Distributed production area material management method and system based on radio frequency identification

Abstract

The present application provides a decentralized production area material management method and system based on radio frequency identification, which relates to the field of material management technology, including: determining multiple material types according to material management needs; performing spectrum scanning and signal interference analysis on the target area; introducing a predetermined allocation analysis strategy to perform frequency band allocation; deploying M RFID readers based on M working frequency bands; performing label allocation for sub-areas according to the material allocation sequence and in combination with the label allocation hierarchical mechanism; and establishing a target material management plan based on the first material management plan. This application can solve the technical problem in the prior art that the accuracy of radio frequency identification is reduced due to interference between various devices in the decentralized production area, which further affects the efficiency of material management. By using spectrum scanning and dynamic frequency band allocation, signal interference is avoided, labels are allocated to materials, and the efficiency of material management is improved.

Description

Technical Field

[0001] The present application relates to the technical field of material management, and in particular to a distributed production area material management method and system based on radio frequency identification. Background Art

[0002] As the number of power plants increases, the amount of materials and equipment required increases, making the management of power equipment increasingly difficult and posing serious safety risks to power plant management. Distributed production areas within substations often involve the daily management and deployment of a large number of equipment, tools, parts, and other supplies, including equipment maintenance, spare material storage, tool management, and spare parts delivery. Radio frequency identification (RFID) embeds material information into RFID tags and uses RFID readers to automatically track, locate, and manage these materials, eliminating traditional manual inspections and data entry. While RFID technology can effectively improve material management efficiency, in complex environments like substations, RF signals are susceptible to interference, reducing the accuracy of RFID systems and impacting overall material management efficiency. Distributed production areas within substations typically contain a large number of devices and electronic instruments. These devices generate strong electromagnetic interference during operation, potentially affecting the communication signals between RFID readers and tags. This can lead to errors in material location tracking and delayed inventory data, impacting material management efficiency.

[0003] In summary, the existing technology has technical problems such as interference between devices due to the wide variety of devices and complex layout, which leads to reduced accuracy of radio frequency identification and further affects the efficiency of material management. Summary of the Invention

[0004] The purpose of this application is to provide a decentralized production area material management method and system based on radio frequency identification, so as to solve the technical problems in the prior art that due to the wide variety of equipment and complex layout, there is interference between the devices, which leads to reduced accuracy of radio frequency identification and further affects the efficiency of material management.

[0005] In view of the above problems, the present application provides a decentralized production area material management method and system based on radio frequency identification.

[0006] In the first aspect, the present application provides a decentralized production area material management method based on radio frequency identification, which is implemented by a decentralized production area material management system based on radio frequency identification, wherein the decentralized production area material management method based on radio frequency identification includes: obtaining multiple material types according to the material management needs of the target area; performing a spectrum scan on the target area, performing a signal interference analysis based on the spectrum scanning results, and determining P dense signal frequency bands and Q evacuation signal frequency bands, wherein P and Q are both positive integers, and P is greater than or equal to Q; introducing a predetermined allocation analysis strategy to perform frequency band allocation on the P dense signal frequency bands and the Q evacuation signal frequency bands, and establishing A sub-region frequency band mapping table is established, wherein the sub-region frequency band mapping table includes M sub-regions and M working frequency bands, M is a positive integer, and M=P+Q; based on the M working frequency bands, M RFID readers are deployed in the M sub-regions; a first sub-region is extracted from the M sub-regions, and a first RFID reader corresponding to the first sub-region is matched in the M RFID readers; priority scores are performed based on the multiple material types to obtain a material allocation sequence, and in combination with a label allocation hierarchical mechanism, a label is assigned to the first sub-region through the first RFID reader to obtain a first material management plan; based on the first material management plan, a target material management plan for the target area is established.

[0007] In the second aspect, the present application also provides a decentralized production area material management system based on radio frequency identification, which is used to execute the decentralized production area material management method based on radio frequency identification as described in the first aspect, wherein the decentralized production area material management system based on radio frequency identification includes: a material classification module, the material classification module is used to obtain multiple material types according to the material management needs of the target area; an interference analysis module, the interference analysis module is used to perform spectrum scanning on the target area, perform signal interference analysis based on the spectrum scanning results, and determine P dense signal frequency bands and Q evacuation signal frequency bands, wherein P and Q are both positive integers, and P is greater than or equal to Q; a frequency band allocation module, the frequency band allocation module is used to introduce a predetermined allocation analysis strategy to perform frequency band allocation on the P dense signal frequency bands and the Q evacuation signal frequency bands, and establish a sub-area frequency band mapping table, wherein the sub The regional frequency band mapping table includes M sub-regions and M working frequency bands, where M is a positive integer and M=P+Q; a reader / writer deployment module, wherein the reader / writer deployment module is used to deploy M RFID readers / writers to the M sub-regions based on the M working frequency bands; a first extraction module, wherein the first extraction module is used to extract a first sub-region from the M sub-regions and match a first RFID reader / writer corresponding to the first sub-region in the M RFID readers / writers; a hierarchical allocation module, wherein the hierarchical allocation module is used to perform priority scoring based on the multiple material types to obtain a material allocation sequence, and in combination with a label allocation hierarchical mechanism, perform label allocation for the first sub-region through the first RFID reader / writer to obtain a first material management plan; a material management module, wherein the material management module is used to establish a target material management plan for the target area based on the first material management plan.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0009] The method includes obtaining multiple material types based on material management requirements of a target area; performing a spectrum scan on the target area, performing signal interference analysis based on the spectrum scan results, and determining P dense signal frequency bands and Q evacuation signal frequency bands, where P and Q are both positive integers and P is greater than or equal to Q; introducing a predetermined allocation analysis strategy to allocate frequency bands to the P dense signal frequency bands and the Q evacuation signal frequency bands, and establishing a sub-area frequency band mapping table, where the sub-area frequency band mapping table includes M sub-areas and M working frequency bands, where M is a positive integer and M=P+Q; deploying M RFID readers in the M sub-areas based on the M working frequency bands; extracting a first sub-area from the M sub-areas, and matching a first RFID reader corresponding to the first sub-area among the M RFID readers; performing priority scoring based on the multiple material types to obtain a material allocation sequence, and combining a label allocation hierarchical mechanism to allocate a label to the first sub-area via the first RFID reader to obtain a first material management plan; and establishing a target material management plan for the target area based on the first material management plan. That is to say, through spectrum scanning, the wireless signal distribution in the target area is obtained, the dense signal frequency band and the evacuation signal frequency band are identified, and the spectrum resources are dynamically allocated through a predetermined allocation analysis strategy. The target area is divided according to the final optimal working frequency band, and the RFID reader corresponding to the working frequency band is deployed to distribute and read material tags, so as to achieve more efficient and accurate material management and improve the efficiency of material management in decentralized production areas.

[0010] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, which can be implemented in accordance with the contents of the description, and to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are specifically listed below. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in this application or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely exemplary, and a person of ordinary skill in the art can obtain other drawings based on the provided drawings without creative work.

[0012] Figure 1 This is a flow chart of the decentralized production area material management method based on radio frequency identification in this application;

[0013] Figure 2This is a structural diagram of the decentralized production area material management system based on radio frequency identification in this application.

[0014] Explanation of the accompanying symbols: material classification module 11, interference analysis module 12, frequency band allocation module 13, reader deployment module 14, first extraction module 15, hierarchical allocation module 16, material management module 17. DETAILED DESCRIPTION

[0015] This application provides a distributed production area material management method and system based on radio frequency identification, solving the technical problem in the prior art that due to the wide variety of equipment and complex layout, interference exists between the various devices, resulting in reduced radio frequency identification accuracy and further affecting the efficiency of material management. Through spectrum scanning, the wireless signal distribution in the target area is obtained, and the dense signal frequency band and the evacuated signal frequency band are identified. Through a predetermined allocation analysis strategy, the spectrum resources are dynamically allocated. The target area is divided according to the final optimal working frequency band, and RFID readers corresponding to the working frequency band are deployed to allocate and read material tags, achieving more efficient and accurate material management and improving the efficiency of distributed production area material management.

[0016] Below, the technical solutions in this application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of this application, rather than all the embodiments of this application. It should be understood that this application is not limited to the example embodiments described herein. Based on the embodiments of this application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application. It should also be noted that, for the convenience of description, only the parts related to this application, rather than all of them, are shown in the accompanying drawings.

[0017] For example, see the attached Figure 1 The present application provides a decentralized production area material management method based on radio frequency identification, wherein the decentralized production area material management method based on radio frequency identification is applied to a decentralized production area material management system based on radio frequency identification, and the decentralized production area material management method based on radio frequency identification specifically includes the following steps:

[0018] S100: Obtain multiple material types based on material management requirements of the target area.

[0019] Specifically, the material management needs of the target area are typically captured, typically for a specific area requiring material management, such as a distributed production area within a substation. Material management needs encompass the management requirements for materials within the target area, encompassing aspects such as inventory management, circulation, tracking, allocation, and usage. A detailed analysis of the material management needs within the target area is conducted to understand which materials require detailed management and which can be managed more simply. Different types of materials have different management requirements. Materials are classified based on factors such as function, purpose, and value, resulting in multiple material types. By deriving multiple material types based on the material management needs of the target area, different materials can be managed differently, improving the efficiency of material allocation and scheduling.

[0020] S200: Performing a spectrum scan on the target area, performing a signal interference analysis based on the spectrum scan result, and determining P dense signal frequency bands and Q evacuation signal frequency bands, where P and Q are both positive integers, and P is greater than or equal to Q.

[0021] Furthermore, the present application S200 includes:

[0022] A spectrum analyzer is used to comprehensively scan the target area according to a preset step width to obtain M signal frequency bands; a frequency band classifier is trained based on a historical spectrum data set and a corresponding historical spectrum annotation set; and the M signal frequency bands are divided by the frequency band classifier to obtain P dense signal frequency bands and Q sparse signal frequency bands.

[0023] Specifically, a spectrum analyzer is used to comprehensively scan the target area according to a preset step width, scanning one by one within a fixed frequency range, collecting the signal strength and distribution in different frequency bands, and obtaining M signal frequency bands. Signals in different frequency bands correspond to different transmission and reception performances, affecting the recognition efficiency and anti-interference ability of the RFID reader. A spectrum analyzer is an electronic test device used to measure and analyze the spectrum of a signal, especially the frequency, amplitude and other parameters of the signal. During the spectrum scanning process, the step width refers to the interval between each frequency scan. Usually, the step width is set to a certain frequency range (such as 10MHz or 100kHz) so that the spectrum analyzer can gradually cover all signal frequency bands during the scanning process. The preset step width is an approximate width pre-defined based on the actual situation of the target area to ensure that the entire target area can be covered.

[0024] Historical spectrum datasets and corresponding historical spectrum annotation sets are obtained from the control center of the decentralized production area. These datasets contain frequency utilization and interference intensity in different environments and at different times. This allows the identification of frequency bands with high interference and relatively low interference. If multiple strong signals overlap or the noise bandwidth increases significantly on the spectrum, this indicates interference. Based on the historical spectrum datasets and corresponding historical spectrum annotation sets, appropriate models are selected to build classifiers, including decision trees, random forests, support vector machines (SVMs), and convolutional neural networks (CNNs). Random forests, for example, are an ensemble learning method that uses multiple decision trees for classification. During training, each tree randomly selects certain features from the data and establishes classification rules based on these features. The final classification result is determined by the votes of all decision trees, significantly reducing the overfitting problem of individual trees.

[0025] Data preprocessing is performed on the historical spectrum dataset and historical spectrum annotation set. Feature extraction, such as signal frequency, signal strength, and interference intensity, is performed on these processed datasets and historical spectrum annotation sets. Each feature in the model helps the decision tree split nodes, ultimately arriving at the classification result. A random forest constructs multiple decision trees by randomly selecting features and sample subsets. The predictions of these decision trees are then voted on to arrive at the final classification result. The historical spectrum dataset and historical spectrum annotation set are divided into a training set (e.g., 80%) and a validation set (e.g., 20%). The model is trained using the training set, and its accuracy is tested using the validation set. Model performance is optimized through methods such as cross-validation and hyperparameter tuning. During training, the model selects the optimal splitting features (e.g., signal strength and interference intensity) based on different decision trees to classify different frequency bands, namely, dense and sparse bands.

[0026] The frequency band classifier uses a trained random forest model to classify newly input spectral data (e.g., M signal frequency bands) into dense or sparse signal bands. Convergence criteria are set for the model, such as a validation set loss of less than 0.01 for five consecutive rounds or a training set accuracy of 95%. Training of the frequency band classifier is iteratively performed until convergence criteria are met; otherwise, parameter adjustments or data processing optimization are continued.

[0027] M signal frequency bands are input into a trained frequency band classifier and automatically divided into P dense signal frequency bands and Q sparse signal frequency bands. Dense signal frequency bands are those with high signal strength and high interference intensity within the frequency range, which are prone to interference. Sparse signal frequency bands are those with low interference intensity and are usually idle or interference-free. These bands can be used for frequency band reallocation or as backup bands. The trained frequency band classifier can classify signal frequency bands, providing a basis for subsequent regional division, avoiding overcrowding or interference in dense signal frequency bands, and improving signal stability across the entire area.

[0028] S300: Introduce a predetermined allocation analysis strategy to perform frequency band allocation on the P dense signal frequency bands and the Q sparse signal frequency bands, and establish a sub-region frequency band mapping table, wherein the sub-region frequency band mapping table includes M sub-regions and M working frequency bands, M is a positive integer, and M=P+Q.

[0029] Specifically, the predetermined allocation analysis strategy refers to a method of analyzing frequency bands based on the interference and utilization of signal frequency bands. It considers the interference between different frequency bands and determines how to transfer part of the traffic in dense signal bands with higher interference intensity to idle or less loaded evacuation signal bands. Reasonable allocation rules are formulated based on the density and idleness of the frequency bands. For example, if the interference intensity of dense signal bands in a certain area is high, while the interference of evacuation signal bands is low, the predetermined allocation analysis strategy may prioritize allocating dense signal bands to low-interference areas, or transfer some traffic to evacuation bands.

[0030] All signal frequency bands in the P densely populated signal bands that exceed a preset signal interference threshold are considered Y densely interfering signal frequency bands. These frequency bands are considered to be excessively interfering and may cause signal quality degradation. In other words, a maximum signal interference strength value is pre-set, and the interference strengths of the P densely populated signal bands are compared with this value to obtain the Y densely interfering signal frequency bands.

[0031] For Y densely interfering signal bands, some traffic from the dense signal bands with higher interference intensity is transferred to the nearest idle or lightly loaded evacuation signal band, resulting in M ​​updated operating frequency bands with minimal interference between them. A corresponding regional spectrum graph is drawn based on the M operating frequency bands, displaying information such as the interference intensity and utilization rate of each signal band within the target area, providing a visual representation of signal distribution. Based on the regional spectrum graph, the target area is divided into M sub-areas. Based on the mapping relationship between the M sub-areas and the M operating frequency bands, a sub-area frequency band mapping table is constructed, recording each sub-area and its assigned operating frequency band. This ensures that the signal bands of each sub-area do not overlap with those of other areas, thereby reducing interference. By adopting a predetermined allocation analysis strategy, dense signal bands and evacuation signal bands are rationally allocated, minimizing signal interference. By rationally dividing the operating frequency bands, the frequency band utilization efficiency of each sub-area is optimized, avoiding overcrowding or waste of idle resources, thereby improving spectrum resource utilization.

[0032] S400: Based on the M operating frequency bands, deploy M RFID readers in the M sub-areas.

[0033] S500: Extract a first sub-region from the M sub-regions, and match a first RFID reader / writer corresponding to the first sub-region among the M RFID readers / writers.

[0034] Specifically, the target area is divided into M sub-areas based on M operating frequency bands. Each sub-area requires an RFID reader / writer to identify items. To avoid frequency interference between different sub-areas, the RFID reader / writer in each sub-area will operate on a unique frequency band assigned to that area. Each RFID reader / writer is configured to be compatible with the operating frequency band corresponding to its area. An RFID (Radio Frequency Identification) reader / writer is a device used to read or write RFID tags, identifying the tag information without contacting the item. RFID readers / writers communicate with RFID tags based on their assigned operating frequency bands. Within the target area, RFID readers / writers are deployed based on the location and spatial layout of the sub-areas. Each RFID reader / writer should be appropriately positioned to effectively cover the entire sub-area and avoid interference with RFID readers / writers in adjacent areas. After deploying the RFID readers / writers, their configuration should be adjusted based on actual conditions to optimize recognition range and efficiency. This one-to-one allocation method theoretically minimizes conflicts and improves read / write efficiency.

[0035] A random area is selected from the M subareas as the first subarea, and the first RFID reader corresponding to the first subarea is determined from the M RFID readers. Subareas and RFID readers have a one-to-one correspondence. By deploying RFID readers in each subarea and ensuring that they operate in different frequency bands, interference between frequency bands can be effectively avoided, ensuring that materials in each subarea can be accurately identified.

[0036] S600: Priority scoring is performed based on the multiple material types to obtain a material allocation sequence. In combination with a label allocation hierarchical mechanism, labels are allocated to the first sub-area through the first RFID reader to obtain a first material management solution.

[0037] Specifically, material types refer to the different types of items or equipment involved in material management, and each material type has different management requirements. Based on the characteristics, requirements, and importance of the materials, all material types are prioritized and scored to obtain a weight value corresponding to each material type, which helps determine which materials require priority management or allocation. The priority score can be calculated based on factors such as the frequency of use, value, urgency, and safety requirements of the materials. For example, priority score = a × frequency of use + b × material value + c × urgency. Sort multiple material types from high to low according to their priority scores to obtain a material allocation sequence. Each sub-area may require different types and quantities of materials depending on its function, area, and operational requirements. Based on the material priority in the material allocation sequence, the material type that best matches the material needs of each sub-area is selected and the materials are allocated one by one.

[0038] The hierarchical tag allocation mechanism assigns different tags to different materials based on their permissions, frequency of use, and changes in demand. By associating permission identifiers (such as administrator permissions, general permissions, and special permissions) with material tags and keys, this ensures that only personnel who meet the permission requirements can operate or access the corresponding materials. Based on the priority score and allocation sequence of the materials, combined with the hierarchical tag allocation mechanism, appropriate RFID tags are assigned to each material type. Based on the aforementioned priority score and hierarchical tag allocation mechanism, tags are assigned to materials in the first sub-area through the first RFID reader / writer, which is responsible for reading and writing tag information. Through tag allocation and priority sorting, a first material management plan is formed, detailing the tag allocation, storage method, flow path, and other contents of the materials in the first sub-area.

[0039] S700: Establishing a target material management plan for the target area based on the first material management plan.

[0040] Specifically, based on the first material management plan, the above steps are repeated for all other sub-regions within the M sub-regions, resulting in a material management plan corresponding to each sub-region, thereby completing the target material management plan for the target region. By rationally allocating management resources within the region based on material management needs and the division of the M sub-regions, and integrating RFID technology to label materials, ensuring a one-to-one correspondence between each material and key, and using RFID technology to track the flow of materials within the target region in real time, the accuracy of material management can be improved, the risk of loss and misuse can be reduced, and the efficiency of material management in decentralized production areas can be enhanced.

[0041] Furthermore, the present application S300 includes:

[0042] According to the predetermined allocation analysis strategy, the signal frequency bands exceeding the preset signal interference threshold are screened out from the P dense signal frequency bands, and dynamic frequency band reallocation is performed in combination with the Q evacuation signal frequency bands to obtain M working frequency bands; a regional frequency spectrum diagram is drawn based on the M working frequency bands; according to the regional frequency spectrum diagram, the target area is divided into the M sub-areas in combination with the material management requirements; based on the M sub-areas and the M working frequency bands, the sub-area frequency band mapping table is constructed.

[0043] Specifically, according to the predetermined allocation analysis strategy, the signal frequency bands that exceed the preset signal interference threshold are screened out from the P dense signal frequency bands, the adjacent evacuation signal frequency bands are detected, and the idle frequency band resources are released. That is to say, all the signal frequency bands of the P dense signal frequency bands that exceed the preset signal interference threshold are dynamically reallocated, and the adjacent evacuation signal frequency band closest to the current dense signal frequency band is selected from the Q evacuation signal frequency bands, and part of the traffic of the dense signal band with higher interference intensity is transferred to the idle or low-load evacuation signal frequency band. The frequency band boundaries are adjusted to ensure that there is no spectrum overlap between the frequency bands, thereby avoiding new interference. Until all the signal frequency bands that exceed the preset signal interference threshold in the P dense signal frequency bands are transferred, the current latest working frequency band is obtained, forming M reallocated working frequency bands.

[0044] Use a spectrum analyzer to record the M reallocated operating frequency bands, their interference intensity, and utilization rates. Visualize the data to generate a regional spectrum diagram, showing the signal characteristics of different frequency bands. The regional spectrum diagram is a visualization tool used to display information such as the interference intensity and utilization rate of each signal frequency band within the target area, providing an intuitive view of signal distribution. Based on the regional spectrum diagram, the target area is divided into M initial sub-areas. Based on the spatial layout diagram of the target area, determine the M material flow paths within the M initial sub-areas, and perform path frequency statistics to form a material path frequency matrix. Based on material management requirements, determine the material density of the M initial sub-areas to construct a material density distribution matrix.

[0045] While ensuring that the resulting frequency band division (M signal frequency bands) remains unchanged, a multi-objective optimization search is performed on the M initial sub-regions, using the material path frequency matrix and material density distribution matrix as constraints, with minimizing path cost, maximizing spatial optimization, and material density balance as the objective functions. The final M sub-region division results are obtained, ensuring that the frequency bands do not change due to regional division adjustments. Based on the one-to-one correspondence between the M sub-regions and the M operating frequency bands, a sub-region frequency band mapping table is constructed to clearly define the operating frequency band corresponding to each sub-region. Through screening and reallocation, signal interference is reduced, the stability of radio frequency identification is improved, and the combination of dense and sparse signal frequency bands optimizes the utilization of spectrum resources and improves the efficiency of material management.

[0046] Furthermore, the present application further comprises the following steps:

[0047] Step A: Adjust the preset step width based on the preset step length to obtain the target step width; Step B: Adjust the resolution of the spectrum analyzer according to the target step width, monitor the P dense signal frequency bands in real time, and obtain P signal interference intensities; Step C: Filter the Y dense interference signal frequency bands whose signal interference intensities exceed the preset signal interference threshold among the P dense interference signal frequency bands; Step D: Extract the first dense interference signal frequency band from the Y dense interference signal frequency bands; Step E: Perform dynamic frequency band reallocation based on the first dense interference signal frequency band and the first adjacent sparse signal frequency band to obtain the first working frequency band; traverse the Y dense interference signal frequency bands, repeat steps D to E, until the M working frequency bands are obtained.

[0048] Specifically, the preset step size is a parameter used to control scanning accuracy during spectrum analysis and adjust the step width of the spectrum scan. The preset step width is adjusted based on the preset step size to determine the target step width, allowing the spectrum analyzer to detect more accurate data. The spectrum analyzer's resolution is adjusted according to the target step width, and P densely packed signal frequency bands are monitored in real time, recording the signal interference intensity of each frequency band. Adjusting the resolution can change the accuracy of the spectrum analyzer. Higher accuracy results in finer resolution, and smaller resolution can help detect more subtle signal interference.

[0049] The adjusted spectrum analyzer is used to monitor the P densely populated signal bands in real time again, recording the interference intensity of each band for use in analyzing band utilization and identifying areas of interference and signal overload. An interference threshold is set; bands exceeding this threshold are considered densely interfering and excessively interfering, potentially causing signal quality degradation and impacting the normal operation of the material management system. The signal interference intensities of the P densely populated signal bands are obtained, and Y densely interfering signal bands exceeding the preset signal interference threshold are selected. These bands exhibit high signal interference intensities and may significantly impact normal communications or equipment operation.

[0050] A dense interference signal frequency band is randomly selected from the Y dense interference signal frequency bands as the first dense interference signal frequency band. Under the constraints of minimizing the overall interference intensity or balancing the load of each frequency band, the first adjacent evacuation signal frequency band is extracted from the Q evacuation signal frequency bands. In other words, the evacuation signal frequency band closest to the first dense interference signal frequency band among the Q evacuation signal frequency bands is selected as the first adjacent evacuation signal frequency band. Based on the load value of the first dense interference signal frequency band and the available capacity of the first adjacent evacuation signal frequency band, the migration traffic that needs to be migrated from the first dense interference signal frequency band to the first adjacent evacuation signal frequency band is calculated, and frequency band modulation is performed accordingly to obtain the updated first working frequency band. Part of the traffic of the first dense interference signal band is transferred to the evacuation frequency band to ensure that there is no spectrum overlap between the two.

[0051] The remaining densely interfering signal bands among the Y densely interfering signal bands are dynamically reallocated according to the process in steps D and E. Ultimately, through dynamic adjustment, M stable operating frequency bands are obtained. This dynamic reallocation of frequency bands effectively reduces the interference intensity of densely interfering signal bands and improves signal quality.

[0052] Furthermore, the present application further comprises the following steps:

[0053] Minimizing the overall interference intensity or balancing the load of each frequency band is used as a constraint condition; based on the constraint condition, the first adjacent evacuation signal frequency band is extracted from the Q evacuation signal frequency bands; the migration flow is calculated according to the load value of the first dense interference signal frequency band and the available capacity of the first adjacent evacuation signal frequency band; according to the migration flow, the first dense interference signal frequency band is modulated to the first adjacent evacuation signal frequency band to obtain the first updated dense signal frequency band and the first updated evacuation signal frequency band; according to the first updated dense signal frequency band and the first updated evacuation signal frequency band, the first working frequency band is formed.

[0054] Specifically, minimizing overall interference intensity means reducing interference intensity across the entire area by adjusting frequency band allocation. The lower the interference intensity, the higher the signal quality and the more efficient the communication. Balancing the load across frequency bands aims to ensure that the load on each band is as balanced as possible, that is, to avoid excessively high loads on one band and excessively low loads on others, which helps improve the efficient use of spectrum resources. Minimizing overall interference intensity or balancing the load across frequency bands is used as a constraint to ensure that the load on each band does not exceed its maximum capacity, the interference intensity does not exceed a threshold, and the total capacity of dynamically allocated frequency bands must meet the load requirements of densely populated frequency bands. For densely populated signal bands, the transferred traffic cannot exceed the load of the current band and cannot exceed the remaining capacity of the evacuation band. Based on the constraints, multiple evacuation signal bands that meet the constraints are selected from the Q evacuation signal bands as candidate bands, i.e., multiple candidate evacuation signal bands.

[0055] Use the Euclidean distance formula to calculate the distance between the first dense interference signal band and multiple candidate evacuation signal bands. Select the candidate adjacent evacuation signal band closest to the first dense interference signal band as the first adjacent evacuation signal band. Obtain the load value of the dense interference signal band and the available capacity of the first adjacent evacuation signal band. Calculate the traffic to be migrated based on the load value and available capacity. Calculate the traffic to be migrated based on the required band capacity and the available bandwidth of the evacuation band. The amount of traffic to be migrated determines how much traffic needs to be removed from the dense signal band and transferred to the evacuation band to reduce the burden on the dense signal band. For signal bands requiring frequency reallocation, first adjust their band boundaries to avoid spectrum overlap. Specifically, the adjustment method involves expanding the bandwidth outside the dense signal band to reduce its interference intensity and expanding the bandwidth toward the evacuation signal band to provide more available spectrum resources. When adjusting the boundaries, ensure that there is no overlap between the two frequency ranges. Spectrum analysis and simulation tools can be used to verify whether the adjusted frequency bands will overlap.

[0056] Based on the calculated migration traffic, some traffic is migrated from the dense interference signal band to the first adjacent evacuation signal band. After migration, the interference intensity of the dense band will decrease, while the interference intensity of the evacuation signal band may increase. Through simulation or real-time monitoring, the load and interference intensity of the frequency bands after migration are evaluated. The interference intensity and load of all frequency bands are confirmed to meet the preset thresholds. If any frequency bands still do not meet the requirements, the frequency band allocation is readjusted. If the system status remains unstable after migration, the migration strategy may need to be adjusted or more evacuation signal bands may need to be selected. After the migration, updated dense interference signal bands and updated evacuation signal bands are obtained. Based on the first updated dense interference signal band and the first updated evacuation signal band, a first operating frequency band is constructed. The first operating frequency band meets the conditions of low interference and balanced load. By dynamically selecting the evacuation signal band based on the interference intensity and load, the overall interference intensity of the spectrum is effectively controlled after traffic migration. The traffic migration process balances the load of the frequency bands, avoids overloading of certain frequency bands, and improves spectrum utilization efficiency.

[0057] Furthermore, the present application further comprises the following steps:

[0058] Based on the regional frequency spectrum diagram, the target area is divided into M initial sub-areas; based on the spatial layout diagram of the target area, M material flow paths of the M initial sub-areas are determined; frequency statistics are performed based on the M material flow paths to form a material path frequency matrix; based on the material management requirements, the M material densities of the M initial sub-areas are determined; based on the M material densities, a material density distribution matrix is ​​constructed; with the material path frequency matrix and the material density distribution matrix as constraints, and with minimizing path cost, maximizing spatial optimization and material density balance as objective functions, multi-objective optimization is performed on the M initial sub-areas to obtain the M sub-areas.

[0059] Specifically, the regional spectrum map visualizes spectrum usage in the target area, displaying the interference intensity and load of each frequency band at different spatial locations. Based on the regional spectrum map, the target area is divided into M initial sub-areas based on the interference intensity and load of the spectrum within the area. After determining the initial sub-areas, the material flow paths within each sub-area are determined based on the spatial layout of the target area. The material flow path refers to the path of materials from one sub-area to another, which affects the allocation of frequency band resources. Based on the statistical data of the material flow paths, a material path frequency matrix is ​​established to reflect the flow frequency of each path.

[0060] The material path frequency matrix represents the frequency of material flows within the target area. It describes how often materials flow from one area to another and is used to assess the density of material flows, thereby optimizing the paths. The material flow path for each sub-area can be represented as the frequency of material flows from one area to another. A material path frequency matrix is ​​constructed, where each element represents the frequency of material flows from one area to another.

[0061] The material density of each sub-region is the amount of material stored per unit area within that region. This can be calculated based on material management needs, namely the ratio of total material quantity to regional area. The material density distribution matrix represents the distribution of material density across sub-regions within the target area, describing the concentration of materials within each sub-region. Each matrix element represents the material density of a sub-region. The balance of material density directly affects the rationality of material distribution across regions.

[0062] Path costs are crucial in substation material management, especially during material collection, return, and equipment maintenance. Frequent material handling and key usage can increase operational costs and time, so optimizing logistics paths is essential. This includes considerations such as material handling time from storage to the point of use; key collection and return routes, lock access time, and cross-flow and path planning between areas.

[0063] Uneven material density in a substation may lead to excessive storage of materials in certain areas, affecting efficiency and increasing management difficulty. Therefore, it is necessary to consider the space utilization rate of each material storage point; the storage of high-value, high-frequency materials; the matching of keys and materials, and the key management of high-value materials should be more stringent. The goal of space optimization is to make rational use of space and avoid excessive accumulation or waste in any area. When performing multi-objective optimization, it may be necessary to set appropriate weights for each objective function to balance conflicts between different objectives. If there is a contradiction between space optimization and path cost (such as a contradiction between the shortest path and optimal space utilization), set weights to guide the optimization direction.

[0064] Multi-objective optimization involves finding the optimal solution through an optimization algorithm while satisfying multiple constraints. These optimization algorithms aim to minimize path cost, maximize spatial optimization, and balance material density. Path cost refers to the resources, time, or expense required to circulate a material flow path. Spatial optimization involves rationally arranging material and frequency resources in various areas within a limited space to maximize spatial utilization while minimizing interference. Material density balance ensures that material density is distributed as evenly as possible to avoid overcrowding in certain areas, which could lead to management difficulties or frequency overload. Based on the requirements of multi-objective optimization, an appropriate optimization algorithm, such as particle swarm optimization or genetic algorithm, is selected. Starting from a given initial region partition (i.e., M initial subregions), an initial solution is generated and the initial path cost, spatial optimization, and material density balance are calculated. For each solution, path cost, spatial optimization, and material density balance are calculated, and the performance of each solution is evaluated based on the objective function. The particle swarm optimization algorithm is used to continuously update the set of solutions. In each generation, the solution is updated based on the objective function and constraints until a stopping criterion (such as the number of iterations or accuracy requirements) is met. The solution obtained by the optimization algorithm can combine the optimization results of different objective functions through weights to obtain a comprehensive optimal solution.

[0065] Through multi-objective optimization, we find the optimal sub-area division to achieve balanced material density, minimize the cost of each material flow path, and maximize the efficiency of frequency resources. By rationally dividing sub-areas and optimizing material flow paths, frequency resource allocation becomes more efficient, avoiding waste of frequency resources and excessive interference.

[0066] Furthermore, the present application S600 includes:

[0067] Determine the corresponding multiple tag models based on the multiple material types; initialize the first RFID reader / writer using the multiple tag models in combination with the first working frequency band of the M working frequency bands; according to the first material allocation sequence, perform tag allocation for the first sub-area using the initialized first RFID reader / writer to obtain multiple first material RFID tags and corresponding multiple first RFID keys; determine allocation authority based on the tag allocation hierarchical mechanism, and add the multiple first material RFID tags and the multiple first RFID keys to the first material management plan according to the allocation authority.

[0068] Specifically, different materials may use different types of RFID tags (such as LF, HF, UHF, etc.). Based on the type of materials in the target area, the appropriate RFID tag model is automatically selected, and the reader's operating mode is adjusted according to the frequency band and frequency range. Different types of materials require different types of tags, and the choice of tag model affects the material's identification efficiency, reading range, and storage capacity. Based on the first working frequency band of M working frequency bands and in combination with multiple tag models, the first RFID reader is initialized and the working frequency band of the RFID reader is configured, including setting the working frequency band, reading parameters, tag type, etc., so that it can read or write RFID tags in the specified frequency band.

[0069] RFID readers should have an automatic power regulation mechanism that dynamically adjusts power output based on the material tag model and specifications. The RFID reader's power output should be automatically adjusted based on the material storage density, the required read distance of the material tags, and the specific storage environment. RFID tags are assigned to the materials in the first sub-area in descending order of priority based on the material allocation sequence. Multiple first material RFID tags and corresponding first RFID keys are generated. Each tag contains unique identification information for the material, including the material number, type, specifications, receipt record, and usage history. RFID technology is used to update the tag status in real time during the material collection, use, and return process.

[0070] A hierarchical tag allocation mechanism is introduced to determine the allocation permissions for different materials. By associating permission identifiers (such as administrator permissions, general permissions, and special permissions) with material tags and keys, it ensures that only personnel who meet the permission requirements can operate or access the corresponding materials. Based on the hierarchical tag allocation mechanism, the allocation permissions for each material tag are determined. All assigned tags will be integrated into the material management plan according to permissions to ensure efficient management of materials. The RFID tag of each material not only helps to track the location and status of the material in real time, but also provides managers with detailed material flow data to reduce material loss and misuse. Through automated tag allocation and permission management, the material management process is more efficient, reducing human resource investment and improving the efficiency of material management in the overall production area.

[0071] Furthermore, the present application further comprises the following steps:

[0072] The allocated permissions include administrator permissions, general permissions, and special permissions; the multiple material types are grouped in multiple dimensions to obtain a first material group, a second material group, and a third material group; based on the administrator permissions, the general permissions, and the special permissions, permissions are allocated to the first material group, the second material group, and the third material group through the first RFID reader to obtain multiple initial permission tags; based on the usage frequency and demand changes of the multiple material types, the multiple initial permission tags are updated to obtain multiple updated permission tags.

[0073] Specifically, assigning permissions means granting different management permissions to different people or materials, usually divided according to management levels and importance. Different permission levels determine the access scope of certain operations and resources. Administrators have full control over all materials; ordinary permissions can only access and operate certain low-value materials, can only collect materials during specific working hours, and can only collect materials within the scope of their job responsibilities; special permissions require additional authentication for high-value materials. The specific permission allocation can be adjusted according to actual conditions, and the access authentication corresponding to different permissions is also different. For example, administrator permissions and special permissions usually require double verification to prevent unauthorized personnel from accessing sensitive areas.

[0074] Material grouping is the process of categorizing and organizing materials based on characteristics such as type, purpose, importance, and frequency of use, allowing for more refined management and control. Multiple material types are grouped in multiple dimensions, including usage requirements, material requirements, and material importance, resulting in the first, second, and third material groups, allowing for differentiated authority allocation and management based on the characteristics of the materials. Material grouping can be based on multiple dimensions, such as material importance, frequency of use, usage environment, and management level. The first material group refers to the high-level material group, which requires strict authority control and is limited to administrators or personnel with special authority to collect or operate; the second material group refers to the intermediate material group, which can be collected by ordinary employees but may be subject to time, quantity, and other restrictions; the third material group is the low-level material group, which has looser authority but still requires recording and monitoring.

[0075] Assign appropriate permissions to materials based on different material groups and permission types, ensuring access across material groups for personnel of different roles. Develop allocation strategies using administrator, general, and special permissions to ensure secure material management. Administrator permissions allow access and management of tag information for all materials, including all material groups; general permissions limit access and management to low-priority or regular material groups; and special permissions are used for handling high-risk or high-value materials (such as electronic component groups and high-end equipment groups).

[0076] When materials are collected or returned, an RFID reader reads the material tag and extracts the relevant permission information from the tag, verifying in real time whether the operator meets the required permissions. For high-value materials or keys, secondary verification is often required, using biometric or identity verification methods such as fingerprint recognition, identity verification cards, and facial recognition. All operations, including material collection and return, are logged and categorized by permission. Multi-level permission management ensures that different personnel can only access and operate materials and equipment within their scope of permission through a reasonable permission hierarchy, dynamic permission allocation, and strict verification mechanisms.

[0077] Assign an initial permission tag to each material to ensure that different material groups can be managed according to the predetermined permission assignment rules. The initial permission tag is generated by the RFID reader and bound to the material. Each tag contains the access permission information of the material to control the access scope of different personnel. According to the classification and permission of the material, appropriate RFID tags and keys are assigned to different material groups. For high-level materials, use high-security RFID tags, such as encryption technology or authentication mechanisms to prevent unauthorized reading. Use RFID tags to identify materials and ensure that the label of each material is consistent with the material type and permission level. RFID tags for different materials can store different information (such as material name, specifications, storage location, recipient, etc.).

[0078] Update permission tags based on the frequency of use and changes in demand for materials to ensure that material management adapts to dynamically changing needs. Changes in frequency of use and demand can lead to changes in material classification or management strategies. Therefore, permission tags need to be updated regularly or as needed to allow materials to flexibly adapt to new management strategies. Frequently used materials may require expanded permissions, while infrequently used materials should have their permissions narrowed. As the importance and value of materials change, permissions may need to be adjusted based on new assessments. Changes in the status of materials (such as loaned, returned, and maintained) can affect permission settings in real time. For example, materials under repair can have access rights reduced, allowing only those with specific permissions to perform maintenance. Through the aforementioned grouping, permission allocation, and tag update mechanisms, a complete material management solution is formed that not only ensures the security and mobility of materials, but also ensures the efficiency and flexibility of material management.

[0079] Furthermore, the present application further comprises the following steps:

[0080] The target material is monitored in real time through an RFID reader to obtain the real-time status of the material; the expected material status of the target material is obtained according to the target material management plan; if the real-time status of the material does not meet the expected material status, an alarm mechanism is triggered; based on the alarm mechanism, an alarm notification is generated and the real-time status of the material is updated.

[0081] Specifically, through the automatic identification and tracking function of the RFID reader, the target materials are monitored in real time, and information such as the location, quantity, and usage status of the materials is obtained to reflect the status of the materials, including whether they have been collected, whether they have been returned on time, whether they have been returned correctly, and whether the cabinet door has been opened illegally. According to the target material management plan, the expected status of each material is determined, such as the return time of the material and the authority of the material. The expected status of the target material is set according to the management strategy and the purpose of the material. The expected status is the ideal state that each material should achieve. Once an abnormal material status is detected (such as non-return, overdue collection, etc.), an alarm will be triggered, including sound and light alarms, system pop-up notifications, SMS or email notifications to relevant personnel. In the material management process, the expected status of each material is set according to factors such as the purpose and demand of the material. These expected statuses can be used as the target status of the material for comparison with the actual status.

[0082] The actual status of the materials is compared with the expected status. If it is found that the status does not meet the expectations, the alarm mechanism is triggered. When the alarm is triggered, an alarm notification is generated and the status of the materials is updated in real time so that subsequent measures can be taken. A detailed alarm notification is generated, including the reason for the alarm (such as overdue return, misplacement, etc.), relevant material information, comparison between the current status and the expected status, and handling suggestions. For example, materials should be in the warehouse status, but when they are returned overdue or returned to the wrong location, an alarm is automatically triggered. Managers can investigate and handle according to the alarm notification. By comparing the real-time status of materials with the expected status, abnormal situations can be quickly identified, and alarm notifications can be triggered in advance to help respond as early as possible, avoid delays, and improve the efficiency and intelligence level of material management in distributed production areas.

[0083] In summary, the distributed production area material management method based on radio frequency identification provided by this application has the following technical effects:

[0084] The method includes obtaining multiple material types based on material management requirements of a target area; performing a spectrum scan on the target area, performing signal interference analysis based on the spectrum scan results, and determining P dense signal frequency bands and Q evacuation signal frequency bands, where P and Q are both positive integers and P is greater than or equal to Q; introducing a predetermined allocation analysis strategy to allocate frequency bands to the P dense signal frequency bands and the Q evacuation signal frequency bands, and establishing a sub-area frequency band mapping table, where the sub-area frequency band mapping table includes M sub-areas and M working frequency bands, where M is a positive integer and M=P+Q; deploying M RFID readers in the M sub-areas based on the M working frequency bands; extracting a first sub-area from the M sub-areas, and matching a first RFID reader corresponding to the first sub-area among the M RFID readers; performing priority scoring based on the multiple material types to obtain a material allocation sequence, and combining a label allocation hierarchical mechanism to allocate a label to the first sub-area via the first RFID reader to obtain a first material management plan; and establishing a target material management plan for the target area based on the first material management plan. That is to say, through spectrum scanning, the wireless signal distribution in the target area is obtained, the dense signal frequency band and the evacuation signal frequency band are identified, and the spectrum resources are dynamically allocated through a predetermined allocation analysis strategy. The target area is divided according to the final optimal working frequency band, and the RFID reader corresponding to the working frequency band is deployed to distribute and read material tags, so as to achieve more efficient and accurate material management and improve the efficiency of material management in decentralized production areas.

[0085] Example 2: Based on the same inventive concept as the decentralized production area material management method based on radio frequency identification in the aforementioned example 1, this application also provides a decentralized production area material management system based on radio frequency identification. Figure 2 , the decentralized production area material management system based on radio frequency identification includes:

[0086] A material classification module 11 is used to obtain multiple material types according to the material management needs of the target area; an interference analysis module 12 is used to perform spectrum scanning on the target area, perform signal interference analysis based on the spectrum scanning results, and determine P dense signal frequency bands and Q evacuation signal frequency bands, wherein P and Q are both positive integers, and P is greater than or equal to Q; a frequency band allocation module 13 is used to introduce a predetermined allocation analysis strategy to allocate frequency bands to the P dense signal frequency bands and the Q evacuation signal frequency bands, and establish a sub-area frequency band mapping table, wherein the sub-area frequency band mapping table includes M sub-areas and M working frequency bands, M is a positive integer, and M=P+Q; a reader deployment module 14 is used to read and write The device deployment module 14 is used to deploy M RFID readers in the M sub-areas based on the M working frequency bands; the first extraction module 15, the first extraction module 15 is used to extract the first sub-area from the M sub-areas, and match the first RFID reader corresponding to the first sub-area in the M RFID readers; the hierarchical allocation module 16, the hierarchical allocation module 16 is used to perform priority scoring based on the multiple material types to obtain a material allocation sequence, and in combination with the label allocation hierarchical mechanism, perform label allocation for the first sub-area through the first RFID reader to obtain a first material management plan; the material management module 17, the material management module 17 is used to establish a target material management plan for the target area based on the first material management plan.

[0087] Furthermore, the interference analysis module 12 in the decentralized production area material management system based on radio frequency identification is further used to:

[0088] A spectrum analyzer is used to comprehensively scan the target area according to a preset step width to obtain M signal frequency bands; a frequency band classifier is trained based on a historical spectrum data set and a corresponding historical spectrum annotation set; and the M signal frequency bands are divided by the frequency band classifier to obtain P dense signal frequency bands and Q sparse signal frequency bands.

[0089] Furthermore, the frequency band allocation module 13 in the decentralized production area material management system based on radio frequency identification is further used to:

[0090] According to the predetermined allocation analysis strategy, the signal frequency bands exceeding the preset signal interference threshold are screened out from the P dense signal frequency bands, and dynamic frequency band reallocation is performed in combination with the Q evacuation signal frequency bands to obtain M working frequency bands; a regional frequency spectrum diagram is drawn based on the M working frequency bands; according to the regional frequency spectrum diagram, the target area is divided into the M sub-areas in combination with the material management requirements; based on the M sub-areas and the M working frequency bands, the sub-area frequency band mapping table is constructed.

[0091] Furthermore, the frequency band allocation module 13 in the decentralized production area material management system based on radio frequency identification is further used to:

[0092] Step A: Adjust the preset step width based on the preset step length to obtain the target step width; Step B: Adjust the resolution of the spectrum analyzer according to the target step width, monitor the P dense signal frequency bands in real time, and obtain P signal interference intensities; Step C: Filter the Y dense interference signal frequency bands whose signal interference intensities exceed the preset signal interference threshold among the P dense interference signal frequency bands; Step D: Extract the first dense interference signal frequency band from the Y dense interference signal frequency bands; Step E: Perform dynamic frequency band reallocation based on the first dense interference signal frequency band and the first adjacent sparse signal frequency band to obtain the first working frequency band; traverse the Y dense interference signal frequency bands, repeat steps D to E, until the M working frequency bands are obtained.

[0093] Furthermore, the frequency band allocation module 13 in the decentralized production area material management system based on radio frequency identification is further used to:

[0094] Minimizing the overall interference intensity or balancing the load of each frequency band is used as a constraint condition; based on the constraint condition, the first adjacent evacuation signal frequency band is extracted from the Q evacuation signal frequency bands; the migration flow is calculated according to the load value of the first dense interference signal frequency band and the available capacity of the first adjacent evacuation signal frequency band; according to the migration flow, the first dense interference signal frequency band is modulated to the first adjacent evacuation signal frequency band to obtain the first updated dense signal frequency band and the first updated evacuation signal frequency band; according to the first updated dense signal frequency band and the first updated evacuation signal frequency band, the first working frequency band is formed.

[0095] Furthermore, the frequency band allocation module 13 in the decentralized production area material management system based on radio frequency identification is further used to:

[0096] Based on the regional frequency spectrum diagram, the target area is divided into M initial sub-areas; based on the spatial layout diagram of the target area, M material flow paths of the M initial sub-areas are determined; frequency statistics are performed based on the M material flow paths to form a material path frequency matrix; based on the material management requirements, the M material densities of the M initial sub-areas are determined; based on the M material densities, a material density distribution matrix is ​​constructed; with the material path frequency matrix and the material density distribution matrix as constraints, and with minimizing path cost, maximizing spatial optimization and material density balance as objective functions, multi-objective optimization is performed on the M initial sub-areas to obtain the M sub-areas.

[0097] Furthermore, the hierarchical allocation module 16 in the decentralized production area material management system based on radio frequency identification is further used to:

[0098] Determine the corresponding multiple tag models based on the multiple material types; initialize the first RFID reader / writer using the multiple tag models in combination with the first working frequency band of the M working frequency bands; according to the first material allocation sequence, perform tag allocation for the first sub-area using the initialized first RFID reader / writer to obtain multiple first material RFID tags and corresponding multiple first RFID keys; determine allocation authority based on the tag allocation hierarchical mechanism, and add the multiple first material RFID tags and the multiple first RFID keys to the first material management plan according to the allocation authority.

[0099] Furthermore, the hierarchical allocation module 16 in the decentralized production area material management system based on radio frequency identification is further used to:

[0100] The allocated permissions include administrator permissions, general permissions, and special permissions; the multiple material types are grouped in multiple dimensions to obtain a first material group, a second material group, and a third material group; based on the administrator permissions, the general permissions, and the special permissions, permissions are allocated to the first material group, the second material group, and the third material group through the first RFID reader to obtain multiple initial permission tags; based on the usage frequency and demand changes of the multiple material types, the multiple initial permission tags are updated to obtain multiple updated permission tags.

[0101] Furthermore, the RFID-based decentralized production area material management system further includes a material early warning module, which is further configured to:

[0102] The target material is monitored in real time through an RFID reader to obtain the real-time status of the material; the expected material status of the target material is obtained according to the target material management plan; if the real-time status of the material does not meet the expected material status, an alarm mechanism is triggered; based on the alarm mechanism, an alarm notification is generated and the real-time status of the material is updated.

[0103] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. Figure 1The RFID-based decentralized production area material management method and specific examples in Example 1 are also applicable to the RFID-based decentralized production area material management system in this embodiment. Through the detailed description of the RFID-based decentralized production area material management method, those skilled in the art can clearly understand the RFID-based decentralized production area material management system in this embodiment. Therefore, for the sake of brevity, it will not be described in detail here. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple. For relevant parts, please refer to the method description.

[0104] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one 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 application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

[0105] Obviously, those skilled in the art may make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application is intended to include these modifications and variations.

Claims

1. A decentralized production area material management method based on radio frequency identification, characterized in that: include: Based on the material management needs of the target area, multiple material types are obtained; Performing a spectrum scan on the target area, performing a signal interference analysis based on the spectrum scan results, and determining P dense signal frequency bands and Q evacuation signal frequency bands, where P and Q are both positive integers and P is greater than or equal to Q; Introducing a predetermined allocation analysis strategy to perform frequency band reallocation on the P dense signal frequency bands and the Q evacuation signal frequency bands, and establishing a sub-region frequency band mapping table, wherein the sub-region frequency band mapping table includes M sub-regions and M working frequency bands, where M is a positive integer and M=P+Q; Based on the M working frequency bands, deploy M RFID readers in the M sub-areas; Step 1: extracting a first sub-region from the M sub-regions, and matching a first RFID reader / writer corresponding to the first sub-region among the M RFID readers / writers; Step 2: Prioritize the multiple material types to obtain a material allocation sequence, and use the first RFID reader to assign tags to the first sub-area in combination with a label allocation hierarchical mechanism to obtain a first material management plan; Repeat steps 1 to 2 for each of the M sub-regions to obtain a material management plan corresponding to each sub-region, and establish a target material management plan for the target region.

2. The distributed production area material management method based on radio frequency identification according to claim 1 is characterized in that: Performing a spectrum scan on the target area, performing a signal interference analysis based on the spectrum scan results, and determining P dense signal frequency bands and Q evacuation signal frequency bands, including: The target area is fully scanned by a spectrum analyzer according to a preset step width to obtain M signal frequency bands; Train a frequency band classifier based on the historical spectrum dataset and the corresponding historical spectrum annotation set; The M signal frequency bands are divided by the frequency band classifier to obtain P dense signal frequency bands and Q sparse signal frequency bands.

3. The distributed production area material management method based on radio frequency identification according to claim 2 is characterized in that: Introducing a predetermined allocation analysis strategy to perform frequency band reallocation on the P dense signal frequency bands and the Q evacuation signal frequency bands, and establishing a sub-region frequency band mapping table, including: According to the predetermined allocation analysis strategy, filter the signal frequency bands exceeding the preset signal interference threshold among the P dense signal frequency bands, and perform dynamic frequency band reallocation in combination with the Q sparse signal frequency bands to obtain M working frequency bands; Drawing a regional spectrum diagram based on the M working frequency bands; Dividing the target area into the M sub-areas according to the regional spectrum diagram and in combination with the material management requirements; Based on the M sub-areas and the M working frequency bands, the sub-area frequency band mapping table is constructed.

4. The distributed production area material management method based on radio frequency identification according to claim 3 is characterized in that: According to the predetermined allocation analysis strategy, signal frequency bands exceeding a preset signal interference threshold are screened out from the P dense signal frequency bands, and dynamic frequency band reallocation is performed in combination with the Q sparse signal frequency bands to obtain M working frequency bands, including: Step A: adjusting the preset step width based on the preset step length to obtain a target step width; Step B: adjusting the resolution of the spectrum analyzer according to the target step width, monitoring the P dense signal frequency bands in real time, and obtaining P signal interference intensities; Step C: screening Y dense interference signal frequency bands whose signal interference intensities exceed the preset signal interference threshold among the P signal interference intensities; Step D: extracting a first dense interference signal frequency band from the Y dense interference signal frequency bands; Step E: Dynamically reallocating frequency bands based on the first dense interference signal frequency band and the first adjacent evacuation signal frequency band to obtain a first operating frequency band, wherein the first adjacent evacuation signal frequency band is the evacuation signal frequency band that is closest to the first dense interference signal frequency band among the Q evacuation signal frequency bands; Traverse the Y dense interference signal frequency bands and repeat steps D to E until the M working frequency bands are obtained.

5. The distributed production area material management method based on radio frequency identification according to claim 4 is characterized in that: Dynamically reallocating frequency bands based on the first dense interference signal frequency band and the first adjacent sparse signal frequency band to obtain a first operating frequency band includes: Minimizing the overall interference intensity or balancing the load of each frequency band is used as a constraint; Based on the constraint condition, extracting a first adjacent evacuation signal frequency band from the Q evacuation signal frequency bands; Calculating migration traffic according to the load value of the first dense interference signal frequency band and the available capacity of the first adjacent evacuation signal frequency band; According to the migration traffic, modulate the first dense interference signal frequency band to the first adjacent evacuation signal frequency band to obtain a first updated dense signal frequency band and a first updated evacuation signal frequency band; The first working frequency band is established according to the first update intensive signal frequency band and the first update evacuation signal frequency band.

6. The decentralized production area material management method based on radio frequency identification according to claim 3 is characterized in that: According to the regional spectrum diagram and in combination with the material management requirements, the target area is divided into the M sub-areas, including: Based on the regional spectrum map, the target area is divided into M initial sub-areas; Determining M material flow paths of the M initial sub-areas according to the spatial layout diagram of the target area; Perform frequency statistics based on the M material flow paths to form a material path frequency matrix; Determining the M material densities of the M initial sub-areas according to the material management requirements; Based on the M material densities, construct a material density distribution matrix; With the material path frequency matrix and the material density distribution matrix as constraints, and minimizing path cost, maximizing spatial optimization and material density balance as objective functions, a multi-objective optimization is performed on the M initial sub-regions to obtain the M sub-regions.

7. The distributed production area material management method based on radio frequency identification according to claim 1 is characterized in that: In combination with the label allocation hierarchical mechanism, the first RFID reader is used to allocate labels to the first sub-area, thereby obtaining a first material management solution, including: Determining corresponding label models according to the multiple material types; Initializing the first RFID reader / writer using the multiple tag models and the first working frequency band of the M working frequency bands; According to the first material distribution sequence, the initialized first RFID reader / writer performs tag distribution for the first sub-area to obtain a plurality of first material RFID tags and a corresponding plurality of first RFID keys; The allocation authority is determined based on the tag allocation hierarchical mechanism, and the plurality of first material RFID tags and the plurality of first RFID keys are added to the first material management solution according to the allocation authority.

8. The distributed production area material management method based on radio frequency identification according to claim 7 is characterized in that: The assigned permissions include administrator permissions, general permissions and special permissions; Performing multi-dimensional material grouping on the multiple material types to obtain a first material group, a second material group, and a third material group; Based on the administrator authority, the general authority, and the special authority, the first RFID reader / writer assigns authority to the first material group, the second material group, and the third material group to obtain a plurality of initial authority tags; Based on the usage frequencies and demand changes of the multiple material types, multiple initial authority tags are updated to obtain multiple updated authority tags.

9. The decentralized production area material management method based on radio frequency identification according to claim 1, characterized in that: Also includes: Use RFID readers to monitor target materials in real time and obtain their real-time status; Obtaining the desired material status of the target material according to the target material management plan; If the real-time status of the material does not meet the expected status of the material, an alarm mechanism is triggered; Based on the alarm mechanism, an alarm notification is generated and the real-time status of the materials is updated.

10. A decentralized production area material management system based on radio frequency identification, characterized in that: The steps for implementing the method for managing materials in a decentralized production area based on radio frequency identification according to any one of claims 1 to 9, wherein the decentralized production area material management system based on radio frequency identification comprises: A material classification module, which is used to obtain multiple material types based on the material management needs of the target area; an interference analysis module, configured to perform a spectrum scan on the target area, perform signal interference analysis based on the spectrum scan results, and determine P dense signal frequency bands and Q evacuation signal frequency bands, where P and Q are both positive integers and P is greater than or equal to Q; a frequency band allocation module, the frequency band allocation module being configured to introduce a predetermined allocation analysis strategy to allocate frequency bands to the P dense signal frequency bands and the Q evacuation signal frequency bands, and establish a sub-region frequency band mapping table, wherein the sub-region frequency band mapping table includes M sub-regions and M working frequency bands, where M is a positive integer and M=P+Q; A reader / writer deployment module, configured to deploy M RFID readers / writers in the M sub-areas based on the M operating frequency bands; a first extraction module, configured to extract a first sub-region from the M sub-regions and match a first RFID reader / writer corresponding to the first sub-region among the M RFID readers / writers; a hierarchical allocation module configured to perform priority scoring based on the multiple material types to obtain a material allocation sequence, and to allocate tags to the first sub-area using the first RFID reader / writer in combination with a hierarchical tag allocation mechanism to obtain a first material management plan; A material management module is used to establish a target material management plan for the target area based on the first material management plan.

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