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

Abstract

The invention provides a distributed production area material management method and system based on radio frequency identification, and relates to the technical field of material management, and the method comprises the steps: determining a plurality of material types according to a material management demand; performing frequency spectrum scanning and signal interference analysis on the target area; introducing a predetermined distribution analysis strategy to carry out frequency band distribution; based on the M working frequency bands, deploying M RFID reader-writers; according to the material distribution sequence, in combination with a label distribution layering mechanism, performing label distribution on the sub-regions; and establishing a target material management scheme based on the first material management scheme. According to the invention, the technical problem that the accuracy of radio frequency identification is reduced and the material management efficiency is further influenced due to interference among devices in a distributed production area in the prior art can be solved, signal interference is avoided through frequency spectrum scanning and dynamic frequency band distribution, the material is subjected to label distribution, and the material management efficiency is improved. And the material management efficiency 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] With the increase in the number of stations, various materials and equipment are increasing, and the management of power equipment is becoming more and more difficult, which brings serious safety hazards to the safety management of power plants. The decentralized production area of ​​the substation usually involves the daily management and deployment of a large number of equipment, tools, parts and other materials, including equipment maintenance, spare material storage, tool management, and parts distribution. Radio frequency identification embeds material information into RFID tags and uses RFID readers to automatically track, locate and manage materials, avoiding traditional manual inspection and manual entry. Although RFID technology can effectively improve the efficiency of material management, in complex environments such as substations, radio frequency signals are susceptible to interference, resulting in reduced recognition accuracy of the RFID system, thereby affecting the overall efficiency of material management. There are usually a large number of equipment and electronic instruments in the decentralized production area of ​​substations. These devices will generate strong electromagnetic interference during operation, which may affect the communication signal between the RFID reader and the tag, resulting in material location tracking errors, inventory data lags and other problems, affecting the efficiency of material management.

[0003] In summary, the prior art has technical problems in that due to the wide variety of equipment and complex layout, interference exists between the equipment, resulting in reduced accuracy of radio frequency identification, which 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 problem 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, and the decentralized production area material management method based on radio frequency identification 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 for 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 scoring is 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 a spectrum scan 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 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 The regional frequency band mapping table includes M sub-regions and M working frequency bands, M is a positive integer, and M=P+Q; a reader / writer deployment module, 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, the first extraction module is used to extract a first sub-region from the M sub-regions, and match the first RFID reader / writer corresponding to the first sub-region in the M RFID readers / writers; a hierarchical allocation module, 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, 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] According to the material management requirements of the target area, multiple material types are obtained; spectrum scanning is performed on the target area, signal interference analysis is carried out based on the spectrum scanning results, and P dense signal frequency bands and Q sparse signal frequency bands are determined, where P and Q are both positive integers, and P is greater than or equal to Q; a predetermined allocation analysis strategy is introduced to allocate the P dense signal frequency bands and the Q sparse signal frequency bands, and a sub-region frequency band mapping table is established, where 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; the first sub-region is extracted from the M sub-regions, and the first RFID reader corresponding to the first sub-region is matched among the M RFID readers; priority scoring is performed based on the multiple material types to obtain a material allocation sequence, and in combination with a label allocation hierarchical mechanism, labels are allocated 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 formed. That is to say, by performing spectrum scanning to obtain the wireless signal distribution in the target area, identifying dense signal frequency bands and sparse signal frequency bands, through a predetermined allocation analysis strategy, dynamically allocating spectrum resources, dividing the target area according to the finally determined optimal working frequency band, and deploying RFID readers corresponding to this working frequency band for material label allocation and reading, more efficient and accurate material management is achieved, and the efficiency of material management in decentralized production areas is improved.

[0010] The above description is only an overview of the technical solution of this application. In order to be able to understand the technical means of this application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of this application more obvious and understandable, the specific embodiments of this application are specifically exemplified below. It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of this application, nor is it used to limit the scope of this application. Other features of this application will become easily understood through the following description. Brief Description of the Drawings

[0011] In order to more clearly illustrate the technical solutions in this application or in the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings described below are only exemplary, and for those of ordinary skill in the art, other drawings can be obtained according to the provided drawings without creative efforts.

[0012] Figure 1 It is a schematic flowchart of the method for material management in a decentralized production area based on radio frequency identification of this application;

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

[0014] Explanation of reference numerals in the drawings: 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 implementation manners

[0015] By providing a distributed production area material management method and system based on radio frequency identification, this application solves the technical problem in the prior art that due to the large variety and complex layout of equipment, there is interference between various equipment, resulting in a reduction in the accuracy of radio frequency identification, further affecting the efficiency of material management. By obtaining the distribution of wireless signals in the target area through spectrum scanning, identifying dense signal frequency bands and sparse signal frequency bands, dynamically allocating spectrum resources through a predetermined allocation analysis strategy, dividing the target area according to the finally determined optimal working frequency band, and deploying RFID readers corresponding to this working frequency band for material label allocation and reading, it realizes more efficient and accurate material management and improves the efficiency of material management in the distributed production area.

[0016] Next, the technical solutions in this application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a 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 by the exemplary embodiments described here. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of this application. Additionally, it should be noted that for the sake of description, only parts related to this application are shown in the drawings rather than all of them.

[0017] Embodiment 1, please refer to the attached Figure 1 This application provides a distributed production area material management method based on radio frequency identification. Among them, the distributed production area material management method based on radio frequency identification is applied to a distributed production area material management system based on radio frequency identification. The distributed production area material management method based on radio frequency identification specifically includes the following steps:

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

[0019] Specifically, obtaining the material management requirements of the target area, which is usually a specific area where material management is required, such as the decentralized production area of a substation. The material management requirements are the management requirements for materials in the target area, including various aspects such as inventory management, circulation, tracking, distribution, and use of materials. Conduct a detailed analysis of the material management requirements in the target area to understand which materials need to be finely managed and which materials can be simply managed. Different types of materials have different management requirements. Classify the materials according to factors such as their functions, uses, and values to obtain multiple material types. By obtaining multiple material types based on the material management requirements of the target area and implementing different management for different materials, the efficiency of material distribution and scheduling is improved.

[0020] S200: Perform a spectrum scan on the target area, conduct signal interference analysis based on the spectrum scan results, and determine P dense signal frequency bands and Q sparse signal frequency bands, where P and Q are both positive integers, and P is greater than or equal to Q.

[0021] Furthermore, S200 of this application includes:

[0022] Perform a comprehensive scan of the target area by a spectrum analyzer according to a preset step width to obtain M signal frequency bands; train a frequency band classifier based on a historical spectrum data set and the corresponding historical spectrum annotation set; use the frequency band classifier to divide the M signal frequency bands to obtain P dense signal frequency bands and Q sparse signal frequency bands.

[0023] Specifically, use a spectrum analyzer to perform a comprehensive scan of the target area according to a preset step width, scan one by one within a fixed frequency range, collect the intensity and distribution of signals in different frequency bands to obtain M signal frequency bands. Signals in different frequency bands have different transmission and reception performances, which affect the identification 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 signals, especially parameters such as the frequency and amplitude of signals. During the spectrum scan, the step width refers to the interval of each frequency scan. Usually, the step width is set to a certain frequency range (such as 10 MHz or 100 kHz) so that the spectrum analyzer can gradually cover all signal frequency bands during the scan. The preset step width is a pre-defined approximation width based on the actual situation of the target area to ensure that the entire target area can be covered.

[0024] Obtain the historical spectrum dataset and the corresponding historical spectrum annotation set from the control center of the distributed production area, which contain the frequency utilization rate and interference intensity in different environments and at different times, and determine which frequency bands have strong interference and which are relatively idle. If multiple strong signals overlap on the spectrum or the noise bandwidth increases significantly, it indicates the presence of interference. According to the historical spectrum dataset and the corresponding historical spectrum annotation set, select a suitable model to construct a classifier, including decision trees, random forests, support vector machines (SVMs), convolutional neural networks (CNNs), etc. Taking the random forest as an example, a random forest is an ensemble learning method that uses multiple decision trees for classification. Each tree randomly selects some features of the data during training and establishes classification rules based on these features. The final classification result is determined by the voting of all decision trees, which can significantly reduce the overfitting problem of a single tree.

[0025] Perform data preprocessing on the historical spectrum dataset and the historical spectrum annotation set, and perform feature extraction on the processed historical spectrum dataset and historical spectrum annotation set, such as features like the frequency of the signal, signal strength, interference intensity, etc. Each feature will help the decision tree perform node splitting in the model, and finally obtain the classification result. The random forest constructs multiple decision trees by randomly selecting feature and sample subsets, and votes on the prediction results of these decision trees to obtain the final classification result. Divide the historical spectrum dataset and the historical spectrum annotation set into a training set (e.g., 80%) and a validation set (e.g., 20%), use the training set to train the model, and use the validation set to test the accuracy of the model. Optimize the model performance through methods such as cross-validation and hyperparameter tuning. During the training process, the model will select the optimal splitting features (such as signal strength and interference intensity) based on different decision trees to classify different frequency bands, namely dense frequency bands and sparse frequency bands.

[0026] The frequency band classifier uses the trained random forest model to classify newly input spectrum data (such as M signal frequency bands) into dense signal frequency bands or sparse signal frequency bands. Set the convergence conditions of the model, such as the validation set loss changing less than 0.01 for 5 consecutive rounds or the training set accuracy reaching 95%. Iteratively train the frequency band classifier until the convergence conditions are met, then stop training; otherwise, continue to adjust parameters or optimize the data processing process.

[0027] Input M signal frequency bands into the trained frequency band classifier, which are automatically divided into P dense signal frequency bands and Q sparse signal frequency bands. Dense signal frequency bands refer to those frequency bands with high signal intensity and relatively high interference intensity within the frequency range, which are prone to interference; sparse signal frequency bands refer to those frequency bands with relatively low interference intensity, usually idle or interference-free frequency bands, which can be used for frequency band reallocation or as backup frequency bands. Through the trained frequency band classifier, the signal frequency bands are classified, providing a basis for subsequent area division, avoiding overcrowding or interference in dense signal frequency bands, and improving the signal stability of the entire area.

[0028] S300: Introduce a predetermined allocation analysis strategy to allocate frequency bands for the P dense signal frequency bands and the Q sparse signal frequency bands, and establish a sub-region frequency band mapping table, where 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 frequency band analysis based on the interference situation and utilization situation of signal frequency bands, considering the interference situation between different frequency bands, and determining how to transfer part of the traffic of dense signal frequency bands with higher interference intensity to sparse signal frequency bands that are idle or have lower load. Reasonable allocation rules are formulated according to the density and idle degree of frequency bands. For example, if the interference intensity of dense signal frequency bands in a certain area is relatively high while the interference of sparse signal frequency bands is relatively low, the predetermined allocation analysis strategy may preferentially allocate dense signal frequency bands to low-interference areas or transfer some traffic to sparse frequency bands.

[0030] All signal frequency bands in the P dense signal frequency bands that exceed the preset signal interference threshold are regarded as Y dense interference signal frequency bands. These frequency bands are considered to be overly interfered and may lead to a decline in signal quality. That is to say, a maximum value of signal interference intensity is preset, and the interference intensity of the P dense signal frequency bands is compared with it to obtain Y dense interference signal frequency bands.

[0031] For Y dense interference signal frequency bands, transfer part of the traffic of the dense signal frequency bands with higher interference intensity to the nearest idle or less-loaded evacuation signal frequency bands, obtaining M updated working frequency bands with minimal interference between these working frequency bands. Draw the corresponding regional spectrum diagram based on the M working frequency bands to display information such as the interference intensity and utilization rate of each signal frequency band within the target area, which can visually show the signal distribution. Divide the target area into M sub-areas according to the regional spectrum diagram. According to the mapping relationship between the M sub-areas and the M working frequency bands, construct a sub-area frequency band mapping table to record each sub-area and its assigned working frequency band, ensuring that the signal frequency bands of each sub-area do not overlap with those of other areas, thereby reducing interference. By adopting a predetermined allocation analysis strategy, the dense signal frequency bands and the evacuation signal frequency bands are reasonably allocated to ensure the minimization of signal interference. By reasonably dividing the working frequency bands, ensure the optimal utilization efficiency of the frequency bands in each sub-area, avoiding the problems of overcrowded frequency bands or wasted idle resources, thereby improving the utilization rate of spectrum resources.

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

[0033] S500: Extract the first sub-area from the M sub-areas and match the first RFID reader corresponding to the first sub-area among the M RFID readers.

[0034] Specifically, after dividing the target area into M sub-areas according to the M working frequency bands, each sub-area requires an RFID reader for material identification. To avoid frequency band interference between different sub-areas, the RFID reader of each sub-area will operate on the unique frequency band assigned to this area. Each RFID reader will be configured to be compatible with the working frequency band corresponding to its area. An RFID (Radio Frequency Identification) reader is a device used to read or write RFID tags and can identify the information of the tags without contacting the items. The RFID reader communicates with the RFID tag according to the assigned working frequency band. Within the target area, the RFID readers are deployed according to the location and spatial layout of the sub-areas. Each RFID reader should be located at an appropriate position so as to effectively cover the entire sub-area and not interfere with the RFID readers in adjacent areas. After deploying the RFID readers, adjust their configurations according to the actual situation to optimize the identification range and identification efficiency. The one-to-one allocation method can theoretically minimize conflicts and improve the reading and writing efficiency.

[0035] Randomly select one area from the M sub-areas as the first sub-area, and determine the first RFID reader corresponding to the first sub-area among the M RFID readers. The sub-areas and the RFID readers are in one-to-one correspondence. By deploying RFID readers in each sub-area and ensuring that these RFID readers work in different frequency bands, the interference between frequency bands can be effectively avoided, ensuring that the materials in each sub-area can be accurately identified.

[0036] S600: Based on the multiple material types, perform a priority score to obtain a material allocation sequence. Combining with the label allocation hierarchical mechanism, use the first RFID reader to allocate labels for the first sub-area to obtain the first material management plan.

[0037] Specifically, the material type refers to different types of items or equipment involved in material management, and each material type has different management requirements. According to the characteristics, requirements, and importance of the materials, perform a priority score on all material types to obtain the weight value corresponding to each material type, which helps to determine which materials need to be managed or allocated first. The priority score can be calculated based on factors such as the usage frequency, value, urgency, and safety requirements of the materials. For example, the priority score = a × usage frequency + b × material value + c × urgency. Sort the multiple material types in descending order of the priority score to obtain the material allocation sequence. Each sub-area may require different types and quantities of materials according to its function, area, and operation requirements. According to the material priority in the material allocation sequence, select the material type that best matches the material requirements of each sub-area and allocate the materials one by one.

[0038] The label allocation hierarchical mechanism means that different labels are allocated to different materials according to the permissions, usage frequencies, and demand changes of the materials. Through permission identifiers (such as administrator permission, general permission, and special permission), they are associated with the material labels and keys to ensure that only personnel meeting the permission requirements can operate or access the corresponding materials. According to the priority score and allocation sequence of the materials, combined with the label allocation hierarchical mechanism, allocate appropriate RFID tags to each material type. Based on the above priority score and label allocation hierarchical mechanism, use the first RFID reader to allocate labels to the materials in the first sub-area. The first RFID reader is responsible for reading and writing label information. Through label allocation and priority sorting, form the first material management plan, which details the label allocation, storage method, flow path, etc. of the materials in the first sub-area.

[0039] S700: Based on the first material management plan, form the target material management plan for the target area.

[0040] Specifically, according to the first material management plan, the above steps are executed for the other sub-regions among the M sub-regions, so as to obtain the material management plan corresponding to each sub-region, and thus complete the target material management plan for the target region. By reasonably allocating the management resources within the region according to the material management requirements and the division of the M sub-regions, and combining the RFID technology to allocate labels to the materials, it is ensured that each material corresponds to a key one by one, and the flow of materials within the target region is tracked in real time through the RFID technology, which can improve the accuracy of material management, reduce the risks of loss and misuse, and improve the efficiency of material management in decentralized production regions.

[0041] Further, step S300 of the present application includes:

[0042] According to the predetermined allocation analysis strategy, filter out the signal frequency bands that exceed the preset signal interference threshold among the P dense signal frequency bands, and perform dynamic frequency band reallocation in combination with the Q evacuation signal frequency bands to obtain M working frequency bands; draw a regional frequency spectrum diagram based on the M working frequency bands; according to the regional frequency spectrum diagram, divide the target region into the M sub-regions in combination with the material management requirements; based on the M sub-regions and the M working frequency bands, construct a sub-region frequency band mapping table.

[0043] Specifically, according to the predetermined allocation analysis strategy, filter out the signal frequency bands that exceed the preset signal interference threshold from the P dense signal frequency bands, detect the adjacent evacuation signal frequency bands, and release the idle frequency band resources. That is to say, perform dynamic frequency band reallocation on all the signal frequency bands that exceed the preset signal interference threshold among the P dense signal frequency bands, select the adjacent evacuation signal frequency band closest to the current dense signal frequency band from the Q evacuation signal frequency bands, and transfer part of the traffic of the dense signal frequency band with higher interference intensity to the idle or low-load evacuation signal frequency band. Adjust the frequency band boundary to ensure that there is no spectrum overlap between the frequency bands, so as to avoid new interference. After all the signal frequency bands that exceed the preset signal interference threshold among the P dense signal frequency bands have been subjected to traffic transfer, the current latest working frequency bands are obtained, and M reallocated working frequency bands are formed.

[0044] Use a spectrum analyzer to record the M reallocated working frequency bands and their interference intensity and utilization rate. Visualize the data to generate a regional frequency spectrum diagram, which shows the signal characteristics of different frequency bands. The regional frequency 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 region, and can intuitively display the signal distribution. According to the regional frequency spectrum diagram, divide the target region into M initial sub-regions. According to the spatial layout diagram of the target region, determine the M material flow paths of the M initial sub-regions, and perform path frequency statistics to form a material path frequency matrix. According to the material management requirements, determine the material density of the M initial sub-regions, so as to construct a material density distribution matrix.

[0045] Under the condition of ensuring that the frequency band division result (M signal frequency bands) remains unchanged, taking the material path frequency matrix and the material density distribution matrix as constraint conditions, and minimizing the path cost, maximizing the spatial optimization and the material density balance as the objective functions, multi-objective optimization is performed on the M initial sub-regions to obtain the final M sub-region division results, ensuring that the frequency band does not change due to the adjustment of the region division. According to the one-to-one correspondence between the M sub-regions and the M working frequency bands, a sub-region frequency band mapping table is constructed to clarify the working frequency band corresponding to each sub-region. Through screening and reallocation, signal interference is reduced, the stability of radio frequency identification is improved, the utilization of spectrum resources is optimized by combining dense and sparse signal frequency bands, and the efficiency of material management is improved.

[0046] Further, the present application further includes the following steps:

[0047] Step A: Adjust the preset step width based on a preset step size to obtain a target step width; Step B: Adjust the resolution of the spectrum analyzer according to the target step width, and perform real-time monitoring on the P dense signal frequency bands to obtain P signal interference intensities; Step C: Screen out Y dense interference signal frequency bands that exceed the preset signal interference threshold among the P signal interference intensities; 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, and 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 the scanning accuracy in the spectrum analysis process, and it adjusts the step width of the spectrum scanning. Adjust the preset step width based on the preset step size to determine the target step width, so that the spectrum analyzer can detect more accurate data. Adjust the resolution of the spectrum analyzer according to the target step width, and perform real-time monitoring on the P dense signal frequency bands, and record the signal interference intensity of each frequency band. Adjusting the resolution can change the accuracy of the spectrum analyzer. The higher the accuracy, the finer the resolution. A smaller resolution can help monitor more subtle signal interference situations.

[0049] The adjusted spectrum analyzer is used to monitor the P dense signal frequency bands in real time again, record the interference intensity of each frequency band, which is used to analyze the utilization of the frequency bands and identify the areas of interference and signal overload. A interference threshold is set, and the frequency bands exceeding this threshold are considered dense interference frequency bands, which are considered to be overly interfered and may cause a decline in signal quality, thus affecting the normal operation of the material management system. Obtain the signal interference intensities of the P dense signal frequency bands, and screen out Y dense interference signal frequency bands that exceed the preset signal interference threshold. These frequency bands have relatively high signal interference intensities and may have a greater impact on normal communication or equipment operation.

[0050] Arbitrarily extract a dense interference signal frequency band from the Y dense interference signal frequency bands as the first dense interference signal frequency band. Under the constraint of minimizing the overall interference intensity or balancing the loads of each frequency band, extract the first adjacent evacuation signal frequency band from the Q evacuation signal frequency bands, that is, the evacuation signal frequency band closest to the first dense interference signal frequency band among the Q evacuation signal frequency bands, as the first adjacent evacuation signal frequency band. Calculate the migration traffic that needs to be migrated from the first dense interference signal frequency band to the first adjacent evacuation signal frequency band 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, and perform frequency band modulation accordingly to obtain the updated first working frequency band. Transfer part of the traffic of the first dense interference signal frequency band to the evacuation frequency band to ensure that there is no spectrum overlap between the two.

[0051] For the remaining dense interference signal frequency bands among the Y dense interference signal frequency bands, perform dynamic reallocation according to the processes of steps D and E. Finally, through dynamic adjustment, M stable working frequency bands are obtained. Through the dynamic reallocation of the frequency bands, the interference intensity of the dense interference signal frequency bands is effectively reduced, and the signal quality is improved.

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

[0053] Taking minimizing the overall interference intensity or balancing the loads of each frequency band as a constraint condition; based on the constraint condition, extract the first adjacent evacuation signal frequency band from the Q evacuation signal frequency bands; calculate the 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 the first updated dense signal frequency band and the first updated evacuation signal frequency band; form the first working frequency band according to the first updated dense signal frequency band and the first updated evacuation signal frequency band.

[0054] Specifically, minimizing the overall interference intensity means reducing the interference intensity within the entire area by adjusting the frequency band allocation. The lower the interference intensity, the higher the signal quality and the higher the communication efficiency. Balancing the loads of each frequency band aims to make the loads of each frequency band as balanced as possible, that is, to avoid a situation where the load of a certain frequency band is too high while the loads of other frequency bands are too low, which helps improve the utilization efficiency of spectrum resources. Taking minimizing the overall interference intensity or balancing the loads of each frequency band as a constraint condition, it is ensured that the loads of each frequency band cannot exceed their maximum capacities, the interference intensity cannot exceed the threshold, and the total capacity of the dynamically allocated frequency bands must meet the load requirements of the dense frequency bands. For the dense signal frequency bands, the transferred traffic cannot exceed the load of the current frequency band and cannot exceed the remaining capacity of the evacuation frequency band. According to the constraint conditions, multiple evacuation signal frequency bands that meet the constraint conditions are selected from the Q evacuation signal frequency bands as candidate frequency bands, that is, multiple candidate evacuation signal frequency bands.

[0055] Using the Euclidean distance formula, calculate the distances between the first dense interference signal frequency band and multiple candidate evacuation signal frequency bands. Select the candidate adjacent evacuation signal frequency band closest to the first dense interference signal frequency band as the first adjacent evacuation signal frequency band. Obtain the load value of the dense interference signal frequency band and the available capacity of the first adjacent evacuation signal frequency band. Calculate the transferred traffic according to the load value and the available capacity. Calculate the transferred traffic according to the required frequency band capacity and the available bandwidth of the evacuation frequency band. The transferred traffic determines how much traffic needs to be moved out of the dense signal frequency band and transferred to the evacuation frequency band to relieve the burden on the dense signal frequency band. For the signal frequency bands that require frequency band reallocation, their frequency band boundaries need to be adjusted first to avoid spectrum overlap. The specific adjustment method is as follows: Expand part of the frequency band bandwidth outside the dense signal frequency band to reduce its interference intensity; expand the bandwidth to the evacuation signal frequency band to provide more available spectrum resources. When adjusting the boundaries, ensure that there is no overlap between the frequency ranges of the two, and the adjusted frequency bands can be detected for overlap through spectrum analysis and simulation tools.

[0056] According to the calculated migration traffic, part of the traffic is migrated from the dense interference signal frequency band to the first adjacent evacuation signal frequency band. After migration, the interference intensity in the dense frequency band will decrease, while the interference intensity in the evacuation frequency band may increase. Through simulation or real-time monitoring, evaluate the frequency band load and interference intensity after migration. Confirm whether the interference intensity and load of all frequency bands meet the preset thresholds. If there are still frequency bands that do not meet the requirements, readjust the frequency band allocation. If the system state after migration is still unstable, it may be necessary to readjust the migration strategy or select more evacuation frequency bands again. After migration, the updated dense interference signal frequency band and the updated evacuation signal frequency band are obtained. According to the first updated dense interference signal frequency band and the first updated evacuation signal frequency band, a first working frequency band is constructed, and the first working frequency band meets the conditions of low interference and load balance. By dynamically selecting the evacuation signal frequency band according to the interference intensity and load conditions, after migrating the traffic, the interference intensity of the overall spectrum is effectively controlled. The process of migrating the traffic balances the load of the frequency band, avoids the situation of overloading of some frequency bands, and improves the spectrum utilization efficiency.

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

[0058] Based on the regional spectrum diagram, divide the target area into M initial sub-areas; according to the spatial layout diagram of the target area, determine the M material flow paths of the M initial sub-areas; conduct frequency statistics based on the M material flow paths to form a material path frequency matrix; through the material management requirements, determine the M material densities of the M initial sub-areas; 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 constraint conditions, and with minimizing the path cost, maximizing the spatial optimization, and material density balance as the objective function, perform multi-objective optimization on the M initial sub-areas to obtain the M sub-areas.

[0059] Specifically, the regional spectrum diagram is a visual representation of the spectrum usage situation in the target area, showing the interference intensity, load conditions, etc. of each frequency band at different spatial positions. Dividing the target area into M initial sub-areas according to the regional spectrum diagram is based on the interference intensity, load conditions, etc. of the spectrum within the area. After determining the initial sub-areas, determine the material flow paths within each sub-area according to the spatial layout diagram of the target area. The material flow path refers to the path of the material from one sub-area to another sub-area, which affects the allocation of frequency band resources. Based on the statistical data of the material flow paths, establish a material path frequency matrix to reflect the flow frequency of each path.

[0060] The material path frequency matrix represents the frequency of material flow within the target area, describes the flow frequency of materials from one area to another, and is used to evaluate the density of material flow, so as to adjust the optimization of the path. The material flow path of each sub-area can be expressed as the material flow frequency from a certain area to other areas, and a material path frequency matrix is constructed. Each element in the matrix represents the material flow frequency from one area to another area.

[0061] The material density of each sub-area is the material storage per unit area of the area, which can be statistically calculated according to the material management requirements, that is, the ratio of the total material quantity and the area of the area. The material density distribution matrix represents the material density distribution of each sub-area within the target area, and is used to describe the concentration degree of materials in each sub-area. Each matrix element represents the material density of a sub-area. The balance of material density directly affects whether the distribution of materials among regions is reasonable.

[0062] Path cost is very important in substation material management, especially during material collection, return, and equipment maintenance. Frequent material handling and key use may increase operation costs and time. Therefore, it is necessary to optimize the logistics path, considering the handling time of materials from the storage area to the usage location; the path of key acquisition and return and the access time of locks; the cross-flow and path planning between regions.

[0063] Uneven material density in the substation may lead to excessive storage of materials in some 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 and frequently used materials; the matching problem of keys and materials. The key management corresponding to high-value materials should be more rigorous. The goal of space optimization is to make reasonable use of space and avoid over-accumulation or waste in the area. When performing multi-objective optimization, it may be necessary to set appropriate weights for each objective function to balance the conflicts between different objectives. If there is a conflict between space optimization and path cost (such as a conflict may occur between the shortest path and the optimal space utilization), set weights to guide the optimization direction.

[0064] Multi-objective optimization refers to finding the optimal solution through an optimization algorithm under multiple constraint conditions, that is, minimizing the path cost, maximizing the space optimization, and balancing the material density. The path cost refers to the resources, time, or expenses required for the material flow path. Space optimization means reasonably arranging the materials and frequency band resources in each area in a limited space to maximize the space utilization while reducing interference. The balance of material density means that the distribution of material density should be as uniform as possible to avoid excessive concentration of materials in some areas, causing management difficulties or frequency band overload. Based on the requirements of multi-objective optimization, an appropriate algorithm is selected for optimization, such as particle swarm optimization, genetic algorithm, etc. Starting from the given initial area division (i.e., M initial sub-areas), an initial solution is generated, and the initial path cost, space optimization, and material density balance are calculated. For each solution, the values of the path cost, space optimization, and material density balance are calculated, and then according to the objective function, the quality of each solution is evaluated. The particle swarm optimization algorithm is used to continuously update the set of solutions. In each generation, the solutions are updated according to the objective function and constraint conditions until the stopping criterion (such as the number of iterations or the accuracy requirement) is met. The solution obtained through 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, the optimal sub-area division is found to balance the material density, minimize the cost of each material flow path, and maximize the utilization efficiency of the frequency band resources. By reasonably dividing the sub-areas and optimizing the material flow path, the allocation of frequency band resources is made more efficient, avoiding waste and excessive interference of frequency band resources.

[0066] Furthermore, step S600 of the present application includes:

[0067] Determine the corresponding multiple tag models according to the multiple material types; initialize the first RFID reader through the multiple tag models in combination with the first working frequency band of the M working frequency bands; according to the first material distribution sequence, use the initialized first RFID reader to allocate tags to the first sub-area to obtain multiple first material RFID tags and corresponding multiple first RFID keys; determine the allocation authority based on the tag allocation hierarchical mechanism, and add the multiple first material RFID tags and 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.). According to the material types in the target area, the appropriate RFID tag model is automatically selected, and the working mode of the reader-writer is adjusted according to the frequency band and frequency range. Different types of materials require different kinds of tags, and the selection of tag models will affect the identification efficiency, reading range, storage capacity, etc. of the materials. According to the first working frequency band among M working frequency bands, combined with multiple tag models, the first RFID reader-writer is initialized, and the working frequency band of the RFID reader-writer is configured, including setting the working frequency band, reading parameters, tag types, etc., so that it can read or write RFID tags in the specified frequency band.

[0069] The RFID reader-writer should have an automatic power adjustment mechanism, which can dynamically adjust the power output according to the model and specifications of the material tags. According to the storage density of the materials, the reading distance requirements of the material tags, and the specific environment of the storage location, the power output of the RFID reader-writer is automatically adjusted. According to the material distribution sequence, in order of priority, RFID tags are allocated to the materials in the first sub-region in turn, obtaining multiple first material RFID tags and corresponding multiple first RFID keys. Each tag contains the unique identification information of the material, including material number, type, specification, requisition record, usage history, etc. During the process of material collection, use, and return, the status of the tag is updated in real time through RFID technology.

[0070] A tag allocation hierarchical mechanism is introduced to determine the allocation permissions for different materials. Through permission identifiers (such as administrator permission, general permission, and special permission), they are associated with the material tags and keys to ensure that only personnel meeting the permission requirements can operate or access the corresponding materials. Based on the tag allocation hierarchical mechanism, the allocation permissions for each type of material tag are determined. All allocated tags will be integrated into the material management plan according to the permissions to ensure the 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 detailed material flow data for the management personnel, reducing material loss and misuse. Through automated tag allocation and permission management, the material management process is more efficient, reducing the input of human resources and improving the efficiency of overall material management in the production area.

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

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

[0073] Specifically, allocating permissions means assigning different management permissions to different personnel 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 permissions over all materials; general permissions can only access and operate certain low-value materials, can only receive materials during specific working hours, and can only receive materials within their own job responsibilities; special permissions require additional authentication to receive high-value materials. The specific permission allocation can be adjusted according to the actual situation, and the access authentication corresponding to different permissions is also different. For example, administrator permissions and special permissions usually require dual verification to prevent unauthorized personnel from accessing sensitive areas.

[0074] Material grouping is to classify and organize materials according to characteristics such as type, use, importance, and usage frequency for more refined management and control. The multiple material types are grouped in multiple dimensions, including usage requirements, material requirements, and material importance, to obtain the first material group, the second material group, and the third material group for differential permission allocation and management according to the characteristics of the materials. Material grouping can be carried out in multiple dimensions such as material importance, usage frequency, usage environment, and management level. The first material group refers to the high-level material group, which requires strict permission control and can only be received or operated by administrators or personnel with special permissions; the second material group refers to the intermediate-level material group, which ordinary employees can receive, but there may be restrictions in terms of time, quantity, etc.; the third material group is the low-level material group, with relatively loose permissions, but still needs to be recorded and monitored.

[0075] Appropriate permissions are allocated to materials according to different material groups and permission types to ensure the access capabilities of personnel in different roles among different material groups. By formulating allocation strategies through administrator permissions, general permissions, and special permissions, the security of material management is ensured. Administrator permissions can access and manage the label information of all materials, including all material groups; general permissions can only access and manage the information of low-priority or regular material groups; special permissions are used to handle high-risk or high-value materials (such as electronic component groups, high-end equipment groups, etc.).

[0076] When receiving or returning materials, the RFID reader will read the material tags and extract relevant permission information from the tags to verify in real time whether the operator meets the permission requirements. For high-value materials or keys, secondary verification is usually required, which is confirmed through biometric or authentication methods such as fingerprint recognition, identity verification cards, and face recognition. All operations, including material receipt and return, will be recorded in the log and classified according to permissions. Multi-level permission management ensures that different personnel can only access and operate materials and equipment within their permission scope through reasonable permission level division, dynamic permission allocation, and strict verification mechanisms.

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

[0078] Update the permission tags according to the usage frequency and demand changes of the materials to ensure that the material management adapts to the dynamically changing demands. The usage frequency and demand changes will cause changes in the classification or management strategy of the materials. Therefore, it is necessary to update the permission tags regularly or according to the demand so that the materials can flexibly adapt to the new management strategy. Materials with high usage frequency may require an expanded permission scope, while materials with low usage frequency should have a reduced permission scope. As the importance and value of the materials change, the permissions may need to be adjusted according to the new assessment results. The status changes of the materials (such as being lent out, returned, maintained, etc.) can affect the permission settings in real time. For example, materials under maintenance can have their access permissions reduced, and only those with specific permissions are allowed to perform maintenance. Through the above grouping, permission allocation, and tag update mechanisms, a complete set of material management solutions is formed, which not only ensures the safety and liquidity of the materials but also guarantees the efficiency and flexibility of the material management.

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

[0080] Real-time monitor the target materials through the RFID reader to obtain the real-time status of the materials; according to the target material management solution, obtain the expected status of the target materials; if the real-time status of the materials does not meet the expected status of the materials, trigger the alarm mechanism; based on the alarm mechanism, generate an alarm notification and update the real-time status of the materials.

[0081] Specifically, through the automatic identification and tracking function of the RFID reader, the target materials are monitored in real time to obtain information such as the location, quantity, and usage status of the materials, reflecting the status of the materials, including whether they have been issued, whether they are returned on time, whether they are returned correctly, and whether the cabinet door has been illegally opened. 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 permissions of the material. The expected status of the target material is set according to the management strategy and the use of the material, and the expected status is the ideal status that each material should achieve. Once an abnormal material status (such as non-return, overdue issue, etc.) is detected, an alarm will be triggered, including audible and visual alarms, system pop-up notifications, text messages or email notifications to relevant personnel. During the material management process, the expected status of each material is set according to factors such as the use and demand of the material, and 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 material is compared with the expected status. If a status that does not meet the expectation is found, the alarm mechanism is triggered. When the alarm is triggered, an alarm notification is generated and the material status is updated in real time for subsequent measures to be taken. A detailed alarm notification is generated, including the reason for the alarm (such as overdue return, wrong placement, etc.), relevant material information, comparison of the current status with the expected status, and treatment suggestions. For example, when a material should be in the in-stock state but is overdue for return or placed in the wrong location, the alarm is automatically triggered. The management personnel can conduct investigations and handle the situation based on the alarm notification. By comparing the real-time status of the material with the expected status, abnormal situations can be quickly identified, alarm notifications can be triggered in advance, helping to make responses earlier, avoid delays, and improve the efficiency and intelligent level of material management in decentralized production areas.

[0083] In summary, the method for managing materials in a decentralized production area based on radio frequency identification provided by this application has the following technical effects:

[0084] According to the material management requirements of the target area, multiple material types are obtained; spectrum scanning is performed on the target area, signal interference analysis is carried out based on the spectrum scanning results, P dense signal frequency bands and Q sparse signal frequency bands are determined, where P and Q are both positive integers, and P is greater than or equal to Q; a predetermined allocation analysis strategy is introduced to allocate the P dense signal frequency bands and the Q sparse signal frequency bands, and a sub-region frequency band mapping table is established, where 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 the first RFID reader corresponding to the first sub-region is matched among the M RFID readers; priority scoring is performed based on the multiple material types to obtain a material allocation sequence, combined with a label allocation hierarchical mechanism, and labels are allocated 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 formed. That is, by spectrum scanning, the wireless signal distribution in the target area is obtained, dense signal frequency bands and sparse signal frequency bands are identified, through a predetermined allocation analysis strategy, the spectrum resources are dynamically allocated, the target area is divided according to the finally determined optimal working frequency band, and RFID readers corresponding to this working frequency band are deployed for material label allocation and reading, so as to achieve more efficient and accurate material management and improve the efficiency of material management in decentralized production areas.

[0085] Embodiment 2. Based on the same inventive concept as the method for material management in a decentralized production area based on radio frequency identification in the foregoing Embodiment 1, the present application also provides a system for material management in a decentralized production area based on radio frequency identification. Please refer to the appendix Figure 2 , the system for material management in a decentralized production area based on radio frequency identification includes:

[0086] Material classification module 11, which is used to obtain multiple material types according to the material management requirements of the target area; interference analysis module 12, which is used to perform spectrum scanning on the target area, conduct signal interference analysis based on the spectrum scanning results, and determine P dense signal frequency bands and Q sparse signal frequency bands, where P and Q are both positive integers, and P is greater than or equal to Q; frequency band allocation module 13, which is used to introduce a predetermined allocation analysis strategy to allocate the P dense signal frequency bands and the Q sparse signal frequency bands, and establish a sub-region frequency band mapping table, where 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; reader / writer deployment module 14, which is used to deploy M RFID readers / writers for the M sub-regions based on the M working frequency bands; first extraction module 15, which is used to extract a first sub-region from the M sub-regions and match the first RFID reader / writer corresponding to the first sub-region among the M RFID readers / writers; hierarchical allocation module 16, which is used to perform priority scoring based on the multiple material types to obtain a material allocation sequence, combine the label allocation hierarchical mechanism, and allocate labels for the first sub-region through the first RFID reader / writer to obtain a first material management plan; material management module 17, which is used to form 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 radio frequency identification-based decentralized production area material management system is further used for:

[0088] Conduct a comprehensive scan of the target area by a spectrum analyzer according to a preset step width to obtain M signal frequency bands; train a frequency band classifier based on a historical spectrum data set and a corresponding historical spectrum annotation set; divide the M signal frequency bands through 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 radio frequency identification-based decentralized production area material management system is further used for:

[0090] According to the predetermined allocation analysis strategy, screen the signal frequency bands in the P dense signal frequency bands that exceed the preset signal interference threshold, combine with the Q sparse signal frequency bands for dynamic frequency band reallocation to obtain M working frequency bands; draw a regional spectrum diagram based on the M working frequency bands; divide the target area into the M sub-regions according to the regional spectrum diagram in combination with the material management requirements; construct the sub-region frequency band mapping table based on the M sub-regions and the M working frequency bands.

[0091] Furthermore, the frequency band allocation module 13 in the RFID-based decentralized production area material management system is further configured to:

[0092] Step A: Adjust the preset step width based on a preset step size to obtain a target step width; Step B: Adjust the resolution of the spectrum analyzer according to the target step width, and monitor the P dense signal frequency bands in real time to obtain P signal interference intensities; Step C: Screen out Y dense interference signal frequency bands among the P signal interference intensities that exceed the preset signal interference threshold; Step D: Extract the first dense interference signal frequency band from the Y dense interference signal frequency bands; Step E: Perform dynamic frequency band reassignment based on the first dense interference signal frequency band and the first adjacent evacuation signal frequency band to obtain the first working frequency band; Traverse the Y dense interference signal frequency bands, and repeat Steps D to E until the M working frequency bands are obtained.

[0093] Furthermore, the frequency band allocation module 13 in the RFID-based decentralized production area material management system is further configured to:

[0094] Take minimizing the overall interference intensity or balancing the load of each frequency band as a constraint condition; Based on the constraint condition, extract the first adjacent evacuation signal frequency band from the Q evacuation signal frequency bands; Calculate the migration flow 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; Modulate the first dense interference signal frequency band to the first adjacent evacuation signal frequency band according to the migration flow to obtain the first updated dense signal frequency band and the first updated evacuation signal frequency band; Form the first working frequency band according to the first updated dense signal frequency band and the first updated evacuation signal frequency band.

[0095] Furthermore, the frequency band allocation module 13 in the RFID-based decentralized production area material management system is further configured to:

[0096] Based on the regional spectrum diagram, divide the target area into M initial sub-areas; Determine the 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; Determine the M material densities of the M initial sub-areas through the material management requirements; Construct a material density distribution matrix based on the M material densities; Take the material path frequency matrix and the material density distribution matrix as constraint conditions, and take minimizing the path cost, maximizing the spatial optimization and the material density balance as the objective function, and perform multi-objective optimization on the M initial sub-areas to obtain the M sub-areas.

[0097] Furthermore, the hierarchical allocation module 16 in the RFID-based decentralized production area material management system is further configured to:

[0098] Determine corresponding multiple tag models according to the multiple material types; initialize the first RFID reader through 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, use the initialized first RFID reader to allocate tags to the first sub-region, obtaining multiple first material RFID tags and corresponding multiple first RFID keys; determine the allocation authority based on the tag allocation hierarchical mechanism, and add the multiple first material RFID tags and multiple first RFID keys to the first material management plan according to the allocation authority.

[0099] Furthermore, the hierarchical allocation module 16 in the RFID-based decentralized production area material management system is further configured to:

[0100] The allocation authority includes administrator authority, general authority, and special authority; perform 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, use the first RFID reader to perform authority allocation for the first material group, the second material group, and the third material group, obtaining multiple initial authority tags; update the multiple initial authority tags based on the usage frequency and demand changes of the multiple material types to obtain multiple updated authority tags.

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

[0102] Real-time monitor the target material through an RFID reader to obtain the real-time state of the material; obtain the expected state of the material according to the target material management plan; if the real-time state of the material does not conform to the expected state of the material, trigger an alarm mechanism; based on the alarm mechanism, generate an alarm notification and update the real-time state of the material.

[0103] The various embodiments in this specification are described in a progressive manner, and the key point of each embodiment is the difference from other embodiments. The foregoing Figure 1The method and specific example of the decentralized production area material management based on radio frequency identification in the first embodiment are equally applicable to the decentralized production area material management system based on radio frequency identification in this embodiment. Through the above detailed description of the method of the decentralized production area material management based on radio frequency identification, those skilled in the art can clearly know the decentralized production area material management system based on radio frequency identification in this embodiment. Therefore, for the sake of simplicity of the specification, it will not be elaborated here. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple. For the relevant parts, please refer to the description in the method section.

[0104] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0105] Obviously, those skilled in the art can 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 equivalent technologies, the present application is also intended to include these changes and modifications.

Claims

1. A decentralized production area material management method based on radio frequency identification, characterized in that: include: According to 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 result, 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 allocate 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, 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; 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; Priority scoring is performed based on the multiple material types to obtain a material allocation sequence, and 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 plan; Based on the first material management plan, a target material management plan for the target area is established.

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 result, 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; Training a frequency band classifier based on a historical spectrum dataset and a 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 allocate 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, the signal frequency bands exceeding the preset signal interference threshold are screened out from the P dense signal frequency bands, and the dynamic frequency band reallocation is performed in combination with the Q sparse signal frequency bands to obtain M working frequency bands; Draw a regional spectrum diagram based on the M working frequency bands; According to the regional 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.

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, the signal frequency bands exceeding the preset signal interference threshold in the P dense signal frequency bands are screened, and the 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 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: performing dynamic frequency band reallocation based on the first dense interference signal frequency band and the first adjacent evacuation signal frequency band to obtain a first working frequency band; The Y dense interference signal frequency bands are traversed, and steps D to E are repeated until the M working frequency bands are obtained.

5. The decentralized production area material management method based on radio frequency identification according to claim 4 is characterized in that: Dynamically reallocating the frequency band based on the first dense interference signal frequency band and the first adjacent sparse signal frequency band to obtain a first working 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 distributed production area material management method based on radio frequency identification according to claim 3 is characterized in that: According to the regional spectrum diagram, the target area is divided into the M sub-areas in combination with the material management requirements, including: Based on the regional frequency spectrum, the target region is divided into M initial sub-regions; 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; Taking 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, multi-objective optimization is performed on the M initial sub-regions to obtain the M sub-regions.

7. The decentralized 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, and a first material management solution is obtained, including: Determine a plurality of corresponding label models according to the plurality of material types; Initializing the first RFID reader / writer by using the multiple tag models and combining 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 label distribution for the first sub-area to obtain a plurality of first material RFID labels and a corresponding plurality of first RFID keys; The allocation authority is determined based on the label allocation hierarchical mechanism, and the plurality of first material RFID labels 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 authority is assigned to the first material group, the second material group and the third material group through the first RFID reader / writer 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 is characterized in that: Also includes: Monitor target materials in real time through RFID readers to obtain real-time status of materials; According to the target material management plan, obtaining the expected material status of the target material; 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 decentralized production area material management method 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, wherein the material classification module is used to obtain multiple material types according to the material management requirements 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 result, 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 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, M is a positive integer, and M=P+Q; A reader / writer deployment module, the reader / writer deployment module is used to deploy M RFID readers / writers in the M sub-areas based on the M working frequency bands; A first extraction module, 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 among the M RFID readers-writers; A hierarchical allocation module, 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-area 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.

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