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

Abstract

The invention discloses a radon gas detection method and device, electronic equipment and a storage medium, the method is applied to a processing module of radon gas detection equipment, the radon gas detection equipment further comprises a detection module, the detection module is used for detecting radon gas and generating a detection signal when the radon gas is detected, and the method comprises the following steps: collecting the detection signal according to a first frequency, multiple pieces of first detection data are obtained; acquiring first peak data in the plurality of pieces of first detection data, and determining whether invalid feature data exists in the plurality of pieces of first detection data according to the first peak data; if the invalid feature data does not exist in the multiple pieces of first detection data, the multiple pieces of first detection data are recorded as a first effective data set, and the first effective data set is used for calculating the radon gas concentration. By implementing the method provided by the invention, the problem that radon gas detection equipment is easily influenced by factors such as touch or environmental vibration and the like and misinformation is caused is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of radon gas detection and processing, and in particular to a radon gas detection method, device, electronic equipment and storage medium. Background Art

[0002] Portable radon gas detection equipment is usually used in indoor or semi-indoor scenes such as houses, warehouses, and courtyards. This type of radon gas detection equipment uses the electrostatic collection method to detect radon gas. The principle of the electrostatic collection method is: there is a radon concentration difference inside and outside the high-pressure collection chamber, and the radon gas in the test environment enters the diffusion chamber in the form of diffusion and establishes a new radioactive balance. The radon diffused into the high-pressure collection chamber decays to produce radon daughters, which are collected on the central detector under the action of electricity, and then the alpha particles produced by its decay will cause the detector to generate a corresponding pulse electrical signal. The signal is transmitted to the amplifier circuit through the signal line to amplify the pulse signal, and then it is collected by a microprocessor. The microprocessor determines whether the pulse comes from the alpha particles emitted by radon and its daughters based on the pulse peak and waveform data, and finally infers the radon concentration in the environment by pulse counting.

[0003] In the product architecture of the prior art, since the pulse electrical signal before amplification is a small current at the pA level, when the device is vibrated or touched, it is likely to generate an electrical signal of the same level. The microprocessor will therefore collect erroneous data, which will cause the radon gas detection equipment to be easily affected by touch or environmental vibration and cause false alarms. Summary of the invention

[0004] In response to the above problems, the embodiments of the present application provide a radon gas detection method, device, electronic device and storage medium. The solution of the present application is conducive to solving the problem that radon gas detection equipment is easily affected by factors such as touch or environmental vibration and causes false alarms.

[0005] In a first aspect, an embodiment of the present application provides a radon gas detection method, which is applied to a processing module of a radon gas detection device. The radon gas detection device also includes a detection module, which is used to detect radon gas and generate a detection signal when radon gas is detected. The method includes: collecting the detection signal at a first frequency to obtain a plurality of first detection data; obtaining first peak data from the plurality of first detection data, and determining whether invalid characteristic data exists in the plurality of first detection data based on the first peak data; if invalid characteristic data does not exist in the plurality of first detection data, recording the plurality of first detection data as a first valid data group, and the first valid data group is used to calculate the radon gas concentration.

[0006] It can be seen that in the embodiment of the present application, the processing module is used to determine whether there are invalid characteristic data in multiple detection data, and the radon gas concentration is determined only based on the valid data group without invalid characteristic data, thereby eliminating false touch signals caused by touch or environmental vibration, and solving the problem that radon gas detection equipment is easily affected by factors such as touch or environmental vibration and causes false alarms.

[0007] In combination with the first aspect, in a possible embodiment, determining whether invalid characteristic data exists in multiple first detection data is based on the first peak data, including: if the first peak data is not within the valid numerical range, determining that the first peak data is invalid characteristic data; if the first peak data is within the valid numerical range, determining whether the collection time of the first peak data is before the first moment; if the collection time of the first peak data is not before the first moment, determining that the first peak data is invalid characteristic data.

[0008] It can be seen that in the embodiment of the present application, according to whether the peak data in the multiple detection data is within the valid numerical range, and secondly, the collection time of the peak data, it is possible to determine whether there is invalid characteristic data in the multiple detection data, and then identify the invalid data including the invalid characteristic data, thereby improving the detection accuracy of the radon detection device. At the same time, the numerical range of the first peak data and the collection time are determined in steps. When the first peak data is not within the valid numerical range, it can be directly determined that the first peak data is invalid characteristic data without executing subsequent steps, thereby improving the processing efficiency of the radon detection device.

[0009] In combination with the first aspect, in a possible embodiment, if the collection time of the first peak data is before the first moment, the method also includes: if the first target data is less than or equal to the second target data, then determining that the first target data is invalid feature data, wherein the collection time of the first target data is earlier than the collection time of the second target data, and the collection time of the first target data and the collection time of the second target data are both later than the collection time of the first peak data; if the first target data is greater than the first detection data whose collection time is after the first target data, then determining whether the first target data before the second moment is greater than a preset value, and the second moment is after the first moment; if the collection time of the first target data is before the second moment and the first target data is less than or equal to the preset value, then determining the first target data as invalid feature data.

[0010] It can be seen that in the embodiment of the present application, in the process of determining whether there is invalid feature number data in multiple detection data, whether the detection data after the peak data is invalid feature data is also considered, which further improves the detection accuracy of the radon gas detection equipment.

[0011] In combination with the first aspect, in a possible embodiment, before collecting the detection signal at a first frequency to obtain multiple first detection data, the method also includes: collecting the detection signal at a second frequency to obtain second detection data, and determining that the second detection data is greater than a preset value and the second frequency is less than the first frequency.

[0012] It can be seen that in the embodiment of the present application, the processing module collects detection signals at a relatively low frequency, and obtains detection data for determining the radon concentration only when the detection module may detect the presence of radon gas in the environment. This allows the processing module to be in a dormant state when there is no radon gas in the environment, thereby reducing the energy consumption of the radon detection equipment.

[0013] In combination with the first aspect, in a possible embodiment, after recording multiple first detection data as a first valid data group, the method also includes: collecting detection signals at a second frequency to obtain third detection data; if the third detection data is greater than a preset value, collecting detection signals at the first frequency to obtain multiple fourth detection data; obtaining second peak data from the multiple fourth detection data, and determining whether there is invalid feature data in the multiple fourth detection data based on the second peak data; if there is no invalid feature data in the multiple fourth detection data, recording the multiple fourth detection data as a second valid data group; if the generation time difference between the first valid data group and the second valid data group is less than the preset time difference, modifying the first valid data group to a first invalid data group.

[0014] It can be seen that in the embodiment of the present application, by judging whether the generation time difference of two adjacent valid data groups is less than the preset time difference, it is possible to further judge that there is no invalid data group with invalid characteristic data, thereby further improving the detection accuracy of the radon gas detection equipment.

[0015] In combination with the first aspect, in a possible embodiment, after collecting the detection signal at the first frequency, the method also includes: if the third target data is less than or equal to a preset value, stop collecting the detection signal at the first frequency, the third target data is the first detection data among multiple first detection data whose collection time is before the second time; and determine the multiple first detection data as a first invalid data group.

[0016] It can be seen that in the embodiment of the present application, by judging whether the detection data collected is less than or equal to the preset value during the process of collecting the detection signal, the processing module can stop collecting the detection signal in advance when the detection data is less than or equal to the preset value, and there is no need to execute the subsequent step of determining whether there is invalid characteristic data in the detection data, thereby improving the detection efficiency of the radon gas detection equipment.

[0017] In combination with the first aspect, in a possible embodiment, before obtaining first peak data among a plurality of first monitoring data, the method further includes: determining that the number of the plurality of first detection data is a preset number.

[0018] In a second aspect, an embodiment of the present application provides a radon gas detection device, which is used to perform a radon gas detection method. The radon gas detection device belongs to a radon gas detection device. The radon gas detection device also includes a detection module, which is used to detect radon gas and generate a detection signal when radon gas is detected. The processing module includes: A collection unit, used for collecting detection signals at a first frequency to obtain a plurality of first detection data; a determination unit, configured to obtain first peak data from the plurality of first detection data, and determine whether invalid feature data exists in the plurality of first detection data according to the first peak data; The recording unit is used for recording the plurality of first detection data as a first valid data group if there is no invalid characteristic data in the plurality of first detection data, and the first valid data group is used for calculating the radon gas concentration.

[0019] In a third aspect, an embodiment of the present application provides an electronic device comprising 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 one or more instructions are suitable for being loaded by the processor and executing part or all of the methods of the first aspect and / or the second aspect.

[0020] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium storing a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the method of the first aspect and / or the second aspect.

[0021] In a fifth aspect, the present application provides a computer program product. When a computer reads and executes the computer program product, the computer executes part or all of the method of the first aspect and / or the second aspect.

[0022] It can be understood that the beneficial effects of the embodiments of the second to fifth aspects can refer to the beneficial effects of the method of the first aspect, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0024] Figure 1 A schematic diagram of a radon gas detection method provided in an embodiment of the present application; Figure 2 A schematic diagram of an application scenario of a radon gas detection method provided in an embodiment of the present application; Figure 3 A schematic diagram of the connection between a detection module and a processing module provided in an embodiment of the present application; Figure 4 A schematic diagram of an image of a plurality of first detection data provided in an embodiment of the present application; Figure 5A A schematic diagram of the first type of invalid feature data provided in an embodiment of the present application; Figure 5B A schematic diagram of the second type of invalid feature data provided in an embodiment of the present application; Figure 5C A schematic diagram of the third type of invalid feature data provided in an embodiment of the present application; Figure 5D A schematic diagram of the fourth type of invalid feature data provided in an embodiment of the present application; Figure 6 A schematic diagram of a flow chart of another radon gas detection method provided in an embodiment of the present application; Figure 7 A schematic flow chart of another radon gas detection method provided in an embodiment of the present application; Figure 8 A schematic diagram of the structure of a radon gas detection device provided in an embodiment of the present application; Fig. 9 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0025] Explanation of the accompanying drawings: application scenario 200; radon gas detection equipment 201; user terminal 202; processing module 2011; detection module 2012; electrostatic collection chamber 301; alpha particle detector 302; preamplifier circuit 303; linear pulse amplifier circuit 304; comparator 305; analog-to-digital conversion interface 306; radon gas detection device 800; acquisition unit 801; determination unit 802; recording unit 803; electronic device 900; memory 901; processor 902; communication interface 903; bus 904. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0027] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0028] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0029] The embodiments of the present application are described below in conjunction with the accompanying drawings.

[0030] Example 1: Please see Figure 1 , Figure 1 A schematic diagram of a radon gas detection method provided in an embodiment of the present application is shown in FIG. Figure 1 As shown, steps S101-S103 are included: S101: A processing module collects detection signals at a first frequency to obtain a plurality of first detection data.

[0031] Specifically, see Figure 2 , Figure 2 A schematic diagram of an application scenario of a radon gas detection method provided in an embodiment of the present application is provided. Figure 1 The radon gas detection method shown can be implemented based on the application scenario 200, which includes a radon gas detection device 201 and a user terminal 202. The radon gas detection device 201 is connected to the user terminal 202.

[0032] The radon gas detection device 201 is deployed in indoor or semi-open areas such as houses, courtyards, warehouses, etc., and detects the radon gas concentration in the environment to be tested in the deployed area.

[0033] The radon detection device 201 also includes a processing module 2011 and a detection module 2012. The detection module 2012 is used to detect the radon concentration of the environment to be detected by the radon detection device 201, and generate a detection signal when radon is detected. Specifically, the detection signal here is a pulse electrical signal generated by the alpha particles generated by radon during the decay process and detected by the detection module 2012.

[0034] The processing module 2011 is specifically a central processing unit or a microcontroller, which is used to determine the radon concentration of the deployed area of ​​the radon detection device 201 according to the detection signal generated by the detection module 2012. When radon is detected in the deployed area of ​​the radon detection device 201, or the radon concentration is too high, an alarm is issued, and the alarm here includes sending an alarm message to the user terminal 202.

[0035] For example, see Figure 3 , Figure 3 A connection diagram of a detection module and a processing module provided in an embodiment of the present application, wherein the detection module 2012 includes an electrostatic collection chamber 301, an α particle detector 302, a preamplifier circuit 303, a linear pulse amplification circuit 304, and a comparator 305; the processing module 2011 includes an analog-to-digital conversion interface 306.

[0036] The electrostatic collection chamber 301 is used to collect the gas in the measured environment. When the gas in the measured environment includes radon, the radon gas (the gas in the measured environment including radon) enters the electrostatic collection chamber 301, and the radon and radon progeny in the radon gas decay to produce α particles, which are collected on the α particle detector 302 under the action of electricity, so that the α particle detector 302 generates a corresponding electrical signal. After the electrical signal is shaped and amplified by the linear pulse amplifier circuit 304 and the comparator 305, it is input into the processing module 2011 through the analog-to-digital conversion interface 306.

[0037] The detection signal here is a pulse electric signal generated by the detection module 2012 based on alpha particles generated during the decay process of radon gas in the environment. The processing module 2011 is connected to the detection module 2012 via an analog to digital conversion interface 306 (Analog to Digital Converte, ADC). The first frequency here is the frequency of collecting detection signal data.

[0038] Exemplarily, if the first frequency here is 200 kHz, the processing module collects the detection signal at an interval of 5 μs through the continuous acquisition mode of the ADC, and collects 100 times to obtain 100 first detection data, that is, a plurality of first detection data.

[0039] S102: The processing module obtains first peak data from a plurality of first detection data, and determines whether invalid feature data exists in the plurality of first detection data according to the first peak data.

[0040] Specifically, as mentioned above, the detection module will generate a detection signal when radon gas is detected. However, when the radon detection device is touched or the environment in which the radon detection device is located vibrates, the detection module will be mistakenly triggered and generate a detection signal. In order to avoid the detection signal generated by the false triggering of the detection module affecting the final detection result, the processing module determines whether there is invalid characteristic data in the multiple first detection data based on the first peak data. Invalid characteristic data is the data in the detection signal generated by the false triggering of the detection module. The first peak data here is the data corresponding to the first upper inflection point in the curve formed by the multiple first detection data.

[0041] Figure 4 This is a schematic diagram of an image of a plurality of first detection data provided in an embodiment of the present application. It can be seen that Figure 4 In the parabola-like curve shown, the collection order of the first peak data is the 17th data collected, and its value is 561.

[0042] According to the value of the first peak data and the order of collecting the first peak data, it is possible to determine whether there are invalid characteristic data in the multiple first detection data. Since the peak data corresponds to the energy of the alpha particle, radon-222 and its decay products 218 PO, 214 PO, 210 PO, the corresponding alpha particle energy is 5.48Mev, 6.00Mev, 7.69Mev, 5.30Mev. Adding the energy attenuation and deviation in the detection process, the corresponding value on the ADC channel address is a range.

[0043] Therefore, if the value of the first peak data is not within the preset range (corresponding to the energy of the α particles), the first peak data is invalid characteristic data.

[0044] In addition, during the radon decay process, the corresponding detection data will only have one peak data. Therefore, if the value of the first detection data after the first peak data is greater than the first peak data, the first peak data and the first detection data greater than the first peak data are also invalid characteristic data.

[0045] The above judgment conditions are only examples and may include more or fewer judgment criteria in actual application scenarios.

[0046] Optionally, determining whether invalid characteristic data exists in multiple first detection data based on the first peak data includes: if the first peak data is not within the valid numerical range, determining that the first peak data is invalid characteristic data; if the first peak data is within the valid numerical range, judging whether the collection time of the first peak data is before the first moment; if the collection time of the first peak data is not before the first moment, determining that the first peak data is invalid characteristic data.

[0047] Specifically, in the embodiment of the present application, it is mainly determined whether the first peak data is invalid characteristic data. Since the peak data corresponds to the energy of the alpha particles, the value corresponding to the peak data should be a range (for example, 300~800, which is only an example here, depending on the configuration of the radon gas detection equipment).

[0048] For example, see Figure 5A , Figure 5A Schematic diagram of the first type of invalid feature data provided in the embodiment of the present application. In this example, the valid value range of the peak value data is 300~800. It can be seen that Figure 5A In the example, the data collected in the 15th acquisition sequence is the first peak data, and the ADC channel address value corresponding to the first peak data shown is 260, which is not within the above-mentioned valid value range. Therefore, the peak data is an invalid feature data.

[0049] In the embodiment of the present application, since the processing module needs to perform a series of initializations from being awakened by the pulse signal to starting collection, it takes a certain amount of time (for example, 70μs), and the time for the pulse to reach the peak is roughly between (100μs and 150μs), that is, the time from the start of collection to reaching the peak is (30μs to 80μs). Under the premise that the processing module collects one point in 5μs, the peak data should be between the first detection data of the 6th to 16th in the collection order. Taking into account factors such as test errors, the peak data is within the 20th point.

[0050] Therefore, after determining that the first peak data is within the valid value range, the processing module is also required to determine whether the acquisition time of the first peak data is before the first time.

[0051] For example, see Figure 5B , Figure 5B Schematic diagram of the second type of invalid feature data provided in the embodiment of the present application. In this example, the collection time of the first detection data in the collection order of 21 is set as the first time. Figure 5B As shown, the 25th data collected with an ADC channel address value of 450 is the first peak data. It can be seen that the collection time of the first peak data is not before the first moment, so the peak data is invalid feature data.

[0052] It can be seen that in the embodiment of the present application, according to whether the peak data in the multiple detection data is within the valid numerical range, and secondly, the collection time of the peak data, it is possible to determine whether there is invalid characteristic data in the multiple detection data, and then identify the invalid data including the invalid characteristic data, thereby improving the detection accuracy of the radon detection device. At the same time, the numerical range of the first peak data and the collection time are determined in steps. When the first peak data is not within the valid numerical range, it can be directly determined that the first peak data is invalid characteristic data without executing subsequent steps, thereby improving the processing efficiency of the radon detection device.

[0053] Optionally, if the collection time of the first peak data is before the first moment, the method also includes: if the first target data is less than or equal to the second target data, then determining that the first target data is invalid feature data, wherein the collection time of the first target data is earlier than the collection time of the second target data, and the collection time of the first target data and the collection time of the second target data are both later than the collection time of the first peak data; if the first target data is greater than the first detection data whose collection time is after the first target data, then determining whether the first target data before the second moment is greater than a preset value, and the second moment is after the first moment; if the collection time of the first target data is before the second moment and the first target data is less than or equal to the preset value, then determining the first target data as invalid feature data.

[0054] Specifically, in the embodiment of the present application, in addition to determining whether the first peak data is invalid feature data, it is also necessary to determine whether the first target data collected later than the first peak data is invalid feature data. The collection time of the second target data is later than the collection time of the first target data and the first peak data.

[0055] First of all, based on the characteristics of radon gas decay, among multiple first detection data, the value of the first target data after the first peak data should decrease. If, among the multiple first detection data collected, the values ​​of the multiple first detection data are high and low, it means that the detection signal corresponding to the multiple first detection data is a continuous electrical signal caused by vibration, and a new vibration is generated when the previous vibration completely stops, causing the detection signal value to rise again.

[0056] Therefore, it is necessary to first determine whether the first target data is less than or equal to the second target data, so as to determine whether the data of the plurality of first detection data after the first peak data decreases.

[0057] For example, see Figure 5C , Figure 5CThis is a schematic diagram of the third type of invalid feature data provided in an embodiment of the present application. In this example, the first target data in the acquisition order between 41-61 are all less than or equal to the corresponding second target data, and therefore the first target data in the acquisition order between 41-61 are all invalid feature data.

[0058] Finally, it is also necessary to determine whether the first target data before the second moment is greater than the preset value. This is because based on the characteristics of radon gas decay, the data decrease rate after the first peak data should be slow, at least lasting for a period of time (such as 200μs, etc.). Therefore, the detection data before the second moment (for example, the moment corresponding to the first detection data in the 60th acquisition sequence) is less than or equal to the preset value, indicating that the corresponding detection signal is a false touch signal caused by vibration and other reasons.

[0059] For example, see Figure 5D , Figure 5D This is a schematic diagram of the fourth type of invalid feature data provided in an embodiment of the present application. In this example, the moment corresponding to the first target data in the 60th acquisition order is the second moment. It can be seen that the value of the first target data in the 45th acquisition order is equal to the second target data (here 0), so the first target data in the 45th acquisition order is invalid feature data.

[0060] It can be seen that in the embodiment of the present application, in the process of determining whether there is invalid feature number data in multiple detection data, whether the detection data after the peak data is invalid feature data is also considered, which further improves the detection accuracy of the radon gas detection equipment.

[0061] S103: If there is no invalid characteristic data in the plurality of first detection data, the processing module records the plurality of first detection data as a first valid data group, and the first valid data group is used to calculate the radon gas concentration.

[0062] Specifically, only when there is no invalid characteristic data in the multiple first detection data, the processing module will record the multiple first detection data as the first valid data group, that is, based on the data value, generation time, combined with the electric field efficiency and temperature and humidity calibration parameters of at least one valid data group, the concentration of radon gas in the environment (usually in Bq / m³) can be calculated.

[0063] Furthermore, if invalid characteristic data exist in the plurality of first detection data, the processing module records the plurality of first detection data as an invalid data group, and the invalid data group does not participate in the subsequent calculation of determining the radon gas concentration.

[0064] It can be seen that in the embodiment of the present application, the processing module is used to determine whether there are invalid characteristic data in multiple detection data, and the radon gas concentration is determined only based on the valid data group in which no invalid characteristic data exists. This eliminates false touch signals caused by touch or environmental vibration, and solves the problem that radon gas detection equipment is easily falsely alarmed by factors such as touch or environmental vibration.

[0065] Optionally, the method further includes: determining a detection time period, the detection time period including a generation time corresponding to the first valid data group; and judging the concentration of radon gas according to the number of valid data groups in the first detection time period and the value of the detection data of the valid data groups.

[0066] Specifically, in the embodiment of the present application, the concentration of radon gas is judged by determining the detection period, and the detection period here is determined based on the generation time corresponding to the first valid data group. The generation time of the first valid data group specifically refers to the acquisition time of the first detection data with the first order in the first valid data group. The moment after the preset time from the generation time of the first data group is the detection period here. The processing module specifically judges the concentration of radon gas based on the number of valid data groups and the numerical value of the detection data of the valid data groups, and the valid data groups here include the first valid data group in the embodiment of the present application and the second valid data group, the third valid data group, etc. in the subsequent application embodiments.

[0067] Embodiment 2: Embodiment 1 describes a radon gas detection method for obtaining a plurality of first valid data based on a first frequency and then determining the radon gas concentration based on the valid data obtained by the first frequency. Based on Embodiment 1, the application embodiment also provides a radon gas detection method including two acquisition frequencies, see Figure 6 , Figure 6 A flow chart of another radon gas detection method provided in the embodiment of the present application can be based on Figure 2 The application scenario 200 shown is implemented as Figure 6 As shown, steps S601-S604 are included: S601: The processing module collects detection signals according to a second frequency to obtain second detection data, and determines that the second detection data is greater than a preset value and the second frequency is less than the first frequency.

[0068] Specifically, in the embodiment of the present application, the radon concentration in the environment is usually low, so the detection signal generated by the detection module is usually lower than the preset threshold value (usually 0, but may be other values ​​based on the internal structure of the detection module). Therefore, in this case, the processing module is usually in a dormant state and collects detection signals at a lower second frequency. When the second detection data is greater than the preset value, the processing module ends the dormant state, that is, it is awakened by the detection signal, and then the processing module collects the detection signal at the first frequency.

[0069] It can be seen that in the embodiment of the present application, the processing module collects detection signals at a relatively low frequency, and obtains detection data for determining the radon concentration only when the detection module may detect the presence of radon gas in the environment. This allows the processing module to be in a dormant state when there is no radon gas in the environment, thereby reducing the energy consumption of the radon detection equipment.

[0070] S602: The processing module collects detection signals according to a first frequency to obtain a plurality of first detection data.

[0071] S603: The processing module obtains first peak data from the plurality of first detection data, and determines whether invalid feature data exists in the plurality of first detection data according to the first peak data.

[0072] Optionally, determining whether invalid characteristic data exists in multiple first detection data based on the first peak data includes: if the first peak data is not within the valid numerical range, determining that the first peak data is invalid characteristic data; if the first peak data is within the valid numerical range, judging whether the collection time of the first peak data is before the first moment; if the collection time of the first peak data is not before the first moment, determining that the first peak data is invalid characteristic data.

[0073] Optionally, if the collection time of the first peak data is before the first moment, the method also includes: if the first target data is less than or equal to the second target data, then determining that the first target data is invalid feature data, wherein the collection time of the first target data is earlier than the collection time of the second target data, and the collection time of the first target data and the collection time of the second target data are both later than the collection time of the first peak data; if the first target data is greater than the first detection data whose collection time is after the first target data, then determining whether the first target data before the second moment is greater than a preset value, and the second moment is after the first moment; if the collection time of the first target data is before the second moment and the first target data is less than or equal to the preset value, then determining the first target data as invalid feature data.

[0074] S604: If there is no invalid characteristic data in the plurality of first detection data, the processing module records the plurality of first detection data as a first valid data group, and the first valid data group is used to calculate the radon gas concentration.

[0075] Optionally, the method further includes: determining a detection time period, the detection time period including a generation time corresponding to the first valid data group; and judging the concentration of radon gas according to the number of valid data groups in the first detection time period and the value of the detection data of the valid data groups.

[0076] For the detailed description of steps S602-S604, please refer to the relevant description of the aforementioned steps S101-S103, which will not be repeated here.

[0077] Optionally, after recording multiple first detection data as a first valid data group, the method also includes: collecting detection signals at a second frequency to obtain third detection data; if the third detection data is greater than a preset value, collecting detection signals at the first frequency to obtain multiple fourth detection data; obtaining second peak data from the multiple fourth detection data, and determining whether invalid feature data exists in the multiple fourth detection data based on the second peak data; if invalid feature data does not exist in the multiple fourth detection data, recording the multiple fourth detection data as a second valid data group; if the generation time difference between the first valid data group and the second valid data group is less than the preset time difference, modifying the first valid data group to a first invalid data group.

[0078] Specifically, after recording the plurality of first detection data as the first valid data group, the processing process for the plurality of first detection data is temporarily terminated. As described in the previous embodiment, the processing module determines the radon concentration in the environment, specifically through the data values, generation time and other characteristics of the plurality of valid data groups within a period of time. Therefore, within a period of time after recording the plurality of first detection data as the first valid data group, the detection module may also obtain a new valid data group.

[0079] After recording the plurality of first detection data as the first valid data group, that is, after the processing module finishes processing the plurality of first detection data, the processing module returns to the sleep state and collects detection signals at the second frequency to obtain third detection data.

[0080] If the third detection data is greater than the preset value, that is, the detection module detects radon gas in the environment again, the processing module collects the detection signal according to the first frequency to obtain a plurality of fourth detection data.

[0081] For a detailed description of how the processing module determines whether invalid characteristic data exists in multiple fourth detection data based on the second peak data, please refer to the related description of how the processing module determines whether invalid characteristic data exists in multiple first detection data based on the first peak data in the aforementioned content, which will not be repeated here.

[0082] In addition, if the generation time of the second valid data set is also within the detection period, the second valid data set is also used to calculate the radon gas concentration in the subsequent steps.

[0083] It should be noted that, usually in the process of radon gas measurement, it is very rare to generate multiple valid data groups in a short period of time (except in environments with extremely high radon gas concentrations). However, the interference pulses generated by external vibrations are likely to be generated at the ms level. At this time, the valid data group can be further judged by recording the time difference between the two groups of valid data.

[0084] If the generation time difference between the first valid data group and the second valid data group is less than the preset time difference (for example, 1 second), it indicates that the situation described above where multiple valid data groups are generated in a short period of time has occurred. In this case, the first valid data group is modified to the first invalid data group.

[0085] The generated time difference here is specifically calculated based on the difference between the acquisition time of the detection data with the first acquisition sequence in the first data group and the acquisition time of the detection data with the first acquisition sequence in the second valid data group.

[0086] Furthermore, whether the second valid data group needs to be modified into the second invalid data group needs to be determined by generating a valid data group whose time is later than the second valid data group.

[0087] It can be seen that in the embodiment of the present application, by judging whether the generation time difference of two adjacent valid data groups is less than the preset time difference, it is possible to further judge that there is no invalid data group with invalid characteristic data, thereby further improving the detection accuracy of the radon gas detection equipment.

[0088] Optionally, if there are multiple consecutive valid data groups that are modified into invalid data groups within a preset time period, and the generation time differences between adjacent valid data groups in the multiple consecutive valid data groups are all less than the preset time difference; then stop collecting detection signals, and collect detection signals according to the first frequency after the preset time to obtain multiple fifth detection data; obtain the third peak data in the multiple fifth detection data, and determine whether there are invalid characteristic data in the multiple fifth detection data based on the third peak data; if there are no invalid characteristic data in the multiple fifth detection data, generate an alarm message, and the alarm message is used to indicate that the current radon gas concentration exceeds the measuring range of the radon gas detection equipment.

[0089] Specifically, in the embodiment of the present application, if there are multiple (specifically 3, 4 or 5 groups, etc.) continuous valid data groups that are modified to invalid data groups within a preset time period, it actually means that the detection module generates multiple valid data groups in a short period of time, but the generation time difference between adjacent valid data groups in the multiple valid data groups is small, so there are multiple continuous valid data groups that are modified to invalid data groups. This may be caused by continuous vibration or because the radon concentration in the environment exceeds the range of the radon detection device.

[0090] Therefore, under the premise that there are multiple consecutive valid data groups that are modified into invalid data groups within the preset time period, and the generation time difference between adjacent valid data groups in the multiple consecutive valid data groups is less than the preset time difference, the processing module of the radon gas detection equipment stops collecting detection signals, the detection module also stops running, and after a preset time (for example, 30s, 1min, etc.), it re-collects detection signals according to the first frequency.

[0091] After the preset time, if the reason why multiple consecutive valid data groups are modified into invalid data groups is that the radon gas detection device is subjected to continuous vibration or continuous touching, then after the preset time, the detection module is highly likely to be unable to generate a valid detection signal.

[0092] If the processing module obtains multiple fifth detection data; and according to the third peak data in the multiple fifth detection data, it is determined that there is no invalid characteristic data in the multiple fifth detection data, the multiple fifth detection data are a valid detection data group. For the detailed judgment process, please refer to the above description of judging whether there is invalid characteristic data in the multiple first detection data according to the first peak data, which will not be repeated here.

[0093] It should be noted that the radon gas detection equipment is usually not subjected to continuous vibration or continuous touching for too long, and the multiple sets of detection data generated during this period will not all be valid data sets. Therefore, it is judged that the radon gas concentration in the environment is high at this time, and an alarm message is generated to indicate that the current radon gas concentration exceeds the measuring range of the radon gas detection equipment.

[0094] Furthermore, the radon gas detection device will alarm or send an alarm message to the user terminal based on the alarm information to warn that the radon gas concentration in the alarm environment exceeds the range of the radon gas detection device.

[0095] It can be seen that in the embodiment of the present application, when there are multiple groups of continuous valid data groups that are modified into invalid data groups, by pausing the collection of detection signals and re-collecting the newly collected detection data after a preset time, it can be determined whether the situation in which multiple groups of continuous valid data groups are modified into invalid data groups is due to continuous vibration or excessive radon gas concentration, thereby improving the reliability of the radon gas detection equipment.

[0096] Embodiment 3: The above embodiment 1 describes a radon gas detection method for determining whether the multiple detection data are a valid detection data group based on the multiple detection data after obtaining the multiple detection data. Based on embodiment 1, the embodiment of the present application also adopts another radon gas detection method for determining whether the multiple detection data obtained are invalid data from the stage of obtaining the multiple detection data. Figure 7 , Figure 7 A flow chart of another radon gas detection method provided in the embodiment of the present application can be based on Figure 2 The application scenario 200 shown is implemented as Figure 7 The method comprises steps S701-S704: S701: The processing module collects detection signals at a first frequency to obtain a plurality of first detection data.

[0097] Optionally, after collecting the detection signal at the first frequency, the method also includes: if the third target data is less than or equal to a preset value, stop collecting the detection signal at the first frequency, the third target data being the first detection data among multiple first detection data whose collection moment is before the second moment; and determine the multiple first detection data as a first invalid data group.

[0098] Specifically, in an embodiment of the present application, in the process of collecting multiple first detection data, it is simultaneously determined whether the third target data is less than or equal to a preset value. The third target data is the first detection data among the multiple first detection data whose collection time is before the second time. For example, if the second time is the collection time corresponding to the 61st first detection data collected in the collection order, the third target data here is the first 60 first detection data.

[0099] If the third target data is less than or equal to the preset value, the detection signal acquisition at the first frequency is stopped. In this case, the plurality of first detection data can be determined as the first invalid data group, because the value of the first detection data before the second moment in the valid data group will not be less than the preset value (the preset value is usually 0).

[0100] Therefore, when the value of the first detection data before the second moment is less than the preset value, it can be directly determined that the current detection signal is a false touch signal caused by vibration and touch, and the corresponding multiple first detection data are also an invalid data group.

[0101] S702: The processing module determines that the number of the plurality of first detection data is a preset number.

[0102] Specifically, in the embodiment of the present application, during the process of collecting a plurality of first detection data, it is determined whether invalid characteristic data is obtained at the same time. If invalid characteristic data exists in the plurality of first target data, the processing module will terminate the collection of detection signals according to the first frequency in advance, so the plurality of first detection data will be less than a preset number (such as 100). Only when it is determined that the number of the plurality of first detection data is the preset number, will it be determined whether invalid characteristic data exists in the plurality of first detection data according to the first peak data.

[0103] S703: The processing module obtains first peak data from the plurality of first detection data, and determines whether invalid feature data exists in the plurality of first detection data according to the first peak data.

[0104] Optionally, determining whether invalid characteristic data exists in multiple first detection data based on the first peak data includes: if the first peak data is not within the valid numerical range, determining that the first peak data is invalid characteristic data; if the first peak data is within the valid numerical range, judging whether the collection time of the first peak data is before the first moment; if the collection time of the first peak data is not before the first moment, determining that the first peak data is invalid characteristic data.

[0105] Optionally, if the collection time of the first peak data is before the first moment, the method also includes: if the first target data is less than or equal to the second target data, then determining that the first target data is invalid feature data, wherein the collection time of the first target data is earlier than the collection time of the second target data, and the collection time of the first target data and the collection time of the second target data are both later than the collection time of the first peak data; if the first target data is greater than the first detection data whose collection time is after the first target data, then determining whether the first target data before the second moment is greater than a preset value, and the second moment is after the first moment; if the collection time of the first target data is before the second moment and the first target data is less than or equal to the preset value, then determining the first target data as invalid feature data.

[0106] S704: If there is no invalid characteristic data in the plurality of first detection data, the processing module records the plurality of first detection data as a first valid data group, and the first valid data group is used to calculate the radon gas concentration.

[0107] Optionally, the method further includes: determining a detection time period, the detection time period including a generation time corresponding to the first valid data group; and judging the concentration of radon gas according to the number of valid data groups in the first detection time period and the value of the detection data of the valid data groups.

[0108] For detailed descriptions of steps S703-S704, please refer to the relevant descriptions of steps S101-S103, which will not be repeated here.

[0109] It can be seen that in the embodiment of the present application, by judging whether the detection data collected is less than or equal to the preset value during the process of collecting the detection signal, the processing module can stop collecting the detection signal in advance when the detection data is less than or equal to the preset value, and there is no need to execute the subsequent step of determining whether there is invalid characteristic data in the detection data, thereby improving the detection efficiency of the radon gas detection equipment.

[0110] By implementing the method in the above-mentioned application embodiment, it can be seen that by judging whether there are invalid characteristic data in multiple detection data through the processing module, the problem of false alarms caused by factors such as touch or environmental vibration of the radon detection equipment is solved. Judging whether there are invalid characteristic data in steps improves the processing efficiency of the radon detection equipment. Acquiring detection signals according to different acquisition frequencies reduces the energy consumption of the radon detection equipment. Judging the generation time difference of two adjacent valid data groups to further determine whether the valid data group is an invalid data group improves the detection accuracy of the radon detection equipment. Judging whether the collected detection data is less than or equal to the preset value in the process of collecting the detection signal improves the detection efficiency of the radon detection equipment.

[0111] Based on the description of the above configuration method embodiment, the present application also provides a radon gas detection device 800, which can be operated at Figure 2 A computer program (including program code) in the processing module 2011 shown in FIG. Figure 1 , Figure 6 and Figure 7 See the method shown in Figure 8 , Figure 8 A schematic diagram of the structure of a radon gas detection device provided in an embodiment of the present application, the radon gas detection device 800 comprises: The collecting unit 801 is used to collect the detection signal according to the first frequency to obtain a plurality of first detection data; A determination unit 802 is used to obtain first peak data from a plurality of first detection data, and determine whether there is invalid feature data in the plurality of first detection data according to the first peak data; The recording unit 803 is configured to record the plurality of first detection data as a first valid data group if there is no invalid characteristic data in the plurality of first detection data, and the first valid data group is used to calculate the radon gas concentration.

[0112] In a possible embodiment, in terms of determining whether invalid characteristic data exists in multiple first detection data based on the first peak data, the determination unit 802 is also specifically used to: if the first peak data is not within the valid numerical range, determine that the first peak data is invalid characteristic data; if the first peak data is within the valid numerical range, determine whether the collection time of the first peak data is before the first moment; if the collection time of the first peak data is not before the first moment, determine that the first peak data is invalid characteristic data.

[0113] In a possible embodiment, if the collection time of the first peak data is before the first moment, the determination unit 802 is also specifically used to: if the first target data is less than or equal to the second target data, determine that the first target data is invalid feature data, wherein the collection time of the first target data is earlier than the collection time of the second target data, and the collection time of the first target data and the collection time of the second target data are both later than the collection time of the first peak data; if the first target data is greater than the first detection data whose collection time is after the first target data, determine whether the first target data before the second moment is greater than a preset value, and the second moment is after the first moment; if the collection time of the first target data is before the second moment and the first target data is less than or equal to the preset value, determine the first target data as invalid feature data.

[0114] In a possible embodiment, before collecting the detection signal at the first frequency to obtain multiple first detection data, the collection unit 801 is further specifically used to: collect the detection signal at the second frequency to obtain second detection data, and determine that the second detection data is greater than a preset value and the second frequency is less than the first frequency.

[0115] In a possible embodiment, after recording multiple first detection data as a first valid data group, the acquisition unit 801 is further specifically used to: acquire detection signals at a second frequency to obtain third detection data; if the third detection data is greater than a preset value, acquire detection signals at the first frequency to obtain multiple fourth detection data; obtain second peak data from the multiple fourth detection data, and determine whether invalid feature data exists in the multiple fourth detection data based on the second peak data; if invalid feature data does not exist in the multiple fourth detection data, record the multiple fourth detection data as a second valid data group; if the generation time difference between the first valid data group and the second valid data group is less than the preset time difference, modify the first valid data group to a first invalid data group.

[0116] In a possible embodiment, after collecting the detection signal at the first frequency, the collection unit 801 is further specifically used to: stop collecting the detection signal at the first frequency if the third target data is less than or equal to a preset value, and the third target data is the first detection data among multiple first detection data whose collection time is before the second time; determine the multiple first detection data as a first invalid data group.

[0117] In a possible embodiment, before obtaining the first peak data among the plurality of first monitoring data, the determining unit 802 is further specifically configured to: determine that the number of the plurality of first detection data is a preset number.

[0118] Based on the description of the above method embodiment and device embodiment, please refer to Fig. 9 , Fig. 9A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Fig. 9 The electronic device 900 shown (the electronic device 900 may be a computer device, Figure 2 The processing module 2011 shown includes a memory 901, a processor 902, a communication interface 903 and a bus 904. The memory 901, the processor 902 and the communication interface 903 are connected to each other through the bus 904.

[0119] The memory 901 may be a read-only memory (ROM), a static storage device, a dynamic storage device or a random access memory (RAM).

[0120] The memory 901 can store programs. When the program code stored in the memory 901 is executed by the processor 902, the processor 902 and the communication interface 903 are used to execute the various steps of the radon gas detection method of the embodiment of the present application.

[0121] The processor 902 can adopt a general-purpose central processing unit (CPU), a microcontroller, an application-specific integrated circuit (ASIC), a graphics processing unit (GPU) or one or more integrated circuits to execute relevant programs to implement the functions required to be performed by the units in the electronic device 900 of the embodiment of the present application, or to execute the radon gas detection method of the method embodiment of the present application.

[0122] The processor 902 may also be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the radon gas detection method of the present application may be completed by an integrated logic circuit of hardware or software instructions in the processor 902. The above-mentioned processor 902 may also be a general-purpose processor, a digital signal processor (Digital Signal Processing, DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (Field Programmable Gate Array, FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application may be implemented or executed. The general-purpose processor may be a microcontroller or the processor may also be any conventional processor, etc. The steps of the method disclosed in the embodiments of the present application may be directly embodied as being executed by a hardware decoding processor, or may be executed by a combination of hardware and software modules in a decoding processor. The software module may be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 901, and the processor 902 reads the information in the memory 901, and combines its hardware to complete the functions required to be performed by the units included in the electronic device 900 of the embodiment of the present application, or executes the radon gas detection method of the method embodiment of the present application.

[0123] The communication interface 903 uses a transceiver device such as, but not limited to, a transceiver to implement communication between the electronic device 900 and other devices or a communication network. For example, data can be acquired through the communication interface 903 .

[0124] The bus 904 may include a path for transmitting information between various components of the electronic device 900 (eg, the memory 901 , the processor 902 , and the communication interface 903 ).

[0125] It should be noted that although Fig. 9 The electronic device 900 shown only shows a memory 901, a processor 902, and a communication interface 903. However, in the specific implementation process, those skilled in the art should understand that the electronic device 900 also includes other devices necessary for normal operation. At the same time, according to specific needs, those skilled in the art should understand that the electronic device 900 may also include hardware devices for implementing other additional functions. In addition, those skilled in the art should understand that the electronic device 900 may also only include the devices necessary for implementing the embodiments of the present application, and does not necessarily include Fig. 9 All devices shown in .

[0126] An embodiment of the present application further provides a chip, which includes a processor and a data interface. The processor reads instructions stored in a memory through the data interface to implement the radon gas detection method.

[0127] Optionally, as an implementation manner, the chip may further include a memory, in which instructions are stored, and the processor is used to execute the instructions stored in the memory. When the instructions are executed, the processor is used to execute the radon gas detection method.

[0128] An embodiment of the present application also provides a computer-readable storage medium, which stores instructions. When the computer-readable storage medium is executed on a computer or a processor, the computer or the processor executes one or more steps in any of the above methods.

[0129] The embodiment of the present application further provides a computer program product including instructions. When the computer program product is executed on a computer or a processor, the computer or the processor executes one or more steps in any of the above methods.

[0130] Those skilled in the art will appreciate that the functions described in conjunction with the various illustrative logic blocks, modules, and algorithm steps disclosed herein can be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions described in the various illustrative logic blocks, modules, and steps can be stored or transmitted as one or more instructions or codes on a computer-readable medium and executed by a hardware-based processing unit. Computer-readable media may include computer-readable storage media, which corresponds to tangible media, such as data storage media, or includes any media that facilitates the transfer of computer programs from one place to another (e.g., based on a communication protocol). In this manner, computer-readable media may generally correspond to (1) non-temporary tangible computer-readable storage media, or (2) communication media, such as signals or carrier waves. Data storage media may be any available media that can be accessed by one or more computers or one or more processors to retrieve instructions, codes, and / or data structures for implementing the techniques described in this application. A computer program product may include a computer-readable medium.

[0131] As an example and not limitation, such computer-readable storage media may include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage, flash memory, or any other medium that can be used to store the desired program code in the form of instructions or data structures and can be accessed by a computer. Also, any connection is properly referred to as a computer-readable medium. For example, if instructions are transmitted from a website, server or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio and microwave are included in the definition of media. However, it should be understood that the computer-readable storage media and data storage media do not include connections, carrier waves, signals or other temporary media, but are actually directed to non-temporary tangible storage media. As used herein, disks and optical disks include compact disks (CDs), laser optical disks, optical optical disks, digital versatile disks (DVDs), and Blu-ray disks, where disks typically reproduce data magnetically, while optical disks reproduce data optically using lasers. Combinations of the above should also be included within the scope of computer-readable media.

[0132] Instructions may be executed by one or more processors, such as one or more digital signal processors (DSPs), general purpose microcontrollers, application specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuits. Thus, the term "processor" as used herein may refer to any of the aforementioned structures or any other structures suitable for implementing the techniques described herein. Additionally, in some aspects, the functions described by the various illustrative logic blocks, modules, and steps described herein may be provided within dedicated hardware and / or software modules configured for encoding and decoding, or incorporated in a combined codec. Moreover, the techniques may be fully implemented in one or more circuits or logic elements.

[0133] The techniques of the present application may be implemented in a variety of devices or apparatuses, including a wireless handset, an integrated circuit (IC), or a set of ICs (e.g., a chipset). Various components, modules, or units are described in the present application to emphasize the functional aspects of the device for performing the disclosed techniques, but they do not necessarily need to be implemented by different hardware units. In fact, as described above, the various units may be combined in an encoded hardware unit in conjunction with appropriate software and / or firmware, or provided by interoperating hardware units (including one or more processors as described above).

[0134] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the specific descriptions of the corresponding steps in the aforementioned method embodiments, and will not be repeated here.

[0135] It should be understood that in the description of the present application, unless otherwise specified, " / " indicates that the objects associated before and after are in an "or" relationship, for example, A / B can represent A or B; wherein A and B can be singular or plural. Also, in the description of the present application, unless otherwise specified, "multiple" refers to two or more than two. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, wherein a, b, c can be single or multiple. In addition, in order to facilitate the clear description of the technical solutions of the embodiments of the present application, in the embodiments of the present application, the words "first", "second", etc. are used to distinguish the same items or similar items with substantially the same functions and effects. Those skilled in the art can understand that the words "first", "second", etc. do not limit the quantity and execution order, and the words "first", "second", etc. do not limit them to be necessarily different. Meanwhile, in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete manner for ease of understanding.

[0136] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the division of the unit is only a logical function division, and there may be other division methods in actual implementation, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. The mutual coupling, direct coupling, or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0137] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0138] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a read-only memory (ROM), or a random access memory (RAM), or a magnetic medium, such as a floppy disk, a hard disk, a tape, a disk, or an optical medium, such as a digital versatile disc (DVD), or a semiconductor medium, such as a solid state disk (SSD), etc.

[0139] The above is only a specific implementation of the embodiment of the present application, but the protection scope of the embodiment of the present application is not limited thereto, and any changes or replacements within the technical scope disclosed in the embodiment of the present application should be included in the protection scope of the embodiment of the present application. Therefore, the protection scope of the embodiment of the present application should be based on the protection scope of the claims.

[0140] The device embodiments described above are merely illustrative, wherein the units and modules described as separate components may or may not be physically separated. In addition, some or all of the units and modules may be selected according to actual needs to achieve the purpose of the present embodiment. Those of ordinary skill in the art may understand and implement the present invention without creative effort.

[0141] The above is only a specific implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A radon gas detection method, characterized in that: A processing module applied to a radon gas detection device, wherein the radon gas detection device further comprises a detection module, wherein the detection module is used to detect radon gas and generate a detection signal when radon gas is detected. The method comprises: Collecting the detection signal at a first frequency to obtain a plurality of first detection data; Acquire first peak data from the plurality of first detection data, and determine whether invalid feature data exists in the plurality of first detection data according to the first peak data; If the invalid characteristic data does not exist in the plurality of first detection data, the plurality of first detection data are recorded as a first valid data group, and the first valid data group is used to calculate the radon gas concentration.

2. The method according to claim 1, characterized in that The determining, according to the first peak data, whether there is invalid feature data in the plurality of first detection data comprises: If the first peak value data is not within the valid value range, determining that the first peak value data is invalid feature data; If the first peak data is within the valid value range, determining whether the collection time of the first peak data is before the first time; If the collection time of the first peak data is not before the first time, it is determined that the first peak data is invalid feature data.

3. The method according to claim 1, characterized in that If the acquisition time of the first peak data is before the first time, the method further includes: If the first target data is less than or equal to the second target data, the first target data is determined to be the invalid feature data, wherein the collection time of the first target data is earlier than the collection time of the second target data, and the collection time of the first target data and the collection time of the second target data are both later than the collection time of the first peak data; If the first target data is greater than the first detection data collected after the first target data, determining whether the first target data before a second time is greater than a preset value, the second time being after the first time; If the collection time of the first target data is before the second time and the first target data is less than or equal to a preset value, the first target data is determined as the invalid feature data.

4. The method according to any one of claims 1 to 3, characterized in that: Before collecting the detection signal at the first frequency to obtain a plurality of first detection data, the method further includes: The detection signal is collected at a second frequency to obtain second detection data, and it is determined that the second detection data is greater than a preset value, and the second frequency is less than the first frequency.

5. The method according to claim 4, characterized in that After recording the plurality of first detection data as a first valid data group, the method further includes: Collecting the detection signal at a second frequency to obtain third detection data; If the third detection data is greater than a preset value, collecting the detection signal at a first frequency to obtain a plurality of fourth detection data; Acquire second peak data from the plurality of fourth detection data, and determine whether invalid feature data exists in the plurality of fourth detection data according to the second peak data; If the invalid feature data does not exist in the plurality of fourth detection data, recording the plurality of fourth detection data as a second valid data group; If the generation time difference between the first valid data group and the second valid data group is less than a preset time difference, the first valid data group is modified to a first invalid data group.

6. The method according to claim 1 or 2, characterized in that: After collecting the detection signal according to the first frequency, the method further includes: If the third target data is less than or equal to a preset value, stop collecting the detection signal at the first frequency, the third target data being the first detection data collected before the second time among the multiple first detection data; The plurality of first detection data are determined as a first invalid data group.

7. The method according to claim 6, characterized in that Before determining whether invalid feature data exists in the plurality of first detection data according to the first peak data, the method further includes: Determine that the number of the plurality of first detection data is a preset number.

8. A radon gas detection device, characterized in that: The radon gas detection device is used to perform the radon gas detection method. The radon gas detection device belongs to radon gas detection equipment. The radon gas detection equipment also includes a detection module. The detection module is used to detect radon gas and generate a detection signal when radon gas is detected. The device includes: A collection unit, used for collecting the detection signal at a first frequency to obtain a plurality of first detection data; a determining unit, configured to obtain first peak data from the plurality of first detection data, and determine whether invalid feature data exists in the plurality of first detection data according to the first peak data; A recording unit is used for recording the plurality of first detection data as a first valid data group if the invalid characteristic data does not exist in the plurality of first detection data, wherein the first valid data group is used for calculating the radon gas concentration.

9. An electronic device, characterized in that: The method comprises 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 programs include instructions for executing the steps in the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute the method according to any one of claims 1 to 7.

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