Radon gas detection method and device, electronic equipment and storage medium

Abstract

The invention provides a radon gas detection method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining the number of first particles, second particles and third particles generated after the atomic decay of radon gas collected within a preset time period, the first particles being particles emitted after the decay of radon-222, the second particles being particles emitted after the decay of polonium-218, and the third particles being particles emitted after the decay of polonium-218; the third particles are particles emitted after decay of polonium-214; a first humidity value is determined according to a first ratio between the number of the second particles or the third particles and the number of the first particles, and the smaller the first ratio is, the larger the first humidity value is; a first calibration coefficient is determined according to the first humidity value, and the smaller the first humidity value is, the smaller the first calibration coefficient is; and determining a first concentration value of the radon gas according to the first calibration coefficient and the number of fifth particles, wherein the fifth particles are at least one of the second particles and the third particles. Therefore, an additional humidity sensor is avoided, and the production cost of the product is reduced.

Description

Technical Field

[0001] This application relates to the technical field of radiation protection, and particularly to a radon gas detection method, device, electronic device, and storage medium. Background Art

[0002] Radon is a radioactive element that exists in a gaseous state at normal temperature and pressure. It is generally formed near the surface of uranium-containing substances such as soil or rock and diffuses into the surrounding air. Radon gas is colorless and odorless, which means that it is difficult for humans to detect its presence and concentration. Since radon gas is radioactive, long-term exposure to high concentrations of radon gas will greatly increase the risk of cancer and is the second leading cause of fatal lung cancer after smoking.

[0003] When detecting the concentration of radon gas, environmental humidity will have a certain impact. Currently, detection instruments use additional humidity sensors to compensate for the concentration, but this will increase the production cost of the product. Summary of the Invention

[0004] This application provides a radon gas detection method, device, electronic device, and storage medium. By using the ratio between the quantities of the particles respectively collected during the atomic decay processes of radon, specifically the ratio between the quantities of the particles emitted by radon-222, polonium-218, and polonium-214, the current humidity state is reflected, thereby compensating for the concentration. This avoids the situation of introducing a humidity sensor to determine the humidity value when measuring the radon gas concentration, thus reducing the production cost of the product.

[0005] In a first aspect, this application provides a radon gas detection method, which includes: Obtain the quantities respectively corresponding to the first particle, second particle, and third particle generated after the atomic decay of the radon gas collected within a preset time period. The first particle is the particle emitted after the decay of radon-222, the second particle is the particle emitted after the decay of polonium-218, and the third particle is the particle emitted after the decay of polonium-214; Determine a first humidity value according to the first ratio between the quantity of the fourth particle and the quantity of the first particle. The fourth particle is the second particle or the third particle, and the smaller the first ratio, the larger the first humidity value; Determine a first calibration coefficient according to the first humidity value. The smaller the first humidity value, the smaller the first calibration coefficient; Determine a first concentration value of the radon gas according to the first calibration coefficient and the quantity of the fifth particle. The fifth particle is at least one of the second particle and the third particle.

[0006] It can be seen that in the present application, since polonium-218 and polonium-214 are positively charged particles and have a certain probability of being neutralized by water molecules (OH-) in the environment, they are greatly affected by humidity. However, radon-222 is a gas and will not be neutralized by water molecules (OH-). Therefore, under different humidities and a constant radon concentration, the number of particles collected emitted by radon-222 changes little, but the number of particles collected emitted by polonium-218 and polonium-214 will be greatly affected. Therefore, in the present application, by measuring the ratio of the number of particles collected emitted by polonium-218 or polonium-214 to the number of particles collected emitted by radon-222 at different humidities, the change in humidity is reflected. For example, when the ratio becomes smaller, it indicates that the humidity increases. This can avoid the situation of introducing a humidity sensor to determine the humidity value when measuring the radon concentration, thereby reducing the production cost of the product.

[0007] In a feasible example, determining the first calibration coefficient according to the first humidity value includes: Obtaining a calibration coefficient-concentration curve corresponding to the first humidity value, where the calibration coefficient-concentration curve is used to represent the corresponding calibration coefficients at different concentrations; Determining a second ratio between the concentration corresponding to each coordinate point among multiple coordinate points on the calibration coefficient-concentration curve and the calibration coefficient; Determining a target coordinate point corresponding to the second ratio corresponding to the number of the fifth particles among multiple second ratios; Determining the calibration coefficient corresponding to the target coordinate point on the calibration coefficient-concentration curve as the first calibration coefficient.

[0008] In the present application, by calculating the ratio of the concentration to the calibration coefficient of each coordinate point in the calibration coefficient concentration curve and positioning the target coordinate point based on the matching relationship between the current number of the fifth particles and the ratio, the corresponding calibration coefficient is finally extracted as a compensation parameter. In this way, through the collaborative optimization of humidity, concentration, and calibration coefficient, the effects of humidity and concentration on the calibration coefficient can be considered respectively, and at the same time, the efficiency of positioning the calibration coefficient can be improved by using the pre-stored curve data, enhancing the detection accuracy and anti-interference ability of the radon detection instrument under environmental conditions of humidity change and concentration fluctuation.

[0009] In a feasible example, determining the first calibration coefficient according to the first humidity value includes: Obtaining a calibration coefficient-humidity curve and a calibration coefficient-concentration curve, where the calibration coefficient-humidity curve is used to represent the corresponding calibration coefficients at different humidities, and the calibration coefficient-concentration curve is used to represent the corresponding calibration coefficients at different concentrations; Determining a second calibration coefficient corresponding to the first humidity value according to the calibration coefficient-humidity curve; Determining a second concentration value according to the second calibration coefficient and the number of the fifth particles; Determine the first calibration coefficient according to the second concentration value and the calibration coefficient-concentration curve, and the first calibration coefficient corresponds to the second concentration value.

[0010] In the present application, first calculate the initial concentration through the initial second calibration coefficient corresponding to the current humidity, and then determine the first calibration coefficient from the calibration coefficient-concentration curve based on the initial concentration, so as to realize the feedback loop adjustment of the calibration coefficient. It solves the possible deviation of the single variable mapping, and enhances the detection accuracy and anti-interference ability of the radon gas detection instrument under the environmental conditions of humidity change and concentration fluctuation.

[0011] In a feasible example, obtaining the quantities corresponding to the first particle, the second particle, and the third particle generated after the radon gas collected within the preset time duration undergoes atomic decay includes: Step 4-1: Collect multiple signal values by collecting the pulse signals corresponding to a single particle generated after the radon gas undergoes atomic decay multiple times; Step 4-2: Determine the target particle corresponding to the multiple signal values, and the target particle is the first particle, the second particle, or the third particle; Step 4-3: Set the target quantity corresponding to the target particle to N + 1, where N is the quantity of the target particle determined before collecting the pulse signals corresponding to a single particle multiple times; Repeat steps 4-1 to 4-3 for M times to obtain the quantities of the first particle, the second particle, and the third particle respectively, where M is determined according to the preset time duration.

[0012] In the present application, within the preset time duration, by collecting the pulse signals corresponding to a single particle generated after the radon gas undergoes atomic decay multiple times to obtain multiple signal values, and determining the target particle according to the multiple signal values, the accuracy of particle type recognition can be improved.

[0013] In a feasible example, determining the target particle corresponding to the multiple signal values includes: Perform pulse waveform fitting on the multiple signal values based on the collection order to obtain the target pulse waveform; Determine the target peak value in the target pulse waveform; When it is determined that the change trend of the target pulse waveform meets the preset change trend and the target peak value is within the first peak value range corresponding to the first particle, determine that the target particle corresponding to the multiple signal values is the first particle; When it is determined that the change trend of the target pulse waveform meets the preset change trend and the target peak value is within the second peak value range corresponding to the second particle, determine that the target particle corresponding to the multiple signal values is the second particle; When it is determined that the change trend of the target pulse waveform meets the preset change trend and the target peak value is within the third peak value range corresponding to the third particle, the target particle corresponding to the multiple signal values is determined to be the third particle.

[0014] In this application, through the generation of a pulse waveform that eliminates the step effect based on mathematical fitting, the loss of details caused by the sampling interval can be compensated. And by combining the multi-dimensional determination conditions of the morphological parameters and the peak value range, the discrimination accuracy of the particle type can be improved, providing more accurate basic data for subsequent humidity compensation and concentration calculation.

[0015] In a feasible example, after determining the target peak value in the target pulse waveform, the method further includes: Determine the first slope corresponding to each signal value between the starting signal value and the target peak value in the target pulse waveform; Determine the second slope corresponding to each signal value between the target peak value and the end signal value in the target pulse waveform; Determine the first mean value among the multiple first slopes and the second mean value among the multiple second slopes; When the first mean value is greater than the first preset threshold and the second mean value is less than the second preset threshold, it is determined that the change trend of the target pulse waveform meets the preset change trend.

[0016] In this application, through the quantitative analysis of the slope statistical characteristics, the morphological judgment is upgraded from qualitative description to quantitative constraint, improving the recognition accuracy of the target particle. And the mean value statistical method can effectively filter the single-point noise interference, also improving the recognition accuracy of the target particle.

[0017] In a feasible example, determining the first concentration value of radon gas according to the first calibration coefficient and the number of the fourth particles includes: Obtain the air flow velocity; Adjust the first calibration coefficient according to the air flow velocity to obtain a third calibration coefficient, where the third calibration coefficient is less than the first calibration coefficient, and the faster the air flow velocity, the greater the difference between the first calibration coefficient and the third calibration coefficient; Determine the first concentration value of radon gas according to the third calibration coefficient and the number of the fourth particles.

[0018] In this application, by obtaining the air flow velocity in real time to establish a dynamic correction mechanism, the technical effects of improving the detection accuracy, enhancing the environmental adaptability and expanding the application scenarios can be achieved.

[0019] In a feasible example, adjusting the first calibration coefficient according to the air flow velocity to obtain a third calibration coefficient includes: When the air flow velocity is less than the preset velocity, determine a third calibration coefficient according to the difference between the first calibration coefficient and the first adjustment coefficient, where the first adjustment coefficient is determined according to the product of the first air flow velocity and the first weight value; When the first air flow velocity is greater than or equal to the preset velocity, determine the third calibration coefficient according to the product of the first calibration coefficient and the second adjustment coefficient, where the second adjustment coefficient is determined according to the negative exponential function of the third adjustment coefficient with the natural number as the base, and the third adjustment coefficient is determined according to the product of the first air flow velocity and the second weight value.

[0020] In this application, by comparing the air flow velocity with a preset threshold value to divide the low wind speed and high wind speed working condition types, and combining linear compensation and exponential compensation to differentially adjust the calibration coefficients under the low wind speed and high wind speed working conditions. Among them, the linear compensation realizes the progressive compensation of the low wind speed working condition through simple subtraction operations, and the exponential compensation uses exponential function operations to cope with the sharp impact of the high wind speed working condition. Significantly improve the adaptability and detection accuracy of the detection instrument in a complex air flow environment.

[0021] In a second aspect, this application provides a radon detection device, which includes: An acquisition unit, configured to acquire the quantities corresponding to the first particle, the second particle, and the third particle generated after the atomic decay of the radon gas collected within a preset duration, where the first particle is the particle emitted after the decay of radon-222, the second particle is the particle emitted after the decay of polonium-218, and the third particle is the particle emitted after the decay of polonium-214; A processing unit, configured to determine a first humidity value according to the first ratio between the quantity of the fourth particle and the quantity of the first particle, where the fourth particle is the second particle or the third particle, and the smaller the first ratio, the larger the first humidity value; The processing unit is further configured to determine a first calibration coefficient according to the first humidity value, and the smaller the first humidity value, the smaller the first calibration coefficient; The processing unit is further configured to determine a first concentration value of the radon gas according to the first calibration coefficient and the quantity of the fifth particle, where the fifth particle is at least one of the second particle and the third particle.

[0022] In a third aspect, this application provides an electronic device, which includes a processor, a memory, and a communication interface. The processor, the memory, and the communication interface are interconnected and complete the communication work among them. The memory stores executable program codes, the communication interface is used for wireless communication, and the processor is used to retrieve the executable program codes stored on the memory and execute some or all of the steps described in any method of the first aspect.

[0023] Fourthly, the present application provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements some or all of the steps described in the first aspect of the present application.

[0024] Fifthly, the present application provides a computer program product including a computer program which, when executed by a processor, implements some or all of the steps described in the first aspect of the present application. This computer program product can be a software installation package. Description of the Drawings

[0025] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following briefly introduces the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0026] Figure 1 It is a schematic structural diagram of a radon gas detection system provided by an embodiment of the present application; Figure 2 It is a schematic flowchart of a radon gas detection method provided by an embodiment of the present application; Figure 3 It is a schematic flowchart of another radon gas detection method provided by an embodiment of the present application; Figure 4 It is a schematic flowchart of yet another radon gas detection method provided by an embodiment of the present application; Figure 5 It is a schematic flowchart of still another radon gas detection method provided by an embodiment of the present application; Figure 6 It is a schematic structural diagram of a pulse waveform provided by an embodiment of the present application; Figure 7 It is a block diagram of the functional units of a radon gas detection device provided by an embodiment of the present application; Figure 8 It is a block diagram of the functional units of another radon gas detection device provided by an embodiment of the present application; Figure 9 It is a block diagram of the structure of an electronic device provided by an embodiment of the present application. Detailed Embodiments

[0027] To enable those skilled in the art to better understand the solution of this application, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without creative efforts belong to the scope of protection of this application.

[0028] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned accompanying drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps is not limited to the listed steps, but optionally further includes steps not listed, or optionally further includes other steps inherent to these processes, methods, products or devices.

[0029] Referring to "embodiments" herein means that the specific features, structures or characteristics described in conjunction with the embodiments can be included in at least one embodiment of this application. The appearance of this phrase at various positions in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0030] Radon is a radioactive element that exists in a gaseous state under normal temperature and pressure. It is generally formed near the surface of uranium-containing substances such as soil or rock and diffuses into the surrounding air. Radon gas is colorless and odorless, which means that it is difficult for humans to detect its presence and concentration. Since radon gas is radioactive, long-term exposure to high concentrations of radon gas will greatly increase the risk of cancer and is the second leading cause of fatal lung cancer after smoking. At the same time, when detecting the concentration of radon gas, it is mainly through collecting the number of particles generated during the decay of radon gas. After radon gas decays, it will produce positively charged daughter body polonium, and there is a certain probability that polonium will be neutralized by water molecules (OH-) in the environment. Therefore, the environmental humidity state will have a certain impact on the concentration calculation of radon gas. It is necessary to supplement the concentration of radon gas through the environmental humidity state. Moreover, high humidity will inhibit the diffusion of radon gas, resulting in a decrease in the number of particles emitted after the decay of radon gas detected.

[0031] The current radon gas detection instruments mainly detect the current humidity by adding an additional humidity sensor, so as to make an additional compensation for the concentration of radon gas. However, this will increase the production cost of the detection instrument.

[0032] Based on this, the present application obtains the quantities corresponding to the first particle, the second particle, and the third particle respectively generated after the atomic decay of the radon gas collected within a preset time period. The first particle is the particle emitted after the decay of radon-222, the second particle is the particle emitted after the decay of polonium-218, and the third particle is the particle emitted after the decay of polonium-214. Subsequently, a first humidity value is determined according to the first ratio between the quantity of the fourth particle and the quantity of the first particle. The fourth particle is either the second particle or the third particle. The smaller the first ratio, the larger the first humidity value. A first calibration coefficient is determined according to the first humidity value. The smaller the first humidity value, the smaller the first calibration coefficient. A first concentration value of the radon gas is determined according to the first calibration coefficient and the quantity of the fifth particle. The fifth particle is at least one of the second particle and the third particle.

[0033] Since polonium-218 and polonium-214 are positively charged particles and there is a certain probability that they will be neutralized by water molecules (OH-) in the environment, they are greatly affected by humidity. However, radon-222 is a gas and will not be neutralized by water molecules (OH-). Therefore, under different humidity conditions and with a constant radon gas concentration, the change in the collected quantity of the particles emitted by radon-222 is small, but the collected quantities of the particles emitted by polonium-218 and polonium-214 will be significantly affected. Therefore, the change in humidity can be reflected by measuring the ratio of the collected quantity of the particles emitted by polonium-218 or polonium-214 to the collected quantity of the particles emitted by radon-222 under different humidity conditions. For example, when the ratio becomes smaller, it indicates that the humidity increases. This can avoid the situation of introducing a humidity sensor to determine the humidity value when measuring the radon gas concentration, thereby reducing the production cost of the product.

[0034] The following introduces the prior art related to the present application.

[0035] An analog-to-digital converter (ADC) is an electronic component that converts an analog signal into a digital signal.

[0036] Radon-222 refers to a part of radon that will release particles through alpha decay.

[0037] Polonium-218 refers to the daughter product generated by the decay of radon-222.

[0038] Polonium-214 refers to the product of the decay of polonium-218 and can be collectively referred to as radon daughters with polonium-218.

[0039] An alpha particle refers to a particle emitted when a radioactive substance undergoes alpha decay.

[0040] The radon-222 decay chain. When radon decays, it emits α particles with an energy of approximately 5.49 MeV. The generated polonium (Po)-218 has a half-life of approximately 3 minutes and then emits α particles with an energy of approximately 6.0 MeV. The generated lead-214 has a half-life of approximately 27 minutes and then undergoes β decay to form bismuth-214, and the half-life of bismuth-214 is 20 minutes, after which it undergoes β decay to form polonium-214. The half-life of polonium-214 is approximately 164 microseconds, and then it emits α particles with an energy of approximately 7.7 MeV to generate lead-210, and the half-life of lead-210 is 22 years.

[0041] Bq / m³ (becquerels per cubic meter) is used to represent the radioactivity of radon in each cubic meter of air. 100 Bq / m³ means that in 1 cubic meter of air, radon atoms decay 100 times per second.

[0042] The following introduces the system architecture involved in this application.

[0043] Please refer to Figure 1 , Figure 1 which is a schematic structural diagram of a radon gas detection system provided by an embodiment of this application. As Figure 1 shown, the radon gas detection system 100 includes an electrostatic collection chamber 101, a photodiode 102, a preamplifier circuit 103, a linear pulse amplifier circuit 104, a comparator 105, and a controller 106.

[0044] The electrostatic collection chamber 101 mainly captures and concentrates the α particles generated during the decay of radon gas into the detection area of the photodiode 102 through the action of an electrostatic field.

[0045] The photodiode 102 is mainly used to convert the kinetic energy of α particles into an optical signal and then convert it into an electrical signal through the photoelectric effect.

[0046] The preamplifier circuit 103 is mainly used to preliminarily amplify and shape the weak electrical signal output by the photodiode 102 to improve the signal-to-noise ratio and match the input requirements of the subsequent circuit.

[0047] The linear pulse amplifier circuit 104 is mainly used to further amplify the amplified pulse signal and adjust its amplitude and width to meet the input requirements of the comparator.

[0048] The comparator 105 is used to compare the analog signal output by the linear pulse amplifier circuit 104 with a preset threshold, and at the same time, it also outputs an interrupt signal (high / low level) for triggering ADC sampling.

[0049] The controller 106 includes an ADC detection port for converting the analog electrical signal into a digital signal and performing analysis and processing.

[0050] Specifically, after the gas to be measured enters the electrostatic collection chamber 101, atomic decay occurs. The generated α particles are converted into electrical signals by the photodiode 102. After the pre-amplification circuit 103 obtains the electrical signals, it shapes and amplifies them. The linear pulse amplification circuit 104 further amplifies the electrical signals and adjusts the pulse width. After noise reduction processing by the comparator 105, the signals are input to the ADC detection port of the controller 106, where the analog electrical signals are converted into digital signals and analyzed and processed.

[0051] Based on this, the controller 106 obtains the quantities corresponding to the first particles, second particles, and third particles generated after the radon gas collected within a preset time duration undergoes atomic decay. The first particles are the particles emitted after the decay of radon-222, the second particles are the particles emitted after the decay of polonium-218, and the third particles are the particles emitted after the decay of polonium-214. Subsequently, a first humidity value is determined according to the first ratio between the quantity of the fourth particles and the quantity of the first particles. The fourth particles are any one of the second particles and the third particles. The smaller the first ratio, the larger the first humidity value. A first calibration coefficient is determined according to the first humidity value. The smaller the first humidity value, the smaller the first calibration coefficient. The first concentration value of the radon gas is determined according to the first calibration coefficient and the quantity of the fifth particles. The fifth particles are at least one of the second particles and the third particles.

[0052] Since polonium-218 and polonium-214 are positively charged particles and there is a certain probability that they will be neutralized by water molecules (OH-) in the environment, they are greatly affected by humidity. However, radon-222 is a gas and will not be neutralized by water molecules (OH-). Therefore, under different humidity conditions and a constant radon gas concentration, the change in the collected quantity of the particles emitted by radon-222 is small, but the collected quantity of the particles emitted by polonium-218 and polonium-214 will be greatly affected. Therefore, in this application, by measuring the ratio of the collected quantity of the particles emitted by polonium-218 or polonium-214 to the collected quantity of the particles emitted by radon-222 under different humidity conditions, the change in humidity is reflected. For example, when the ratio becomes smaller, it indicates that the humidity increases. This can avoid adding an additional humidity sensor to determine the humidity value, thereby reducing the production cost of the product.

[0053] Based on this, the embodiments of this application provide a radon gas detection method, which will be described in detail below with reference to the accompanying drawings.

[0054] Embodiment 1, the main process of the radon gas detection method will be described below.

[0055] Please refer to Figure 2 , Figure 2 which is a schematic flowchart of a radon gas detection method provided by the embodiments of this application. This method is applied to the above-mentioned controller. As Figure 2 shown, this method includes the following steps.

[0056] Step S201: Obtain the respective quantities of the first particle, the second particle, and the third particle generated after the atomic decay of the radon gas collected within a preset time period.

[0057] Among them, the first particle is the particle emitted after the decay of radon-222 (half-life of approximately 3.8 days), the second particle is the particle emitted after the decay of polonium-218 (half-life of approximately 3 minutes), and the third particle is the particle emitted after the decay of polonium-214 (half-life of only 164 microseconds), and their energies are approximately 5.49 MeV, approximately 6.0 MeV, and approximately 7.69 MeV respectively. The quantities of the first particle, the second particle, and the third particle can be obtained by using an electrostatic collection chamber to capture the radon gas in the environment, and using the electric field effect to move the charged particles generated by the decay to the surface of the photodiode. After the photoelectric effect generates current pulses, continuous sampling is carried out through a preamplifier circuit, a linear pulse amplifier circuit, a comparator to trigger the ADC module, and finally the ADC data is analyzed through a filtering algorithm and the count values of each particle are statistically obtained.

[0058] Step S202: Determine the first humidity value according to the first ratio between the quantity of the fourth particle and the quantity of the first particle.

[0059] Among them, the fourth particle is the second particle or the third particle. The smaller the first ratio, the larger the first humidity value. The fourth particle can be a general term for the particles emitted by polonium-218 or polonium-214. Both are positively charged daughters and are prone to neutralization reactions with water molecules (OH⁻) in the air. The first humidity value can be obtained by mapping the first ratio to a preset calibration curve. For example, when the humidity increases, the probability of water molecules neutralizing polonium particles increases, resulting in a decrease in the count of the fourth particle, while radon-222 is not easily neutralized by water molecules (OH⁻), thereby causing the first ratio to decrease, and the corresponding first humidity value increases. This process calculates the ratio through the count values extracted from the previous steps and combines the corresponding calibration curve to achieve a quantitative assessment of the humidity state, avoiding the direct use of a humidity sensor, and indirectly reflecting the environmental humidity by using the sensitivity of polonium particles to humidity.

[0060] Step S203: Determine the first calibration coefficient according to the first humidity value.

[0061] Among them, the smaller the first humidity value, the smaller the first calibration coefficient. The first calibration coefficient can be a correction parameter used to convert the count data into the actual concentration, and its value has a positive correlation with humidity. The calibration coefficient can be obtained by querying the calibration curve stored in the microcontroller's FLASH. This curve is established based on the relationship between the count and the concentration measured in advance at different humidities in a radon gas generation device with a constant concentration. For example, at low humidity, the polonium particle count is relatively high, and at this time, the value of the calibration coefficient K is small; conversely, at high humidity, the polonium particle count decreases, and the K value needs to be increased to compensate for the concentration calculation deviation. This process dynamically adjusts the calibration coefficient to enable the concentration calculation result to adapt to the count changes under different humidity conditions and improve the detection accuracy.

[0062] Step S204, determine the first concentration value of the radon gas according to the first calibration coefficient and the number of the fifth particles.

[0063] Among them, the fifth particle is at least one of the second particle and the third particle. The first concentration value can be the finally output radon gas concentration result, with the unit of Bq / m³, and is calculated by the product of the calibration coefficient and the count data. The number of the fifth particles can be the count values of polonium-218 and / or polonium-214.

[0064] Before the current step, place the device in a radon gas generation device with a constant concentration and humidity to calibrate the device. After a period of time, a certain amount of counts will be collected for the first particle, the second particle, and the third particle. Since radon is a gas and is not affected by the electric field in the diffusion chamber, it may exist at any position in the diffusion chamber. Therefore, only a relatively low probability of the α particles emitted by it can hit the photodiode in the diffusion chamber. While polonium is a positively charged particle and will move to the photodiode under the action of the electric field in the diffusion chamber and then decay on the photodiode, and the α particles emitted have a high probability of hitting the photodiode. So the count of the first particle will be less than the counts of the second particle and the third particle. In this case, if the count of the first particle is directly used to estimate the radon gas concentration, the result will not be accurate enough due to the too low count rate. Although the second particle and the third particle are not the counts generated by the radon parent body, they are also part of the decay chain and the source is radon. Therefore, the radon gas concentration can be indirectly obtained through the counts of the second particle and the third particle. And since polonium-214 is decayed from polonium-218 and is also positively charged, when the concentration is balanced, the count of the second particle is approximately equal to that of the third particle. By calibrating different concentration points in the radon gas generation device, the relationship between the concentration and the count rate can be reflected. That is, the concentration is equal to the number of the fourth particles multiplied by the corresponding calibration coefficient. And the sum of the numbers of the second particle and the third particle can also be used for calibration. In this way, on the basis of the increased count rate, the accuracy of the concentration detection can also be improved.

[0065] It can be seen that in this application, by acquiring the particles emitted after the decay of radon-222, polonium-218, and polonium-214, indirectly inferring the environmental humidity using the ratio of the count of radon-222 to the progeny count of polonium, and dynamically adjusting the calibration coefficient based on the humidity state, and finally calculating the concentration value by combining the progeny count of polonium, the following technical effects can be achieved: humidity compensation is realized through the energy spectrum analysis and ratio relationship of atomic decay products, avoiding the hardware cost of additional humidity sensors, and significantly improving the detection sensitivity in low-concentration environments by using the progeny count of polonium instead of the parent count.

[0066] Embodiment 2. Based on the method for determining the first calibration coefficient, the radon detection method will be described in detail below.

[0067] Please refer to Figure 3 , Figure 3 which is a schematic flowchart of another radon detection method provided by an embodiment of this application. This method is applied to the above-mentioned controller, as Figure 3 shown. This method includes the following steps.

[0068] Step S301: Obtain the quantities corresponding to the first particle, the second particle, and the third particle generated after the atomic decay of the radon gas collected within a preset time period.

[0069] Step S302: Determine the first humidity value according to the first ratio between the quantity of the fourth particle and the quantity of the first particle.

[0070] Step S303: Obtain the calibration coefficient-concentration curve corresponding to the first humidity value.

[0071] Among them, the calibration coefficient-concentration curve is used to represent the calibration coefficients corresponding to different concentrations. The calibration coefficient-concentration curve can be a pre-established parameter mapping relationship used to characterize the correlation between environmental humidity, radon gas concentration, and the calibration coefficient, and can be generated by experimental calibration or data fitting. Exemplarily, there can be multiple calibration coefficient-concentration curves, and multiple calibration coefficient-concentration curves respectively correspond to different humidity conditions, and each calibration coefficient-concentration curve contains the calibration coefficients corresponding to different concentrations. For example, when the humidity is 50%, the calibration coefficient corresponding to a concentration of 200 Bq / m³ may be 0.8, and the calibration coefficient corresponding to a concentration of 400 Bq / m³ may be 0.6.

[0072] Step S304: Determine the second ratio between the concentration and the calibration coefficient corresponding to each coordinate point among the multiple coordinate points on the calibration coefficient-concentration curve.

[0073] Among them, the second ratio is the ratio of the concentration to the calibration coefficient, that is, the value obtained by dividing the concentration value of each coordinate point among multiple coordinate points on the curve by the corresponding calibration coefficient value. Exemplarily, if the concentration of a certain coordinate point is C1 and the calibration coefficient is K1, then the second ratio is C1 / K1. The calculation of this ratio can convert the correlation between the concentration and the calibration coefficient into an intermediate variable, facilitating the subsequent matching process. It can be understood that the multiple coordinate points on the calibration coefficient-concentration curve can be multiple coordinate points selected from the calibration coefficient-concentration curve based on a preset concentration interval.

[0074] Step S305: Determine the target coordinate point corresponding to the second ratio corresponding to the number of the fifth particles among the multiple second ratios.

[0075] Among them, the target coordinate point can be the coordinate position on the calibration coefficient-concentration curve where the second ratio is the same as the number of the fifth particles. It can be understood that since the multiple second ratios are determined from multiple coordinate points selected from the calibration coefficient-concentration curve, there may not be a second ratio among the multiple second ratios that is exactly the same as the number of the fifth particles. In this case, the second ratio with the smallest difference from the number of the fifth particles can be selected as the second ratio corresponding to the number of the fifth particles among the multiple second ratios.

[0076] Step S306: Determine the calibration coefficient corresponding to the target coordinate point on the calibration coefficient-concentration curve as the first calibration coefficient.

[0077] It can be seen that the above process calls the calibration coefficient-concentration curve in the storage unit, calculates the ratio of the concentration to the calibration coefficient of each coordinate point, and locates the target coordinate point based on the matching relationship between the current number of the fifth particles and the ratio, and finally extracts the corresponding calibration coefficient as the compensation parameter. In this way, through the collaborative optimization of humidity, concentration, and calibration coefficient, the influence of humidity and concentration on the calibration coefficient can be considered respectively, and at the same time, the pre-stored curve data can be used to improve the efficiency of locating the calibration coefficient, enhancing the detection accuracy and anti-interference ability of the radon gas detection instrument under environmental conditions of humidity change and concentration fluctuation.

[0078] Step S307: Determine the first concentration value of the radon gas according to the first calibration coefficient and the number of the fifth particles.

[0079] Embodiment 3: Based on another determination method of the first calibration coefficient, the radon gas detection method will be described in detail below.

[0080] Please refer to Figure 4 , Figure 4 which is a schematic flowchart of another radon gas detection method provided by the embodiment of the present application. This method is applied to the above-mentioned controller, as Figure 4 shown, and this method includes the following steps.

[0081] Step S401: Obtain the quantities corresponding to the first particle, the second particle, and the third particle respectively that are generated after the radon gas collected within a preset duration undergoes atomic decay.

[0082] Step S402: Determine the first humidity value based on the first ratio between the quantity of the fourth particle and the quantity of the first particle.

[0083] Step S403: Obtain the calibration coefficient - humidity curve and the calibration coefficient - concentration curve.

[0084] Among them, the calibration coefficient - humidity curve is used to represent the calibration coefficients corresponding to different humidities, and the calibration coefficient - concentration curve is used to represent the calibration coefficients corresponding to different concentrations.

[0085] The calibration coefficient - humidity curve can be a pre - stored data set that records the correspondence between different humidity values and calibration coefficients under a fixed concentration condition, and can be obtained by calling the storage unit of the controller. The calibration coefficient - concentration curve can be a pre - stored data set that records the correspondence between different concentration values and calibration coefficients under a fixed humidity condition, and can be obtained by calling the same storage unit.

[0086] By calling these two curves simultaneously, it can provide multi - dimensional parameter constraints for the subsequent dynamic calibration of the calibration coefficient. For example, when both humidity and concentration change, it can avoid the limitations of single - variable mapping.

[0087] Step S404: Determine the second calibration coefficient corresponding to the first humidity value according to the calibration coefficient - humidity curve.

[0088] Among them, the second calibration coefficient can be an initial compensation parameter obtained by matching in the calibration coefficient - humidity curve based on the currently measured humidity value. Exemplarily, if the current humidity is 60%, then by looking up the curve data points, K1 = 0.75 can be obtained. This process initially establishes the influence compensation of environmental humidity on the detection result through the direct mapping relationship between humidity and the calibration coefficient.

[0089] Step S405: Determine the second concentration value based on the second calibration coefficient and the quantity of the fifth particle.

[0090] Among them, the second concentration value can be determined according to the product of the second calibration coefficient and the quantity of the fifth particle.

[0091] Step S406: Determine the first calibration coefficient according to the second concentration value and the calibration coefficient - concentration curve. The first calibration coefficient corresponds to the second concentration value.

[0092] The above process first calculates the initial concentration through the initial second calibration coefficient corresponding to the current humidity, and then determines the first calibration coefficient from the calibration coefficient-concentration curve based on the initial concentration, thereby enabling a feedback loop adjustment of the calibration coefficient. This solves the possible deviation of a single variable mapping and enhances the detection accuracy and anti-interference ability of the radon gas detection instrument under environmental conditions of humidity change and concentration fluctuation.

[0093] Step S407: Determine the first concentration value of radon gas according to the first calibration coefficient and the number of fifth particles.

[0094] Embodiment 4: The radon gas detection method will be described in detail below based on the acquisition details of the number of target particles.

[0095] Please refer to Figure 5 , Figure 5 , which is a schematic flowchart of another radon gas detection method provided by an embodiment of the present application. This method is applied to the above-mentioned controller, as Figure 5 shown. The method includes the following steps.

[0096] Step S501: Collect multiple signal values by collecting multiple times the pulse signals corresponding to single particles generated after the atomic decay of radon gas.

[0097] Among them, the pulse signals corresponding to single particles generated after the atomic decay of radon gas are transmitted from the comparator to the controller. When the comparator transmits this pulse signal, it also transmits an interrupt signal for controlling the ADC to perform multiple collections.

[0098] This multiple collection can refer to multiple analog-to-digital conversion operations continuously performed by the ADC after a single interrupt signal is triggered. It forms a waveform sequence containing noise and valid signals through continuous sampling at a fixed time interval. The implementation of multiple collections can be achieved by the controller starting the continuous collection mode of the ADC after receiving the interrupt signal, for example, continuously collecting 100 signal values at intervals of 5 μs.

[0099] Step S502: Determine the target particles corresponding to the multiple signal values.

[0100] Among them, the target particles are the first particle, the second particle, or the third particle. The determination of the target particles can be achieved by detecting the multiple signal values collected through a filtering algorithm.

[0101] In a specific example, determining the target particles corresponding to multiple signal values includes: performing pulse waveform fitting on the multiple signal values based on the acquisition order to obtain a target pulse waveform; determining the target peak value in the target pulse waveform; when it is determined that the change trend of the target pulse waveform meets a preset change trend and the target peak value is within the first peak value range corresponding to the first particle, determining that the target particle corresponding to the multiple signal values is the first particle; when it is determined that the change trend of the target pulse waveform meets a preset change trend and the target peak value is within the second peak value range corresponding to the second particle, determining that the target particle corresponding to the multiple signal values is the second particle; when it is determined that the change trend of the target pulse waveform meets a preset change trend and the target peak value is within the third peak value range corresponding to the third particle, determining that the target particle corresponding to the multiple signal values is the third particle.

[0102] Among them, pulse waveform fitting can be a process of curve fitting the continuously acquired signal values through mathematical methods to eliminate the step effect, which can be achieved through cubic spline interpolation or exponential decay model. Exemplarily, the fitting method includes using different models for the rising edge and the falling edge respectively to match the response characteristics of the photodiode. The target peak value can be the highest point value of the waveform curve after fitting, and can be extracted from the fitting result through a peak detection algorithm. Exemplarily, the peak value can be used to reflect the total ionization energy released by the interaction between alpha particles and the photodiode. The preset change trend can be the fluctuation state of the waveform. For example, it is first in an upward fluctuation state, and after reaching the high point, it is in a downward fluctuation state.

[0103] The first peak value range can be the signal value interval corresponding to the specific particle energy. Exemplarily, the range can be set as [450, 460] channel addresses for the first particle. The preset change trend can be a combined constraint of parameters such as the waveform rise time and the full width at half maximum. Exemplarily, the morphology can include that the steepness of the rising edge needs to be greater than a threshold and the waveform symmetry parameter is within a specified interval. The second peak value range and the third peak value range can be the signal value intervals corresponding to different particle energies. Exemplarily, the second peak value range and the third peak value range can be set as [560, 570] channel addresses and [670, 680] channel addresses respectively to distinguish the second particle from the third particle.

[0104] It can be seen that through the generation of the pulse waveform that eliminates the step effect based on mathematical fitting, the loss of details caused by the sampling interval can be compensated. And by combining the multi-dimensional determination conditions of the morphological parameters and the peak value range, the discrimination accuracy of the particle type can be improved, providing more accurate basic data for subsequent humidity compensation and concentration calculation.

[0105] Further, after determining the target peak value in the target pulse waveform, the method further includes: determining, in the target pulse waveform, a first slope corresponding to each signal value between the starting signal value and the target peak value; determining, in the target pulse waveform, a second slope corresponding to each signal value between the target peak value and the end signal value; determining a first mean value among the multiple first slopes and a second mean value among the multiple second slopes; and when the first mean value is greater than a first preset threshold and the second mean value is less than a second preset threshold, determining that the change trend of the target pulse waveform meets a preset change trend.

[0106] Wherein, the first slope can be a quantization parameter representing the local steepness of the rising segment of the waveform, and can be calculated by the ratio of the difference between the signal values of adjacent sampling points to the acquisition time interval. Exemplarily, in the signal values of adjacent sampling points, the calculation formula for the first slope corresponding to the later signal value is:

[0107] Wherein, ΔV / Δt represents the first slope, V1 and V2 respectively represent the signal values of adjacent front and back points, and Δt represents the time interval.

[0108] The second slope can be a quantization parameter representing the local attenuation rate of the falling segment of the waveform, and its acquisition method is the same as that of the first slope, but the calculation range is limited to the interval from the target peak value to the end signal value. This is because the pulse waveforms corresponding to the first particle, the second particle, and the third particle should satisfy the morphology of rising first and then falling. Therefore, when calculating, multiple signal values can be directly divided into two parts according to the peak value. Thus, the slopes corresponding to the signal values of the two parts are calculated respectively.

[0109] The first mean value can be a statistical characteristic value reflecting the overall rising trend of the waveform, and is obtained by adding all the first slope values and then dividing by the number of sampling points. The second mean value can be a statistical characteristic value reflecting the overall attenuation trend of the waveform, and its calculation method is the same as that of the first mean value. This is because during the process of obtaining signal values, there may be certain errors in the signal values. Then, for the left part of the peak value of the generated target pulse waveform, it may not be guaranteed that the slope corresponding to each signal value on the waveform is positive, and for the right part of the peak value of the generated target pulse waveform, it may not be guaranteed that the slope corresponding to each signal value on the waveform is negative. Therefore, the first mean value is used to reflect the slope of the overall rising trend of the waveform, and the second mean value is used to reflect the slope of the overall falling trend of the waveform.

[0110] Based on this, the first preset threshold can be a reference value of the rising segment slope set according to the energy characteristics of the target particle. The second preset threshold can be a reference value of the falling segment slope set according to the attenuation characteristics of the target particle. The first preset threshold should be greater than zero, and the second preset threshold should be less than zero.

[0111] It can be seen that through the quantitative analysis of the slope statistical features, the morphological judgment is upgraded from qualitative description to quantitative constraint, improving the recognition accuracy of target particles. Moreover, the mean statistical method can effectively filter out the interference of single-point noise, also improving the recognition accuracy of target particles.

[0112] Exemplarily, please refer to Figure 6 , Figure 6 which is a schematic structural diagram of a pulse waveform provided by an embodiment of the present application. As Figure 6 shown, it includes the pulse waveform corresponding to the first particle with a peak value of 452, the pulse waveform corresponding to the second particle with a peak value of 561, and the pulse waveform corresponding to the third particle with a peak value of 674. The horizontal axis of this pulse waveform corresponds to the number of acquisitions, and the vertical axis corresponds to the ADC channel address (signal value). It can be understood that this peak value is used to reflect the energy of the α particle. For example, the peak value of 452 is the 5.49Mev α particle emitted by radon-222, the peak value of 561 is the 6Mev α particle emitted by radon daughter polonium-218, and the peak value of 674 is the 7.69Mev α particle emitted by radon daughter polonium-214.

[0113] Step S503, set the target number corresponding to the target particle to N + 1.

[0114] Wherein, N is the number of target particles determined before multiple acquisitions of the pulse signal corresponding to a single particle. For example, when it is determined that multiple signal values correspond to the first particle, the current value of the counter corresponding to the first particle is incremented by 1. It can be understood that in the actual application process, not every acquisition cycle will collect a single particle among the first particle, the second particle, or the third particle. When the obtained target pulse waveforms do not meet the pulse waveforms corresponding to the first particle, the second particle, or the third particle, the acquisition of the next cycle will be restarted.

[0115] Step S504, repeat steps S501 to S503 M times to obtain the numbers of the first particle, the second particle, and the third particle respectively.

[0116] Wherein, M is determined according to a preset duration. It can be understood that this preset duration is also the standard duration of the experiment corresponding to the determination of the aforementioned calibration coefficient-concentration curve and calibration coefficient-humidity curve. The operation of repeating step M times can be achieved by calculating the ratio of the preset duration to the duration of a single acquisition cycle. For example, if the preset duration is 1 hour and each acquisition cycle takes 1 second, then M = 3600 times. The determination of the M value can be based on the duration requirement of the detection task and the system resource allocation strategy. For example, by setting the total detection duration and calculating the corresponding number of cycles to balance accuracy and energy consumption.

[0117] It can be seen that within the preset time period, multiple signal values are obtained by multiple acquisitions of pulse signals corresponding to single particles generated after atomic decay of radon gas, and target particles are determined based on the multiple signal values, which can improve the accuracy of particle type recognition.

[0118] Step S505, obtaining the number of target particles generated by atomic decay of radon gas collected within a preset time period.

[0119] Among them, the target particle is the first particle, the second particle or the third particle, the first particle is the particle emitted after the decay of radon-222, the second particle is the particle emitted after the decay of polonium-218, and the third particle is the particle emitted after the decay of polonium-214.

[0120] Step S506 , determining a first humidity value according to a first ratio between the number of fourth particles and the number of first particles.

[0121] The fourth particle is any one of the second particle and the third particle, and the smaller the first ratio is, the larger the first humidity value is.

[0122] Step S507: determining a first calibration coefficient according to the first humidity value.

[0123] Among them, the smaller the first humidity value is, the smaller the first calibration coefficient is.

[0124] Step S508: determining a first concentration value of radon gas according to the first calibration coefficient and the number of fifth particles.

[0125] The fifth particle is at least one of the second particle and the third particle.

[0126] Furthermore, a first concentration value of radon gas is determined according to the first calibration coefficient and the number of fourth particles, including: obtaining the airflow velocity; adjusting the first calibration coefficient according to the airflow velocity to obtain a third calibration coefficient, the third calibration coefficient being smaller than the first calibration coefficient, and the faster the airflow velocity, the greater the difference between the first calibration coefficient and the third calibration coefficient; and determining the first concentration value of radon gas according to the third calibration coefficient and the number of fourth particles.

[0127] The airflow velocity may be a physical quantity that characterizes the flow rate of ambient air, and may be obtained through a built-in or external airflow sensor, and the sensor may include one or more of a thermal sensor, a differential pressure sensor, or an ultrasonic sensor. For example, a thermal sensor calculates the airflow velocity by detecting changes in the heat dissipation rate of a component, and its working principle is based on the correlation between heat transfer and air flow rate in thermodynamics.

[0128] The third calibration coefficient can be a dynamically adjusted parameter obtained by correcting the first calibration coefficient with the air flow velocity. The difference between the first calibration coefficient and the third calibration coefficient is positively correlated with the air flow velocity. Exemplarily, when the air flow velocity increases from 0.1 m / s to 0.5 m / s, the reduction amplitude of the third calibration coefficient relative to the initial value will increase with the increase in velocity.

[0129] Adjusting the first calibration coefficient according to the air flow velocity can be achieved by establishing a mapping relationship between the air flow velocity and the calibration coefficient correction factor. In a specific embodiment, this mapping relationship is obtained through experimental calibration.

[0130] It can be seen that by obtaining the air flow velocity in real time to establish a dynamic correction mechanism, technical effects such as improving detection accuracy, enhancing environmental adaptability, and expanding application scenarios can be achieved.

[0131] Furthermore, adjusting the first calibration coefficient according to the air flow velocity to obtain the third calibration coefficient includes: when the air flow velocity is less than the preset velocity, determining the third calibration coefficient according to the difference between the first calibration coefficient and the first adjustment coefficient, where the first adjustment coefficient is determined according to the product of the first air flow velocity and the first weight; when the first air flow velocity is greater than or equal to the preset velocity, determining the third calibration coefficient according to the product of the first calibration coefficient and the second adjustment coefficient, where the second adjustment coefficient is determined according to the negative exponential function of the third adjustment coefficient with the natural number as the base, and the third adjustment coefficient is determined according to the product of the first air flow velocity and the second weight.

[0132] Among them, the preset velocity is a threshold parameter set in advance, such as 0.5 m / s, which is used as the determination benchmark for dividing low-speed and high-speed working conditions. The first adjustment coefficient is an intermediate variable in the linear compensation model, and its value is determined by the product of the air flow velocity and the first weight. The first weight is an experimentally calibrated linear compensation coefficient, such as 0.02 / (m / s), which is stored in the storage unit of the microcontroller. When the air flow velocity is less than the preset velocity, the adjustment formula for the first calibration coefficient is as follows:

[0133] Among them, T3 is used to represent the third calibration coefficient, T1 is used to represent the first calibration coefficient, v is used to represent the air flow velocity, and a is used to represent the first weight.

[0134] The second adjustment coefficient is an intermediate variable in the exponential compensation model, and its value is generated by the negative exponential function operation of the natural number. The exponential part of this exponential function is composed of the product of the air flow velocity and the second weight. The second weight is an experimentally calibrated exponential compensation coefficient, such as 0.1 / (m / s), which is also determined by experimental fitting. When the air flow velocity is greater than or equal to the preset velocity, the adjustment formula for the first calibration coefficient is as follows:

[0135] Among them, e is used to represent a natural number, and b is used to represent the second weight value.

[0136] It can be seen that by comparing the air flow velocity with a preset threshold to divide the low wind speed and high wind speed working condition types, and combining linear compensation and exponential compensation to differentially adjust the calibration coefficients under the low wind speed and high wind speed working conditions respectively. Among them, linear compensation realizes the progressive compensation of the low wind speed working condition through simple subtraction operations, and exponential compensation uses exponential function operations to cope with the sharp influence of the high wind speed working condition. This significantly improves the adaptability and detection accuracy of the detection instrument in a complex air flow environment.

[0137] Consistent with the embodiments shown above, please refer to Figure 7 , Figure 7 This is a functional unit composition block diagram of a radon detection device provided by an embodiment of the present application. The radon detection device is a part of the above controller or the controller, as Figure 7 shown, the radon detection device 70 includes: An acquisition unit 701, configured to acquire the quantities corresponding to the first particle, the second particle, and the third particle generated after the atomic decay of the radon gas collected within a preset time period. The first particle is the particle emitted after the decay of radon-222, the second particle is the particle emitted after the decay of polonium-218, and the third particle is the particle emitted after the decay of polonium-214; A processing unit 702, configured to determine a first humidity value according to a first ratio between the quantity of the fourth particle and the quantity of the first particle. The fourth particle is the second particle or the third particle, and the smaller the first ratio, the larger the first humidity value; The processing unit 702 is further configured to determine a first calibration coefficient according to the first humidity value. The smaller the first humidity value, the smaller the first calibration coefficient; The processing unit 702 is further configured to determine a first concentration value of the radon gas according to the first calibration coefficient and the quantity of the fifth particle. The fifth particle is at least one of the second particle and the third particle.

[0138] In a feasible embodiment, in terms of determining the first calibration coefficient according to the first humidity value, the processing unit 702 is specifically configured to: Obtain a calibration coefficient-concentration curve corresponding to the first humidity value. The calibration coefficient-concentration curve is used to represent the calibration coefficients corresponding to different concentrations; Determine a second ratio between the concentration and the calibration coefficient corresponding to each coordinate point among multiple coordinate points on the calibration coefficient-concentration curve; Determine a target coordinate point corresponding to the second ratio corresponding to the quantity of the fifth particle among the multiple second ratios; Determine the calibration coefficient corresponding to the target coordinate point on the calibration coefficient-concentration curve as the first calibration coefficient.

[0139] In a feasible embodiment, in terms of determining the first calibration coefficient according to the first humidity value, the processing unit 702 is specifically configured to: Obtain a calibration coefficient-humidity curve and a calibration coefficient-concentration curve. The calibration coefficient-humidity curve is used to represent the corresponding calibration coefficients at different humidities, and the calibration coefficient-concentration curve is used to represent the corresponding calibration coefficients at different concentrations; Determine the second calibration coefficient corresponding to the first humidity value according to the calibration coefficient-humidity curve; Determine the second concentration value according to the second calibration coefficient and the number of fifth particles; Determine the first calibration coefficient according to the second concentration value and the calibration coefficient-concentration curve. The first calibration coefficient corresponds to the second concentration value.

[0140] In a feasible embodiment, in terms of obtaining the quantities corresponding to the first particle, the second particle, and the third particle respectively generated after the radon gas collected within a preset duration undergoes atomic decay, the obtaining unit 701 is specifically configured to: Step 4-1: Collect the pulse signals corresponding to a single particle generated after the radon gas undergoes atomic decay multiple times to obtain multiple signal values; Step 4-2: Determine the target particle corresponding to the multiple signal values. The target particle is the first particle, the second particle, or the third particle; Step 4-3: Set the target quantity corresponding to the target particle to N + 1, where N is the quantity of the target particle determined before collecting the pulse signals corresponding to the single particle multiple times; Repeat steps 4-1 to 4-3 for M times to obtain the quantities of the first particle, the second particle, and the third particle respectively. M is determined according to the preset duration.

[0141] In a feasible embodiment, in terms of determining the target particle corresponding to the multiple signal values, the obtaining unit 701 is specifically configured to: Perform pulse waveform fitting on the multiple signal values based on the collection order to obtain a target pulse waveform; Determine the target peak value in the target pulse waveform; When it is determined that the change trend of the target pulse waveform satisfies a preset change trend and the target peak value is within the first peak value range corresponding to the first particle, determine that the target particle corresponding to the multiple signal values is the first particle; When it is determined that the change trend of the target pulse waveform satisfies a preset change trend and the target peak value is within the second peak value range corresponding to the second particle, determine that the target particle corresponding to the multiple signal values is the second particle; When it is determined that the change trend of the target pulse waveform meets the preset change trend and the target peak value is within the third peak value range corresponding to the third particle, the target particle corresponding to the multiple signal values is determined to be the third particle.

[0142] In a feasible embodiment, after determining the target peak value in the target pulse waveform, the obtaining unit 701 is further configured to: Determine the first slope corresponding to each signal value between the starting signal value and the target peak value in the target pulse waveform; Determine the second slope corresponding to each signal value between the target peak value and the end signal value in the target pulse waveform; Determine the first mean value among the multiple first slopes and the second mean value among the multiple second slopes; When the first mean value is greater than the first preset threshold and the second mean value is less than the second preset threshold, it is determined that the change trend of the target pulse waveform meets the preset change trend.

[0143] In a feasible embodiment, in terms of determining the first concentration value of radon gas according to the first calibration coefficient and the number of the fourth particles, the processing unit 702 is specifically configured to: Obtain the air flow velocity; Adjust the first calibration coefficient according to the air flow velocity to obtain a third calibration coefficient, where the third calibration coefficient is less than the first calibration coefficient, and the faster the air flow velocity, the greater the difference between the first calibration coefficient and the third calibration coefficient; Determine the first concentration value of radon gas according to the third calibration coefficient and the number of the fourth particles.

[0144] In a feasible embodiment, in terms of adjusting the first calibration coefficient according to the air flow velocity to obtain the third calibration coefficient, the processing unit 702 is specifically configured to: When the air flow velocity is less than the preset velocity, determine the third calibration coefficient according to the difference between the first calibration coefficient and the first adjustment coefficient, where the first adjustment coefficient is determined according to the product of the first air flow velocity and the first weight; When the first air flow velocity is greater than or equal to the preset velocity, determine the third calibration coefficient according to the product of the first calibration coefficient and the second adjustment coefficient, where the second adjustment coefficient is determined according to the negative exponential function of the third adjustment coefficient with the natural number as the base, and the third adjustment coefficient is determined according to the product of the first air flow velocity and the second weight.

[0145] It can be understood that since the method embodiment and the device embodiment are different presentation forms of the same technical concept, therefore, the content of the method embodiment part in this application should be synchronously adapted to the device embodiment part, and will not be elaborated here.

[0146] In the case of adopting an integrated unit, as Figure 8 shownFigure 8 This is a functional unit composition block diagram of another radon gas detection device provided by an embodiment of the present application. In Figure 8 , the radon gas detection device 70 includes: a processing module 812 and a communication module 811. The processing module 812 is used to control and manage the actions of the radon gas detection device 70. For example, steps of an acquisition unit 701 and a processing unit 702, and / or other processes for implementing the technologies described herein. The communication module 811 is used to support the interaction between the radon gas detection device 70 and other devices. As Figure 8 shown, the radon gas detection device 70 may further include a storage module 813, and the storage module 813 is used to store program codes and data of the radon gas detection device 70.

[0147] Among them, the processing module 812 may be a processor or a controller. For example, it may be a central processing unit (CPU), a general-purpose processor, a digital signal processor (DSP), an ASIC, an FPGA or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute various exemplary logic blocks, modules, and circuits described in combination with the disclosure of the present application. The processor may also be a combination for implementing computing functions, such as a combination including one or more microprocessors, a combination of a DSP and a microprocessor, and so on. The communication module 811 may be a transceiver, an RF circuit, or a communication interface, etc. The storage module 813 may be a memory.

[0148] Among them, all relevant contents of each scenario involved in the above method embodiment can be cited in the function descriptions of the corresponding functional modules, and will not be repeated here. The above radon gas detection device 70 can all execute the above Figure 2 shown radon gas detection method.

[0149] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. A computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions according to the embodiments of the present application 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 devices. 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 in a wired or wireless manner. The computer-readable storage medium can be any available medium that the computer can access or a data storage device such as a server or data center that contains one or more collections of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0150] Figure 9 FIG. is a block diagram of an electronic device provided in an embodiment of the present application. As Figure 9 shown, the electronic device 900 may include one or more of the following components: a processor 901, a memory 902, and a communication interface 903. The processor 901, the memory 902, and the communication interface 903 are interconnected and perform communication with each other. The memory 902 may store one or more computer programs, and the one or more computer programs may be configured to be executed by one or more processors 901 to implement the methods described in the above embodiments.

[0151] The processor 901 may include one or more processing cores. The processor 901 connects various parts within the entire electronic device 900 using various interfaces and circuits. By running or executing instructions, programs, code sets, or instruction sets stored in the memory 902, and by invoking data stored in the memory 902, it performs various functions of the electronic device 900 and processes data. Optionally, the processor 901 may be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), or programmable logic array (PLA). The processor 901 may integrate a combination of one or several of a central processing unit (CPU), a graphics processing unit (GPU), and a modem, etc. It can be understood that the above-mentioned modem may not be integrated into the processor 901 and may be implemented separately through a communication chip.

[0152] The memory 902 may include a random access memory (RAM) and may also include a read-only memory (ROM). The memory 902 is used to store instructions, programs, code, code sets, or instruction sets. The memory 902 may include a program storage area and a data storage area. Among them, the program storage area may store instructions for implementing an operating system, instructions for implementing at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing each of the above method embodiments, etc. The data storage area may also store data created during the use of the electronic device 900.

[0153] It can be understood that the electronic device 900 may include more or fewer structural elements than those in the above structural block diagram. For example, it includes a power module, physical buttons, a WiFi (Wireless Fidelity) module, a speaker, a Bluetooth module, sensors, etc., which are not limited herein.

[0154] The above-mentioned electronic device 900 may be a controller or a part of a controller.

[0155] An embodiment of the present application provides a computer-readable storage medium. Among them, a computer program is stored in the computer-readable storage medium. When the computer program is executed by a processor, it implements some or all of the steps of any one of the radon gas detection methods described in the above method embodiments.

[0156] The embodiments of the present application also provide a computer program product, including a computer program. When the computer program is executed by a processor, it implements some or all of the steps of any one of the radon detection methods described in the foregoing method embodiments. This computer program product can be a software installation package.

[0157] It should be noted that, for any of the method embodiments of the foregoing radon detection methods, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the present application is not limited by the described action sequence, because according to the present application, some steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily essential to the present application.

[0158] Although the present application has been described in conjunction with various embodiments herein, however, in the process of implementing the claimed present application, those skilled in the art can understand and realize other variations of the disclosed embodiments by viewing the drawings, the disclosed content, and the appended claims. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude a plurality of situations. Certain measures are recited in mutually different dependent claims, but this does not mean that these measures cannot be combined to produce good results.

[0159] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of any of the foregoing method embodiments of the radon detection method can be completed by instructing relevant hardware through a program. This program can be stored in a computer-readable memory, and the memory can include: a flash drive, a read-only memory (abbreviation: ROM), a random access memory (abbreviation: RAM), a magnetic disk, or an optical disc, etc.

[0160] The above has introduced the embodiments of the present application in detail. Specific examples are used herein to elaborate on the principles and implementation manners of a radon detection method, device, electronic device, and storage medium of the present application. The description of the above embodiments is only used to help understand the method and its core idea of the present application; at the same time, for those of ordinary skill in the art, according to the idea of a radon detection method, device, electronic device, and storage medium of the present application, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to the present application.

[0161] This application is described with reference to the flowcharts and / or block diagrams of methods, hardware products, and computer program products according to the embodiments of this application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 or multiple blocks.

[0162] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device implements the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 or multiple blocks.

[0163] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 or multiple blocks.

[0164] It can be understood that any product that is controlled or configured to execute the processing method of the flowchart described in the method embodiment of a radon gas detection method of this application, such as the terminal and computer program product of the above flowchart, belongs to the category of related products described in this application.

[0165] Obviously, those skilled in the art can make various changes and modifications to a radon gas detection method, device, electronic device, and storage medium provided by this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalent technologies, this application also intends to include these changes and modifications.

Claims

1. A radon gas detection method, characterized in that, The method includes: obtaining the respective quantities of the first particle, the second particle, and the third particle generated after the atomic decay of the radon gas collected within a preset time period, where the first particle is the particle emitted after the decay of radon-222, the second particle is the particle emitted after the decay of polonium-218, and the third particle is the particle emitted after the decay of polonium-214; determining a first humidity value according to a first ratio between the quantity of a fourth particle and the quantity of the first particle, where the fourth particle is the second particle or the third particle, and the smaller the first ratio, the larger the first humidity value; determining a first calibration coefficient according to the first humidity value, where the smaller the first humidity value, the smaller the first calibration coefficient; determining a first concentration value of the radon gas according to the first calibration coefficient and the quantity of a fifth particle, where the fifth particle is at least one of the second particle and the third particle.

2. The method according to claim 1, wherein The determining the first calibration coefficient according to the first humidity value includes: obtaining a calibration coefficient-concentration curve corresponding to the first humidity value, where the calibration coefficient-concentration curve is used to represent the calibration coefficients corresponding to different concentrations; determining a second ratio between the concentration and the calibration coefficient corresponding to each coordinate point among multiple coordinate points on the calibration coefficient-concentration curve; determining a target coordinate point corresponding to the second ratio corresponding to the quantity of the fifth particle among the multiple second ratios; determining the calibration coefficient corresponding to the target coordinate point on the calibration coefficient-concentration curve as the first calibration coefficient.

3. The method according to claim 1, characterized in that, The determining the first calibration coefficient according to the first humidity value includes: obtaining a calibration coefficient-humidity curve and a calibration coefficient-concentration curve, where the calibration coefficient-humidity curve is used to represent the calibration coefficients corresponding to different humidities, and the calibration coefficient-concentration curve is used to represent the calibration coefficients corresponding to different concentrations; determining a second calibration coefficient corresponding to the first humidity value according to the calibration coefficient-humidity curve; determining a second concentration value according to the second calibration coefficient and the quantity of the fifth particle; determining the first calibration coefficient according to the second concentration value and the calibration coefficient-concentration curve, where the first calibration coefficient corresponds to the second concentration value.

4. The method according to any one of claims 1 to 3, characterized in that, The obtaining the respective quantities of the first particle, the second particle, and the third particle generated after the atomic decay of the radon gas collected within a preset time period includes: Step 4-1: Collecting multiple signal values of the pulse signal corresponding to a single particle generated after the atomic decay of the radon gas; Step 4-2: Determining the target particle corresponding to the multiple signal values, where the target particle is the first particle, the second particle, or the third particle; Step 4-3: Setting the target quantity corresponding to the target particle to N + 1, where N is the quantity of the target particle determined before collecting the multiple signal values of the pulse signal corresponding to the single particle; Repeating steps 4-1 to 4-3 for M times to obtain the quantities of the first particle, the second particle, and the third particle respectively, where M is determined according to the preset time period.

5. The method according to claim 4, wherein The determining the target particle corresponding to the multiple signal values includes: Perform pulse waveform fitting on the multiple signal values based on the acquisition order to obtain a target pulse waveform; Determine a target peak value in the target pulse waveform; When it is determined that the change trend of the target pulse waveform meets a preset change trend and the target peak value is within the first peak value range corresponding to the first particle, determine that the target particle corresponding to the multiple signal values is the first particle; When it is determined that the change trend of the target pulse waveform meets a preset change trend and the target peak value is within the second peak value range corresponding to the second particle, determine that the target particle corresponding to the multiple signal values is the second particle; When it is determined that the change trend of the target pulse waveform meets a preset change trend and the target peak value is within the third peak value range corresponding to the third particle, determine that the target particle corresponding to the multiple signal values is the third particle.

6. The method according to claim 5, wherein After determining the target peak value in the target pulse waveform, the method further includes: Determine a first slope corresponding to each signal value between the starting signal value and the target peak value in the target pulse waveform; Determine a second slope corresponding to each signal value between the target peak value and the ending signal value in the target pulse waveform; Determine a first mean value among the multiple first slopes and a second mean value among the multiple second slopes; When the first mean value is greater than a first preset threshold and the second mean value is less than a second preset threshold, determine that the change trend of the target pulse waveform meets the preset change trend.

7. The method according to any one of claims 1-3, characterized in that The determining the first concentration value of radon gas according to the first calibration coefficient and the number of the fourth particles includes: Obtain the air flow velocity; Adjust the first calibration coefficient according to the air flow velocity to obtain a third calibration coefficient, the third calibration coefficient is less than the first calibration coefficient, and the faster the air flow velocity, the greater the difference between the first calibration coefficient and the third calibration coefficient; Determine the first concentration value of radon gas according to the third calibration coefficient and the number of the fourth particles.

8. A radon gas detection device, characterized in that, The device includes: An acquisition unit, configured to acquire the quantities corresponding to the first particle, the second particle, and the third particle respectively generated after the atomic decay of the radon gas collected within a preset time period, where the first particle is the particle emitted after the decay of radon-222, the second particle is the particle emitted after the decay of polonium-218, and the third particle is the particle emitted after the decay of polonium-214; A processing unit, configured to determine a first humidity value according to a first ratio between the number of the fourth particles and the number of the first particles, where the fourth particle is the second particle or the third particle, and the smaller the first ratio, the greater the first humidity value; The processing unit is further configured to determine a first calibration coefficient according to the first humidity value, and the smaller the first humidity value, the smaller the first calibration coefficient; The processing unit is further configured to determine a first concentration value of radon gas according to the first calibration coefficient and the number of the fifth particles, where the fifth particle is at least one of the second particle and the third particle.

9. An electronic device, the device comprising a processor, a memory, and executable program code stored on the memory, characterized in that, The processor is configured to retrieve the executable program code stored on the memory to execute the method according to any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method according to any one of claims 1-7.

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