Batch calibration method and device based on GE function

Abstract

The invention provides a batch calibration method and device based on a GE function, and relates to the field of radiation detection. The method comprises the following steps: performing energy calibration on target to-be-detected equipment according to a preset acquisition mode under a standard source, and obtaining first energy spectrum data corresponding to the target to-be-detected equipment based on the energy calibration; performing dead time correction operation on the first energy spectrum data; inputting the first energy spectrum data after the dead time correction into a GE energy spectrum correction model, and outputting second energy spectrum correction data based on the GE energy spectrum correction model; integrating the second energy spectrum correction data based on a polynomial weight function to calculate a dose rate corresponding to the target to-be-detected equipment; and on the basis of the corresponding dosage rate of the to-be-detected equipment, carrying out batch calibration on the plurality of to-be-detected equipment. The problem that the whole calibration process consumes a large amount of time due to the fact that data collection, analysis and calculation of GE function parameters are needed for multiple times in the calibration process of a traditional radiation calibration method is solved.

Description

Technical Field

[0001] The present application relates to the field of radiation detection, and in particular to a batch calibration method and device based on GE function. Background Art

[0002] Calibration methods for radiation measurement equipment have been widely used across industries, particularly in healthcare, industry, and environmental monitoring. With the continuous advancement of technology, radiation dose measurement technology is moving towards higher accuracy, faster processing speeds, and greater automation. Traditional calibration methods typically rely on manual sampling and calculations, which not only require significant time and human resources but are also susceptible to operator error.

[0003] During the mass production of devices, traditional radiometric calibration methods face significant technical bottlenecks. The energy spectrum acquisition time for a single device is long, and the calibration process requires multiple steps of data acquisition, analysis, and calculation of GE function parameters, which consumes a significant amount of time.

[0004] Therefore, there is an urgent need for a batch calibration method and device based on GE function. Summary of the Invention

[0005] The present application provides a batch calibration method and device based on GE function, which solves the problem that the traditional radiation calibration method consumes a lot of time due to the need for multiple data collection, analysis and calculation of GE function parameters during the calibration process.

[0006] In a first aspect of the present application, a batch calibration method based on a GE function is provided, the method comprising: performing energy calibration on a target device to be detected according to a preset acquisition method under a standard source, and obtaining first energy spectrum data corresponding to the target device to be detected based on the energy calibration, where the target device to be detected is any one of a plurality of devices to be detected; performing a dead time correction operation on the first energy spectrum data; inputting the first energy spectrum data after the dead time correction into a GE energy spectrum correction model, and outputting second energy spectrum correction data based on the GE energy spectrum correction model; integrating the second energy spectrum correction data based on a polynomial weight function to calculate a dose rate corresponding to the target device to be detected; and performing batch calibration on a plurality of devices to be detected based on the corresponding dose rates of the devices to be detected.

[0007] Optionally, the target device to be detected is energy calibrated according to a preset acquisition method under a standard source, specifically including: comparing the energy spectrum channel address corresponding to the characteristic energy peak of the standard source with the preset target channel address; adjusting the multi-channel amplification factor of the target device to be detected according to the comparison result so that the characteristic energy peak is located at the preset target channel address for energy calibration.

[0008] Optionally, a dead time correction operation is performed on the first energy spectrum data, specifically including: combining a preset single pulse dead time parameter and based on the output count rate corresponding to the first energy spectrum data, performing a nonlinear inversion calculation on the output count rate using the Lambert W function to obtain the corresponding input count rate; and performing a dead time correction operation on the first energy spectrum data based on the input count rate.

[0009] Optionally, before inputting the first energy spectrum data after dead time correction into the GE energy spectrum correction model and outputting the second energy spectrum correction data based on the GE energy spectrum correction model, it is necessary to construct a GE energy spectrum correction model, specifically including: extracting the count value at each characteristic energy peak in the first energy spectrum data after dead time correction based on the characteristic energy peak position of the standard source and the corresponding theoretical dose rate data; using a polynomial regression method to fit the functional relationship between the count value at each characteristic energy peak and the corresponding dose rate to obtain the polynomial coefficients of the GE function; and constructing the GE energy spectrum correction model based on the functional relationship and the polynomial coefficients.

[0010] Optionally, the second energy spectrum correction data is integrated based on a polynomial weight function to calculate the dose rate corresponding to the target device to be detected, specifically including: multiplying the count value at each characteristic energy peak in the second energy spectrum data by the value of the polynomial weight function at the corresponding energy channel channel by channel; and performing a weighted integration operation on the product within a set energy range to calculate the dose rate corresponding to the target device to be detected.

[0011] Optionally, a weighted integral operation is performed on the product result within a set energy range to calculate the dose rate corresponding to the target device to be detected, specifically including: calculating the dose rate corresponding to the target device to be detected according to the following formula:

[0012] in, is the dose rate, is the characteristic energy peak, is the count value at each characteristic energy peak in the second energy spectrum data, are the polynomial coefficients obtained by fitting, is the order of the polynomial, is the index of the power in the polynomial, is the set lower limit of the integral energy, The set upper limit of integral energy.

[0013] Optionally, based on the corresponding dose rates of the devices to be tested, batch calibration is performed on multiple devices to be tested, specifically including: collecting multiple actual dose points under a standard dose field and obtaining the displayed dose values ​​corresponding to the devices to be tested; constructing a linear correction model based on the multiple actual dose points and the displayed dose values; and converting the displayed dose rates of multiple devices to be tested based on the linear correction model for batch calibration.

[0014] In a second aspect of the present application, a batch calibration device based on GE function is provided, the device includes an acquisition module and a processing module, wherein: The acquisition module is used to perform energy calibration on the target device to be detected according to a preset acquisition method under a standard source, and obtain first energy spectrum data corresponding to the target device to be detected based on the energy calibration. The target device to be detected is any one of the multiple devices to be detected.

[0015] A processing module is used to perform a dead time correction operation on the first energy spectrum data; input the first energy spectrum data after the dead time correction into the GE energy spectrum correction model, and output second energy spectrum correction data based on the GE energy spectrum correction model; integrate the second energy spectrum correction data based on a polynomial weight function to calculate the dose rate corresponding to the target device to be detected; and batch calibrate multiple devices to be detected based on the corresponding dose rates of the devices to be detected.

[0016] In the third aspect of the present application, an electronic device is provided, including a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device performs any of the methods described above.

[0017] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and the computer program is executed by a processor to perform any of the above methods.

[0018] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: 1. Under the standard source, the target device to be detected is energy calibrated according to the preset acquisition method, and the first energy spectrum data corresponding to the target device to be detected is obtained based on the energy calibration, where the target device to be detected is any one of the multiple devices to be detected; a dead time correction operation is performed on the first energy spectrum data; the first energy spectrum data after the dead time correction is input into the GE energy spectrum correction model, and the second energy spectrum correction data is output based on the GE energy spectrum correction model; the second energy spectrum correction data is integrated based on the polynomial weight function to calculate the dose rate corresponding to the target device to be detected; based on the dose rate corresponding to the device to be detected, a batch of multiple devices to be detected are calibrated, thereby significantly reducing the operational steps of separate spectrum acquisition and fitting for each device, greatly compressing the overall calibration cycle, effectively reducing the human participation and calculation complexity, and realizing fast, low-cost, standardized dose calibration of large quantities of equipment while ensuring the controllable accuracy of dose rate measurement, thereby improving the efficiency and economy in the equipment production process.

[0019] 2. Compare the energy spectrum channel address corresponding to the characteristic energy peak of the standard source with the preset target channel address; adjust the multi-channel amplification factor of the target device to be tested based on the comparison results so that the characteristic energy peak is located at the preset target channel address for energy calibration, thereby achieving a unified mapping benchmark for different devices on the energy channel axis, ensuring that subsequent energy spectrum data is comparable and transferable across devices, and providing a standardized input basis for the construction and batch calibration of the GE function model.

[0020] 3. Combined with the preset single-pulse dead time parameters and based on the output count rate corresponding to the first energy spectrum data, the output count rate is nonlinearly inverted using the Lambert W function to obtain the corresponding input count rate. Based on the input count rate, a dead time correction operation is performed on the first energy spectrum data to compensate for the count loss caused by the pulse pile-up effect under high count rate conditions, restore energy spectrum data close to the actual physical response, and improve the accuracy and stability of subsequent dose rate calculations. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 Schematic diagram of a batch calibration method based on GE function provided in an embodiment of the present application; Figures 2a to 2d This is a dose rate calibration and correction diagram provided in an embodiment of the present application; Figure 3 Schematic diagram of a module of a batch calibration device based on GE function provided in an embodiment of the present application; Figure 4 This is a structural diagram of an electronic device provided in an embodiment of the present application.

[0022] Explanation of the reference numerals: 31, acquisition module; 32, processing module; 401, processor; 402, communication bus; 403, user interface; 404, network interface; 405, memory. DETAILED DESCRIPTION

[0023] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0024] The terms used in the following examples of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification of the present application, the singular expressions "a", "an", "said", "above", "the", and "this" are intended to include plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in the present application refers to and includes any or all possible combinations of one or more of the listed items.

[0025] In the following, the terms "first" and "second" are used for descriptive purposes only and should not be understood to imply or suggest relative importance or implicitly indicate the number of the technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of this application, unless otherwise specified, "plurality" means two or more.

[0026] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.

[0027] Please refer to Figure 1 , which shows a flow chart of a batch calibration method based on GE function provided in an embodiment of the present application, the flow chart mainly includes the following steps: S101 to S105.

[0028] Step S101 : energy calibration is performed on a target device to be detected according to a preset acquisition method under a standard source, and first energy spectrum data corresponding to the target device to be detected is acquired based on the energy calibration.

[0029] Specifically, a radioactive nuclide with a clear characteristic gamma energy peak in the standard source is placed at the measurement position of the target device to be detected, and the gamma energy spectrum is collected according to a preset collection method such as a unified collection time, sampling time interval, distance and detection angle; after completing the preliminary spectrum collection, the position of the corresponding characteristic energy peak in the energy spectrum (i.e., its peak channel number on the channel axis) is extracted, and the peak channel number is compared with the theoretical energy value of the standard source; if the characteristic peak position is not aligned with the preset target channel, the multi-channel amplification factor of the target device to be detected is adjusted according to the difference (for example, the amplifier gain or the system ADC parameters are adjusted), the energy spectrum is re-collected and compared again until the characteristic peak position is adjusted to within the preset channel tolerance range, thereby completing the linear or nonlinear calibration of the energy axis; after the calibration is completed, the full spectrum measurement of the standard source is performed again with the same collection parameters to obtain the first energy spectrum data covering the set energy range, and the first energy spectrum data is the original input relied on for the subsequent dose rate calculation. Among them, the "target device to be tested" refers to a device selected arbitrarily from the "multiple devices to be tested", which is used to perform a complete energy calibration and GE function construction process under a standard radiation source environment. Multiple devices to be tested usually refer to a group of gamma-ray detection devices in the same production batch or with the same structural configuration. These devices are highly consistent in terms of material selection, manufacturing parameters, detection crystals and front-end circuits. Therefore, a representative metrology model can be constructed by performing energy calibration, dead time correction and GE function fitting on one of the devices (i.e., the target device to be tested). Subsequently, the metrology model can be applied to the remaining multiple devices to be tested through correction mapping to achieve batch rapid calibration, thereby significantly reducing repeated spectrum acquisition and calculation time and improving calibration efficiency. In this possible implementation, step S101 further includes: comparing the energy spectrum channel address corresponding to the characteristic energy peak of the standard source with the preset target channel address; adjusting the multi-channel amplification factor of the target device to be tested according to the comparison result so that the characteristic energy peak is located at the preset target channel address for energy calibration.

[0030] Specifically, a standard radiation source with a single or multiple characteristic γ energy spectrum peaks, such as ^137Cs, ^60Co or ^152Eu, is selected. The energy peak formed in the spectrum is used as an alignment reference. The standard source is placed at a preset reference position in front of the target device to be tested, and energy spectrum acquisition is started with a unified sampling time and spatial layout parameters. From the collected original energy spectrum, the channel position of the most significant characteristic peak, i.e., the peak position channel address, is extracted through a peak recognition algorithm. ; The system presets that the energy peak should be located in a certain target channel , in order to unify the energy axis coordinate system of all devices, if ≠ , calculate its channel offset = According to the offset, the gain coefficient of the amplifier circuit in the device is adjusted or the sampling resolution of the analog-to-digital conversion module is adjusted to correct the amplitude of channel compression or expansion; after the adjustment is completed, the energy spectrum is collected again and the above comparison process is repeated until the characteristic energy peak Stable landing on the target site The tolerance range ultimately determines the current energy-channel mapping relationship of the device, which serves as the unified energy scale benchmark for the device in subsequent GE function fitting and spectral data processing, thereby ensuring that different devices have a comparable and transferable data expression basis.

[0031] Step S102: performing a dead time correction operation on the first energy spectrum data.

[0032] Specifically, in combination with the preset single pulse dead time parameter and based on the output count rate corresponding to the first energy spectrum data, a nonlinear inversion calculation is performed on the output count rate using the Lambert W function to obtain the corresponding input count rate; and a dead time correction operation is performed on the first energy spectrum data based on the input count rate: The dead time correction operation is performed on the first energy spectrum data. Specifically, combined with the preset single pulse dead time parameter , and based on the total output count rate corresponding to the first energy spectrum data , the Lambert W function is used to perform nonlinear inversion calculation on the output count rate to obtain the corresponding input count rate , the calculation process satisfies the following relationship:

[0033] in, is the Lambert W function, which is used to solve the nonlinear distortion model caused by pulse accumulation at high counting rates; obtain the input counting rate After that, it is regarded as the real counting rate of the detection system in the ideal state without pile-up distortion. Based on this value, the counts of each energy channel in the first energy spectrum data are reverse normalized. The correction method can adopt proportional scaling or statistical expansion based on the channel response distribution, multiplying all channel counts by a unified amplification factor. / , realizing time compensation repair of full spectrum counts; finally, the energy spectrum data after dead time correction is obtained, which retains the energy distribution characteristics of the original energy spectrum while restoring the total count loss caused by the pile-up effect, providing a more realistic input basis for subsequent GE function weighted calculation.

[0034] Step S103 : inputting the first energy spectrum data after the dead time correction into the GE energy spectrum correction model, and outputting second energy spectrum correction data based on the GE energy spectrum correction model.

[0035] Specifically, based on the characteristic energy peak positions of multiple standard sources and the corresponding theoretical dose rate data, polynomial regression is used to fit the functional relationship between channel count values ​​and dose rates, a GE function model is constructed, and its polynomial coefficients are determined; the first energy spectrum data after dead time correction is used as input, and weighted processing is performed channel by channel according to the polynomial weights corresponding to each energy channel in the GE function model; the weighted channel data are integrated, and the second energy spectrum correction data representing the contribution of different energy channels to the dose is output as the basis for subsequent integral calculations.

[0036] In a possible embodiment, step S103 also includes: extracting the count value at each characteristic energy peak in the first energy spectrum data after dead time correction based on the characteristic energy peak position of the standard source and the corresponding theoretical dose rate data; using a polynomial regression method to fit the functional relationship between the count value at each characteristic energy peak and the corresponding dose rate to obtain the polynomial coefficients of the GE function; and constructing a GE energy spectrum correction model based on the functional relationship and the polynomial coefficients.

[0037] Specifically, a polynomial regression method is used to fit the functional relationship between the count value and the corresponding dose rate at each characteristic energy peak to obtain the polynomial coefficients of the GE function. Based on the functional relationship and polynomial coefficients, a GE spectrum correction model is constructed. Specifically, a standard source with multiple known γ energy peaks (such as 152Eu or 60Co) is selected. Combined with the known characteristic energy positions in the radionuclide database and the theoretical air absorption dose rate value under set geometric conditions, the corresponding peak position channel in the first energy spectrum data after dead time correction is located. The count value corresponding to each peak position is extracted to form a set of energy-count-dose rate paired samples. The count value in this sample is used as the independent variable and the corresponding dose rate as the dependent variable. A dose weight function model is constructed, and the least squares method is used for polynomial fitting. The fitting expression is:

[0038] in, is the GE function, are the polynomial coefficients obtained by fitting, is the energy corresponding to the characteristic peak, that is, the characteristic energy peak, is the order of the polynomial, representing the highest power of the constructed GE function, The index of the power in the polynomial.

[0039] Step S104 : integrating the second energy spectrum correction data based on a polynomial weight function to calculate a dose rate corresponding to the target device to be inspected.

[0040] Specifically, the count value of each energy channel in the second energy spectrum correction data is first multiplied by the corresponding polynomial weight function channel by channel; then, a weighted integral operation is performed on the product results of all channels within the set energy range to calculate the air absorption dose rate of the target equipment to be detected.

[0041] In a possible embodiment, step S104 also includes: multiplying the count value at each characteristic energy peak in the second energy spectrum data by the value of the polynomial weight function at the corresponding energy channel channel by channel; performing a weighted integration operation on the product within a set energy range to calculate the dose rate corresponding to the target device to be detected.

[0042] Specifically, the count value corresponding to each energy channel in the second energy spectrum correction data is recorded as N(E), and based on the constructed GE function model g(E)=∑_(k=0)^n a_k⋅E^k, the weight coefficient at each energy channel is calculated respectively, that is, the polynomial function is substituted into the energy value E of each channel to obtain its dose contribution weight; then, the count value N(E) of each channel is multiplied by the g(E) value of the corresponding channel one by one to form a set of dose contribution vectors; then, within the set integration interval E_min to E_max, the product values ​​of all channels are numerically integrated to accumulate the dose contributions of all channels to obtain the air absorption dose rate D of the target device within this energy range, which is calculated as follows:

[0043] in, is the dose rate, is the characteristic energy peak, is the count value at each characteristic energy peak in the second energy spectrum data, are the polynomial coefficients obtained by fitting, is the order of the polynomial, is the index of the power in the polynomial, is the set lower limit of the integral energy, The set upper limit of integral energy.

[0044] Step S105 : performing batch calibration on a plurality of devices to be tested based on the corresponding dose rates of the devices to be tested.

[0045] Specifically, the displayed dose rate of the device under test is measured under a standard source and compared with the actual dose rate to determine the relationship between the displayed and actual dose rates for each device. Based on this relationship, a correction model is established between the displayed and actual dose rates using linear regression or least squares methods to obtain a correction coefficient. This correction model is then applied to other devices under test, adjusting their displayed dose rates to calibrate and obtain accurate dose rates, thereby achieving dose rate calibration for batches of devices.

[0046] In a possible embodiment, step S105 also includes: collecting multiple actual dose points under a standard dose field and obtaining displayed dose values ​​corresponding to the device to be tested; constructing a linear correction model based on the multiple actual dose points and displayed dose values; and converting the displayed dose rates of the multiple devices to be tested based on the linear correction model for batch calibration.

[0047] Specifically, multiple actual dose points with known true dose rates are first selected in the standard dose field. These points are measured using multiple devices to be tested, and the dose values ​​displayed by the devices (displayed dose rates) are recorded. The true dose rate at each actual dose point is then paired with the dose value displayed by the corresponding device. Based on these data points, a linear relationship model between the displayed dose rate and the true dose rate is constructed using the least squares method or linear regression method. This model can be expressed as:

[0048] in, is the true dose rate, Display dose values ​​for the device, and is the linear correction coefficient obtained through regression analysis. Finally, the linear correction model is used to convert the displayed dose rates of other devices to be tested to obtain their corresponding true dose rates, thereby completing batch calibration of multiple devices.

[0049] Through the above method, although the accuracy of the GE function is reduced, the equipment performance still meets the indicators and greatly reduces the labor and time costs. The test results show that the dose rate accuracy meets the deviation within 25%. Please refer to Figures 2a to 2d ,in, Figures 2a to 2d A dose rate calibration and correction diagram provided in an embodiment of the present application is shown. Figures 2a to 2d In the figure, the measurement errors of four different detectors before and after dose rate calibration and correction, as well as the comparison of fitting curves, are shown during the batch calibration process of the GE function. Each figure corresponds to a detector with a different number, which proves the universality and calibration effect of the GE function calibration model proposed in this application among multiple devices.

[0050] Please refer to Figure 3 , which shows a module schematic diagram of a batch calibration device based on GE function provided in an embodiment of the present application, the device includes an acquisition module 31 and a processing module 32, wherein, The acquisition module 31 is used to perform energy calibration on the target device to be detected according to a preset acquisition method under a standard source, and obtain first energy spectrum data corresponding to the target device to be detected based on the energy calibration. The target device to be detected is any one of the multiple devices to be detected.

[0051] The processing module 32 is used to perform a dead time correction operation on the first energy spectrum data; input the first energy spectrum data after the dead time correction into the GE energy spectrum correction model, and output second energy spectrum correction data based on the GE energy spectrum correction model; integrate the second energy spectrum correction data based on a polynomial weight function to calculate the dose rate corresponding to the target device to be detected; and batch calibrate multiple devices to be detected based on the corresponding dose rates of the devices to be detected.

[0052] In one possible embodiment, the acquisition module 31 is used to perform energy calibration on the target device to be detected according to a preset acquisition method under a standard source, specifically including: comparing the energy spectrum channel address corresponding to the characteristic energy peak of the standard source with the preset target channel address; adjusting the multi-channel amplification factor of the target device to be detected according to the comparison result so that the characteristic energy peak is located at the preset target channel address for energy calibration.

[0053] In one possible embodiment, the processing module 32 is used to perform a dead time correction operation on the first energy spectrum data, specifically including: combining a preset single pulse dead time parameter and based on the output count rate corresponding to the first energy spectrum data, using the Lambert W function to perform a nonlinear inversion calculation on the output count rate to obtain the corresponding input count rate; performing a dead time correction operation on the first energy spectrum data based on the input count rate.

[0054] In one possible embodiment, the processing module 32 is used to construct a GE energy spectrum correction model before inputting the first energy spectrum data after dead time correction into the GE energy spectrum correction model and outputting the second energy spectrum correction data based on the GE energy spectrum correction model, specifically including: extracting the count value at each characteristic energy peak in the first energy spectrum data after dead time correction based on the characteristic energy peak position of the standard source and the corresponding theoretical dose rate data; using a polynomial regression method to fit the functional relationship between the count value at each characteristic energy peak and the corresponding dose rate to obtain the polynomial coefficients of the GE function; and constructing the GE energy spectrum correction model based on the functional relationship and the polynomial coefficients.

[0055] In one possible embodiment, the processing module 32 is used to integrate the second energy spectrum correction data based on a polynomial weight function to calculate the dose rate corresponding to the target device to be detected, specifically including: multiplying the count value at each characteristic energy peak in the second energy spectrum data by the value of the polynomial weight function at the corresponding energy channel channel by channel; performing a weighted integration operation on the product within a set energy range to calculate the dose rate corresponding to the target device to be detected.

[0056] In one possible embodiment, the processing module 32 is configured to perform a weighted integral operation on the product result within a set energy range to calculate the dose rate corresponding to the target device to be inspected, specifically including: calculating the dose rate corresponding to the target device to be inspected according to the following formula:

[0057] in, is the dose rate, is the characteristic energy peak, is the count value at each characteristic energy peak in the second energy spectrum data, are the polynomial coefficients obtained by fitting, is the order of the polynomial, is the index of the power in the polynomial, is the set lower limit of the integral energy, The set upper limit of integral energy.

[0058] In one possible embodiment, the processing module 32 is used to perform batch calibration on multiple devices to be detected based on the corresponding dose rates of the devices to be detected, specifically including: collecting multiple actual dose points under a standard dose field and obtaining the displayed dose values ​​corresponding to the devices to be detected; constructing a linear correction model based on the multiple actual dose points and the displayed dose values; and converting the displayed dose rates of the multiple devices to be detected based on the linear correction model for batch calibration.

[0059] It should be noted that the above embodiments provide devices that implement their functions using only the division of the above functional modules as examples. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiments are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0060] This application also provides an electronic device. Figure 4 , Figure 44 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present application. The electronic device may include: at least one processor 401, at least one communication bus 402, a user interface 403, at least one network interface 404, and a memory 405.

[0061] The communication bus 402 is used to implement the connection and communication between these components.

[0062] The user interface 403 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 403 may also include a standard wired interface and a wireless interface.

[0063] The network interface 404 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0064] Processor 401 may include one or more processing cores. Using various interfaces and circuits, processor 401 connects to various components within the server. It executes instructions, programs, code sets, or instruction sets stored in memory 405, as well as accesses data stored in memory 405, to perform various server functions and process data. Optionally, processor 401 may be implemented using at least one of the following hardware forms: a digital signal processing (DSP), a field-programmable gate array (FPGA), or a programmable logic array (PLA). Processor 401 may integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. The CPU primarily processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing content displayed on the display screen; and the modem handles wireless communications. It is understood that the modem may also be implemented independently of the processor 401 and implemented as a separate chip.

[0065] Among them, the memory 405 may include a random access memory (RAM) or a read-only memory (Read-Only Memory). Optionally, the memory 405 includes a non-transitory computer-readable storage medium. The memory 405 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 405 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 405 may also optionally be at least one storage device located away from the aforementioned processor 401. Refer to Figure 4 , the memory 405 as a computer storage medium may include an operating system, a network communication module, a user interface module and a batch calibration application based on GE functions.

[0066] exist Figure 4 In the electronic device shown, the user interface 403 is mainly used to provide an input interface for the user and obtain the data input by the user; and the processor 401 can be used to call the batch calibration application based on the GE function stored in the memory 405. When executed by one or more processors 401, the electronic device executes one or more of the methods described in the above embodiments. It should be noted that for the aforementioned method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should know that this application is not limited to the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for this application.

[0067] The present application also provides a computer-readable storage medium storing instructions, which, when executed by one or more processors, enable an electronic device to execute one or more of the methods described in the above embodiments.

[0068] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0069] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are merely schematic, such as the division of units, which is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interface, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0070] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0071] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0072] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of this application, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the method of this application. The aforementioned memory includes various media that can store program code, such as USB flash drives, mobile hard drives, magnetic disks, or optical disks.

[0073] The above descriptions are merely exemplary embodiments disclosed in this application and are not intended to limit the scope of this application. That is, any equivalent changes and modifications made based on the teachings disclosed in this application are still within the scope of this application.

[0074] This application is intended to cover any modifications, uses or adaptations disclosed in this application, which follow the general principles disclosed in this application and include common knowledge or customary technical means in the technical field not disclosed in this application.

Claims

1. A batch calibration method based on GE function, characterized in that: The method comprises: Performing energy calibration on a target device to be detected according to a preset acquisition method under a standard source, and acquiring first energy spectrum data corresponding to the target device to be detected based on the energy calibration, wherein the target device to be detected is any one of the multiple devices to be detected; performing a dead time correction operation on the first energy spectrum data; inputting the first energy spectrum data after the dead time correction into a GE energy spectrum correction model, and outputting second energy spectrum correction data based on the GE energy spectrum correction model; Integrating the second energy spectrum correction data based on a polynomial weight function to calculate a dose rate corresponding to the target device to be inspected; Based on the dose rates corresponding to the devices to be detected, batch calibration is performed on a plurality of the devices to be detected.

2. The method according to claim 1, characterized in that The energy calibration of the target device to be detected according to a preset acquisition method under the standard source specifically includes: Comparing the energy spectrum channel address corresponding to the characteristic energy peak of the standard source with the preset target channel address; The multi-channel amplification factor of the target device to be detected is adjusted according to the comparison result so that the characteristic energy peak is located at the preset target channel address to perform the energy calibration.

3. The method according to claim 1, characterized in that The performing of the dead time correction operation on the first energy spectrum data specifically includes: In combination with a preset single pulse dead time parameter and based on the output count rate corresponding to the first energy spectrum data, a nonlinear inversion calculation is performed on the output count rate using a Lambert W function to obtain a corresponding input count rate; The dead time correction operation is performed on the first energy spectrum data based on the input count rate.

4. The method according to claim 1, wherein Before inputting the first energy spectrum data after the dead time correction into the GE energy spectrum correction model and outputting the second energy spectrum correction data based on the GE energy spectrum correction model, it is necessary to construct the GE energy spectrum correction model, which specifically includes: extracting the count value at each characteristic energy peak in the first energy spectrum data after dead time correction based on the characteristic energy peak position of the standard source and the corresponding theoretical dose rate data; A polynomial regression method is used to fit the functional relationship between the count value at each characteristic energy peak and the corresponding dose rate to obtain the polynomial coefficients of the GE function; The GE energy spectrum correction model is constructed based on the functional relationship and the polynomial coefficients.

5. The method according to claim 1, characterized in that The integrating the second energy spectrum correction data based on the polynomial weight function to calculate the dose rate corresponding to the target device to be detected specifically includes: Multiplying the count value at each characteristic energy peak in the second energy spectrum data by the value of the polynomial weight function at the corresponding energy channel channel by channel; A weighted integration operation is performed on the product result within a set energy range to calculate the dose rate corresponding to the target device to be inspected.

6. The method according to claim 5, characterized in that The weighted integration operation is performed on the product result within a set energy range to calculate the dose rate corresponding to the target device to be detected, specifically including: The dose rate corresponding to the target device to be detected is calculated according to the following formula: ； in, is the dose rate, is the characteristic energy peak, is the count value at each characteristic energy peak in the second energy spectrum data, are the polynomial coefficients obtained by fitting, is the order of the polynomial, is the index of the power in the polynomial, is the set lower limit of the integral energy, The set upper limit of integral energy.

7. The method according to claim 1, characterized in that The batch calibration of the plurality of devices to be detected based on the dose rates corresponding to the devices to be detected specifically includes: Collecting multiple actual dose points in a standard dose field and obtaining the displayed dose value corresponding to the device to be tested; constructing a linear correction model according to a plurality of the actual dose points and the displayed dose values; The displayed dose rates of the plurality of devices to be detected are converted based on the linear correction model to perform the batch calibration.

8. A batch calibration device based on GE function, characterized in that: The device includes an acquisition module and a processing module, wherein: The acquisition module is configured to perform energy calibration on a target device to be detected according to a preset acquisition method under a standard source, and acquire first energy spectrum data corresponding to the target device to be detected based on the energy calibration, wherein the target device to be detected is any one of the multiple devices to be detected; The processing module is used to perform a dead time correction operation on the first energy spectrum data; input the first energy spectrum data after dead time correction into a GE energy spectrum correction model, and output second energy spectrum correction data based on the GE energy spectrum correction model; integrate the second energy spectrum correction data based on a polynomial weight function to calculate the dose rate corresponding to the target device to be detected; and batch calibrate multiple devices to be detected based on the dose rate corresponding to the device to be detected.

9. An electronic device, characterized in that: The electronic device comprises a processor, a communication bus, a user interface, a network interface and a memory, wherein the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is performed.

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