A temperature compensation correction algorithm for nuclear detectors

Abstract

This invention discloses a temperature compensation correction algorithm for a nuclear detector, comprising the following steps: The temperature compensation algorithm mainly determines the left and right boundaries of the characteristic peak, the peak position, peak height, and half-width, locks the channel address corresponding to the drifted characteristic peak, and then uses the spectral data of the known peak region to form complete corrected spectral data using a Gaussian fitting function, thereby achieving temperature compensation. The temperature in this invention has a relatively small impact on the pulse count of the nuclear detector but a significant impact on the energy spectrum data, manifested as a shift in the spectral line data of the characteristic peak.

Description

Technical Field

[0001] This invention relates to the field of nuclear detector technology, specifically to a temperature compensation correction algorithm for nuclear detectors. Background Technology

[0002] Nuclear detectors, as core components of radiation environment monitoring systems, play a crucial role in sensing radiation intensity and detecting radioactive materials. However, most current radiation environment monitoring systems are highly dependent on ambient temperature, with some even experiencing sluggish response and reduced detection efficiency in frigid outdoor conditions during winter. This is primarily because changes in ambient temperature affect the performance of nuclear detectors, including variations in the luminous efficiency of the NaI scintillator, the multiplication factor of the photomultiplier tube, the amplification factor of the amplifier, and the discriminator value. Since temperature changes further lead to a series of measurement errors in nuclear detectors performing radionuclide energy spectrum analysis, such as energy spectrum drift and energy response deviations, we propose a temperature compensation correction algorithm for nuclear detectors. Summary of the Invention

[0003] The purpose of this invention is to provide a temperature compensation correction algorithm for nuclear detectors, which solves the existing problems.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a nuclear detector temperature compensation correction algorithm, comprising the following steps:

[0005] The temperature compensation algorithm mainly determines the left and right boundaries of the characteristic peak, the peak position, peak height, and half-width and height, locks the channel address corresponding to the drifted characteristic peak, and then uses the spectral data of the known peak region to form a complete corrected spectral data using a Gaussian fitting function to achieve temperature compensation.

[0006] A temperature compensation correction algorithm for a nuclear detector, further specifically implemented by the algorithm, includes the following steps:

[0007] Step 1: Use the first derivative calculation formula (Formula 1) to solve for the first derivative of the spectral data after heating or cooling according to the channel value distribution. Where... Let y be the first derivative at point m. m-2 For the spectral data of the channel address m-2, y m-1 y m+1 y m+2 And so on;

[0008]

[0009] Step 2: Determine the left boundary address of the characteristic peak region: The first derivative value of the directional spectrum data should be positive and continue to increase as the channel address increases. If formulas 2, 3, and 4 are satisfied simultaneously, then the corresponding channel address m is considered to be... L This is the starting address of the left boundary of the characteristic peak region;

[0010]

[0011]

[0012]

[0013] y in Formula 2, Formula 3, and Formula 4 mL It is m L The spectral data of Tao It is m L The first derivative of the smoothed spectrum; K is a constant, which is the abscissa of the normal distribution at a certain confidence level, and is chosen to be 0.95 here; m L The standard deviation of the first derivative value is shown in Formula 5;

[0014]

[0015] Continue searching along the direction of increasing channel addresses. If a channel address simultaneously satisfies Formulas 6, 7, and 8, then that channel address is considered to be the right boundary channel address m of the peak region. R ;

[0016]

[0017]

[0018]

[0019] The calculation is the same as in Formula 5; after the left and right boundaries of the peak region are determined, it is necessary to check the width and height of the peak region; the width of the peak region must meet the following conditions:

[0020] W = m R -m L >1 (9)

[0021]

[0022] In the formula W init It is the width of the characteristic peak of the same experimental radiation source under normal initial conditions (suitable temperature and humidity environment for nuclear detectors);

[0023] When formulas 9, 10, and 11 below are satisfied, it is considered that a characteristic peak exists in this region;

[0024]

[0025] In the above formula, y init B init These represent the height of the characteristic peak and the background value of the same experimental radiation source under normal initial conditions (suitable operating temperature and humidity environment for the nuclear detector); K is the threshold value, typically set to 2.4.

[0026] The channel address corresponding to the characteristic peak should meet the following condition: the first derivative values ​​of the spectral data on both sides change from positive to negative, and the position of the zero point of the first derivative is the channel address ch corresponding to the characteristic peak. m ;

[0027] Let peak height and road address data (y i ,ch i (i = 1, 2, ..., N), can be described by formula 12:

[0028]

[0029] In the above formula, y is to be estimated max ch max FHWM and FHWM represent the peak height, peak position, and half-width of the Gaussian curve, respectively; taking the logarithm of Equation 12, we get:

[0030]

[0031]

[0032] Let lny i =z i , Equation 13 can then be transformed into a quadratic polynomial fitting function:

[0033]

[0034] Introducing measurement error ξ i And represented in matrix

[0035]

[0036] According to the least squares principle, the generalized least squares solution of the matrix B formed by the fitting constants b0, b1, and b2 can be obtained as follows:

[0037] B = (X) T X) -1 X T Z (17)

[0038] Therefore, according to Formula 14, FWHM and ch can be solved. max and y max Then, the Gaussian function in formula 13 can be obtained;

[0039] Step 3: Based on the distribution patterns of ray energy and channel address, use the following Gaussian function to fit new spectral lines, thereby achieving the purpose of data correction.

[0040] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0041] The temperature of this invention has a relatively small effect on the pulse count of the nuclear detector, but a large effect on the energy spectrum data, which is manifested as a shift in the characteristic peak spectral line data.

[0042] The temperature compensation algorithm used in this invention mainly determines the left and right boundaries of the characteristic peak, the peak position, peak height, and half-width and height, locks the channel address corresponding to the drifted characteristic peak, and then uses the spectral data of the known peak region to form complete corrected spectral data using a Gaussian fitting function to achieve temperature compensation. Detailed Implementation

[0043] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0044] Implementation Case 1

[0045] A temperature compensation correction algorithm for a nuclear detector includes the following steps:

[0046] The temperature compensation algorithm mainly determines the left and right boundaries of the characteristic peak, the peak position, peak height, and half-width and height, locks the channel address corresponding to the drifted characteristic peak, and then uses the spectral data of the known peak region to form a complete corrected spectral data using a Gaussian fitting function to achieve temperature compensation.

[0047] Specific Implementation Case 2

[0048] A temperature compensation correction algorithm for a nuclear detector, further specifically implemented by the algorithm, includes the following steps:

[0049] Step 1: Use the first derivative calculation formula (Formula 1) to solve for the first derivative of the spectral data after heating or cooling according to the channel value distribution. Where... Let y be the first derivative at point m. m-2 For the spectral data of the channel address m-2, y m-1 y m+1 y m+2 And so on;

[0050]

[0051] Step 2: Determine the left boundary address of the characteristic peak region: The first derivative value of the directional spectrum data should be positive and continue to increase as the channel address increases. If formulas 2, 3, and 4 are satisfied simultaneously, then the corresponding channel address m is considered to be... L This is the starting address of the left boundary of the characteristic peak region;

[0052]

[0053]

[0054]

[0055] y in Formula 2, Formula 3, and Formula 4 mL It is m L The spectral data of Tao It is m L The first derivative of the smoothed spectrum; K is a constant, which is the abscissa of the normal distribution at a certain confidence level, and is chosen to be 0.95 here; m L The standard deviation of the first derivative value is shown in Formula 5;

[0056]

[0057] Continue searching along the direction of increasing channel addresses. If a channel address simultaneously satisfies Formulas 6, 7, and 8, then that channel address is considered to be the right boundary channel address m of the peak region. R ;

[0058]

[0059]

[0060]

[0061] The calculation is the same as in Formula 5; after the left and right boundaries of the peak region are determined, it is necessary to check the width and height of the peak region; the width of the peak region must meet the following conditions:

[0062] W = m R -m L >1 (9)

[0063]

[0064] In the formula W init It is the width of the characteristic peak of the same experimental radiation source under normal initial conditions (suitable temperature and humidity environment for nuclear detectors);

[0065] When formulas 9, 10, and 11 below are satisfied, it is considered that a characteristic peak exists in this region;

[0066]

[0067] In the above formula, y init B init These represent the height of the characteristic peak and the background value of the same experimental radiation source under normal initial conditions (suitable operating temperature and humidity environment for the nuclear detector); K is the threshold value, typically set to 2.4.

[0068] The channel address corresponding to the characteristic peak should meet the following condition: the first derivative values ​​of the spectral data on both sides change from positive to negative, and the position of the zero point of the first derivative is the channel address ch corresponding to the characteristic peak. m ;

[0069] Let peak height and road address data (y i ,ch i (i = 1, 2, ..., N), can be described by formula 12:

[0070]

[0071] In the above formula, y is to be estimated max ch max FHWM and FHWM represent the peak height, peak position, and half-width of the Gaussian curve, respectively; taking the logarithm of Equation 12, we get:

[0072]

[0073]

[0074] Let lny i =z i , Equation 13 can then be transformed into a quadratic polynomial fitting function:

[0075]

[0076] Introducing measurement error ξ i And represented in matrix

[0077]

[0078] According to the least squares principle, the generalized least squares solution of the matrix B formed by the fitting constants b0, b1, and b2 can be obtained as follows:

[0079] B = (X) T X) -1 X T Z (17)

[0080] Therefore, according to Formula 14, FWHM and ch can be solved. max and y max Then, the Gaussian function in formula 13 can be obtained;

[0081] Step 3: Based on the distribution patterns of ray energy and channel address, use the following Gaussian function to fit new spectral lines, thereby achieving the purpose of data correction.

[0082] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A temperature compensation correction algorithm for a nuclear detector, characterized in that, Includes the following steps: The temperature compensation algorithm mainly determines the left and right boundaries of the characteristic peak, the peak position, peak height and half width and height, locks the channel address corresponding to the drifted characteristic peak, and then uses the spectral data of the known peak area to form a complete corrected spectral data by using a Gaussian fitting function to achieve temperature compensation. The specific implementation algorithm includes the following steps: Step 1: Use formula 1 to calculate the first derivative of the spectral data after heating or cooling, based on the channel value distribution. In the formula... Let m be the first derivative at the address m. This is the spectral data for the channel address m-2. , , And so on; （1） Step 2: Determine the left boundary address of the characteristic peak region: The first derivative value of the directional spectrum data should be positive and continue to increase as the channel address increases. If formulas 2, 3, and 4 are satisfied simultaneously, then the corresponding channel address m is considered to be... L This is the starting address of the left boundary of the characteristic peak region; （2） （3） （4） y in Formula 2, Formula 3, and Formula 4 mL It is m L The spectral data of Tao It is m L The first derivative of the smoothed spectrum; K is a constant, which is the abscissa of the normal distribution at a certain confidence level, and is chosen to be 0.95 here; m L The standard deviation of the first derivative value is shown in Formula 5; （5） Continue searching along the direction of increasing channel addresses. If a channel address simultaneously satisfies Formulas 6, 7, and 8, then that channel address is considered to be the right boundary channel address m of the peak region. R ; （6） （7） （8） The calculation is the same as in Formula 5; after the left and right boundaries of the peak region are determined, it is necessary to check the width and height of the peak region; the width of the peak region must meet the following conditions: （9） （10） In the formula W init It is the width of the characteristic peak of the same experimental radiation source in the normal initial state, where the normal initial state is the suitable temperature and humidity environment for the nuclear detector. When formulas 9, 10, and 11 below are satisfied, it is considered that a characteristic peak exists in this region; （11） In the above formula , These represent the height of the characteristic peak and the background value of the same experimental radiation source under normal initial conditions (suitable temperature and humidity environment for nuclear detectors); K is the threshold value, typically taken as 2.

4. The channel address corresponding to the characteristic peak should meet the following condition: the first derivative values ​​of the spectral data on both sides change from positive to negative, and the position of the zero point of the first derivative is the channel address corresponding to the characteristic peak. ; Set peak height and road address data This can be described using Formula 12: （12） The formula above is to be estimated , FHWM and FHWM represent the peak height, peak position, and half-width of the Gaussian curve, respectively; taking the logarithm of Equation 12, we get: （13） （14） make , , , Then, Formula 13 can be transformed into a quadratic polynomial fitting function: (15） Introducing measurement error And represented in matrix form: （16） According to the least squares principle, the fitting constants can be obtained. , and The generalized least squares solution of the matrix B is: （17） Therefore, according to Formula 14, FWHM can be solved. and Then, the Gaussian function in formula 13 can be obtained; Step 3: Based on the distribution patterns of ray energy and channel address, use a Gaussian function to fit new spectral lines, thereby achieving the purpose of data correction.

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