A method and device for adaptive spectrum stabilization of a gamma spectrometer

Abstract

The present invention proposes an adaptive spectrum stabilization method and device for a gamma spectrometer, comprising: when a scintillation crystal of the gamma spectrometer receives gamma rays, obtaining a spectrum line array of the gamma spectrometer, extracting the maximum value in the spectrum line array as a spectrum stabilization result, comparing the spectrum stabilization result with a preset spectrum stabilization target to see whether they are the same; if so, determining that the gamma spectrometer has been calibrated and executing a detection step; otherwise, executing a spectrum stabilization step; determining whether a difference between the spectrum stabilization result and the spectrum stabilization target is less than a preset value; if so, executing software spectrum stabilization processing, adjusting the spectrum line array by a coefficient to calibrate the spectrum stabilization result to be the same as the spectrum stabilization target, executing a detection step; otherwise, executing hardware spectrum stabilization processing, adjusting the power supply voltage of a photomultiplier tube in the gamma spectrometer to change the field strength of the electric field inside the photomultiplier tube until the spectrum stabilization result is calibrated to be the same as the spectrum stabilization target, and executing a detection step.

Description

Technical Field

[0001] The present invention relates to the technical field of smart agricultural soil testing. The present invention performs soil nutrient data detection based on gamma spectroscopy technology, primarily for the detection of trace radionuclides contained in the soil background. Specifically, the present invention relates to a method and device for adaptive spectrum stabilization using a CPU and FPGA software, designed to address the need for spectrum stabilization after a gamma spectrometer completes preliminary channel address calculations and statistics due to channel address shifts caused by environmental changes such as temperature, humidity, and air pressure. Background Art

[0002] Soil nutrient gamma spectrum detectors usually use a detector structure of NaI, CsI or other scintillation crystals + photomultiplier tubes (PMTs) + preamplifier circuits + single-ended to differential circuits + ADCs. The principle is that when the gamma rays of the soil to be tested are incident on the NaI scintillator and interact with the NaI scintillator crystals, the secondary electrons generated ionize or excite the scintillator molecules. When de-excited, the NaI scintillator crystals emit a large number of photons. After the photons are focused on the photocathode of the photomultiplier tube, they produce photoelectrons on the photocathode through the photoelectric effect. The photoelectrons are gradually multiplied in the photomultiplier tube. The electrons multiplied by each multiplier are collected at the anode and form a detector output voltage pulse through the preamplifier circuit. After the voltage pulse passes through the signal amplification and shaping circuit and the single-ended to differential drive circuit, it enters the ADC for sampling and multi-channel pulse amplitude analysis, thereby obtaining multi-channel spectrum data (spectral line data) for gamma spectrum measurement.

[0003] The multi-channel pulse front-end circuit comprises, in sequence, a current-to-voltage conversion circuit, a preamplifier, a single-ended-to-differential converter, an ADC sampling circuit, and an FPGA digital processing circuit. The corresponding signal conversion process for gamma ray spectrum measurement is: gamma ray energy - luminescence intensity of the NaI crystal - number of photoelectrons - current pulse - voltage pulse amplitude - pulse amplitude after single-ended signal amplification and shaping - differential signal pulse amplitude - digitized pulse amplitude. Due to the presence of various naturally occurring radionuclides, each with its own amplitude, digitization is required to cover all radionuclide amplitudes.

[0004] In practical applications, temperature affects the sensitivity and dark current of photomultiplier tubes (PMTs). The temperature effect on sensitivity can be divided into two parts: the cathode sensitivity and the multiplication stage sensitivity. The temperature characteristics of the cathode sensitivity are related to both wavelength and the type of photocathode surface. Near the critical wavelength of the long-wavelength limit, the temperature coefficient varies significantly from negative to positive.

[0005] Since the characteristics of crystals and photomultiplier tubes (PMTs) are known to be affected by the environment, the channel address of the same nuclide collected by the gamma spectrometer under different conditions will be different. Therefore, software or hardware spectrum stabilization design must be carried out according to different environments.

[0006] Currently, spectrum stabilization for gamma spectrometers has primarily focused on temperature compensation. For example, this involves recording spectral line data at different temperatures and then establishing a corresponding functional relationship. In practical applications, this involves acquiring ambient temperature data in real time. Using this known functional relationship, new spectral lines are then reverse-calculated to achieve spectrum stabilization.

[0007] The general process of spectrum stabilization of the currently commonly used gamma spectrometer is as follows: Figure 1 As shown, this method focuses solely on temperature compensation. This approach, based solely on software algorithms, can lose some signal when temperature changes significantly and the original signal deviates significantly. Furthermore, spectral drift is not limited to temperature alone but can also be caused by other factors, including but not limited to:

[0008] Humidity: The effect of humidity on photomultiplier tubes is mainly to increase the leakage current on the surface of the glass core column, and the rust on the surface of the pins will also cause poor contact, and may also cause the transmittance of the purple glass to decrease; secondly, the dirt on the surface of the pins will also cause the pins to rust and increase the leakage current.

[0009] Air pressure: Photomultiplier tubes can be used not only in an atmospheric pressure environment, but also in a reduced pressure environment. However, changes in air pressure may cause discharge between the internal leads of the photomultiplier tube. The internal vacuum degree of a general photomultiplier tube is 10 5 Pa, so in order to avoid discharge, the lead electrodes need to be kept at a sufficient distance. In addition, the design of the electrode leads of the tube base and tube holder outside the photomultiplier tube is also considered to not cause discharge in an atmospheric pressure or vacuum environment.

[0010] In summary, multi-channel digital gamma spectrometers are affected by factors such as temperature, humidity, and air pressure during real-time acquisition, resulting in significant channel offset. Without compensation, accurate data cannot be obtained. Traditional compensation methods focus solely on temperature, using software algorithms to compensate for temperature variations based on a preset temperature compensation function. This compensation approach to spectrum stabilization presents several issues: 1) While compensation is based on temperature, the actual position of the temperature sensor does not represent the temperature at the crystal or PMT, resulting in a certain degree of deviation in the temperature sensor position. 2) Spectral line drift and temperature curves reflect the relationship between equilibrium and temperature. However, the detected temperature during environmental changes may differ from the equilibrium temperature of the crystal and PMT, causing a certain degree of temperature equilibrium deviation. Temperature equilibrium can be understood as the difference between the surface and internal temperatures of the scintillation crystal during ambient temperature fluctuations, requiring time for the internal and external temperatures to reach equilibrium. 3) Compensation based solely on temperature cannot compensate for the effects of environmental factors such as humidity and air pressure, resulting in deviations between the compensated and actual values. 4) Software-based compensation alone cannot prevent situations where environmental changes cause mismatches in the front-end signal conditioning, resulting in loss of actual spectral lines or reduced resolution. Summary of the Invention

[0011] The purpose of the present invention is to propose a design method for adaptive spectrum stabilization of a gamma-ray spectrometer combining software and hardware, so as to solve the problem of spectrum line drift caused by changes in ambient temperature, humidity, air pressure, etc. The spectrum lines of the same energy are stabilized at the same channel address through the adaptive spectrum stabilization method coordinated by software and hardware, so that the digital gamma-ray spectrometer can be used in a wide range of environmental scenarios and obtain sufficient stability.

[0012] In view of the shortcomings of existing technologies, such as Figure 5 As shown, the present invention proposes an adaptive spectrum stabilization method for a gamma spectrometer, which includes:

[0013] In an initial step, when a scintillation crystal of a gamma spectrometer receives gamma rays, a spectrum line array of the gamma spectrometer is obtained, a maximum value in the spectrum line array is extracted as a spectrum stabilization result, and the spectrum stabilization result is compared with a preset spectrum stabilization target to determine whether it is the same. If the same, the gamma spectrometer is determined to be calibrated and a detection step is executed; otherwise, a spectrum stabilization step is executed;

[0014] a spectrum stabilization step, determining whether the difference between the spectrum stabilization result and the spectrum stabilization target is less than a preset value; if so, performing software spectrum stabilization processing, adjusting the spectrum line array by coefficients to calibrate the spectrum stabilization result to be the same as the spectrum stabilization target, and performing the detection step; otherwise, performing hardware spectrum stabilization processing, by regulating the power supply voltage of the photomultiplier tube in the gamma spectrometer to change the field strength of the electric field inside the photomultiplier tube, until the spectrum stabilization result is calibrated to be the same as the spectrum stabilization target, and performing the detection step;

[0015] The detection step is to use the gamma spectrometer to monitor the soil to be detected, obtain a spectral line array of the soil, and analyze the spectral line array to obtain soil nutrient data.

[0016] The adaptive spectrum stabilization method of the gamma spectrometer is described, wherein the gamma spectrometer includes an FPGA, which is used to complete pulse signal channel address calculation based on the digital signal output by the analog-to-digital converter in the gamma spectrometer to obtain a spectral line array.

[0017] In the adaptive spectrum stabilization method for a gamma spectrometer, the FPGA adjusts the spectrum line array according to the coefficients.

[0018] In the adaptive spectrum stabilization method for a gamma spectrometer, the power supply for the photomultiplier tube is provided by a digital-to-analog converter, and the FPGA regulates the power supply voltage of the photomultiplier tube by controlling the voltage output by the digital-to-analog converter.

[0019] like Figure 6 As shown, the present invention also proposes an adaptive spectrum stabilization device for a gamma spectrometer, comprising:

[0020] The initialization module obtains the spectral line array of the gamma spectrometer when the scintillation crystal of the gamma spectrometer receives gamma rays, extracts the maximum value in the spectral line array as the spectrum stabilization result, and compares the spectrum stabilization result with the preset spectrum stabilization target to see if they are the same. If they are the same, the gamma spectrometer is determined to be calibrated and the detection module is executed. Otherwise, the spectrum stabilization module is executed.

[0021] a spectrum stabilization module that determines whether the difference between the spectrum stabilization result and the spectrum stabilization target is less than a preset value. If so, software spectrum stabilization is performed to adjust the spectrum line array by coefficients to calibrate the spectrum stabilization result to the same as the spectrum stabilization target, and the detection module is executed. Otherwise, hardware spectrum stabilization is performed to adjust the power supply voltage of the photomultiplier tube in the gamma spectrometer to change the field strength of the electric field inside the photomultiplier tube until the spectrum stabilization result is calibrated to the same as the spectrum stabilization target, and the detection module is executed;

[0022] The detection module uses the gamma spectrometer to monitor the soil to be detected, obtains the spectral line array of the soil, and analyzes the spectral line array to obtain soil nutrient data.

[0023] The adaptive spectrum stabilization device of the gamma spectrometer includes an FPGA, which is used to complete pulse signal channel address calculation based on the digital signal output by the analog-to-digital converter in the gamma spectrometer to obtain a spectral line array.

[0024] The adaptive spectrum stabilization device of the gamma spectrometer, wherein the FPGA adjusts the spectral line array according to the coefficient; the power supply of the photomultiplier tube is provided by the digital-to-analog converter, and the FPGA regulates the power supply voltage of the photomultiplier tube by controlling the voltage output by the digital-to-analog converter.

[0025] The present invention also proposes an electronic device, which includes the adaptive spectrum stabilization device described above. The electronic device may be connected to an information display device, which is used to display the soil nutrient data using display parameters and attributes set by the user or through an artificial intelligence model.

[0026] The present invention also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the adaptive spectrum stabilization method are implemented.

[0027] The present invention also provides a computer program product, comprising a computer program, wherein the computer program implements the steps of the adaptive spectrum stabilization method when executed by a processor.

[0028] From the above scheme, it can be seen that the advantages of the present invention are:

[0029] The present invention combines hardware circuits with software algorithms to take into account factors such as temperature, humidity, and air pressure, quantifying spectral drift. Larger drifts are adjusted at the source of the signal by changing the PMT high voltage to accommodate subsequent signal conditioning circuits, avoiding spectral line loss or reduced resolution. Smaller drifts are stabilized by using software coefficient compensation. Compared to traditional temperature compensation methods, this method can achieve spectral stabilization based on a combination of factors such as temperature, humidity, and air pressure. Simultaneously, by adjusting the PMT high voltage, it addresses the issues of low resolution and spectral line loss associated with traditional compensation methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 Traditional temperature compensation spectrum stabilization flow chart

[0031] Figure 2 Block diagram of spectrum stabilization at large offsets

[0032] Figure 3 Block diagram of spectrum stabilization at small offsets

[0033] Figure 4 This is a structural block diagram of the device of the present invention;

[0034] Figure 5 Flow chart of the method of the present invention;

[0035] Figure 6 This is a module diagram of the device of the present invention;

[0036] Figure 7 This is a schematic structural diagram of a first electronic device of the present invention;

[0037] Figure 8 This is a schematic diagram of the application environment structure of the first electronic device of the present invention;

[0038] Figure 9 This is a schematic structural diagram of a second electronic device according to the present invention.

[0039] Reference numerals:

[0040] A-First electronic device;

[0041] Adaptive spectrum stabilization device for B-gamma spectrometer;

[0042] C-data acquisition equipment;

[0043] D-information display device;

[0044] 1000- second electronic device;

[0045] Ⅰ-computing unit;

[0046] II-ROM;

[0047] III-RAM;

[0048] IV-bus;

[0049] V-interface;

[0050] VI-input unit;

[0051] VII-output unit;

[0052] VIII-Storage medium;

[0053] IX-Communication unit. DETAILED DESCRIPTION

[0054] It should be noted that, in this application, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0055] Without further constraints, an element defined by the phrase "comprises a..." does not preclude the existence of additional identical elements in the process, method, article or apparatus that includes the element.

[0056] The processor described in the present invention is the control center of an electronic device and can be a single processor or a collective term for multiple processing elements. For example, it can be one or more central processing units (CPUs), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention, such as one or more digital signal processors (DSPs) or one or more field programmable gate arrays (FPGAs).

[0057] Optionally, the processor can perform various functions of the electronic device by running or executing a software program stored in the memory, and calling data stored in the memory.

[0058] In a specific implementation, as an embodiment, the processor may include one or more CPUs. Each of these processors may be a single-core processor (single-CPU) or a multi-core processor (multi-CPU). The processor here may refer to one or more devices, circuits, and / or processing cores for processing data (e.g., computer program instructions). Electronic devices may include: servers, desktop computers, laptops, smartphones, tablet computers, embedded computers, etc., wherein the embedded computers include vehicles and robots, etc.

[0059] The memory is used to store the software program for executing the solution of the present invention, and the execution is controlled by the processor. The specific implementation method can refer to the above method embodiment and will not be repeated here.

[0060] It should be noted that the structure of the electronic device shown in the drawings of the present invention does not constitute a limitation thereto, and the actual knowledge structure recognition device may include more or fewer components than shown in the drawings, or a combination of certain components, or a different arrangement of components.

[0061] The above embodiments can be implemented in whole or in part through software, hardware (such as circuits), firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions described in accordance with the embodiments of the present invention are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired method (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains a collection of one or more available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, or magnetic tape), an optical medium (such as a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0062] It should also be understood that the term "and / or" in this document simply describes an association between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A alone, A and B together, or B alone. A and B can be singular or plural. Furthermore, the character " / " in this document generally indicates an "or" relationship between the related objects, but it may also indicate an "and / or" relationship. For specific understanding, please refer to the context.

[0063] In this disclosure, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, "at least one of a, b, or c" can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or plural.

[0064] It should also be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0065] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is merely 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 device, 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 interface, indirect coupling or communication connection of the device or unit, which can be electrical, mechanical or other forms.

[0066] The units described as separate components may or may not be physically separate, and the 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.

[0067] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0068] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0069] Therefore, the present invention proposes a method and process for adaptive spectrum stabilization of a gamma spectrometer using a combination of software and hardware, involving software and hardware, such as Figure 4 As shown, it includes: PMT bias circuit, current-voltage conversion circuit, preamplifier circuit, single-ended to differential circuit, A / D converter, FPGA chip, high-precision DAC, PMT high-voltage control circuit, and CPU software control.

[0070] The method comprises the following steps: the current pulse output by the multiplier tube is converted into a voltage pulse signal through a current-voltage conversion circuit;

[0071] The voltage pulse signal enters the first-stage amplifier circuit, which is composed of an operational amplifier, and the amplification factor can be controlled by a digitally controlled resistor;

[0072] The single-ended to differential conversion circuit converts the voltage pulse single-ended signal after the first stage amplification into a differential signal;

[0073] The differential pulse signal enters the ADC, thereby completing the discretization of the analog voltage differential signal into a digital signal.

[0074] The FPGA uses an algorithm to calculate the pulse signal's channel address and reports it to the CPU. The CPU then statistically analyzes the result and divides it into two parts based on a preset parameter, depending on whether the deviation is greater than or less than this parameter. If the adjustment is large, feedback is sent to the FPGA to compensate for the PMT high-voltage control. If the adjustment is small, the FPGA fine-tunes the software coefficients. For example, if the input radiation peak of potassium-containing soil is at 490 (the spectral stability target), if it is measured at 496 (the spectral stability result), calibration and spectral stabilization are performed. When it stabilizes at the spectral stability target of 490, the radiation peak positions of the remaining soil elements are considered to have also been calibrated and stabilized.

[0075] To illustrate the above-mentioned features and effects of the present invention more clearly and easily, the following embodiments are specifically described below with reference to the accompanying drawings. This specification discloses one or more embodiments incorporating the features of the present invention. The disclosed embodiments are for illustrative purposes only. The scope of protection of the present invention is not limited to the disclosed embodiments; the present invention is defined by the appended claims.

[0076] 1. Spectrum stabilization process at large offsets

[0077] The FPGA reads the high-speed raw data collected by the ADC and uses a related algorithm to calculate and count spectral line data over a certain period of time. This data is then transmitted to the CPU via an interface. Due to the random statistical characteristics of the spectral lines, the CPU first filters and conditions the raw spectral lines, applying a low-pass filter using a Gaussian sliding center window without changing the center information of the channel address. The conditioned data is then passed through the K40 center peak detection algorithm to calculate the channel address of the center peak. The spectrum stabilization algorithm, which imports the configured parameters, then outputs the stabilized spectrum result. In the event of a large offset, the output instruction to modify the PMT high voltage is sent back to the FPGA. The spectral line data is an array, and the maximum value within the configured parameter range is searched. The coordinate number corresponding to the maximum value is the stabilization result. The offset is calculated by subtracting the spectrum stabilization target (also a coordinate number) set by the software from this coordinate number.

[0078] After receiving the instruction to modify the PMT high voltage, the FPGA writes the relevant parameters into the high-precision DAC module to drive the PMT high voltage module to adjust the corresponding high voltage value. The high voltage value corresponds to the field strength of the internal electric field. As the field strength increases, the amplitude increases and the channel address increases. Modifications made to the original signal are suitable for subsequent conditioning circuits to improve resolution without signal loss. Its principle block diagram is shown below. Figure 2 As shown in the green link, it requires a combination of software and hardware to complete:

[0079] First, the CPU filters the received FPGA data, then calculates the maximum value within the set area, calculates the coordinate number x1 corresponding to this maximum value, and then subtracts the system-set coordinate default number x2. If (x1-x2) is greater than the set parameter, generally 10 by default, then the CPU subtracts the preset value, such as 10, from the original PMT voltage y1, and sends the new data to the FPGA through instructions. The FPGA configures this data into the DAC, and the DAC output change is reflected in the high-voltage module, which acts on the PMT through the newly modified voltage.

[0080] If (x1-x2) is less than the set parameter, generally -10 by default, the CPU adds 10 to the original PMT voltage y1 and sends the signal data to the FPGA through instructions. The FPGA configures this data into the DAC. The DAC output change is reflected in the high-voltage module, and the high-voltage module acts on the PMT through the newly modified voltage.

[0081] 2. Spectrum stabilization process at small offsets

[0082] The FPGA reads the high-speed raw data collected by the ADC and uses a related algorithm to calculate and statistically analyze spectral line data over a specified period of time. The data is then transmitted to the CPU via an interface. Due to the random statistical nature of the spectral lines, the CPU first filters and conditions the raw spectral lines. Low-pass filtering is performed using a Gaussian sliding center window, preserving the center information of the channel address. The conditioned data is then processed using the K40 center peak detection algorithm to calculate the channel address of the center peak. The spectrum stabilization algorithm, which imports the configured parameters, then outputs the stabilized spectrum. If there is a small offset, the CPU returns the output instructions for modifying the FPGA coefficients to the FPGA.

[0083] After receiving the instruction to modify the FPGA coefficient, the FPGA writes the relevant parameters into the spectrum calculation module and adjusts the internal logic of the FPGA calculation through the coefficient to obtain higher spectrum stability. Figure 3 As shown by the green link in the figure, this spectrum stabilization link is completed by the software algorithm of the CPU and FPGA. The FPGA can now be equivalent to an amplifier algorithm module. Normally, the input is x and the output is y. In addition, a coefficient a is input. In this case, the input is x and the output is a*y. If the coefficient is 1, the original value remains unchanged. If the coefficient is greater than 1, the output increases, and if the coefficient is less than 1, the output decreases.

[0084] The following is a system embodiment corresponding to the above method embodiment. This embodiment can be implemented in conjunction with the above embodiment. The relevant technical details mentioned in the above embodiment are still valid in this embodiment and will not be repeated here to reduce repetition. Accordingly, the relevant technical details mentioned in this embodiment can also be applied to the above embodiment.

[0085] like Figure 6 As shown, the present invention also proposes an adaptive spectrum stabilization device for a gamma spectrometer, comprising:

[0086] The initialization module obtains the spectral line array of the gamma spectrometer when the scintillation crystal of the gamma spectrometer receives gamma rays, extracts the maximum value in the spectral line array as the spectrum stabilization result, and compares the spectrum stabilization result with the preset spectrum stabilization target to see if they are the same. If they are the same, the gamma spectrometer is determined to be calibrated and the detection module is executed. Otherwise, the spectrum stabilization module is executed.

[0087] a spectrum stabilization module that determines whether the difference between the spectrum stabilization result and the spectrum stabilization target is less than a preset value. If so, software spectrum stabilization is performed to adjust the spectrum line array by coefficients to calibrate the spectrum stabilization result to the same as the spectrum stabilization target, and the detection module is executed. Otherwise, hardware spectrum stabilization is performed to adjust the power supply voltage of the photomultiplier tube in the gamma spectrometer to change the field strength of the electric field inside the photomultiplier tube until the spectrum stabilization result is calibrated to the same as the spectrum stabilization target, and the detection module is executed;

[0088] The detection module uses the gamma spectrometer to monitor the soil to be detected, obtains the spectral line array of the soil, and analyzes the spectral line array to obtain soil nutrient data.

[0089] The adaptive spectrum stabilization device of the gamma spectrometer includes an FPGA, which is used to complete pulse signal channel address calculation based on the digital signal output by the analog-to-digital converter in the gamma spectrometer to obtain a spectral line array.

[0090] The adaptive spectrum stabilization device of the gamma spectrometer, wherein the FPGA adjusts the spectral line array according to the coefficient; the power supply of the photomultiplier tube is provided by the digital-to-analog converter, and the FPGA regulates the power supply voltage of the photomultiplier tube by controlling the voltage output by the digital-to-analog converter.

[0091] The present invention also proposes an electronic device, wherein the electronic device is connected to an information display device, and the information display device is used to display the soil nutrient data using display parameters and attributes set by the user or through an artificial intelligence model.

[0092] The present invention also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the adaptive spectrum stabilization method are implemented.

[0093] The present invention also provides a computer program product, comprising a computer program, wherein the computer program implements the steps of the adaptive spectrum stabilization method when executed by a processor.

[0094] like Figure 7 As shown, the present invention further proposes a first electronic device A in another embodiment, comprising the adaptive spectrum stabilization device.

[0095] like Figure 8 As shown, the first electronic device A can also be connected to the data acquisition device C and the information display device D through a wired or wireless information transmission scheme. The data acquisition device C is used to collect soil rays, and the information display device D is used to display the soil nutrient data analyzed by the present invention.

[0096] The information display device D can organize and process the data output by the first electronic device A based on the information display mechanism to improve the readability of the data output by the first electronic device A. The information display mechanism can be manually preset, for example, the data output by the first electronic device A is visually displayed, which can be based on the display parameters and / or attributes set by the user. The display parameters can be, for example, the display data range, and the display attributes can be, for example, the display font, color, whether to scroll, etc. The user is presented with the key information specified by the user, such as the spectrum array, soil nutrient data, etc. The user can understand this information more promptly without having to access the secondary page or scroll the page, saving the user's operation. Or the information display mechanism can be an artificial intelligence AI display model, which can learn the user's key information based on the user's previous usage habits, such as viewing time, number of clicks, number of edits, etc., and then automatically present the user with rich and necessary key information.

[0097] The present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a readable storage medium. When the computer program is executed by a processor, the computer can execute the adaptive spectrum stabilization method provided by the above methods.

[0098] In another embodiment, the present invention further proposes a storage medium VIII for storing a computer program for executing the adaptive spectrum stabilization method. It should be understood that the storage medium in the embodiment of the present invention may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0099] Figure 9 A schematic block diagram of a second electronic device 1000 that can be used to implement an embodiment of the present invention is shown. The second electronic device 1000 electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The second electronic device 1000 can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein. The second electronic device 1000 may be the same as or different from the first electronic device A.

[0100] The second electronic device 1000 includes a computing unit I, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory II (ROM) or a computer program loaded from a storage medium VIII into a random access memory (RAM) III. Various programs and data required for the operation of the device 1000 can also be stored in the RAM III. The computing unit I, ROM II, and RAM III are connected to each other via a bus IV. An input / output (I / O) interface V is also connected to the bus IV.

[0101] Multiple components in the second electronic device 1000 are connected to the I / O interface V, including: an input unit VI, such as a keyboard and mouse; an output unit VII, such as various types of displays and speakers; a storage medium VIII, such as a magnetic disk and optical disk; and a communication unit IX, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit IX allows the second electronic device 1000 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0102] Computing unit I can be various general and / or special processing components with processing and computing capabilities. Some examples of computing unit I include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units that run machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. Computing unit I performs the various methods and processes described above, such as method steps S1-S3. For example, in some embodiments, the method can be implemented as a computer software program that is tangibly contained in a machine-readable medium, such as a storage medium VIII. In some embodiments, part or all of the computer program can be loaded and / or installed on the device 1000 via ROM II and / or communication unit IX. When the computer program is loaded into RAM III and executed by computing unit I, one or more steps of the method described above can be performed. Alternatively, in other embodiments, computing unit I can be configured to execute the method in any other appropriate manner (e.g., by means of firmware).

[0103] Although the embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the description and implementation methods. They can be fully applied to various fields suitable for the present invention. For those familiar with the art, additional modifications can be easily implemented. Therefore, without departing from the general concept defined by the claims and the scope of equivalents, the present invention is not limited to the specific details and illustrations shown and described herein.

Claims

1. An adaptive spectrum stabilization method for a gamma spectrometer, characterized in that: include: In an initial step, when a scintillation crystal of a gamma spectrometer receives gamma rays, a spectrum line array of the gamma spectrometer is obtained, a maximum value in the spectrum line array is extracted as a spectrum stabilization result, and the spectrum stabilization result is compared with a preset spectrum stabilization target to determine whether it is the same. If the same, the gamma spectrometer is determined to be calibrated and a detection step is executed; otherwise, a spectrum stabilization step is executed; a spectrum stabilization step, determining whether the difference between the spectrum stabilization result and the spectrum stabilization target is less than a preset value; if so, performing software spectrum stabilization processing, adjusting the spectrum line array by coefficients to calibrate the spectrum stabilization result to be the same as the spectrum stabilization target, and performing the detection step; otherwise, performing hardware spectrum stabilization processing, by regulating the power supply voltage of the photomultiplier tube in the gamma spectrometer to change the field strength of the electric field inside the photomultiplier tube, until the spectrum stabilization result is calibrated to be the same as the spectrum stabilization target, and performing the detection step; The detection step is to use the gamma spectrometer to monitor the soil to be detected, obtain a spectral line array of the soil, and analyze the spectral line array to obtain soil nutrient data.

2. The adaptive spectrum stabilization method for a gamma spectrometer according to claim 1, wherein: The gamma spectrometer includes an FPGA, which is used to complete pulse signal channel address calculation according to the digital signal output by the analog-to-digital converter in the gamma spectrometer to obtain a spectrum line array.

3. The adaptive spectrum stabilization method for a gamma spectrometer according to claim 2, wherein: The FPGA adjusts the spectral line array according to the coefficients.

4. The adaptive spectrum stabilization method for a gamma spectrometer according to claim 2, wherein: The power supply of the photomultiplier tube is provided by a digital-to-analog converter, and the FPGA regulates the power supply voltage of the photomultiplier tube by controlling the voltage output by the digital-to-analog converter.

5. An adaptive spectrum stabilization device for a gamma spectrometer, characterized in that: include: The initialization module obtains the spectral line array of the gamma spectrometer when the scintillation crystal of the gamma spectrometer receives gamma rays, extracts the maximum value in the spectral line array as the spectrum stabilization result, and compares the spectrum stabilization result with the preset spectrum stabilization target to see if they are the same. If they are the same, the gamma spectrometer is determined to be calibrated and the detection module is executed. Otherwise, the spectrum stabilization module is executed. a spectrum stabilization module that determines whether the difference between the spectrum stabilization result and the spectrum stabilization target is less than a preset value. If so, software spectrum stabilization is performed to adjust the spectrum line array by coefficients to calibrate the spectrum stabilization result to the same as the spectrum stabilization target, and the detection module is executed. Otherwise, hardware spectrum stabilization is performed to adjust the power supply voltage of the photomultiplier tube in the gamma spectrometer to change the field strength of the electric field inside the photomultiplier tube until the spectrum stabilization result is calibrated to the same as the spectrum stabilization target, and the detection module is executed; The detection module uses the gamma spectrometer to monitor the soil to be detected, obtains the spectral line array of the soil, and analyzes the spectral line array to obtain soil nutrient data.

6. The adaptive spectrum stabilization device for a gamma spectrometer according to claim 5, characterized in that: The gamma spectrometer includes an FPGA, which is used to complete pulse signal channel address calculation according to the digital signal output by the analog-to-digital converter in the gamma spectrometer to obtain a spectrum line array.

7. The adaptive spectrum stabilization device for a gamma spectrometer according to claim 6, wherein: The FPGA adjusts the spectral line array according to the coefficient; the power supply of the photomultiplier tube is provided by the digital-to-analog converter, and the FPGA regulates the power supply voltage of the photomultiplier tube by controlling the voltage output by the digital-to-analog converter.

8. An electronic device, characterized in that: The electronic device comprises the adaptive spectrum stabilization device according to any one of claims 5 to 7, wherein the electronic device is connected to an information display device, and the information display device is used to display the soil nutrient data using display parameters and attributes set by a user or through an artificial intelligence model.

9. A computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of the adaptive spectrum stabilization method according to any one of claims 1 to 4 are implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the adaptive spectrum stabilization method according to any one of claims 1 to 4 are implemented.

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