Nuclear power station intelligent physical management method, device and equipment

Abstract

The invention provides an intelligent logistics management method, device and equipment for a nuclear power station, and relates to the technical field of logistics management. In some embodiments of the present disclosure, sensor data is collected by using sensor networks installed inside and around a nuclear power station; processing the sensor data to obtain an analysis result; according to an analysis result, generating a logistics path and a scheduling plan; wherein the scheduling plan is associated with the cargo priority, the safety requirement and the resource availability; in the logistics execution stage, an automatic guiding system and an unmanned transportation vehicle are used for carrying out cargo transportation, the cargo state and the vehicle state are tracked through a monitoring system, and efficient and safe transportation of cargos is achieved. After the logistics operation is completed, the logistics path and the scheduling plan are adjusted according to the collected feedback data, the automation degree of the logistics operation is improved, and then the data processing efficiency, the resource allocation efficiency and the safety are improved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of logistics management, and in particular to a method, device and equipment for intelligent logistics management of nuclear power plants. Background Art

[0002] As an energy facility, nuclear power plants have extremely high safety and efficiency requirements for logistics management. Traditional logistics management relies on manpower for cargo handling, recording, and monitoring, which is not only time-consuming and labor-intensive, but also increases the risk of personnel being exposed to potentially dangerous environments.

[0003] At present, the existing nuclear power plant logistics management system has low data processing efficiency, low resource allocation efficiency and low safety. Summary of the Invention

[0004] The present disclosure provides a method, device and equipment for intelligent logistics management of nuclear power plants, so as to at least solve the problems of low data processing efficiency, low resource allocation efficiency and low security in the existing field.

[0005] The technical solutions disclosed in this disclosure are as follows:

[0006] The present disclosure provides a method for intelligent logistics management of a nuclear power plant, including:

[0007] Collect sensor data using a network of sensors installed in and around the nuclear power plant;

[0008] Processing the sensor data to obtain analysis results;

[0009] Generating a logistics route and a scheduling plan based on the analysis results; wherein the scheduling plan is associated with cargo priority, safety requirements, and resource availability;

[0010] In the logistics execution stage, automated guidance systems and unmanned transport vehicles are used to transport goods, and monitoring systems are used to track the status of goods and vehicles;

[0011] After the logistics operation is completed, the logistics path and the scheduling plan are adjusted according to the collected feedback data.

[0012] Optionally, the sensor network includes: radio frequency identification tags and readers, GPS sensors and indoor positioning systems, temperature sensors, humidity sensors, radiation detectors, vibration analyzers, temperature sensors and pressure gauges.

[0013] Optionally, after collecting sensor data using a sensor network installed inside and around the nuclear power plant, the method further includes:

[0014] For sensors at fixed locations, a wired connection is used to transmit the sensor data;

[0015] For mobile devices or remote monitoring points, wireless communication is used to transmit the sensor data.

[0016] Optionally, the processing the sensor data to obtain an analysis result includes:

[0017] Eliminating erroneous data and abnormal values ​​in the sensor data to obtain preliminary sensor data;

[0018] performing a timestamp alignment operation on the preliminary sensor data to obtain aligned sensor data;

[0019] Calculating basic statistics of the aligned sensor data;

[0020] According to the basic statistics, trends and periodic changes in the data are identified to obtain the analysis results.

[0021] Optionally, generating a logistics route and a scheduling plan based on the analysis results includes:

[0022] Obtaining the analysis results, wherein the analysis results include: logistics demand forecasts, potential bottleneck identification, updated safety limits, radiation level data, and availability of machines and human resources;

[0023] Sorting out logistics tasks according to the cargo priority, expiration date and the safety requirements;

[0024] Based on the resource availability, assign corresponding machine and personnel resources to each of the logistics tasks;

[0025] The target path from the starting point to the end point is calculated according to a graph theory algorithm to obtain the logistics path and the scheduling plan, wherein the target path avoids high-radiation areas or other safety restricted areas.

[0026] Optionally, the method further includes:

[0027] Determine the urgency score based on the due date of the task;

[0028] Determine the importance score based on the cargo's importance to the operation of the nuclear power plant;

[0029] Determine a security level score based on the type of cargo and the security risks associated with the cargo;

[0030] The cargo priority score is calculated based on the urgency score, the first weight, the importance score, the second weight, the security level score and the third weight; wherein the first weight is the weight corresponding to the urgency score, the second weight is the weight corresponding to the importance score, and the third weight is the weight corresponding to the security level score.

[0031] Optionally, the logistics execution stage includes: a preparation stage, a transportation stage, and a handover stage; in the logistics execution stage, the use of an automated guidance system and unmanned transport vehicles to transport goods and the tracking of goods and vehicle status through a monitoring system include:

[0032] During the preparation phase, the logistics execution system obtains the scheduling plan and the logistics route, and performs a self-test on the unmanned transport vehicle, including: battery level testing, sensor function testing, and communication system testing; and detecting the environmental conditions on the logistics route.

[0033] During the transportation phase, the unmanned transport vehicle autonomously navigates along a predetermined route using GPS sensors, an inertial navigation system, and a visual recognition system; monitors vehicle status, location, and surroundings; and calculates and adjusts the logistics route.

[0034] During the handover phase, when the unmanned transport vehicle arrives at the designated location, the loading and unloading operations of the cargo are completed through the automated loading system; after the cargo is unloaded, the automated loading system sends a task completion signal; during the entire transportation process, all operation data and status information are synchronized to the central control system.

[0035] Optionally, after the logistics operation is completed, adjusting the logistics path and the scheduling plan according to the collected feedback data includes:

[0036] Calculate the actual transportation time based on the actual start and end time of each logistics operation;

[0037] After the goods arrive at the destination, they are scanned physically or automatically to record any abnormal events that occur during the logistics operation;

[0038] The logistics route and the scheduling plan are adjusted according to the actual transportation time, the planned transportation time and the abnormal event.

[0039] The present disclosure also provides an intelligent logistics management device for a nuclear power plant, including:

[0040] a collection module for collecting sensor data using a sensor network installed inside and around the nuclear power plant;

[0041] A processing module, configured to process the sensor data to obtain analysis results;

[0042] A generation module, configured to generate a logistics route and a scheduling plan based on the analysis results; wherein the scheduling plan is associated with cargo priority, safety requirements, and resource availability;

[0043] Tracking module, used to implement cargo transportation using automated guidance systems and unmanned transport vehicles during the logistics execution phase, and to track cargo and vehicle status through a monitoring system;

[0044] The adjustment module is used to adjust the logistics path and the scheduling plan according to the collected feedback data after the logistics operation is completed.

[0045] The present disclosure also provides an electronic device, including:

[0046] processor;

[0047] a memory for storing processor-executable instructions;

[0048] The processor is configured to execute instructions to implement each step in the above method.

[0049] The technical solutions provided by the embodiments of the present disclosure bring at least the following beneficial effects:

[0050] In some embodiments of the present disclosure, sensor data is collected using a sensor network installed inside and around a nuclear power plant; the sensor data is processed to obtain analysis results; based on the analysis results, a logistics path and a scheduling plan are generated; wherein the scheduling plan is associated with cargo priority, safety requirements, and resource availability; in the logistics execution stage, automated guidance systems and unmanned transport vehicles are used to implement cargo transportation, and the cargo status and vehicle status are tracked through a monitoring system to achieve efficient and safe transportation of cargo; after the logistics operation is completed, the logistics path and scheduling plan are adjusted based on the collected feedback data to improve the degree of automation of the logistics operation, thereby improving data processing efficiency, improving resource allocation efficiency, and improving safety.

[0051] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The accompanying drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the description are used to explain the principles of the present disclosure, and do not constitute an improper limitation of the present disclosure.

[0053] Figure 1A flowchart of an intelligent logistics management method for a nuclear power plant provided by an exemplary embodiment of the present disclosure;

[0054] Figure 2 A schematic structural diagram of an intelligent logistics management device for a nuclear power plant provided by an exemplary embodiment of the present disclosure;

[0055] Figure 3 A schematic structural diagram of an electronic device provided by an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0056] In order to enable ordinary people in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.

[0057] It should be noted that the terms "first," "second," and the like in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or precedence. It should be understood that the numbers used in this manner are interchangeable where appropriate so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure.

[0058] It should be noted that the user information involved in this disclosure includes but is not limited to: user device information and user personal information; the collection, storage, use, processing, transmission, provision and disclosure of user information in this disclosure comply with the relevant laws and regulations and do not violate public order and good morals.

[0059] In response to the above technical problems, in some embodiments of the present disclosure, sensor data is collected using a sensor network installed inside and around a nuclear power plant; the sensor data is processed to obtain analysis results; based on the analysis results, a logistics path and a scheduling plan are generated; wherein the scheduling plan is associated with cargo priority, safety requirements, and resource availability; in the logistics execution stage, automated guidance systems and unmanned transport vehicles are used to implement cargo transportation, and the cargo status and vehicle status are tracked through a monitoring system to achieve efficient and safe transportation of cargo; after the logistics operation is completed, the logistics path and scheduling plan are adjusted based on the collected feedback data to improve the degree of automation of the logistics operation, thereby improving data processing efficiency, improving resource allocation efficiency, and improving safety.

[0060] The technical solutions provided by various embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0061] Figure 1The following is a flow chart of a method for intelligent logistics management of a nuclear power plant provided by an exemplary embodiment of the present disclosure. Figure 1 As shown, the method includes:

[0062] S101: Collect sensor data using a sensor network installed inside and around the nuclear power plant;

[0063] S102: Process the sensor data to obtain analysis results;

[0064] S103: Generate a logistics route and scheduling plan based on the analysis results; wherein the scheduling plan is associated with cargo priority, safety requirements, and resource availability;

[0065] S104: In the logistics execution phase, automated guidance systems and unmanned transport vehicles are used to transport goods, and the status of goods and vehicles is tracked through monitoring systems;

[0066] S105: After the logistics operation is completed, the logistics route and scheduling plan are adjusted according to the collected feedback data.

[0067] In this embodiment, the execution subject of the above method is a terminal device or a server.

[0068] Among them, terminal devices include but are not limited to mobile stations (MS), mobile terminals, mobile phones, handsets, and portable equipment. The terminal devices can communicate with one or more core networks via a radio access network (RAN). For example, the terminal devices can be mobile phones (or "cellular" phones), computers with wireless communication capabilities, etc. The terminal devices can also be computers with wireless transceiver capabilities, virtual reality (VR) terminal devices, AR terminal devices, wireless terminals in industrial control, wireless terminals in self-driving, wireless terminals in remote medical care, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, wireless terminals in smart homes, etc., and the operating systems installed on the terminal devices include but are not limited to: iOS, Android, Windows, Linux, Mac OS, etc. In different networks, a terminal may be called by different names, such as user equipment, mobile station, subscriber unit, station, cellular phone, personal digital assistant, wireless modem, wireless communication device, handheld device, laptop computer, cordless phone, wireless local loop station, television, etc. For the convenience of description, the terminal is referred to as terminal equipment in this embodiment.

[0069] In this embodiment, the server implementation is not limited. For example, the server can be a conventional server, a cloud server, a cloud host, a virtual center, or other server devices. The server components primarily include a processor, a hard disk, memory, a system bus, and other common computer architecture types.

[0070] It should be noted that the sensor network includes: radio frequency identification tags and readers, GPS sensors and indoor positioning systems, temperature sensors, humidity sensors, radiation detectors, vibration analyzers, temperature sensors and pressure gauges. Among them, GPS sensors and indoor positioning systems are used to obtain high-precision location information outdoors and indoors; temperature sensors, humidity sensors, and radiation detectors are arranged to monitor environmental variables to ensure the safety of the operating environment; vibration analyzers, temperature sensors and pressure gauges are installed on key equipment to monitor the operating status of the equipment in real time. The present disclosure collects real-time data through a sensor network installed inside and around the nuclear power plant, including cargo location, personnel dynamics, machine status and environmental variables, providing a comprehensive data foundation for the data analysis module; after fusion and analysis, these data can accurately determine current logistics needs and potential bottlenecks, thereby providing data-driven decision support.

[0071] In some embodiments of the present disclosure, fixed-location sensors use wired connections to transmit sensor data, while mobile devices or remote monitoring points use wireless communication to transmit sensor data. Collecting real-time data also involves transmitting the data. For fixed-location sensors, wired connections are used to ensure data transmission stability and security, while for mobile devices or remote monitoring points, wireless communication is used to transmit data for flexible deployment and scalability.

[0072] In some embodiments of the present disclosure, sensor data is processed to obtain analysis results. One achievable method is to remove erroneous data and outliers from the sensor data to obtain preliminary sensor data; perform timestamp alignment on the preliminary sensor data to obtain aligned sensor data; calculate basic statistics of the aligned sensor data; and identify trends and periodic changes in the data based on the basic statistics to obtain analysis results. For example, the data analysis module performs preliminary screening on the collected data, removes erroneous data and outliers, ensures the accuracy of the data, and integrates data from different sensors to obtain more comprehensive monitoring results. At the same time, timestamp alignment is performed to ensure that the timestamps of all data are consistent, which facilitates time series analysis; the data is fused and analyzed using a preset algorithm to determine the current logistics demand and potential bottlenecks. First, a descriptive analysis of the data is required, which involves calculating the basic statistics of the data set, as expressed by:

[0073]

[0074] In the formula, σ represents the degree of deviation of the data value from the mean value, xi represents each data value in the data set, represents the average value of the data set, and n represents the number of data values ​​in the data set;

[0075] After calculating the basic statistics, identify the trends and cyclical changes in the data. The expression is:

[0076] SES t =αX t +(1-α)SES t-1 ;

[0077] Where α is the smoothing coefficient (0<α<1), Xt is the actual data value at the current time point, and SESt-1 is the smoothing value at the previous time point.

[0078] In some embodiments of the present disclosure, a logistics path and scheduling plan are generated based on the analysis results. One implementation method is to obtain analysis results, wherein the analysis results include: logistics demand forecasts, potential bottleneck identification, updated safety limits, radiation level data, and machine and human resource availability; sorting logistics tasks according to cargo priority, expiration time, and safety requirements; allocating corresponding machine and human resources to each logistics task based on resource availability; and calculating a target path from a starting point to a destination using a graph theory algorithm to obtain a logistics path and scheduling plan, wherein the target path avoids high radiation areas or other safety restricted areas. The output from the data analysis module is received, including logistics demand forecasts, potential bottleneck identification, real-time updates of safety limits, radiation level data, and machine and human resource availability; sorting logistics tasks according to cargo priority, expiration time, and associated safety requirements; allocating the most appropriate machine and human resources to each logistics task based on real-time resource availability; using a graph theory algorithm to calculate the optimal path from the starting point to the destination, while avoiding high radiation areas or other safety restricted areas. The logistics planning module outputs the optimized logistics path and scheduling plan for execution. During execution, the logistics operations are monitored in real time and, if any deviations are found, the plan is adjusted based on actual conditions. The disclosed logistics planning module automatically generates optimized logistics routes and scheduling plans based on data analysis results, taking into account factors such as cargo priority, safety requirements, and resource availability; it uses graph theory algorithms to calculate the optimal path from the starting point to the end point, while avoiding high-radiation areas or other safety-restricted areas, ensuring the safety and efficiency of logistics operations.

[0079] In some embodiments of the present disclosure, an urgency score is determined based on the due time of the task; an importance score is determined based on the importance of the cargo to the operation of the nuclear power plant; a safety level score is determined based on the type of cargo and the safety risks associated with the cargo; and a cargo priority score is calculated based on the urgency score, a first weight, an importance score, a second weight, a safety level score, and a third weight; wherein the first weight is a weight corresponding to the urgency score, the second weight is a weight corresponding to the importance score, and the third weight is a weight corresponding to the safety level score.

[0080] The calculation formula for cargo priority score is as follows:

[0081] Priority Score = w u ×Urgency+w i ×Importance+w s ×Safety Level

[0082] Among them, ω u is the first weight, ω i is the second weight, ω s It is the third weight, Urgency is the urgency score, Importance is the importance score, and Safety Level is the safety level score.

[0083] It should be noted that the logistics execution stage includes: preparation stage, transportation stage and handover stage.

[0084] In some embodiments of the present disclosure, during the logistics execution phase, automated guidance systems and unmanned transport vehicles are used to implement cargo transportation, and a monitoring system is used to track cargo and vehicle status. One possible implementation method is that during the preparation phase, the logistics execution system obtains the scheduling plan and logistics route and performs self-inspections on the unmanned transport vehicles, including: battery power testing, sensor function testing, and communication system testing; and detecting environmental conditions along the logistics route. During the transportation phase, the unmanned transport vehicles use GPS sensors, inertial navigation systems, and visual recognition systems to autonomously navigate along the predetermined route; monitor vehicle status, vehicle location, and the surrounding environment; and calculate and adjust the logistics route. During the handover phase, when the unmanned transport vehicle arrives at the designated location, the automated loading system completes the loading and unloading of the cargo. After the cargo is unloaded, the automated loading system sends a task completion signal. Throughout the transportation process, all operational data and status information are synchronized to the central control system. During the logistics execution phase, the present disclosure uses automated guidance systems and unmanned transport vehicles to implement cargo transportation, and a monitoring system is used to track cargo and vehicle status in real time. This reduces the need for personnel to directly contact high-risk environments and improves the safety and efficiency of logistics operations.

[0085] Among them, during the preparation stage, the logistics execution system receives the scheduling plan and route instructions from the logistics planning module; performs self-inspections on unmanned transport vehicles, including battery power, sensor functions, and communication systems, to ensure that the vehicles are in optimal condition; and uses radiation monitoring equipment and other environmental sensing equipment to detect environmental conditions on the transport route in real time to ensure safe passage.

[0086] During the transportation phase, unmanned transport vehicles use high-precision GPS, inertial navigation systems, and visual recognition systems to navigate along predetermined routes. The monitoring system uses on-board cameras and sensors to track the vehicle's status and position in real time, while monitoring the surrounding environment and obstacles to ensure safe driving. For emergencies or environmental changes detected on the route, the system can calculate and adjust the driving route in real time to avoid potential risks.

[0087] During the handover phase, after arriving at the designated location, the loading and unloading of goods is completed through an automated loading system, reducing direct contact of personnel with high-risk environments; after the goods are successfully delivered to the destination and unloaded, the system automatically sends a task completion signal; throughout the entire process, all operation data and status information are synchronized to the central control system in real time for easy recording and subsequent analysis.

[0088] In some embodiments of the present disclosure, after a logistics operation is completed, the logistics routing and scheduling plan are adjusted based on the collected feedback data. One possible implementation involves calculating the actual transportation time based on the actual start and end time of each logistics operation; performing physical or automated scanning of the goods upon arrival at the destination to record any abnormalities that occurred during the logistics operation; and adjusting the logistics routing and scheduling plan based on the actual transportation time, planned transportation time, and any abnormalities. Among them, the actual start and end time of each logistics operation is recorded, the total transportation time is calculated, and after the goods arrive at the destination, a physical or automated scan is performed to confirm the integrity of the goods, and all abnormal events that occur during the logistics operation are recorded; the planned and actual transportation times are compared to identify the causes of time delays, analyze the events of cargo damage or loss, determine their causes, and evaluate the effectiveness of existing safety measures; based on the results of the transportation time and abnormal event analysis, the logistics path planning is adjusted to reduce the risk and time consumption of future operations; based on the performance evaluation results, the allocation of human resources and equipment is adjusted to improve transportation efficiency; in response to cargo integrity issues and abnormal events, the operating protocols and safety measures are updated to enhance the safety of future operations; the adjusted logistics management strategy is deployed to the system and prepared for the next logistics operation. After the new strategy is implemented, the performance and safety status of the logistics operation are continuously monitored to ensure the effectiveness of the improvement measures. After the logistics operation is completed, the feedback data of the disclosed embodiment is collected, including transportation time, cargo integrity and abnormal events, and the logistics management strategy is dynamically adjusted by optimizing the feedback module; a closed-loop improvement process is formed, so that the system can continuously learn and adapt to the changing environment and needs.

[0089] The entire intelligent logistics management method disclosed in the present invention is permeated with the principle of safety first; from data collection, analysis, planning to execution, emphasis is placed on the consideration and response measures for safety factors; through precise data analysis and flexible logistics planning, the method can optimize resource allocation and improve resource utilization efficiency; it has a high degree of adaptability and can cope with various complex situations and emergencies in nuclear power plant logistics management; through real-time data collection and analysis, the system can quickly respond to environmental changes and emergencies, ensuring the continuity and stability of logistics operations; through real-time data collection and recording, the method improves the transparency and traceability of logistics operations; all operation data and status information are synchronized to the central control system in real time for easy recording and subsequent analysis, providing strong support for the stable operation of the nuclear power plant.

[0090] Figure 2 Schematic diagram of the structure of a nuclear power plant intelligent logistics management device 20 provided by an exemplary embodiment of the present disclosure. Figure 2 As shown, the intelligent logistics management device 20 of a nuclear power plant includes: a collection module 21 , a processing module 22 , a generation module 23 , a tracking module 24 and an adjustment module 25 .

[0091] The collection module 21 is used to collect sensor data using a sensor network installed inside and around the nuclear power plant;

[0092] The processing module 22 is used to process the sensor data and obtain analysis results;

[0093] A generation module 23 is used to generate a logistics route and a scheduling plan based on the analysis results; wherein the scheduling plan is associated with cargo priority, safety requirements, and resource availability;

[0094] Tracking module 24, used for implementing cargo transportation using automated guidance systems and unmanned transport vehicles during the logistics execution phase, and tracking cargo status and vehicle status through a monitoring system;

[0095] The adjustment module 25 is used to adjust the logistics path and scheduling plan according to the collected feedback data after the logistics operation is completed.

[0096] Regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0097] Figure 3 FIG. 1 is a structural diagram of an electronic device provided by an exemplary embodiment of the present disclosure. Figure 3 As shown, the electronic device includes: a memory 31 and a processor 32. In addition, the electronic device also includes a power supply component 33 and a communication component 34.

[0098] The memory 31 is used to store computer programs and can be configured to store various other data to support operations on the electronic device. Examples of such data include instructions for any application or method operating on the electronic device.

[0099] The memory 31 can be implemented by any type of volatile or non-volatile memory device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0100] The communication component 34 is used for data transmission with other devices.

[0101] The processor 32 can execute computer instructions stored in the memory 31 to: collect sensor data using a sensor network installed inside and around the nuclear power plant; process the sensor data to obtain analysis results; generate a logistics path and scheduling plan based on the analysis results; wherein the scheduling plan is associated with cargo priority, safety requirements and resource availability; during the logistics execution stage, use an automated guidance system and unmanned transport vehicles to implement cargo transportation and track the cargo status and vehicle status through a monitoring system; after the logistics operation is completed, adjust the logistics path and scheduling plan based on the collected feedback data.

[0102] Accordingly, the embodiment of the present disclosure further provides a computer-readable storage medium storing a computer program. When the computer-readable storage medium stores the computer program and the computer program is executed by one or more processors, the one or more processors are caused to execute Figure 1 Each step in the method embodiment.

[0103] Accordingly, the present disclosure also provides a computer program product, which includes a computer program / instruction, and the computer program / instruction is executed by a processor. Figure 1 Each step in the method embodiment.

[0104] above Figure 3The communication component is configured to facilitate wired or wireless communication between the device where the communication component is located and other devices. The device where the communication component is located can access a wireless network based on a communication standard, such as WiFi, 2G, 3G, 4G / LTE, 5G and other mobile communication networks, or a combination thereof. In an exemplary embodiment, the communication component receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0105] above Figure 3 The power supply component in a device provides power to various components of the device in which the power supply component is located. The power supply component may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the device in which the power supply component is located.

[0106] The electronic device also includes a display screen and an audio component.

[0107] The display screen includes a screen, which may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from a user. The touch panel includes one or more touch sensors to sense touches, slides, and gestures on the touch panel. The touch sensor can not only sense the boundaries of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation.

[0108] The audio component can be configured to output and / or input audio signals. For example, the audio component includes a microphone (MIC), and when the device where the audio component is located is in an operating mode, such as call mode, recording mode, and voice recognition mode, the microphone is configured to receive external audio signals. The received audio signal can be further stored in a memory or sent via a communication component. In some embodiments, the audio component also includes a speaker for outputting audio signals.

[0109] Those skilled in the art will appreciate that the embodiments of the present disclosure may be provided as methods, systems, or computer program products. Therefore, the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present disclosure may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0110] The present disclosure is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present disclosure. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0111] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0112] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0113] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0114] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0115] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory media such as modulated data signals and carrier waves.

[0116] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device that includes the element.

[0117] The above are merely specific embodiments of the present disclosure, intended to enable those skilled in the art to understand and implement the present disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure is not limited to these embodiments, but is to be construed in the broadest manner consistent with the principles and novel features disclosed herein.

Claims

1. A method for intelligent logistics management of a nuclear power plant, characterized in that: include: Collect sensor data using a network of sensors installed in and around the nuclear power plant; Processing the sensor data to obtain analysis results; Generating a logistics route and a scheduling plan based on the analysis results; wherein the scheduling plan is associated with cargo priority, safety requirements, and resource availability; In the logistics execution stage, automated guidance systems and unmanned transport vehicles are used to transport goods, and monitoring systems are used to track the status of goods and vehicles; After the logistics operation is completed, the logistics path and the scheduling plan are adjusted according to the collected feedback data.

2. The method according to claim 1, characterized in that The sensor network includes: radio frequency identification tags and readers, GPS sensors and indoor positioning systems, temperature sensors, humidity sensors, radiation detectors, vibration analyzers, temperature sensors and pressure gauges.

3. The method according to claim 1, characterized in that After collecting sensor data using the sensor network installed inside and around the nuclear power plant, the method further includes: For sensors at fixed locations, a wired connection is used to transmit the sensor data; For mobile devices or remote monitoring points, wireless communication is used to transmit the sensor data.

4. The method according to claim 1, wherein The processing of the sensor data to obtain analysis results includes: Eliminating erroneous data and abnormal values ​​in the sensor data to obtain preliminary sensor data; performing a timestamp alignment operation on the preliminary sensor data to obtain aligned sensor data; Calculating basic statistics of the aligned sensor data; According to the basic statistics, trends and periodic changes in the data are identified to obtain the analysis results.

5. The method according to claim 1, wherein Generating a logistics route and a scheduling plan based on the analysis results includes: Obtaining the analysis results, wherein the analysis results include: logistics demand forecasts, potential bottleneck identification, updated safety limits, radiation level data, and availability of machines and human resources; Sorting out logistics tasks according to the cargo priority, expiration date and the safety requirements; Based on the resource availability, assign corresponding machine and personnel resources to each of the logistics tasks; The target path from the starting point to the end point is calculated according to a graph theory algorithm to obtain the logistics path and the scheduling plan, wherein the target path avoids high-radiation areas or other safety restricted areas.

6. The method according to claim 5, characterized in that The method further comprises: Determine the urgency score based on the due date of the task; Determine the importance score based on the cargo's importance to the operation of the nuclear power plant; Determine a security level score based on the type of cargo and the security risks associated with the cargo; The cargo priority score is calculated based on the urgency score, the first weight, the importance score, the second weight, the security level score and the third weight; wherein the first weight is the weight corresponding to the urgency score, the second weight is the weight corresponding to the importance score, and the third weight is the weight corresponding to the security level score.

7. The method according to claim 1, characterized in that The logistics execution stage includes: preparation stage, transportation stage and handover stage; in the logistics execution stage, the use of automated guidance systems and unmanned transport vehicles to transport goods and the tracking of goods and vehicle status through monitoring systems include: During the preparation phase, the logistics execution system obtains the scheduling plan and the logistics route, and performs a self-test on the unmanned transport vehicle, including: battery power testing, sensor function testing, and communication system testing; and detecting the environmental conditions on the logistics route; During the transportation phase, the unmanned transport vehicle autonomously navigates along a predetermined route using GPS sensors, an inertial navigation system, and a visual recognition system; monitors vehicle status, location, and surroundings; and calculates and adjusts the logistics route. During the handover phase, when the unmanned transport vehicle arrives at the designated location, the loading and unloading operations of the cargo are completed through the automated loading system; after the cargo is unloaded, the automated loading system sends a task completion signal; during the entire transportation process, all operation data and status information are synchronized to the central control system.

8. The method according to claim 1, characterized in that After the logistics operation is completed, the logistics route and the scheduling plan are adjusted according to the collected feedback data, including: Calculate the actual transportation time based on the actual start and end time of each logistics operation; After the goods arrive at the destination, they are scanned physically or automatically to record any abnormal events that occur during the logistics operation; The logistics route and the scheduling plan are adjusted according to the actual transportation time, the planned transportation time and the abnormal event.

9. An intelligent logistics management device for a nuclear power plant, characterized in that: include: A collection module for collecting sensor data using a sensor network installed inside and around the nuclear power plant; A processing module, configured to process the sensor data to obtain analysis results; A generation module, configured to generate a logistics route and a scheduling plan based on the analysis results; wherein the scheduling plan is associated with cargo priority, safety requirements, and resource availability; Tracking module, used to implement cargo transportation using automated guidance systems and unmanned transport vehicles during the logistics execution phase, and to track cargo and vehicle status through a monitoring system; The adjustment module is used to adjust the logistics path and the scheduling plan according to the collected feedback data after the logistics operation is completed.

10. An electronic device, characterized in that: include: processor; a memory for storing processor-executable instructions; The processor is configured to execute instructions to implement each step in the method according to any one of claims 1 to 8.

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