A method for calibrating a regional radiation monitor

Abstract

The present application relates to the technical field of sensing monitoring correction, in particular to a kind of area radiation monitor's verification method.The method is combined with the deviation value change between different environment types and system preset value variation section, and according to the disturbance influence degree of the deviation change trend degree in variation section, the difference between the disturbance difference index obtained by combining the confusion situation analysis of radiation dose rate data detection and other variation sections;Determine the power influence time through the matching between power change and environmental parameter change and time difference;Combined with the power change of the disturbance influence degree, the disturbance difference index and the power influence time of all environmental types, the fitting weight of the moment is obtained, and the radiation dose rate data is fitted and calibrated for verification.The present application considers the electromagnetic interference reservation in system by the disturbance influence of multiple environments to radiation dose rate data, and comprehensively determines the fitting weight of data point, improves the accuracy of fitting calibration, and realizes more reliable result verification.

Description

Technical Field

[0001] This invention relates to the field of sensor monitoring and correction technology, and specifically to a calibration method for a regional radiation monitoring instrument. Background Technology

[0002] With the development of technology and the expansion of industrial applications, radiation pollution has gradually become a focus of industrial attention. Regional radiation monitoring instruments, as a key technological device equipped with intelligent sensors, are widely used in environmental monitoring, nuclear energy facilities, medical care, and scientific research, among other fields, to ensure safe and controllable radiation levels. These devices can monitor the radiation dose rate in the air in real time, providing crucial data support for environmental protection and public safety.

[0003] The calibration process for existing regional radiation monitoring instruments typically requires multiple repetitions to determine and test their stability and accuracy. The test results are usually repeated a fixed number of times, and the deviations from each repetition are summed without distinction. However, due to the high-intensity operation of the testing environment and some technical limitations, it is impossible to achieve ideal constant temperature and humidity conditions during environmental control. Furthermore, instability caused by long-term circuit wear and tear often leads to environmental differences between some test results, thus requiring fitting calibration.

[0004] However, in the current testing environment, in addition to the monitor deviation caused by temperature and humidity changes, there is also the problem of power fluctuation in the power supply system that causes the environmental control system to be inaccurate. This problem is usually accompanied by electromagnetic interference, which will also lead to more complex interference in the acquired dose rate data. Therefore, conventional fitting methods often cannot accurately identify the degree of interference to the data points, resulting in inaccurate calibration results and unreliable verification results. Summary of the Invention

[0005] To address the technical problem in existing technologies where the degree of interference to data points cannot be accurately identified, leading to inaccurate calibration results, the present invention aims to provide a calibration method for a regional radiation monitor. The specific technical solution adopted is as follows: This invention provides a method for calibrating a regional radiation monitoring instrument, the method comprising: During the testing period, radiation dose rate data at each sampling time was obtained through a regional radiation monitoring instrument, and parameter values ​​and power values ​​in the power supply system were acquired for each sampling time under each environmental type. For each environmental type, the test period is divided into segments based on the variation of the deviation between the parameter values ​​at the time-series upsampling moments and the system preset values. Based on the degree and trend of the deviation values ​​in the segments, combined with the distribution of the segments, the interference impact of each segment is obtained. Based on the approximation between the degree of disorder in radiation dose rate data and the interference impact of each segment, the degree of difference between each segment and other segments is analyzed to obtain the interference difference index of each segment. For each environment type, the sampling times are matched based on the consistency of the temporal changes in parameter and power value differences between adjacent sampling times to obtain the environment matching time for each sampling time. The power impact time of the sampling time is determined based on the time difference between the sampling time and the environment matching time for all environment types, as well as the interference difference index of the change segment under the environment type in which the sampling time is located. Based on the interference impact and interference difference index of the changing segment under the environmental type at each sampling time, and combined with the power influence of the sampling time on the degree of power value change at the sampling time, the fitting weight of each sampling time is obtained. The radiation dose rate data during the test period is fitted using fitting weights to obtain calibrated radiation dose rate data; the calibration is then performed using the calibrated radiation dose rate data.

[0006] Furthermore, the method for obtaining the change segment includes: For any environment type, calculate the difference between the parameter value of that environment type at each sampling time and the system preset value, and use it as the deviation value of that environment type at each sampling time; Curve fitting is performed on the continuous deviation values ​​in the time sequence of the test period to obtain the deviation curve for this environment type; the extreme points in the deviation curve for this environment type are obtained; and the time period between each two adjacent extreme points is taken as a variation segment.

[0007] Furthermore, the method for obtaining the interference impact degree includes: For any given environmental type and any given range of variation, perform principal component analysis on the deviation value of that range to obtain the principal component direction of that range; use the absolute value of the slope of the principal component direction of that range as the trend of variation of that range. The number of sampling times in the change segment is taken as the distribution length of the change segment; Calculate the numerical difference of the deviation between each two adjacent sampling times in the change segment, and calculate the mean of all numerical differences to obtain the change fluctuation of the change segment; By combining the trend degree, distribution length, and fluctuation degree of the change segment, the interference impact degree of the change segment can be obtained.

[0008] Furthermore, the method of combining the trend degree, distribution length, and fluctuation degree of the change segment to obtain the interference impact degree of the change segment includes: The distribution length of the change segment is negatively correlated and normalized to obtain the distribution influence of the change segment; The disturbance impact of a change segment is obtained by multiplying its trend degree, fluctuation degree, and distribution impact degree.

[0009] Furthermore, the method for obtaining the interference difference index includes: For any variation segment of any environmental type, the standard deviation of all radiation dose rate data in that variation segment is normalized to obtain the radiation disorder of that variation segment. The interference fit of the change segment is obtained by negatively mapping the normalized value of the interference impact degree to the difference in radiation disorder degree. Calculate the difference in interference matching degree between the change segment and each other change segment of the corresponding environment type, and use it as the fitness difference between the change segment and each other change segment; Calculate the mean of the fit difference between this change segment and all other change segments of the corresponding environment type to obtain the interference difference index of this change segment.

[0010] Furthermore, the method for obtaining the environmental matching time includes: During the test period, the power difference between each sampling time (excluding the first sampling time) and the previous sampling time in the time sequence is taken as the power difference value for each sampling time; all power difference values ​​are arranged in time sequence to obtain the power difference sequence. For any environment type, the difference between the parameter values ​​of that environment type at each sampling time except the first sampling time and the previous sampling time in the time series is taken as the parameter difference value at each sampling time; all parameter difference values ​​are arranged in time series to obtain the parameter difference sequence of that environment type. DTW matching is performed between the power difference sequence and the parameter difference sequence of the environment type to obtain matching pairs for the environment type; the sampling time corresponding to the parameter difference value in the matching pair is after the sampling time corresponding to the power difference value. In this environment type, the sampling time corresponding to the power difference value in the matching pair is used as the environment matching time corresponding to the sampling time of the parameter difference value.

[0011] Furthermore, the method for obtaining the power influence time includes: The mean time difference between each sampling time and each environment matching time under all environment types is averaged to obtain the mean time difference for each sampling time. The mean of the interference difference index for each sampling time across all environmental types is used as the time-interference difference degree for each sampling time; the ratio of the interference difference degree for each sampling time to the total interference difference degree for all sampling times is used as the interference confidence weight for each sampling time. The mean time difference of all sampling times is weighted and summed using the interference confidence weight as the weight, and then rounded to obtain the delay time difference; The time of the time interval delay before the sampling time is taken as the power influence time of the sampling time.

[0012] Furthermore, the method for obtaining the fitting weights includes: For any given sampling time, the average interference impact of that sampling time across all environmental types in the change segment is used as the interference index for that sampling time. The mean value of the interference difference index at the sampling time for all environmental types in the change segment is taken as the interference significance index at that sampling time. The difference in power value between the power influence time at this sampling time and the sampling time before the power influence time is used as the power interference index at this sampling time. By combining the interference index, the interference significance index, and the power interference index at that sampling moment, the fitting weight at that sampling moment is obtained.

[0013] Furthermore, the step of combining the interference index, interference significance index, and power interference index at the sampling time to obtain the fitting weight at the sampling time includes: The values ​​of the significant interference index, power interference index, and interference index at the sampling time are multiplied together and normalized to obtain the fitting weight at that sampling time.

[0014] Furthermore, the method for obtaining the calibration radiation dose rate data includes: The time-series radiation dose rate data are weighted according to the fitting weight at each sampling time, and then fitted using the least squares method. The fitted radiation dose rate data is used as the calibration radiation dose rate data.

[0015] The present invention has the following beneficial effects: This invention combines the deviation changes of different environmental types to analyze interference in different time periods. It divides the system into segments based on the deviation from preset values, and obtains the interference impact degree based on the trend of deviation changes within each segment. This provides an initial analysis of the potential interference impact of environmental factors during each time period. Then, it analyzes the differences between the interference impact degree and other segments by considering the disorder in radiation dose rate data detection, thus obtaining an interference difference index. By approximating the disorder in the radiation dose rate data with the interference impact degree, it characterizes the degree of fit of the interference impact on each segment. Combined with other segments, this interference difference index reflects the possibility of additional electromagnetic interference in the interference impact. Considering that electromagnetic interference caused by power changes is a case that needs to be retained, and given the delayed nature of power-induced environmental changes, the power impact time corresponding to each moment is determined by matching power changes with environmental parameter changes and the time difference. This reflects that environmental changes at each moment correspond to possible power changes. Therefore, the presence of electromagnetic interference can be determined by using the interference difference index and the power change at the power impact time. Finally, by combining the interference impact degree under all environmental types at each moment, as well as the interference difference index and power change at the time of power influence, a fitting weight is obtained to perform a more accurate fitting calibration on the radiation dose rate data before verification. This invention analyzes the interference degree by comparing the segmented radiation dose rate data with various environmental influences, and analyzes the electromagnetic interference influence within the system by matching the delay with power changes. It comprehensively determines the fitting weight of the data point at each moment, improving the accuracy of the fitting calibration and achieving more reliable result verification. Attached Figure Description

[0016] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention 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 the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A flowchart illustrating a method for calibrating a regional radiation monitoring instrument according to an embodiment of the present invention; Figure 2 This is a flowchart of a method for obtaining the degree of interference according to an embodiment of the present invention. Detailed Implementation

[0018] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a regional radiation monitoring instrument calibration method proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0020] The following describes in detail, with reference to the accompanying drawings, a specific scheme for the calibration method of a regional radiation monitoring instrument provided by the present invention.

[0021] Please see Figure 1 The diagram illustrates a flowchart of a verification method for a regional radiation monitoring instrument according to an embodiment of the present invention. The method includes the following steps: S1: During the test period, radiation dose rate data at each sampling time is obtained through the regional radiation monitoring instrument, and parameter values ​​and power values ​​in the power supply system are obtained for each sampling time under each environmental type.

[0022] In this embodiment of the invention, when calibrating the current regional radiation monitoring instrument, it is necessary to collect radiation dose data during the test period of multiple test processes using the regional radiation monitoring instrument. Since there will be a lot of interference when acquiring data, the radiation dose rate data needs to be calibrated before calibration. Considering the influence of the test power supply system and environmental factors, the onboard intelligent sensor collects reference values ​​for different environmental types and power values ​​in the power supply system during the current test process.

[0023] In this embodiment of the invention, the environment type includes temperature and humidity. Temperature and humidity data are collected by placing temperature and humidity sensors in the test environment as parameter values. Power values ​​are obtained from the power supply system used in the test environment to reflect the working status of the equipment in the test environment. The sampling frequency is set to once per second. The specific test period length and sampling frequency can be adjusted by the implementer according to the specific implementation scenario, and are not limited here.

[0024] It should be noted that, for ease of calculation, all data involved in the calculations in this embodiment of the invention have undergone data preprocessing to eliminate the influence of dimensions. The specific methods for eliminating the influence of dimensions are well-known to those skilled in the art and are not limited here.

[0025] S2: For each environmental type, the test period is divided into segments based on the variation of the deviation between the parameter values ​​at the time of upsampling and the system preset values. Based on the degree and trend of the deviation values ​​in the segments, and combined with the distribution of the segments, the interference impact of each segment is obtained. Based on the approximation between the degree of disorder in radiation dose rate data and the interference impact of each segment, the degree of difference between each segment and other segments is analyzed to obtain the interference difference index of each segment.

[0026] During testing, when the environmental control system in the test environment is operating under ideal conditions, the time-series radiation dose rate data acquired by the regional radiation monitor will be closer to the actual test results. Ideal operating conditions refer to conditions where environmental parameters are constant. However, due to the difficulty in maintaining constant environmental control and the high workload on the power supply system caused by prolonged operation, the actual performance of the environmental control system may not meet the preset expectations. Therefore, the radiation dose rate reflected by the recorded environmental parameter values ​​may not be ideal.

[0027] Therefore, the deviation between the parameter values ​​of the environmental type and the system preset values ​​is first used to reflect the degree of interference that environmental factors may cause. Considering the constant control conditions required for the test environment, when the environmental data deviates, the control system needs to adjust the changes in environmental parameters. Therefore, the changes in environmental parameter deviations usually have the same trend in continuous segments. Thus, the time periods are divided based on the changes in deviations of different environmental types to facilitate subsequent segmented analysis of interference.

[0028] Preferably, in this embodiment of the invention, the method for obtaining the change segment includes: First, for any environment type, calculate the difference between the parameter value of that environment type at each sampling time and the system preset value. This difference is taken as the deviation value of that environment type at each sampling time. For example, in a constant temperature and humidity control system, the system preset value is the ideal preset temperature and preset humidity data. It should be noted that the implementer can adjust the value of the system preset value according to the specific implementation scenario. For example, the system preset value is 20℃ when the environment type is temperature, and 50% when the environment type is humidity. There are no restrictions here.

[0029] Furthermore, the continuous deviation values ​​over the test period are subjected to curve fitting to obtain the deviation curve for this environmental type. The extreme points in the deviation curve for this environmental type are then identified, and the magnitude of the deviation is reflected through curve fitting. During environmental control and adjustment, when deviations occur in the test environment, the environmental parameters are adjusted to the ideal state to ensure constant conditions, and the deviation value changes in a periodic decreasing trend.

[0030] Therefore, the time interval between each two adjacent extreme points is considered as a variation segment. The changes within each segment can reflect the interference of environmental factors on radiation dose rate data detection. Thus, the potential interference level is further analyzed through variation segments under different types of environmental factors. It should be noted that obtaining extreme points is a technique well-known to those skilled in the art, such as using the derivative method, where points where the first derivative is zero and the second derivative exists are taken as extreme points. The methods for obtaining these extreme points will not be elaborated upon here.

[0031] Within each change segment, the greater and more complex the changes in environmental parameters, the greater the impact of environmental factors on detection. Therefore, the interference and impact of environmental factors should be comprehensively analyzed by considering the rapidity of changes within each segment, the degree of local fluctuations, and the overall trend of changes.

[0032] Preferably, in this embodiment of the invention, the method for obtaining the interference impact degree is described in [reference needed]. Figure 2 The diagram illustrates a flowchart of a method for obtaining interference influence according to an embodiment of the present invention, which includes the following steps: S201: Obtain the trend of change of each segment based on the overall rate of change of the deviation value in each segment.

[0033] The greater the overall adjustment of environmental parameters in the change segment, the more likely it is to cause detection impact. Therefore, the degree of interference is analyzed by the degree of change in the overall trend.

[0034] In this embodiment of the invention, for any change segment of any environmental type, principal component analysis is performed on the deviation value of the change segment to obtain the principal component direction of the change segment. The main trend features of the data in the change segment are extracted through principal component analysis, which facilitates the analysis of the main changes in the data.

[0035] Furthermore, the absolute value of the slope of the principal component direction of this change segment is taken as the trend degree of change of this change segment. The magnitude of the slope reflects the speed of the trend. The larger the slope value, that is, the greater the trend degree, the greater the degree of trend change, and the greater the potential interference effect. It should be noted that principal component analysis and slope acquisition are techniques well known to those skilled in the art, and will not be elaborated here.

[0036] S202: Obtain the distribution length of each variation segment based on its length.

[0037] The shorter the duration of the change segment, the faster the adjustment process and the more significant the impact of the degree of change. This can be reflected by the length of the change segment.

[0038] In this embodiment of the invention, the number of sampling times in the change segment is taken as the distribution length of the change segment. The more sampling times there are, the longer the distribution of the change segment is.

[0039] S203: Obtain the degree of variation of the change segment based on the degree of change of the continuous parameter values ​​in each change segment.

[0040] Due to the influence of the testing equipment during the adjustment process, there may be many small changes in the change segment. Since the fluctuations are small, the degree of interference may be relatively low. Therefore, we further analyze the degree of continuous change by looking at the changes over consecutive time intervals. When the degree of continuous change is large, the interference effect is greater.

[0041] In this embodiment of the invention, the numerical difference of the deviation value between each two adjacent sampling times in the change segment is calculated, and the mean of all numerical differences is calculated to obtain the change fluctuation of the change segment. The greater the change fluctuation, the more drastic the continuous change of the deviation value, and the higher the possibility of interference.

[0042] S204: By combining the trend degree, distribution length and fluctuation degree of the change segment, the interference impact degree of the change segment is obtained.

[0043] The greater the trend of change, the greater the fluctuation of change, indicating that the overall trend of change is more drastic and the fluctuation of continuous change is greater, and the greater the possibility of interference from environmental factors. The smaller the distribution length, the more significant the change is, the faster the change is, and the more significant the interference effect is.

[0044] In this embodiment of the invention, the distribution length of the change segment is negatively correlated and normalized to obtain the distribution influence degree of the change segment. Furthermore, the product of the change trend degree, change volatility degree, and distribution influence degree of the change segment is used to obtain the interference influence degree of the change segment. By combining these three indicators through a product, the detection interference impact that may be caused by the degree of environmental parameter deviation is reflected. The greater the interference influence degree of the change segment, the higher the probability of interference affecting data detection on the change segment.

[0045] It should be noted that negative correlation mapping and normalization are techniques well known to those skilled in the art. Negative correlation mapping can use inverse proportional values, and normalization can use the maximum and minimum value normalization method. These will not be elaborated or limited here.

[0046] This completes the analysis of environmental parameters on the changing segment and yields the degree of interference impact.

[0047] Further, an adaptation analysis can be conducted on the degree of interference caused by environmental factors in each variation segment and the degree of disorder in the detected radiation dose rate. When the interference is greater and the degree of disorder is higher, it reflects that the actual impact of the interference is higher. When the interference is more consistent, it indicates that the interference is an environmental interference situation that needs to be corrected.

[0048] However, when electromagnetic interference occurs in the power supply system equipment, this interference will cause changes in radiation dose rate data, but at the same time it will affect the identification capability of environmental monitoring equipment, resulting in changes in the monitoring of environmental parameters. At this time, the interference situation needs to be preserved. Therefore, the changes in the segments are analyzed first, and the discrepancies between the adaptation situations are observed to see if there is any interference superposition.

[0049] Preferably, in this embodiment of the invention, the method for obtaining the interference difference index includes: First, for any variation segment of any environmental type, the standard deviation of all radiation dose rate data in that variation segment is normalized to obtain the radiation disorder of that variation segment. The standard deviation reflects the degree to which the radiation dose rate data is affected. The larger the standard deviation, the higher the degree to which the radiation dose rate data is affected by interference.

[0050] Further, the interference impact degree of this change segment is normalized and negatively correlated with the difference in radiation disorder to obtain the interference fit degree of this change segment. The normalized value reflects the approximation between the interference caused by environmental factors and the degree of interference to the radiation dose rate. The smaller the difference, the higher the degree of interference and the degree of interference, and the greater the fit degree.

[0051] To reflect other possible interference situations, the differences in the adaptability of multiple variation segments are considered. The difference in interference matching degree between the variation segment and each other variation segment of the corresponding environment type is calculated as the adaptability difference between the variation segment and each other variation segment. The larger the difference, the higher the degree of inconsistency in adaptability, and the more likely the variation segment is to have other interference situations.

[0052] Finally, the mean of the adaptation difference between this variation segment and all other variation segments of the corresponding environmental type is calculated to obtain the interference difference index of this variation segment. The overall difference between this variation segment and other variation segments reflects the degree of electromagnetic interference influence of this variation segment, and this interference needs to be retained.

[0053] S3: For each environment type, based on the consistency of the temporal changes in parameter value differences and power value differences between adjacent sampling times, the sampling times are matched to obtain the environment matching time for each sampling time; based on the time difference between the sampling time and the environment matching time for all environment types, and the interference difference index of the change segment under the environment type in which the sampling time is located, the power influence time of the sampling time is determined.

[0054] For potential electromagnetic interference caused by changes in system power, and the impact of such electromagnetic interference on environmental parameters is not a real-time response but has a certain delay, the asymmetric matching of data changes in time can be used to determine the time when power changes may have an impact at each sampling moment, so as to subsequently determine the degree of impact of power-induced changes at each sampling moment.

[0055] Considering that the response to changes caused by electromagnetic interference is relatively consistent, we first perform time-series matching to initially match the parameter value changes for each environmental type to obtain the environmental matching time. Then, we combine the multi-environment type matching results of all sampling times to comprehensively determine a more accurate power impact time.

[0056] Preferably, in this embodiment of the invention, the method for obtaining the environmental matching time includes: First, during the test period, the power difference between each sampling time (excluding the first sampling time) and the previous sampling time in the time sequence is taken as the power difference value for each sampling time. The first sampling time does not reflect the change in the previous time, so no change matching is performed. All power difference values ​​are arranged in time sequence to obtain the power difference sequence, and the power values ​​are sorted according to the degree of change between time.

[0057] Similarly, for any environment type, the difference between the parameter values ​​of that environment type at each sampling time (excluding the first sampling time) and the previous sampling time in the time series is taken as the parameter difference value at each sampling time. All parameter difference values ​​are arranged in time series to obtain the parameter difference sequence of that environment type, and the parameter values ​​are also sorted according to the changes over time.

[0058] Further DTW matching is performed on the power difference sequence and the parameter difference sequence of this environment type to obtain matching pairs for this environment type. Usually, the order of events is not considered when performing DTW matching, but the delay characteristics of power due to environmental changes require restrictions on the acquisition of matching pairs.

[0059] When matching the sampling time corresponding to the parameter difference value in the pair, it is after the sampling time corresponding to the power difference value. That is, when matching each parameter difference value in the power difference sequence, only the time sequence before the sampling time corresponding to the parameter difference value is considered. It should be noted that DTW matching is a well-known technique in the art. The one-way time constraint is a simple condition. The constraint method of matching the time sequence with the preceding window can be used, etc., which will not be specifically limited or elaborated here.

[0060] Furthermore, under this environment type, the sampling time corresponding to the power difference value in the matched pair is taken as the environment matching time corresponding to the parameter difference value. The pre-conditioning of each sampling time is applied to the matching situation. That is, the sampling time corresponding to the power difference sequence in the matched pair is uniformly taken as the environment matching time, so that the subsequent analysis is uniform and it is convenient to analyze the impact of power at different sampling times.

[0061] The delay time is obtained by combining the matching results of the sampling time under different environmental types. The interference difference index reflects the possible electromagnetic interference at that time. The greater the electromagnetic interference, the greater the reliability of the delay matching corresponding to the sampling time. Therefore, the interference difference index of the changing segment corresponding to the sampling time is used as a reliability weight to adjust the delay time difference and obtain the power-affected time.

[0062] Preferably, in this embodiment of the invention, the method for obtaining the power influence time includes: First, the average time difference between each sampling time and each environment matching time under all environment types is calculated to obtain the mean time difference of each sampling time. The mean value reflects the magnitude of the delay deviation of the sampling time under all environment type matching.

[0063] Furthermore, the mean value of the interference difference index for each sampling time across all environmental types is used as the time-interference difference degree for each sampling time, thus comprehensively analyzing the probability of electromagnetic interference at each sampling time under all environmental types. The ratio of the interference difference degree for each sampling time to the sum of the interference difference degrees at all sampling times is used as the interference confidence weight for each sampling time. This weight is then normalized by the proportion of the accumulated values ​​at all times and weighted accordingly.

[0064] Then, the interference confidence weight is used as the weight to sum the mean time difference of all sampling times, and the result is rounded to obtain the delay time difference. The confidence contribution of the time difference is adjusted by the weight, and a more accurate delay deviation is obtained by combining the results.

[0065] Finally, the time interval delay before the sampling time is taken as the power impact time of the sampling time. This standardizes the determination of the time at which environmental interference at the sampling time might be affected by power, facilitating subsequent analysis of the degree of impact.

[0066] S4: Based on the interference impact and interference difference index of the changing segment under the environmental type at each sampling time, and combined with the power influence of the sampling time on the degree of power value change at the sampling time, obtain the fitting weight for each sampling time.

[0067] During the fitting and calibration of radiation dose rate data, the continuous impact of environmental interference needs to be fitted. When the probability of electromagnetic interference is high and the impact caused by power is significant, it is necessary to constrain the interference fitting to avoid smoothing out actual quality issues of the monitor. Therefore, the degree of influence of environmental interference is characterized by the interference impact degree, the degree of electromagnetic interference is characterized by the interference difference index, and the degree of interference caused by power factors is characterized by the power value change at the power influence time, thus obtaining the fitting weights at the sampling time.

[0068] Preferably, in this embodiment of the invention, the method for obtaining the fitting weights includes: First, for any given sampling time, the average interference impact of that sampling time across all environmental types in the change segment is used as the interference index for that sampling time. Combined with the interference impact of the change segment under different environmental types at the sampling time, the degree of environmental interference is comprehensively reflected. The greater the degree of environmental interference, the lower the reliability of the data detection, and the smaller the fitting weight should be.

[0069] Furthermore, the mean of the interference difference index for all environmental types at the sampling time is used as the interference significance index for that sampling time. Combined with the interference difference index for different environmental types at the sampling time, the degree of electromagnetic interference that may occur is comprehensively reflected. The larger the interference difference index, the higher the possibility of other electromagnetic interference, and the greater the weight is considered when fitting the data.

[0070] Furthermore, the difference in power value between the power influence time and the previous sampling time is used as the power interference index at that sampling time. The greater the difference in power value at the power influence time, the higher the degree of electromagnetic interference caused by power, and the greater the weight considered in the fitting.

[0071] Finally, by combining the interference index, the significant interference index, and the power interference index at the sampling time, the fitting weight for that sampling time is obtained. In this embodiment of the invention, the values ​​of the significant interference index, the power interference index, and the interference index at the sampling time, which are negatively correlated, are multiplied together and then normalized to obtain the fitting weight for that sampling time.

[0072] This completes the analysis of interference with the radiation dose rate data at each sampling time and the acquisition of the weights required for correcting the fit.

[0073] S5: The radiation dose rate data during the test period is fitted based on the fitting weights to obtain calibrated radiation dose rate data; the calibration is performed using the calibrated radiation dose rate data.

[0074] In regional radiation monitoring instrument data calibration, a fitting correction method is typically used. By adding fitting weights to the fitting model, fitted corrected data can be obtained. In this embodiment of the invention, the method for obtaining calibration radiation dose rate data includes: The time-series radiation dose rate data are weighted according to the fitting weight at each sampling time, and then fitted using the least squares method. The fitted radiation dose rate data is used as the calibration radiation dose rate data. It should be noted that the least squares fitting method is a technique well known to those skilled in the art, and will not be described in detail here.

[0075] The radiation monitoring instrument in the current area can be verified by calibrating the radiation dose rate data. In the embodiments of the present invention, the verification can be carried out based on the verification standard, such as the "Calibration Specification for Fixed X and Gamma Radiation Dose Rate Monitors for Site Monitoring". The specific verification method is a well-known technical means and is not adjusted, so it will not be described in detail here.

[0076] In summary, this invention analyzes interference in different time periods by considering the deviation changes of different environmental types. It divides the time periods into segments based on the deviation values ​​from the system's preset values, and obtains the interference impact degree based on the trend of deviation changes within each segment. This provides a preliminary analysis of the potential interference impact of environmental factors during each time period. Then, it analyzes the differences between the interference impact degree and other segments by considering the disorder in radiation dose rate data detection, thus obtaining an interference difference index. By comparing the interference impact degree with the disorder approximation of radiation dose rate data, it characterizes the degree of fit of the interference impact on each segment. Combined with analysis of other segments, it obtains the interference difference index, reflecting the possibility of additional electromagnetic interference in the interference impact. Considering that electromagnetic interference caused by power changes is a case that needs to be retained, and given the delayed nature of power-induced environmental changes, the power impact time corresponding to each moment is determined by matching power changes with environmental parameter changes and the time difference. This reflects that environmental changes at each moment correspond to possible power changes. Therefore, the presence of electromagnetic interference can be determined by using the interference difference index and the power change at the power impact time. Finally, by combining the interference impact degree under all environmental types at each moment, as well as the interference difference index and power change at the time of power influence, a fitting weight is obtained to perform a more accurate fitting calibration on the radiation dose rate data before verification. This invention analyzes the interference degree by comparing the segmented radiation dose rate data with various environmental influences, and analyzes the electromagnetic interference influence within the system by matching the delay with power changes. It comprehensively determines the fitting weight of the data point at each moment, improving the accuracy of the fitting calibration and achieving more reliable result verification.

[0077] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0078] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A method for calibrating a regional radiation monitoring instrument, characterized in that, The method includes: During the testing period, radiation dose rate data at each sampling time was obtained through a regional radiation monitoring instrument, and parameter values ​​and power values ​​in the power supply system were acquired at each sampling time under each environmental type. For each environmental type, the test period is divided into segments based on the variation of the deviation between the parameter values ​​at the time-series upsampling moments and the system preset values. Based on the degree and trend of the deviation values ​​in the segments, combined with the distribution of the segments, the interference impact of each segment is obtained. Based on the approximation between the degree of disorder in radiation dose rate data and the interference impact of each segment, the degree of difference between each segment and other segments is analyzed to obtain the interference difference index of each segment. For each environment type, the sampling times are matched based on the consistency of the temporal changes in parameter and power value differences between adjacent sampling times to obtain the environment matching time for each sampling time. The power impact time of the sampling time is determined based on the time difference between the sampling time and the environment matching time for all environment types, as well as the interference difference index of the change segment under the environment type in which the sampling time is located. Based on the interference impact and interference difference index of the changing segment under the environmental type at each sampling time, and combined with the power influence of the sampling time on the degree of power value change at the sampling time, the fitting weight of each sampling time is obtained. The radiation dose rate data during the test period are fitted using fitting weights to obtain calibrated radiation dose rate data; the calibration is then performed using the calibrated radiation dose rate data. The method for obtaining the variation segment includes: for any environment type, calculating the difference between the parameter value of the environment type and the system preset value at each sampling time, as the deviation value of the environment type at each sampling time; performing curve fitting on the continuous deviation values ​​in the time sequence of the test period to obtain the deviation curve of the environment type; obtaining the extreme points in the deviation curve of the environment type; and taking the time period between each two adjacent extreme points as a variation segment. The method for obtaining the power impact time includes: averaging the time difference between each sampling time and each environment matching time under all environment types to obtain the mean time difference of each sampling time; taking the mean of the interference difference index of each sampling time in the change segment of all environment types as the time interference difference degree of each sampling time; taking the ratio of the interference difference degree of each sampling time to the sum of the interference difference degrees of all sampling times as the interference confidence weight of each sampling time; using the interference confidence weight as the weight to perform a weighted summation of the mean time differences of all sampling times and rounding to obtain the delay time difference; and taking the time of the delay time difference length before the sampling time as the power impact time of the sampling time.

2. The calibration method for a regional radiation monitoring instrument according to claim 1, characterized in that, The method for obtaining the interference impact includes: For any given environmental type and any given range of variation, perform principal component analysis on the deviation value of that range to obtain the principal component direction of that range; use the absolute value of the slope of the principal component direction of that range as the trend of variation of that range. The number of sampling times in the change segment is taken as the distribution length of the change segment; Calculate the numerical difference of the deviation between each two adjacent sampling times in the change segment, and calculate the mean of all numerical differences to obtain the change fluctuation of the change segment; By combining the trend degree, distribution length, and fluctuation degree of the change segment, the interference impact degree of the change segment can be obtained.

3. The calibration method for a regional radiation monitoring instrument according to claim 2, characterized in that, The interference impact of the change segment is obtained by combining its trend degree, distribution length, and fluctuation degree, including: The distribution length of the change segment is negatively correlated and normalized to obtain the distribution influence of the change segment; The disturbance impact of a change segment is obtained by multiplying its trend degree, fluctuation degree, and distribution impact degree.

4. The calibration method for a regional radiation monitoring instrument according to claim 1, characterized in that, The method for obtaining the interference difference index includes: For any variation segment of any environmental type, the standard deviation of all radiation dose rate data in that variation segment is normalized to obtain the radiation disorder of that variation segment. The interference fit of the change segment is obtained by negatively mapping the normalized value of the interference impact degree to the difference in radiation disorder degree. Calculate the difference in interference matching degree between the change segment and each other change segment of the corresponding environment type, and use it as the fitness difference between the change segment and each other change segment; Calculate the mean of the fit difference between this change segment and all other change segments of the corresponding environment type to obtain the interference difference index of this change segment.

5. The calibration method for a regional radiation monitoring instrument according to claim 1, characterized in that, The method for obtaining the environmental matching time includes: During the test period, the power difference between each sampling time (excluding the first sampling time) and the previous sampling time in the time sequence is taken as the power difference value for each sampling time; all power difference values ​​are arranged in time sequence to obtain the power difference sequence. For any environment type, the difference between the parameter values ​​of that environment type at each sampling time except the first sampling time and the previous sampling time in the time series is taken as the parameter difference value at each sampling time; all parameter difference values ​​are arranged in time series to obtain the parameter difference sequence of that environment type. DTW matching is performed between the power difference sequence and the parameter difference sequence of the environment type to obtain matching pairs for the environment type; the sampling time corresponding to the parameter difference value in the matching pair is after the sampling time corresponding to the power difference value. In this environment type, the sampling time corresponding to the power difference value in the matching pair is used as the environment matching time corresponding to the sampling time of the parameter difference value.

6. The calibration method for a regional radiation monitoring instrument according to claim 1, characterized in that, The method for obtaining the fitting weights includes: For any given sampling time, the average interference impact of that sampling time across all environmental types in the change segment is used as the interference index for that sampling time. The mean value of the interference difference index at the sampling time for all environmental types in the change segment is taken as the interference significance index at that sampling time. The difference in power value between the power influence time at this sampling time and the sampling time before the power influence time is used as the power interference index at this sampling time. By combining the interference index, the interference significance index, and the power interference index at that sampling moment, the fitting weight at that sampling moment is obtained.

7. The calibration method for a regional radiation monitoring instrument according to claim 6, characterized in that, The process of combining the interference index, interference significance index, and power interference index at that sampling time to obtain the fitting weights for that sampling time includes: The values ​​of the significant interference index, power interference index, and interference index at the sampling time are multiplied together and normalized to obtain the fitting weight at that sampling time.

8. The calibration method for a regional radiation monitoring instrument according to claim 1, characterized in that, The method for obtaining the calibration radiation dose rate data includes: The time-series radiation dose rate data are weighted according to the fitting weight at each sampling time, and then fitted using the least squares method. The fitted radiation dose rate data is used as the calibration radiation dose rate data.

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