A regional radiation monitor spectrum stabilization method and system

Abstract

This invention relates to the field of radiation monitoring technology, specifically to a method and system for stabilizing the spectrum of a regional radiation monitoring instrument. The method includes: acquiring the radiation intensity at each monitoring point; obtaining the local similarity between each monitoring point at each moment and other moments based on the differences in the variation characteristics of radiation intensity within a local area at different times; obtaining a first measurement accuracy by combining the differences in radiation intensity at different times of each monitoring point, the distribution characteristics of isoradial boundary lines, and the local similarity; obtaining a second measurement accuracy based on the changes in the location of the radiation source, the radiation intensity of the radiation source, and the distance between the radiation source and the monitoring point; screening abnormal moments by combining the first and second measurement accuracies; and correcting the radiation intensity at abnormal moments by integrating the variation indicators of each monitoring point at each moment with other monitoring points, the local similarity, the first measurement accuracy, and the second measurement accuracy, thereby achieving spectrum stabilization. This invention improves the spectrum stabilization effect.

Description

Technical Field

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

[0002] The area radiation monitor is used to monitor radiation levels in areas of nuclear medicine departments. When particles or rays pass through a gas, they collide and ionize, producing numerous ion pairs. Under the influence of an electric field, these ion pairs move towards two electrodes and are collected. An electrical signal is output from the external circuit. A pulse shaper converts this signal into a pulse signal, and a counter counts the number of pulses to obtain the radiation intensity. Spectrum stabilization is used to correct for spectral drift in the monitor, i.e., measurement errors caused by changes in the energy spectrum with temperature.

[0003] Existing methods for stabilizing the spectrum involve using a cubic polynomial function as a temperature correction function for energy spectrum processing. However, due to issues such as air circulation, personnel movement, and radiation source movement in radiation monitoring areas like nuclear medicine departments, the accuracy of the monitoring data collected by the monitoring instrument cannot be determined, which in turn makes it impossible to determine whether the correction value is accurate. Therefore, the stabilization effect cannot be guaranteed. Summary of the Invention

[0004] To address the problem that existing methods cannot guarantee the spectral stabilization effect of radiation monitoring instruments, the present invention aims to provide a spectral stabilization method and system for regional radiation monitoring instruments, the specific technical solution of which is as follows:

[0005] In a first aspect, the present invention provides a method for stabilizing the spectrum of a regional radiation monitoring instrument, the method comprising the following steps:

[0006] Obtain the radiation intensity at different monitoring points in the monitoring area within a preset time period;

[0007] The radiation intensity of all monitoring points at each time moment is projected onto a three-dimensional coordinate system, and several isoradiative edge lines in the three-dimensional coordinate system corresponding to each time moment are determined based on the radiation intensity. According to the difference in the variation characteristics of radiation intensity in the local area of ​​each monitoring point at different times, the local similarity of each monitoring point at each time moment with other times moment is obtained. Combining the difference in radiation intensity of each monitoring point at different times moment, the distribution characteristics of isoradiative edge lines and local similarity, the radiation source at each time moment and the first measurement accuracy of each monitoring point at each time moment are obtained.

[0008] Based on the changes in the location of the radiation source, the radiation intensity of the radiation source, and the relative distance between the radiation source and each monitoring point within a preset time period, the change index of each monitoring point at each moment is determined; combined with the differences in the change index and radiation intensity of different monitoring points at each moment, the second measurement accuracy of each monitoring point at each moment is obtained; and the abnormal moments of the monitoring points are screened by combining the first measurement accuracy and the second measurement accuracy.

[0009] By combining the change indicators of each monitoring point with those of other monitoring points at each time, the local similarity, the first measurement accuracy, and the second measurement accuracy, the radiation intensity at abnormal times is corrected; the corrected radiation intensity is then used for spectrum stabilization.

[0010] Preferably, the step of obtaining the local similarity of each monitoring point at each time point to other times based on the differences in the variation characteristics of radiation intensity within the local area at different times of each monitoring point includes:

[0011] Calculate the difference in slope between the lines connecting the radiation intensities of two adjacent moments within the neighborhood time window of the candidate monitoring point at the first and second moments, respectively.

[0012] Based on the difference in radiation intensity and the slope difference between corresponding moments within the neighborhood time window of the first and second moments of the candidate monitoring point, the local similarity between the first and second moments of the candidate monitoring point is obtained. The difference in radiation intensity and the slope difference between the corresponding moments are negatively correlated with the local similarity.

[0013] The candidate monitoring point can be any monitoring point, and the first time and the second time are any two times within a preset time period.

[0014] Preferably, by combining the differences in radiation intensity at different times at each monitoring point, the distribution characteristics of isoradiative boundary lines, and local similarities, the radiation source at each time moment is obtained, including:

[0015] For candidate monitoring points:

[0016] If there are other isoradioactive boundary lines inside the isoradioactive boundary line where the candidate monitoring point is located at the time of analysis, then the probability that the candidate monitoring point is a radiation source at the time of analysis is set to 0; if there are no other isoradioactive boundary lines inside the isoradioactive boundary line where the candidate monitoring point is located at the time of analysis, then the first difference between the radiation intensity corresponding to the isoradioactive boundary line where the candidate monitoring point is located at the time of analysis and the radiation intensity corresponding to the isoradioactive boundary line closest to the candidate monitoring point is located at the time of analysis is calculated, and the normalized result of the first difference is taken as the probability that the candidate monitoring point is a radiation source at the time of analysis.

[0017] If the probability is greater than a preset probability threshold, then the candidate monitoring point will be used as the radiation source at the time to be analyzed.

[0018] The time to be analyzed is any time within a preset time period.

[0019] Preferably, the acquisition of the first measurement accuracy at each monitoring point at each time moment includes:

[0020] For candidate monitoring points at the time to be analyzed:

[0021] The local similarity of the candidate monitoring point to be analyzed time with each other time is sorted in descending order of local similarity to obtain the local similarity sequence of the candidate monitoring point to be analyzed time; the first preset number of time moments in the local similarity sequence are taken as the similar time moments of the candidate monitoring point to be analyzed time.

[0022] The initial accuracy of the candidate monitoring point at the time to be analyzed is obtained based on the local similarity between the candidate monitoring point at the time to be analyzed and each of its similar times, and the difference in radiation intensity between the candidate monitoring point at the time to be analyzed and each of its similar times. The local similarity between the candidate monitoring point at the time to be analyzed and each of its similar times, and the difference in radiation intensity between the candidate monitoring point at the time to be analyzed and each of its similar times are both negatively correlated with the initial accuracy.

[0023] For any radiation source, candidate monitoring points are connected to the radiation source by line segments. Starting from the candidate monitoring point, the monitoring points are traversed along the line segments in sequence. The monitoring points on each isoradiation edge line first passed by all line segments constitute the monitoring point sequence. If the radiation intensity of all monitoring points in the monitoring point sequence increases sequentially at the time of analysis, then the candidate monitoring point is determined to belong to the radiation source at the time of analysis.

[0024] The first measurement accuracy of the candidate monitoring point at the time to be analyzed is obtained based on the distance between the radiation source to which the candidate monitoring point belongs and the radiation source to which each time in the neighborhood time window belongs, and the initial accuracy.

[0025] Preferably, the step of determining the change index of each monitoring point at each moment based on the changes in the location of the radiation source, the radiation intensity of the radiation source, and the relative distance between the radiation source and each monitoring point within a preset time period includes:

[0026] Normalized mutual information based on the Parzen window method is used as the registration algorithm to match radiation sources within a preset time period. Radiation sources with coordinate changes at adjacent times are recorded as dynamic radiation sources at the next time in the adjacent time period.

[0027] For the candidate monitoring point at the time to be analyzed, calculate the coordinate distance between each dynamic radiation source and the candidate monitoring point at the time to be analyzed, as well as the coordinate distance between each dynamic radiation source and the candidate monitoring point at the start of displacement at the time to be analyzed. Based on the coordinate distance between each dynamic radiation source and the candidate monitoring point at the time to be analyzed, the coordinate distance between each dynamic radiation source and the candidate monitoring point at the start of displacement at the time to be analyzed, and the radiation intensity of each dynamic radiation source at the time to be analyzed, obtain the change index of the candidate monitoring point at the time to be analyzed.

[0028] Preferably, the step of combining the differences in change indicators and radiation intensity at different monitoring points at each time moment to obtain the second measurement accuracy at each monitoring point at each time moment includes:

[0029] For candidate monitoring points at the time to be analyzed:

[0030] At the time to be analyzed, the second difference of the change index between the candidate monitoring point and other monitoring points is calculated. All the second differences are arranged in descending order to obtain the second difference sequence. The other monitoring points corresponding to the first preset number of elements in the second difference sequence are determined as similar monitoring points of the candidate monitoring point at the time to be analyzed.

[0031] The second measurement accuracy of the candidate monitoring point at the time of analysis is obtained based on the second difference between the candidate monitoring point and its similar monitoring points at the time to be analyzed and the difference in radiation intensity between the candidate monitoring point and its similar monitoring points at the time to be analyzed. Both the second difference between the candidate monitoring point and its similar monitoring points at the time to be analyzed and the difference in radiation intensity between the candidate monitoring point and its similar monitoring points at the time to be analyzed are negatively correlated with the second measurement accuracy.

[0032] Preferably, the step of combining the first measurement accuracy and the second measurement accuracy to screen abnormal moments of monitoring points includes:

[0033] The sum of the first measurement accuracy of the candidate monitoring point at the time to be analyzed and the second measurement accuracy of the candidate monitoring point at the time to be analyzed is determined as the comprehensive measurement accuracy of the candidate monitoring point at the time to be analyzed.

[0034] If the overall measurement accuracy is less than the preset accuracy threshold, then the time to be analyzed is determined to be an abnormal time for the candidate monitoring point.

[0035] Preferably, the step of correcting the radiation intensity at abnormal times by integrating the change indicators of each monitoring point with those of other monitoring points at each time moment, the local similarity, the first measurement accuracy, and the second measurement accuracy includes:

[0036] For the candidate monitoring point at the time to be analyzed: calculate the negative correlation normalization result of the difference between the change index of the candidate monitoring point at the time to be analyzed and the change index of the first abnormal time; based on the local similarity between the candidate monitoring point at the time to be analyzed and the first abnormal time, the comprehensive measurement accuracy of the candidate monitoring point at the time to be analyzed, and the negative correlation normalization result, obtain the reference degree of the candidate monitoring point at the time to be analyzed to the first abnormal time; if the reference degree is greater than a preset reference threshold, then the time to be analyzed is used as the reference time of the first abnormal time of the candidate monitoring point;

[0037] By combining the reference degree of all reference times of the candidate monitoring point at the first anomalous moment with the radiation intensity of all reference times of the candidate monitoring point at the first anomalous moment, the corrected radiation intensity of the candidate monitoring point at the first anomalous moment is obtained.

[0038] The first abnormal time is any abnormal time of the candidate monitoring point.

[0039] Preferably, the step of obtaining the reference level of the candidate monitoring point to be analyzed to the first abnormal time based on the local similarity between the candidate monitoring point to be analyzed time and the first abnormal time, the comprehensive measurement accuracy of the candidate monitoring point to be analyzed time, and the negative correlation normalization result includes:

[0040] The product of the local similarity between the candidate monitoring point to be analyzed and the first abnormal time, the comprehensive measurement accuracy of the candidate monitoring point to be analyzed, and the negative correlation normalization result is determined as the reference degree of the candidate monitoring point to be analyzed to the first abnormal time.

[0041] Secondly, the present invention provides a regional radiation monitoring instrument spectrum stabilization system, the system comprising:

[0042] The data acquisition module obtains the radiation intensity at different monitoring points in the monitoring area within a preset time period;

[0043] The first calculation module is used to project the radiation intensity of all monitoring points at each time moment onto a three-dimensional coordinate system, and determine several isoradiative edge lines in the three-dimensional coordinate system corresponding to each time moment based on the radiation intensity; according to the differences in the variation characteristics of radiation intensity in the local area of ​​each monitoring point at different times, the local similarity of each monitoring point at each time moment with other times moment is obtained; combining the differences in radiation intensity of each monitoring point at different times moment, the distribution characteristics of isoradiative edge lines and local similarity, the radiation source at each time moment and the first measurement accuracy of each monitoring point at each time moment are obtained.

[0044] The abnormal moment filtering module is used to determine the change index of each monitoring point at each moment based on the changes in the location of the radiation source, the radiation intensity of the radiation source, and the relative distance between the radiation source and each monitoring point within a preset time period; combined with the differences in the change index and radiation intensity of different monitoring points at each moment, the second measurement accuracy of each monitoring point at each moment is obtained; and the abnormal moments of the monitoring points are filtered by combining the first measurement accuracy and the second measurement accuracy.

[0045] The correction module is used to correct the radiation intensity at abnormal times by combining the change indicators of each monitoring point with those of other monitoring points at each time, the local similarity, the first measurement accuracy, and the second measurement accuracy; and to perform spectrum stabilization operation using the corrected radiation intensity.

[0046] The present invention has at least the following beneficial effects:

[0047] This invention addresses the problem of inaccurate radiation intensity monitoring in radiation monitoring areas, which affects subsequent spectrum stabilization. First, based on the radiation intensity of all monitoring points in the monitoring area at each moment within a preset time period, multiple isoradiative boundary lines are determined for each moment. Then, based on the differences in the variation characteristics of radiation intensity within the local area of ​​each monitoring point at different moments and the distribution characteristics of the isoradiative boundary lines, the static distribution characteristics of the radiation intensity of the monitoring points are evaluated, the radiation source at each moment is determined, and the first measurement accuracy of each monitoring point at each moment is obtained. Next, based on the changes in the location of the radiation source within the preset time period, the radiation intensity of the radiation source, and the relative distance between the radiation source and each monitoring point, the dynamic characteristics of the radiation intensity of the monitoring points changing over time are evaluated, and a second measurement accuracy of each monitoring point at each moment is obtained. Furthermore, by combining static and dynamic characteristics, abnormal moments of the monitoring points are screened, and the radiation intensity at abnormal moments is corrected by comprehensively considering the variation indicators of each monitoring point with other monitoring points at each moment, the local similarity of each monitoring point at each moment with other moments, and the first and second measurement accuracies. The corrected radiation intensity is then used for spectrum stabilization, improving the stabilization effect and facilitating long-term monitoring and accurate analysis of each monitoring point in the monitoring area. Attached Figure Description

[0048] 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.

[0049] Figure 1A flowchart illustrating a method for stabilizing the spectrum of a regional radiation monitoring instrument, provided in an embodiment of the present invention;

[0050] Figure 2 This is a structural block diagram of a regional radiation monitoring instrument spectrum stabilization system provided in an embodiment of the present invention. Detailed Implementation

[0051] To further illustrate the technical means and effects adopted by the present invention to achieve the intended purpose, the following detailed description of a regional radiation monitoring instrument spectrum stabilization method and system proposed according to the present invention is provided in conjunction with the accompanying drawings and preferred embodiments.

[0052] 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.

[0053] The following description, in conjunction with the accompanying drawings, details the specific scheme of the spectral stabilization method and system for a regional radiation monitoring instrument provided by the present invention.

[0054] An example of a spectral stabilization method for a regional radiation monitoring instrument:

[0055] The specific scenario addressed in this embodiment is as follows: During the spectral stabilization process of a radiation monitoring instrument, if there is a difference between the collected radiation intensity and the actual radiation intensity, it will directly affect the spectral stabilization effect. In areas such as nuclear medicine departments that require long-term monitoring of nuclear radiation intensity, due to changes in radiation sources, the existing method of using a cubic polynomial function as a temperature correction function for energy spectrum processing to remove temperature effects is not accurate enough, thus affecting the energy spectrum processing effect. This embodiment first analyzes the collected radiation intensity data, filters out the times when anomalies occur, and corrects the radiation intensity at the times when anomalies occur, making the obtained radiation intensity data more accurate, thereby improving the subsequent energy spectrum processing effect.

[0056] This embodiment proposes a method for stabilizing the spectrum of a regional radiation monitoring instrument, such as... Figure 1 As shown, a method for stabilizing the spectrum of a regional radiation monitoring instrument in this embodiment includes the following steps:

[0057] Step S1: Obtain the radiation intensity of different monitoring points in the monitoring area within a preset time period.

[0058] In this embodiment, multiple monitoring points are evenly distributed throughout the monitoring area, with one monitoring instrument placed at each point to monitor radiation intensity. The radiation intensity is collected once per minute, meaning that the radiation intensity of all monitoring points in the monitoring area is collected every minute. This embodiment collects the radiation intensity of each monitoring point in the monitoring area within a preset time period. In this embodiment, the preset time period is one month. In specific applications, the implementer can set the length of the preset time period and the radiation intensity collection frequency, as well as the number of monitoring points and the distance between them, according to specific circumstances.

[0059] Thus, this embodiment has collected the radiation intensity of each monitoring point in the monitoring area at each moment within a preset time period.

[0060] Step S2: Project the radiation intensity of all monitoring points at each time point onto the three-dimensional coordinate system, and determine several isoradiative edge lines in the three-dimensional coordinate system corresponding to each time point based on the radiation intensity; according to the differences in the variation characteristics of radiation intensity in the local area of ​​each monitoring point at different times, obtain the local similarity of each monitoring point at each time point with other times; combine the differences in radiation intensity of each monitoring point at different times point, the distribution characteristics of isoradiative edge lines, and local similarity to obtain the radiation source at each time point and the first measurement accuracy of each monitoring point at each time point.

[0061] Within the monitoring area, radiation sources exist, and the radiation intensity at each monitoring point decreases with increasing distance from the radiation source, thus exhibiting a certain distribution pattern. By analyzing the changes in radiation intensity at the monitoring points and the conformity to this distribution pattern, the static characteristics of the monitoring points can be obtained. Furthermore, the monitoring area may experience the movement of radiation sources, such as the use of nuclear radiation instruments, the storage and retrieval of radiation chemicals, and the movement of related personnel in nuclear medicine departments. Analyzing the regularity of radiation intensity changes and the existence of movement trajectories can yield the dynamic characteristics of the monitoring points. The combined static and dynamic characteristics characterize the accuracy of the monitoring data; therefore, by analyzing the degree to which a monitoring point conforms to both static and dynamic characteristics, the measurement accuracy of the monitoring point can be determined.

[0062] Because the monitoring points are evenly distributed within the monitoring area, some monitoring points have higher radiation intensities due to their proximity to the radiation source, while the radiation intensities of other monitoring points gradually decrease with increasing distance from the radiation source. If we consider the radiation intensity as the altitude of the monitoring points on a 3D map, then the 3D map contains several mountain-like regions, with the mountaintops representing the locations of the radiation sources. The altitude of each point on the mountain represents the elevation, which is also the radiation intensity. The contour lines on the 3D map are equivalent to isoradiometric boundaries. Therefore, a radiation intensity distribution map of the monitoring area at any given time can be drawn.

[0063] For any given moment within a preset time period: the radiation intensity of all monitoring points in the monitoring area at that moment is projected onto a three-dimensional Cartesian coordinate system. The origin O is the lower left corner of the monitoring area, the Y-axis points horizontally to the right, the X-axis points horizontally forward, and the Z-axis points vertically upward. The XOY plane represents the actual map of the monitoring area. The coordinates of any monitoring point are denoted as (x, y, z), where x is the distance between the monitoring point and the Y-axis, y is the distance between the monitoring point and the X-axis, and z is the radiation intensity of the monitoring point. In the constructed Cartesian coordinate system, based on the radiation intensity of each monitoring point, adjacent monitoring points with the same radiation intensity are connected by straight lines to obtain multiple curves. Each curve is recorded as an isoradioactive edge line, thus obtaining multiple isoradioactive edge lines. Using the above method, processing the three-dimensional Cartesian coordinate system corresponding to each moment within the preset time period yields multiple isoradioactive edge lines for each moment.

[0064] Starting from the monitoring points themselves, the radiation intensity fluctuates over time. By comparing the similarity of the fluctuations and values ​​of the radiation intensity at any given monitoring time in historical data, the accuracy of the monitoring data at the corresponding monitoring time can be analyzed. In addition, there is also similarity in the radiation intensity between monitoring points. The relationship between the radiation intensity between monitoring points can be obtained by analyzing the distribution of isoradiation edges. By analyzing whether the monitoring points conform to the regularity of radiation distribution, the accuracy of the measurement at the monitoring time can be determined.

[0065] The following embodiment uses a monitoring point within the monitoring area as an example for illustration. The method provided in this embodiment can be used to process other monitoring points.

[0066] Specifically, any monitoring point within the monitoring area is designated as a candidate monitoring point, and any two moments within a preset time period are designated as the first moment and the second moment, respectively. The slope difference between the lines connecting the radiation intensities of two adjacent moments within the neighborhood time window of the candidate monitoring point at the first moment and the second moment is calculated. Based on the difference in radiation intensities between corresponding moments within the neighborhood time window of the candidate monitoring point at the first moment and the second moment and the slope difference, the local similarity between the candidate monitoring point at the first moment and the second moment is obtained. The difference in radiation intensities between corresponding moments and the slope difference are both negatively correlated with the local similarity.

[0067] Among them, a negative correlation means that the dependent variable decreases as the independent variable increases, and the dependent variable increases as the independent variable decreases. It can be a subtraction relationship, a division relationship, etc., which is determined by the actual application.

[0068] In this embodiment, a specific formula for calculating local similarity is given. The local similarity between the candidate monitoring point at the first time and the second time can be expressed as:

[0069]

[0070] Where L represents the local similarity between the first and second moments of the candidate monitoring point, and I represents the number of moments within the neighborhood time window. Let represent the slope of the line connecting the radiation intensity at time i and the radiation intensity at time i+1 within the neighborhood time window of the candidate monitoring point at time i. Let represent the slope of the line connecting the radiation intensity at time i and the radiation intensity at time i+1 within the neighborhood time window of the candidate monitoring point at time i-2. This represents the radiation intensity at time i within the neighborhood time window of the candidate monitoring point at time i. Let represent the radiation intensity at time i within the neighborhood time window of the candidate monitoring point at time i, and exp() represent an exponential function with the natural constant as the base. Indicates the absolute value sign.

[0071] It should be noted that in this embodiment, the line connecting adjacent moments of radiation intensity is a straight line. For any moment within a preset time period, the process of obtaining the neighborhood time window for that moment is as follows: using that moment as the center moment of the window, obtain a window of a preset duration, and use this window as the neighborhood time window for that moment. In this embodiment, the preset duration is set to 11 minutes; in specific applications, the implementer can set it according to specific circumstances.

[0072] The slope of the line connecting the radiation intensity at time i and time i+1 within the neighborhood time window of the first time of the candidate monitoring point is different from the slope of the line connecting the radiation intensity at time i and time i+1 within the neighborhood time window of the second time. The larger the absolute value, the greater the difference in the slopes between the two. This is the sum of the slope differences of the lines connecting the radiation intensities of two adjacent moments within the neighborhood time window of the candidate monitoring point at the first and second moments. The smaller this value, the more similar the changing trends of the candidate monitoring point within the neighborhood time window at the first and second moments. The absolute value represents the difference between the radiation intensity at time i within the neighborhood time window of the first time and the radiation intensity at time i within the neighborhood time window of the second time. The larger the absolute value, the greater the difference in radiation intensity. This represents the sum of differences in radiation intensity between corresponding times within the neighborhood time window of the candidate monitoring point at times one and two. The smaller this value, the more similar the overall radiation intensity is within the neighborhood time window of the candidate monitoring point at times one and two. The smaller the sum of the differences in the slopes of the lines connecting the radiation intensities of two adjacent times within the neighborhood time window of the candidate monitoring point at times one and two, and the smaller the sum of the differences in radiation intensity between corresponding times within the neighborhood time window of the candidate monitoring point at times one and two, the more similar the radiation conditions are within the neighborhood time window of the candidate monitoring point at times one and two, i.e., the greater the local similarity between the candidate monitoring point at times one and two.

[0073] Using the above method, the local similarity between every two moments of the candidate monitoring points within the preset time period can be calculated. Next, the differences in radiation intensity, the distribution characteristics of isoradiation edge lines, and the local similarity of the candidate monitoring points at different moments will be combined to determine whether the location of the candidate monitoring point at each moment is a radiation source, and to make a preliminary evaluation of the accuracy of the monitoring data of the candidate monitoring points at each moment.

[0074] Specifically, for candidate monitoring points:

[0075] The following explanation uses any moment within a preset time period as an example. The method provided in this embodiment can be used for other moments within the preset time period. Any moment within the preset time period is designated as the moment to be analyzed. For the moment to be analyzed, if there are other isoradioactive edge lines within the isoradioactive edge line where the candidate monitoring point is located at the moment to be analyzed, the probability that the candidate monitoring point at the moment to be analyzed is a radiation source is set to 0. If there are no other isoradioactive edge lines within the isoradioactive edge line where the candidate monitoring point is located at the moment to be analyzed, the absolute value of the difference between the radiation intensity corresponding to the isoradioactive edge line where the candidate monitoring point is located at the moment to be analyzed and the radiation intensity corresponding to the nearest isoradioactive edge line is calculated. This absolute value is designated as the first difference, and the normalized result of the first difference is taken as the probability that the candidate monitoring point at the moment to be analyzed is a radiation source. Linear normalization can be used to normalize the first difference, ensuring the normalization result is within [0, 1]. Linear normalization is a prior art technique and will not be elaborated further here. If the probability is greater than a preset probability threshold, the candidate monitoring point is taken as the radiation source for the moment to be analyzed. In this embodiment, the probability threshold is set to 0.8. In specific applications, the implementer can set it according to the specific situation. It should be noted that if the isoradial edge line is a non-closed line segment, then it has no interior, and therefore there are no other isoradial edge lines inside it.

[0076] For the candidate monitoring point to be analyzed time: the local similarity of the candidate monitoring point to be analyzed time with each other time is sorted in descending order of local similarity to obtain the local similarity sequence of the candidate monitoring point to be analyzed time; the first preset number of time in the local similarity sequence is taken as the similar time of the candidate monitoring point to be analyzed time, that is, multiple similar time of the candidate monitoring point to be analyzed time are selected from the preset time period; in this embodiment, the preset number is 10, and in specific applications, the implementer can set it according to the specific situation.

[0077] The initial accuracy of the candidate monitoring point at the time to be analyzed is obtained based on the local similarity between the candidate monitoring point at the time to be analyzed and each of its similar times, and the difference in radiation intensity between the candidate monitoring point at the time to be analyzed and each of its similar times. The local similarity between the candidate monitoring point at the time to be analyzed and each of its similar times, and the difference in radiation intensity between the candidate monitoring point at the time to be analyzed and each of its similar times are both negatively correlated with the initial accuracy.

[0078] Among them, a negative correlation means that the dependent variable decreases as the independent variable increases, and the dependent variable increases as the independent variable decreases. It can be a subtraction relationship, a division relationship, etc., which is determined by the actual application.

[0079] In this embodiment, a specific formula for calculating the initial accuracy is given. The initial accuracy of the candidate monitoring point at the time of analysis can be expressed as:

[0080]

[0081] in, This represents the initial accuracy of the candidate monitoring point at the time to be analyzed, where M is the number of similar times for the candidate monitoring point at the time to be analyzed. This indicates the radiation intensity at the candidate monitoring point at the time of analysis. This represents the radiation intensity at the m-th similar moment of the time to be analyzed at the candidate monitoring point. This represents the local similarity between the candidate monitoring point at the time to be analyzed and its m-th similar time. The symbol indicates the absolute value, and exp() represents an exponential function with the natural constant as the base.

[0082] This value characterizes the difference in radiation intensity between the candidate monitoring point at the time of analysis and its m-th similar time. A larger value indicates a greater difference in radiation intensity between the two times. Using the local similarity between the candidate monitoring point at the time of analysis and its similar times as weights, a weighted sum is calculated on the differences in radiation intensity between these two times. A smaller difference in radiation intensity between the candidate monitoring point at the time of analysis and its similar times indicates higher accuracy of the monitoring data at that time, meaning a greater initial accuracy.

[0083] For any given radiation source, candidate monitoring points are connected to the source via line segments. Starting from a candidate monitoring point, the process iterates along each line segment sequentially. The monitoring points on each isoradiation edge line first crossed by the line segment constitute a monitoring point sequence. If the radiation intensity of all monitoring points in the sequence increases sequentially at the time of analysis, then the candidate monitoring point at the time of analysis belongs to that radiation source. This method can be used to screen multiple radiation sources to which candidate monitoring points belong at the time of analysis.

[0084] The first measurement accuracy of the candidate monitoring point at the time to be analyzed is obtained based on the distance between the radiation source to which the candidate monitoring point belongs and the radiation source to which each time in the neighborhood time window belongs, and the initial accuracy.

[0085] In this embodiment, a specific formula for calculating the first measurement accuracy is given. The first measurement accuracy of the candidate monitoring point at the time to be analyzed can be expressed as:

[0086]

[0087] in, This indicates the first measurement accuracy of the candidate monitoring point at the time to be analyzed. The initial accuracy of the candidate monitoring point at the time to be analyzed is represented by I, where I represents the number of times within the neighborhood time window, and H represents the number of radiation sources to which the candidate monitoring point belongs at the time to be analyzed. This indicates the h-th radiation source to which the candidate monitoring point belongs at the time to be analyzed. This represents the radiation source that is closest to the h-th radiation source at the i-th time interval of the candidate monitoring point within the neighborhood time window of the time to be analyzed. This indicates the calculation of the distance function. express and The distance between them.

[0088] It adds the distances of all radiation sources at the candidate monitoring point at the time to be analyzed to the nearest radiation source corresponding to all radiation sources at each monitoring time within the neighborhood time window. This represents the positional change of the radiation sources within the neighborhood time window. The smaller this value, the less the positional change, and therefore the higher the accuracy of the first measurement at the candidate monitoring point at the time to be analyzed.

[0089] Using the above method, the radiation source at each moment within a preset time period can be screened out, and the first measurement accuracy of each monitoring point in the monitoring area at each moment within the preset time period can be calculated.

[0090] Step S3: Based on the changes in the location of the radiation source, the radiation intensity of the radiation source, and the relative distance between the radiation source and each monitoring point within a preset time period, determine the change index of each monitoring point at each moment; combine the differences in the change index and radiation intensity of different monitoring points at each moment to obtain the second measurement accuracy of each monitoring point at each moment; combine the first measurement accuracy and the second measurement accuracy to screen abnormal moments of the monitoring points.

[0091] The monitoring area involves ventilation, storage and retrieval of radiation drugs, and personnel movement. Therefore, evaluating the accuracy of monitoring data solely from a static perspective is insufficient. By analyzing the changes in radiation sources over time, the dynamic characteristics of monitoring points affected by these radiation sources can be obtained. When a radiation source approaches, the radiation intensity at the monitoring point also increases. Therefore, the more regular the changes in radiation sources, the higher the measurement accuracy.

[0092] Normalized mutual information based on the Parzen window method is used as the registration algorithm to match radiation sources within a preset time period. Radiation sources with coordinate changes at adjacent times are recorded as dynamic radiation sources at the next time in the adjacent time period.

[0093] The following explanation uses candidate monitoring points as an example. For the time to be analyzed of a candidate monitoring point, the coordinate distance between each dynamic radiation source and the candidate monitoring point at the time to be analyzed, as well as the coordinate distance between each dynamic radiation source and the candidate monitoring point at the start of displacement at the time to be analyzed, are calculated. Based on the coordinate distance between each dynamic radiation source and the candidate monitoring point at the time to be analyzed, the coordinate distance between each dynamic radiation source and the candidate monitoring point at the start of displacement at the time to be analyzed, and the radiation intensity of each dynamic radiation source at the time to be analyzed, the change index of the candidate monitoring point at the time to be analyzed is obtained.

[0094] The change indicators of candidate monitoring points at the time of analysis can be expressed as:

[0095]

[0096] Where E represents the change index of the candidate monitoring point at the time to be analyzed, and C represents the number of dynamic radiation sources at the time to be analyzed. Let represent the radiation intensity of the c-th dynamic radiation source at the time to be analyzed. This represents the coordinate distance between the c-th dynamic radiation source at the moment of analysis and the candidate monitoring point at the start of its displacement. The coordinate distance between the c-th dynamic radiation source and the candidate monitoring point at the time to be analyzed is represented by , and norm() represents the normalization function.

[0097] This means that the distance between each dynamic radiation source and the point at which displacement begins before the analysis time is weighted by the radiation intensity of the dynamic radiation source. The closer the distance becomes and the stronger the radiation intensity becomes, the greater the change index for the candidate monitoring point.

[0098] For candidate monitoring points at the time to be analyzed:

[0099] At the time to be analyzed, the absolute value of the difference between the change index of the candidate monitoring point and each other monitoring point is calculated, and this absolute value is recorded as the second difference. The second differences between the candidate monitoring point and all other monitoring points are arranged in descending order to obtain the second difference sequence. The other monitoring points corresponding to the first preset number of elements in the second difference sequence are determined as similar monitoring points of the candidate monitoring point at the time to be analyzed. Using this method, multiple similar monitoring points of the candidate monitoring point at the time to be analyzed can be screened out. In this embodiment, the preset number is 10. In specific applications, the implementer can set it according to the specific situation.

[0100] Next, based on the second difference between the candidate monitoring point and its similar monitoring points at the time to be analyzed and the difference in radiation intensity between the candidate monitoring point and its similar monitoring points at the time to be analyzed, the second measurement accuracy of the candidate monitoring point at the time to be analyzed is obtained. The second difference between the candidate monitoring point and its similar monitoring points at the time to be analyzed and the difference in radiation intensity between the candidate monitoring point and its similar monitoring points at the time to be analyzed are both negatively correlated with the second measurement accuracy.

[0101] Among them, a negative correlation means that the dependent variable decreases as the independent variable increases, and the dependent variable increases as the independent variable decreases. It can be a subtraction relationship, a division relationship, etc., which is determined by the actual application.

[0102] In this embodiment, a specific formula for calculating the second measurement accuracy is given. The second measurement accuracy of the candidate monitoring point at the time to be analyzed can be expressed as:

[0103]

[0104] in, The second measurement accuracy of the candidate monitoring point at the time of analysis is represented by U, the number of similar monitoring points at the time of analysis of the candidate monitoring point is represented by E, and the change index of the candidate monitoring point at the time of analysis is represented by E. Indicators representing changes in similar monitoring points at the time the candidate monitoring point is to be analyzed. This indicates the radiation intensity at the candidate monitoring point at the time of analysis. This represents the radiation intensity of the u-th similar monitoring point at the time to be analyzed from the candidate monitoring point. The symbol indicates the absolute value, and exp() represents an exponential function with the natural constant as the base.

[0105] In this embodiment, adding 0.1 to the denominator of the second measurement accuracy calculation formula is to prevent the denominator from being 0. This value is used to characterize the similarity of the change index between a candidate monitoring point and its u-th similar monitoring point at the time of analysis. The larger the value, the more similar the change index, the stronger the reference value of the corresponding monitoring point, and the greater its weight. The smaller the difference in radiation intensity between the candidate monitoring point and its similar monitoring points at the time of analysis, the stronger the accuracy of the second measurement.

[0106] Using the above method, the first and second measurement accuracies of the candidate monitoring point at the time of analysis were obtained. These accuracies characterize the accuracy of the monitoring data at the candidate monitoring point at the time of analysis from both static and dynamic perspectives, respectively. A higher value for either the static or dynamic measurement accuracy indicates higher measurement accuracy at that monitoring point. Therefore, the sum of the first and second measurement accuracies of the candidate monitoring point at the time of analysis is determined as the comprehensive measurement accuracy of the candidate monitoring point at the time of analysis. If the comprehensive measurement accuracy is less than a preset accuracy threshold, the time of analysis is determined to be an abnormal time for the candidate monitoring point. In this embodiment, the preset accuracy threshold is 0.95; however, in specific applications, the implementer can set this threshold according to specific circumstances.

[0107] Using the above method, it is possible to filter out abnormal moments for each monitoring point in the monitoring area within a preset time period.

[0108] Step S4: Based on the changes in each monitoring point and other monitoring points at each time, the local similarity, the first measurement accuracy, and the second measurement accuracy, the radiation intensity at abnormal times is corrected; the corrected radiation intensity is used for spectrum stabilization.

[0109] For any monitoring point at any monitoring time, the radiation intensity data at monitoring times with high similarity in neighboring time windows, high similarity in change indicators, and high accuracy can better represent the radiation intensity of the monitoring point at the corresponding monitoring time. Therefore, the data at times with lower accuracy can be replaced by the radiation intensity data at these monitoring times.

[0110] Specifically, for the candidate monitoring points at the time to be analyzed:

[0111] Next, we will analyze any abnormal moment of a candidate monitoring point as an example. We will denote any abnormal moment of a candidate monitoring point as the first abnormal moment, and calculate the negative correlation normalization result of the difference between the change index of the candidate monitoring point at the time to be analyzed and the change index of the first abnormal moment. The product of the local similarity between the candidate monitoring point at the time to be analyzed and the first abnormal moment, the comprehensive measurement accuracy of the candidate monitoring point at the time to be analyzed, and the negative correlation normalization result will be determined as the reference degree of the candidate monitoring point at the time to be analyzed to the first abnormal moment. The reference degree of the candidate monitoring point at the time to be analyzed to the first abnormal moment can be expressed as:

[0112]

[0113] Where W represents the reference level of the candidate monitoring point at the time to be analyzed to the first abnormal time, and K represents the overall measurement accuracy of the candidate monitoring point at the time to be analyzed. This indicates the local similarity between the candidate monitoring point at the time to be analyzed and the first anomaly time, where E represents the change index of the candidate monitoring point at the time to be analyzed. The expression represents the change index of the candidate monitoring point at the first anomaly time, and exp() represents the exponential function with the natural constant as the base. Indicates the absolute value sign.

[0114] The difference between the change index of the candidate monitoring point at the time of analysis and the change index at the first abnormal time is characterized. The negative correlation normalization result characterizes the difference between the change index of the candidate monitoring point at the time of analysis and the change index of the first anomalous time. The higher the comprehensive measurement accuracy of the candidate monitoring point at the time of analysis, the higher the local similarity between the candidate monitoring point at the time of analysis and the first anomalous time, and the smaller the difference between the change index of the candidate monitoring point at the time of analysis and the change index of the first anomalous time, the greater the reference value of the monitoring data of the candidate monitoring point at the time of analysis for the first anomalous time, that is, the greater the reference degree of the candidate monitoring point at the time of analysis for the first anomalous time.

[0115] If the reference value of the candidate monitoring point's time to be analyzed to the first abnormal time is greater than the preset reference threshold, then the time to be analyzed will be used as the reference time for the first abnormal time of the candidate monitoring point. The preset reference threshold is set by the implementer according to the specific circumstances.

[0116] Using the above method, multiple reference times for the first abnormal moment of the candidate monitoring point can be selected.

[0117] Next, by combining the reference degree of all reference times of the candidate monitoring point at the first anomalous moment with the radiation intensity of all reference times of the candidate monitoring point at the first anomalous moment, the corrected radiation intensity of the candidate monitoring point at the first anomalous moment is obtained.

[0118] In this embodiment, a specific formula for calculating the corrected radiation intensity is given. The corrected radiation intensity at the first anomaly moment of the candidate monitoring point can be expressed as:

[0119]

[0120] in, This represents the radiation intensity corrected for the first anomalous moment at the candidate monitoring point, where A represents the number of reference moments for the first anomalous moment at the candidate monitoring point. This indicates the degree of reference of the a-th reference time to the first anomalous time at the candidate monitoring point. This represents the radiation intensity at the a-th reference time when the candidate monitoring point is at the first anomalous time.

[0121] In this embodiment, the radiation intensity at each abnormal moment of a candidate monitoring point is weighted by the reference degree, and the radiation intensity at all reference moments is weighted and averaged. This corrects the abnormal monitoring data and obtains the corrected radiation intensity.

[0122] Using the method provided in this embodiment, the radiation intensity at abnormal moments within a preset time period of all monitoring points in the monitoring area is corrected, and the corrected radiation intensity is obtained.

[0123] In subsequent spectrum stabilization operations on the radiation monitor, the existing spectrum stabilization methods were directly applied based on the corrected radiation intensity, eliminating interference from abnormal data and effectively ensuring the spectrum stabilization effect.

[0124] To address the issue of inaccurate radiation intensity monitoring in radiation monitoring areas, which affects subsequent spectrum stabilization, this embodiment first determines multiple isoradiative boundary lines corresponding to each moment based on the radiation intensity of all monitoring points in the monitoring area at each moment within a preset time period. Then, based on the differences in the variation characteristics of radiation intensity in the local area of ​​each monitoring point at different moments and the distribution characteristics of the isoradiative boundary lines, the static distribution characteristics of the radiation intensity of the monitoring points are evaluated, the radiation source at each moment is determined, and the first measurement accuracy of each monitoring point at each moment is obtained. Next, based on the changes in the position of the radiation source, the radiation intensity of the radiation source, and the relative distance between the radiation source and each monitoring point within the preset time period, the dynamic characteristics of the radiation intensity of the monitoring points changing over time are evaluated, and the second measurement accuracy of each monitoring point at each moment is obtained. Furthermore, by combining static and dynamic characteristics, abnormal moments of the monitoring points are screened, and the radiation intensity of abnormal moments is corrected by comprehensively considering the change indicators of each monitoring point and other monitoring points at each moment, the local similarity of each monitoring point at each moment with other moments, and the first and second measurement accuracies. Subsequently, the corrected radiation intensity is used for spectrum stabilization operations, which improves the spectrum stabilization effect and is beneficial for long-term monitoring and accurate analysis of each monitoring point in the monitoring area.

[0125] An embodiment of a regional radiation monitoring instrument spectrum stabilization system:

[0126] See Figure 2 The diagram illustrates a structural block diagram of a regional radiation monitoring spectrum stabilization system provided in an embodiment of the present invention. The system may include a data acquisition module, a first calculation module, an abnormal time screening module, and a correction module.

[0127] The data acquisition module obtains the radiation intensity of different monitoring points in the monitoring area within a preset time period.

[0128] The first calculation module is used to project the radiation intensity of all monitoring points at each time moment onto a three-dimensional coordinate system, and determine several isoradiative edge lines in the three-dimensional coordinate system corresponding to each time moment based on the radiation intensity; according to the differences in the variation characteristics of radiation intensity in the local area of ​​each monitoring point at different times, the local similarity of each monitoring point at each time moment with other times moment is obtained; combining the differences in radiation intensity of each monitoring point at different times moment, the distribution characteristics of isoradiative edge lines and local similarity, the radiation source at each time moment and the first measurement accuracy of each monitoring point at each time moment are obtained.

[0129] The abnormal moment filtering module is used to determine the change index of each monitoring point at each moment based on the changes in the location of the radiation source, the radiation intensity of the radiation source, and the relative distance between the radiation source and each monitoring point within a preset time period; combined with the differences in the change index and radiation intensity of different monitoring points at each moment, the second measurement accuracy of each monitoring point at each moment is obtained; and the abnormal moments of the monitoring points are filtered by combining the first measurement accuracy and the second measurement accuracy.

[0130] The correction module is used to correct the radiation intensity at abnormal times by combining the change indicators of each monitoring point with those of other monitoring points at each time, the local similarity, the first measurement accuracy, and the second measurement accuracy; and to perform spectrum stabilization operation using the corrected radiation intensity.

[0131] It should be understood that Figure 2 The structural block diagram and modules of the regional radiation monitoring spectrum stabilization system shown can be implemented in various ways. For example, in some embodiments, the system and its modules can be implemented by hardware, software, or a combination of both. The hardware portion can be implemented using dedicated logic; the software portion can be stored in memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated hardware. Those skilled in the art will understand that the above-described methods and systems can be implemented using computer-executable instructions and / or included in processor control code, for example, on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The systems and modules of this specification can be implemented not only by hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field-programmable gate arrays, programmable logic devices, etc., but also by software executed by various types of processors, or by a combination of the above-described hardware circuits and software (e.g., firmware).

[0132] For more details about the above modules, please refer to other parts of this manual; they will not be repeated here.

[0133] In other embodiments, a regional radiation monitoring spectrum stabilization system device is also provided, including a memory and a processor. The memory stores executable program code, and the processor calls and runs the executable program code from the memory, causing the device to execute the welding control method applied to a pulse welding machine described above. Specifically, the device may be a chip, component, or module. The chip may include a connected processor and memory; wherein the memory stores instructions, and when the processor calls and executes the instructions, the chip can execute the regional radiation monitoring spectrum stabilization method provided in the above embodiments.

[0134] In other embodiments, a computer program product is also provided, which, when run on a computer, causes the computer to perform the aforementioned related steps to implement the regional radiation monitoring spectrum stabilization method provided in the above embodiments.

[0135] In other embodiments, a computer-readable storage medium is also provided, which stores computer program code. When the computer program code is run on a computer, the computer performs the above-described method steps to implement the regional radiation monitoring spectrum stabilization method provided in the above embodiments.

[0136] The systems, electronic devices, computer program products, and computer-readable storage media provided are all used to execute the corresponding methods provided above. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects of the corresponding methods provided above, and will not be repeated here.

[0137] It should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for stabilizing the spectrum of a regional radiation monitoring instrument, characterized in that, The method includes the following steps: Obtain the radiation intensity at different monitoring points in the monitoring area within a preset time period; The radiation intensity of all monitoring points at each time moment is projected onto a three-dimensional coordinate system, and several isoradiative edge lines in the three-dimensional coordinate system corresponding to each time moment are determined based on the radiation intensity. According to the difference in the variation characteristics of radiation intensity in the local area of ​​each monitoring point at different times, the local similarity of each monitoring point at each time moment with other times moment is obtained. Combining the difference in radiation intensity of each monitoring point at different times moment, the distribution characteristics of isoradiative edge lines and local similarity, the radiation source at each time moment and the first measurement accuracy of each monitoring point at each time moment are obtained. Based on the changes in the location of the radiation source, the radiation intensity of the radiation source, and the relative distance between the radiation source and each monitoring point within a preset time period, the change index of each monitoring point at each moment is determined; combined with the differences in the change index and radiation intensity of different monitoring points at each moment, the second measurement accuracy of each monitoring point at each moment is obtained; and the abnormal moments of the monitoring points are screened by combining the first measurement accuracy and the second measurement accuracy. By combining the change indicators of each monitoring point with those of other monitoring points at each time, the local similarity, the first measurement accuracy, and the second measurement accuracy, the radiation intensity at abnormal times is corrected; the corrected radiation intensity is then used for spectrum stabilization.

2. The spectral stabilization method for a regional radiation monitoring instrument according to claim 1, characterized in that, The method of obtaining the local similarity between each monitoring point at each time and other times based on the differences in the variation characteristics of radiation intensity within the local area at different times includes: Calculate the difference in slope between the lines connecting the radiation intensities of two adjacent moments within the neighborhood time window of the candidate monitoring point at the first and second moments, respectively. Based on the difference in radiation intensity and the slope difference between corresponding moments within the neighborhood time window of the first and second moments of the candidate monitoring point, the local similarity between the first and second moments of the candidate monitoring point is obtained. The difference in radiation intensity and the slope difference between the corresponding moments are negatively correlated with the local similarity. The candidate monitoring point can be any monitoring point, and the first time and the second time are any two times within a preset time period.

3. The spectral stabilization method for a regional radiation monitoring instrument according to claim 2, characterized in that, By combining the differences in radiation intensity at each monitoring point at different times, the distribution characteristics of isoradiative boundary lines, and local similarities, the radiation source at each time moment is obtained, including: For candidate monitoring points: If there are other isoradioactive boundary lines inside the isoradioactive boundary line where the candidate monitoring point is located at the time of analysis, then the probability that the candidate monitoring point is a radiation source at the time of analysis is set to 0; if there are no other isoradioactive boundary lines inside the isoradioactive boundary line where the candidate monitoring point is located at the time of analysis, then the first difference between the radiation intensity corresponding to the isoradioactive boundary line where the candidate monitoring point is located at the time of analysis and the radiation intensity corresponding to the isoradioactive boundary line closest to the candidate monitoring point is located at the time of analysis is calculated, and the normalized result of the first difference is taken as the probability that the candidate monitoring point is a radiation source at the time of analysis. If the probability is greater than a preset probability threshold, then the candidate monitoring point will be used as the radiation source at the time to be analyzed. The time to be analyzed is any time within a preset time period.

4. The spectral stabilization method for a regional radiation monitoring instrument according to claim 3, characterized in that, The acquisition of the first measurement accuracy at each monitoring point at each time moment includes: For candidate monitoring points at the time to be analyzed: The local similarity of the candidate monitoring point to be analyzed time with each other time is sorted in descending order of local similarity to obtain the local similarity sequence of the candidate monitoring point to be analyzed time; the first preset number of time moments in the local similarity sequence are taken as the similar time moments of the candidate monitoring point to be analyzed time. The initial accuracy of the candidate monitoring point at the time to be analyzed is obtained based on the local similarity between the candidate monitoring point at the time to be analyzed and each of its similar times, and the difference in radiation intensity between the candidate monitoring point at the time to be analyzed and each of its similar times. The local similarity between the candidate monitoring point at the time to be analyzed and each of its similar times, and the difference in radiation intensity between the candidate monitoring point at the time to be analyzed and each of its similar times are both negatively correlated with the initial accuracy. For any radiation source, candidate monitoring points are connected to the radiation source by line segments. Starting from the candidate monitoring point, the monitoring points are traversed along the line segments in sequence. The monitoring points on each isoradiation edge line first passed by all line segments constitute the monitoring point sequence. If the radiation intensity of all monitoring points in the monitoring point sequence increases sequentially at the time of analysis, then the candidate monitoring point is determined to belong to the radiation source at the time of analysis. The first measurement accuracy of the candidate monitoring point at the time to be analyzed is obtained based on the distance between the radiation source to which the candidate monitoring point belongs and the radiation source to which each time in the neighborhood time window belongs, and the initial accuracy.

5. The spectral stabilization method for a regional radiation monitoring instrument according to claim 3, characterized in that, The step of determining the change index of each monitoring point at each moment based on the changes in the location of the radiation source, the radiation intensity of the radiation source, and the relative distance between the radiation source and each monitoring point within a preset time period includes: Normalized mutual information based on the Parzen window method is used as the registration algorithm to match radiation sources within a preset time period. Radiation sources with coordinate changes at adjacent times are recorded as dynamic radiation sources at the next time in the adjacent time period. For the candidate monitoring point at the time to be analyzed, calculate the coordinate distance between each dynamic radiation source and the candidate monitoring point at the time to be analyzed, as well as the coordinate distance between each dynamic radiation source and the candidate monitoring point at the start of displacement at the time to be analyzed. Based on the coordinate distance between each dynamic radiation source and the candidate monitoring point at the time to be analyzed, the coordinate distance between each dynamic radiation source and the candidate monitoring point at the start of displacement at the time to be analyzed, and the radiation intensity of each dynamic radiation source at the time to be analyzed, obtain the change index of the candidate monitoring point at the time to be analyzed.

6. The spectral stabilization method for a regional radiation monitoring instrument according to claim 3, characterized in that, The second measurement accuracy for each monitoring point at each moment is obtained by combining the differences in changing indicators and radiation intensity at different monitoring points at each time point, including: For candidate monitoring points at the time to be analyzed: At the time to be analyzed, the second difference of the change index between the candidate monitoring point and other monitoring points is calculated. All the second differences are arranged in descending order to obtain the second difference sequence. The other monitoring points corresponding to the first preset number of elements in the second difference sequence are determined as similar monitoring points of the candidate monitoring point at the time to be analyzed. The second measurement accuracy of the candidate monitoring point at the time of analysis is obtained based on the second difference between the candidate monitoring point and its similar monitoring points at the time to be analyzed and the difference in radiation intensity between the candidate monitoring point and its similar monitoring points at the time to be analyzed. Both the second difference between the candidate monitoring point and its similar monitoring points at the time to be analyzed and the difference in radiation intensity between the candidate monitoring point and its similar monitoring points at the time to be analyzed are negatively correlated with the second measurement accuracy.

7. The spectral stabilization method for a regional radiation monitoring instrument according to claim 3, characterized in that, The process of combining the first measurement accuracy and the second measurement accuracy to screen abnormal moments of monitoring points includes: The sum of the first measurement accuracy of the candidate monitoring point at the time to be analyzed and the second measurement accuracy of the candidate monitoring point at the time to be analyzed is determined as the comprehensive measurement accuracy of the candidate monitoring point at the time to be analyzed. If the overall measurement accuracy is less than the preset accuracy threshold, then the time to be analyzed is determined to be an abnormal time for the candidate monitoring point.

8. The spectral stabilization method for a regional radiation monitoring instrument according to claim 7, characterized in that, The correction of radiation intensity at abnormal times, based on the combined changes of each monitoring point with other monitoring points at each time moment, the local similarity, the first measurement accuracy, and the second measurement accuracy, includes: For the candidate monitoring point at the time to be analyzed: calculate the negative correlation normalization result of the difference between the change index of the candidate monitoring point at the time to be analyzed and the change index of the first abnormal time; based on the local similarity between the candidate monitoring point at the time to be analyzed and the first abnormal time, the comprehensive measurement accuracy of the candidate monitoring point at the time to be analyzed, and the negative correlation normalization result, obtain the reference degree of the candidate monitoring point at the time to be analyzed to the first abnormal time; if the reference degree is greater than a preset reference threshold, then the time to be analyzed is used as the reference time of the first abnormal time of the candidate monitoring point; By combining the reference degree of all reference times of the candidate monitoring point at the first anomalous moment with the radiation intensity of all reference times of the candidate monitoring point at the first anomalous moment, the corrected radiation intensity of the candidate monitoring point at the first anomalous moment is obtained. The first abnormal time is any abnormal time of the candidate monitoring point.

9. The spectral stabilization method for a regional radiation monitoring instrument according to claim 8, characterized in that, The step of obtaining the reference level of the candidate monitoring point's analysis time to the first anomalous time based on the local similarity between the candidate monitoring point's analysis time and the first anomalous time, the comprehensive measurement accuracy of the candidate monitoring point's analysis time, and the negative correlation normalization result includes: The product of the local similarity between the candidate monitoring point to be analyzed and the first abnormal time, the comprehensive measurement accuracy of the candidate monitoring point to be analyzed, and the negative correlation normalization result is determined as the reference degree of the candidate monitoring point to be analyzed to the first abnormal time.

10. A spectral stabilization system for a regional radiation monitoring instrument, characterized in that, The system includes: The data acquisition module obtains the radiation intensity at different monitoring points in the monitoring area within a preset time period; The first calculation module is used to project the radiation intensity of all monitoring points at each time moment onto a three-dimensional coordinate system, and determine several isoradiative edge lines in the three-dimensional coordinate system corresponding to each time moment based on the radiation intensity; according to the differences in the variation characteristics of radiation intensity in the local area of ​​each monitoring point at different times, the local similarity of each monitoring point at each time moment with other times moment is obtained; combining the differences in radiation intensity of each monitoring point at different times moment, the distribution characteristics of isoradiative edge lines and local similarity, the radiation source at each time moment and the first measurement accuracy of each monitoring point at each time moment are obtained. The abnormal moment filtering module is used to determine the change index of each monitoring point at each moment based on the changes in the location of the radiation source, the radiation intensity of the radiation source, and the relative distance between the radiation source and each monitoring point within a preset time period; combined with the differences in the change index and radiation intensity of different monitoring points at each moment, the second measurement accuracy of each monitoring point at each moment is obtained; and the abnormal moments of the monitoring points are filtered by combining the first measurement accuracy and the second measurement accuracy. The correction module is used to correct the radiation intensity at abnormal times by combining the change indicators of each monitoring point with those of other monitoring points at each time, the local similarity, the first measurement accuracy, and the second measurement accuracy; and to perform spectrum stabilization operation using the corrected radiation intensity.

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