A method and device for detecting light leakage of an alpha, beta surface contamination detector

Abstract

The application discloses a kind of alpha, beta surface pollution detector light leakage detection method and device, it is related to radiation monitoring sensing technical field, the method of the present application includes: using sensor to collect the light signal in detection chamber, obtain the intensity component of red, green, blue three color channels;The ratio of blue light intensity component and the sum of red, green light intensity component is calculated;According to the ratio and the dynamic threshold parameter of preset light leakage determination;If it is determined that natural light leaks, trigger alarm and shield current detection data.The core of the present application is that the luminescence spectrum of ZnS (Ag) scintillator is concentrated in blue light band, while natural light is full-band continuous spectrum.By analyzing the proportional relationship of RGB color components, the accurate and rapid differentiation between light leakage signal and real nuclear radiation signal is realized.This method effectively solves the technical problem that traditional hardware shielding method cannot identify micro-hole light leakage, and has the advantages of high detection sensitivity, fast response and strong anti-interference ability.

Description

Technical Field

[0001] This invention belongs to the field of radiation monitoring and sensing technology, specifically relating to a method and device for detecting light leakage in α and β surface contamination detectors. Background Technology

[0002] In the field of nuclear radiation monitoring, alpha and beta surface contamination detectors are core equipment for detecting radioactive materials, and their performance directly affects the accuracy of nuclear safety monitoring. These detectors typically consist of a plastic scintillator, a photomultiplier tube (PMT), and a sealed detection chamber. The scintillator is coated with a ZnS(Ag) (silver-activated zinc sulfide) fluorescent layer sensitive to alpha and beta particles, and covered in front of it by an extremely thin (usually 1-2 μm) aluminum film window. Its working principle is as follows: when a radioactive particle passes through the 1-2 μm thick aluminum film window, its energy is converted into fluorescent photons by the scintillator. These photons are then converted into electrical signals by the PMT, and pulse amplitude analysis is used to distinguish between alpha and beta particles.

[0003] However, the detector's performance is highly dependent on its optical sealing. The ultra-thin aluminum membrane, which provides protection and sealing, is extremely susceptible to microporous damage during actual use due to mechanical stress, chemical corrosion, or changes in ambient temperature and humidity. Once the aluminum membrane is damaged, visible light from the environment (such as sunlight or indoor lighting) can directly penetrate and illuminate the scintillator, where it is received by the photomultiplier tube, generating interference pulses similar to real radioactive signals. This background noise and false signals caused by light leakage can severely interfere with the assessment of real radioactive contamination, leading to distorted monitoring data and posing a potential threat to nuclear safety.

[0004] Currently, the mainstream approach to address light leakage is hardware shielding, such as adding a physical light shield to the detector or using narrowband filters that only allow specific wavelengths (such as blue light) to pass through. While these methods can reduce the influence of ambient light to some extent, they have the following drawbacks: First, they lack the sensitivity to detect micro-aperture leakage signals, making it difficult to capture weak ambient light interference; second, ambient light and scintillator fluorescence signals highly overlap in the frequency domain, making it easy for existing separation techniques to produce misjudgments; finally, in strong light environments, the PMT is prone to saturation, leading to signal distortion and affecting measurement accuracy. Summary of the Invention

[0005] To address the aforementioned problems in the prior art, this invention provides a method and apparatus for detecting light leakage in α and β surface contamination detectors. The technical problem to be solved by this invention is achieved through the following technical solution:

[0006] This invention provides a method for detecting light leakage in α and β surface contamination detectors, comprising:

[0007] Step 1: Use sensors to collect light signals inside the detection chamber to obtain intensity components of three color channels, including red, green and blue light;

[0008] Step 2: Calculate the ratio of the intensity component of the blue light to the sum of the intensity components of the red light and the green light based on the intensity components of the three color channels;

[0009] Step 3: Determine detector light leakage based on the ratio and preset dynamic threshold parameters;

[0010] Step 4: In response to the judgment result of natural light leakage, trigger the alarm device and block the current detection data of the detector.

[0011] This invention provides a light leakage detection device for α and β surface contamination detectors, applicable to the light leakage detection method for α and β surface contamination detectors described in any of the above embodiments, comprising:

[0012] The sensor is used to collect light signals within the detection chamber and obtain intensity components of three color channels, including red, green, and blue light.

[0013] The microprocessor is configured to calculate the ratio of the intensity component of the blue light to the sum of the intensity components of the red light and the green light based on the intensity components of the three color channels; determine detector light leakage based on the ratio and a preset dynamic threshold parameter; and generate a control signal and block the current detection data of the detector in response to the determination result of natural light leakage.

[0014] An alarm device is used to issue a warning based on the received control signal when the determination result is light leakage from natural light.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0016] 1. The light leakage detection method for α and β surface contamination detectors of the present invention, by monitoring the ratio of the intensity components of blue light to those of red and green light, and utilizing the characteristic that the main emission peak of ZnS(Ag) scintillator is in the 420nm blue light band and that natural light is a mixture of all wavelengths, achieves accurate identification of light leakage signals, significantly improving detection efficiency and reliability. The use of dynamic threshold parameters allows for adaptive adjustment based on ambient light intensity, ensuring accuracy and stability of discrimination under different lighting conditions.

[0017] 2. The light leakage detection device for α and β surface contamination detectors of the present invention only requires a conventional ambient light sensor, without the need for additional optical beam splitting devices or complex hardware modifications. It is suitable for embedded systems and can be easily integrated into existing detector equipment.

[0018] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described in detail below with reference to the accompanying drawings. Attached Figure Description

[0019] Figure 1 This is a flowchart of a light leakage detection method for α and β surface contamination detectors provided in an embodiment of the present invention;

[0020] Figure 2 This is a hardware principle block diagram of an α, β surface contamination detector light leakage detection device provided in an embodiment of the present invention;

[0021] Figure 3 This is a logic block diagram of a light leakage detection device for an α and β surface contamination detector provided in an embodiment of the present invention. Detailed Implementation

[0022] To further illustrate the technical means and effects adopted by the present invention to achieve the intended purpose, the following describes in detail, with reference to the accompanying drawings and specific embodiments, a light leakage detection method and apparatus for α and β surface contamination detectors proposed according to the present invention.

[0023] The foregoing and other technical contents, features, and effects of the present invention will be clearly presented in the following detailed description of specific embodiments in conjunction with the accompanying drawings. Through the description of the specific embodiments, a more in-depth and concrete understanding can be gained of the technical means and effects adopted by the present invention to achieve its intended purpose. However, the accompanying drawings are for reference and illustration only and are not intended to limit the technical solutions of the present invention.

[0024] In the first aspect, embodiments of the present invention provide a method for detecting light leakage in α and β surface contamination detectors. The core of this method is to monitor the ratio of the intensity components of blue light (B) to the intensity components of red light (R) and green light (G), and to utilize the characteristic that the main emission peak of ZnS(Ag) scintillator is in the 420nm blue light band and that natural light is a mixture of all wavelengths to achieve accurate identification of light leakage signals.

[0025] Please see Figure 1 , Figure 1 This is a flowchart of a light leakage detection method for α and β surface contamination detectors provided in an embodiment of the present invention, as shown below. Figure 1 As shown, the light leakage detection method for α and β surface contamination detectors according to an embodiment of the present invention includes the following steps:

[0026] Step 1: Use sensors to collect light signals inside the detection chamber to obtain intensity components of three color channels, including red, green and blue light.

[0027] In one alternative embodiment, the sensor includes an RGB sensor, a multi-channel spectral sensor, or a photodiode array with filters.

[0028] Preferably, a general-purpose RGB sensor can be used, which is inexpensive and easy to integrate into the circuitry of existing detectors, without the need for a complex and expensive optical beam splitting system.

[0029] Understandably, using a multi-channel spectral sensor can obtain more precise spectral information for subsequent discrimination algorithms. A photodiode array is employed, with corresponding narrowband filters (such as a blue light filter with a center wavelength of 420nm and a green light filter with a center wavelength of 550nm) configured at its front end. The light intensity of different wavelength bands is measured separately for subsequent judgment. This invention is not limited to RGB sensors, multi-channel spectral sensors, or photodiode arrays with filters; any optical sensing scheme capable of acquiring light intensity information across multiple wavelength bands (at least covering the blue light band and one of the red / green bands) is acceptable.

[0030] Step 2: Calculate the ratio of the intensity component of blue light to the sum of the intensity components of red and green light based on the intensity components of the three color channels.

[0031] Understandably, to eliminate the slight influence of background dark current, the dark noise background value of each channel can be subtracted first (which can be obtained through factory calibration). Then, the ratio of the intensity component of blue light to the sum of the intensity components of red and green light is calculated, i.e., B / (R+G). Where B represents the intensity component of blue light, R is the intensity component of red light, and G is the intensity component of green light.

[0032] In this embodiment, the calculated ratio is used for subsequent detector leakage determination. The ratio method, rather than the absolute value, is used for subsequent determination, which can effectively offset the influence of factors such as changes in the overall intensity of the light source and fluctuations in sensor gain, thereby improving the robustness of the determination.

[0033] Step 3: Determine detector light leakage based on the ratio and preset dynamic threshold parameters.

[0034] In this embodiment, step 3 includes:

[0035] Step 3.1: Compare the ratio with the dynamic threshold parameter;

[0036] Step 3.2: Based on the comparison results and the intensity components of the three color channels, obtain the judgment result.

[0037] Specifically, step 3.2 includes:

[0038] When B / (R+G)< kWhen the intensity components of red light and green light are not lower than the preset ratio of the intensity component of blue light, the result is natural light leakage.

[0039] When B / (R+G)≥ k When both the intensity components of red light and green light are below the preset noise threshold, the result is determined to be scintillator emission.

[0040] In this embodiment, the preset ratio is 20%, and the noise threshold is three times the standard deviation of the sensor's dark noise. Here, B represents the intensity component of blue light, R represents the intensity component of red light, and G represents the intensity component of green light. k This is a dynamic threshold parameter.

[0041] That is, when the ratio satisfies the condition: B / (R+G)< k If R≥20%B and G≥20%B, then the current light signal is determined to be caused by light leakage from natural light entering the chamber through the broken aluminum film.

[0042] When the ratio satisfies the condition: B / (R+G)≥ k And R < 3σ dark G < 3σ dark , σ dark If the dark noise standard deviation of the sensor is given, then the current light signal is determined to be emitted by a ZnS(Ag) scintillator excited by α / β particles, which is an effective radiation detection signal.

[0043] In this embodiment, by introducing the absolute level (noise level judgment) and relative ratio (ratio with the intensity component of blue light) of the intensity components of red and green light as dual criteria, the accuracy of the distinction is greatly improved, and misjudgment caused by the failure of a single ratio criterion in extremely weak or extremely strong light environments is effectively avoided.

[0044] In this embodiment, the dynamic threshold parameter k The dynamic threshold parameter can be obtained through experimental calibration and is adaptively adjusted according to the ambient light intensity.

[0045] Optionally, dynamic threshold parameters can be obtained based on the acquired ambient light intensity using a pre-stored illumination-threshold mapping table or illumination-threshold fitting formula.

[0046] The illumination-threshold fitting formula is as follows:

[0047] ;

[0048] In the formula, For dynamic threshold parameters, As the initial threshold, For ambient light intensity, For reference light intensity, This is the adjustment coefficient.

[0049] In this embodiment, by adaptively adjusting the dynamic threshold parameter, the method of the present invention can intelligently adapt to various complex lighting conditions, such as from a dark room to strong outdoor light. This overcomes the defect of the fixed threshold method, which is prone to generating a large number of false alarms or missed alarms when the environment changes, and significantly improves the stability and reliability of the detection method of the present invention under all-weather conditions.

[0050] Step 4: In response to the judgment result of natural light leakage, trigger the alarm device and block the current detection data of the detector.

[0051] In this embodiment, when natural light leakage is detected, an alarm device is triggered, such as an audible alarm, a light indicator, or a display screen, to remind the operator to check the integrity of the detector's aluminum film. Simultaneously, the data at that time point is marked as invalid and masked to ensure that subsequent radioactivity analysis calculations are not affected by this interference signal.

[0052] Furthermore, the principle of detector light leakage determination in this embodiment will be explained.

[0053] The main emission wavelength of the ZnS(Ag) phosphor layer in the plastic scintillator is around 420 nm, which is in the blue light region. Its emission spectrum peak range is 395 nm to 425 nm, also in the blue light band, and the spectral distribution is relatively narrow, with the main energy concentrated in the blue light region. The relative light output of other bands, such as red and green light, is extremely low. The scintillator emission is generated by the characteristic transitions of the ZnS(Ag) activator. The spectrum is monochromatic, with almost no red light (wavelength around 600 nm) and green light (wavelength around 550 nm) components, or their proportion is negligible.

[0054] Natural light (such as sunlight and indoor lighting) is a continuous spectrum that includes red, green, and blue components. The proportions of red, green, and blue components vary depending on the light source (such as incandescent lamps which are redder and fluorescent lamps which are bluer-greener). However, it generally exhibits a multi-band mixed characteristic and is not concentrated solely in the blue light band.

[0055] Therefore, the scintillator emits light with the following color component characteristics: when the scintillator is excited by α / β rays, the light detected by the sensor is dominated by the blue light component, while the red and green light components are extremely low, close to the noise level. That is, B >> R and G, and B is absolutely dominant in the R / G / B ratio.

[0056] Natural light exhibits the following color component characteristics: the red, green, and blue components of natural light all have a certain intensity, and their proportions are close to the distribution of the natural spectrum. For example, in sunlight, R:G:B≈31:59:10, with slight differences for different light sources. There will not be a situation where a single blue light component is significantly higher than other components. That is, R and G will not approach zero, and the proportion of B is usually lower than that of scintillator emission.

[0057] Based on the color component characteristics of scintillator emission and natural light, the two light sources can be quantitatively distinguished by setting a threshold ratio for the RGB components, such as the B / (R+G) threshold. Specifically, if the sensor detects that the intensity component of blue light is significantly higher than that of red and green light, and the intensity components of red and green light are close to the background noise, then the light signal is very likely from scintillator emission. If the red, green, and blue components all have significant intensity values, and the ratios conform to the spectral characteristics of natural light, for example, the intensity components of red and green light are not less than 20% of the intensity component of blue light, then the light signal comes from natural light, i.e., light leakage.

[0058] Furthermore, the detailed process of adaptive adjustment of the dynamic threshold parameters in this embodiment will be explained.

[0059] First, calibrate the initial threshold under experimental conditions. In a standard darkroom and under ambient light conditions of varying intensities (e.g., 0 Lux, 100 Lux, 500 Lux), background ambient light data was collected when there was no radiation source (the aluminum film was intact but ambient light was present), and signal data was collected when simulating scintillator emission (using a 450nm blue LED to simulate the emission characteristics of a ZnS(Ag) scintillator, and introducing it as a standard signal into the detection chamber). For each set of collected data, the B / (R+G) ratio was calculated, and statistical analysis was used to determine a set of different ambient light intensities. The optimal threshold (characterized by the intensity component of green light or the total light intensity) forms the initial threshold. (Threshold at reference light intensity,) and reference light intensity (calibration) (The reference ambient light intensity used at that time).

[0060] Optionally, during the initial calibration phase, different ambient light intensities can be recorded. Pairing the data with the corresponding optimal thresholds creates a light-threshold mapping table, which is then stored. In practical applications, the current light level is measured in real time. By looking up a table and using an interpolation algorithm (such as linear interpolation), the most suitable dynamic threshold parameter can be obtained. .

[0061] Optionally, a description can also be established based on the calibration experimental data. and Mathematical models of the relationship between them, such as linear fitting formulas. It is understandable It is usually a positive number because when the ambient light intensity When enhanced, the absolute value of the blue light component in ambient light also increases, requiring a corresponding increase in the dynamic threshold parameter. This avoids misinterpreting the relatively increased blue light component in strong ambient light as a scintillator signal; conversely, in dark environments, the threshold is lowered to maintain sensitivity to weak scintillator signals. In practical applications, the current dynamic threshold parameters are calculated in real time using this linear fitting formula.

[0062] Understandably, if the ambient light intensity With dynamic threshold parameters The relationship is non-linear, and more complex models such as polynomial fitting and piecewise linear fitting can be used to obtain a non-linear fitting formula to calculate the dynamic threshold parameter.

[0063] Alternatively, a Kalman filter can be introduced to optimally estimate the threshold, or a machine learning algorithm can be used to continuously fine-tune the dynamic threshold parameters based on recorded historical data and judgment results, combined with manual confirmation or known radioactive source test results, to achieve self-evolution and thus improve the accuracy of judgment.

[0064] The light leakage detection method for α and β surface contamination detectors of this invention monitors the ratio of the intensity components of blue light to those of red and green light. Utilizing the characteristic that the main emission peak of ZnS(Ag) scintillator is in the 420nm blue light band and that natural light is a mixture of all wavelengths, it achieves accurate identification of light leakage signals, significantly improving detection efficiency and reliability. The use of dynamic threshold parameters allows for adaptive adjustment based on ambient light intensity, ensuring accuracy and stability under different lighting conditions.

[0065] Secondly, embodiments of the present invention provide a light leakage detection device for α and β surface contamination detectors, applicable to the light leakage detection method for α and β surface contamination detectors provided in the first aspect, comprising: a sensor, a microprocessor, and an alarm device. The sensor is used to collect light signals within the detection chamber, obtaining intensity components of three color channels including red, green, and blue light; the microprocessor is used to calculate the ratio of the intensity component of blue light to the sum of the intensity components of red and green light based on the intensity components of the three color channels; to determine light leakage of the detector based on the ratio and a preset dynamic threshold parameter; in response to the determination result being natural light leakage, a control signal is generated and the current detection data of the detector is blocked; the alarm device is used to issue a warning based on the received control signal when the determination result is natural light leakage.

[0066] In this embodiment, the communication interface between the sensor and the microprocessor is an I2C (Inter-Integrated Circuit), SPI (Serial Peripheral Interface), or UART (universal asynchronous receiver-transmitter) interface; the signal output interface between the microprocessor and the alarm device is a GPIO (General Purpose Input Output), PWM (Pulse Width Modulation), or wireless transmission interface.

[0067] In an alternative embodiment, the sensor may be an RGB sensor, a multi-channel spectral sensor, or a photodiode array with filters.

[0068] Taking an RGB sensor as an example, the working process of the light leakage detection device for the α and β surface contamination detector in this embodiment will be explained. Please refer to [link to previous document]. Figure 2 and Figure 3 , Figure 2 This is a hardware principle block diagram of an α, β surface contamination detector light leakage detection device provided in an embodiment of the present invention. Figure 3 This is a logic block diagram of a light leakage detection device for an α and β surface contamination detector provided in an embodiment of the present invention.

[0069] The workflow of the light leakage detection device for the α and β surface contamination detector in this embodiment is as follows: The RGB sensor acquires spectral component values ​​in real time and sends the light intensity data of blue, red, and green light to the microprocessor through standard communication interfaces (including but not limited to I2C, SPI, UART, etc.); the microprocessor has a built-in feature spectrum recognition algorithm to dynamically analyze the B / (R+G) component ratio relationship and compare it with the dynamic threshold parameter verified by calibration experiments. k (Automatic adjustment based on ambient light intensity) Comparison is performed. When B / (R+G)≥ k Furthermore, if the R and G components are less than three times the standard deviation of the sensor's dark noise (i.e., close to the noise level), it is determined to be luminescence from a ZnS(Ag) scintillator; if B / (R+G) < k If the R, G, and B components all have significant values ​​(e.g., the R and G components are not less than 20% of the B component), then it is determined to be ambient light leakage. At this time, the microprocessor outputs a control signal through the signal output interface (including but not limited to GPIO, PWM, wireless transmission, etc.) to trigger the alarm device and automatically shields abnormal data to ensure the accuracy of the detection results.

[0070] The light leakage detection device for α and β surface contamination detectors of the present invention only requires a conventional ambient light sensor, without the need for additional optical beam splitting devices or complex hardware modifications. It is suitable for embedded systems and can be easily integrated into existing detector equipment.

[0071] For details regarding the light leakage detection device for the α and β surface contamination detector and its corresponding beneficial effects, please refer to the relevant content of the light leakage detection method for the α and β surface contamination detector provided in the first aspect, which will not be repeated here.

[0072] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations are intended to cover non-exclusive inclusion, such that an article or device comprising a list of elements includes not only those elements but also other elements not expressly listed. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the article or device comprising said element. Terms such as "connected" or "linked" are not limited to physical or mechanical connections but can include electrical connections, whether direct or indirect. The orientations or positional relationships indicated by terms such as "upper," "lower," "left," and "right" are based on the orientations or positional relationships shown in the accompanying drawings and are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as limiting the invention.

[0073] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features or characteristics described may be combined in any suitable manner in one or more embodiments or examples. In addition, those skilled in the art can combine and integrate the different embodiments or examples described in this specification.

[0074] The above description, in conjunction with specific preferred embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, various simple deductions or substitutions can be made without departing from the concept of the present invention, and all such modifications and substitutions should be considered within the scope of protection of the present invention.

Claims

1. A method for detecting light leakage in α and β surface contamination detectors, characterized in that, include: Step 1: Use sensors to collect light signals inside the detection chamber to obtain intensity components of three color channels, including red, green and blue light; Step 2: Calculate the ratio of the intensity component of the blue light to the sum of the intensity components of the red light and the green light based on the intensity components of the three color channels; Step 3: Determine detector light leakage based on the ratio and preset dynamic threshold parameters; The dynamic threshold parameter is adaptively adjusted according to the ambient light intensity, including: Based on the acquired ambient light intensity, the dynamic threshold parameters are obtained using a pre-stored illumination-threshold mapping table or an illumination-threshold fitting formula, wherein the illumination-threshold fitting formula is: ； In the formula, For dynamic threshold parameters, As the initial threshold, For ambient light intensity, For reference light intensity, This is the adjustment coefficient; Step 4: In response to the judgment result of natural light leakage, trigger the alarm device and block the current detection data of the detector.

2. The light leakage detection method for α and β surface contamination detectors according to claim 1, characterized in that, The sensor includes an RGB sensor, a multi-channel spectral sensor, or a photodiode array with filters.

3. The light leakage detection method for α and β surface contamination detectors according to claim 1, characterized in that, Step 3 includes: Step 3.1: Compare the ratio with the dynamic threshold parameter; Step 3.2: Based on the comparison results and the intensity components of the three color channels, the determination result is obtained.

4. The light leakage detection method for α and β surface contamination detectors according to claim 3, characterized in that, Step 3.2 includes: When B / (R+G)< k When the intensity components of the red light and the green light are both not lower than the preset ratio of the intensity component of the blue light, the determination result is natural light leakage. When B / (R+G)≥ k When the intensity components of the red light and the green light are both below a preset noise threshold, the determination result is that the scintillator emits light. Where B represents the intensity component of blue light, R represents the intensity component of red light, and G represents the intensity component of green light. k This is a dynamic threshold parameter.

5. The light leakage detection method for α and β surface contamination detectors according to claim 4, characterized in that, The preset ratio is 20%.

6. The light leakage detection method for α and β surface contamination detectors according to claim 4, characterized in that, The noise threshold is three times the dark noise standard deviation of the sensor.

7. A light leakage detection device for α and β surface contamination detectors, characterized in that, The light leakage detection method for α and β surface contamination detectors according to any one of claims 1-6 includes: The sensor is used to collect light signals within the detection chamber and obtain intensity components of three color channels, including red, green, and blue light. The microprocessor is configured to calculate the ratio of the intensity component of the blue light to the sum of the intensity components of the red light and the green light based on the intensity components of the three color channels; determine detector light leakage based on the ratio and a preset dynamic threshold parameter; and generate a control signal and block the current detection data of the detector in response to the determination result of natural light leakage. An alarm device is used to issue a warning based on the received control signal when the determination result is light leakage from natural light.

8. The light leakage detection device for α and β surface contamination detectors according to claim 7, characterized in that, The communication interface between the sensor and the microprocessor is an I2C, SPI, or UART interface; the signal output interface between the microprocessor and the alarm device is a GPIO, PWM, or wireless transmission interface.

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