Radon concentration determination method, apparatus, electronic device, and storage medium

Abstract

The application discloses a radon concentration determination method and device, electronic equipment and storage medium. The method comprises the following steps: being applied to an intelligent radon sensor system, the intelligent radon sensor system comprising a radon sensor, a radioactive source module and a radioactive signal detection module; the radioactive source module is used for generating a reference radioactive signal; firstly, the radon concentration corresponding to a target area is acquired by the radon sensor to obtain a reference radon concentration value; then, a target radioactive signal in the target area is acquired by the radioactive signal detection module, wherein the target radioactive signal is a radioactive signal obtained after the reference radioactive signal is propagated in the target area and is affected by environmental parameters in the target area; then, a radon concentration adjustment coefficient is determined based on the parameter difference between the reference radioactive signal and the target radioactive signal; finally, the reference radon concentration value is adjusted based on the radon concentration adjustment coefficient to obtain a first target radon concentration value. The application improves the accuracy of radon concentration detection.

Description

Technical Field

[0001] This invention relates to the field of environmental monitoring technology, and in particular to a method, apparatus, electronic device, and storage medium for determining radon concentration. Background Technology

[0002] Radon, a radioactive gas, is widely present in various scenarios such as underground spaces, building interiors, and mining sites. Real-time and accurate detection of radon concentration in the environment is an important technical means to ensure the personal safety of workers and control the safety status of the environment.

[0003] Currently, most existing radon concentration detection methods rely on sensors to directly collect gas data to calculate the concentration. The detection process is easily affected by various factors such as ambient temperature, air pressure, air flow, and sensor aging or malfunction. Environmental factors can directly change the propagation state and transmission parameters of radioactive detection signals, resulting in large deviations in the raw concentration data collected by the sensors and low overall detection accuracy. Therefore, improving the accuracy of radon concentration detection is an urgent problem to be solved. Summary of the Invention

[0004] This application provides a method, apparatus, electronic device, and storage medium for determining radon concentration, which improves the accuracy of radon concentration detection.

[0005] In a first aspect, embodiments of this application provide a method for determining radon concentration, applied to an intelligent radon sensor system. The intelligent radon sensor system includes a radon sensor, a radiation source module, and a radiation signal detection module. The radiation source module is used to generate a reference radiation signal. The method includes: The radon concentration in the target area is obtained by using the radon sensor to obtain a reference radon concentration value. The target radiation signal within the target area is acquired by the radiation signal detection module; the target radiation signal is the radiation signal obtained after the reference radiation signal propagates in the target area and is affected by environmental parameters within the target area. The radon concentration adjustment coefficient is determined based on the parameter differences between the reference radiation signal and the target radiation signal; The reference radon concentration value is adjusted based on the radon concentration adjustment coefficient to obtain the first target radon concentration value; The step of determining the radon concentration adjustment coefficient based on the parameter difference between the reference radiation signal and the target radiation signal includes: Determine the number of first radioactive particles, the peak value of the first radioactive signal, and the average transmission rate of the first radioactive particles corresponding to the reference radioactive signal. Determine the number of second radioactive particles, the peak value of the second radioactive signal, and the average transmission rate of the second radioactive particles corresponding to the target radioactive signal; The difference in the number of radioactive particles is determined based on the first number of radioactive particles and the second number of radioactive particles; The difference in radiation signal peak values ​​is determined based on the first radiation signal peak value and the second radiation signal peak value. The difference in average transmission rate of radioactive particles is determined based on the first average transmission rate of radioactive particles and the second average transmission rate of radioactive particles. The radon concentration adjustment coefficient is determined based on the difference in the number of radioactive particles, the difference in the peak value of the radioactive signal, and the difference in the average transmission rate of the radioactive particles.

[0006] Secondly, this application provides a radon concentration determination device applied to an intelligent radon sensor system. The intelligent radon sensor system includes a radon sensor, a radiation source module, and a radiation signal detection module. The radiation source module is used to generate a reference radiation signal. The device includes an acquisition unit and a processing unit. The acquisition unit is used to acquire the radon concentration corresponding to the target area through the radon sensor to obtain a reference radon concentration value; The target radiation signal within the target area is acquired by the radiation signal detection module; the target radiation signal is the radiation signal obtained after the reference radiation signal propagates in the target area and is affected by environmental parameters within the target area. The processing unit is used to determine the radon concentration adjustment coefficient based on the parameter difference between the reference radiation signal and the target radiation signal; The reference radon concentration value is adjusted based on the radon concentration adjustment coefficient to obtain the first target radon concentration value; The step of determining the radon concentration adjustment coefficient based on the parameter difference between the reference radiation signal and the target radiation signal includes: Determine the number of first radioactive particles, the peak value of the first radioactive signal, and the average transmission rate of the first radioactive particles corresponding to the reference radioactive signal. Determine the number of second radioactive particles, the peak value of the second radioactive signal, and the average transmission rate of the second radioactive particles corresponding to the target radioactive signal; The difference in the number of radioactive particles is determined based on the first number of radioactive particles and the second number of radioactive particles; The difference in radiation signal peak values ​​is determined based on the first radiation signal peak value and the second radiation signal peak value. The difference in average transmission rate of radioactive particles is determined based on the first average transmission rate of radioactive particles and the second average transmission rate of radioactive particles. The radon concentration adjustment coefficient is determined based on the difference in the number of radioactive particles, the difference in the peak value of the radioactive signal, and the difference in the average transmission rate of the radioactive particles.

[0007] Thirdly, embodiments of the present invention provide an electronic device, including: a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor to cause the electronic device to perform the method as described in the first aspect.

[0008] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program that is executed by a processor to implement the method as described in the first aspect.

[0009] Fifthly, embodiments of the present invention provide a computer program product including a non-transitory computer-readable storage medium storing a computer program, such that a computer performs the method as described in the first aspect.

[0010] Implementing the embodiments of the present invention has the following beneficial effects: As can be seen, the radon concentration determination method described in this embodiment of the invention is applied to an intelligent radon sensor system. The intelligent radon sensor system includes a radon sensor, a radiation source module, and a radiation signal detection module. The radiation source module is used to generate a reference radiation signal. First, the radon concentration corresponding to the target area is obtained through the radon sensor to obtain a reference radon concentration value. Then, the target radiation signal within the target area is obtained through the radiation signal detection module. The target radiation signal is the radiation signal obtained after the reference radiation signal propagates in the target area and is affected by the environmental parameters within the target area. Next, a radon concentration adjustment coefficient is determined based on the parameter difference between the reference radiation signal and the target radiation signal. Finally, the reference radon concentration value is adjusted based on the radon concentration adjustment coefficient to obtain a first target radon concentration value, thereby improving the accuracy of radon concentration detection. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of this application or the background art, the accompanying drawings used in the embodiments of this application or the background art will be described below.

[0012] Figure 1 This is a schematic diagram of the structure of an intelligent radon gas sensor system provided in an embodiment of this application; Figure 2 This is a flowchart of a method for determining radon concentration provided in an embodiment of this application; Figure 3This is a flowchart of a method for determining a radon concentration adjustment coefficient provided in an embodiment of this application; Figure 4 This is a flowchart of a method for determining a second target radon concentration value provided in an embodiment of this application; Figure 5 This is a flowchart illustrating how to determine a target health level value according to an embodiment of this application; Figure 6 This is a flowchart of a method for determining the remaining lifespan of a sensor, provided in an embodiment of this application. Figure 7 This is a schematic diagram of a radon concentration determination device provided in an embodiment of this application; Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0013] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present application.

[0014] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0015] In this document, the term "implementation" means that a specific feature, structure, or characteristic described in connection with an implementation may be included in at least one implementation of this application. The appearance of this phrase in various places in the specification does not necessarily refer to the same implementation, nor is it a separate or alternative implementation mutually exclusive with other implementations. It will be explicitly and implicitly understood by those skilled in the art that the implementations described herein can be combined with other implementations.

[0016] Please see Figure 1 , Figure 1 This is a schematic diagram of the structure of an intelligent radon gas sensor system provided in an embodiment of this application. Figure 1The intelligent radon sensor system includes a radon sensor, a radiation source module, and a radiation signal detection module.

[0017] In this embodiment, the radon sensor is the core detection device within the intelligent radon sensor system, used to directly collect the radon content of the area to be measured. The radon sensor can be deployed in different types of environments to detect radon gas and its decay products in real time. It completes the raw radon concentration data acquisition through its built-in sensing structure, stably outputting the raw radon concentration value without environmental interference correction. The radon sensor can continuously perform radon concentration sampling for extended periods, forming the fundamental hardware structure for the intelligent radon sensor system to acquire initial concentration detection data. However, the raw concentration values ​​collected by the radon sensor are easily affected by external environmental conditions such as temperature, air pressure, and air composition within the area to be measured, leading to detection deviations.

[0018] The radon sensor can be any of the following: electrostatic collection radon detection sensor, scintillator radon detection sensor, or semiconductor pulse counting radon detection sensor. It can directly collect and sense radon gas in the surrounding space in real time. It relies on the internal nuclear radiation sensing structure to capture the ray signal released during the decay of radon gas. After internal circuit calculation and conversion, it outputs the real-time radon concentration value, thereby obtaining the reference radon concentration value. It can be deployed for a long time in various test scenarios such as indoors, underground, and around building walls to complete the continuous concentration collection work.

[0019] The radiation source module is an independently configured reference signal generation component within the intelligent radon sensor system. The inherent physical parameters of the emitted signal remain constant, and the module's operating conditions do not autonomously deviate. The radiation source module continuously emits a reference radiation signal with fixed inherent parameters and uniform basic signal attributes. Under a vacuum standard environment, the basic characteristic parameters of the reference radiation signal, such as the number of radioactive particles, peak value, and average transmission rate of radioactive particles, remain constant. When the reference radiation signal propagates into a space containing radon gas and experiencing temperature and pressure variations, the different radon concentrations, ambient temperature, and ambient pressure within the test area will cause varying degrees of obstruction and attenuation to the propagation path, energy loss, and particle propagation state of the reference radiation signal, thus causing regular changes in the characteristic parameters of the propagated radiation signal. The radiation source module provides a standard reference signal for the intelligent radon sensor system. By comparing the changed signal parameters after propagation with the fixed basic parameters of the reference radiation signal, the influence of radon concentration and various environmental conditions on signal propagation can be quantified.

[0020] It should be noted that, in this embodiment, the radioactive source module can be equipped with an alpha radioactive source. An alpha radioactive source can stably and continuously emit alpha particle rays to form a reference radioactive signal. The alpha radioactive source itself has stable physicochemical properties; the inherent number, energy intensity, and normal propagation speed of the emitted particles remain constant. The working state of the radioactive source module itself is not affected by various external factors. When the reference radioactive signal emitted by the alpha radioactive source propagates in free space, its characteristic parameters remain constant. When this reference radioactive signal enters a target area containing radon gas, the radon gas within the area will significantly block, scatter, and absorb the alpha particles. Simultaneously, changes in ambient temperature and atmospheric pressure will alter the density of the air medium, further affecting the overall propagation state of the alpha particle swarm. Ultimately, this results in regular changes in the number of particles, signal peak value, and average particle propagation speed of the target radioactive signal after propagation.

[0021] The radiation source module can be a sealed radiation emission device with a built-in solid-state alpha radiation source. The device is completely sealed and protected. A standard alpha radiation source is fixedly arranged inside, which can release alpha particle rays outward at a uniform speed and stably as a reference radiation signal. The overall structure is resistant to the influence of external temperature, humidity and air pressure. The total number of emitted particles, the peak energy and the average propagation speed of particles under normal conditions are all kept constant.

[0022] The radiation signal detection module is a dedicated functional component within the intelligent radon sensor system, responsible for receiving radiation signals and acquiring characteristic parameters. This module primarily receives the target radiation signal emitted by the radiation source module and propagating within the target area in real time. During the actual propagation process, various conditions within the target area, such as radon concentration, air composition, ambient temperature changes, and atmospheric pressure fluctuations, all exert varying degrees of resistance on the radiation signal. This results in regular changes in the target radiation signal compared to the original reference signal, including particle number loss, signal peak attenuation, and altered average particle propagation rate. The radiation signal detection module can accurately acquire multiple measured characteristic parameters corresponding to the target radiation signal, such as the actual number of radiation particles, the actual peak value of the radiation signal, and the actual average propagation rate of the radiation particles. The intelligent radon sensor system can then calculate the overall environmental impact based on the differences in these parameters, thereby determining an appropriate radon concentration adjustment coefficient for the current environment.

[0023] The radiation signal detection module can be any one of a zinc sulfide scintillation detector, a silicon photoelectric detector, or an ionization chamber-type radiation receiver. This type of device can accurately receive alpha radiation signals that have completed propagation in the area to be measured. It can identify and count the number of incident particles and collect the peak radiation energy in real time. At the same time, it can calculate the average transmission rate of the particle group by combining the propagation distance and the reception time, and fully collect various signal parameters that have changed after being affected by radon gas and the environment.

[0024] It should be explained that within the intelligent radon sensor system, the radon sensor, the radiation source module, and the radiation signal detection module work together in a coordinated manner. The radiation source module can be installed and deployed independently and continuously emit a reference radiation signal. The radiation signal detection module can be positioned opposite the radiation source module to receive the target radiation signal after it has propagated through the target area environment. The radon sensor can be independently deployed in the target area to directly collect the on-site radon concentration. The radon sensor, radiation source module, and radiation signal detection module are all electrically connected to the data processing center of the intelligent radon sensor system, enabling them to transmit the concentration data and radiation signal characteristic parameters they collect to the radon sensor system for centralized calculation and analysis.

[0025] Please see Figure 2 , Figure 2 This is a flowchart of a method for determining radon concentration according to an embodiment of this application. The method is applied to an intelligent radon sensor system, which includes a radon sensor, a radiation source module, and a radiation signal detection module. The radiation source module is used to generate a reference radiation signal. The method includes, but is not limited to, the following steps: S201: Obtain the radon concentration corresponding to the target area through the radon sensor to obtain a reference radon concentration value.

[0026] In this embodiment, the target area is the designated spatial range where accurate detection of radon concentration is required. This target area can be any actual place where radon gas accumulation and diffusion occur, such as indoor living spaces, underground working tunnels, the space surrounding building construction walls, and geological exploration and monitoring sites.

[0027] In this embodiment, after the radon gas sensor is deployed inside the target area where the concentration needs to be detected, it continuously senses the radon gas present in the air of the target area and the ray particles released during the decay of radon gas by relying on the nuclear radiation sensing detection structure of the radon gas sensor itself. The radon gas sensor collects radon-related detection data in the area in real time and obtains the radon concentration value corresponding to the current state of the target area. The concentration value obtained by direct detection without correction for external environmental interference is determined as the reference radon concentration value.

[0028] S202: Obtain the target radiation signal within the target area through the radiation signal detection module.

[0029] In this embodiment, the target radiation signal is the radiation signal obtained after the reference radiation signal propagates in the target area and is affected by environmental parameters within the target area.

[0030] The radiation signal detection module can monitor the radiation propagating in the target area in real time and continuously capture the reference radiation signal emitted by the radiation source module. As the reference radiation signal travels through the target area, it will fully interact with the radon gas and air medium present in the area. At the same time, it will also be affected by various environmental parameters such as temperature and air pressure, resulting in changes such as particle number attenuation, energy peak change, and overall propagation rate change. The radiation signal detection module collects the radiation signal after the above changes, thereby obtaining the target radiation signal.

[0031] The target radiation signal is the actual radiation signal formed after the reference radiation signal propagates through the target area. The number of radiation particles contained within it is lost to varying degrees compared to the initial reference state, and the peak signal energy will show corresponding attenuation changes. The average transmission rate of the group of radiation particles will also change regularly with the radon concentration, air density, and temperature and pressure conditions in the area. The magnitude of parameter changes is directly related to the strength of various environmental factors within the target area, and can intuitively reflect the comprehensive effect of the environment of the area under test on the propagation of radiation.

[0032] S203: Determine the radon concentration adjustment coefficient based on the parameter difference between the reference radiation signal and the target radiation signal.

[0033] In this embodiment, the differences in the number of radioactive particles, the peak value of the radioactive signal, and the average transmission rate of the radioactive particles corresponding to the reference radioactive signal, as well as the differences in the number of radioactive particles and the peak value of the radioactive signal corresponding to the target radioactive signal, can be calculated respectively. Then, based on each difference, the corresponding individual environmental impact parameters are determined. All individual environmental impact parameters are integrated to obtain the target environmental impact parameters. Finally, based on the target environmental impact parameters, the radon concentration adjustment coefficient adapted to the current detection scenario is calculated.

[0034] S204: Adjust the reference radon concentration value based on the radon concentration adjustment coefficient to obtain the first target radon concentration value.

[0035] In this embodiment, the collected reference radon concentration value and the calculated radon concentration adjustment coefficient can be calculated according to the preset data correction calculation logic. The adjustment coefficient is used to offset the detection errors caused by various environmental factors such as radon distribution, temperature, air pressure and air medium in the target area, and the initially collected reference radon concentration value is corrected to obtain a first target radon concentration value with higher detection accuracy.

[0036] Specifically, the first target radon concentration value can be calculated as follows: The first target radon concentration value = the reference radon concentration value × (1 + radon concentration adjustment coefficient); The reference radon concentration value can be adjusted based on the radon concentration adjustment coefficient in the above manner to obtain the first target radon concentration value.

[0037] It should be explained that the value of the radon concentration adjustment coefficient is determined based on the differences in various characteristic parameters between the reference and target radiation signals. When the environmental interference in the target area is weak and the changes in various parameters of the radiation signal are small, the radon concentration adjustment coefficient is set to a smaller value. Conversely, when the radon content in the target area is high and temperature and pressure fluctuations are large, leading to increased radiation signal loss and deformation, the radon concentration adjustment coefficient is set to a larger value accordingly. The radon concentration adjustment coefficient can be flexibly adapted to different positive and negative values ​​based on the actual on-site detection environment, accurately matching the detection deviation amplitude under different operating conditions and ensuring that the concentration correction results closely match the actual detection situation.

[0038] It can be seen that by first relying on the radon sensor to quickly obtain the original reference radon concentration value on site, then using the radiation source module to output a stable and reliable reference radiation signal, and using the radiation signal detection module to collect the target radiation signal affected by the actual environment, the radon concentration adjustment coefficient that reflects the degree of environmental interference can be accurately calculated by comparing the parameter differences between the two types of radiation signals. This allows for reasonable correction of the initial concentration value. This approach retains the advantages of direct on-site sampling, which is convenient and efficient, while effectively offsetting the detection deviations caused by various external factors such as radon distribution, temperature, air pressure, and air medium in the target area. This significantly reduces the adverse effects of environmental conditions on the radon concentration detection results and effectively improves the accuracy of radon concentration detection.

[0039] Please see Figure 3 , Figure 3 This application provides a flowchart for determining a radon concentration adjustment coefficient, including but not limited to the following steps: S301: Determine the number of first radioactive particles, the peak value of the first radioactive signal, and the average transmission rate of the first radioactive particles corresponding to the reference radioactive signal.

[0040] In this embodiment, the first number of radioactive particles is the total number of radioactive particles that the reference radioactive signal stably releases per unit time under standard interference-free conditions. The first number of radioactive particles is determined by the inherent properties of the radioactive source module itself, and the value remains constant over a long period of time, which can intuitively reflect the total number of particles released by the reference radioactive signal and the basic intensity of radiation.

[0041] The first radiation signal peak value is the maximum energy value of the reference radiation signal when it is in a standard propagation state. It represents the highest energy intensity that the reference radiation signal itself can reach, and the first radiation signal peak value will not change with the external environment.

[0042] The first average transmission rate of radioactive particles is the overall average velocity formed when all radioactive particles within the reference radioactive signal propagate at a constant speed in a standard medium environment. It can reflect the speed of normal propagation of radioactive particles under the reference state.

[0043] S302: Determine the number of second radioactive particles, the peak value of the second radioactive signal, and the average transmission rate of the second radioactive particles corresponding to the target radioactive signal.

[0044] In this embodiment, the second number of radioactive particles is the number of reference radioactive particles that originally corresponded to the first number of radioactive particles. After passing through the target area space and being blocked and absorbed by various environmental factors, the second number of radioactive particles is the number of particles that are actually captured and counted by the radioactive signal detection module. The second number of radioactive particles is formed by the loss and change of the first number of radioactive particles due to the effect of the on-site environment, which can intuitively reflect the change of the total number of particles compared with the reference value.

[0045] The second radiation signal peak is the actual maximum energy value of the reference radiation signal that originally had the first radiation signal peak, after it continuously loses energy during propagation in the target area. The second radiation signal peak is transformed from the first radiation signal peak due to the attenuation caused by the external environment, and can clearly reflect the degree of decrease in signal energy relative to the reference state.

[0046] The second average transmission rate of radioactive particles is the actual overall velocity of a group of radioactive particles that originally had the first average transmission rate of radioactive particles after entering different media environments in the target area and propagating. The second average transmission rate of radioactive particles is formed after the first average transmission rate of radioactive particles is changed by environmental conditions, and accurately reflects the actual difference between the particle propagation speed and the standard reference speed.

[0047] S303: Determine the difference in the number of radioactive particles based on the first number of radioactive particles and the second number of radioactive particles.

[0048] In this embodiment, the difference between the number of first radioactive particles representing the baseline standard state and the number of second radioactive particles obtained after propagation through the target area environment is calculated to obtain the difference in the number of radioactive particles. The difference in the number of radioactive particles can intuitively reflect the total amount of particle loss caused by the external environment during the propagation process, and clearly reflect the strength of the blocking and absorption effect of the target area environment on the formation of radioactive particles.

[0049] S304: Determine the difference in radiation signal peak values ​​based on the first radiation signal peak value and the second radiation signal peak value.

[0050] In this embodiment, the difference between the peak value of the first radiation signal under standard operating conditions and the peak value of the second radiation signal after energy attenuation due to environmental interference in the target area is calculated to obtain the radiation signal peak value difference. The radiation signal peak value difference can intuitively reflect the amount of energy loss of the reference radiation signal during propagation and accurately reflect the degree of weakening of radiation signal energy caused by various environmental factors on site.

[0051] S305: Determine the difference in average transmission rate of radioactive particles based on the first average transmission rate of radioactive particles and the second average transmission rate of radioactive particles.

[0052] In this embodiment, the difference between the first average transmission rate of radioactive particles under standard propagation conditions and the second average transmission rate of radioactive particles measured in the actual space of the target area is calculated to obtain the difference in average transmission rate of radioactive particles. The difference in average transmission rate of radioactive particles can intuitively reflect the impact of changes in the environmental medium on the particle motion state and accurately reflect the extent of change in the propagation speed of radioactive particles caused by the actual environment compared to the standard environment.

[0053] S306: Determine the radon concentration adjustment coefficient based on the difference in the number of radioactive particles, the difference in the peak value of the radioactive signal, and the difference in the average transmission rate of the radioactive particles.

[0054] In this embodiment, for example, determining a first environmental impact parameter corresponding to the difference in the number of radioactive particles, a second environmental impact parameter corresponding to the difference in the peak value of the radioactive signal, and a third environmental impact parameter corresponding to the difference in the average transmission rate of the radioactive particles can be achieved by: Specifically, this can be a preset first mapping relationship between the difference in the number of radioactive particles and the environmental impact parameter, based on which the first environmental impact parameter corresponding to the difference in the number of radioactive particles can be determined; it can be a preset second mapping relationship between the difference in the peak value of the radioactive signal and the environmental impact parameter, based on which the second environmental impact parameter corresponding to the difference in the peak value of the radioactive signal can be determined; and it can be a preset third mapping relationship between the difference in the average transmission rate of radioactive particles and the environmental impact parameter, based on which the third environmental impact parameter corresponding to the difference in the average transmission rate of the radioactive particles can be determined.

[0055] For example, the target environmental impact parameter is determined based on the first environmental impact parameter, the second environmental impact parameter, and the third environmental impact parameter. Specifically, the first weight corresponding to the first environmental impact parameter, the second weight corresponding to the second environmental impact parameter, and the third weight corresponding to the third environmental impact parameter can be determined first, wherein the sum of the first weight, the second weight, and the third weight is 1.

[0056] Specifically, the target environmental impact parameters can be calculated as follows: Target environmental impact parameter = First environmental impact parameter × First weight + Second environmental impact parameter × Second weight + Third environmental impact parameter × Third weight; The target environmental impact parameters can be determined using the method described above.

[0057] For example, the radon concentration adjustment coefficient is determined based on the target environmental impact parameter. Specifically, the target environmental impact parameter can be used to characterize the overall environmental interference strength corresponding to the target area. The radon concentration adjustment coefficient corresponding to the target environmental impact parameter can be determined according to the pre-established correspondence mapping relationship between the target environmental impact parameter and the radon concentration adjustment coefficient. When the value of the target environmental impact parameter is larger, it means that the comprehensive interference effect formed by factors such as radon gas, temperature, and air pressure in the target area is stronger, and the concentration error generated by detection is also larger. The value of the radon concentration adjustment coefficient obtained accordingly also increases. Conversely, the smaller the target environmental impact parameter is, the weaker the degree of environmental interference is, and the smaller the value of the radon concentration adjustment coefficient obtained is.

[0058] It can be seen that by first collecting three basic parameters—the number of radioactive particles, the peak value of the radioactive signal, and the average transmission rate of radioactive particles—corresponding to the reference and target radioactive signals, respectively, and then calculating the corresponding differences between each parameter, the different types of differences are converted into corresponding individual environmental impact parameters. By integrating all individual environmental impact parameters, the overall target environmental impact parameters are obtained, and the radon concentration adjustment coefficient is determined. By calculating from three different dimensions—particle number loss, signal energy attenuation, and particle propagation rate change—the interference effects of various environmental factors such as on-site radon distribution, temperature, air pressure, and air medium can be comprehensively taken into account. The environmental impact at different levels is accurately quantified, effectively avoiding the judgment bias of a single evaluation method. The resulting adjustment coefficient can truly match the interference state of the actual detection environment, effectively adapting to various complex detection environments and significantly improving the accuracy of the final radon concentration detection results.

[0059] The intelligent radon sensor system also includes a temperature sensor and a pressure sensor. Please refer to [link / reference]. Figure 4 , Figure 4 This application provides a flowchart for determining a second target radon concentration value, including but not limited to the following steps: S401: Determine the radon concentration difference between the reference radon concentration value and the first target radon concentration value to obtain the first radon concentration difference value.

[0060] In this embodiment, the reference radon concentration value without environmental correction is compared with the first target radon concentration value obtained after calibration by adjustment coefficient. The numerical deviation between the two is calculated to obtain the first radon concentration difference value. The first radon concentration difference value can initially reflect the numerical change before and after the initial concentration correction.

[0061] S402: Obtain the ambient temperature value of the target area through the temperature sensor, and obtain the ambient air pressure value of the target area through the air pressure sensor.

[0062] In this embodiment, the actual ambient temperature data of the current target area is collected in real time using temperature sensors that have been deployed and installed, and the actual ambient air pressure data of the target area is collected synchronously using air pressure sensors.

[0063] S403: Determine the temperature difference between the ambient temperature value and the preset ambient temperature, and the pressure difference between the ambient air pressure value and the preset ambient air pressure.

[0064] In this embodiment, the actual ambient temperature measured on site is compared with the pre-set standard ambient temperature to obtain the temperature difference. Then, the actual ambient air pressure is compared with the pre-set standard ambient air pressure to obtain the air pressure difference. This can clearly show the degree of deviation of the environmental parameters of the current working condition from the standard working condition.

[0065] S404: Determine the second radon concentration difference corresponding to the temperature difference and the third radon concentration difference corresponding to the pressure difference under the radon concentration conditions corresponding to the reference radon concentration value.

[0066] In this embodiment, the actual detection conditions corresponding to different radon concentrations are obtained in advance. Based on the actual detection conditions corresponding to different radon concentrations, the mapping relationship between temperature difference and radon concentration error, and between pressure difference and radon concentration error are determined respectively, so that each radon concentration condition is equipped with an independent mapping relationship. After determining the current actual reference radon concentration condition, the mapping relationship between temperature difference and radon concentration difference under that condition is retrieved. Then, the calculated temperature difference is substituted into the mapping relationship to obtain the second radon concentration difference corresponding to the temperature difference. At the same time, the obtained pressure difference is substituted into the mapping relationship between pressure difference and radon concentration difference under the same condition to determine the third radon concentration difference corresponding to the pressure difference.

[0067] S405: Determine the fourth radon concentration difference based on the second radon concentration difference and the third radon concentration difference.

[0068] In this embodiment, the second radon concentration difference and the third radon concentration difference can be added together, or a weighted combination can be made according to the actual influence ratio of temperature and air pressure on the detection results, taking into account the concentration detection deviations brought about by the two types of environmental factors, so as to determine the fourth radon concentration difference that can reflect the combined effect of temperature and air pressure.

[0069] S406: Determine the target health status value corresponding to the radon sensor based on the first radon concentration difference and the fourth radon concentration difference.

[0070] In this embodiment, the first radon concentration difference is a theoretical deviation of the overall environment calculated based on the law of interference of the radiation signal with the whole-domain environment. It can cover the influence of various hidden environmental factors on the detection results. The fourth radon concentration difference is a direct actual environmental deviation calculated based on the on-site measured temperature and pressure data. It can reflect the detection influence brought about by the explicit environmental conditions. Under the premise that the sensor performance is normal, the first radon concentration difference calculated by the comprehensive environmental interference and the fourth radon concentration difference calculated by the temperature and pressure changes will show a synchronous increase and decrease trend with the environmental changes. There will be no situation where one fluctuates greatly while the other remains stable. However, when the radon sensor has its own problems such as component aging and decreased detection sensitivity, the concentration data output by the sensor will show a systematic deviation, directly breaking the original correspondence between the two types of deviations. This causes the ratio of the two values ​​to deviate from the normal range. By comparing the matching status and deviation of the two concentration differences, the interference of external environmental factors can be eliminated, the data deviation caused by the abnormal performance of the sensor itself can be accurately identified, and then the target health level value corresponding to the radon sensor can be reasonably determined according to the degree of deviation.

[0071] It should be noted that, in this embodiment, the target health level value of the radon sensor can also be determined by comparing pulse energy spectrum features. Specifically, sufficient reference source pulse data can be collected first and a corresponding energy spectrum can be generated. A convolutional neural network can be used to extract the energy spectrum-specific feature vector, and the cosine similarity between the vector and the reference feature vector stored at the time of device delivery can be calculated. The target health level value of the radon sensor can then be determined based on the cosine similarity.

[0072] In this embodiment, the reference source pulse data refers to the stable and dose-fixed ray signal emitted by the radiation reference source of the radiation source module to the radon gas sensor. After receiving the ray, the sensor converts it into an electrical pulse signal. After continuously collecting one thousand sets of such pulse data, they are integrated and plotted to form a ray energy spectrum. The ray energy spectrum can intuitively reflect the sensor's recognition and response characteristics to ray energy. Acquisition in calibration mode can eliminate interference from ambient gas and ensure uniform and standardized detection conditions. Subsequently, a convolutional neural network is used to perform deep feature mining on the generated energy spectrum to extract a unique feature vector that can represent the sensor's current detection performance. The standard reference feature vector retained by the same standard reference source collected during the equipment's factory commissioning stage is retrieved, which is the preset reference feature vector. The two sets of feature vectors are substituted into the formula to calculate the cosine similarity between them. Then, the calculated cosine similarity value is converted into a health score according to a preset mapping relationship, thereby accurately determining the target health value of the radon gas sensor.

[0073] It can be seen that by leveraging convolutional neural networks to deeply mine the detailed features of the energy spectrum, subtle performance changes such as aging of sensor detection elements, sensitivity decay, and signal response shift can be accurately captured. By comparing the similarity with the original factory benchmark data, the actual wear and tear of the equipment can be objectively restored. This allows for the early prediction of potential device aging hazards and the accurate differentiation between normal performance fluctuations and substantial faults.

[0074] S407: When the target health level value is greater than the health level threshold, determine the radon concentration compensation coefficient corresponding to the target health level value.

[0075] In this embodiment, when the target health level value is greater than the health level threshold, it indicates that the radon sensor has a slight detection offset problem, which has not yet reached the level of serious abnormality requiring fault repair. There is no need to directly issue a fault detection-related alarm. Instead, it is only necessary to match a radon concentration compensation coefficient that is appropriate to the detection deviation reflected by the current target health level value. By using this compensation coefficient to further calibrate and correct the first target radon concentration value that has already undergone environmental correction, the detection error caused by the slight sensor abnormality can be offset, ensuring that the concentration detection result remains accurate.

[0076] In this embodiment, it can be a mapping relationship between a preset health level value and a radon concentration compensation coefficient. Based on this mapping relationship, the radon concentration compensation coefficient corresponding to the target health level value can be determined.

[0077] It should be explained that when the target health level value is less than or equal to the health level threshold, a first alarm message is generated based on the target health level value. The first alarm message is used to prompt the radon sensor to perform a fault detection operation. Specifically, when the obtained target health level value of the radon sensor is less than or equal to the preset health level threshold, it means that the overall operating performance of the radon sensor has failed to meet the normal operating standard, the detection accuracy has declined significantly, and there are various potential abnormal operating risks. The corresponding first alarm message can be generated based on the current actual target health level value. The first alarm message can promptly remind relevant personnel to carry out fault detection work on the radon sensor with abnormal status as soon as possible, and prevent the radon sensor from continuing to perform concentration detection operations with faults, resulting in a large number of erroneous detection data.

[0078] S408: Adjust the first target radon concentration value based on the radon concentration compensation coefficient to obtain the second target radon concentration value.

[0079] In this embodiment, the second target radon concentration value can be determined in the following manner: Second target radon concentration value = First target radon concentration value × (1 + radon concentration compensation coefficient); The first target radon concentration value can be adjusted based on the radon concentration compensation coefficient in the manner described above to obtain the second target radon concentration value.

[0080] As can be seen, when the obtained sensor target health value is higher than the set threshold, it indicates that the sensor has experienced significant performance deviation and decreased detection accuracy. At this time, the corresponding radon concentration compensation coefficient is matched according to the actual health status. The first target radon concentration detection value is corrected and calibrated using the radon concentration compensation coefficient, thereby obtaining an accurate second target radon concentration value. This can specifically compensate for the systematic detection error caused by the aging of the sensor components and the decrease in sensitivity, effectively offset the data deviation caused by the abnormal state of the equipment itself, and thus ensure the accuracy of the radon concentration detection results.

[0081] Please see Figure 5 , Figure 5 This application provides a flowchart for determining a target health level value, including but not limited to the following steps: S501: Determine the abnormal deviation value of radon concentration based on the first radon concentration difference and the fourth radon concentration difference.

[0082] In this embodiment, when the external environment fluctuates normally and the radon sensor is in good working order, the deviation between the first radon concentration difference calculated from the comprehensive environmental interference and the fourth radon concentration difference calculated from the temperature and pressure changes will be stable within a preset reasonable range. When the overall deviation obtained from the comparison of the two exceeds the predetermined reasonable range, it can be determined that the deviation is no longer a normal error caused by environmental factors. Then, based on the actual deviation from the range, calculations are performed to finally determine the abnormal deviation value of radon concentration caused by the radon sensor's own malfunction.

[0083] It needs to be explained that when the external environment is stable and there are no drastic changes, and the radon sensor is functioning normally, the difference between the first radon concentration difference calculated based on the degree of interference from the radiation signal and the fourth radon concentration difference calculated based on changes in on-site temperature and air pressure will remain stable within a preset reasonable range over a long period. This range is used to accommodate normal detection errors caused by all natural environmental changes, such as slight increases in indoor temperature or slight fluctuations in air pressure, which will cause slight changes in the two concentration differences. However, the final comparison result will still not fall outside the predetermined range. Once the result obtained after comparing the two concentration differences exceeds the preset reasonable range, the normal influence of external environmental factors can be ruled out. It can be determined that the excess deviation is not caused by environmental fluctuations, but by problems such as aging of internal components of the radon sensor, decreased detection sensitivity, or signal acquisition failure. By calculating the specific magnitude of the actual value exceeding the reasonable range, the abnormal deviation value of radon concentration caused solely by sensor malfunction can be accurately calculated.

[0084] S502: Determine the health status value corresponding to the abnormal deviation value of the radon concentration, and obtain a reference health status value.

[0085] In this embodiment, it can be a preset mapping relationship between abnormal radon concentration values ​​and health status values. Based on this mapping relationship, the health status value corresponding to the abnormal radon concentration value can be determined to obtain a reference health status value.

[0086] S503: Obtain the failure frequency of the radon gas sensor within a historical time period.

[0087] In this embodiment, a higher historical failure frequency of the radon sensor indicates a lower long-term operational stability of the equipment and more severe wear and tear on internal components. Conversely, a lower historical failure frequency indicates a stable and reliable long-term operation of the equipment without frequent abnormalities. Obtaining the failure frequency of the radon sensor over a historical period allows for an assessment of the long-term operational stability of the radon sensor.

[0088] S504: Determine the optimization factor corresponding to the fault frequency.

[0089] In this embodiment, it can be a preset mapping relationship between fault frequency and optimization factor, and the optimization factor corresponding to the fault frequency can be determined based on this mapping relationship.

[0090] S505: Adjust the reference health level value based on the optimization factor to obtain the target health level value.

[0091] In this embodiment, the target health level value can be calculated in the following manner: Target health score = Reference health score × (1 + Optimization factor); The reference health value can be adjusted based on the optimization factor in the manner described above to obtain the target health value.

[0092] As can be seen, by first combining the concentration difference values ​​of two different dimensions to calculate the abnormal deviation value, and then using the magnitude of the deviation to preliminarily derive the reference health level value, it is possible to quickly distinguish between normal environmental fluctuations and data deviations caused by the equipment itself, accurately determine the current real-time working status of the sensor, and then combine the operational hazards and performance losses accumulated during the long-term use of the sensor to avoid biased judgments based on a single detection result, so that the final determined target health level value is more in line with the actual situation of the sensor.

[0093] The intelligent radon gas sensor system also includes a health status value recording module; please refer to [link / reference]. Figure 6 , Figure 6This application provides a flowchart for determining the remaining lifespan of a sensor, including but not limited to the following steps: S601: The radon gas sensor obtains multiple target health values ​​corresponding to multiple health value recording times through the health value recording module.

[0094] In this embodiment, the health status value recording module is used to acquire the target health status value obtained by the radon gas sensor in real time according to the preset acquisition sequence, and to store the health status data corresponding to different recording times in an orderly manner.

[0095] Since the health status value recording module is used to store the target health status values ​​corresponding to the radon gas sensor at different recording times, multiple target health status values ​​corresponding to the radon gas sensor at multiple health status value recording times can be obtained through the health status value recording module.

[0096] S602: Based on the recording times of the multiple health status values ​​and the multiple target health status values, a linear fit is performed to obtain a linear curve of the change in the target health status values.

[0097] In this embodiment, the time of recording the health status value can be used as the time dimension coordinate, and the target health status value collected at the corresponding time can be used as the state dimension coordinate. Multiple sets of time series data can be linearly fitted to obtain a straight line of target health status value change that can characterize the overall trend of the sensor's health status.

[0098] S603: Determine the target slope corresponding to the straight line of change of the target health value.

[0099] In this embodiment, by selecting any two points on the line of change of the target health value, the target slope corresponding to the line of change of the target health value can be calculated.

[0100] S604: Determine the rate of decay of the health status value based on the target slope.

[0101] In this embodiment, the decay rate of the health status value corresponding to the radon gas sensor can be quantitatively determined based on the magnitude and trend of the target slope.

[0102] S605: Determine the remaining service life of the radon sensor based on the decay rate of the health status value and the usage time of the radon sensor.

[0103] In this embodiment, after determining the decay rate of the radon sensor, and combining the actual usage time accumulated from the time the radon sensor was put into use to the current time, and referring to the preset minimum health level usage threshold of the radon sensor, the remaining service life of the radon sensor that can maintain a qualified detection working state can be calculated according to the decay rate of the health level value.

[0104] It can be seen that by continuously storing the target health status value at different time periods through the health status value recording module, and then obtaining a straight line of health status change through linear fitting of time series data, the rate of decline of health status value can be accurately quantified based on the slope of the straight line, and the remaining service life can be estimated by combining the actual usage time of the radon sensor. This allows for a precise grasp of the overall law of radon sensor performance degradation over time, and the time node when the radon sensor performance approaches the lower limit of use can be known in advance.

[0105] It should be explained that, in this embodiment, when the remaining service life is less than the remaining service life threshold, a second alarm message is generated based on the remaining service life. The second alarm message is used to prompt the replacement of the radon sensor. Specifically, when the remaining service life of the radon sensor is less than the preset remaining service life threshold, it can be determined that the radon sensor is about to reach its normal service life and cannot maintain a precise and stable concentration detection state for a long time. At this time, a corresponding second alarm message can be generated based on the currently calculated remaining service life data. This second alarm message can clearly and intuitively remind relevant maintenance personnel to complete the overall replacement of the radon sensor that is close to its service life in a timely manner, effectively avoiding deviations in detection results caused by the radon sensor being used beyond its service life.

[0106] In summary, implementing the embodiments of the present invention has the following beneficial effects: As can be seen, the radon concentration determination method described in this embodiment of the invention is applied to an intelligent radon sensor system. The intelligent radon sensor system includes a radon sensor, a radiation source module, and a radiation signal detection module. The radiation source module is used to generate a reference radiation signal. First, the radon concentration corresponding to the target area is obtained through the radon sensor to obtain a reference radon concentration value. Then, the target radiation signal within the target area is obtained through the radiation signal detection module. The target radiation signal is the radiation signal obtained after the reference radiation signal propagates in the target area and is affected by the environmental parameters within the target area. Next, a radon concentration adjustment coefficient is determined based on the parameter difference between the reference radiation signal and the target radiation signal. Finally, the reference radon concentration value is adjusted based on the radon concentration adjustment coefficient to obtain a first target radon concentration value, thereby improving the accuracy of radon concentration detection.

[0107] Please see Figure 7 , Figure 7 This is a schematic diagram of the structure of a radon concentration determination device provided in an embodiment of this application. The radon concentration determination device 700 is applied to an intelligent radon sensor system. The intelligent radon sensor system includes a radon sensor, a radiation source module, and a radiation signal detection module. The radiation source module is used to generate a reference radiation signal. The radon concentration determination device 700 includes: an acquisition unit 701 and a processing unit 702. The acquisition unit 701 is used to acquire the radon concentration corresponding to the target area through the radon sensor and obtain a reference radon concentration value. The target radiation signal within the target area is acquired by the radiation signal detection module; the target radiation signal is the radiation signal obtained after the reference radiation signal propagates in the target area and is affected by environmental parameters within the target area. The processing unit 702 is used to determine the radon concentration adjustment coefficient based on the parameter difference between the reference radiation signal and the target radiation signal; The reference radon concentration value is adjusted based on the radon concentration adjustment coefficient to obtain the first target radon concentration value; The step of determining the radon concentration adjustment coefficient based on the parameter difference between the reference radiation signal and the target radiation signal includes: Determine the number of first radioactive particles, the peak value of the first radioactive signal, and the average transmission rate of the first radioactive particles corresponding to the reference radioactive signal. Determine the number of second radioactive particles, the peak value of the second radioactive signal, and the average transmission rate of the second radioactive particles corresponding to the target radioactive signal; The difference in the number of radioactive particles is determined based on the first number of radioactive particles and the second number of radioactive particles; The difference in radiation signal peak values ​​is determined based on the first radiation signal peak value and the second radiation signal peak value. The difference in average transmission rate of radioactive particles is determined based on the first average transmission rate of radioactive particles and the second average transmission rate of radioactive particles. The radon concentration adjustment coefficient is determined based on the difference in the number of radioactive particles, the difference in the peak value of the radioactive signal, and the difference in the average transmission rate of the radioactive particles.

[0108] In some possible implementations, the processing unit 702 is specifically configured to: determine the radon concentration adjustment coefficient based on the difference in the number of radioactive particles, the difference in the peak value of the radioactive signal, and the difference in the average transmission rate of the radioactive particles. Determine the first environmental impact parameter corresponding to the difference in the number of radioactive particles, the second environmental impact parameter corresponding to the difference in the peak value of the radioactive signal, and the third environmental impact parameter corresponding to the difference in the average transmission rate of the radioactive particles; The target environmental impact parameter is determined based on the first environmental impact parameter, the second environmental impact parameter, and the third environmental impact parameter; The radon concentration adjustment coefficient is determined based on the target environmental impact parameters.

[0109] In some possible implementations, the intelligent radon sensor system further includes a temperature sensor and a pressure sensor, and the processing unit 702 is specifically used for: The radon concentration difference between the reference radon concentration value and the first target radon concentration value is determined to obtain the first radon concentration difference value; The ambient temperature value of the target area is obtained through the temperature sensor, and the ambient air pressure value of the target area is obtained through the air pressure sensor. Determine the temperature difference between the ambient temperature value and the preset ambient temperature, and the pressure difference between the ambient air pressure value and the preset ambient air pressure; Determine the second radon concentration difference corresponding to the temperature difference and the third radon concentration difference corresponding to the pressure difference under the radon concentration conditions corresponding to the reference radon concentration value; The fourth radon concentration difference is determined based on the second radon concentration difference and the third radon concentration difference; The target health status value corresponding to the radon sensor is determined based on the first radon concentration difference and the fourth radon concentration difference; When the target health level value is greater than the health level threshold, a radon concentration compensation coefficient corresponding to the target health level value is determined; The first target radon concentration value is adjusted based on the radon concentration compensation coefficient to obtain the second target radon concentration value.

[0110] In some possible implementations, in determining the target health level value corresponding to the radon sensor based on the first radon concentration difference and the fourth radon concentration difference, the processing unit 702 is specifically configured to: The abnormal deviation value of radon concentration is determined based on the first radon concentration difference and the fourth radon concentration difference; Determine the health status value corresponding to the abnormal deviation value of the radon concentration to obtain a reference health status value; Obtain the failure frequency of the radon gas sensor within a historical time period; Determine the optimization factor corresponding to the fault frequency; The target health value is obtained by adjusting the reference health value based on the optimization factor.

[0111] In some possible implementations, the intelligent radon sensor system further includes a health level value recording module and a processing unit 702, which are specifically used for: The health status value recording module obtains multiple target health status values ​​corresponding to multiple health status value recording times of the radon gas sensor; Based on the multiple health status value recording times and the multiple target health status values, a linear fit is performed to obtain a linear curve of the target health status value change. Determine the target slope corresponding to the linear change in the target health value; The rate of decay of the health status value is determined based on the target slope; The remaining lifespan of the radon sensor is determined based on the decay rate of the health status value and the usage time of the radon sensor.

[0112] In some possible implementations, the intelligent radon gas sensor system further includes an alarm module and a processing unit 702, which is specifically used for: When the target health level value is less than or equal to the health level threshold, a first alarm message is generated based on the target health level value; the first alarm message is used to prompt a fault detection operation for the radon gas sensor. When the remaining service life is less than the remaining service life threshold, a second alarm message is generated based on the remaining service life; the second alarm message is used to prompt the replacement of the radon gas sensor.

[0113] Please see Figure 8 , Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device is applied to an intelligent radon gas sensor system, which includes a radon gas sensor, a radiation source module, and a radiation signal detection module. The radiation source module is used to generate a reference radiation signal. Figure 8 As shown, the electronic device 800 includes a transceiver 801, a processor 802, and a memory 803. These are connected via a bus 804. The memory 803 stores computer programs and data, and the transceiver 801 can transmit data stored in the memory 803 to the processor 802. The program includes instructions for performing the following steps: The radon concentration in the target area is obtained by using the radon sensor to obtain a reference radon concentration value. The target radiation signal within the target area is acquired by the radiation signal detection module; the target radiation signal is the radiation signal obtained after the reference radiation signal propagates in the target area and is affected by environmental parameters within the target area. The radon concentration adjustment coefficient is determined based on the parameter differences between the reference radiation signal and the target radiation signal; The reference radon concentration value is adjusted based on the radon concentration adjustment coefficient to obtain the first target radon concentration value; The step of determining the radon concentration adjustment coefficient based on the parameter difference between the reference radiation signal and the target radiation signal includes: Determine the number of first radioactive particles, the peak value of the first radioactive signal, and the average transmission rate of the first radioactive particles corresponding to the reference radioactive signal. Determine the number of second radioactive particles, the peak value of the second radioactive signal, and the average transmission rate of the second radioactive particles corresponding to the target radioactive signal; The difference in the number of radioactive particles is determined based on the first number of radioactive particles and the second number of radioactive particles; The difference in radiation signal peak values ​​is determined based on the first radiation signal peak value and the second radiation signal peak value. The difference in average transmission rate of radioactive particles is determined based on the first average transmission rate of radioactive particles and the second average transmission rate of radioactive particles. The radon concentration adjustment coefficient is determined based on the difference in the number of radioactive particles, the difference in the peak value of the radioactive signal, and the difference in the average transmission rate of the radioactive particles.

[0114] In some possible implementations, the above procedure includes instructions for performing the following steps in determining the radon concentration adjustment coefficient based on the difference in the number of radioactive particles, the difference in the peak value of the radioactive signal, and the difference in the average transmission rate of the radioactive particles: Determine the first environmental impact parameter corresponding to the difference in the number of radioactive particles, the second environmental impact parameter corresponding to the difference in the peak value of the radioactive signal, and the third environmental impact parameter corresponding to the difference in the average transmission rate of the radioactive particles; The target environmental impact parameter is determined based on the first environmental impact parameter, the second environmental impact parameter, and the third environmental impact parameter; The radon concentration adjustment coefficient is determined based on the target environmental impact parameters.

[0115] In some possible implementations, the intelligent radon sensor system further includes a temperature sensor and a pressure sensor, and the above-described program includes instructions for performing the following steps: The radon concentration difference between the reference radon concentration value and the first target radon concentration value is determined to obtain the first radon concentration difference value; The ambient temperature value of the target area is obtained through the temperature sensor, and the ambient air pressure value of the target area is obtained through the air pressure sensor. Determine the temperature difference between the ambient temperature value and the preset ambient temperature, and the pressure difference between the ambient air pressure value and the preset ambient air pressure; Determine the second radon concentration difference corresponding to the temperature difference and the third radon concentration difference corresponding to the pressure difference under the radon concentration conditions corresponding to the reference radon concentration value; The fourth radon concentration difference is determined based on the second radon concentration difference and the third radon concentration difference; The target health status value corresponding to the radon sensor is determined based on the first radon concentration difference and the fourth radon concentration difference; When the target health level value is greater than the health level threshold, a radon concentration compensation coefficient corresponding to the target health level value is determined; The first target radon concentration value is adjusted based on the radon concentration compensation coefficient to obtain the second target radon concentration value.

[0116] In some possible implementations, in determining the target health status value corresponding to the radon sensor based on the first radon concentration difference and the fourth radon concentration difference, the above procedure includes instructions for performing the following steps: The abnormal deviation value of radon concentration is determined based on the first radon concentration difference and the fourth radon concentration difference; Determine the health status value corresponding to the abnormal deviation value of the radon concentration to obtain a reference health status value; Obtain the failure frequency of the radon gas sensor within a historical time period; Determine the optimization factor corresponding to the fault frequency; The target health value is obtained by adjusting the reference health value based on the optimization factor.

[0117] In some possible implementations, the intelligent radon sensor system further includes a health status value recording module, and the aforementioned program includes instructions for performing the following steps: The health status value recording module obtains multiple target health status values ​​corresponding to multiple health status value recording times of the radon gas sensor; Based on the multiple health status value recording times and the multiple target health status values, a linear fit is performed to obtain a linear curve of the target health status value change. Determine the target slope corresponding to the linear change in the target health value; The rate of decay of the health status value is determined based on the target slope; The remaining lifespan of the radon sensor is determined based on the decay rate of the health status value and the usage time of the radon sensor.

[0118] In some possible implementations, the intelligent radon sensor system further includes an alarm module, and the aforementioned program includes instructions for performing the following steps: When the target health level value is less than or equal to the health level threshold, a first alarm message is generated based on the target health level value; the first alarm message is used to prompt a fault detection operation for the radon gas sensor. When the remaining service life is less than the remaining service life threshold, a second alarm message is generated based on the remaining service life; the second alarm message is used to prompt the replacement of the radon gas sensor.

[0119] It should be understood that the electronic devices mentioned in this application may include smartphones (such as Android phones, iOS phones, Windows Phones, etc.), tablets, PDAs, laptops, mobile internet devices (MIDs) or wearable devices, servers, edge computing nodes, etc. The above-mentioned electronic devices are merely examples and not exhaustive, and include, but are not limited to, the electronic devices described above.

[0120] This application also provides a computer-readable storage medium storing a computer program that is executed by a processor to implement some or all of the steps of any of the methods described in the above method embodiments.

[0121] This application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods described in the above method embodiments.

[0122] It should be noted that, for the sake of simplicity, the aforementioned methods are described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are optional, and the actions and modules involved are not necessarily essential to this application.

[0123] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0124] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical or other forms.

[0125] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0126] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software program module.

[0127] If the integrated unit is implemented as a software program module and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0128] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage device, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0129] The embodiments of this application have been described in detail above. Specific examples have been used in this document to illustrate the principles and implementation methods of this application. The description of the embodiments above is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for determining radon gas concentration, characterized in that, An application is made in an intelligent radon sensor system, the intelligent radon sensor system including a radon sensor, a radiation source module, and a radiation signal detection module, the radiation source module being used to generate a reference radiation signal, the method including: The radon concentration in the target area is obtained by using the radon sensor to obtain a reference radon concentration value. The target radiation signal within the target area is acquired by the radiation signal detection module; the target radiation signal is the radiation signal obtained after the reference radiation signal propagates in the target area and is affected by environmental parameters within the target area. The radon concentration adjustment coefficient is determined based on the parameter differences between the reference radiation signal and the target radiation signal; The reference radon concentration value is adjusted based on the radon concentration adjustment coefficient to obtain the first target radon concentration value; The step of determining the radon concentration adjustment coefficient based on the parameter difference between the reference radiation signal and the target radiation signal includes: Determine the number of first radioactive particles, the peak value of the first radioactive signal, and the average transmission rate of the first radioactive particles corresponding to the reference radioactive signal. Determine the number of second radioactive particles, the peak value of the second radioactive signal, and the average transmission rate of the second radioactive particles corresponding to the target radioactive signal; The difference in the number of radioactive particles is determined based on the first number of radioactive particles and the second number of radioactive particles; The difference in radiation signal peak values ​​is determined based on the first radiation signal peak value and the second radiation signal peak value. The difference in average transmission rate of radioactive particles is determined based on the first average transmission rate of radioactive particles and the second average transmission rate of radioactive particles. The radon concentration adjustment coefficient is determined based on the difference in the number of radioactive particles, the difference in the peak value of the radioactive signal, and the difference in the average transmission rate of the radioactive particles. The step of determining the radon concentration adjustment coefficient based on the difference in the number of radioactive particles, the difference in the peak value of the radioactive signal, and the difference in the average transmission rate of the radioactive particles includes: Determine the first environmental impact parameter corresponding to the difference in the number of radioactive particles, the second environmental impact parameter corresponding to the difference in the peak value of the radioactive signal, and the third environmental impact parameter corresponding to the difference in the average transmission rate of the radioactive particles; The target environmental impact parameter is determined based on the first environmental impact parameter, the second environmental impact parameter, and the third environmental impact parameter; The radon concentration adjustment coefficient is determined based on the target environmental impact parameters.

2. The method as described in claim 1, characterized in that, The intelligent radon gas sensor system further includes a temperature sensor and a pressure sensor, and the method further includes: The radon concentration difference between the reference radon concentration value and the first target radon concentration value is determined to obtain the first radon concentration difference value; The ambient temperature value of the target area is obtained through the temperature sensor, and the ambient air pressure value of the target area is obtained through the air pressure sensor. Determine the temperature difference between the ambient temperature value and the preset ambient temperature, and the pressure difference between the ambient air pressure value and the preset ambient air pressure; Determine the second radon concentration difference corresponding to the temperature difference and the third radon concentration difference corresponding to the pressure difference under the radon concentration conditions corresponding to the reference radon concentration value; The fourth radon concentration difference is determined based on the second radon concentration difference and the third radon concentration difference; The target health status value corresponding to the radon sensor is determined based on the first radon concentration difference and the fourth radon concentration difference; When the target health level value is greater than the health level threshold, a radon concentration compensation coefficient corresponding to the target health level value is determined; The first target radon concentration value is adjusted based on the radon concentration compensation coefficient to obtain the second target radon concentration value.

3. The method as described in claim 2, characterized in that, Determining the target health status value corresponding to the radon sensor based on the first radon concentration difference and the fourth radon concentration difference includes: The abnormal deviation value of radon concentration is determined based on the first radon concentration difference and the fourth radon concentration difference; Determine the health status value corresponding to the abnormal deviation value of the radon concentration to obtain a reference health status value; Obtain the failure frequency of the radon gas sensor within a historical time period; Determine the optimization factor corresponding to the fault frequency; The target health value is obtained by adjusting the reference health value based on the optimization factor.

4. The method as described in claim 3, characterized in that, The intelligent radon gas sensor system also includes a health status value recording module, and the method further includes: The health status value recording module obtains multiple target health status values ​​corresponding to multiple health status value recording times of the radon gas sensor; Based on the multiple health status value recording times and the multiple target health status values, a linear fit is performed to obtain a linear curve of the target health status value change. Determine the target slope corresponding to the linear change in the target health value; The rate of decay of the health status value is determined based on the target slope; The remaining lifespan of the radon sensor is determined based on the decay rate of the health status value and the usage time of the radon sensor.

5. The method as described in claim 4, characterized in that, The intelligent radon gas sensor system also includes an alarm module, and the method further includes: When the target health level value is less than or equal to the health level threshold, a first alarm message is generated based on the target health level value; the first alarm message is used to prompt a fault detection operation for the radon gas sensor. When the remaining service life is less than the remaining service life threshold, a second alarm message is generated based on the remaining service life; the second alarm message is used to prompt the replacement of the radon gas sensor.

6. A radon concentration determination device, characterized in that, An intelligent radon sensor system is used, comprising a radon sensor, a radiation source module, and a radiation signal detection module. The radiation source module is used to generate a reference radiation signal. The device includes an acquisition unit and a processing unit. The acquisition unit is used to acquire the radon concentration corresponding to the target area through the radon sensor to obtain a reference radon concentration value; The target radiation signal within the target area is acquired by the radiation signal detection module; the target radiation signal is the radiation signal obtained after the reference radiation signal propagates in the target area and is affected by environmental parameters within the target area. The processing unit is used to determine the radon concentration adjustment coefficient based on the parameter difference between the reference radiation signal and the target radiation signal; The reference radon concentration value is adjusted based on the radon concentration adjustment coefficient to obtain the first target radon concentration value; The step of determining the radon concentration adjustment coefficient based on the parameter difference between the reference radiation signal and the target radiation signal includes: Determine the number of first radioactive particles, the peak value of the first radioactive signal, and the average transmission rate of the first radioactive particles corresponding to the reference radioactive signal. Determine the number of second radioactive particles, the peak value of the second radioactive signal, and the average transmission rate of the second radioactive particles corresponding to the target radioactive signal; The difference in the number of radioactive particles is determined based on the first number of radioactive particles and the second number of radioactive particles; The difference in radiation signal peak values ​​is determined based on the first radiation signal peak value and the second radiation signal peak value. The difference in average transmission rate of radioactive particles is determined based on the first average transmission rate of radioactive particles and the second average transmission rate of radioactive particles. The radon concentration adjustment coefficient is determined based on the difference in the number of radioactive particles, the difference in the peak value of the radioactive signal, and the difference in the average transmission rate of the radioactive particles. The step of determining the radon concentration adjustment coefficient based on the difference in the number of radioactive particles, the difference in the peak value of the radioactive signal, and the difference in the average transmission rate of the radioactive particles includes: Determine the first environmental impact parameter corresponding to the difference in the number of radioactive particles, the second environmental impact parameter corresponding to the difference in the peak value of the radioactive signal, and the third environmental impact parameter corresponding to the difference in the average transmission rate of the radioactive particles; The target environmental impact parameter is determined based on the first environmental impact parameter, the second environmental impact parameter, and the third environmental impact parameter; The radon concentration adjustment coefficient is determined based on the target environmental impact parameters.

7. An electronic device, characterized in that, The method includes a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the one or more programs include instructions for performing the steps of the method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that is executed by a processor to implement the method as described in any one of claims 1-5.

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