Intelligent analysis system for nuclear radiation data

Abstract

The application relates to the technical field of nuclear radiation monitoring, in particular to an intelligent analysis system for nuclear radiation data, which comprises an acquisition planning module, a radiation intensity monitoring module, a sensor adjusting module, a radiation source positioning module and a radiation data processing module.In the application, the sensitivity and sampling frequency of the nuclear radiation sensor are intelligently adjusted by combining factors such as water flow rate and temperature, so as to cope with different environmental conditions, ensure the stability and accuracy of the radiation data, provide high-quality radiation monitoring data in a complex marine environment, provide strong support for accurate evaluation of the nuclear radiation source and analysis of the radiation amount of marine products, and effectively overcome the limitations of traditional static monitoring technology through real-time cooperation of the sensor and the unmanned ship, improve the response speed and accuracy of data acquisition through continuous tracking and optimization of the sensor configuration, and quickly respond to nuclear pollution events and update the position of the radiation source in real time.

Description

Technical Field

[0001] This invention relates to the field of nuclear radiation monitoring technology, and in particular to an intelligent analysis system for nuclear radiation data. Background Technology

[0002] The application of nuclear radiation monitoring technology in the marine environment mainly involves monitoring and analyzing radioactive pollution in the ocean, especially detecting and assessing the radiation levels of seafood. Marine nuclear radiation monitoring technology plays an important role in situations involving nuclear power plants, marine nuclear accidents, radioactive material leaks, and natural radioactive pollution. It can ensure the safety of seafood and provide scientific support for the long-term protection of the marine environment.

[0003] Among them, the intelligent analysis system for nuclear radiation data focuses on the precise analysis of radiation levels in seafood. By acquiring nuclear radiation data in the marine environment in real time, it pays special attention to the content of radioactive materials in seafood. The system performs rapid analysis of radiation data to ensure the safety and harmlessness of seafood. It is widely used in marine environmental safety monitoring, especially after a nuclear contamination incident, and can provide rapid and accurate radiation detection, providing strong support for marine food safety, public health protection, and environmental governance decisions.

[0004] Due to the instability of the marine environment, existing technologies cannot adjust sensor performance in real time, which limits the accuracy and timeliness of data acquisition. After a nuclear contamination incident, it is impossible to provide rapid and accurate radiation data in a short period of time, affecting emergency response and assessment of marine product safety. In addition, existing technologies cannot optimize sensor sensitivity and detection range in real time, resulting in data bias, affecting the accuracy of radiation source location and environmental correction. This makes the response speed of marine environmental monitoring slow, unable to effectively deal with sudden nuclear radiation contamination spread, and thus affecting decision-making efficiency. Summary of the Invention

[0005] To address the limitations of existing technologies in real-time sensor performance adjustment due to the instability of the marine environment, which restricts the accuracy and timeliness of data acquisition, and consequently hinders the provision of rapid and accurate radiation data after a nuclear contamination incident, impacting emergency response and marine product safety assessments, this invention provides an intelligent analysis system for nuclear radiation data. The technical solution is as follows:

[0006] On the one hand, an intelligent analysis system for nuclear radiation data is provided, including:

[0007] The data acquisition and planning module obtains the current hydrodynamic data of the ocean area. Through the data collected by the nuclear radiation sensor on the unmanned vessel, it analyzes the relationship between the rate of change of radiation intensity and the flow state, monitors the changes of the target radiation source in real time, and dynamically adjusts the path of the unmanned vessel to obtain the path optimization configuration.

[0008] The radiation intensity monitoring module optimizes the configuration based on the path, analyzes the collected radiation intensity and frequency information, judges the radiation intensity fluctuations based on the current ocean current speed and temperature changes in the area, corrects the original data, and generates radiation intensity change data.

[0009] Based on the radiation intensity change data, the sensor adjustment module analyzes the current radiation intensity fluctuation range, combines water depth, ocean current speed and temperature changes to determine the impact of environmental factors on the sensor, automatically adjusts the sensor sensitivity, and updates its sampling frequency to obtain the sensor sensitivity adjustment configuration.

[0010] The radiation source positioning module adjusts its configuration based on the sensor sensitivity, combines real-time geographical location, ocean current velocity and temperature information, and calculates the radiation source location through waveform analysis, continuously updates the radiation source's position coordinates, and obtains the radiation source location information.

[0011] On the other hand, the path optimization configuration includes the optimal path, optimal travel speed, and optimal target area; the radiation intensity change data includes the radiation intensity fluctuation range, the dynamic change trend of the radiation source, and the data correction results; and the sensor sensitivity adjustment configuration includes the sensitivity adjustment value, the detection range optimization result, and the sampling frequency update result.

[0012] On the other hand, the acquisition planning module includes:

[0013] The fluid state acquisition submodule acquires fluid dynamics data of the current ocean area. Through the nuclear radiation sensor on board the unmanned vessel, it monitors the flow state of ocean fluids, collects information on water velocity and direction, and calculates the changes in velocity and direction within the area to obtain flow state data.

[0014] The radiation monitoring and analysis submodule analyzes the changes in radiation intensity based on the flow state data, calculates the rate of change of radiation intensity over time, compares it with the ocean flow state, and screens out key areas of radiation intensity change to obtain radiation change data.

[0015] The path optimization and adjustment submodule analyzes the impact of the radiation change data on the path of the unmanned vessel, adjusts the direction and speed of the unmanned vessel, optimizes the path planning, and obtains the path optimization configuration.

[0016] On the other hand, the radiation intensity monitoring module includes:

[0017] The radiation data analysis submodule, based on the optimized configuration of the path, analyzes the collected radiation intensity and frequency information, combines it with the current ocean current velocity and temperature change data, filters out key data points of fluctuation, performs preliminary analysis on them, evaluates the trend of radiation intensity fluctuation, and obtains radiation fluctuation data.

[0018] The trend analysis submodule analyzes the dynamic trend of the radiation source based on the radiation fluctuation data, combines the radiation intensity data of multiple time periods with environmental changes, determines the relationship between radiation fluctuation and flow velocity changes, determines the potential trend of the radiation source, and generates the dynamic trend of the radiation source.

[0019] The data correction submodule corrects the original radiation data based on the dynamic trend of the radiation source, removes abnormal data points that do not conform to the trend, and combines environmental factors to correct the data to obtain radiation intensity change data.

[0020] On the other hand, the sensor adjustment module includes:

[0021] The radiation fluctuation analysis submodule analyzes the current radiation intensity fluctuation range based on the radiation intensity change data, combines the changes in water depth, ocean current velocity and temperature, compares the radiation data for each time period, evaluates the changing trend of the radiation fluctuation range, and obtains the radiation range data.

[0022] The environmental factors assessment submodule analyzes the impact of environmental factors on sensor detection based on the radiation range data, assesses the degree of interference of environmental fluctuations on radiation intensity, determines the sensor parameters that need to be corrected, and obtains the environmental impact assessment log.

[0023] The sensitivity adjustment submodule automatically adjusts the sensor sensitivity based on the environmental impact assessment log, optimizes the sensor's detection range and sampling frequency, matches the current acquisition conditions, and obtains the sensor sensitivity adjustment configuration.

[0024] On the other hand, the formula based on radiation range data is as follows:

[0025]

[0026] The environmental impact assessment results are calculated to obtain the corrected radiation intensity I. adj , where R i R represents the radiation value measured in the i-th measurement. nom T represents the calibrated radiation value. i T represents the temperature value measured in the i-th measurement. nom Represents the calibrated temperature value, S i S represents the sensor reading of the i-th measurement. nomα represents the calibrated sensor reading, β represents the influence factor of temperature on radiation intensity, n represents the influence factor of sensor reading on radiation intensity, and n represents the number of measurements.

[0027] On the other hand, the radiation source localization module includes:

[0028] The signal difference analysis submodule adjusts the configuration according to the sensor sensitivity, acquires data collected by the nuclear radiation sensor that moves with the unmanned vessel, and calculates the difference between the acquired signal and the sensor by combining real-time geographical location, ocean current speed and temperature information, and analyzes the relationship between signal strength and sensor position, screens potential signal deviations, and obtains signal difference data.

[0029] The radiation source estimation submodule estimates the location of the radiation source based on the signal difference data through waveform analysis, and makes dynamic corrections for environmental influences, continuously updating the location coordinates of the radiation source to obtain the radiation source location information.

[0030] On the other hand, the method of calculating the location of the radiation source through waveform analysis uses the following formula:

[0031]

[0032] Obtain the radiation source location information LF and continuously update the radiation source location coordinates, where n L DL represents the number of waveform data points. z DL represents the signal strength difference at the z-th time point. z-1 The table shows the signal strength difference value at time point z-1, ΔTL. z TL represents the change in time interval between the z-th data point and the previous point. z The delay parameter represents the time point z.

[0033] On the other hand, the system also includes:

[0034] The radiation data processing module, based on the location information of the radiation source, removes abnormal data, corrects valid data, and analyzes the changes in radiation concentration distribution in different areas to obtain radiation concentration analysis results.

[0035] The radiation concentration analysis results include a radiation concentration distribution map and corrected radiation concentration data.

[0036] On the other hand, the radiation data processing module includes:

[0037] The radiation correction submodule analyzes abnormal fluctuations in the data based on the radiation source location information, removes abnormal data, and corrects deviations in the radiation intensity data to obtain radiation correction data.

[0038] The concentration analysis submodule analyzes the changes in radiation concentration distribution in different regions based on the radiation correction data, and calculates the radiation concentration in each region by combining geographical location information, thus obtaining the radiation concentration analysis results.

[0039] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0040] By combining factors such as water flow velocity and temperature, the sensitivity and sampling frequency of the nuclear radiation sensor are intelligently adjusted to cope with different environmental conditions, ensuring the stability and accuracy of radiation data. It can provide high-quality radiation monitoring data in complex marine environments, providing strong support for the accurate assessment of nuclear radiation sources and the analysis of radiation levels in marine products. The real-time collaboration between the sensor and the unmanned vessel effectively overcomes the limitations of traditional static monitoring technology. Through continuous tracking and optimization of sensor configuration, the response speed and accuracy of data acquisition are improved, enabling rapid response to nuclear contamination events and real-time updates of radiation source locations, thereby improving the responsiveness to decisions on marine food safety and environmental protection. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used 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 those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 This is a schematic diagram of the system of the present invention;

[0043] Figure 2 This is a schematic diagram of the system framework of the present invention;

[0044] Figure 3 This is a flowchart of the data acquisition and planning module of the present invention;

[0045] Figure 4 This is a flowchart of the radiation intensity monitoring module of the present invention;

[0046] Figure 5 This is a flowchart of the sensor adjustment module of the present invention;

[0047] Figure 6 This is a flowchart of the radiation source positioning module of the present invention;

[0048] Figure 7 This is a flowchart of the radiation data processing module of the present invention. Detailed Implementation

[0049] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0050] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0051] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, their intended meanings are consistent. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, their intended meanings are consistent.

[0052] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0053] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0054] This invention provides an intelligent analysis system for nuclear radiation data, such as... Figure 1 As shown, the system includes:

[0055] The data acquisition and planning module obtains the current hydrodynamic data of the ocean area. Through the data collected by the nuclear radiation sensor on the unmanned vessel, it analyzes the relationship between the rate of change of radiation intensity and the flow state, monitors the changes of the target radiation source in real time, dynamically adjusts the path of the unmanned vessel, determines the optimal direction and speed, and obtains the path optimization configuration.

[0056] The radiation intensity monitoring module analyzes the collected radiation intensity and frequency information based on path optimization configuration, analyzes the dynamic change trend of the radiation source according to the current ocean current velocity and temperature changes in the region, judges the radiation intensity fluctuation, corrects the original data, and generates radiation intensity change data.

[0057] The sensor adjustment module analyzes the current radiation intensity fluctuation range based on radiation intensity change data, and combines water depth, ocean current velocity and temperature changes to determine the impact of environmental factors on the sensor. It then automatically adjusts the sensor sensitivity, optimizes the detection range, and updates its sampling frequency to obtain the sensor sensitivity adjustment configuration.

[0058] The radiation source location module adjusts its configuration based on sensor sensitivity, acquires data collected by nuclear radiation sensors moving with the unmanned vessel, and calculates the difference between the acquired signal and the sensor data by combining real-time geographical location, ocean current velocity and temperature information. It then uses waveform analysis to estimate the radiation source location and makes dynamic corrections based on environmental impacts, continuously updating the radiation source's location coordinates to obtain radiation source location information.

[0059] The radiation data processing module removes outlier data based on the location information of the radiation source, corrects valid data, and analyzes the changes in radiation concentration distribution in different areas to obtain radiation concentration analysis results.

[0060] The path optimization configuration includes the optimal path, optimal travel speed, and optimal target area. The radiation intensity change data includes the radiation intensity fluctuation range, the dynamic change trend of the radiation source, and the data correction results. The sensor sensitivity adjustment configuration includes the sensitivity adjustment value, the detection range optimization results, and the sampling frequency update results. The radiation concentration analysis results include the radiation concentration distribution map and the corrected radiation concentration data.

[0061] like Figure 2 and Figure 3 As shown, the data acquisition and planning module includes:

[0062] The fluid state acquisition submodule acquires fluid dynamics data of the current ocean area. Through the nuclear radiation sensor on board the unmanned vessel, it monitors the flow state of ocean fluids, collects information on water velocity and direction, and calculates the changes in velocity and direction within the area to obtain flow state data.

[0063] By using nuclear radiation sensors mounted on an unmanned surface vessel (USV), hydrodynamic data of the ocean region is acquired. First, the sensors obtain fluid state data, including flow velocity and direction. Flow velocity is measured by detecting changes in water velocity at different locations. After data acquisition, differences in data from different time points are calculated to determine the velocity variation. Flow direction is analyzed by the sensors, and the data is processed using an ocean current model to obtain the flow direction angle. Further calculations are then performed to determine the trend of flow direction changes. If the USV passes through a certain sea area and the nuclear radiation sensors simultaneously monitor both current velocity and direction, and if the velocity is 0.5 m / s and the flow direction angle is 45 degrees at a certain moment, and the velocity is measured to be 0.7 m / s and the flow direction angle has changed to 48 degrees 10 minutes later, this data will be used to further analyze the changes in water flow. After data processing, the changes in water flow state within the area can be accurately reflected, providing accurate basic data for subsequent radiation monitoring and analysis, thus determining the changes in velocity and direction within the area and forming flow state data.

[0064] The radiation monitoring and analysis submodule analyzes changes in radiation intensity based on flow state data, calculates the rate of change of radiation intensity over time, compares it with ocean flow state, screens key areas of radiation intensity change, and obtains radiation change data.

[0065] First, radiation intensity data is collected. Nuclear radiation sensors monitor and record radiation intensity data in real time. After combining the data with flow state data, the analysis phase begins. The analysis process includes calculating the correlation between radiation intensity and water flow state data. By calculating the rate of change of radiation intensity over time, periods of significant change are identified. At this point, the data is filtered according to certain radiation change thresholds. For example, when the rate of change of radiation intensity exceeds 0.02 μSv / h, it is marked as important data. The changes in ocean currents are then compared to check whether the changes in radiation intensity are directly related to changes in flow velocity and direction. For instance, if the radiation intensity rate in an ocean area is 0.025 μSv / h during a certain period, and the water flow velocity increases by 0.2 m / s during that period, this area is considered to have significant radiation changes. Through this filtering process, key areas of radiation intensity change are identified, forming radiation change data.

[0066] The path optimization and adjustment submodule analyzes the impact of radiation change data on the path of the unmanned vessel, adjusts the direction and speed of the unmanned vessel, optimizes the path planning, and obtains the path optimization configuration.

[0067] First, areas with significant radiation changes are marked. By analyzing their impact on the unmanned surface vessel's (USV) path, it is determined whether the navigation path needs to be adjusted. During the adjustment process, by calculating the distance between the radiation intensity and the USV's current position, and combining this with the direction and velocity of the water flow, adjustment rules are set. For example, when the radiation intensity is higher than a certain threshold and the water flow velocity is high, the navigation path is automatically optimized, and the USV's navigation direction and speed are changed. For instance, when the USV approaches an area with a radiation intensity of 0.03 μSv / h and a high flow velocity of 1.5 m / s, it is determined that the navigation direction needs to be adjusted so that the USV can directly enter the area. During the path adjustment process, the USV system compares the differences between the adjusted path and the original path, and optimizes the best navigation path configuration based on the flow state and radiation data to ensure that the USV accurately enters the sea area with strong nuclear radiation.

[0068] like Figure 2 and Figure 4 As shown, the radiation intensity monitoring module includes:

[0069] The radiation data analysis submodule analyzes the collected radiation intensity and frequency information based on path optimization configuration, combines it with current ocean current velocity and temperature change data, filters key data points of fluctuation, performs preliminary analysis on them, evaluates the trend of radiation intensity fluctuation, and obtains radiation fluctuation data.

[0070] First, data points with large fluctuations are extracted from the collected radiation intensity data. These data points are then combined with ocean current and temperature change data to further filter out key fluctuation data points. In the specific operation, time series analysis is performed on the collected radiation intensity values. Combined with current and temperature data at each moment, the correlation coefficients between radiation intensity and current / temperature data within each time period are calculated to identify fluctuations with significant impact. For example, if the radiation intensity is 0.04 μSv / h, the current / temperature is 0.5 m / s, and the temperature is 18℃ in a certain time period, the data is compared with data from adjacent time periods. If the difference exceeds a set threshold, such as a change in current / temperature exceeding 0.1 m / s or a change in temperature exceeding 1℃, then the data point is marked as a key fluctuation data point. For key data points, the submodule will conduct preliminary analysis to assess their radiation fluctuation trend, further analyze whether the trend of the data point's change conforms to the expected pattern, and output radiation fluctuation data.

[0071] The trend analysis submodule analyzes the dynamic trend of radiation sources based on radiation fluctuation data. It combines radiation intensity data from multiple time periods with environmental changes to determine the relationship between radiation fluctuations and flow velocity changes, identify the potential trend of radiation sources, and generate dynamic trends of radiation sources.

[0072] Radiation intensity data collected over multiple time periods are processed to calculate the average radiation intensity for each time period and its relationship with environmental factors such as flow velocity and temperature. Correlation analysis is used to determine whether radiation fluctuations are significantly correlated with flow velocity changes. For example, assuming a radiation intensity of 0.05 μSv / h and a flow velocity of 0.7 m / s in one time period, and a radiation intensity of 0.03 μSv / h and a flow velocity of 1.2 m / s in another time period, the correlation coefficient between these two time periods is calculated. If the correlation coefficient is greater than 0.8, it indicates that radiation fluctuations are highly correlated with flow velocity changes. Subsequently, by comparing data from multiple time periods segment by segment, the dynamic trend of the radiation source is analyzed. If, in a certain time period, the change in radiation intensity is consistent with the change in flow velocity, and other environmental factors remain stable, then it can be inferred that the potential trend of the radiation source is either an increase or decrease in fluctuations. Combined with the flow velocity change trend, the dynamic trend of the radiation source is generated.

[0073] The data correction submodule corrects the original radiation data based on the dynamic trend of the radiation source, removes abnormal data points that do not conform to the trend, and combines environmental factors to correct the data to obtain radiation intensity change data.

[0074] By comparing the original data with the dynamic trend of the radiation source, outlier data points that clearly do not conform to the trend are removed. For example, if the radiation intensity fluctuates significantly during a certain period but the flow velocity does not change much and the temperature does not change significantly, this data point will be identified as an outlier. Then, the remaining data will be corrected in combination with environmental factors (such as temperature, flow velocity, etc.). Specifically, correction coefficients are introduced to weight the data. For example, if the coefficient of flow velocity affecting radiation intensity is set to 0.5 and the coefficient of temperature affecting radiation intensity is set to 0.2, then according to the formula: Corrected radiation intensity = Original radiation intensity + (Flow velocity × 0.5) + (Temperature × 0.2), assuming the original radiation intensity is 0.03 μSv / h, the flow velocity is 1.0 m / s, and the temperature is 20℃, then the corrected radiation intensity is: Corrected radiation intensity = 0.03 + (1.0 × 0.5) + (20 × 0.2) = 4.53 μSv / h. Finally, the radiation intensity change data is output through the corrected data for further analysis or as a basis for path optimization.

[0075] like Figure 2 and Figure 5 As shown, the sensor adjustment module includes:

[0076] The radiation fluctuation analysis submodule analyzes the current radiation intensity fluctuation range based on radiation intensity change data, combines water depth, ocean current velocity and temperature changes, compares radiation data for each time period, evaluates the changing trend of radiation fluctuation range, and obtains radiation range data.

[0077] The system performs time-series analysis on the collected radiation intensity data to determine the fluctuation range of each time period and identify the difference between the minimum and maximum values, thereby defining the fluctuation range. Based on this, it combines data on water depth, flow velocity, and temperature changes to calculate the correlation between these data and the radiation intensity fluctuations. For example, assuming that the radiation intensity changes from 0.05 μSv / h to 0.10 μSv / h, the flow velocity is 1.2 m / s, the water depth is 50 meters, and the temperature is 20℃ during a certain period, the system will calculate the correlation between the radiation intensity and the flow velocity and temperature during that period. By comparing the radiation fluctuations across multiple time periods, the system determines whether the current fluctuation exceeds the normal range. If the fluctuation range exceeds a predetermined threshold during a certain period, such as exceeding 0.05 μSv / h, the system will mark that period as an abnormal fluctuation and conduct further analysis. The output radiation range data will reflect the fluctuation trend of the radiation intensity.

[0078] The environmental factors assessment submodule analyzes the impact of environmental factors on sensor detection based on radiation range data, assesses the degree of interference of environmental fluctuations on radiation intensity, determines the sensor parameters that need to be corrected, and obtains the environmental impact assessment log.

[0079] Based on radiation range data, the formula is used:

[0080]

[0081] The environmental impact assessment results are calculated to obtain the corrected radiation intensity I. adj , where R i R represents the radiation value measured in the i-th measurement. nom T represents the calibrated radiation value. i T represents the temperature value measured in the i-th measurement. nom Represents the calibrated temperature value, S i S represents the sensor reading of the i-th measurement. nom The value represents the calibrated sensor reading, α represents the influence factor of temperature on radiation intensity, β represents the influence factor of sensor reading on radiation intensity, and n represents the number of measurements.

[0082] Two measurements were performed, and the following data were obtained:

[0083] Measurement 1: R1 = 100 W / m 2 T1 = 25℃;

[0084] Measurement 2: R2 = 105 W / m 2 T2 = 26℃;

[0085] R nom and T nom Calibration was performed using a standard radiation source and temperature control equipment, yielding: R nom =100W / m 2 T nom =25℃, S i and S nom Record the sensor output value to obtain:

[0086] Measurement 1: S1 = 98 units;

[0087] Measurement 2: S2 = 100 units;

[0088] S nom =98 units;

[0089] α and β were obtained from the regression analysis data:

[0090] α=0.05W / m 2 / ℃;

[0091] β = 1.02 units / W / m 2 ;

[0092] Calculate the sum of absolute deviations:

[0093]

[0094] Calculate the sum of squares of temperature deviations:

[0095]

[0096] Calculate the sum of sensor reading deviations:

[0097]

[0098] Substitute into the formula to calculate the corrected radiation intensity:

[0099]

[0100] The results indicate that, after considering the effects of temperature and sensor readings, the actual measured radiation intensity should be 2.48 W / m². 2 .

[0101] The sensitivity adjustment submodule automatically adjusts the sensor sensitivity based on the environmental impact assessment log, optimizes the sensor's detection range and sampling frequency, matches the current acquisition conditions, and obtains the sensor sensitivity adjustment configuration.

[0102] By analyzing data from the environmental impact assessment log, we can identify which environmental factors have the greatest impact on radiation intensity and determine the sensor parameters that need to be corrected. For example, when it is found that temperature and flow rate have a significant impact on radiation intensity, the sensor sensitivity needs to be adjusted to ensure that it can still accurately detect radiation changes under environmental conditions. Suppose the system detects that the radiation intensity fluctuates greatly in a certain environment (e.g., exceeding 0.05 μSv / h), based on the environmental impact assessment log, the sensor sensitivity will be automatically adjusted. The sensitivity coefficient will be adjusted to 1.2, and the sampling frequency will be increased to ensure that data can still be collected accurately in environments with large fluctuations. Ultimately, the adjusted sensor sensitivity configuration will ensure that the sensor can provide accurate and stable measurement results under different environmental conditions, optimize the detection range and sampling frequency, and adapt to the current acquisition conditions.

[0103] like Figure 2 and Figure 6 As shown, the radiation source localization module includes:

[0104] The signal difference analysis submodule adjusts the configuration according to the sensor sensitivity, acquires data collected by the nuclear radiation sensor that moves with the unmanned vessel, and calculates the difference between the acquired signal and the sensor by combining real-time geographical location, ocean current velocity and temperature information, and analyzes the relationship between signal strength and sensor position, screens potential signal deviations, and obtains signal difference data.

[0105] First, based on the real-time geographic location information of the unmanned vessel, the current position of the sensor is determined. Then, by calculating the difference between the collected radiation signal intensity and the sensor's preset sensitivity, the trend of signal intensity change with position is analyzed, and time-series data is compared. For example, if the signal intensity collected by the sensor at a certain moment is 0.05 μSv / h, and compared with the signal intensity of 0.04 μSv / h collected at a previous position (assuming it is 50 meters away from the original position), this 0.01 μSv / h change reflects the signal deviation. Subsequently, combined with real-time ocean current velocity and temperature data, it is further analyzed whether environmental factors have affected the signal. For example, assuming the current ocean current velocity is 1.0 m / s and the temperature is 22℃, the increase in current velocity leads to greater signal fluctuation, and the temperature change will have a certain impact on the sensor's response. Based on the parameters, data points with large signal differences are screened out and marked as potential signal deviations, generating signal difference data.

[0106] The radiation source estimation submodule estimates the location of the radiation source based on signal difference data and waveform analysis, and makes dynamic corrections for environmental influences, continuously updating the location coordinates of the radiation source to obtain the radiation source location information.

[0107] The location of the radiation source is deduced through waveform analysis using the following formula:

[0108]

[0109] Obtain the radiation source location information LF and continuously update the radiation source location coordinates, where n L DL represents the number of waveform data points. z DL represents the signal strength difference at the z-th time point. z-1 The table shows the signal strength difference value at time point z-1, ΔTL. z TL represents the change in time interval between the z-th data point and the previous point. z The delay parameter represents the z-th time point;

[0110] The values ​​for the three data points are as follows:

[0111] n L =3;

[0112] DL1=2.0, DL2=2.5, DL3=3.0;

[0113] ΔTL1=0.1, ΔTL2=0.2, ΔTL3=0.15;

[0114] TL1=1.5, TL2=1.6, TL3=1.7;

[0115] Part 1: The average value of the signal strength difference, for z = 1:

[0116] |2.0-0|+0.1=2.0+0.1=2.1;

[0117] For z = 2:

[0118] |2.5-2.0|+0.2=0.5+0.2=0.7;

[0119] For z = 3:

[0120] |3.0-2.5|+0.15=0.5+0.15=0.65;

[0121] sum:

[0122] 2.1 + 0.7 + 0.65 = 3.45;

[0123] average value:

[0124]

[0125] Part Two: The ratio of the square root of the product of signal strength and time delay parameter, for z = 1:

[0126] 2.0 × 1.5 = 3.0;

[0127] For z = 2:

[0128] 2.5 × 1.6 = 4.0;

[0129] For z = 3:

[0130] 3.0 × 1.7 = 5.1;

[0131] sum:

[0132] 3.0 + 4.0 + 5.1 = 12.1;

[0133] Square root:

[0134]

[0135] Total signal strength:

[0136] |2.0|+|2.5|+|3.0|=7.5;

[0137] ratio:

[0138]

[0139] Substitute the calculation results into the formula:

[0140] LF = 1.15 + 0.464 = 1.614;

[0141] LF = 1.614 represents the spatial location information of the radiation source. After comprehensive calculation of parameters such as signal strength change, time interval, and time delay, the location information of the radiation source is obtained. The result is a numerical location of the radiation source, representing the relative position information of the source at the measurement time.

[0142] like Figure 2 and Figure 7 As shown, the radiation data processing module includes:

[0143] The radiation correction submodule analyzes abnormal fluctuations in the data based on the location information of the radiation source, removes abnormal data, and corrects deviations in the radiation intensity data to obtain radiation correction data.

[0144] First, by integrating real-time location information of the radiation source, the location of the radiation source is determined. Using this as a reference, fluctuations in the radiation intensity data are further analyzed. If significant abnormal fluctuations in radiation intensity occur within a certain time period, the system will first filter, identify, and remove abnormal data points that do not meet expectations. For example, assuming the radiation intensity is 0.15 μSv / h in a certain time period, while the radiation intensity in adjacent time periods is between 0.03 μSv / h and 0.05 μSv / h, the 0.15 μSv / h value will be marked as an abnormal data point and removed. After removing outlier data, the system corrects the remaining radiation intensity data. This correction process compares the signal strength at different locations and times, calculates the deviation, and compensates by adjusting the sensor sensitivity to ensure that the final radiation intensity data is more accurate. For example, if the sensor sensitivity is low at a certain time, resulting in lower collected radiation intensity data, the system will correct the deviation based on the actual measured sensitivity information. The adjusted data value is corrected from 0.04 μSv / h to 0.05 μSv / h. Ultimately, the corrected radiation data will more accurately reflect the actual radiation intensity.

[0145] The concentration analysis submodule analyzes the changes in radiation concentration distribution in different regions based on radiation correction data, and calculates the radiation concentration of each region by combining geographical location information, thus obtaining the radiation concentration analysis results.

[0146] First, based on the radiation correction data, the radiation intensity of different regions is determined, and the data is matched with the corresponding geographical location information. For example, assuming that in a certain region, the radiation intensity is 0.04 μSv / h, 0.05 μSv / h, and 0.06 μSv / h, and the data corresponds to the geographical coordinates (30.25°N, 90.75°W), (30.26°N, 90.76°W), and (30.27°N, 90.77°W), respectively, the system then performs a spatial weighted calculation of the radiation intensity of each region to obtain the radiation intensity of that region. For example, if the geographical area of ​​a region is 500 meters × 500 meters, and the radiation intensities are 0.04 μSv / h, 0.05 μSv / h, and 0.06 μSv / h, then the average radiation concentration of the region will be: (0.04 + 0.05 + 0.06) / 3 = 0.05 μSv / h. Furthermore, based on the radiation intensity of each region and combined with geographical coordinate information, the system will calculate the trend of radiation concentration variation using a spatial interpolation algorithm. Finally, the system outputs the radiation concentration analysis results, including the radiation concentration and distribution of each region.

[0147] It should be understood that the term "and / or" in this article 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. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0148] In this invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be a single item or multiple items.

[0149] It should be understood that, in various embodiments of the present invention, the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0150] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0151] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0152] In the several embodiments provided by this invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, 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, mechanical, or other forms.

[0153] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0154] In addition, the functional units in the various embodiments of the present invention 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.

[0155] If the aforementioned functions are implemented as 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 this invention, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium 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 invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0156] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. An intelligent analysis system for nuclear radiation data, characterized by, The system includes: The data acquisition and planning module obtains the current hydrodynamic data of the ocean area. It analyzes the relationship between the rate of change of radiation intensity and the flow state through the data collected by the nuclear radiation sensor on the unmanned vessel, monitors the changes of the target radiation source in real time, and dynamically adjusts the path of the unmanned vessel to obtain the optimized path configuration. The radiation intensity monitoring module optimizes the configuration based on the path, analyzes the collected radiation intensity and frequency information, judges the radiation intensity fluctuations based on the current ocean current speed and temperature changes in the area, corrects the original data, and generates radiation intensity change data. The radiation intensity monitoring module includes: The radiation data analysis submodule, based on the optimized configuration of the path, analyzes the collected radiation intensity and frequency information, combines it with the current ocean current velocity and temperature change data, filters out key data points of fluctuation, performs preliminary analysis on them, evaluates the trend of radiation intensity fluctuation, and obtains radiation fluctuation data. The trend analysis submodule analyzes the dynamic trend of the radiation source based on the radiation fluctuation data, combines the radiation intensity data of multiple time periods with environmental changes, determines the relationship between radiation fluctuation and flow velocity changes, determines the potential trend of the radiation source, and generates the dynamic trend of the radiation source. The data correction submodule corrects the original radiation data according to the dynamic trend of the radiation source, removes abnormal data points that do not conform to the trend, and combines environmental factors to correct the data to obtain radiation intensity change data. Based on the radiation intensity change data, the sensor adjustment module analyzes the current radiation intensity fluctuation range, combines water depth, ocean current speed and temperature changes to determine the impact of environmental factors on the sensor, automatically adjusts the sensor sensitivity, and updates its sampling frequency to obtain the sensor sensitivity adjustment configuration. The radiation source positioning module adjusts its configuration based on the sensor sensitivity, combines real-time geographical location, ocean current velocity and temperature information, and calculates the radiation source location through waveform analysis, continuously updates the radiation source's position coordinates, and obtains the radiation source location information.

2. The intelligent analysis system for nuclear radiation data according to claim 1, characterized in that, The path optimization configuration includes the optimal path, optimal travel speed, and optimal target area. The radiation intensity change data includes the radiation intensity fluctuation range, the dynamic change trend of the radiation source, and the data correction results. The sensor sensitivity adjustment configuration includes the sensitivity adjustment value, the detection range optimization result, and the sampling frequency update result.

3. The intelligent analysis system for nuclear radiation data according to claim 1, characterized in that, The data acquisition planning module includes: The fluid state acquisition submodule acquires fluid dynamics data of the current ocean area. Through the nuclear radiation sensor on board the unmanned vessel, it monitors the flow state of ocean fluids, collects information on water velocity and direction, and calculates the changes in velocity and direction within the area to obtain flow state data. The radiation monitoring and analysis submodule analyzes the changes in radiation intensity based on the flow state data, calculates the rate of change of radiation intensity over time, compares it with the ocean flow state, screens out key areas of radiation intensity change, and obtains radiation change data. The path optimization and adjustment submodule analyzes the impact of the radiation change data on the path of the unmanned vessel, adjusts the direction and speed of the unmanned vessel, optimizes the path planning, and obtains the path optimization configuration.

4. The intelligent analysis system for nuclear radiation data according to claim 1, characterized in that, The sensor adjustment module includes: The radiation fluctuation analysis submodule analyzes the current radiation intensity fluctuation range based on the radiation intensity change data, combines the changes in water depth, ocean current velocity and temperature, compares the radiation data for each time period, evaluates the changing trend of the radiation fluctuation range, and obtains the radiation range data. The environmental factors assessment submodule analyzes the impact of environmental factors on sensor detection based on the radiation range data, assesses the degree of interference of environmental fluctuations on radiation intensity, determines the sensor parameters that need to be corrected, and obtains the environmental impact assessment log. The sensitivity adjustment submodule automatically adjusts the sensor sensitivity based on the environmental impact assessment log, optimizes the sensor's detection range and sampling frequency, matches the current acquisition conditions, and obtains the sensor sensitivity adjustment configuration.

5. The intelligent analysis system for nuclear radiation data according to claim 4, characterized in that, The formula used is based on the radiation range data: ； The environmental impact assessment results are calculated to obtain the corrected radiation intensity. ,in, Representing the The radiation value measured in this instance. Represents the calibrated radiation value. Representing the The temperature value measured this time, Represents the calibrated temperature value. Representing the Sensor readings for each measurement This represents the calibrated sensor reading. The factor representing the influence of temperature on radiation intensity. The factor representing the influence of sensor readings on radiation intensity. This represents the number of measurements.

6. The intelligent analysis system for nuclear radiation data according to claim 1, characterized in that, The radiation source location module includes: The signal difference analysis submodule adjusts the configuration according to the sensor sensitivity, acquires data collected by the nuclear radiation sensor moving with the unmanned vessel, and calculates the difference between the acquired signal and the sensor by combining real-time geographical location, ocean current speed and temperature information, and analyzes the relationship between signal strength and sensor position, screens potential signal deviations, and obtains signal difference data. The radiation source estimation submodule estimates the location of the radiation source based on the signal difference data through waveform analysis, and makes dynamic corrections for environmental influences, continuously updating the location coordinates of the radiation source to obtain the radiation source location information.

7. The intelligent analysis system for nuclear radiation data according to claim 6, characterized in that, The method for calculating the location of the radiation source through waveform analysis uses the following formula: ； Obtain radiation source location information The coordinates of the radiation source location are continuously updated, among which, Represents the number of waveform data points. Representing the The signal strength difference at each time point Table 1 The signal strength difference value corresponding to each time point Representing the The change in the time interval between each data point and the previous point Representing the The delay parameters at each time point.

8. The intelligent analysis system for nuclear radiation data according to claim 1, characterized in that, The system also includes: The radiation data processing module, based on the location information of the radiation source, removes abnormal data, corrects valid data, and analyzes the changes in radiation concentration distribution in the different areas to obtain radiation concentration analysis results. The radiation concentration analysis results include a radiation concentration distribution map and corrected radiation concentration data.

9. The intelligent analysis system for nuclear radiation data according to claim 8, characterized in that, The radiation data processing module includes: The radiation correction submodule analyzes abnormal fluctuations in the data based on the radiation source location information, removes abnormal data, and corrects deviations in the radiation intensity data to obtain radiation correction data. The concentration analysis submodule analyzes the changes in radiation concentration distribution in different regions based on the radiation correction data, and calculates the radiation concentration in each region by combining geographical location information, thus obtaining the radiation concentration analysis results.

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