Real-time monitoring system for radioactive exhaust emission radiation dose

Abstract

The application relates to the technical field of radiation protection and environmental monitoring, and particularly discloses a real-time monitoring system for radiation dose of radioactive waste gas emission, which comprises a fixed monitoring base station network, an autonomous mobile monitoring cluster, a data fusion and cooperative control center, and a radiation dose field three-dimensional reconstruction and evaluation terminal. Through air-ground cooperative monitoring, plume prediction based on an atmospheric diffusion model and intelligent path planning, and a spatial interpolation algorithm with physical constraints, efficient tracking of a three-dimensional dynamic diffusion process of a radioactive plume, accurate reconstruction of a three-dimensional dose field and visualized evaluation are realized. The system fundamentally changes the passive and static monitoring paradigm by constructing an air-ground cooperative monitoring system composed of a fixed base station network and an autonomous mobile cluster.

Description

Technical Field

[0001] This invention belongs to the field of radiation protection and environmental monitoring technology, specifically relating to a real-time monitoring system for radiation dose from radioactive waste gas emissions. Background Technology

[0002] In the field of nuclear energy and radioactive isotope applications, the safe emission and dosage control of radioactive waste gases are core aspects of protecting the environment and public health. This field involves monitoring and assessing the types, activities, and migration and transformation behaviors of radionuclides in emitted waste gases, aiming to ensure that emission activities comply with the principles of optimal radiation protection.

[0003] Real-time monitoring of radiation dose from radioactive waste gas emissions is a key technological direction for environmental radiation safety supervision. This technology aims to acquire real-time radiation level data near the emission outlet and in the downwind area by deploying monitoring equipment, in order to assess the immediate radiation impact of emission activities on the surrounding environment and provide a basis for emergency response decisions.

[0004] Deploying fixed radiation monitoring probes near emission outlets or in pre-designated downwind areas has significant limitations: fixed monitoring points cannot actively track the dynamic diffusion path of the "radioactive plume" formed in the atmosphere after exhaust emissions, especially under complex meteorological conditions, making it difficult to determine the actual impact range and maximum dose point of pollutants. Existing systems lack real-time, three-dimensional sensing capabilities for the spatial distribution and temporal evolution of plumes, resulting in monitoring data that only reflects the dose rate at local, fixed locations, failing to fully depict the overall movement and dose field distribution of the pollution cloud. This can cause dose assessment results to deviate significantly from reality, failing to provide reliable support for accurate radiation impact assessment and protective actions. Summary of the Invention

[0005] The purpose of this invention is to provide a real-time monitoring system for radiation dose of radioactive waste gas emissions, in order to solve the technical contradiction that existing fixed-point monitoring technologies cannot track the dynamic diffusion path of radioactive waste gas plumes in real time and are difficult to obtain their three-dimensional spatial dose distribution, thus leading to inaccurate radiation impact assessments.

[0006] To achieve the above objectives, the present invention provides a real-time radiation dose monitoring system for radioactive waste gas emissions. The system includes: a network of fixed monitoring base stations deployed near the radioactive waste gas emission source; a mobile monitoring cluster consisting of multiple autonomous mobile monitoring nodes; a data fusion and collaborative control center communicatively connected to the fixed monitoring base station network and the mobile monitoring cluster; and a radiation dose field three-dimensional reconstruction and assessment terminal connected to the data fusion and collaborative control center.

[0007] The fixed monitoring base station network consists of at least three spatially distributed fixed radiation monitoring base stations. Each fixed radiation monitoring base station integrates a high-sensitivity gamma-ray spectrum detection module, a meteorological parameter acquisition module, and a first data communication module. The high-sensitivity gamma-ray spectrum detection module is used to continuously measure the gamma-ray spectrum and dose rate data at its location. The meteorological parameter acquisition module is used to collect real-time data on wind speed, wind direction, temperature, humidity, and air pressure at its location. The first data communication module is used to upload the collected spectrum data, dose rate data, and meteorological data to the data fusion and collaborative control center in real time.

[0008] The mobile monitoring cluster comprises at least two autonomous mobile monitoring nodes. Each autonomous mobile monitoring node includes a mobile platform, a rapid-response radiation monitoring unit mounted on the platform, a precise positioning and navigation unit, a second data communication module, and a local control unit. The mobile platform is a rotorcraft capable of vertical takeoff and landing and hovering. The rapid-response radiation monitoring unit integrates a lightweight scintillator detector and a multichannel analyzer for real-time measurement of gamma dose rate and energy spectrum characteristics at specific points in the air during movement. The precise positioning and navigation unit integrates a satellite positioning receiver, an inertial measurement unit, and a laser ranging radar for centimeter-level precise positioning, autonomous path planning, and obstacle avoidance flight of the mobile monitoring node. The second data communication module is used for bidirectional data and command transmission with the data fusion and collaborative control center. The local control unit receives commands from the data fusion and collaborative control center and controls the mobile platform and the rapid-response radiation monitoring unit to perform corresponding monitoring tasks.

[0009] The data fusion and collaborative control center is the core decision-making and coordination hub of the system, comprising a data receiving and preprocessing module, a plume diffusion prediction and path planning module, and a cluster collaborative control module. The data receiving and preprocessing module receives and synchronizes monitoring data and status information from all fixed monitoring base stations and mobile monitoring nodes. The plume diffusion prediction and path planning module, based on real-time received emission source information, meteorological field data from the fixed monitoring base station network, and atmospheric diffusion models, dynamically predicts the three-dimensional spatial diffusion trend and possible concentration distribution of the radioactive plume within a specific future time period, and accordingly generates the optimal collaborative detection path for the mobile monitoring cluster. Based on the generated collaborative detection path, the cluster collaborative control module assigns specific flight waypoints, monitoring altitudes, and sampling frequency commands to the local control units of each mobile monitoring node, and monitors the task execution status of the entire mobile monitoring cluster.

[0010] The three-dimensional radiation dose field reconstruction and assessment terminal includes a spatiotemporal data interpolation and reconstruction engine and a dose assessment and visualization module. The spatiotemporal data interpolation and reconstruction engine receives discrete dose rate data points collected in the spatiotemporal domain by a fixed monitoring base station network and a mobile monitoring cluster from the data fusion and collaborative control center. Combined with synchronized meteorological data, it uses a physically constrained Kriging spatial interpolation algorithm to reconstruct a continuous three-dimensional dose rate distribution field of the radioactive plume within the monitoring airspace. Based on the reconstructed three-dimensional dose rate distribution field, the dose assessment and visualization module calculates and outputs key assessment indicators, including but not limited to the dose rate distribution along the plume's central axis, the location and value of the maximum dose point projected on the ground, and the dose rate isosurface at a specific height. It then displays the morphological evolution of the plume and the spatial structure of the dose field in real time using a three-dimensional graphical representation.

[0011] Furthermore, the workflow of the plume diffusion prediction and path planning module specifically includes the following steps: First, the module initializes a Gaussian plume diffusion model or a Lagrange particle diffusion model, and the model parameters are dynamically calibrated based on real-time meteorological data. Next, starting from the emission source, the module calculates the initial diffusion parameters of the plume in the horizontal and vertical directions, combined with the current wind speed and direction. Then, the module iteratively calculates forward at a fixed time step to predict the spatial position and morphological changes of the plume cluster within the next 5 to 30 minutes, generating a predicted plume envelope that evolves over time. Finally, the path planning algorithm, aiming to maximize information gain or minimize detection uncertainty, calculates a series of spatially dispersed and temporally connected waypoint sequences for each node in the mobile monitoring cluster within the predicted plume envelope, ensuring that the cluster can perform three-dimensional coverage sampling of the plume body.

[0012] Furthermore, the specific implementation of the physically constrained Kriging spatial interpolation algorithm is as follows: the algorithm treats each monitoring data point as a function of spatial location and time. When constructing the variogram model, not only is the geometric distance between data points considered, but real-time wind direction is also introduced as an anisotropy factor, making the interpolation weight along the wind direction higher than that perpendicular to the wind direction. Simultaneously, the algorithm incorporates the concentration decay law described by the atmospheric diffusion equation as a soft constraint into the Kriging equations, ensuring that the three-dimensional dose field generated by the interpolation physically conforms to the basic laws of plume diffusion, thus obtaining reasonable estimates even in areas with sparse monitoring data points.

[0013] Furthermore, the specific mode of collaborative detection performed by the mobile monitoring cluster is as follows: the cluster collaborative control module of the data fusion and collaborative control center organizes the mobile monitoring cluster into a leader-follower formation. One mobile monitoring node is designated as the leader node, which flies to the upstream or core region of the predicted plume envelope according to path planning instructions. The remaining mobile monitoring nodes, as subordinate nodes, dynamically adjust their positions based on the real-time dose rate measurement data fed back by the leader node and the global optimization instructions issued by the data fusion and collaborative control center, forming a fan-shaped scanning array of the plume cross-section or a gradient tracking queue of the plume longitudinal direction, thereby achieving synchronous capture of the plume structure from different dimensions.

[0014] Furthermore, the system operates within an adaptive triggering and multi-mode switching framework. This framework includes a regular patrol mode and an emergency tracking mode. In the regular patrol mode, the mobile monitoring cluster conducts a background radiation level survey according to a preset grid. When any unit in the fixed monitoring base station network or the mobile monitoring cluster detects a dose rate exceeding a preset Level 1 threshold, the system automatically switches to the emergency tracking mode. In the emergency tracking mode, the data fusion and collaborative control center immediately activates the plume diffusion prediction and path planning module and instructs the mobile monitoring cluster to abandon its original patrol mission, rush to and lock onto the area exceeding the radiation standard, and conduct high-density, high-dynamic tracking and monitoring of the radioactive plume according to the aforementioned collaborative detection mode.

[0015] Furthermore, the high-sensitivity gamma spectral detection module in the fixed monitoring base station network employs a lanthanum bromide or zinc cadmium telluride detector with an energy resolution better than 3%, enabling it to identify and analyze the characteristic gamma rays of different radionuclides in the mixed radionuclide exhaust gas. The data receiving and preprocessing module of the data fusion and collaborative control center includes an energy spectrum analysis submodule. This submodule analyzes the uploaded energy spectrum data to identify characteristic peaks of key radionuclides such as iodine-131, xenon-133, and cesium-137, and estimates their activity concentrations, providing radionuclide-specific data for dose assessment.

[0016] Furthermore, all data communication links in the system employ a wireless communication protocol with timestamp synchronization to ensure strict alignment of data from distributed monitoring nodes on the timeline. This is fundamental to achieving high-precision spatiotemporal data fusion and three-dimensional field reconstruction. The data fusion and collaborative control center is equipped with data caching and retransmission mechanisms to cope with potential brief communication interruptions in complex environments.

[0017] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0018] 1. This invention fundamentally changes the passive, static monitoring paradigm by constructing an air-ground collaborative monitoring system composed of a fixed base station network and an autonomous mobile cluster. The mobile monitoring cluster can actively track and three-dimensionally scan dynamically spreading radioactive plumes, acquiring their discrete dose data in three-dimensional space. Combined with background and meteorological data provided by fixed base stations, it achieves real-time capture of the plume's entire life cycle trajectory and structural morphology, solving the core technical problem that fixed-point monitoring cannot reflect the true diffusion path and impact range of pollutants.

[0019] 2. This invention, through data fusion and the integrated atmospheric diffusion prediction and intelligent path planning capabilities of the collaborative control center, endows the monitoring system with proactive and adaptive optimization characteristics. The system can predict the plume's trajectory based on real-time meteorological conditions and proactively direct mobile monitoring nodes to the most information-rich spatial locations for sampling, greatly improving the efficiency of monitoring operations and the relevance of data collection. This avoids aimless flight and data redundancy, ensuring the acquisition of key data that best characterizes the plume's features with limited resources.

[0020] 3. This invention utilizes a physical constraint spatial interpolation algorithm employed in the three-dimensional reconstruction and assessment terminal of the radiation dose field to transform discrete and sparse monitoring data into a continuous and complete three-dimensional dose rate distribution field. This technology not only provides an intuitive three-dimensional visualization of the plume but also accurately calculates key assessment parameters such as the ground maximum dose point and axial dose distribution. This elevates radiation environmental impact assessment from a rough estimation based on single-point data to a precise calculation based on three-dimensional dose field data, providing unprecedented reliable data support and scenario awareness capabilities for radiation protection decision-making. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the overall technical architecture of the real-time monitoring system for radiation dose from radioactive waste gas emissions proposed in this invention.

[0022] Figure 2 This is a schematic diagram of the core principle framework of the air-ground collaborative monitoring system in this invention;

[0023] Figure 3 This is a logical flowchart of the plume diffusion prediction and path planning module in this invention;

[0024] Figure 4 This is a schematic diagram of the interaction relationship and data flow of the mobile monitoring cluster collaborative detection mode in this invention;

[0025] Figure 5 This is a schematic diagram of the principle framework of the three-dimensional reconstruction and evaluation terminal for radiation dose field in this invention. Detailed Implementation

[0026] Example 1: The overall technical architecture of the real-time radiation dose monitoring system for radioactive waste gas emissions described in this invention is shown in the attached figure. Figures 1 to 5 As shown, the system consists of four core components: a fixed monitoring base station network, a mobile monitoring cluster, a data fusion and collaborative control center, and a radiation dose field three-dimensional reconstruction and assessment terminal. The components interact with each other and coordinate commands through highly reliable wireless communication links, forming a closed-loop, adaptive, and forward-looking dynamic monitoring system.

[0027] A network of fixed monitoring base stations is deployed in the area surrounding the radioactive waste gas emission source, forming the static sensing base of the system. This network consists of no fewer than three spatially non-collinear fixed radiation monitoring base stations to ensure sufficient geometric diversity in the spatial coverage of the meteorological and radiation fields around the emission source. Each fixed radiation monitoring base station integrates a high-sensitivity gamma spectrum detection module, a meteorological parameter acquisition module, and a primary data communication module.

[0028] The high-sensitivity gamma-ray spectroscopy detection module uses a lanthanum bromide scintillator crystal or a zinc cadmium telluride semiconductor detector as its core sensing element. Its energy resolution is better than 3%, effectively distinguishing the characteristic gamma-ray peaks of typical radionuclides such as iodine-131 (364 kEV), xenon-133 (81 kEV), and cesium-137 (662 kEV) at the 511 kEV energy point. The module continuously acquires gamma-ray spectral data at its location at a sampling frequency of once per second and simultaneously outputs the ambient dose rate in microsieverts per hour.

[0029] The meteorological parameter acquisition module includes an ultrasonic wind speed and direction sensor, a digital temperature and humidity probe, and a barometer, which are used to acquire five key meteorological parameters in real time: wind speed (range 0 to 30 m / s, accuracy ±0.3 m / s), wind direction (resolution 1 degree), temperature (range -40 to 80 degrees Celsius, accuracy ±0.5 degrees Celsius), humidity (range 0 to 100% relative humidity, accuracy ±2%), and atmospheric pressure (range 300 to 1100 hPa, accuracy ±1 hPa).

[0030] The first data communication module employs an industrial-grade wireless communication protocol that supports timestamp synchronization, such as a mesh network based on the IEEE 802.11s standard or the LoRaWAN protocol on a dedicated frequency band. It packages and uploads the aforementioned energy spectrum data, dose rate data, and meteorological data at a frequency of 1 Hz to the data fusion and collaborative control center. All uploaded data packets are embedded with nanosecond-level timestamps provided by the BeiDou satellite timing system, ensuring strict alignment of multi-source data on the timeline.

[0031] The mobile monitoring cluster, serving as the system's dynamic sensing frontier, consists of no fewer than two autonomous mobile monitoring nodes, and its deployment location can be flexibly adjusted according to mission requirements. Please refer to the appendix. Figure 2 Each autonomous mobile monitoring node includes a mobile platform, a rapid-response radiation monitoring unit, a precise positioning and navigation unit, a second data communication module, and a local control unit. The mobile platform is a quadcopter or hexacopter aircraft with vertical takeoff and landing and hovering capabilities, a maximum takeoff weight of not less than 5 kg, an endurance of not less than 30 minutes, and a wind resistance rating of not less than level 6, enabling it to stably perform monitoring tasks under complex weather conditions.

[0032] The rapid-response radiation monitoring unit is mounted on the gimbal shock-absorbing bracket of the mobile vehicle platform. Its core consists of a lightweight scintillator detector (such as a thallium-doped sodium iodide crystal, 25 mm in diameter and 25 mm in height) paired with a low-power multichannel analyzer. This unit can measure the gamma dose rate at a specific point in the air in real time at a frequency of twice per second during flight, and simultaneously record energy spectrum fragments for subsequent nuclide identification. The precise positioning and navigation unit integrates a dual-frequency BeiDou / GNSS satellite positioning receiver, a three-axis microelectromechanical system inertial measurement unit, and a solid-state laser ranging radar.

[0033] The satellite positioning receiver provides centimeter-level real-time dynamic positioning accuracy; the inertial measurement unit has a sampling frequency of 200 Hz and is used to calculate the trajectory when the GNSS signal is briefly lost; the laser ranging radar has a working wavelength of 905 nanometers and a detection range of 0.1 to 30 meters, and is used to realize obstacle perception and autonomous obstacle avoidance flight.

[0034] The second data communication module adopts a dual-mode redundancy design, with the main channel being a 4G / 5G cellular network and the auxiliary channel being a 2.4 GHz spread spectrum wireless link, ensuring bidirectional communication with the data fusion and collaborative control center can still be maintained in urban canyons or factory areas with obstructed environments. The local control unit is an embedded ARM Cortex-A72 processor running a real-time operating system, responsible for parsing flight commands from the data fusion and collaborative control center (including waypoint coordinates, target altitude, hovering time, sampling frequency, etc.) and coordinating the attitude control of the mobile vehicle platform with the data acquisition timing of the rapid response radiation monitoring unit.

[0035] The data fusion and collaborative control center is the core decision-making hub of the entire system. Its hardware platform is a high-performance server cluster deployed in a secure data center, and its software architecture is shown in the attached figure. Figure 3As shown, the system includes a data receiving and preprocessing module, a plume diffusion prediction and path planning module, and a cluster collaborative control module. The data receiving and preprocessing module continuously monitors all data streams from the fixed monitoring base station network and the mobile monitoring cluster. This module first performs integrity verification and timestamp alignment on the received data packets, eliminating abnormal frames caused by communication interference. Subsequently, it uses a built-in energy spectrum analysis submodule to perform spectral analysis on the gamma energy spectrum data. The spectral analysis process uses the least squares fitting method to match the standard nuclide energy spectrum library, identifying the characteristic peak areas of key nuclides such as iodine-131, xenon-133, and cesium-137, and inverting their air activity concentrations (in becquerels per cubic meter) using the detection efficiency calibration coefficient. All preprocessed structured data (including location, time, dose rate, nuclide activity, and meteorological parameters) is stored in a time-series database for subsequent modules to access.

[0036] The plume diffusion prediction and path planning module dynamically generates the future evolution of the plume using a combination of physical models and data-driven approaches. During initialization, the module loads either a Gaussian plume diffusion model or a Lagrange particle diffusion model. Initial model parameters (such as diffusion coefficients σy and σz) are automatically calibrated based on current measured wind speed, atmospheric stability level (determined by Pasquale classification), and emission source height. Using the emission source coordinates as the origin, the module combines real-time wind field data (with wind speed and direction at the emission outlet obtained through spatial interpolation) provided by a fixed monitoring base station network to calculate the initial diffusion scale of the plume in the horizontal and vertical directions. Subsequently, the module iterates forward with a 10-second time step to predict the three-dimensional trajectory of the plume's centroid and its spatial envelope over the next 5 to 30 minutes. The envelope is represented by a series of ellipsoids or particle clouds that evolve over time, with its boundaries defined by a 95% confidence interval. Based on this, the path planning algorithm is initiated, with the objective function of maximizing information gain. This involves selecting several spatial points within the predicted envelope to minimize the uncertainty of the overall plume dose field caused by the dose rate data collected at these points. The algorithm employs an improved greedy strategy: first, the initial waypoint of the leader node is set upstream of the envelope to ensure it makes initial contact with the nascent plume; then, candidate detection points are evenly distributed across the cross-section of the envelope, and based on the known dose gradient and wind direction vector, the points with the highest information value are selected and assigned to subordinate nodes. The final output is a waypoint sequence for each moving monitoring node, including latitude and longitude, altitude, arrival time window, and sampling frequency (typically 2 Hz).

[0037] The cluster collaborative control module receives the aforementioned waypoint sequence and converts it into specific flight control commands, which are then sent to the local control units of each mobile monitoring node. This module simultaneously monitors the real-time status of all nodes (including battery level, positioning accuracy, communication quality, and mission progress). If a node deviates from its flight path due to a malfunction, the system will immediately trigger a replanning mechanism, allowing the remaining nodes to take over the detection mission. Furthermore, as shown in the attached... Figure 4As shown, the mobile monitoring cluster employs a leader-slave cooperative detection mode when performing tasks. The leader node flies into the upstream region of the predicted plume envelope. Once its rapid-response radiation monitoring unit detects a dose rate exceeding twice the background value, it sends a "plume capture" signal to the data fusion and cooperative control center. The center then activates the dynamic formation logic of the subordinate nodes: each subordinate node automatically adjusts its flight altitude and lateral offset based on the real-time dose rate value returned by the leader node and its own position, combined with global optimization commands, forming a fan-shaped scanning array perpendicular to the wind direction. The array span covers 1.2 times the predicted plume width to ensure complete capture of the plume cross-section. In the vertical dimension, some subordinate nodes are arranged along the wind direction gradient, forming a tracking queue to capture the attenuation characteristics of plume concentration with downwind distance.

[0038] The three-dimensional reconstruction and assessment terminal for the radiation dose field is deployed in the radiation emergency command center, and its principle framework is shown in the attached figure. Figure 5 As shown, the system includes a spatiotemporal data interpolation and reconstruction engine, as well as a dose assessment and visualization module. The spatiotemporal data interpolation and reconstruction engine receives a set of discrete monitoring data points from the data fusion and collaborative control center. Each data point contains three-dimensional spatial coordinates (x, y, z), a timestamp t, a dose rate D, and a synchronous meteorological vector (wind speed u, v, w). The engine employs a physically constrained Kriging spatial interpolation algorithm for three-dimensional field reconstruction. This algorithm first constructs a variogram model considering wind anisotropy. Let the Euclidean distance between any two points P1 and P2 be... The wind direction unit vector is Then the effective distance Defined as:

[0039] ;

[0040] in The anisotropy proportionality coefficient, ranging from 0.3 to 0.7, is derived from historical diffusion events. This formula shows that the distance weight along the wind direction is amplified, while the distance weight perpendicular to the wind direction is compressed, thus reflecting the physical characteristic that plumes extend further in the downwind direction. Based on this, the Kriging equations introduce soft constraints for the atmospheric diffusion equations. Let C(x,y,z,t) be the dose rate field, then it should approximately satisfy:

[0041] ;

[0042] in , , The turbulent diffusion coefficient is... Let be the radioactive decay constant. This partial differential equation is not solved as a hard constraint, but rather transformed into a regularization term added to the Kriging objective function, ensuring that the interpolation results still conform to physical diffusion laws in sparse data regions. Ultimately, the engine outputs a three-dimensional grid dose rate field with a resolution of 10 m × 10 m × 5 m, with a time update period of 30 seconds.

[0043] The dose assessment and visualization module calculates multiple key assessment indicators in real time based on the aforementioned 3D dose field. The plume's central axis is obtained by extracting the maximum dose rate points at each altitude level and fitting spatial curves; the dose rate distribution along this axis is displayed as a line graph. The maximum dose point projected onto the ground is obtained by searching for the global maximum after integrating the 3D field onto the z=0 plane; its geographic coordinates and dose values ​​are highlighted on the electronic map. Dose rate isosurfaces at specific altitudes (e.g., 10 meters, 50 meters) are generated into triangular meshes using the Marching Cubes algorithm and rendered with a semi-transparent color gradient, transitioning from blue (low dose) to red (high dose). All visualization results are dynamically presented in a 3D Earth scene using WebGL technology, supporting interactive rotation, zooming, and cross-sectional viewing.

[0044] The system operates within an adaptive triggering and multi-mode switching framework. In normal cruise mode, the mobile monitoring cluster performs background radiation surveys according to a preset 500m × 500m grid, flying at an altitude of 30 meters and a sampling frequency of 0.5 Hz. When any fixed monitoring base station or mobile monitoring node detects a dose rate exceeding the Level 1 threshold (set to be 3 times the local natural background dose rate, typically approximately 0.3 microsieverts per hour) for 5 consecutive seconds, the system automatically switches to emergency tracking mode. At this time, the data fusion and collaborative control center immediately interrupts all routine tasks, activates the plume diffusion prediction and path planning module, and issues a full-speed deployment command to the mobile monitoring cluster. The cluster completes assembly within 5 minutes and enters collaborative detection mode, implementing high-density sampling in the area exceeding the standard (sampling frequency increased to 2 Hz, spatial resolution increased to 100 meters). If the dose rate further exceeds the Level 2 threshold (10 times the background), the system will automatically push early warning information to the radiation emergency management department and recommend the activation of personnel evacuation plans.

[0045] All data communication links are equipped with data caching and retransmission mechanisms. When a mobile monitoring node experiences a communication interruption due to signal obstruction, its local control unit will temporarily store the unuploaded data in the onboard flash memory and retransmit it in chronological order after the connection is restored. The data fusion and collaborative control center has a sliding time window mechanism that processes only valid data from the most recent 10 minutes to prevent historical abnormal data from contaminating the current field reconstruction results.

[0046] In summary, this embodiment achieves real-time, accurate, and dynamic monitoring of the three-dimensional dose field of radioactive exhaust plumes through an air-ground collaborative monitoring architecture, intelligent path planning based on physical models, spatial interpolation algorithms with physical constraints, and a multi-mode adaptive switching mechanism, providing a brand-new technical means for the radiation environment management of nuclear facilities.

[0047] Example 2: Building upon Example 1, this example enhances the vehicle platform and detection unit of the mobile monitoring cluster to adapt to monitoring tasks in more intense or complex terrains. The mobile vehicle platform is replaced with a hybrid-powered vertical takeoff and landing fixed-wing UAV with long endurance, boasting a maximum flight time of 90 minutes and a cruising speed of 20 meters per second, enabling continuous operation within a 10-kilometer radius. This platform is equipped with a dual-redundant flight control system and an anti-electromagnetic interference shield to ensure stable flight even at the edge of strong radiation fields. The rapid-response radiation monitoring unit is upgraded to a multi-modal composite detector, integrating a neutron detection module (using a helium-3 proportional counter tube) and an aerosol sampling subsystem in addition to the original gamma dose rate measurement function. The neutron detection module identifies leaks of fissile materials such as plutonium and americium; the aerosol sampling subsystem extracts air samples via a micro-pump, which are then filtered and analyzed by an onboard laser-induced breakdown spectrometer for elemental composition analysis, enabling indirect monitoring of non-gamma-emitting nuclides (such as strontium-90 and plutonium-239).

[0048] The data fusion and collaborative control center has added a multi-source heterogeneous data fusion submodule. This submodule performs spatiotemporal correlation analysis on gamma, neutron, and aerosol elemental data, constructs multi-dimensional feature vectors, and uses a support vector machine classifier to determine whether there are abnormal changes in the nuclide composition of the emission source. If an unexpected nuclide is detected, the system will automatically raise the warning level and adjust the sampling strategy of the mobile monitoring cluster, such as adding low-altitude hovering sampling below the suspected leak point.

[0049] In addition, the meteorological parameter acquisition module in the fixed monitoring base station network is equipped with a turbulence intensity sensor to directly measure the atmospheric turbulent kinetic energy dissipation rate. This parameter is input into the plume diffusion prediction model, replacing the original empirical diffusion coefficient, significantly improving the prediction accuracy under complex underlying surface conditions (such as factory building complexes). The radiation dose field three-dimensional reconstruction and assessment terminal also introduces a machine learning correction mechanism: using the deviation between measured data and model predictions in historical monitoring events, a lightweight convolutional neural network is trained to post-process and correct the Kriging interpolation results, further improving the reconstruction accuracy of sparsely sampled areas.

[0050] This embodiment is particularly suitable for high-risk scenarios such as large-scale nuclear fuel cycle facilities or decommissioned nuclear power plants. Its enhanced detection capabilities and robustness can effectively respond to potential multi-nucleon mixture leakage accidents and provide key data support for the defense-in-depth system.

Claims

1. A real-time monitoring system for radiation dose from radioactive waste gas emissions, characterized in that, include: A network of fixed monitoring base stations deployed near sources of radioactive waste gas emissions; A mobile monitoring cluster consisting of multiple autonomous mobile monitoring nodes; A data fusion and collaborative control center that is communicatively connected to the fixed monitoring base station network and the mobile monitoring cluster; A radiation dose field three-dimensional reconstruction and assessment terminal connected to the data fusion and collaborative control center; The mobile monitoring cluster comprises at least two autonomous mobile monitoring nodes. Each autonomous mobile monitoring node includes a mobile vehicle platform, a rapid response radiation monitoring unit mounted on the mobile vehicle platform, a precise positioning and navigation unit, a second data communication module, and a local control unit. The mobile vehicle platform is a rotorcraft with vertical take-off and landing and hovering capabilities. The fast-response radiation monitoring unit integrates a lightweight scintillator detector and a multichannel analyzer to measure the gamma dose rate and energy spectrum characteristics of specific points in the air in real time during movement. The precise positioning and navigation unit integrates a satellite positioning receiver, an inertial measurement unit, and a laser ranging radar to achieve centimeter-level precise positioning, autonomous path planning, and obstacle avoidance flight of the mobile monitoring node; the second data communication module is used for bidirectional data and command transmission with the data fusion and collaborative control center; the local control unit is used to receive commands from the data fusion and collaborative control center and control the mobile vehicle platform and the rapid response radiation monitoring unit to perform corresponding monitoring tasks. The data fusion and collaborative control center includes a data receiving and preprocessing module, a plume diffusion prediction and path planning module, and a cluster collaborative control module; the data receiving and preprocessing module is used to receive and synchronize monitoring data and status information from all fixed monitoring base stations and mobile monitoring nodes in real time. The plume diffusion prediction and path planning module dynamically predicts the three-dimensional spatial diffusion trend and possible concentration distribution of radioactive plumes within a specific time period based on real-time received emission source information, meteorological field data from the fixed monitoring base station network, and atmospheric diffusion models. Based on this, it generates the optimal collaborative detection path for the mobile monitoring cluster. The cluster collaborative control module assigns specific flight waypoints, monitoring altitudes, and sampling frequency commands to the local control units of each mobile monitoring node according to the generated collaborative detection path, and monitors the task execution status of the entire mobile monitoring cluster. The three-dimensional reconstruction and assessment terminal for the radiation dose field includes a spatiotemporal data interpolation and reconstruction engine. The spatiotemporal data interpolation and reconstruction engine receives discrete dose rate data points collected in the spatiotemporal domain by the fixed monitoring base station network and the mobile monitoring cluster from the data fusion and collaborative control center. Combined with synchronous meteorological data, it uses a physical constraint-based Kriging spatial interpolation algorithm to reconstruct a continuous three-dimensional dose rate distribution field of the radioactive plume in the monitoring airspace.

2. The real-time monitoring system for radiation dose of radioactive waste gas emissions according to claim 1, characterized in that, The fixed monitoring base station network consists of at least three spatially distributed fixed radiation monitoring base stations. Each fixed radiation monitoring base station integrates a high-sensitivity gamma spectrum detection module, a meteorological parameter acquisition module, and a first data communication module. The high-sensitivity gamma spectrum detection module is used to continuously measure the gamma-ray energy spectrum and dose rate data at its location. The meteorological parameter acquisition module is used to collect wind speed, wind direction, temperature, humidity, and air pressure data at its location in real time. The first data communication module is used to upload the collected energy spectrum data, dose rate data, and meteorological data to the data fusion and collaborative control center in real time.

3. The real-time monitoring system for radiation dose of radioactive waste gas emissions according to claim 2, characterized in that, The three-dimensional reconstruction and assessment terminal for radiation dose field also includes a dose assessment and visualization module; The dose assessment and visualization module calculates and outputs key assessment indicators based on the reconstructed three-dimensional dose rate distribution field, and displays the morphological evolution of the plume and the spatial structure of the dose field in real time in a three-dimensional graphical manner.

4. The real-time monitoring system for radiation dose of radioactive waste gas emissions according to claim 3, characterized in that, The workflow of the plume diffusion prediction and path planning module includes the following steps: Initialize the Gaussian plume diffusion model or the Lagrange particle diffusion model, and dynamically calibrate the model parameters based on real-time meteorological data; Starting from the emission source, and taking into account the current wind speed and direction, calculate the initial diffusion parameters of the plume in the horizontal and vertical directions; Iterative calculations are performed with a fixed time step to predict the spatial location and morphological changes of the plume in the next 5 to 30 minutes, generating a predicted plume envelope that evolves over time. With the goal of maximizing information gain or minimizing detection uncertainty, a series of spatially dispersed and temporally connected waypoint sequences are calculated for each node in the mobile monitoring cluster within the predicted plume envelope.

5. The real-time monitoring system for radiation dose of radioactive waste gas emissions according to claim 4, characterized in that, The specific implementation of the physically constrained Kriging space interpolation algorithm is as follows: The algorithm treats each monitoring data point as a function of spatial location and time; When constructing the variogram model, not only is the geometric distance between data points considered, but the real-time wind direction is also introduced as an anisotropic factor, so that the interpolation weight along the wind direction is higher than that in the vertical wind direction. Meanwhile, the algorithm incorporates the concentration decay law described by the atmospheric diffusion equation as a soft constraint into the Kriging equations to ensure that the interpolated three-dimensional dose field physically conforms to the basic laws of plume diffusion.

6. The real-time monitoring system for radiation dose of radioactive waste gas emissions according to claim 5, characterized in that, The specific mode in which the mobile monitoring cluster performs collaborative detection is as follows: The cluster collaborative control module organizes the mobile monitoring cluster into a leader-follower formation. One of the mobile monitoring nodes is designated as the leader node, which flies to the upstream or core region of the predicted plume envelope according to path planning instructions; The remaining mobile monitoring nodes, as subordinate nodes, dynamically adjust their positions based on the real-time dose rate measurement data fed back by the leader node and the global optimization instructions issued by the data fusion and collaborative control center, forming a fan-shaped scanning array of the plume cross section or a gradient tracking queue of the plume longitudinal direction.

7. The real-time monitoring system for radiation dose of radioactive waste gas emissions according to claim 6, characterized in that, The system operates within an adaptive triggering and multi-mode switching framework, which includes a regular cruise mode and an emergency tracking mode. In normal patrol mode, the mobile monitoring cluster conducts a background radiation level survey according to a preset grid. When any unit in the fixed monitoring base station network or the mobile monitoring cluster detects that the dose rate exceeds the preset first-level threshold, the system automatically switches to emergency tracking mode. In emergency tracking mode, the data fusion and collaborative control center immediately activates the plume diffusion prediction and path planning module, and instructs the mobile monitoring cluster to abandon its original patrol mission, rush to and lock onto the area with excessive radiation, and carry out high-density, high-dynamic tracking and monitoring of the radioactive plume in a collaborative detection mode.

8. The real-time monitoring system for radiation dose of radioactive waste gas emissions according to claim 7, characterized in that, The high-sensitivity gamma-ray spectroscopy detection module in the fixed monitoring base station network uses lanthanum bromide or zinc cadmium telluride detectors, with an energy resolution better than 3%. The data receiving and preprocessing module of the data fusion and collaborative control center includes an energy spectrum analysis submodule. This submodule performs spectral analysis on the uploaded energy spectrum data to identify the characteristic peaks of key nuclides and estimate their activity concentrations.

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