Radiation detection method and system based on adaptive dead time correction

Abstract

The invention relates to the technical field of radiation detection, and provides a radiation detection method and system based on adaptive dead time correction, and the method comprises the steps: obtaining a pulse signal of a radiation detector, and carrying out the preprocessing of the pulse signal, and obtaining initial counting rate data; selecting an initial dead time correction coefficient from a preset correction coefficient library according to a current counting rate range of the initial counting rate data; performing online adjustment on the initial dead time correction coefficient by adopting a self-adaptive algorithm to obtain an adjusted dead time correction coefficient; environment parameters are collected, compensation adjustment is carried out on the adjustment dead time correction coefficient according to the environment parameters, and a compensation dead time correction coefficient is obtained; correcting the initial counting rate data based on the compensation dead time correction coefficient to obtain corrected counting rate data; and converting the corrected counting rate data into radiation dose rate data, and judging whether to trigger an alarm or not according to a preset radiation dose rate threshold value. The accuracy and reliability of radiation detection in the fields of nuclear safety monitoring, emergency response and the like are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of radiation detection, and in particular, to a radiation detection method and system based on adaptive dead time correction. Background Art

[0002] Radiation detection is an important technical means in the fields of radiation protection, nuclear emergency monitoring, medical diagnosis, etc. The core is to accurately measure the intensity and distribution of the radiation field. When traditional radiation detectors receive radiation particles, they will generate electrical pulse signals, and the radiation intensity is deduced by counting these pulses. However, in practical applications, there is inevitably a "dead time" effect in the radiation detection system - that is, during the period when the detector processes a pulse signal, it cannot respond to newly arrived radiation particles, resulting in count loss, especially more significant in high count rate environments. This dead time effect will cause non-linear distortion of the measurement results and seriously affect the accuracy of radiation dose assessment.

[0003] The existing technologies mainly use the fixed parameter correction method, the two-source method, and the analytical model method for dead time correction. Although the basic count loss compensation function is achieved, these methods have obvious defects such as static parameters being unable to cope with dynamic changing count rates, ignoring the influence of environmental factors (such as temperature and energy spectrum distribution), lacking adaptive optimization ability and effective data processing mechanisms. As a result, the correction effect is significantly reduced in complex radiation fields, rapidly changing environments, and scenarios with high-precision measurement requirements, unable to accurately evaluate the radiation dose, and affecting the timeliness and accuracy of radiation protection decisions. Summary of the Invention

[0004] In view of this, the present invention proposes a radiation detection method and system based on adaptive dead time correction, which solves the obvious defects of the existing technologies that static parameters cannot cope with dynamic changing count rates, ignore the influence of environmental factors (such as temperature and energy spectrum distribution), lack adaptive optimization ability and effective data processing mechanisms, resulting in a significant reduction in the correction effect in complex radiation fields, rapidly changing environments, and scenarios with high-precision measurement requirements, being unable to accurately evaluate the radiation dose, and affecting the timeliness and accuracy of radiation protection decisions.

[0005] The technical solution of the present invention is implemented as follows: In the first aspect, the present invention provides a radiation detection method based on adaptive dead time correction, including the following steps:

[0006] Obtain the pulse signal of the radiation detector and perform preprocessing to obtain the initial count rate data;

[0007] According to the current count rate range of the initial count rate data, select the initial dead time correction coefficient from the preset correction coefficient library;

[0008] An adaptive algorithm is used to adjust the initial dead time correction coefficient online to obtain an adjusted dead time correction coefficient;

[0009] Environmental parameters are collected, and the adjusted dead time correction coefficient is compensated and adjusted according to the environmental parameters to obtain a compensated dead time correction coefficient;

[0010] Based on the compensated dead time correction coefficient, the initial count rate data is corrected to obtain corrected count rate data;

[0011] The corrected count rate data is converted into radiation dose rate data, and it is judged whether to trigger an alarm according to a preset radiation dose rate threshold.

[0012] On the basis of the above technical solutions, preferably, the obtaining the pulse signal of the radiation detector and performing preprocessing to obtain initial count rate data includes:

[0013] The pulse signal of the radiation detector is denoised and waveform analyzed to improve the pulse recognition rate and obtain a highly recognizable pulse signal;

[0014] The highly recognizable pulse signals are classified according to energy magnitude and counted to obtain initial count rate data.

[0015] On the basis of the above technical solutions, preferably, the selecting the initial dead time correction coefficient from a preset correction coefficient library according to the current count rate range of the initial count rate data includes:

[0016] The current count rate range where the initial count rate data is located is mapped to one of a plurality of predefined count rate intervals;

[0017] The full-range count rate measurement range of the radiation detector is divided into a plurality of continuous and non-overlapping count rate intervals. An interval identifier is set for each count rate interval. According to the size relationship between the initial count rate data and the boundaries of each count rate interval, the interval identifier to which the current count rate belongs is determined. When the initial count rate data is at the boundary of two adjacent intervals, the preset interval identifier with higher priority is selected;

[0018] A correction coefficient library is constructed based on offline calibration data. Each count rate interval corresponds to a set of correction coefficients including a reference dead time coefficient and reference dead time coefficient adjustment parameters. The correction coefficients corresponding to the current count rate interval are read from the correction coefficient library. When the count rate is close to the interval boundary, the weighted average of the correction coefficients of two adjacent intervals is calculated through a weighted interpolation algorithm as the initial dead time correction coefficient.

[0019] On the basis of the above technical solutions, preferably, the using an adaptive algorithm to adjust the initial dead time correction coefficient online to obtain an adjusted dead time correction coefficient includes:

[0020] Collect a plurality of consecutive count rate samples within a sliding time window of fixed length, and establish a theoretical linear response model based on the linear response characteristics in the low count rate interval;

[0021] Calculate the relative deviation sequence between the actual count rate samples and the theoretical linear response model, perform weighted averaging on the relative deviation sequence to obtain the deviation coefficient of the current time window, and adjust the dead time correction coefficient when the deviation coefficient exceeds a preset threshold;

[0022] Construct the dead time correction coefficient and the change rate of the dead time correction coefficient into a state vector, establish a state transition equation and a measurement equation, where the measurement input is the deviation coefficient, set the process noise matrix and the measurement noise matrix, and iteratively execute the prediction and update stages to output a smoothed and optimized adjusted dead time correction coefficient;

[0023] The calculation formula for the adjusted dead time correction coefficient is:

[0024]

[0025] where τ adj is the adjusted dead time correction coefficient, τ init is the initial dead time correction coefficient, ε1 is the deviation coefficient, N1 is the current count rate value, α1 is the deviation sensitivity parameter, β1 is the deviation response coefficient, γ1 is the high count rate compensation coefficient, δ1 is the count rate dependence parameter, and tanh(·) is the hyperbolic tangent activation function.

[0026] Based on the above technical solutions, preferably, the acquisition environment parameters are used to compensate and adjust the adjusted dead time correction coefficient to obtain a compensated dead time correction coefficient, including:

[0027] Obtain environmental temperature data and calculate the temperature compensation coefficient according to the temperature-dead time relationship model, and perform temperature compensation on the adjusted dead time correction coefficient to obtain the temperature-compensated dead time correction coefficient;

[0028] Analyze the count ratio distribution of each energy window, calculate the energy spectrum compensation coefficient, and perform energy spectrum compensation on the temperature-compensated dead time correction coefficient to obtain the compensated dead time correction coefficient.

[0029] Based on the above technical solutions, preferably, the initial count rate data is corrected based on the compensated dead time correction coefficient to obtain corrected count rate data, including:

[0030] Substitute the initial count rate data and the compensated dead time correction coefficient into the dead time correction model to calculate the initial corrected count rate data;

[0031] Perform dynamic smoothing processing and validity verification on the initial corrected count rate data to obtain the corrected count rate data.

[0032] Based on the above technical solutions, preferably, the conversion of the corrected count rate data into radiation dose rate data and the judgment of whether to trigger an alarm according to a preset radiation dose rate threshold include:

[0033] Establish a count rate-dose rate correspondence model based on offline calibration, select the corresponding dose rate conversion function according to the radiation source type, perform energy weighted compensation according to the count ratio of each energy window, select the corresponding conversion coefficient group for different radiation types, introduce an energy spectrum shape correction factor in wide energy range measurement to compensate for the response differences under different energy distributions, adopt an adaptive smoothing algorithm for the conversion results to reduce the random fluctuations of the radiation dose rate data, and calculate and display the uncertainty of the radiation dose rate measurement in real time;

[0034] Set multi-level alarm thresholds, where the multi-level alarm thresholds include a pre-alarm threshold, a warning threshold, and a danger threshold. Construct a configurable time-dose rate matrix judgment logic to determine the alarm level according to the combination of the dose rate level and the duration. Adopt an alarm debounce algorithm based on time lag to avoid alarm jitter caused by radiation dose rate fluctuations. Analyze the change trend of the radiation dose rate to predict potential over-limit risks in advance. When the dose rate is close to the danger threshold, increase the sampling frequency and processing priority, and adopt different acoustic and optical modes and wireless reporting frequencies for different alarm levels.

[0035] In a second aspect, the present invention also provides a radiation detection system based on adaptive dead time correction, and the system includes:

[0036] A pulse signal processing module, configured to acquire the pulse signal of the radiation detector and perform preprocessing to obtain initial count rate data;

[0037] A dead time correction coefficient selection module, configured to select an initial dead time correction coefficient from a preset correction coefficient library according to the current count rate range of the initial count rate data;

[0038] A dead time correction coefficient adjustment module, configured to perform online adjustment on the initial dead time correction coefficient by using an adaptive algorithm to obtain an adjusted dead time correction coefficient, and the adaptive algorithm is based on the count rate change characteristics within a sliding time window;

[0039] A dead time correction coefficient compensation module, configured to collect environmental parameters, including temperature and energy spectrum distribution data, and perform compensation adjustment on the adjusted dead time correction coefficient according to the environmental parameters to obtain a compensated dead time correction coefficient;

[0040] A count rate correction module, configured to correct the initial count rate data based on the compensated dead time correction coefficient to obtain corrected count rate data;

[0041] The radiation dose alarm module is used to convert the corrected count rate data into radiation dose rate data and determine whether to trigger an alarm according to a preset radiation dose rate threshold.

[0042] In a third aspect, the present invention further provides an electronic device, including: at least one processor, at least one memory, a communication interface, and a bus;

[0043] Wherein, the processor, the memory, and the communication interface complete mutual communication through the bus, the memory stores program instructions executable by the processor, and the processor calls the program instructions to implement the steps of a radiation detection method based on adaptive dead time correction.

[0044] In a fourth aspect, the present invention further provides a computer-readable storage medium, and the computer-readable storage medium stores computer instructions, and the computer instructions enable a computer to implement the steps of a radiation detection method based on adaptive dead time correction.

[0045] A radiation detection method and system based on adaptive dead time correction of the present invention have the following beneficial effects compared with the prior art:

[0046] (1) By combining segmented optimization of the count rate range, an adaptive algorithm for a sliding time window, and real-time compensation of environmental parameters, a complete dead time correction link is constructed, overcoming the correction deviation in an environment with dynamic changes in the count rate, improving the correction accuracy and measurement reliability, eliminating the influence of temperature and energy spectrum changes on the detection system, forming a complete solution from signal acquisition to alarm output, and enhancing the accuracy and reliability of radiation detection in fields such as nuclear safety monitoring and emergency response;

[0047] (2) Through sliding time window sampling, relative deviation sequence analysis, and a Kalman filter state estimation method, dynamic optimization of the dead time correction coefficient is achieved. By introducing a non-linear deviation response model and a high count rate compensation mechanism, the correction parameters can be automatically adjusted according to the actual measurement results, accurately coping with scenarios of rapid changes in radiation intensity, balancing the system response speed and stability, improving the measurement accuracy of radiation detection in complex scenarios, and enhancing the anti-interference ability and environmental adaptability;

[0048] (3) By introducing environmental temperature and energy spectrum distribution parameters in the dead time correction process, temperature compensation and energy spectrum compensation for adjusting the dead time correction coefficient are achieved. Using a high-precision temperature sensor and segmented temperature range modeling, the influence of temperature changes and fluctuations on the dead time correction coefficient is dynamically corrected. And through normalization of the energy window count ratio, template matching, and weighted fusion, adaptive compensation for different energy spectrum types is achieved, improving the correction accuracy and stability in variable environments such as extreme temperatures, complex energy spectra, and high-energy radiation sources, and enhancing the reliability and adaptability of radiation measurement results. Brief Description of the Drawings

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0050] Figure 1 It is a flowchart of a radiation detection method based on adaptive dead time correction of the present invention;

[0051] Figure 2 It is a structural diagram of a radiation detection system based on adaptive dead time correction of the present invention. Detailed Embodiments

[0052] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in combination with the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0053] Please refer to Figure 1 , the present invention provides a radiation detection method based on adaptive dead time correction, including the following steps:

[0054] Obtain the pulse signal of the radiation detector and perform preprocessing to obtain the initial count rate data;

[0055] Select the initial dead time correction coefficient from the preset correction coefficient library according to the current count rate range of the initial count rate data;

[0056] Use an adaptive algorithm to online adjust the initial dead time correction coefficient to obtain an adjusted dead time correction coefficient, and the adaptive algorithm is based on the count rate change characteristics within a sliding time window;

[0057] Collect environmental parameters, including temperature and energy spectrum distribution data, and compensate and adjust the adjusted dead time correction coefficient according to the environmental parameters to obtain a compensated dead time correction coefficient;

[0058] Correct the initial count rate data based on the compensated dead time correction coefficient to obtain corrected count rate data;

[0059] Convert the corrected count rate data into radiation dose rate data, and judge whether to trigger an alarm according to the preset radiation dose rate threshold.

[0060] Specifically, in this embodiment, a complete dead time correction link is constructed by combining segmented optimization of the counting rate range, an adaptive sliding time window algorithm, and real-time compensation of environmental parameters, overcoming the correction deviation in an environment with dynamically changing counting rates, improving the correction accuracy and measurement reliability, eliminating the influence of temperature and energy spectrum changes on the detection system, forming a complete solution from signal acquisition to alarm output, and enhancing the accuracy and reliability of radiation detection in fields such as nuclear safety monitoring and emergency response.

[0061] Obtaining the pulse signal of the radiation detector and performing preprocessing to obtain the initial counting rate data, including:

[0062] Performing denoising and waveform analysis on the pulse signal of the radiation detector to improve the pulse recognition rate and obtain a highly recognizable pulse signal.

[0063] In a specific embodiment, a digital filtering algorithm is used to denoise the pulse signal, filtering out background radiation and electronic noise interference; amplitude discrimination and rise time analysis techniques are used to distinguish effective radiation events from noise events; the pulse waveform is shaped to improve the recognition accuracy of the pulse peak and reduce the influence of pulse pile-up effects.

[0064] Classifying the highly recognizable pulse signals according to energy magnitude and performing counting statistics to obtain the initial counting rate data.

[0065] In a specific embodiment, the pulse signals are divided into multiple preset energy windows according to amplitude height; the pulse events in each energy window are independently counted; a sliding time window technique is used to update the counting rate data of each energy window and the overall in real time; the proportion of the count in each energy window in the total count is calculated.

[0066] Specifically, in this embodiment, by constructing a correction coefficient library with optimized sub-intervals and a dynamic update mechanism, the problem of poor adaptability of a single parameter in traditional methods is solved. Based on the correction coefficient selection strategy for counting rate interval division, by establishing a multi-resolution counting rate segmented model (low / medium / high counting rate intervals) and corresponding correction coefficient groups, combined with a coefficient library update algorithm driven by real-time data, the matching accuracy of the initial correction parameters is improved;

[0067] This embodiment adopts a sliding window data statistics and confidence evaluation mechanism to realize the dynamic maintenance of the correction coefficient library and automatic elimination of abnormal parameters, enabling it to adapt to the changing requirements of different radiation intensity scenarios, effectively reducing the computational complexity of subsequent adaptive adjustments, improving the response speed and correction stability in wide dynamic range measurements, and providing a high-quality initial parameter benchmark for the overall adaptive correction algorithm

[0068] Selecting an initial dead time correction coefficient from a preset correction coefficient library according to the current counting rate range of the initial counting rate data, including:

[0069] Map the current count rate range where the initial count rate data is located to one of a plurality of predefined count rate intervals;

[0070] Divide the full-scale count rate measurement range of the radiation detector into a plurality of consecutive and non-overlapping count rate intervals, set an interval identifier for each count rate interval, determine the interval identifier to which the current count rate belongs according to the magnitude relationship between the initial count rate data and the boundaries of each count rate interval, and when the initial count rate data is at the boundary of two adjacent intervals, select the preset interval identifier with a higher priority;

[0071] Build a correction coefficient library based on offline calibration data. Each count rate interval corresponds to a set of correction coefficients including a reference dead time coefficient and a reference dead time coefficient adjustment parameter. Read the correction coefficients corresponding to the current count rate interval from the correction coefficient library. When the count rate is close to the interval boundary, calculate the weighted average of the correction coefficients of two adjacent intervals as the initial dead time correction coefficient through a weighted interpolation algorithm to smooth the interval transition effect.

[0072] Specifically, in this embodiment, the full-scale count rate range is divided into a plurality of non-overlapping intervals, and dedicated correction parameters are set for each interval. At the same time, an interval boundary priority mechanism and a weighted interpolation algorithm are introduced to effectively eliminate the discontinuous effect during the count rate cross-interval transition.

[0073] The correction coefficient library constructed based on offline calibration data in this embodiment includes the reference coefficients and adjustment parameters of each interval, and can provide the optimal initial correction value for different measurement scenarios, improving the initial accuracy in a changing radiation environment.

[0074] The online adjustment of the initial dead time correction coefficient by using an adaptive algorithm to obtain an adjusted dead time correction coefficient includes:

[0075] Collect a plurality of consecutive count rate samples within a sliding time window of a fixed length, and establish a theoretical linear response model based on the linear response characteristics of the low count rate interval;

[0076] Calculate the relative deviation sequence between the actual count rate samples and the theoretical linear response model, perform a weighted average on the relative deviation sequence to obtain the deviation coefficient of the current time window, and when the deviation coefficient exceeds a preset threshold, adjust the dead time correction coefficient;

[0077] Construct the dead time correction coefficient and the change rate of the dead time correction coefficient as the state vector, establish the state transition equation and the measurement equation. Among them, the measurement input is the deviation coefficient, and the process noise matrix and the measurement noise matrix are set to reflect the system dynamic characteristics and measurement uncertainty. Iteratively execute the prediction and update phases, output the smoothed and optimized adjusted dead time correction coefficient, dynamically adjust the Kalman gain, and achieve a balance between the system response speed and stability;

[0078] The calculation formula of the adjusted dead time correction coefficient is as follows:

[0079]

[0080] where τ adj is the adjusted dead time correction coefficient, τ init is the initial dead time correction coefficient, ε1 is the deviation coefficient, N1 is the current count rate value, α1 is the deviation sensitivity parameter, β1 is the deviation response coefficient, γ1 is the high count rate compensation coefficient, δ1 is the count rate dependence parameter, and tanh(·) is the hyperbolic tangent activation function.

[0081] Specifically, in this embodiment, the dynamic optimization of the dead time correction coefficient is realized through the sliding time window sampling, relative deviation sequence analysis and Kalman filter state estimation method. The non-linear deviation response model and the high count rate compensation mechanism are introduced, so that the correction parameters can be automatically adjusted according to the actual measurement results, accurately respond to the rapid change scenario of the radiation intensity, balance the system response speed and stability, improve the measurement accuracy of the radiation detection in the complex scenario, and enhance the anti-interference ability and environmental adaptability.

[0082] Collect the environmental parameters, and compensate and adjust the adjusted dead time correction coefficient according to the environmental parameters to obtain the compensated dead time correction coefficient, including:

[0083] Obtain the environmental temperature data and calculate the temperature compensation coefficient according to the temperature-dead time relationship model, and perform temperature compensation on the adjusted dead time correction coefficient to obtain the temperature-compensated dead time correction coefficient.

[0084] In a specific embodiment, the built-in high-precision temperature sensor is used to collect the environmental temperature data in real time, establish the temperature-dead time mapping relationship based on the segmented temperature range, adopt different temperature response coefficients for different temperature ranges, consider the temperature gradient effect, introduce the temperature change rate parameter, correct the compensation deviation in the case of temperature mutation, perform exponential smoothing processing on the measured temperature, reduce the influence of temperature fluctuation on the compensation coefficient, and when the environmental temperature exceeds the preset working range, start the temperature anomaly protection mechanism to limit the dead time correction coefficient within the safe boundary.

[0085] Analyze the count ratio distribution of each energy window, calculate the energy spectrum compensation coefficient, perform energy spectrum compensation on the temperature-compensated dead time correction coefficient to obtain the compensated dead time correction coefficient;

[0086] In a specific embodiment, normalize the count rates of each energy window to obtain an energy spectrum distribution feature vector, perform similarity matching between the energy spectrum distribution feature vector and a preset typical energy spectrum template to identify the type of the current radiation field energy spectrum, select a corresponding energy spectrum compensation parameter group according to the energy spectrum type, and calculate the optimal energy spectrum compensation coefficient using a weighted fusion method for the identified energy spectrum type. When the proportion in the high-energy interval increases significantly, dynamically adjust the energy spectrum compensation intensity to adapt to the special response characteristics of high-energy radiation sources.

[0087] In a specific embodiment, the calculation formula for the compensated dead time correction coefficient is:

[0088]

[0089] where τ comp is the compensated dead time correction coefficient, τ adj is the adjusted dead time correction coefficient, is the temperature response function, T is the current temperature, ρ1 is the temperature change rate sensitivity coefficient, Ψ E (·) is the energy spectrum response function, P i is the count ratio of the i-th energy window, η1 is the high-energy response coefficient, H1 is the high-energy region proportion index, κ1 is the first temperature coefficient, κ2 is the second temperature coefficient, T ref is the reference temperature, ω i is the energy window weight coefficient of the i-th energy window, P i,ref is the proportion reference value of the i-th energy window under the standard energy spectrum, and ε2 is the numerical stability constant.

[0090] Specifically, in this embodiment, by introducing the environmental temperature and energy spectrum distribution parameters in the dead time correction process, the temperature compensation and energy spectrum compensation for the adjusted dead time correction coefficient are realized. Using a high-precision temperature sensor and piecewise temperature interval modeling, the influence of temperature changes and fluctuations on the dead time correction coefficient is dynamically corrected. Through normalization, template matching, and weighted fusion of the count ratios of energy windows, adaptive compensation for different energy spectrum types is achieved, improving the correction accuracy and stability in variable environments such as extreme temperatures, complex energy spectra, and high-energy radiation sources, and enhancing the reliability and adaptability of radiation measurement results.

[0091] The correction of the initial count rate data based on the compensated dead time correction coefficient to obtain the corrected count rate data includes:

[0092] Substitute the initial count rate data and the compensated dead time correction coefficient into the dead time correction model to calculate the initial corrected count rate data.

[0093] In a specific embodiment, corresponding dead time correction models are selected for different counting rate intervals, including non-paralyzed models, paralyzed models or mixed models. Linear correction approximation is adopted in the low counting rate interval to reduce the computational load; the standard non-paralyzed correction formula is applied in the medium counting rate interval, and high-order correction terms are adopted in the high counting rate interval to compensate for the pulse pile-up effect. A saturation protection mechanism is introduced. When the calculated correction value exceeds the theoretical maximum counting rate, the correction result is limited within the physically allowed range. The update frequency of the dead time correction model is adaptively adjusted according to the change rate of the radiation field.

[0094] The initial corrected counting rate data is subjected to dynamic smoothing processing and validity verification to ensure the stability and reliability of the correction result, and the corrected counting rate data is obtained.

[0095] In a specific embodiment, an adaptive filtering algorithm is used to smooth the corrected counting rate data. The width of the filtering window is inversely proportional to the change rate of the counting rate. The change gradient of the corrected counting rate in adjacent time windows is calculated. When the gradient exceeds the preset threshold, an outlier detection mechanism is started. According to the trend of historical data, a short-term prediction model is established to judge whether the current correction result conforms to the expected change trend. The correction results that do not conform to the physical law are marked and the recalculation process is triggered. The corresponding relationship between the correction coefficient and the correction result is recorded, and an evaluation index for the correction effect is established.

[0096] Specifically, in this embodiment, the accuracy and reliability of the corrected counting rate are improved through an improved dead time correction model and data processing algorithm. Differentiated correction strategies are adopted for different counting rate intervals (linear approximation in the low interval, standard formula in the medium interval, high-order compensation in the high interval), the optimal model is selected and a saturation protection mechanism is introduced to ensure that the correction result is within the physical meaning range. Especially in its post-processing link, an adaptive filtering algorithm and an outlier detection mechanism based on gradient change are adopted to dynamically adjust the width of the filtering window to respond to different change rates, construct a short-term prediction model for validity verification, and correct the results that do not conform to the physical law.

[0097] This embodiment also establishes a correction effect evaluation and parameter self-learning mechanism to realize the continuous optimization of the system performance, and greatly improves the robustness and measurement accuracy of the detection system under strong radiation fields, rapidly changing environments and high-precision measurement requirements.

[0098] Converting the corrected counting rate data into radiation dose rate data and judging whether to trigger an alarm according to a preset radiation dose rate threshold includes:

[0099] Based on offline calibration, a count rate-dose rate correspondence model is established. The corresponding dose rate conversion function is selected according to the type of radiation source. Energy-weighted compensation is performed according to the count proportion of each energy window to improve the accuracy of dose equivalent conversion. The corresponding conversion coefficient group is selected for different radiation types. A spectrum shape correction factor is introduced in wide energy range measurement to compensate for the response differences under different energy distributions. An adaptive smoothing algorithm is used for the conversion results to reduce the random fluctuations of radiation dose rate data. The uncertainty of radiation dose rate measurement is calculated and displayed in real time to provide a reference for the measurement reliability for users;

[0100] Multiple alarm thresholds are set. The multiple alarm thresholds include a pre-warning threshold, a warning threshold, and a danger threshold. A configurable time-dose rate matrix judgment logic is constructed to determine the alarm level according to the combination of the dose rate level and the duration. An alarm debounce algorithm based on time lag is adopted to avoid alarm jitter caused by fluctuations in the radiation dose rate. According to the analysis of the change trend of the radiation dose rate, potential over-limit risks are predicted in advance to achieve the pre-warning function. When the dose rate approaches the danger threshold, the sampling frequency and processing priority are increased to ensure timely response in high-risk situations. The hierarchical linkage of the audible and visual alarm outputs is realized. Different audible and visual modes and wireless reporting frequencies are adopted for different alarm levels, and the alarm automatic mute and manual confirmation functions are provided to facilitate emergency operations in high-radiation environments.

[0101] Specifically, in this embodiment, through the intelligent conversion of count rate-dose rate and the multi-level alarm strategy, the safety response ability of radiation dose assessment is improved.

[0102] In this embodiment, an accurate conversion model is constructed based on offline calibration data, and an energy-weighted compensation and a spectrum shape correction factor are introduced to achieve high-precision dose equivalent conversion for different radiation types; by designing a multi-level threshold alarm judgment logic, combining a configurable time-dose rate matrix judgment mechanism and a time-lag-based debounce algorithm, the false alarm problem caused by fluctuations is eliminated;

[0103] Through the change trend analysis, this embodiment realizes the pre-warning function, and automatically increases the sampling frequency and processing priority in high-risk situations. Combining the hierarchical linkage of audible and visual alarm outputs and the wireless reporting mechanism, a complete radiation protection emergency response system is constructed, improving the safety pre-warning and danger recognition capabilities of the radiation detection system in key fields such as nuclear emergency monitoring and radiation protection.

[0104] Please refer to Figure 2 , the present invention also provides a radiation detection system based on adaptive dead time correction, and the system includes:

[0105] A pulse signal processing module, configured to obtain the pulse signal of the radiation detector and perform preprocessing to obtain the initial count rate data;

[0106] A dead time correction coefficient selection module, configured to select an initial dead time correction coefficient from a preset correction coefficient library according to the current count rate range of the initial count rate data;

[0107] A dead time correction coefficient adjustment module, configured to perform online adjustment on the initial dead time correction coefficient by using an adaptive algorithm to obtain an adjusted dead time correction coefficient, where the adaptive algorithm is based on the count rate change characteristics within a sliding time window;

[0108] A dead time correction coefficient compensation module, configured to collect environmental parameters, including temperature and energy spectrum distribution data, and perform compensation adjustment on the adjusted dead time correction coefficient according to the environmental parameters to obtain a compensated dead time correction coefficient;

[0109] A count rate correction module, configured to correct the initial count rate data based on the compensated dead time correction coefficient to obtain corrected count rate data;

[0110] A radiation dose alarm module, configured to convert the corrected count rate data into radiation dose rate data, and determine whether to trigger an alarm according to a preset radiation dose rate threshold.

[0111] Specifically, a radiation detection system based on adaptive dead time correction in this embodiment integrates pulse signal processing, dead time correction coefficient selection, dead time correction coefficient adjustment, dead time correction coefficient compensation, count rate correction, and a radiation dose alarm module, constructs a complete processing link from detection signal acquisition to dose alarm, and realizes high modularity and function decoupling while maintaining good cooperation between systems.

[0112] Through the autonomous optimized design of the signal processing front end, the closed-loop adjustment structure of the dead time parameter, and the multi-source data fusion technology, the system achieves a balance between low-latency response and high-precision correction, realizes the real-time execution ability of complex algorithms on an embedded platform with limited resources, and provides a complete, easy-to-deploy, stable-performance, and industrially reliable radiation detection solution.

[0113] The present invention also discloses an electronic device, including: at least one processor, at least one memory communication interface, and a bus: wherein, the processor, the memory, and the communication interface complete communication with each other through the bus; the memory stores program instructions executable by the processor, and the processor calls the program instructions to implement a radiation detection method based on adaptive dead time correction.

[0114] The present invention also discloses a computer-readable storage medium, which stores computer instructions that enable the computer to implement all or part of the steps of the method for radiation detection based on adaptive dead time correction according to an embodiment of the present invention. The storage medium includes various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs.

[0115] The above are only the preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A radiation detection method based on adaptive dead time correction, characterized in that, It includes the following steps: Obtain the pulse signal of the radiation detector and perform preprocessing to obtain initial count rate data; Select an initial dead time correction coefficient from a preset correction coefficient library according to the current count rate range of the initial count rate data; Use an adaptive algorithm to perform online adjustment on the initial dead time correction coefficient to obtain an adjusted dead time correction coefficient; Collect environmental parameters, and perform compensation adjustment on the adjusted dead time correction coefficient according to the environmental parameters to obtain a compensated dead time correction coefficient; Correct the initial count rate data based on the compensated dead time correction coefficient to obtain corrected count rate data; Convert the corrected count rate data into radiation dose rate data, and determine whether to trigger an alarm according to a preset radiation dose rate threshold.

2. The radiation detection method based on adaptive dead time correction as described in claim 1, characterized in that, The obtaining the pulse signal of the radiation detector and performing preprocessing to obtain initial count rate data includes: Perform denoising and waveform analysis on the pulse signal of the radiation detector to improve the pulse recognition rate and obtain a highly recognizable pulse signal; Classify the highly recognizable pulse signals according to energy levels and perform count statistics to obtain initial count rate data.

3. The radiation detection method based on adaptive dead time correction according to claim 1, wherein, The selecting an initial dead time correction coefficient from a preset correction coefficient library according to the current count rate range of the initial count rate data includes: Map the current count rate range where the initial count rate data is located to one of a plurality of predefined count rate intervals; Divide the full-scale count rate measurement range of the radiation detector into a plurality of consecutive and non-overlapping count rate intervals, set an interval identifier for each count rate interval, determine the interval identifier to which the current count rate belongs according to the size relationship between the initial count rate data and the boundaries of each count rate interval, and when the initial count rate data is at the boundary of two adjacent intervals, select the preset interval identifier with a higher priority; Construct a correction coefficient library based on offline calibration data. Each count rate interval corresponds to a set of correction coefficients including a reference dead time coefficient and a reference dead time coefficient adjustment parameter. Read the correction coefficients corresponding to the current count rate interval from the correction coefficient library. When the count rate is close to the interval boundary, calculate the weighted average of the correction coefficients of two adjacent intervals as the initial dead time correction coefficient through a weighted interpolation algorithm.

4. The radiation detection method based on adaptive dead time correction according to claim 3, characterized in that The using an adaptive algorithm to perform online adjustment on the initial dead time correction coefficient to obtain an adjusted dead time correction coefficient includes: Collect a plurality of consecutive count rate samples within a sliding time window of a fixed length, and establish a theoretical linear response model based on the linear response characteristics of the low count rate interval; Calculate the relative deviation sequence between the actual count rate samples and the theoretical linear response model, perform weighted averaging on the relative deviation sequence to obtain the deviation coefficient of the current time window, and adjust the dead time correction coefficient when the deviation coefficient exceeds a preset threshold; Construct a state vector from the dead time correction coefficient and the change rate of the dead time correction coefficient, establish a state transition equation and a measurement equation, where the measurement input is the deviation coefficient, set the process noise matrix and the measurement noise matrix, and iteratively execute the prediction and update phases to output a smoothed and optimized adjusted dead time correction coefficient; The calculation formula for the adjusted dead time correction coefficient is: Among them, τ adj is the adjusted dead time correction coefficient, τ init is the initial dead time correction coefficient, ε1 is the deviation coefficient, N1 is the current count rate value, α1 is the deviation sensitivity parameter, β1 is the deviation response coefficient, γ1 is the high count rate compensation coefficient, δ1 is the count rate dependent parameter, and tanh(·) is the hyperbolic tangent activation function.

5. The radiation detection method based on adaptive dead time correction according to claim 4, wherein The collected environmental parameters are used to compensate and adjust the adjusted dead time correction coefficient according to the environmental parameters to obtain a compensated dead time correction coefficient, including: Obtain environmental temperature data and calculate a temperature compensation coefficient according to a temperature-dead time relationship model, and perform temperature compensation on the adjusted dead time correction coefficient to obtain a temperature-compensated dead time correction coefficient; Analyze the count ratio distribution of each energy window, calculate an energy spectrum compensation coefficient, and perform energy spectrum compensation on the temperature-compensated dead time correction coefficient to obtain a compensated dead time correction coefficient.

6. The radiation detection method based on adaptive dead time correction according to claim 1, wherein, The initial count rate data is corrected based on the compensated dead time correction coefficient to obtain corrected count rate data, including: Substitute the initial count rate data and the compensated dead time correction coefficient into a dead time correction model to calculate and obtain initial corrected count rate data; Perform dynamic smoothing processing and validity verification on the initial corrected count rate data to obtain corrected count rate data.

7. A radiation detection method based on adaptive dead time correction as described in claim 1, characterized in that The corrected count rate data is converted into radiation dose rate data, and it is judged whether to trigger an alarm according to a preset radiation dose rate threshold, including: Based on offline calibration, establish a count rate-dose rate correspondence relationship model, select a corresponding dose rate conversion function according to the radiation source type, perform energy weighted compensation according to the count ratio of each energy window, select a corresponding conversion coefficient group for different radiation types, introduce an energy spectrum shape correction factor in wide energy range measurement to compensate for the response difference under different energy distributions, adopt an adaptive smoothing algorithm for the conversion result to reduce the random fluctuation of the radiation dose rate data, and calculate and display the uncertainty of the radiation dose rate measurement in real time; Set multiple alarm thresholds, where the multiple alarm thresholds include a warning threshold, a warning threshold, and a danger threshold, construct a configurable time-dose rate matrix judgment logic, determine the alarm level according to the dose rate level and duration combination, adopt an alarm de-bounce algorithm based on time lag to avoid alarm jitter caused by radiation dose rate fluctuations, analyze according to the radiation dose rate change trend to predict potential overlimit risks in advance, when the dose rate is close to the danger threshold, increase the sampling frequency and processing priority, and adopt different sound and light modes and wireless reporting frequencies for different alarm levels.

8. A radiation detection system based on adaptive dead time correction for performing a radiation detection method based on adaptive dead time correction according to any one of claims 1-7, characterized in that, The system includes: A pulse signal processing module for obtaining the pulse signal of a radiation detector and performing preprocessing to obtain initial count rate data; A dead time correction coefficient selection module for selecting an initial dead time correction coefficient from a preset correction coefficient library according to the current count rate range of the initial count rate data; A dead time correction coefficient adjustment module for online adjusting the initial dead time correction coefficient by using an adaptive algorithm to obtain an adjusted dead time correction coefficient, and the adaptive algorithm is based on the count rate change characteristics within a sliding time window; A dead time correction coefficient compensation module for collecting environmental parameters, including temperature and energy spectrum distribution data, and compensating and adjusting the adjusted dead time correction coefficient according to the environmental parameters to obtain a compensated dead time correction coefficient; A count rate correction module for correcting the initial count rate data based on the compensated dead time correction coefficient to obtain corrected count rate data; A radiation dose alarm module is used to convert the corrected count rate data into radiation dose rate data and determine whether to trigger an alarm according to a preset radiation dose rate threshold.

9. An electronic device, characterized in that, It includes: At least one processor, at least one memory, a communication interface, and a bus; Wherein, the processor, the memory, and the communication interface complete mutual communication through the bus. The memory stores program instructions executable by the processor, and the processor calls the program instructions to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions, and the computer instructions enable the computer to implement the method according to any one of claims 1 to 7.

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