines a specific radiation line type by the waveform discriminator 15 and combining the determination result with detection from the wave height distribution by the radiation line type determination unit 20, detection accuracy can be increased. Further, by correlating the detection result of a specific radiation type with the pulse height distribution, it is possible to extract the pulse height distribution of the specific radiation type, thereby separating the pulse height distribution and solving the inverse problem calculation.
  • Embodiment 3 is the same as Embodiment 1 or 2.
  • FIG. 8 is a block diagram schematically showing the configuration of the radioactivity analyzer 4 according to the fourth embodiment.
  • the radioactivity analysis device 4 according to the fourth embodiment has two points: the detector 11c of the radiation detection section 10c has a function of detecting a position where energy is imparted by radiation, and the radiation detection section 10c has a trajectory shape detection section 16. This is different from the radioactivity analyzer 1 according to the first embodiment.
  • the radioactivity analyzer 4 includes a radiation detection unit 10c that detects radiation emitted from the measurement target 70 and outputs a first signal D1 based on the detected radiation and a trajectory signal indicating the trajectory shape of the radiation, and
  • the information processing unit 4a specifies the radionuclides included in the radionuclide 70 and calculates the radioactivity strength [Bq] of the radionuclides.
  • the information processing unit 4a is, for example, a computer, and is capable of implementing the radioactivity analysis method according to the fourth embodiment.
  • the radiation detection unit 10c includes a detector 11c having a substance that interacts with radiation, and a circuit that detects the position of a locus to which radiation imparts energy within the interacting substance and outputs a locus shape signal indicating the shape of the locus. It has a trajectory shape detection section 16.
  • the radiation line type determining unit 20c determines the radiation line type based on the first signal D1 including the trajectory shape signal, and outputs a second signal D2 including information indicating the determined radiation line type.
  • the detector 11c has a function of detecting a position energized by radiation.
  • the detector 11c is a device in which a plurality of scintillator crystals are arranged in an array and a photodetector is placed on each of the plurality of scintillator crystals arranged in an array (for example, see Patent Document 2).
  • the detector 11c includes a plurality of regularly arranged scintillator crystals and a camera (for example, a CMOS (Complementary Metal Oxide Semiconductor) camera element, SOI (Silicon-On-Insulator)) that photographs the light generated by the scintillator crystals. An image sensor, etc.) may also be used.
  • CMOS Complementary Metal Oxide Semiconductor
  • SOI Silicon-On-Insulator
  • the detector 11c may be a device having a semiconductor radiation detector (for example, a Ge crystal) and a plurality of strip electrodes regularly arranged at intervals so as to sandwich the semiconductor radiation detector (for example, a Ge crystal). good. Further, the detector 11c may be a device that detects a position energized by radiation using a gas-type radiation detector having a plurality of wires or a plurality of regularly arranged gas-type radiation detectors.
  • FIGS. 9(A) to 9(C) are schematic diagrams showing the locus shapes in the detector 11c of the radiation detection unit 10c for each radiation line type.
  • FIGS. 9A to 9C show trajectory shapes within the detector 11c depending on the radiation type (when viewed from the side and when viewed from above).
  • radiation having a short range and giving large energy such as ⁇ -rays
  • the ⁇ ray has a long range and passes through the detector in a linear manner, so it has an elongated shape.
  • the ⁇ -rays react at one point, so they have a point-like shape with no spread.
  • the radioactivity analysis device 4 and the radioactivity analysis method according to the fourth embodiment by selecting and using a suitable inverse problem calculation algorithm from a plurality of inverse problem calculation algorithms, It is possible to improve the accuracy of problem calculations.
  • detection accuracy can be increased by determining a specific radiation line type by the trajectory shape detection unit 16 and combining the determination result with detection from the pulse height distribution by the radiation line type determination unit 20. Further, by correlating the detection result of a specific radiation type with the pulse height distribution and extracting the pulse height distribution of the specific radiation type, it is possible to separate the pulse height distribution and solve the inverse problem calculation.
  • Embodiment 4 is the same as Embodiment 1 or 2.
  • FIG. 10 is a block diagram schematically showing the configuration of the radioactivity analyzer 5 according to the fifth embodiment.
  • components that are the same as or correspond to those shown in FIG. 1 are given the same reference numerals as those shown in FIG.
  • the radioactivity analysis device 5 according to the fifth embodiment differs from the radioactivity analysis device 1 according to the first embodiment in that the radiation detection section 10d is constituted by a position detection type detector 11d.
  • the radioactivity analyzer 5 detects radiation emitted from the measurement target 70, and outputs a signal D5 indicating the brightness value and trajectory spread according to the radiation line type as a first signal based on the detected radiation. It has a radiation detection section 10d and an information processing section 5a that specifies the radionuclide included in the measurement target 70 and calculates the radioactivity intensity [Bq] of the radionuclide.
  • the information processing unit 5a is, for example, a computer, and is capable of implementing the radioactivity analysis method according to the fifth embodiment.
  • the radiation detection unit 10d includes a substance that interacts with the incident radiation, and generates a signal indicating the position where the radiation imparts energy to the substance and the amount of energy imparted to the substance within the interacting substance as a first signal D5. It has a position detection type detector 11d that outputs.
  • the radiation type determination unit 20d determines the radiation type based on a first signal D5 including a position where energy is applied to the substance and a signal indicating the amount of energy applied to the substance, and determines the determined radiation type.
  • a second signal D2 containing information indicating .
  • the position detection type detector 11d has a function of detecting a position to which energy is applied by the incident radiation, and outputs a pulse having an amplitude corresponding to the applied energy.
  • the position detection type detector 11d has a function of detecting a position to which energy is applied by the incident radiation, and has a function of outputting a luminance value of light generated at the position to which energy is applied.
  • the position detection type detector 11d outputs information on the position where energy is applied and the pulse amplitude.
  • the position detection type detector 11d outputs an image including the position where energy is applied and brightness value information.
  • the radiation type determination unit 20d determines the radiation type based on the position information and the pulse height value output from the position detection type detector 11d, or the image including the position information and the brightness value.
  • the position detection type detector 11d can be realized by the same method as the detector 11c in the fourth embodiment.
  • FIG. 11 is a diagram showing the relationship between the brightness value in the position detection type detector 11d of the radiation detection unit 10d and the spread of the trajectory shape.
  • the relationship between the brightness value and the spread of the locus shape differs depending on the radiation line type.
  • the luminance value of the light emission in the ⁇ -ray trajectory is higher than that of other radiation line types, and the spread of the brightness value (width in the horizontal axis direction in FIG. 11) is larger than that of other radiation line types.
  • the spread of the ⁇ -ray locus is higher than that of other radiation line types, and the luminance value of the emission in the ⁇ -ray locus is lower than that of other radiation line types.
  • the spread of the gamma-ray trajectory is lower than that of other radiation types, and the luminance value of the luminescence in the gamma-ray trajectory is lower than that in the alpha-ray trajectory.
  • the radiation type determination unit 20d can determine the radiation type included in the radiation emitted from the measurement object 70 and generate the second signal D2. .
  • the radioactivity analysis device 5 and the radioactivity analysis method according to the fifth embodiment by selecting and using a suitable inverse problem calculation algorithm from a plurality of inverse problem calculation algorithms, It is possible to improve the accuracy of problem calculations.
  • the pulse height distribution of the specific radiation type can be extracted, and the wave height distribution can be separated and the inverse problem can be solved. Can solve operations.
  • Embodiment 5 is the same as Embodiment 1 or 2.
  • 1 to 5 radioactivity analyzer 1a to 5a information processing section, 10, 10b, 10c, 10d radiation detection section, 11, 11b, 11c detector, 11d position detection type detector, 12 amplifier, 13 waveform shaper, 14 Wave height analysis unit, 15 Waveform discriminator, 16 Trajectory shape detection unit, 20, 20b, 20c, 20d Radiation line type determination unit, 30 Inverse problem calculation algorithm selection unit, 31 Inverse problem calculation algorithm DB, 40 Response function selection unit, 41 Response function DB, 50 inverse problem calculation section, 60 display section, 70 measurement object.

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  • Measurement Of Radiation (AREA)
PCT/JP2022/034696 2022-09-16 2022-09-16 放射能分析装置及び放射能分析方法 Ceased WO2024057514A1 (ja)

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Citations (2)

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JP2014157132A (ja) * 2013-02-18 2014-08-28 Mitsubishi Electric Corp 放射能分析装置および放射能分析方法
JP2015537215A (ja) * 2012-11-23 2015-12-24 クロメック リミテッドＫｒｏｍｅｋ Ｌｉｍｉｔｅｄ スペクトルデータの検出・操作方法

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2015537215A (ja) * 2012-11-23 2015-12-24 クロメック リミテッドＫｒｏｍｅｋ Ｌｉｍｉｔｅｄ スペクトルデータの検出・操作方法
JP2014157132A (ja) * 2013-02-18 2014-08-28 Mitsubishi Electric Corp 放射能分析装置および放射能分析方法

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