179 results about "Radiometric data" patented technology

The invention provides an unmanned aerial vehicle identification early warning method and system. The method comprises the following steps: acquiring RGB image data, thermal radiation data and spectral data of an unmanned aerial vehicle no-fly zone through a visible light camera, an infrared thermal imager and a multispectral imager; performing transmission preprocessing on the RGB image data, the thermal radiation data and the spectral data, and adaptively adjusting multi-level fusion of a fusion weight based on real-time environmental parameters to generate target fusion data; based on a deep learning model and a tracking prediction algorithm, performing unmanned aerial vehicle identification early warning on the target fusion data, and generating early warning data; and transmitting the target fusion data and the corresponding abnormal event log to a cloud server, and updating the deep learning model by adopting the target fusion data and the abnormal event log. Through cooperative work of a multi-mode sensor, visible light, infrared, multispectral and other wave bands are covered, all-weather and full-scene unmanned aerial vehicle detection is achieved, the fusion weight is adjusted in real time based on real-time environment parameters, and the accuracy of the recognition result under the complex air situation is ensured.

The invention discloses a radioactive substance multi-point synchronous detection and identification method and system, and relates to the technical field of radioactive substance monitoring. Comprising the following steps: step 1, collecting multi-point radiation data in real time, and preprocessing and storing the data; step 2, constructing a spatial adjacency matrix, estimating a local spatial gradient, calculating an anomaly degree value, taking optimization measures, and performing collaborative anomaly evaluation on the monitoring nodes; 3, calculating a total fitting error value, reversely deducing a leakage source position and leakage intensity in real time, and taking corresponding measures in real time; 4, abnormal trend identification is carried out, an early warning judgment value is calculated, and graded early warning and multi-node cross confirmation measures are implemented; and 5, receiving and storing various types of data, carrying out visualized analysis on the data, and supporting event processing and feedback. The problems that due to the fact that some devices are good in shielding and have physical obstruction, trace leakage is difficult to detect by a single-point monitor, and the risk of long-term retention pollution exists are solved.

The invention relates to the technical field of photovoltaic module detection, in particular to a hot spot detection system and method for a photovoltaic module. Comprises: a multispectral imaging module configured to synchronously collect image data of a photovoltaic module in a visible light band, a near-infrared band and a long-wave infrared band; the electroluminescence analysis module is in signal connection with the multispectral imaging module and is used for acquiring carrier recombination radiation data of the photovoltaic module in a reverse bias state; the dynamic threshold value processing module is configured to establish a dynamic correlation model of the environment parameters and the hot spot characteristic parameters; the three-dimensional reconstruction module is configured to perform spatial registration on the multispectral imaging data and the electroluminescence data and construct three-dimensional temperature field distribution of the photovoltaic module; the defect positioning module is configured to determine the accurate position of a hot spot according to temperature field distribution and carrier recombination characteristics; according to the scheme, a novel detection system architecture with multi-mode collaboration, high dynamic adaptability and three-dimensional analysis capability is constructed.

The invention discloses a high-resolution solar radiation data correction method and system based on deep learning, and the method comprises the steps: obtaining meteorological data and digital elevation model data, and carrying out the preprocessing; dynamically optimizing parameter configuration of the WRF model, and simulating and outputting high-temporal-spatial-resolution meteorological data as training data; fusing solar radiation flux values in meteorological reanalysis data and near-real-time product meteorological data as label data of a correction model; inputting the high-temporal-spatial-resolution meteorological data and the label data into a pre-constructed multi-scale feature fused deep residual coding and decoding network model for training, and obtaining an optimal parameter model based on multiple loop iterations; and correcting solar radiation flux data output by the WRF mode by using the optimal parameter model. According to the method, the problem that the radiation variable value output by the WRF in the traditional numerical weather mode is consistent with the real data trend but deviates is effectively solved, and the reliability of meteorological data simulation is enhanced.

The invention discloses an intelligent earth surface solar radiation forecasting method based on satellite remote sensing, and belongs to the field of information technology and meteorological technology. The method comprises the following steps: S1, acquiring geostationary satellite observation data, satellite inversion earth surface solar radiation data and terrain factor data, and executing Z-score standardization processing; s2, performing dimensionality reduction on the standardized input sequence and the target data by using a pre-training auto-encoder to obtain latent variables of a historical sequence and a future cloud picture observation sequence; s3, inputting the dimension-reduced historical sequence into a conditional potential space diffusion model, modeling the historical satellite cloud picture sequence, and predicting a probabilistic potential variable of a cloud picture at a future moment; converting the solar radiation prediction result into a corresponding earth surface solar radiation prediction result through an inversion model; and S4, the self-encoder is adopted to perform dimension raising to obtain a final prediction result. According to the method, based on a frequency domain and space domain multi-modal feature adaptive fusion mechanism, while a complex cloud-radiation relation is modeled, predicted structural consistency and physical rationality of radiation intensity are kept.

The invention provides a multi-scale photovoltaic power prediction method and system fusing numerical weather forecast and a physical information neural network, relates to the technical field of photovoltaic power prediction, and realizes rolling prediction of future meteorological parameters and horizontal radiation intensity through numerical weather forecast. The authenticity and the stability of the meteorological data are effectively improved by combining quantile mapping and cascade correction of the time sequence mode attention neural network; and through combined modeling of a physical information neural network and a time sequence characteristic network, meteorological and radiation data subjected to multi-level correction and conversion are deeply fused with a photovoltaic system physical law, and high-precision prediction of photovoltaic power is realized. The whole prediction process has automatic anomaly elimination and deletion complementation capabilities, the prediction robustness under complex meteorological conditions and extreme environments is enhanced, and the sequential response and physical consistency of photovoltaic power are optimized, so that the engineering applicability and intelligent level of the system are greatly improved.

The invention provides a base station electromagnetic radiation visual monitoring method and device, and the method comprises the steps: determining a three-dimensional topographic map of a monitoring region, carrying out the electromagnetic radiation measurement of an actual geographic position corresponding to a preset collection point on the three-dimensional topographic map, and obtaining the actual measurement data; obtaining beam characteristic parameters of each base station and space coordinate data of the actual geographic position, and calculating predicted electromagnetic radiation data of the actual geographic position according to the electromagnetic radiation prediction model; correcting the model, and calculating electromagnetic radiation data of a target area on the three-dimensional topographic map based on actually measured electromagnetic radiation data and the corrected electromagnetic radiation prediction model; and visually displaying the actually measured electromagnetic radiation data of the preset acquisition point and the electromagnetic radiation data of the target area. Therefore, accurate monitoring and visual display of the electromagnetic radiation of the base station are realized, so that the accuracy and reliability of electromagnetic radiation evaluation are improved, and the overall change rule of the electromagnetic radiation value of each position in the whole monitoring area can be visually observed.

The invention discloses a broadband oscillation characterization platform of a multi-chip power module and a near-field characteristic evaluation method, and belongs to the technical field of power electronics. The continuous operation condition of the power converter is decoupled into a series of discrete switching points, transient near-field radiation data of a to-be-tested power module under the discrete switching points are obtained through a double-pulse test, and near-magnetic field radiation signals are reconstructed; performing time-frequency analysis on the reconstructed near magnetic field radiation signal to generate a two-dimensional time-frequency matrix; and calculating a radiation energy entropy value based on the two-dimensional time-frequency matrix, fusing the radiation energy entropy value with the peak amplitude in the two-dimensional time-frequency matrix to generate a comprehensive EMI index for evaluating the broadband oscillation electromagnetic interference risk, and triggering EMI risk early warning when the comprehensive EMI index exceeds a threshold value. According to the method, the spectrum complexity is quantified through the radiation energy entropy, the multi-dimensional EMI risk assessment is carried out by fusing the peak amplitude of the time-frequency matrix, and the broadband oscillation in the multi-chip parallel power module can be accurately and efficiently represented.

The invention discloses a polar cloud mask quality inspection and correction method and device, and compared with the prior art, the method carries out the standardized grid projection of active and passive remote sensor data, and carries out the consistency evaluation of the data quality as the weight. Cloud mask quality inspection and correction between different active and passive remote sensing sensors are realized, the limitation that time-space matching needs to be performed one by one in traditional satellite remote sensing data fusion is broken, and a reliable cloud mask detection result is identified by using high precision of a laser radar and consistency of multiple passive satellites. And then the result is transmitted to radiation data for correction, so that the result is not influenced by different parameters among different satellite sensors, flexible adjustment can be performed according to output requirements of different data sources, spatial resolution and the like, and more comprehensive data support is provided for polar cloud mask product optimization. The method is helpful for improving cognition on scientific problems such as polar cloud radiation effect and polar climate change, and has important scientific research and application values.

The invention discloses an earth surface downlink short-wave radiation space downscaling method based on a super-resolution reconstruction technology, belongs to the technical field of meteorological data analysis, and solves the problems of insufficient solar radiation data space resolution and weak earth surface heterogeneity characterization capability in the prior art. Carrying out super-resolution reconstruction on the radiation data set by adopting a super-resolution combination model, and carrying out weighted fusion on a reconstructed data set output by the super-resolution combination model; according to the method, the output results of the multiple models are subjected to weighted fusion, weight optimization of the super-resolution sub-models is performed in combination with the high-resolution terrain factors, spatial downscaling from 5km to 1km resolution is finally realized, the spatial precision of the solar radiation data is remarkably improved on the basis of keeping the hour-level time resolution of the original data, and the accuracy of the solar radiation data is improved. And more earth surface heterogeneity information can be captured, and meanwhile, the high-time-resolution application requirement is met.

The invention discloses a multi-target path planning method and device, equipment and a storage medium, and relates to the technical field of traffic path planning, and the method comprises the steps: obtaining solar radiation data and original map data, carrying out the multi-source data fusion based on the solar radiation data and the original map data, and obtaining the radiation road network data; based on the radiation road network data, a total cost function of the path length is constructed through an accumulated cost function of the path length and a heuristic function of the estimated cost, and candidate paths are generated according to the total cost function; on the basis of the radiation road network data, calculating the path average radiation intensity of the candidate path, and further obtaining the energy recovery amount of the candidate path; constructing a dual-target cost function based on the total cost function and the energy recovery amount, adjusting node priorities and screening and updating a non-dominated solution set according to the dual-target cost function, and generating a target candidate path set according to the non-dominated solution set; and determining an optimal balance path in the target candidate path set through multi-dimensional index quantitative evaluation and balance coefficient sorting.

The invention provides a multi-sensor data fusion method and system based on an intelligent pod. According to the method, a radiation data flow of an intelligent pod multispectral sensor in an electromagnetic interference field is collected; based on the data, the quantitative attenuation coefficient of the radiation value of each wave band in the interference field is calculated by using a radiation transfer equation. And generating a directional beam of the phased-array antenna by using the coefficient, and scanning a target area to obtain echo data. And finally, performing joint sparse representation on the original radiation data stream and the target echo data to generate a fusion result. The invention discloses multi-sensor data fusion based on an intelligent pod. According to the method, the anti-interference wave beam scanning target is dynamically generated by quantifying the attenuation of electromagnetic interference on radiation of each wave band, and the sensing performance of the intelligent pod in a complex electromagnetic environment is improved by combining the joint sparse representation and fusing the multi-source data.

The invention provides a hyperspectral remote sensing image generation method and device based on three-dimensional scene radiation simulation, relates to the technical field of remote sensing data processing, and aims at solving the technical problems that in the prior art, hyperspectral remote sensing image data acquisition cost is too high, data sources are few, and the resolution is low. The method comprises the following steps: determining three-dimensional scene data according to a user demand; inputting the three-dimensional scene data into a pre-constructed hyperspectral imaging simulation model, and executing the following operations: based on a global coordinate system, starting from an original point, and emitting randomly distributed light to a three-dimensional scene object through a virtual imaging plane, the three-dimensional scene object being used for simulating optical response of a real ground object structure after light incidence; determining an intersection point of each light ray and the three-dimensional scene object; according to the geometric information and the material information corresponding to the intersection point, combining atmospheric radiation parameters, calculating radiation information of light and radiation data of an entrance pupil of the remote sensor; and generating a hyperspectral remote sensing picture according to the radiation data at the entrance pupil.

The invention discloses an electric power intelligent monitoring system based on multi-device cooperative linkage and an operation and maintenance method, and belongs to the technical field of electric power intelligent monitoring and operation and maintenance. Radiation data and historical decay records are collected through a sensor, a linear regression algorithm is adopted to fit and establish an energy spectrum purity attenuation model, and the dose loss proportion is calculated in real time; carrying out dynamic compensation on beam intensity and irradiation time based on the proportion, fusing real-time dose monitoring data by utilizing a Kalman filtering algorithm, and optimizing a beam intensity value to suppress noise interference; the irradiation time is further adjusted according to whether the dose loss exceeds a threshold value or not, and a dynamic compensation combination is formed; the effectiveness of the combination in each stage of the source life cycle is verified through the simulation module, and the verified compensation parameters are updated to the control system in real time, so that closed-loop regulation and control are realized. According to the invention, the whole process of dose output in the irradiation process is accurately and stably controlled, and the consistency and reliability of the irradiation process are remarkably improved.

The invention discloses a resource evaluation method and system based on multi-landform feature correction, which remarkably improves the accuracy of wind speed and solar radiation data by combining physical constraint correction and machine learning methods, and particularly improves the accuracy of the wind speed and solar radiation data under the conditions of complex terrains and multiple earth surface types. The problem of systematic errors existing in ERA5 reanalysis data in the prior art is solved. Specifically, through elimination of invalid values of radiation data at night and correction of wind speed data based on surface roughness, deviation caused by factors such as terrain shielding, vegetation canopy reflectivity and urban building group wind resistance effect is effectively eliminated. The ERA5 data is trained and optimized by using a machine learning model such as a random forest, so that the wind speed and radiation data at different geographic positions, seasons and time periods can be more accurately corrected, and the corrected data is more in line with an actual observation result.

Lowest cost usage scheduling of an energy system during a time interval of interest is achieved by utilizing two components of learning and optimization. First, several learning methods are used to forecast energy production and if needed energy consumption of a given group of energy components as a function of historical production data, weather, and solar irradiance data collected from weather and geo reports. A classification approach is used to select the learning model. A classification approach is used to select the learning model and approach. Then, an optimization problem is formulated and solved to create the optimal schedule of energy usage during time intervals of interests for the given group of energy components subject to scheduling and equipment constraints. Accordingly, integrated iterative methods, programs, and systems are described aiming at minimizing the cost of energy consumption for the given group of energy components within time intervals of interest.

The invention relates to the technical field of quality control detection, in particular to a radiotherapy radiation amount detection device and method based on multi-sensor fusion, and the device comprises a data obtaining module which obtains the state information of the connection between a functional plug-in and a detection base, and a data processing module which obtains the state information of the connection between the functional plug-in and the detection base and obtains the state information of the connection between the functional plug-in and the detection base, determining first space attitude information of each functional plug-in relative to the detection base; the global space attitude determination module is used for determining global space attitude information of each functional plug-in in a radiotherapy coordinate system based on the first space attitude information and second space attitude information of the detection base; the multi-dimensional radiation data detection module is used for synchronously acquiring multi-dimensional radiation detection data from each functional plug-in based on global space attitude information in the process of executing radiotherapy irradiation; according to the invention, through combined sensing formed by the micro displacement sensor and the inertial measurement unit, real-time accurate measurement and dynamic compensation of the spatial attitude of each functional plug-in are realized.

The invention provides a radioactive operation safety assessment and warning system for nuclear medicine medication nursing, and the system comprises a data obtaining and processing module which is used for deploying a space monitoring network and detecting radiation data; the real-time radiation monitoring module is used for collecting operation behavior data and dose data in real time and carrying out abnormal operation identification and risk scoring; the intelligent prediction and evaluation module is used for constructing a risk prediction model and carrying out risk prediction on the real-time data to obtain a predicted risk level; the operation safety evaluation module is used for automatically calculating the safety score of the operation and generating a safety evaluation report; and the diversified intelligent warning module is used for calculating a comprehensive score and carrying out graded sound-light alarm. Through efficient and real-time data monitoring and intelligent and accurate risk assessment and operation safety assessment, the risk of radioactive exposure in nuclear medicine medication nursing can be effectively reduced, the safety of medical staff and patients is guaranteed, and the scientificity and normalization of medical operation are improved.

According to the efficiency adaptation method applied to the solar communication unmanned aerial vehicle in the stratosphere, collaborative optimization of energy management and communication service of the solar unmanned aerial vehicle in the stratosphere environment is achieved by constructing a dynamic solar radiation database, predicting communication load and setting a dynamic threshold value and a multi-objective optimization mechanism. The method has the capability of responding to solar radiation fluctuation and communication load change in real time, effectively avoids the problems of misalignment of electric quantity management and interruption of a communication link, and remarkably improves the cruising ability and task reliability of the unmanned aerial vehicle. Meanwhile, according to the method, through a data-driven closed-loop optimization mechanism, the energy utilization efficiency and the communication quality are both considered, and the method has good practicability and popularization value.

The invention discloses an earth surface short-wave radiation product production method and device and a long-short-term memory network training method and device, and relates to the technical field of aerospace, and a specific implementation scheme is as follows: extracting a first short-wave radiation data set and a second short-wave radiation data set which are aligned in time from first earth surface short-wave radiation data collected by a satellite; acquiring a photovoltaic short-wave radiation data set which is acquired by a ground photovoltaic radiometer and is aligned with the first short-wave radiation data set in time; determining an albedo data set based on the satellite albedo product and the surface land cover product; obtaining an input short-wave radiation data sequence based on the first short-wave radiation data set, the second short-wave radiation data set, the albedo data set, the photovoltaic short-wave radiation data set and the ground photovoltaic radiometer coordinate vector point; inputting the input short-wave radiation data sequence into a pre-trained long short-term memory network to obtain an initial earth surface short-wave radiation product; and obtaining a target earth surface short-wave radiation product based on the initial earth surface short-wave radiation product.

The invention discloses a super-surface sub-terahertz inversion imaging method and system, and relates to the field of multi-dimensional electromagnetic imaging. The problems of view field mismatching, output delay, large-size imaging and the like existing in a directional aperture sharing TR framework of an existing APCI based on the metasurface are solved, synchronous extraction of sub-terahertz frequency band active scattering and passive radiation data is achieved through spatial staggered layout and related average processing technologies, and the system has the advantages that the system is simple in structure and convenient to operate, and the system is easy to popularize and use. And a solution is provided for single-region information decoupling and multi-target fusion imaging. The highly integrated and high-throughput sub-terahertz APCI technology promotes the development of the detection system towards the direction of miniaturized deployment and real-time data reading. Besides, a non-imaging security check scheme is also introduced, non-interactive autonomous identification and hidden monitoring of hidden objects in public scenes are realized, and the method is also suitable for the application fields of aircraft navigation positioning, abnormity monitoring, non-interactive hidden security check and the like.

Methods and computing apparatus for implementing a radiation dosimetry process. An example process may include exposing a first radiation sensitive film to a series of known doses of radiation, measuring a first set of radiation data with a measurement device, and determining a calibration curve. The calibration curve may be determined by selecting Raman spectral ranges based on the first set of radiation data, determining a plurality of band area ratios, and generating the calibration curve based on plotting the band areas and ratios compared to known dose. The radiation dosimetry process then exposes a second radiation sensitive film to an unknown dose of radiation, measures a second set of radiation data for the second radiation sensitive film with the measurement device, and determines a dose exposure level for the second radiation sensitive film by comparing the second set of radiation data with the calibration curve.

The invention discloses a circuit board production process management and control method and system based on a multilayer circuit. The method comprises the following steps: establishing an interlayer transmission line parameter model of a multilayer circuit board, and calculating electromagnetic field distribution based on a deformation telegraph equation and a parallel plate resonance effect; performing transmission characteristic simulation verification; optimizing production environment parameters, and selecting an area of which the electric field intensity is lower than 45% maximum value as a wiring optimal area; implementing a layered wiring strategy, and optimizing an interlayer wiring path according to the transmission matrix; production data are dynamically monitored, temperature, humidity and electromagnetic radiation data are collected in real time, and machining parameters are adjusted in combination with a transmission matrix correction value. According to the method, the transmission characteristics are accurately predicted, the production environment parameters are optimized, the influence of the external environment on the performance of the circuit board is effectively reduced, and the stability and reliability of the circuit board are improved. Through establishment of a parameter model and simulation verification, comprehensive management and control of the production process of the multilayer circuit board are realized.

The invention discloses an offshore salt mist aerosol monitoring system and method based on a drifting buoy, and relates to the technical field of marine atmospheric environment monitoring, and the method comprises the steps: transmitting the position and time information received by a GNSS receiver to a main control module, and carrying out the resolving of the main control module, and obtaining a preliminary direction; transmitting the data of the attitude measuring instrument to the main control module; the main control module corrects the initial azimuth angle and the elevation angle according to the attitude data, and adjusts the accurate direction of the sun photometer according to the correction result; calculating the optical thickness of the aerosol according to radiation data measured by the sun photometer; the aerosol particle spectrum distribution is inversed according to the aerosol optical thickness; and the main control module performs information interaction on the inverted aerosol particle spectrum distribution and the land through the wireless communication module. The defects of a traditional mode are effectively overcome, and the optical parameters and the dynamic change process of the salt mist aerosol are captured more accurately.

The application discloses a kind of based on agent model's air bag template ice shell building weatherability optimization design method, it is related to building design technical field.The problems that existing technology lacks the quantitative evaluation index of ice shell building weatherability and lacks the construction of universal agent model are solved, including: S1 stage is established microclimate response agent model, through orthogonal experimental design to generate ice shell case set, extract morphological characteristics and spatial characteristics, obtain wind snow distribution label by combining CFD simulation, construct neural network agent model;S2 stage is fused multiple tools to realize performance optimization, utilize Grasshopper parametric modeling to extract features, call agent model to predict surface snow wind distribution, obtain radiation data jointly by Ladybug, combine sublimation rate to calculate initial and later strain energy and weatherability index, finally, morphological parameters are multi-objective optimized by NSGA-II algorithm, it has application prospect in the field of ice shell building structure optimization.

This invention relates to the fields of nuclear detection electronics and radiation signal processing technology, specifically to an intelligent analysis system and method for nuclear radiation data. The system includes: acquiring a discrete voltage sequence output by the detector; marking pulse signals as clean pulses and calculating the real-time decay constant; calculating the net signal amplitude using a digital twin state-space recursive model; determining the real-time count rate based on the net signal amplitude and calculating the dynamic time window width based on the real-time count rate; discretely accumulating the net signal amplitude based on the dynamic time window width to generate a single-particle physical energy value; determining the measured peak position based on the single-particle physical energy value and generating a gain adjustment coefficient by combining the measured peak position with the real-time decay constant; and outputting a gain control signal based on the gain adjustment coefficient. This invention ensures precise synchronization between the subsequent calculation model and the current physical state of the detector, thereby significantly improving the physical authenticity and accuracy of energy spectrum analysis under varying temperature conditions.

The application belongs to the field of cold region track engineering and subgrade engineering, and specifically discloses a high-speed rail ballastless track-subgrade freezing characteristic simulation test device based on meteorological conditions in cold regions, which comprises a programmable high-low temperature test box for controlling the alternating change of environmental temperature, a rainfall simulation device for adjusting according to different rainfall in cold regions, a solar radiation simulation device for adjusting according to different illumination in cold regions, a ballastless track structure composed of unit block type structure, a subgrade structure composed of three-layer structure, and a data acquisition and monitoring module for monitoring and collecting deformation displacement, temperature, moisture and radiation data in real time. Through the device, real-time monitoring of relevant parameters such as the temperature of the high-speed rail ballastless track, deformation, the temperature of the subgrade, moisture and deformation in cold regions can be realized, the freezing depth of the subgrade and the contribution of each soil layer in frost heaving deformation can be determined, and the influence of the ballastless track on the freezing characteristics of the subgrade can be further analyzed.

This application relates to a multimodal system for accurately detecting a target location for a vehicle and navigating the vehicle to the target location. The system includes at least one multimodal fiducial marker (4) and a heterogeneous perception device (8) coupled to an unmanned or manned vehicle (9). The marker (4) can be detected by analyzing visual, thermal, and point cloud data. The heterogeneous perception device (8) uses cameras and range sensors to collect both photometric and radiometric data. This multimodal system improves the situational awareness of the vehicle (9) and increases its detection and navigation capabilities. As a result, the system (4, 8) operates in a multimodal manner under challenging environmental conditions, providing the vehicle (9) with the ability to perform robust, redundant, and reliable detection of the vehicle's target location (10).

To provide a ground measurement system capable of precisely obtaining a ground state as moving an RI measuring instrument.SOLUTION: A ground measurement system 1 is provided with: a vibration roller 2 (traveling device); a scattering-type RI measuring instrument 10 mounted on the vibration roller 2; a location information receiver 3 receiving location information of the RI measuring instrument 10; a control device 20 producing measurement results of a compaction degree or water ratio of the ground on the basis of radiation data measured with the RI measuring instrument 10; and a display 4 displaying the location information and the measurement result of the RI measuring instrument 10. Every time traveled distance of the RI measuring instrument 10 reaches a specific distance, the control device 20 produces the measurement results and causes the display 4 to display the measurement results.SELECTED DRAWING: Figure 1

This invention relates to the field of radiation leakage detection technology, and discloses a radiation leakage detection method and apparatus based on a target sensor. The method includes: determining the current state of a radiation device, and acquiring a first set of radiation data of the radiation device in the current state based on the target sensor corresponding to the radiation device and according to the acquisition mode corresponding to the current state; determining whether the radiation device has experienced radiation leakage based on the first set of radiation data and a preset radiation threshold; when radiation leakage occurs, determining the radiation leakage level, and triggering a radiation leakage alarm based on the radiation leakage level. Therefore, this invention can achieve real-time leakage monitoring of radiation devices, adapt to the detection needs of different working states, accurately identify radiation leakage risks and quickly trigger alarm measures, effectively improve the active safety protection capability of radiation devices, and promptly ensure the radiation safety of operators and surrounding personnel, thereby improving the safety and stability of radiation device use.