Efficient radiation worker personal dose management method and system

Abstract

The invention discloses an efficient radiation worker personal dose management method and system, and the method comprises the steps: collecting first object data, and carrying out the first preprocessing; and carrying out synchronous transmission on the preprocessed data, and constructing a real-time data stream. And performing first identification calculation on the synchronous data, analyzing the identified abnormal data, integrating the normal data and analyzing the trend. According to the efficient radiation worker personal dose management method and system, the real-time performance, accuracy and processing efficiency of radiation dose data are remarkably improved, and the problems that in the prior art, abnormal recognition is not accurate, manual operation consumes long time, and the trend analysis capacity is insufficient are solved. According to the invention, more reliable radiation risk early warning and management can be realized in practical application, and the radiation safety level and the management efficiency can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of radiation protection, and particularly to an efficient personal dose management method and system for radiation workers. Background Art

[0002] In recent years, with the extensive development of nuclear energy technology, radiology, and industrial radiation applications, the importance of radiation safety management has become increasingly prominent. Dose monitoring of radiation workers and related personnel is one of the core contents of radiation protection work, aiming to ensure that the radiation exposure level of workers is always within an acceptable range, thereby reducing the health risks brought by radiation. Currently, traditional radiation dose management systems mostly adopt fixed devices or manual recording methods, such as thermoluminescent dosimeters (TLDs) and electronic personal dosimeters (EPDs). Although these methods play an important role in dose monitoring, they have obvious limitations. For example, traditional devices usually lack real-time data transmission and abnormal monitoring capabilities, making it difficult to dynamically obtain radiation dose trends or quickly respond to abnormal radiation events. In addition, due to the lack of correlation analysis with environmental factors, traditional methods have insufficient radiation risk assessment capabilities in complex working scenarios.

[0003] Existing radiation management technologies have many problems in data collection, transmission, and analysis. Specifically: First, traditional dosimeter data usually needs to be manually collected and sorted, which is inefficient and prone to errors; Second, the data processing link lacks effective abnormal identification and analysis means, and it is impossible to accurately distinguish radiation abnormalities caused by equipment failures, environmental changes, or operation abnormalities; Third, existing technologies are difficult to perform real-time trend analysis and risk prediction, resulting in radiation protection work tending more towards passive management and lacking proactive preventive measures. With the development of wireless communication and intelligent computing technologies, modern dose management technologies have the potential for further improvement in terms of real-time performance, accuracy, and intelligence. Summary of the Invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the technical problems solved by the present invention are: Traditional technologies cannot achieve real-time collection and transmission of radiation doses. Especially in complex environments, manual data recording and offline analysis may lead to response delays.

[0006] Existing technologies lack dynamic analysis algorithms that combine environmental factors, historical data, and real-time data, and cannot accurately distinguish equipment abnormalities, environmental radiation abnormalities, and operation abnormalities.

[0007] Existing technologies are difficult to perform short-term fluctuation analysis and long-term trend prediction of radiation doses, and cannot provide proactive warnings or optimization measures for managers.

[0008] Poor system integration: The existing systems have single functions and fail to achieve full-process integration from data collection, transmission, analysis to visualization management, which limits management efficiency and scenario applicability.

[0009] To solve the above technical problems, the present invention provides the following technical solution: An efficient personal dose management method for radiation workers, including: collecting first object data and performing first preprocessing.

[0010] Synchronously transmit the preprocessed data to construct a real-time data stream.

[0011] Perform first identification calculation on the synchronized data, analyze the identified abnormal data, and integrate and analyze the trend of normal data.

[0012] As a preferred solution of the efficient personal dose management method for radiation workers described in the present invention, wherein: the collecting of the first object data includes, through biometric technology, identifying the first object, and collecting the first object data through a monitoring device worn by the first object.

[0013] As a preferred solution of the efficient personal dose management method for radiation workers described in the present invention, wherein: the performing of the first preprocessing includes cleaning, standardizing the collected first object data, extracting key features and analyzing the features.

[0014] As a preferred solution of the efficient personal dose management method for radiation workers described in the present invention, wherein: the synchronously transmitting the preprocessed data to construct a real-time data stream includes packing the preprocessed first object data and the extracted key features, temporarily storing them in an edge computing device, and uploading them to a cloud server through a data transmission protocol to form a real-time data stream.

[0015] As a preferred solution of the efficient personal dose management method for radiation workers described in the present invention, wherein: the first object includes but is not limited to workers entering the radiation control area, and the first preprocessing includes data cleaning, data standardization and feature extraction.

[0016] The first identification calculation is the algorithm dynamic analysis of dose data.

[0017] As a preferred solution of the efficient personal dose management method for radiation workers described in the present invention, wherein: the performing of the first review operation on the synchronized data includes performing a preliminary check on the synchronized data, including integrity verification and validity verification.

[0018] Use an improved dynamic weighted anomaly detection algorithm to analyze the data passing the preliminary check.

[0019] The algorithm process includes inputting real-time dose data, time stamps, historical dose data sequences, and current environmental radiation dose rates.

[0020] Considering the influence of the current environmental radiation dose rate and the historical average environmental radiation dose rate, calculate the dynamic weight, and calculate the dose prediction value at the next time point based on the dynamic weight and the weighted regression model.

[0021] Calculate the deviation between the current dose data of the first object and the predicted value, set the anomaly detection threshold, and when the deviation is greater than the anomaly detection threshold, mark the current dose data as abnormal data.

[0022] As a preferred solution of the efficient personal dose management method for radiation workers described in the present invention, wherein: analyzing the identified abnormal data, integrating and analyzing the trend of normal data includes classifying the abnormal data into equipment anomalies, environmental anomalies, and operation anomalies, and analyzing and troubleshooting them separately.

[0023] Group the normal data according to time periods, the first object number, and the first object's working area, and perform short-term trend analysis and long-term trend prediction.

[0024] An efficient personal dose management system for radiation workers, characterized in that it includes:

[0025] A data acquisition module that acquires data of the first object and performs first preprocessing.

[0026] A synchronous transmission module that synchronously transmits the preprocessed data to construct a real-time data stream.

[0027] A calculation module that performs first identification calculations on the synchronous data, analyzes the identified abnormal data, and integrates and analyzes the trend of normal data.

[0028] A computer device includes a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, it implements the steps of the method described above.

[0029] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the steps of the method described above.

[0030] The beneficial effects of the present invention: It realizes the efficient binding of the identities of workers and radiation monitoring devices, and uses data cleaning, standardization, and feature extraction to ensure the uniqueness and consistency of the collected data. This step provides an accurate and high-quality data basis for subsequent data analysis. By collecting radiation doses, environmental parameters, and auxiliary information in real time, the comprehensiveness and reliability of the data are effectively improved.

[0031] With the collaborative work of edge computing and cloud servers, the real-time transmission and stability of data are ensured. Using protocols such as MQTT or WebSocket meets the requirements of low-latency and high-frequency data transmission, while enhancing the security of the system through data encryption and backup. This step significantly improves the real-time performance and efficiency of radiation dose management, providing real-time data stream support for anomaly monitoring and trend analysis.

[0032] Using the improved Dynamic Weighted Anomaly Detection algorithm (DWAD), combined with environmental factors, historical data, and time intervals, dynamically analyzes dose data and accurately identifies abnormal data. By classifying and analyzing equipment anomalies, environmental anomalies, and operation anomalies, quickly locates the problem source, reducing the false alarm rate and missed alarm rate. This step effectively solves the defect of inaccurate anomaly identification in traditional technologies and greatly improves the intelligent level of radiation safety management.

[0033] Group, store, and integrate normal data, and use the improved ARIMA model to analyze short-term fluctuations and long-term trends of radiation doses. By combining historical data and environmental factors, generates accurate risk assessment and prediction results, providing optimization suggestions and decision-making support for managers. This step realizes the transformation from passive management to active protection, improving the foresight and accuracy of radiation protection. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts. Among them:

[0035] Figure 1 It is the overall flowchart of an efficient personal dose management method and system for radiation workers provided by the first embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0036] To make the above objects, features, and advantages of the present invention more obvious and understandable, the specific embodiments of the present invention will be described in detail below with reference to the drawings of the specification. Obviously, the described embodiments are some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0037] Example 1, referring to Figure 1 , which is an embodiment of the present invention, provides an efficient personal dose management method for radiation workers, including:

[0038] S1: Collect the first object data and perform the first preprocessing.

[0039] In the present invention, the first object is the staff entering the radiation control area, and the first preprocessing includes data cleaning, data standardization, and feature extraction.

[0040] Through biometric (fingerprint, face recognition) technology, identify the identity information of the staff entering the radiation control area. Bind the collected identity information to the radiation monitoring devices (electronic personal dosimeter EPD, thermoluminescent dosimeter TLD, whole body counter WBC) worn by individuals to ensure the uniqueness and traceability of the collected data.

[0041] Utilize the radiation monitoring devices worn by the staff to collect their real-time radiation dose characteristic parameters. The parameters include, but are not limited to, dose rate (radiation dose per unit time), cumulative dose, and radiation field environmental dose rate.

[0042] It should be noted that the data collection device transmits the collected dose data to the edge device in real time through wireless communication technology (such as Bluetooth, ZigBee) or near field communication (NFC) method.

[0043] Collect auxiliary information such as the environmental radiation level, temperature and humidity, and radiation source distribution in the working area for subsequent data verification and analysis.

[0044] Denoise and filter outlier data from the collected data, and eliminate invalid data caused by equipment failures or incorrect operations. Convert the dose data into a unified format to ensure the consistency of data collected by different devices, which is convenient for subsequent analysis. Extract the key features (dose peak, fluctuation trend) of the radiation dose data to provide a basis for subsequent data analysis.

[0045] It should be noted that the first object includes, but is not limited to, the staff entering the radiation control area, and may also be radiation therapy patients in the medical field and equipment operators in nuclear facilities.

[0046] In an alternative embodiment of the present invention, the first object is a radiation therapy patient in the medical field. Mainly focus on the dose monitoring of patients during radiation therapy, pay attention to treatment accuracy and safety, and collect treatment equipment parameters and environmental information to assist in analysis. First, perform patient identity recognition and data binding. Bind patient information through the hospital information management system (HIS), and use a medical card for identity verification. Bind the patient's identity information to the devices used for dose monitoring (such as TLD or electronic personal dosimeter) to ensure the consistency of the radiation dose data with the patient's treatment records.

[0047] During radiotherapy, the monitoring device records the radiation dose data received by the patient in real time, including the local dose rate (radiation dose per unit time at the treatment site), the cumulative treatment dose (total dose during the complete treatment process), and the environmental dose (radiation value in the non-treatment area of the treatment room).

[0048] Collect the parameter settings of the treatment device (such as dose intensity, beam time). Record the environmental radiation level, temperature, and humidity in the treatment room for subsequent analysis and dose correction.

[0049] Remove outliers (such as dose fluctuations caused by equipment startup or suspension), and perform standardization processing on the radiation dose data to ensure data consistency among different treatment devices or monitoring devices.

[0050] Extract key feature values, including:

[0051] Dose peak: used to evaluate the peak radiation at the treatment site.

[0052] Fluctuation trend: used to analyze the dose uniformity during the treatment process.

[0053] In an alternative embodiment of the present invention, the first object is the equipment operator in a nuclear facility. Mainly targeting operators in high-radiation environments, focusing on real-time radiation exposure monitoring and risk analysis in high-radiation areas, and enhancing the practicality of dose data by combining environmental and equipment parameters. First, perform operator identification and binding. Use biometric technology (fingerprint recognition) to identify the identity of the equipment operator, and bind the operator information through the internal monitoring system of the nuclear facility. Associate the operator identity information with the worn radiation monitoring device (such as EPD, WBC) to ensure the traceability of the radiation dose data.

[0054] During operation, the worn monitoring device collects the radiation dose data of the operator in real time, including the dose rate (used to evaluate the radiation level during operation in real time), the cumulative dose (used to record the total radiation exposure of the operator during work), and the working area dose (environmental radiation value collected in combination with the operator's position).

[0055] Synchronously collect the environmental radiation level in the working area of the nuclear facility, the radiation output parameters of the operating equipment, and the operation time. Set dose thresholds for high-radiation areas (such as the reactor area) for anomaly detection.

[0056] Clean up invalid data caused by equipment interference or work scenario switching. Standardize the radiation data according to the equipment model and working area to ensure data consistency.

[0057] Extract the key features of radiation exposure, including:

[0058] Dose accumulation rate: used to analyze the accumulation rate of radiation dose in a short period of time.

[0059] Regional risk distribution: used to evaluate the radiation intensity distribution law in the operation area.

[0060] S2: Synchronously transmit the preprocessed data to build a real-time data stream.

[0061] Pack the preprocessed radiation dose data, environmental information, feature analysis results, etc. The content of data packing includes but is not limited to: personnel number, real-time dose data (dose rate, cumulative dose), environmental information (background radiation, temperature and humidity), timestamp and metadata tags (equipment number, data source). Uniformly format the data to generate a standardized file for subsequent system compatibility and data parsing.

[0062] Temporarily store the packed data in the memory of the edge computing device (such as an embedded computing device) to ensure buffering and retransmission in case of unstable network or transmission interruption. The edge device has preliminary data processing capabilities and can deduplicate and aggregate data collected frequently within a short period.

[0063] Select an appropriate data transmission protocol according to the transmission requirements and scenarios:

[0064] MQTT protocol: Suitable for low-bandwidth, high-latency scenarios to ensure data real-time and stability.

[0065] HTTP / HTTPS protocol: Suitable for conventional network environments with higher data transmission security.

[0066] WebSocket protocol: Used for high-frequency real-time transmission and suitable for building a continuous data stream.

[0067] Transmit the data to the cloud server or local data center through wireless communication technologies (such as 5G, Wi-Fi) or wired networks (such as Ethernet). When the network is unstable, the system automatically switches to the offline storage mode and synchronizes the data immediately after the network resumes.

[0068] The cloud server receives the data transmitted by the edge device in real time, builds a real-time data stream pipeline to ensure that the subsequent analysis module can continuously receive real-time data input.

[0069] S3: Perform the first identification calculation on the synchronized data, analyze the identified abnormal data, and integrate and analyze the trend of normal data.

[0070] In the present invention, the first identification calculation is the algorithm dynamic analysis of dose data. Use an improved dynamic weighted anomaly detection algorithm DWAD to perform the first identification calculation on the synchronized data to distinguish normal data from abnormal data.

[0071] Calculate the deviation between the current data and the predicted value, set the anomaly detection threshold, and if the deviation between the current data and the predicted value is greater than the anomaly detection threshold, mark it as abnormal data.

[0072] Conduct an in-depth analysis of the identified abnormal data to determine its causes and impacts.

[0073] According to the characteristics of the abnormal data, classify it into the following types:

[0074] Equipment anomaly: A sudden anomaly that may be caused by a malfunction of the monitoring equipment.

[0075] Environmental anomaly: A persistent anomaly that may be caused by changes in environmental radiation.

[0076] Operation anomaly: An irregular anomaly that may be caused by improper operation of the staff.

[0077] Integrate the normal data to generate a valuable data set. Group the data according to time period, personnel number, and work area. Store the data after removing anomalies in the database to provide basic data for trend analysis.

[0078] Conduct trend analysis on the normal data, including long-term trend prediction and short-term trend analysis. For short-term trend analysis, use the sliding window method to calculate the change rate of the dose. For long-term trend prediction, use an improved ARIMA (AutoRegressive Integrated Moving Average) model to predict the future dose trend in combination with environmental factors.

[0079] The computer device can be a server. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through the system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the data cluster data of the power monitoring system. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals through a network connection. When the computer program is executed by the processor, it realizes an efficient personal dose management method for radiation workers.

[0080] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the various embodiments provided in this application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the various embodiments provided in this application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the various embodiments provided in this application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0081] Embodiment 2, an embodiment of the present invention, provides an efficient personal dose management method and system for radiation workers. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through simulation experiments.

[0082] To verify the effectiveness of an efficient personal dose management method and system for radiation workers of the present invention in radiation dose management, experiments are carried out in comparison with the prior art. The test subjects are the workers entering the radiation control area. A total of 10 participants are set up and divided into two groups: the experimental group uses the method of the present invention, and the reference group uses traditional technologies for radiation dose monitoring and management. The experiment is carried out in the radiation control area of a certain nuclear facility. The regional background radiation level is 1.2 μSv / h, the operating environment is complex, and there are equipment radiation sources and temperature and humidity fluctuations.

[0083] Prior art steps:

[0084] Staff wear traditional electronic personal dosimeters (EPDs) and manually record dose data. At the end of each working day, the dosimeter data is downloaded to a local computer via a wired connection, and the data is manually cleaned and statistically analyzed. Based on the data changes, simple cumulative dose analysis and comparison are performed, and abnormal data is manually checked.

[0085] Steps of the present invention:

[0086] Staff wear improved monitoring devices, which can collect dose data in real time, including dose rate, cumulative dose, and environmental parameters. The data is transmitted to an edge computing device via a wireless protocol and synchronized to a cloud server, forming a real-time data stream. In the cloud server, a dynamic weighted anomaly detection algorithm (DWAD) is used to perform the first identification calculation on the data, automatically screening abnormal data. The abnormal data is classified and processed according to device anomalies, environmental anomalies, and operation anomalies, and the normal data is grouped and integrated. Based on the integrated data, short-term trend analysis and long-term trend prediction are carried out, providing real-time risk warnings and optimization suggestions to managers. The key parameters recorded during the experiment include real-time dose rate (μSv / h), cumulative dose (μSv), number of abnormal data, data processing time (seconds), and abnormal check accuracy rate. The experimental results are shown in Table 1.

[0087] Table 1 Experimental results

[0088]

[0089] The test data shows that the present invention exhibits obvious advantages in multiple dimensions of radiation dose management.

[0090] The data recorded for the real-time dose rate and cumulative dose of the present invention and the prior art are basically the same, indicating that both methods can accurately collect radiation dose data. However, the present invention realizes real-time data synchronization through wireless transmission and edge computing devices, while the prior art relies on manual downloading, resulting in significant delays. The real-time nature of data processing is a major advantage of the present invention.

[0091] During the experiment, the prior art relies on manual processing of abnormal data, with the check accuracy rate only being 71%-75%, and the number of abnormal data being significantly higher than that of the present invention. This is because the prior art lacks an effective anomaly identification algorithm and is prone to mislabeling non-abnormal data as abnormal, resulting in false alarms. The present invention combines environmental parameters with historical data through a dynamic weighted anomaly detection algorithm to accurately identify anomalies, with the check accuracy rate reaching 94%-96% and the false alarm rate being significantly reduced.

[0092] The data processing time is an important indicator for measuring the efficiency of radiation dose management. In the prior art, due to the need for manual operation and post-processing, the processing time is as high as 230 - 240 seconds. The present invention adopts an automated data processing flow, and through edge computing and cloud algorithms, it only takes 80 - 85 seconds to complete, with the efficiency increased by nearly 3 times.

[0093] The present invention significantly improves the real-time performance, accuracy, and processing efficiency of radiation dose data, and solves the problems in the prior art such as inaccurate anomaly identification, long manual operation time, and insufficient trend analysis ability. The present invention can achieve more reliable radiation risk early warning and management in practical applications, which helps to improve the radiation safety level and management efficiency.

[0094] Embodiment 3 is an embodiment of the present invention, including an efficient personal dose management system for radiation workers, specifically:

[0095] A data acquisition module acquires first object data and performs first preprocessing.

[0096] A synchronous transmission module synchronously transmits the preprocessed data to construct a real-time data stream.

[0097] A calculation module performs first identification calculation on the synchronous data, analyzes the identified abnormal data, and integrates and analyzes the trend of normal data.

[0098] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered by the scope of the claims of the present invention.

Claims

1. An efficient personal dose management method for radiation workers, characterized in that, Including: Collect the first object data and perform the first preprocessing; Synchronously transmit the preprocessed data to construct a real-time data stream; Perform the first recognition calculation on the synchronized data, analyze the recognized abnormal data, and integrate and analyze the trend of the normal data.

2. The efficient personal dose management method for radiation workers according to claim 1, characterized in that: The collection of the first object data includes identifying the first object through biometric technology and collecting the first object data through the monitoring device worn by the first object.

3. The efficient personal dose management method for radiation workers according to claim 2, characterized in that: The performance of the first preprocessing includes cleaning, standardizing the collected first object data, extracting key features, and analyzing the features.

4. The efficient personal dose management method for radiation workers according to claim 3, characterized in that: The synchronous transmission of the preprocessed data to construct a real-time data stream includes packing the preprocessed first object data and the extracted key features, temporarily storing them in the edge computing device, and uploading them to the cloud server through the data transmission protocol to form a real-time data stream.

5. The efficient personal dose management method for radiation workers according to claim 4, characterized in that: The first object includes, but is not limited to, the staff entering the radiation control area, and the first preprocessing includes data cleaning, data standardization, and feature extraction; The first recognition calculation is the algorithm dynamic analysis of dose data.

6. The efficient personal dose management method for radiation workers according to claim 5, characterized in that: The performance of the first review operation on the synchronized data includes performing a preliminary check on the synchronized data, including integrity verification and validity verification; Use the improved dynamic weighted anomaly detection algorithm to analyze the data passing the preliminary check; The algorithm process includes inputting real-time dose data, time stamps, historical dose data sequences, and the current environmental radiation dose rate; Considering the influence of the current environmental radiation dose rate and the historical environmental average radiation dose rate, calculate the dynamic weight, and calculate the dose prediction value at the next time point based on the dynamic weight and the weighted regression model; Calculate the deviation between the current dose data of the first object and the predicted value, set the anomaly detection threshold, and when the deviation is greater than the anomaly detection threshold, mark the current dose data as abnormal data.

7. The efficient personal dose management method for radiation workers according to claim 6, characterized in that: The analysis of the recognized abnormal data and the integration and analysis of the trend of the normal data include classifying the abnormal data into equipment anomalies, environmental anomalies, and operation anomalies, and analyzing and troubleshooting them separately; Group the normal data according to time period, the first object number, and the first object work area, and perform short-term trend analysis and long-term trend prediction.

8. An efficient personal dose management system for radiation workers adopting the method according to any one of claims 1-7, characterized in that: A data collection module that collects the first object data and performs the first preprocessing; A synchronous transmission module that synchronously transmits the preprocessed data to construct a real-time data stream; A calculation module that performs the first recognition calculation on the synchronized data, analyzes the recognized abnormal data, and integrates and analyzes the trend of the normal data.

9. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method according to any one of claims 1 to 7.

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