Radon detection anti-interference identification method and device for complex electromagnetic environment

Abstract

The application discloses a radon detection anti-interference identification method and device for a complex electromagnetic environment, and the method comprises the following steps: collecting a first detection signal in a preset period, pre-processing the first detection signal to obtain a target first detection signal; collecting a first electromagnetic signal in a preset period, pre-processing the first electromagnetic signal to obtain a target first electromagnetic signal; performing feature extraction on the target first electromagnetic signal to obtain a first feature; matching the first feature with electromagnetic interference features of each sample pair in a preset database to obtain a plurality of first matching results; obtaining a target pseudo-signal waveform corresponding to the target matching result; matching the target first detection signal with the target pseudo-signal waveform to obtain a first matching value; and performing effectiveness detection on the target first detection signal according to the first matching value. The embodiment of the application can improve the measurement accuracy and reliability of a radon detector in a complex electromagnetic environment.

Description

Technical Field

[0001] This application relates to the field of radon detection technology, specifically to a radon detection anti-interference identification method and device for complex electromagnetic environments. Background Technology

[0002] Existing radon detection technologies are typically based on the principle of alpha particle pulse ionization chambers. Specifically, they collect the alpha particle ionization current pulses released by radon decay, amplify and discriminate them, and then count the number of pulses per unit time to indirectly estimate the ambient radon concentration. However, with the rapid development of electronic technology and the widespread use of electronic devices (such as communication base stations, wireless charging devices, industrial frequency converters, and smart terminals), the intensity of environmental electromagnetic noise is increasing exponentially. The signal acquisition circuit of radon detectors (especially the preamplifier and pulse discrimination module) is extremely sensitive to electromagnetic interference. Broadband electromagnetic noise (such as radio frequency interference and pulse electromagnetic interference) can easily couple to the main detection channel, inducing a "false rise" in the current pulse and forming electromagnetic pseudo-signals that are difficult to distinguish from real radon decay pulses. This type of interference is characterized by its wide bandwidth, high randomness, and variable waveform, seriously affecting the measurement accuracy and reliability of radon.

[0003] Therefore, it is urgent to solve the problem of how to provide an anti-interference identification method for radon gas detection in complex electromagnetic environments, so as to accurately filter out electromagnetic pseudo signals and improve the measurement accuracy and reliability of radon gas detectors in complex electromagnetic environments. Summary of the Invention

[0004] This application provides a radon detection anti-interference identification method and device for complex electromagnetic environments. It aims to accurately filter out electromagnetic pseudo signals in complex electromagnetic environments, thereby improving the measurement accuracy and reliability of radon detectors in such environments.

[0005] In a first aspect, embodiments of this application provide a radon detection anti-interference identification method for complex electromagnetic environments, applied to a radon detection anti-interference identification system; the radon detection anti-interference identification system includes: a semiconductor radon sensor, a first preprocessing circuit, an electromagnetic sensor, and a second preprocessing circuit; the method includes: The semiconductor radon gas sensor collects a first detection signal over a preset period of time, and the first detection signal is preprocessed by the first preprocessing circuit to obtain the target first detection signal. The electromagnetic sensor collects the first electromagnetic signal during the preset time period, and the second preprocessing circuit preprocesses the first electromagnetic signal to obtain the target first electromagnetic signal. The first electromagnetic signal of the target is subjected to feature extraction to obtain the first feature; The first feature is matched with the electromagnetic interference features of each sample pair in the preset database to obtain multiple first matching results; the preset database stores multiple sample pairs in advance, and each sample pair is a sample pair between electromagnetic interference features and pseudo signal waveforms; the first matching result includes one of the following: matching successful, matching failed; When the plurality of first matching results includes a successfully matched target matching result, the target pseudo signal waveform corresponding to the target matching result is obtained; The target first detection signal is matched with the target pseudo signal waveform to obtain a first matching value; The effectiveness of the first detection signal of the target is detected based on the first matching value to obtain the target effectiveness detection result.

[0006] Secondly, embodiments of this application provide a radon detection anti-interference identification device for complex electromagnetic environments, applied to a radon detection anti-interference identification system; the radon detection anti-interference identification system includes: a semiconductor radon sensor, a first preprocessing circuit, an electromagnetic sensor, and a second preprocessing circuit; the device includes: a collection unit, an extraction unit, a matching unit, an acquisition unit, and a detection unit, wherein, The acquisition unit is configured to acquire a first detection signal for a preset time period through the semiconductor radon gas sensor, and preprocess the first detection signal through the first preprocessing circuit to obtain a target first detection signal; and to acquire a first electromagnetic signal for the preset time period through the electromagnetic sensor, and preprocess the first electromagnetic signal through the second preprocessing circuit to obtain a target first electromagnetic signal. The extraction unit is used to extract features from the target first electromagnetic signal to obtain a first feature; The matching unit is used to match the first feature with the electromagnetic interference features of each sample pair in the preset database to obtain multiple first matching results; the preset database stores multiple sample pairs in advance, and each sample pair is a sample pair between the electromagnetic interference feature and the pseudo signal waveform; the first matching result includes one of the following: matching successful, matching failed; The acquisition unit is used to acquire the target pseudo signal waveform corresponding to the target matching result when the multiple first matching results include a successfully matched target matching result; The matching unit is further configured to match the target first detection signal with the target pseudo signal waveform to obtain a first matching value; The detection unit is used to perform validity detection on the first detection signal of the target based on the first matching value, and obtain the target validity detection result.

[0007] Thirdly, embodiments of this application provide an electronic device, including a processor, a memory, 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 performing the steps in the first aspect of embodiments of this application.

[0008] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program for electronic data interchange, wherein the computer program causes a computer to perform some or all of the steps described in the first aspect of embodiments of this application.

[0009] Fifthly, embodiments of this application provide a computer program product, wherein the computer program product 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 described in the first aspect of embodiments of this application. The computer program product may be a software installation package.

[0010] Implementing the embodiments of this application has the following beneficial effects: As can be seen, the radon detection anti-interference identification method and device for complex electromagnetic environments described in the embodiments of this application are applied to a radon detection anti-interference identification system. First, the system can synchronously acquire radon decay signals (first detection signals) and environmental electromagnetic signals (first electromagnetic signals) through a semiconductor radon sensor and an electromagnetic sensor, and can respectively complete optimizations such as noise suppression and signal amplification through preprocessing circuits. Second, features (e.g., spectral distribution, pulse timing, energy intensity, etc.) can be extracted from the preprocessed electromagnetic signals and compared with a preset database (which pre-stores the mapping relationship between electromagnetic interference features and pseudo signal waveforms). The system matches the electromagnetic interference characteristics of sample pairs in the system to quickly identify whether the current electromagnetic environment induces false radon signals, thus achieving dynamic determination of the interference type. Then, when an electromagnetic interference characteristic is matched, the system can retrieve the corresponding false signal waveform template and compare it with the preprocessed radon detection signal to determine whether the detection signal is contaminated by electromagnetic interference through quantitative matching value. Ultimately, the system achieves electromagnetic interference identification and accurate source tracing and filtering of false signals. In this way, it can accurately filter out electromagnetic false signals in complex electromagnetic environments, improving the measurement accuracy and reliability of radon detectors in complex electromagnetic environments. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a first structural schematic diagram of a radon detection anti-interference identification system for implementing a radon detection anti-interference identification method for complex electromagnetic environments, provided in an embodiment of this application. Figure 2 This is a second structural schematic diagram of a radon detection anti-interference identification system provided in an embodiment of this application for implementing a radon detection anti-interference identification method for complex electromagnetic environments; Figure 3 This is a third structural schematic diagram of a radon detection anti-interference identification system provided in an embodiment of this application for implementing a radon detection anti-interference identification method for complex electromagnetic environments; Figure 4 This is a flowchart illustrating a radon detection and anti-interference identification method for complex electromagnetic environments provided in an embodiment of this application. Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application; Figure 6 This is a block diagram of the functional units of a radon gas detection and anti-interference identification device for complex electromagnetic environments provided in this application embodiment. 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 some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill 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] It should be understood that the term "and / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this document indicates that the preceding and following related objects are in an "or" relationship. In the embodiments of this application, "multiple" refers to two or more.

[0016] In the embodiments of this application, "at least one item" or its similar expression refers to any combination of these items, including any combination of a single item or a plurality of items. "One or more" means one or more, while "multiple" means two or more. For example, "at least one item" of a, b, or c can represent the following seven cases: a, b, c; a and b; a and c; b and c; a, b, and c. Each of a, b, and c can be an element or a set containing one or more elements.

[0017] In this application, the term "connection" refers to various connection methods, such as direct connection or indirect connection, to achieve communication between devices. This application does not impose any limitations on this.

[0018] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0019] Please see Figure 1 , Figure 1 This is a first structural schematic diagram of a radon detection and anti-interference identification system provided in this application embodiment for implementing a radon detection anti-interference identification method for complex electromagnetic environments, as shown below. Figure 1 As shown, the radon detection anti-interference identification system includes a semiconductor radon sensor, a first preprocessing circuit, an electromagnetic sensor, and a second preprocessing circuit; wherein the semiconductor radon sensor, the first preprocessing circuit, the electromagnetic sensor, and the second preprocessing circuit are communicatively connected and / or electrically connected.

[0020] Among them, the semiconductor radon gas sensor, which can be used as a radon gas signal acquisition branch (such as an electrostatic collection chamber group), can be implemented by using a high-voltage power supply to provide a working electric field for the electrostatic collection chamber. After the alpha particles released by radon decay are incident on the semiconductor radon gas sensor, a weak ionization current signal proportional to the energy of the alpha particles is generated, which is used as the raw signal for radon concentration measurement.

[0021] Among them, the electromagnetic sensor, which can be used as an electromagnetic interference acquisition branch, can be independently added in the specific implementation to synchronously acquire the ambient broadband electromagnetic noise signal and use it for subsequent correlation identification of pseudo radon pulses induced by electromagnetic interference.

[0022] The first preprocessing circuit can be used to preprocess the signals acquired by the semiconductor radon gas sensor. Preprocessing can include functions such as converting current signals to voltage signals, baseline stabilization, signal amplification, and signal filtering. For example, the raw radon gas signal first undergoes preliminary processing such as conversion from current signal to voltage signal and baseline stabilization in the preamplifier circuit, and then is input to a linear pulse amplifier to linearly amplify the weak millivolt-level pulse signal to the volt level. At the same time, signal filtering can be performed to preserve the amplitude and waveform characteristics of the pulse.

[0023] The second preprocessing circuit can be used to preprocess the electromagnetic noise signal collected by the electromagnetic sensor. The preprocessing can include signal filtering, signal amplification, impedance matching, etc. Specifically, after the signal conditioning circuit completes the signal filtering, signal amplification, and impedance matching, it is sent together with the amplified radon pulse signal to the back-end analysis module to realize the measurement of total radon, and / or the measurement of radon energy spectrum, or the full spectrum measurement.

[0024] Furthermore, such as Figure 2 As shown, the first preprocessing circuit may include a preamplifier circuit and a linear pulse amplifier. The preamplifier circuit converts the extremely weak charge pulses (e.g., femto-C level (fC)) generated by the ionization of alpha particles in the detector into a proportional voltage signal, facilitating amplification, discrimination, and counting in subsequent circuits. The linear pulse amplifier linearly amplifies the signal from the preamplifier circuit to ensure that the correspondence between the signal amplitude and radon concentration remains undistorted. Simultaneously, it maintains the pulse waveform characteristics (e.g., width, rise time), providing a high-fidelity signal for subsequent analysis.

[0025] The second preprocessing circuit may include a signal conditioning circuit. After the signal conditioning circuit completes signal filtering, signal amplification, and impedance matching, the signal is sent together with the amplified radon pulse signal to the back-end analysis module to realize the measurement of total radon, and / or the measurement of radon energy spectrum, or the measurement of the full spectrum.

[0026] The back-end analysis module can be used to measure total radon, radon energy spectrum, full spectrum, and so on.

[0027] Specifically, the radon total concentration measurement branch can include a comparator circuit and a counter. The comparator circuit compares the amplified pulse with a threshold, allowing only valid pulses with amplitudes exceeding the threshold to pass through, thus filtering out noise or invalid signals. The counter counts the number of valid pulses per unit time. In practice, the higher the radon concentration and the more decay events, the more valid pulses are counted. Therefore, the total radon concentration can be inferred from the counting results; for example, the radon content per cubic meter can be obtained.

[0028] Specifically, the radon energy spectrum measurement branch can include a pulse amplitude analysis circuit, an auxiliary circuit, and a counter. The pulse amplitude analysis circuit is used to divide the amplitude value of each pulse into intervals and count the number of pulses, for example, the number of pulses in low, medium, and high amplitude intervals. Since different isotopes of radon have different decay energies, resulting in differences in pulse amplitude, the energy spectrum can reflect information such as the isotopic composition and decay energy states of radon. The auxiliary circuit provides support for amplitude analysis, such as bias adjustment, gain adjustment, and channel selection, for example, calibrating the amplitude reference and setting the analysis range. The counter is used to count the number of pulses in each amplitude interval to generate energy spectrum data related to amplitude and count rate.

[0029] Specifically, the full-spectrum measurement branch can include an electromagnetic sensor, a semiconductor radon sensor, a multi-channel amplitude analyzer, interface circuitry, a computer system, and application software. The electromagnetic sensor can detect electromagnetic interference signals in the environment, such as power supply noise and electromagnetic radiation. The semiconductor radon sensor can detect the decay energy of different isotopes of radon and convert it into digital signals for subsequent analysis. The multi-channel amplitude analyzer can divide pulse amplitudes (e.g., from the electromagnetic sensor and radon sensor) into more subdivided channels (higher resolution than energy spectrum measurement), count the number of pulses in each channel, and generate more refined full-spectrum data (e.g., covering a wider amplitude range and finer-grained energy distribution). The interface circuitry enables signal transmission and protocol conversion (e.g., USB, Ethernet, etc.) between the multi-channel amplitude analyzer and the computer, ensuring stable data communication. The computer system and application software, after receiving the full spectrum data, can perform data processing (e.g., peak fitting, concentration calculation), storage (e.g., historical data archiving), and visualization (e.g., displaying energy spectrum curves, real-time concentration display), serving as the "brain" and interactive terminal of the system.

[0030] In this embodiment, the system can be designed with three parallel measurement modes, which can be switched or operated in conjunction according to the needs of the scenario, as follows: The radon total gas measurement channel can amplify the radon pulse, set a threshold through a comparator circuit, filter out the effective pulses that are higher than the noise floor, and send them to the counter for statistics. It can quickly output the coarse measurement results of the ambient radon concentration and is suitable for routine rapid inspection scenarios.

[0031] The radon energy spectrum measurement channel can distinguish the amplitude of amplified radon pulses through a pulse amplitude analysis circuit (the pulse amplitude generated by different particles corresponds to their energy characteristics). Combined with the calibration of auxiliary circuits, it can distinguish the characteristic energy peaks of radon and its progeny, realize the accurate measurement of radon concentration, and at the same time, it can preliminarily identify the source of abnormal pulses.

[0032] The full-spectrum measurement channel, specifically, uses a multi-channel amplitude analyzer to simultaneously acquire radon pulse signals and electromagnetic interference signals. The data is then uploaded to the computer system via an interface circuit. Combined with the built-in correlation database (i.e., the mapping relationship between electromagnetic interference characteristics and pseudo-signal waveforms), the system completes the matching and identification of electromagnetic interference and the source filtering of pseudo-signals. Finally, it can output high-precision radon measurement results that have passed anti-interference verification.

[0033] In specific implementation, the main detection channel may include an electrostatic collection cavity, an alpha particle detector, a preamplifier circuit, a linear pulse amplifier circuit, a comparator circuit, and an analog-to-digital converter interface for the processing module. This channel is used to collect suspected radon decay pulse signals and obtain information on the total amount of radon. The auxiliary radon energy spectrum channel acquires the energy spectrum information of radon decay products, which is used to construct a database with the electromagnetic signal spectrum. In this embodiment, the auxiliary electromagnetic sensing channel is achieved by adding a wideband, high-sensitivity electromagnetic field sensor (e.g., a miniaturized near-field magnetic ring probe or electric field flat panel antenna) and its corresponding conditioning and acquisition circuitry. This sensor is placed inside or near the detector housing to monitor the ambient electromagnetic field strength and its time / frequency domain characteristics at the detector's location in real time. This channel is also connected to another ADC interface of the processing module.

[0034] The processing module, in particular, possesses sufficient processing power and multi-channel synchronous acquisition capabilities, as well as the ability to process data from multiple channels in parallel. The processing module may include a microprocessor (MCU).

[0035] Among them, further, such as Figure 3 As shown, the radon detection and interference resistance identification system may further include a storage module and a control module. The storage module can be used to perform storage functions, such as storing a preset database. The control module is essentially the brain of the radon detection and interference resistance identification system, controlling its various modules to perform their respective functions. The control module may include the aforementioned processing module.

[0036] Please see Figure 4 , Figure 4This is a flowchart illustrating a radon detection anti-interference identification method for complex electromagnetic environments provided in this application embodiment. As shown in the figure, it is applied to a radon detection anti-interference identification system. The radon detection anti-interference identification system includes: a semiconductor radon sensor, a first preprocessing circuit, an electromagnetic sensor, and a second preprocessing circuit. The radon detection anti-interference identification method for complex electromagnetic environments includes: S401: The semiconductor radon gas sensor collects a first detection signal for a preset time period, and the first detection signal is preprocessed by the first preprocessing circuit to obtain the target first detection signal.

[0037] The radon detection and anti-interference identification system may include: a semiconductor radon sensor, a first preprocessing circuit, an electromagnetic sensor, and a second preprocessing circuit, which are either communicatively connected or electrically connected.

[0038] The preset time period can be set in advance or set by system default. For example, the preset time period can be 1 second, 10 seconds, 30 seconds, 1 minute, etc.

[0039] In a specific implementation, a first detection signal for a preset time period can be acquired using a semiconductor radon gas sensor. A high-voltage power supply provides a working electric field for the electrostatic collection chamber. Alpha particles released from radon decay are incident on the semiconductor radon gas sensor, generating a weak ionization current signal proportional to the energy of the alpha particles. This signal is used as the raw signal for radon concentration measurement. The first detection signal is then preprocessed by a first preprocessing circuit to obtain the target first detection signal. Specifically, the first preprocessing circuit can include a preamplifier circuit and a linear pulse amplifier. The preamplifier circuit performs preliminary processing such as converting the current signal to a voltage signal and baseline stabilization. The signal is then input to the linear pulse amplifier, which linearly amplifies the weak pulse signal from the millivolt level to the volt level. Simultaneously, filtering can be performed to preserve the pulse amplitude and waveform characteristics.

[0040] S402: The electromagnetic sensor acquires the first electromagnetic signal during the preset time period, and the second preprocessing circuit preprocesses the first electromagnetic signal to obtain the target first electromagnetic signal.

[0041] In this system, while the semiconductor radon sensor acquires the first detection signal during a preset time period, the electromagnetic sensor can simultaneously acquire the first electromagnetic signal during the preset time period. The first electromagnetic signal is preprocessed by the second preprocessing circuit to obtain the target first electromagnetic signal. After signal conditioning circuit completes signal filtering, signal amplification, and impedance matching, the signal signal is sent to the back-end analysis module along with the amplified radon pulse signal to achieve total radon measurement and / or radon energy spectrum measurement, or full spectrum measurement.

[0042] In practice, steps S401 and S402 can be triggered and acquired synchronously. For example, when the main detection channel is triggered by a pulse signal exceeding the threshold, the processing module can synchronously capture the data of the auxiliary electromagnetic sensing channel within a short time window before and after the triggering moment (e.g., 1 millisecond before and after the triggering moment).

[0043] S403: Extract features from the first electromagnetic signal of the target to obtain the first feature.

[0044] The first feature may include at least one of the following: spectral distribution, pulse timing, energy intensity, etc., without limitation. For example, the first feature may also include: energy integral of a specific frequency band, pulse rise time, duration, peak amplitude, and spectral envelope shape.

[0045] In practice, feature extraction can be performed on the target's first electromagnetic signal to obtain the first feature. That is, real-time feature extraction can be performed on the data captured by the auxiliary channel to obtain the environmental electromagnetic feature vector V_current at the current moment. This first feature can be a set of vectors or a feature set.

[0046] S404: Match the first feature with the electromagnetic interference features of each sample pair in the preset database to obtain multiple first matching results; the preset database stores multiple sample pairs in advance, each sample pair being a sample pair between the electromagnetic interference feature and the pseudo signal waveform; the first matching result includes one of the following: successful matching, failed matching.

[0047] The preset database can be stored in the storage module in advance. The preset database stores multiple sample pairs in advance. Each sample pair is a sample pair between electromagnetic interference characteristics and pseudo signal waveforms. Each sample pair can correspond to an interference type or an interference mode. The interference mode can be used to characterize the interference type.

[0048] Interference can include various known electromagnetic interference events, whether man-made or naturally generated, such as switching on and off fluorescent lights, starting a microwave oven, sending and receiving signals on a mobile phone, or bursts of Wi-Fi data. Different electromagnetic interference events can correspond to different types of interference.

[0049] In a specific implementation, for example, during similarity matching and judgment, the similarity between V_current and all V_EMI samples in a preset database can be calculated (e.g., Euclidean distance, cosine similarity). For instance, a similarity threshold S_th can be set. If the electromagnetic interference feature of the first feature and any sample pair in the preset database is greater than the similarity threshold S_th, then the match is successful; otherwise, the match fails.

[0050] In practical implementation, various known electromagnetic interference events (EMIs) are artificially or naturally generated in laboratories or typical application scenarios (e.g., switching on and off fluorescent lights, starting a microwave oven, mobile phone signal transmission and reception, Wi-Fi data bursts, etc.), and data from two channels are recorded simultaneously. Specifically, for the main channel, the waveform of the pulse signal Waveform_EMI that is mistakenly triggered is recorded, and correspondingly, for the auxiliary channel, the time-domain waveform or spectral feature of the electromagnetic field of the interference event, Feature_EMI, is recorded. Then, feature extraction is performed on Feature_EMI, such as energy integral of a specific frequency band, pulse rise time, duration, peak amplitude, spectral envelope shape, etc., to form a feature vector V_EMI. Then, (V_EMI, Waveform_EMI) is used as a sample pair and stored in the "Electromagnetic Interference Feature-Pseudo-Signal Waveform Mapping Database". The database can be continuously updated through on-site learning.

[0051] Furthermore, the pre-set database can include the mapping relationship between electromagnetic interference characteristics and pseudo-signal waveforms. In other words, it can be understood as a mapping database between electromagnetic interference characteristics and pseudo-signal waveforms, which can support online updates and possess continuous learning and evolution capabilities. Specifically, when the detector encounters unknown types of interference in a new environment, the new interference patterns can be learned and added to the database with manual confirmation or the assistance of other algorithms. This enables the system to have long-term adaptability and evolutionary capabilities to cope with interference from new types of electromagnetic devices that may emerge in the future.

[0052] S405: When the plurality of first matching results include a successfully matched target matching result, obtain the target pseudo signal waveform corresponding to the target matching result.

[0053] In specific implementation, when the target matching result is successfully matched among multiple first matching results, the target pseudo signal waveform corresponding to the target matching result can be obtained. That is, when electromagnetic interference features are matched, the corresponding pseudo signal waveform template can be retrieved and compared with the preprocessed radon gas detection signal for waveform similarity. The detection signal is judged to be contaminated by electromagnetic interference by quantizing the matching value, and finally electromagnetic interference identification and accurate source tracing and filtering of pseudo signals are achieved.

[0054] When multiple first matching results include a successfully matched target result, if there is only one target matching result, the target pseudo-signal waveform corresponding to the target matching result can be directly obtained. If multiple first matching results include multiple successfully matched target results, the maximum value among them can be selected to obtain the target pseudo-signal waveform corresponding to the maximum target matching value.

[0055] S406: Match the target first detection signal with the target pseudo signal waveform to obtain a first matching value.

[0056] Specifically, features can be extracted from the first detection signal of the target to obtain the second feature, and the waveform of the target pseudo signal can be extracted to obtain the third feature. The second feature and the third feature are then matched to obtain the first matching value. Both the second and third features can include time-domain features and / or frequency-domain features, such as pulse rise time, pulse width, amplitude distribution / dynamic range, etc.

[0057] In a specific implementation, for example, a preset database contains multiple sample pairs, each corresponding to a database entry. If a database entry exists in the preset database such that its similarity is greater than S_th, and the similarity between the Waveform_EMI corresponding to this database entry and the Waveform_current pulse waveform of the current main channel is also very high (e.g., waveform cross-correlation coefficient > 0.7), then the system can determine with high confidence that the current main channel signal is a pseudo-signal caused by this type of electromagnetic interference.

[0058] S407: Perform validity detection on the first detection signal of the target based on the first matching value to obtain the target validity detection result.

[0059] In practical implementation, a broadband electromagnetic environment sensing channel can be independently added in addition to the main detection channel (which collects radon decay pulse signals). A correlation database (i.e., a preset database) between electromagnetic interference characteristics and pseudo signal waveforms can be established to enable real-time identification and filtering of pseudo radon pulse signals induced by environmental electromagnetic noise. This can solve the problem of identifying and filtering interference pulses with waveforms similar to real radon signals caused by environmental electromagnetic noise, allowing the radon detector to maintain high accuracy and reliability in complex electromagnetic pollution environments. As a result, the reliability, accuracy, and anti-interference robustness of the radon detector in complex electromagnetic environments can be greatly improved.

[0060] For example, a radon detector can be placed near a working microwave oven. In conventional solutions, an abnormally high count rate might be recorded during microwave oven operation (e.g., from 10 counts / hour in the background to 50 counts / hour). However, the radon detector equipped with the embodiment of this application can clearly capture the electromagnetic leakage characteristics of the microwave oven's unique 2.4GHz frequency band through its auxiliary channel. When the main channel is triggered, the system can quickly match the current electromagnetic characteristics with the "microwave oven interference" mode in a preset database, thereby filtering out most of the spurious signals and maintaining the count rate at a normal background level (approximately 12 counts / hour).

[0061] To illustrate further, consider a 24-hour test conducted in an office environment. In traditional methods, the count rate remains stable at night (when electronic devices are off), but fluctuates periodically and irregularly during the daytime working hours. The solution in this application, however, can successfully filter out these fluctuations by identifying electromagnetic characteristics related to router data bursts and mobile communication, ensuring that the count rate curves remain stable both day and night, thus more accurately reflecting the ambient radon concentration.

[0062] As can be seen, the radon detection anti-interference identification method for complex electromagnetic environments described in this application embodiment is applied to a radon detection anti-interference identification system. This system includes a semiconductor radon sensor, a first preprocessing circuit, an electromagnetic sensor, and a second preprocessing circuit. The semiconductor radon sensor collects a first detection signal over a preset time period, and the first preprocessing circuit preprocesses the first detection signal to obtain a target first detection signal. The electromagnetic sensor collects a first electromagnetic signal over a preset time period, and the second preprocessing circuit preprocesses the first electromagnetic signal to obtain a target first electromagnetic signal. Feature extraction is performed on the target first electromagnetic signal to obtain a first feature. The first feature is matched with the electromagnetic interference features of each sample pair in a preset database to obtain multiple first matching results. The preset database stores multiple sample pairs, each of which is a sample pair between an electromagnetic interference feature and a pseudo-signal waveform. Each first matching result includes one of the following: successful matching or failed matching. When a successful target matching result is included among the multiple first matching results, the target pseudo-signal waveform corresponding to the target matching result is obtained. The target first detection signal is matched with the target pseudo-signal waveform to obtain... The first matching value is used to perform validity detection on the first detection signal of the target, and the validity detection result of the target is obtained. First, the system can simultaneously collect radon decay signal (first detection signal) and environmental electromagnetic signal (first electromagnetic signal) through semiconductor radon gas sensor and electromagnetic sensor, and can perform optimization such as noise suppression and signal amplification through preprocessing circuit. Second, features (e.g., spectrum distribution, pulse timing, energy intensity, etc.) can be extracted from the preprocessed electromagnetic signal and compared with sample pairs in a preset database (which pre-stores the mapping relationship between electromagnetic interference features and pseudo signal waveforms). Electromagnetic interference characteristics are matched to quickly identify whether the current electromagnetic environment induces false radon signals, achieving dynamic determination of the interference type. Then, when an electromagnetic interference characteristic is matched, the system can retrieve the corresponding false signal waveform template and compare it with the pre-processed radon detection signal for waveform similarity. The system can determine whether the detection signal is contaminated by electromagnetic interference by quantifying the matching value, ultimately achieving electromagnetic interference identification and accurate source tracing and filtering of false signals. In this way, it can accurately filter out electromagnetic false signals in complex electromagnetic environments, improving the measurement accuracy and reliability of radon detectors in complex electromagnetic environments.

[0063] Optionally, step S407 above, which involves performing validity detection on the first detection signal of the target based on the first matching value to obtain the target validity detection result, can be implemented in the following manner: When the first matching value is greater than or equal to the first threshold, the target validity detection result is determined to include the target first detection signal not being a valid signal; When the first matching value is less than or equal to the second threshold, a second valid signal judgment is performed on the first detection signal of the target to obtain the target validity detection result; the second threshold is less than the first threshold. When the first matching value is greater than the second threshold and less than the first threshold, validity detection is performed based on the target matching result, the first matching value and the target first detection signal to obtain the target validity detection result.

[0064] The first threshold and the second threshold can be preset or set by the system default. The second threshold is less than the first threshold. The values ​​of the first threshold and the second threshold can both be 0 to 1. For example, the first threshold is 0.7 and the second threshold is 0.3.

[0065] In specific implementation, when the first matching value is greater than or equal to the first threshold, the electromagnetic auxiliary channel can be judged as strong interference, and the pulse signal is directly rejected and marked as invalid, that is, the target validity detection result is determined to be that the target first detection signal is not a valid signal.

[0066] Correspondingly, when the first matching value is less than or equal to the second threshold, it can be said that V_current is a calm background electromagnetic noise that does not match the interference pattern in the preset database. In this case, the system can tend to consider the main channel signal as a potentially effective signal, that is, it can perform a second effective signal judgment on the first detection signal of the target to obtain the target effectiveness detection result.

[0067] Accordingly, when the first matching value is greater than the second threshold and less than the first threshold, the validity can be detected based on the target matching result, the first matching value and the target first detection signal to obtain the target validity detection result.

[0068] In this embodiment, a dual boundary is first set between a first threshold and a second threshold. Then, for fuzzy scenarios where the first matching value is between the two thresholds, a multi-dimensional joint analysis of the target matching result, the first matching value, and the target's first detection signal is introduced. Combined with electromagnetic interference type, matching strength, and signal feature details, a refined judgment is made, effectively avoiding the risk of misjudgment that may be caused by a single threshold judgment, improving the accuracy of signal recognition under complex interference, ensuring the system's efficient response capability under conventional interference, and achieving high-precision signal identification under complex scenarios such as strong interference and mixed interference.

[0069] Specifically, for example, the determination of a secondary valid signal can be performed as follows: extract the peak data from the first detection signal of the target, and determine whether the peak value is within a preset valid value range, whether the acquisition time corresponding to the peak value is within a preset time interval, and whether the data change trend after the peak value meets preset conditions. If the peak value is within the preset valid value range, the acquisition time corresponding to the peak value is within a preset time interval, and the data change trend after the peak value meets preset conditions, then the first detection signal of the target is a valid signal; otherwise, the first detection signal is an invalid signal.

[0070] The preset effective value range, preset time interval, and preset conditions can all be preset or set by system default. For example, the preset effective value range can be an empirical value, such as 300~800 for peak data. Similarly, the preset time interval can be an empirical value; specifically, when collecting data at 5µs per point, the peak value should fall between the 6th and 16th points, and with deviation, the peak value should be within the 20th point to be considered normal. The preset conditions can be set as follows: the values ​​of data after the peak decrease, and if the data after the peak is fitted to obtain a fitted line with time on the horizontal axis and the value on the ADC channel on the vertical axis, the absolute value of the slope of the fitted line is obtained. This absolute value must be less than a set value, which can be preset or set by system default. When the absolute value is less than the set value, it indicates that the radon decay characteristics are slowly decaying.

[0071] The secondary valid signal judgment can be based on the peak data obtained from the target first detection signal, and based on a series of preset rules, such as whether the peak value is within the valid value range, whether the peak acquisition time is reasonable, and whether the data change trend after the peak value conforms to the radon decay characteristics, to determine whether there is invalid feature data in the data set. In specific implementation, if it is determined that there is no invalid feature data, the data set is recorded as a valid data set and used to calculate the radon concentration; otherwise, it is recorded as an invalid data set and can be discarded directly.

[0072] Furthermore, optionally, the above step of performing validity detection based on the target matching result, the first matching value, and the target first detection signal to obtain the target validity detection result can be implemented in the following manner: Determine the target matching value and judgment threshold corresponding to the target matching result; Determine the difference between the target matching value and the judgment threshold to obtain a first difference; Determine the difference between the first matching value and the second threshold to obtain the second difference; A first confidence level is determined based on the first difference and the second difference; The effectiveness of the target is detected based on the first confidence level and the first detection signal of the target, and the effectiveness detection result of the target is obtained.

[0073] The judgment threshold can be preset or set by the system default. If the target matching value is greater than the judgment threshold, the match is considered successful; otherwise, the match is considered unsuccessful. In the specific implementation, different matching results can correspond to different interference types or interference modes, and interference types or interference modes can correspond to different judgment thresholds. Therefore, the corresponding target matching value and judgment threshold can be determined based on the target matching result. Of course, the judgment threshold corresponding to each matching result can also be the same.

[0074] Next, the difference between the target matching value and the judgment threshold can be determined to obtain the first difference. The first difference = target matching value - judgment threshold. The larger the first difference, the greater the confidence of the interference signal (the smaller the confidence of the effective signal). Correspondingly, the difference between the first matching value and the second threshold can be determined to obtain the second difference. The second difference = first matching value - second threshold. The larger the second difference, the greater the confidence of the interference signal (the smaller the confidence of the effective signal). Then, the first confidence level is determined based on the first difference and the second difference. Finally, the effectiveness can be detected based on the first confidence level and the first detection signal of the target to obtain the target effectiveness detection result.

[0075] In this embodiment, the difference between the target matching value and the judgment threshold (i.e., the first difference) is first calculated. The first difference is used to characterize the deviation of the interference feature. Then, the difference between the first matching value and the second threshold (the second difference) is combined. The second difference is used to characterize the ambiguity of the signal. Then, the first confidence level is calculated based on the two differences. The two dimensions of interference feature deviation and signal ambiguity are transformed into a quantifiable confidence index. Then, the effectiveness is detected by combining the first detection signal of the target. In complex electromagnetic interference scenarios, it is possible to accurately distinguish between real radon gas signals and pseudo signals, while reducing the false judgment rate.

[0076] Optionally, the above steps, which involve performing validity detection based on the first confidence level and the first detection signal of the target to obtain the target validity detection result, can be implemented in the following manner: When the first confidence level is greater than the preset confidence level, it is determined that the target validity detection result includes the target first detection signal not being a valid signal; When the first confidence level is less than or equal to the preset confidence level, the first detection signal of the target is subjected to a second valid signal judgment to obtain the target validity detection result.

[0077] The preset reliability can be set in advance or by system default. The value range of the preset reliability is 0 to 1. For example, the value range of the preset reliability is 0.6 to 0.9. Specifically, for example, the preset reliability is 0.6.

[0078] In practice, when the first confidence level is greater than the preset confidence level, it indicates that the electromagnetic auxiliary channel is judged as strong interference. If the target validity detection result, including the first detection signal of the target, is not a valid signal, the pulse signal can be directly rejected and marked as an invalid signal. This eliminates the need to enter the complex waveform analysis process of secondary valid signal judgment, thereby improving signal processing efficiency and reducing the false judgment rate.

[0079] Correspondingly, if the first confidence level is less than or equal to the preset confidence level, and it is determined to be non-interference, or uncertain, a second valid signal judgment can be performed on the first detection signal of the target to obtain the target validity detection result.

[0080] The secondary valid signal judgment can be based on the peak data obtained from the target first detection signal, and a series of preset rules (such as whether the peak value is within the valid value range, whether the peak acquisition time is reasonable, and whether the data change trend after the peak value conforms to the radon decay characteristics) can be used to determine whether there is invalid feature data in the data set. In specific implementation, if it is determined that there is no invalid feature data, the data set is recorded as a valid data set and used to calculate the radon concentration; otherwise, it is recorded as an invalid data set and can be discarded directly.

[0081] In this embodiment, the target first detection signal is first divided into two categories, high confidence and low confidence, by setting a preset confidence level. The high confidence scenario (the first confidence level is greater than the preset confidence level) is directly determined as an invalid signal. For the low confidence scenario (the first confidence level is less than or equal to the preset confidence level), a second valid signal judgment is initiated. This can ensure the accuracy of signal recognition under complex interference and reduce the false judgment rate.

[0082] Optionally, the above step of determining the first confidence level based on the first difference and the second difference can be implemented in the following manner: Determine the first reference confidence level corresponding to the first difference; Determine the second reference confidence level corresponding to the second difference; The first confidence level is determined based on the first reference confidence level and the second reference confidence level.

[0083] In a specific implementation, a first mapping relationship between a preset difference and a confidence level can be stored in advance. Based on this first mapping relationship, a first reference confidence level corresponding to the first difference can be determined. Correspondingly, a second mapping relationship between a preset difference and a confidence level can also be stored in advance. Based on this second mapping relationship, a second reference confidence level corresponding to the second difference can be determined. Furthermore, a first weight corresponding to the first difference and a second weight corresponding to the second difference can be obtained. Based on the first weight, the second weight, the first reference confidence level, and the second reference confidence level, a weighted operation is performed to obtain the first confidence level, i.e., first confidence level = first weight × first reference confidence level + second weight × second reference confidence level.

[0084] The sum of the first weight and the second weight is 1. Both the first weight and the second weight can be preset or set by the system default. The value range of the first weight and the second weight is 0~1. For example, the first weight is 0.4 and the second weight is 0.6.

[0085] The values ​​of the first weight and the second weight can be related to the type of interference corresponding to the first matching value. The values ​​of the first weight and the second weight can be different for different types of interference.

[0086] In this embodiment, the first confidence level is calculated based on the two differences, and the dual dimensions of interference feature deviation and signal ambiguity are transformed into a quantifiable confidence index. Then, the effectiveness can be detected by combining the first detection signal of the target. In complex electromagnetic interference scenarios, it can accurately distinguish between real radon gas signals and pseudo signals, while reducing the false judgment rate.

[0087] Optionally, the following steps may also be included: When only the target matching result that failed to match is included in the plurality of first matching results, the target first detection signal is subjected to a second valid signal judgment to obtain the target validity detection result.

[0088] In practice, if each of the multiple first matching results is less than a threshold, it means that the multiple first matching results only include the target matching results that failed to match. At this time, the target first detection signal can be directly judged as a second valid signal to obtain the target validity detection result. That is, when the electromagnetic sensing channel shows that the environment is quiet, the confidence level of the main channel trigger signal being judged as valid will be higher. This helps to more accurately distinguish between real rare radon decay events and background noise fluctuations in extremely low concentration measurements, thereby improving the detection limit and measurement accuracy.

[0089] For example, if the first feature fails to match the electromagnetic interference features of each sample pair in the preset database, it means that V_current exhibits calm background electromagnetic noise, that is, it does not match the interference pattern in the preset database. In this case, the system tends to consider the main channel signal as a potentially effective signal, and then a second effective signal judgment can be performed on the first detection signal of the target to obtain the target effectiveness detection result.

[0090] Optionally, the following steps may also be included: Determine the target electromagnetic signal strength value of the first electromagnetic signal of the target; When the target electromagnetic signal strength value is less than the preset electromagnetic signal strength value, the step of extracting features from the target first electromagnetic signal to obtain the first feature is performed; When the target electromagnetic signal strength value is greater than or equal to the preset electromagnetic signal strength value, the target first detection signal is determined to be an invalid signal.

[0091] In practice, the preset electromagnetic signal strength value can be set in advance or set by system default.

[0092] Specifically, the target electromagnetic signal strength value of the first electromagnetic signal can be determined. If the target electromagnetic signal strength value is less than a preset electromagnetic signal strength value, it is determined to be a weak interference signal. The step of extracting features from the target first electromagnetic signal to obtain the first feature is then performed. This avoids complex matching and confidence calculation operations for weak signals without substantial interference, thus improving overall detection efficiency. Conversely, if the target electromagnetic signal strength value is greater than or equal to the preset electromagnetic signal strength value, it is directly determined to be an invalid signal (strong interference signal), and the target first detection signal is determined to be invalid. In this case, the signal is usually accompanied by obvious electromagnetic noise, equipment failure, and other characteristics, which can be eliminated without further analysis. This quickly filters out false signals in strong interference scenarios and reduces system resource consumption.

[0093] Please see Figure 5 , Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device includes a processor, a memory, a communication interface, and one or more programs. The one or more programs are stored in the memory and configured to be executed by the processor. In this embodiment, the electronic device is applied to a radon detection and anti-interference identification system. The radon detection and anti-interference identification system includes: a semiconductor radon sensor, a first preprocessing circuit, an electromagnetic sensor, and a second preprocessing circuit. The program includes instructions for performing the following steps: The semiconductor radon gas sensor collects a first detection signal over a preset period of time, and the first detection signal is preprocessed by the first preprocessing circuit to obtain the target first detection signal. The electromagnetic sensor collects the first electromagnetic signal during the preset time period, and the second preprocessing circuit preprocesses the first electromagnetic signal to obtain the target first electromagnetic signal. The first electromagnetic signal of the target is subjected to feature extraction to obtain the first feature; The first feature is matched with the electromagnetic interference features of each sample pair in the preset database to obtain multiple first matching results; the preset database stores multiple sample pairs in advance, and each sample pair is a sample pair between electromagnetic interference features and pseudo signal waveforms; the first matching result includes one of the following: matching successful, matching failed; When the plurality of first matching results includes a successfully matched target matching result, the target pseudo signal waveform corresponding to the target matching result is obtained; The target first detection signal is matched with the target pseudo signal waveform to obtain a first matching value; The effectiveness of the first detection signal of the target is detected based on the first matching value to obtain the target effectiveness detection result.

[0094] The electronic device may include a radon detection and anti-interference identification system, or the electronic device may include a control module of the radon detection and anti-interference identification system. The control module may include a processor, or the control module and the processor may be two independent modules.

[0095] Figure 6 This is a functional unit block diagram of a radon detection anti-interference identification device for complex electromagnetic environments provided in this application embodiment. This radon detection anti-interference identification device 600 is applied to a radon detection anti-interference identification system. The radon detection anti-interference identification system includes: a semiconductor radon sensor, a first preprocessing circuit, an electromagnetic sensor, and a second preprocessing circuit. The radon detection anti-interference identification device 600 includes: a collection unit 610, an extraction unit 620, a matching unit 630, an acquisition unit 640, and a detection unit 650. The acquisition unit 610 is used to acquire a first detection signal for a preset time period through the semiconductor radon gas sensor, and preprocess the first detection signal through the first preprocessing circuit to obtain a target first detection signal; and to acquire a first electromagnetic signal for the preset time period through the electromagnetic sensor, and preprocess the first electromagnetic signal through the second preprocessing circuit to obtain a target first electromagnetic signal. The extraction unit 620 is used to extract features from the target first electromagnetic signal to obtain a first feature; The matching unit 630 is used to match the first feature with the electromagnetic interference features of each sample pair in the preset database to obtain multiple first matching results; the preset database stores multiple sample pairs in advance, and each sample pair is a sample pair between electromagnetic interference features and pseudo signal waveforms; the first matching result includes one of the following: matching successful, matching failed; The acquisition unit 640 is used to acquire the target pseudo signal waveform corresponding to the target matching result when the multiple first matching results include a successfully matched target matching result; The matching unit 630 is further configured to match the target first detection signal with the target pseudo signal waveform to obtain a first matching value; The detection unit 650 is used to perform validity detection on the first detection signal of the target based on the first matching value, and obtain the target validity detection result.

[0096] It is understood that the functions of each program module of the radon gas detection and anti-interference identification device 600 for complex electromagnetic environments in this embodiment can be specifically implemented according to the methods in the above method embodiments. The specific implementation process can be referred to the relevant descriptions in the above method embodiments, and will not be repeated here.

[0097] This application also provides a computer storage medium storing a computer program for electronic data interchange, which causes a computer to perform some or all of the steps of any of the methods described in the above method embodiments.

[0098] 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. This computer program product can be a software installation package.

[0099] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all 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 according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0100] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0101] 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 the units described above 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.

[0102] The units described above 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 according to actual needs.

[0103] 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 functional unit.

[0104] If the aforementioned integrated units are implemented as software functional units and sold or used as independent products, they 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 described in 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.

[0105] 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: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc.

[0106] The embodiments of this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The description of the above embodiments 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 radon gas detection and anti-interference identification method for complex electromagnetic environments, characterized in that, Applications include radon gas detection and anti-interference identification systems; The radon detection and anti-interference identification system includes: a semiconductor radon sensor, a first preprocessing circuit, an electromagnetic sensor, and a second preprocessing circuit; the method includes: The semiconductor radon gas sensor collects a first detection signal over a preset period of time, and the first detection signal is preprocessed by the first preprocessing circuit to obtain the target first detection signal. The electromagnetic sensor collects the first electromagnetic signal during the preset time period, and the second preprocessing circuit preprocesses the first electromagnetic signal to obtain the target first electromagnetic signal. The first electromagnetic signal of the target is subjected to feature extraction to obtain the first feature; The first feature is matched with the electromagnetic interference features of each sample pair in the preset database to obtain multiple first matching results; the preset database stores multiple sample pairs in advance, and each sample pair is a sample pair between electromagnetic interference features and pseudo signal waveforms; the first matching result includes one of the following: matching successful, matching failed; When the plurality of first matching results includes a successfully matched target matching result, the target pseudo signal waveform corresponding to the target matching result is obtained; The target first detection signal is matched with the target pseudo signal waveform to obtain a first matching value; The effectiveness of the first detection signal of the target is detected based on the first matching value to obtain the target effectiveness detection result.

2. The method according to claim 1, characterized in that, The step of performing validity detection on the first detection signal of the target based on the first matching value to obtain the target validity detection result includes: When the first matching value is greater than or equal to the first threshold, the target validity detection result is determined to include the target first detection signal not being a valid signal; When the first matching value is less than or equal to the second threshold, a second valid signal judgment is performed on the first detection signal of the target to obtain the target validity detection result; the second threshold is less than the first threshold. When the first matching value is greater than the second threshold and less than the first threshold, validity detection is performed based on the target matching result, the first matching value and the target first detection signal to obtain the target validity detection result.

3. The method according to claim 2, characterized in that, The step of performing validity detection based on the target matching result, the first matching value, and the target first detection signal to obtain the target validity detection result includes: Determine the target matching value and judgment threshold corresponding to the target matching result; Determine the difference between the target matching value and the judgment threshold to obtain a first difference; Determine the difference between the first matching value and the second threshold to obtain the second difference; A first confidence level is determined based on the first difference and the second difference; The effectiveness of the target is detected based on the first confidence level and the first detection signal of the target, and the effectiveness detection result of the target is obtained.

4. The method according to claim 3, characterized in that, The method further includes: When the first confidence level is greater than the preset confidence level, it is determined that the target validity detection result includes the target first detection signal not being a valid signal; When the first confidence level is less than or equal to the preset confidence level, the first detection signal of the target is subjected to a second valid signal judgment to obtain the target validity detection result.

5. The method according to claim 3 or 4, characterized in that, Determining the first confidence level based on the first difference and the second difference includes: Determine the first reference confidence level corresponding to the first difference; Determine the second reference confidence level corresponding to the second difference; The first confidence level is determined based on the first reference confidence level and the second reference confidence level.

6. The method according to any one of claims 1-4, characterized in that, The method further includes: When only the target matching result that failed to match is included in the plurality of first matching results, the target first detection signal is subjected to a second valid signal judgment to obtain the target validity detection result.

7. The method according to any one of claims 1-4, characterized in that, The method further includes: Determine the target electromagnetic signal strength value of the first electromagnetic signal of the target; When the target electromagnetic signal strength value is less than the preset electromagnetic signal strength value, the step of extracting features from the target first electromagnetic signal to obtain the first feature is performed; When the target electromagnetic signal strength value is greater than or equal to the preset electromagnetic signal strength value, the target first detection signal is determined to be an invalid signal.

8. A radon gas detection and anti-interference identification device for complex electromagnetic environments, characterized in that, Applications include radon gas detection and anti-interference identification systems; The radon detection and anti-interference identification system includes: a semiconductor radon sensor, a first preprocessing circuit, an electromagnetic sensor, and a second preprocessing circuit; the device includes: a collection unit, an extraction unit, a matching unit, an acquisition unit, and a detection unit, wherein, The acquisition unit is configured to acquire a first detection signal for a preset time period through the semiconductor radon gas sensor, and preprocess the first detection signal through the first preprocessing circuit to obtain a target first detection signal; and to acquire a first electromagnetic signal for the preset time period through the electromagnetic sensor, and preprocess the first electromagnetic signal through the second preprocessing circuit to obtain a target first electromagnetic signal. The extraction unit is used to extract features from the target first electromagnetic signal to obtain a first feature; The matching unit is used to match the first feature with the electromagnetic interference features of each sample pair in the preset database to obtain multiple first matching results; the preset database stores multiple sample pairs in advance, and each sample pair is a sample pair between the electromagnetic interference feature and the pseudo signal waveform; the first matching result includes one of the following: matching successful, matching failed; The acquisition unit is used to acquire the target pseudo signal waveform corresponding to the target matching result when the multiple first matching results include a successfully matched target matching result; The matching unit is further configured to match the target first detection signal with the target pseudo signal waveform to obtain a first matching value; The detection unit is used to perform validity detection on the first detection signal of the target based on the first matching value, and obtain the target validity detection result.

9. An electronic device, characterized in that, The electronic device includes a processor and a memory for storing one or more programs and configured to be executed by the processor, the programs including instructions for performing the steps of the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, A computer program for storing electronic data interchange, wherein the computer program causes a computer to perform the method as described in any one of claims 1-7.

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