Intelligent wireless radiation monitoring and real-time early warning system and method

Abstract

The invention discloses an intelligent wireless radiation monitoring and real-time early warning system and method, and relates to the technical field of radiation monitoring, and the method comprises the steps: collecting a radiation level, and carrying out the preprocessing; performing data standardization on the radiation level; and performing real-time early warning according to the radiation level. According to the method, standardized processing and comprehensive analysis of the radiation data are realized, the accuracy and comparability of the data are improved, and data fusion and importance consideration of different areas are ensured, so that more efficient and more reliable radiation monitoring and early warning functions are realized. According to the technical scheme, a comprehensive, efficient and safe method is provided for safety monitoring of the radioactive environment, and the practicability and the technical level of a monitoring system are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the field of radiation monitoring technology, and in particular to an intelligent wireless radiation monitoring and real-time early warning system and method. Background Art

[0002] Radiation monitoring is a key technology to ensure personnel safety and environmental protection in nuclear energy production and other radioactive environments. Existing radiation monitoring systems mainly rely on fixed-mounted monitoring equipment or handheld devices. Although these systems can provide radiation level data, they have the following major limitations:

[0003] Response speed: Traditional radiation monitoring equipment usually requires manual arrangement to read and analyze data, resulting in slow data processing and response speed and inability to respond in real time.

[0004] Data real-time: Many systems are unable to transmit monitoring data in real time and require physical collection or data analysis after a specific point in time, which may lead to delayed response in emergency situations.

[0005] System integration and intelligence level: Existing technologies lack sufficient intelligent processing capabilities and cannot automatically analyze radiation trends or predict potential risks. They also lack advanced data processing functions such as predictive models supported by machine learning or artificial intelligence (AI).

[0006] Early warning capabilities: Traditional equipment does not usually have automatic early warning generation capabilities and relies on operators to identify potential dangerous levels, increasing the risk of human error.

[0007] Equipment mobility and adaptability: Fixed monitoring stations may not cover all critical areas, especially in complex nuclear facility layouts. Handheld devices offer some flexibility, but their monitoring capabilities and usage time are limited.

[0008] These limitations have prompted the need for more advanced, integrated and automated radiation monitoring systems, particularly in nuclear power plants and other high-risk environments. Summary of the invention

[0009] In view of the above-mentioned problems, the present invention is proposed.

[0010] Therefore, the technical problems solved by the present invention are: the slow response problem caused by the reliance on manual operation of traditional radiation monitoring equipment, and the delay in response to emergency situations caused by physical collection or timed data analysis. Therefore, the present invention aims to improve the real-time and accurate collection capability of radiation data and the quality of raw data signals, so that the equipment has the ability to automatically generate early warnings, reduces the reliance on operators to identify danger levels, and reduces the risk of human error.

[0011] In order to solve the above technical problems, the present invention provides the following technical solutions: an intelligent wireless radiation monitoring and real-time early warning system, which comprises the following steps:

[0012] Wireless radiation monitoring equipment.

[0013] As a preferred solution of the intelligent wireless radiation monitoring and real-time early warning system described in the present invention, the wireless radiation monitoring device includes a sensor component, a data transmission module, a data relay channel and a power management.

[0014] As a preferred solution of the intelligent wireless radiation monitoring and real-time early warning system described in the present invention, the sensor component is equipped with a radiation sensor.

[0015] The data transmission module is responsible for data transmission.

[0016] The data relay channel is responsible for enhancing signal coverage.

[0017] The power management is responsible for optimizing battery usage efficiency.

[0018] Another object of the present invention is to provide an intelligent wireless radiation monitoring and real-time early warning method, which can solve the problem of slow speed and low efficiency of existing equipment in processing large amounts of radiation data by integrating advanced wireless communication technology and intelligent data analysis algorithms.

[0019] In order to solve the above technical problems, the present invention provides the following technical solutions: an intelligent wireless radiation monitoring and real-time early warning method, comprising:

[0020] Collect radiation levels and perform preprocessing.

[0021] Data were normalized for radiation levels.

[0022] Provide real-time warning based on radiation levels.

[0023] As a preferred solution of the intelligent wireless radiation monitoring and real-time early warning system described in the present invention, the radiation level collection includes collecting data once per second through a sensor, and the voltage signal output by the sensor represents the radiation dose rate and is marked as raw data.

[0024] The preprocessing includes converting the original signal into a digital value, and performing noise removal and data cleaning.

[0025] The data standardization includes single-scenario standardization and multi-scenario standardization.

[0026] As a preferred solution of the intelligent wireless radiation monitoring and real-time early warning system described in the present invention, the single scene standardization includes calculating the mean value (μ) of historical data for a specific single scene.historical )) and standard deviation ((σ historical )), and then normalized, expressed as,

[0027]

[0028] Among them, D t represents the standardized data value at time t in a single scenario, D raw,t Represents the original data value at time t.

[0029] As a preferred solution of the intelligent wireless radiation monitoring and real-time early warning system described in the present invention, the multi-scenario standardization includes adopting a segmented standardization and weighted average method for cross-regional data, which is expressed as:

[0030]

[0031] [D t1 =w 1 ·D t,zone1 +w 2 ·D t,zone2 ]

[0032] Among them, D t,zone1 represents the standardized data value of region 1, D raw,t,zone1 represents the original data points of region 1, μ zone1 represents the original data mean of region 1, σ zone1 represents the standard deviation of the raw data in region 1, D t,zone2 represents the standardized data value of region 2, D raw,t,zone2 represents the original data points of region 2, μ zone2 represents the original data mean of region 2, σ zone2 represents the standard deviation of the raw data in region 2, D t1 Represents the standardized data value at time t in multiple scenarios.

[0033] As a preferred solution of the intelligent wireless radiation monitoring and real-time warning system described in the present invention, the real-time warning based on the radiation level includes monitoring the radiation level and triggering a warning when a preset threshold is reached.

[0034] A computer device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the above-mentioned intelligent wireless radiation monitoring and real-time early warning method are implemented.

[0035] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above-mentioned intelligent wireless radiation monitoring and real-time early warning method.

[0036] Beneficial effects of the present invention: The present invention realizes the standardized processing and comprehensive analysis of radiation data, which not only improves the accuracy and comparability of the data, but also ensures the data fusion and importance consideration of different regions, thereby realizing more efficient and reliable radiation monitoring and early warning functions. Among them, through the high-frequency sensor acquisition system, the real-time and continuity of radiation data are ensured, and the time delay of data during transmission and processing is avoided. Such a design allows the system to capture any slight changes in radiation levels in real time, so as to respond to potential radiation crises in a timely manner. The implementation of data standardization for single scenes and multiple scenes not only improves the uniformity of data processing, but also takes into account the specific needs under different environmental backgrounds. This method makes the data comparable in different scenes, enhances the universality of the analysis results and the ability to adapt to different environments. Through the above technical solutions, the present invention provides a comprehensive, efficient and safe method for the safe monitoring of radioactive environments, which significantly improves the practicality and technical level of the monitoring system. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0038] Figure 1 An overall framework diagram of an intelligent wireless radiation monitoring and real-time early warning system provided for the first embodiment of the present invention.

[0039] Figure 2 This is an overall flow chart of an intelligent wireless radiation monitoring and real-time early warning method provided for the second embodiment of the present invention. DETAILED DESCRIPTION

[0040] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0041] Example 1, reference Figure 1 , is an embodiment of the present invention, providing an intelligent wireless radiation monitoring and real-time warning system, characterized in that:

[0042] Wireless radiation monitoring equipment.

[0043] The wireless radiation monitoring device includes a sensor component 100 , a data transmission module 200 , a data relay channel 300 and a power management 400 .

[0044] The sensor assembly 100 is equipped with a radiation sensor.

[0045] The data transmission module 200 is responsible for data transmission.

[0046] The data relay channel 300 is responsible for enhancing signal coverage.

[0047] Power management 400 is responsible for optimizing battery usage efficiency.

[0048] Example 2, reference Figure 2 , is an embodiment of the present invention, and provides a method of an intelligent wireless radiation monitoring and real-time early warning system, characterized in that it includes:

[0049] Collect radiation levels and perform preprocessing.

[0050] Data were normalized for radiation levels.

[0051] Provide real-time warning based on radiation levels.

[0052] Collecting radiation levels includes collecting data once a second through a sensor, and the voltage signal output by the sensor represents the radiation dose rate and is marked as raw data;

[0053] Preprocessing includes converting the original signal into digital values ​​and performing denoising and data cleaning;

[0054] Data standardization includes single-scenario standardization and multi-scenario standardization.

[0055] Single scenario standardization includes calculating the mean of historical data (μ historical )) and standard deviation ((σ historical )), and then normalized, expressed as,

[0056]

[0057] Among them, D t represents the standardized data value at time t in a single scenario, D raw,t Represents the original data value at time t.

[0058] Multi-scenario standardization includes, for cross-regional data, using segmented standardization and weighted average methods, expressed as,

[0059]

[0060] [D t1 =w 1·D t,zone1 +w 2 ·D t,zone2 ]

[0061] Among them, D t,zone1 represents the standardized data value of region 1, D raw,t,zone1 represents the original data points of region 1, μ zone1 represents the original data mean of region 1, σ zone1 represents the standard deviation of the raw data in region 1, D t,zone2 represents the standardized data value of region 2, D raw,t,zone2 represents the original data points of region 2, μ zone2 represents the original data mean of region 2, σ zone2 represents the standard deviation of the raw data in region 2, D t1 Represents the standardized data value at time t in multiple scenarios.

[0062] Calculate the mean and standard deviation of historical data for a specific scenario and use these statistical parameters to convert the raw data into standardized data.

[0063] This method takes into account the environmental characteristics of a single scene and ensures the relevance and accuracy of current data to the scene through learning from historical data.

[0064] The method of segmented normalization and weighted average is adopted to conduct a comprehensive analysis considering the characteristics of different regions.

[0065] Multi-scenario analysis enhances the applicability and flexibility of the system, and can provide stable and reliable data processing in different environments.

[0066] Real-time warning based on radiation levels includes monitoring radiation levels and triggering warnings when preset thresholds are reached.

[0067] 1. Get and calculate data values.

[0068] The algorithm continuously monitors radiation data for a period of time. Assuming a time window length is \(N\) (such as the past 10 minutes), the mean and standard deviation of \(N\) real-time radiation data points will be calculated.

[0069] Calculation of average radiation intensity (μ):

[0070]

[0071] Among them, (x i ) is the (i)th radiation intensity value in the sliding window, and (N) is the number of data points in the window.

[0072]

[0073] Based on the statistical characteristics of historical data, the system first calculates a baseline threshold:

[0074] [T 基准 =μ 历史 +k 基准 ×σ 历史 ]

[0075] Among them, (k 基准 ) is the basic threshold adjustment factor, usually based on the initial calibration of the system.

[0076] Adaptive adjustment mechanism

[0077] 1. Real-time data deviation detection and correction

[0078] The system will real-time radiation intensity (μ 实时 ) and the reference threshold (T 基准 ) to compare and calculate the deviation between real-time data and historical data:

[0079] [Δμ=μ 实时 -μ 历史 ]

[0080] When the deviation (Δμ) exceeds a certain preset critical value, the system automatically corrects the threshold adjustment coefficient (k) to dynamically adjust the detection threshold.

[0081] 2. Threshold adjustment formula

[0082] According to the deviation of real-time radiation intensity, the system dynamically adjusts the final detection threshold (T new ):

[0083] [T new =T 基准 +f(Δμ)×k 动态 ]

[0084] Definition of function (f(Δμ)): This function can be a linear or nonlinear function, specifically used to dynamically adjust the threshold according to the deviation (Δμ). It can be designed as:

[0085] [f(Δμ)=α·Δμ]

[0086] Where (α) is the adjustment coefficient, which is used to control the amplification or reduction of the deviation.

[0087] Real-time data deviation detection and correction, dynamic adjustment of detection thresholds, enable the system to adjust response strategies according to actual conditions, and improve the accuracy and adaptability of early warnings.

[0088] Using adjustable linear or non-linear functions, the threshold is dynamically adjusted according to the deviation of real-time radiation intensity, allowing the system to maintain efficient and accurate monitoring capabilities in changing environments.

[0089] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program code.

[0090] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0091] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0092] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0093] Embodiment 3: In this embodiment, in order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments. This embodiment experiments the existing traditional method and the method of this embodiment respectively.

[0094] Wireless radiation monitoring devices are installed in three different areas of the nuclear power plant (around the reactor core, cooling system, and waste disposal area). These devices continuously monitor the radiation levels in their respective areas and transmit the data to the server for processing. In order to ensure that the data is comparable and accurate, we need to standardize the data and give different weights to different areas considering their importance.

[0095] 1. Data Collection

[0096] Each monitoring device continuously collects radiation data in its respective area. The device records the radiation dose rate (i.e. the amount of radiation detected per second) once per second. The data is represented by a voltage signal and converted into a digital value through an analog-to-digital converter (ADC).

[0097] Reactor core peripheral raw data (voltage signal): 3.8V, 3.6V, 3.7V, 3.9V

[0098] Cooling system raw data (voltage signal): 2.4V, 2.5V, 2.3V, 2.4V

[0099] The original data of waste treatment area (voltage signal): 1.2V, 1.3V, 1.1V, 1.2V

[0100] 2. Data Preprocessing

[0101] Preprocessing involves removing noise and outliers from the data. For example, if a data point deviates significantly from the other data points, it can be considered an outlier and removed.

[0102] Reactor core peripheral data: 3.8V, 3.6V, 3.7V, 3.9V

[0103] Cooling system data: 2.4V, 2.5V, 2.3V, 2.4V

[0104] Waste treatment area data: 1.2V, 1.3V, 1.1V, 1.2V

[0105] 3. Data Standardization

[0106] In order to make the data from different regions comparable, we need to standardize the data. Standardization includes the following steps:

[0107] Step 1: Calculate the mean and standard deviation of each region

[0108] Mean ((μ)): The average value of all data points.

[0109] Standard deviation (σ): The average deviation of data points from the mean, which indicates the degree of dispersion of the data.

[0110] Reactor core peripheral data: 3.8V, 3.6V, 3.7V, 3.9V

[0111] Average: (3.8+3.6+3.7+3.9) / 4=3.75V

[0112] Standard Deviation

[0113]

[0114] Cooling system data: 2.4V, 2.5V, 2.3V, 2.4V

[0115] Mean((μ cooling )): (2.4+2.5+2.3+2.4) / 4 = 2.4V standard deviation

[0116]

[0117] Waste treatment area data: 1.2V, 1.3V, 1.1V, 1.2V average ((μ waste )): (1.2+1.3+1.1+1.2) / 4=1.2V standard deviation

[0118]

[0119] Step 2: Standardize the formula

[0120] Use the normalization formula to convert each data point to a normalized value:

[0121]

[0122] Normalized data around the reactor core:

[0123]

[0124] Standardized data of cooling system:

[0125]

[0126] Standardized data of waste disposal area:

[0127]

[0128] 4. Multi-scenario data processing and weighted averaging

[0129] In order to integrate data from different areas and consider the importance of each area, we use the weighted average method. Assume that the importance weights of the reactor core area, cooling system, and waste treatment area are (w 1 =0.5)、(w 2 =0.3)、(w 3 =0.2).

[0130] Reactor core surrounding weight: (w 1 =0.5)

[0131] Cooling system weight: (w 2 =0.3)

[0132] Waste treatment area weight: (w 3 =0.2)

[0133] Steps: Weighted Average Formula

[0134] Combine the normalized data and weights to calculate the comprehensive normalized data:

[0135] [D combined =w 1 ·D core +w 2 ·D cooling +w 3 ·D waste ]

[0136] Comprehensive data:

[0137] Data point 1: (0.5 0.45 + 0.3 0 + 0.2 0 = 0.225)

[0138] Data Point 2:

[0139] (0.5·-1.36+0.3·1.25+0.2·1.25≈-0.68+0.375+0.25

[0140] =-0.055)

[0141] Data point 3: (0.5·-0.45+0.3·-1.25+0.2·-1.25

[0142] ≈-0.225-0.375-0.25=-0.85)

[0143] Data point 4: (0.5 1.36 + 0.3 0 + 0.2 0 = 0.68)

[0144] 5. Data compression and transmission

[0145] In order to optimize data transmission efficiency, the standardized data can be compressed. The data is compressed into a smaller format and encrypted before transmission to ensure data security.

[0146] 6. Data decompression

[0147] After receiving the data, the server decodes and restores the original standardized data.

[0148] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. An intelligent wireless radiation monitoring and real-time early warning system, characterized in that: include: Wireless radiation monitoring equipment.

2. The intelligent wireless radiation monitoring and real-time early warning system according to claim 1, characterized in that: The wireless radiation monitoring device comprises a sensor component (100), a data transmission module (200), a data relay channel (300) and a power management (400).

3. The intelligent wireless radiation monitoring and real-time early warning system according to claim 2, characterized in that: The sensor assembly (100) is equipped with a radiation sensor; The data transmission module (200) is responsible for data transmission; The data relay channel (300) is responsible for enhancing signal coverage; The power management (400) is responsible for optimizing battery usage efficiency.

4. A method using an intelligent wireless radiation monitoring and real-time early warning system as claimed in any one of claims 1 to 3, characterized in that: include: Collect radiation levels and perform pre-processing; Data normalization for radiation levels; Provide real-time warning based on radiation levels.

5. The intelligent wireless radiation monitoring and real-time early warning method according to claim 4, characterized in that: The collecting of radiation levels includes collecting data once per second through a sensor, wherein a voltage signal output by the sensor represents a radiation dose rate and is marked as raw data; The preprocessing includes converting the original signal into a digital value, and performing denoising and data cleaning; The data standardization includes single-scenario standardization and multi-scenario standardization.

6. The intelligent wireless radiation monitoring and real-time early warning method according to claim 5, characterized in that: The single scene standardization includes calculating the mean of historical data (μ historical )) and standard deviation ((σ historical )), and then normalized, expressed as, Among them, D t represents the standardized data value at time t in a single scenario, D raw,t Represents the original data value at time t.

7. The intelligent wireless radiation monitoring and real-time early warning method according to claim 6, characterized in that: The multi-scenario standardization includes, for cross-regional data, using segmented standardization and weighted average methods, expressed as: [D t1 =w1·D t,zone1 +w2·D t,zone2 ] Among them, D t,zone1 represents the standardized data value of region 1, D raw,t,zone1 represents the original data points of region 1, μ zone1 represents the original data mean of region 1, σ zone1 represents the standard deviation of the raw data in region 1, D t,zone2 represents the standardized data value of region 2, D raw,t,zone2 represents the original data points of region 2, μ zone2 represents the original data mean of region 2, σ zone2 represents the standard deviation of the raw data in region 2, D t1 Represents the standardized data value at time t in multiple scenarios.

8. The intelligent wireless radiation monitoring and real-time early warning method according to claim 7, characterized in that: The real-time warning according to the radiation level includes: Monitors radiation levels and triggers an alert when preset thresholds are reached.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of an intelligent wireless radiation monitoring and real-time early warning method described in any one of claims 4 to 8 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of an intelligent wireless radiation monitoring and real-time early warning method as described in any one of claims 4 to 8 are implemented.

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