Fixed asset dynamic management method and system based on RFID tag

Abstract

The invention belongs to the technical field of Internet of Things, and discloses a fixed asset dynamic management method and system based on an RFID tag, and the method comprises the steps: obtaining the fixed asset data of an enterprise through employing a radio frequency identification technology, and providing the feature data of the fixed asset; based on the extracted feature data of the fixed assets, evaluating the feature data of the fixed assets by using a state analysis algorithm, and identifying key factors influencing the health state of the fixed assets; on the basis of a trend analysis algorithm, key factors influencing the health state of the fixed assets are analyzed, and the change trend of the health state of the fixed assets is obtained; and an asset maintenance plan and an operation strategy are optimized in combination with the change trend and the real-time operation state of the fixed assets. According to the invention, the real-time performance and accuracy of asset management are improved, the workload of manual checking is reduced, and the risk of loss and loss of assets is reduced, so that the overall management efficiency and decision-making quality are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet of Things, and in particular to a method and system for dynamic management of fixed assets based on RFID tags. Background Art

[0002] With the development of RFID (radio frequency identification) technology, more and more enterprises and institutions are applying it to the dynamic management of fixed assets. RFID technology uses radio signals to identify and read and write relevant data of specific targets without physical contact. It supports the identification of high-speed moving objects and the simultaneous reading of multiple tags, and the operation is fast and efficient. Especially in the field of fixed asset management, with the rapid expansion of the asset scale of schools, hospitals, enterprises and other units, the asset structure is becoming more and more complex, and the traditional manual registration method can no longer meet the management needs. Many enterprises and units still use manual registration or paper file management methods, which cannot achieve real-time data update and information management, resulting in the inability to record fixed asset changes in a timely manner, and the loss or transfer of assets is difficult to perceive in a timely manner. This has brought huge challenges to asset management and inventory work.

[0003] Existing technologies are not convenient for analyzing asset health status and changing trends, and cannot accurately identify key factors affecting asset health, resulting in a lack of data support for asset maintenance and operation strategies. In addition, they lack trend analysis and real-time data feedback, and are unable to predict changes in asset health status, resulting in delayed adjustments to maintenance plans and an inability to effectively prevent asset failures or losses.

[0004] Therefore, how to provide a method and system for dynamic management of fixed assets based on RFID tags is a problem that needs to be solved urgently. Summary of the invention

[0005] The embodiments of the present invention provide a method and system for dynamic management of fixed assets based on RFID tags to solve the problems in the prior art that it is inconvenient to analyze the health status and change trends of assets, and it is impossible to accurately identify the key factors affecting the health of assets, resulting in a lack of data support for asset maintenance and operation strategies, and a lack of trend analysis and real-time data feedback, and it is impossible to predict changes in the health status of assets, resulting in delayed adjustments to maintenance plans and an inability to effectively prevent asset failures or losses.

[0006] In order to have a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not a general review, nor is it intended to identify key / important components or to describe the scope of protection of these embodiments. Its only purpose is to present some concepts in a simple form as a prelude to the detailed description that follows.

[0007] According to a first aspect of an embodiment of the present invention, a method for dynamic management of fixed assets based on RFID tags is provided.

[0008] In one embodiment, a method for dynamic management of fixed assets based on RFID tags includes: Use radio frequency identification technology to obtain enterprise fixed asset data and propose fixed asset feature data; Based on the extracted fixed asset characteristic data, the status analysis algorithm is used to evaluate the fixed asset characteristic data and identify the key factors affecting the health status of fixed assets; Based on the trend analysis algorithm, the key factors affecting the health status of fixed assets are analyzed to obtain the changing trend of the health status of fixed assets; and the asset maintenance plan and operation strategy are optimized by combining the changing trend with the real-time operating status of fixed assets.

[0009] In one embodiment, based on the extracted fixed asset feature data, the fixed asset feature data is evaluated using a status analysis algorithm to identify key factors affecting the health status of fixed assets, including: Use chaos mapping to generate the initial population of fixed asset characteristic data and set the parameters of the state analysis algorithm; Based on the extracted fixed asset characteristic data, the health fitness value of each fixed asset is calculated to evaluate its current health status; Based on the health fitness value of each fixed asset, the fixed asset characteristic data population is sorted using a sorting algorithm, the fixed asset characteristic data population is re-divided, and a hierarchy system is established; During the iteration process, according to the change of health fitness value, the global optimal health state position in the fixed asset group is updated, and the asset characteristics of the current optimal health state are recorded; By analyzing the fixed asset health status data updated during the iteration process, the key features that affect the asset health status are identified.

[0010] In one embodiment, based on the trend analysis algorithm, the key factors affecting the health status of fixed assets are analyzed to obtain the changing trend of the health status of fixed assets; and the asset maintenance plan and operation strategy are optimized by combining the changing trend and the real-time operation status of the fixed assets, including: Randomly initialize the parent population, variant population, and offspring population according to the key factors of health status within the preset range, and set the parameters of the trend analysis algorithm; The root mean square error is used as the fitness function to calculate the health fitness of each fixed asset, and the parent population is sorted from high to low according to the fitness; Update each individual in the parent population and generate a new offspring population through crossover and mutation operations; Compare the fitness of the offspring and the parent. If the offspring is in a healthier state than the parent, replace the parent with the offspring; otherwise, adjust the parameters of the trend analysis algorithm. Determine whether the maximum number of iterations has been reached. If so, output the optimal health fitness; if not, continue to update each individual in the parent population; The optimal health fitness is used as the penalty parameter and kernel function parameter of the support vector regression machine to build a trend prediction model, and based on the trend prediction model, the changing trend of the health status of fixed assets is obtained; Optimize asset maintenance plans and operation strategies based on change trends and real-time operating status.

[0011] According to a second aspect of an embodiment of the present invention, a dynamic management system for fixed assets based on RFID tags is provided.

[0012] In one embodiment, a fixed asset dynamic management system based on RFID tags includes: The data acquisition module is used to acquire the enterprise fixed asset data using the wireless radio frequency identification technology and to obtain the fixed asset characteristic data; The factor analysis module is used to evaluate the fixed asset characteristic data based on the extracted fixed asset characteristic data using the status analysis algorithm to identify the key factors affecting the health status of the fixed assets; The trend analysis and management module is used to analyze the key factors affecting the health status of fixed assets based on the trend analysis algorithm, and obtain the changing trend of the health status of fixed assets; and optimize the asset maintenance plan and operation strategy by combining the changing trend with the real-time operating status of fixed assets.

[0013] According to a third aspect of an embodiment of the present invention, a computer device is provided.

[0014] In some embodiments, the computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0015] According to a fourth aspect of embodiments of the present invention, a computer-readable storage medium is provided.

[0016] In one embodiment, the computer-readable storage medium stores a computer program, and the computer program implements the steps of the above method when executed by a processor.

[0017] The technical solution provided by the embodiment of the present invention may have the following beneficial effects: 1. The present invention evaluates the health status of assets through a status analysis algorithm, can accurately identify the key factors affecting the health of fixed assets, and predict the changing trend of the health status through a trend analysis algorithm. Combined with the real-time operating status, it optimizes the maintenance plan and operation strategy of the assets, which not only improves the real-time and accuracy of asset management, but also reduces the workload of manual inventory, reduces the risk of asset loss and loss, and improves the overall management efficiency and decision-making quality.

[0018] 2. The present invention combines chaotic mapping, triangular fuzzy number sorting analysis and health fitness assessment to optimize the analysis and classification of fixed asset health status, dynamically divide asset groups using sorting algorithms, improve management accuracy, optimize maintenance strategies based on trend prediction, improve asset utilization efficiency, and realize intelligent dynamic management.

[0019] 3. The present invention combines trend analysis algorithm with support vector regression machine to accurately predict the changing trend of the health status of fixed assets, monitor asset status in real time and optimize maintenance plans and operation strategies, improve management accuracy and efficiency, extend asset life, reduce failure rate, and realize intelligent and effective dynamic management of fixed assets based on RFID tags.

[0020] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0022] Figure 1 is a flow chart of a method for dynamic management of fixed assets based on RFID tags according to an exemplary embodiment; Figure 2 is a principle block diagram of a fixed asset dynamic management system based on RFID tags according to an exemplary embodiment; Figure 3 The figure is a schematic diagram showing the structure of a computer device according to an exemplary embodiment. DETAILED DESCRIPTION

[0023] The following description and accompanying drawings fully illustrate the specific embodiments of this article so that those skilled in the art can practice them. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. The scope of the embodiments of this article includes the entire scope of the claims, as well as all available equivalents of the claims. Herein, the terms "first", "second", etc. are only used to distinguish one element from another, without requiring or implying any actual relationship or order between these elements. In fact, the first element can also be called the second element, and vice versa. Moreover, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that the structure, device or equipment including a series of elements includes not only those elements, but also other elements that are not explicitly listed, or also include elements inherent to such structure, device or equipment. In the absence of more restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the structure, device or equipment including the elements. Each embodiment is described in a progressive manner herein, and each embodiment focuses on the differences from other embodiments, and the same and similar parts between the embodiments can be referred to each other.

[0024] The terms "longitudinal", "lateral", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc. in this document indicate the orientation or position relationship based on the orientation or position relationship shown in the drawings, and are only for the convenience of describing this document and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In the description of this document, unless otherwise specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a mechanical connection or an electrical connection, it can also be the internal communication of two elements, it can be a direct connection, or it can be an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0025] As used herein, the term "plurality" means two or more than two, unless otherwise specified.

[0026] In this document, the character " / " indicates that the preceding and following objects are in an "or" relationship. For example, A / B means: A or B.

[0027] In this article, the term "and / or" is a description of the association relationship between objects, indicating that three relationships may exist. For example, A and / or B means: A or B, or, A and B.

[0028] It should be understood that, although the various steps in the flow chart are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the figure may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0029] Each module in the device or system of the present application can be implemented in whole or in part by software, hardware, or a combination thereof. The above modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to the above modules.

[0030] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0031] Figure 1 An embodiment of the fixed asset dynamic management method based on RFID tags of the present invention is shown.

[0032] In this optional embodiment, the method for dynamic management of fixed assets based on RFID tags includes: Step S101, using radio frequency identification technology (i.e., RFID tags) to obtain enterprise fixed asset data and extract fixed asset feature data; Specifically, enterprise fixed asset data includes: basic asset information, location and storage information, maintenance and operation records, asset status and health status, etc.

[0033] Specifically, fixed asset characteristic data include: health fitness data, usage and maintenance data, environmental data and fault data, etc.

[0034] Step S102, based on the extracted fixed asset characteristic data, using a status analysis algorithm to evaluate the fixed asset characteristic data, and identifying key factors affecting the health status of the fixed assets; Specifically, the key factors include: usage, maintenance and repair records, asset load and working status, environmental factors, performance indicators, equipment aging degree and operator factors.

[0035] Step S103, based on the trend analysis algorithm, analyze the key factors affecting the health status of fixed assets to obtain the changing trend of the health status of fixed assets; and optimize the asset maintenance plan and operation strategy by combining the changing trend and the real-time operation status of fixed assets.

[0036] Specifically, asset maintenance plans include: preventive maintenance plans, corrective maintenance plans, spare parts management, maintenance cost management, etc.

[0037] Specifically, the operation strategies include: load management, real-time monitoring and adjustment, optimization of operating time, energy efficiency optimization, risk assessment and emergency response, etc.

[0038] In this optional embodiment, when using wireless radio frequency identification technology to obtain enterprise fixed asset data and propose fixed asset characteristic data, a number of fixed asset data points can be randomly extracted from the obtained enterprise fixed asset data, and a preliminary asset operation characteristic model can be constructed based on the data points of the several fixed assets; all fixed asset data points are input into the preliminary asset operation characteristic model, the difference between each fixed asset data point and the preliminary asset operation characteristic model is calculated, and a threshold is set for classification; if a data point of a fixed asset is less than the threshold, it is classified as a normal fixed asset data point, otherwise, it is classified as an abnormal fixed asset data point; determine whether to adopt a new asset operation characteristic model, if the number of normal fixed asset data points is the largest, select the new asset operation characteristic model as the final asset operation characteristic model, and extract the fixed asset characteristic data based on the final asset operation characteristic model, otherwise, abandon the current asset operation characteristic model and reconstruct the asset operation characteristic model.

[0039] In this optional embodiment, when evaluating the fixed asset characteristic data based on the extracted fixed asset characteristic data using a state analysis algorithm and identifying the key factors affecting the health status of the fixed assets, a chaotic map (i.e., a Tent chaotic map) can be used to generate an initial population of the fixed asset characteristic data, and the parameters of the state analysis algorithm can be set; based on the extracted fixed asset characteristic data, the health fitness value of each fixed asset is calculated to evaluate its current health status; based on the health fitness value of each fixed asset, the fixed asset characteristic data population is sorted using a sorting algorithm, the fixed asset characteristic data groups are re-divided, and a hierarchy is established; during the iteration process, the global optimal health status position in the fixed asset group is updated according to the change in the health fitness value, and the asset characteristics of the current optimal health status are recorded; by analyzing the fixed asset health status data updated during the iteration process, the key characteristics affecting the asset health status are identified.

[0040] Specifically, the state analysis algorithm is an improved chicken swarm optimization algorithm. The basic chicken swarm optimization algorithm may be premature and fall into a local optimum. Therefore, the present invention uses Tent chaotic mapping to initialize the population to improve the uniformity and ergodicity of the initial population.

[0041] In this optional embodiment, based on the health fitness value of each fixed asset, a sorting algorithm is used to sort the fixed asset characteristic data population, the fixed asset characteristic data groups are re-divided, and a hierarchy system is established. A triangular fuzzy number complementary judgment matrix can be constructed according to the health fitness value of each fixed asset; a consistency check is performed on the constructed triangular fuzzy number complementary judgment matrix, and if the consistency meets the preset standard, the sorting weight of the triangular fuzzy number complementary judgment matrix is ​​calculated, otherwise, the triangular fuzzy number complementary judgment matrix is ​​corrected and recalculated according to the current fitness value; the fixed asset groups are sorted, and the sorting weight value corresponding to each fixed asset is calculated according to the health fitness value of each fixed asset; based on the sorting results and the sorting weight values, the fixed asset characteristic data groups are re-divided, and a hierarchy system is established according to the high and low health fitness values.

[0042] Specifically, the sorting algorithm is a triangular fuzzy number complementary judgment matrix sorting method of a niche genetic algorithm. The triangular fuzzy number complementary judgment matrix is ​​a matrix form used in fuzzy decision analysis. It combines the concepts of fuzzy numbers and complementary matrices to help conduct decision analysis with strong uncertainty and ambiguity.

[0043] Specifically, the ranking weights of the triangular fuzzy number complementary judgment matrix are calculated by the fuzzy hierarchical analysis method, including: 1) Construct triangular fuzzy number judgment matrix; 2) Perform weighted averaging on fuzzy numbers; 3) Normalize the matrix; 4) Calculate the weight vector; 5) Conduct consistency check; 6) Sort according to the weight vector to obtain the final sorting result.

[0044] In this optional embodiment, the formula for calculating the ranking weight value corresponding to each fixed asset is: ; Where W i represents the ranking weight value of the i-th fixed asset; f i represents the health fitness value of the i-th fixed asset; r i represents the ranking rank of the i-th fixed asset; α represents the health fitness adjustment factor; β represents the ranking adjustment factor; N represents the total number of fixed asset groups; e represents the exponential decay function.

[0045] In this optional embodiment, when the groups of fixed asset characteristic data are re-divided based on the sorting results and sorting weight values, and a hierarchical system is established according to the health fitness values, a threshold of the health fitness value can be set according to the sorting results of the fixed assets, and the fixed assets can be sorted according to the fitness values ​​to determine the grouping criteria; the fixed assets can be divided into several health levels according to the sorting weight values ​​and the health fitness values ​​and the determined grouping criteria; a health level is assigned to each group of fixed asset characteristic data according to the division results, with assets with high health fitness values ​​being classified as high levels and assets with low health fitness values ​​being classified as low levels.

[0046] In this optional embodiment, the formula for updating the global optimal health status position in the fixed asset group is: ; In the formula, H global (t+1) represents the global optimal health status position of the fixed asset group after updating in the t+1th iteration; H global (t) represents the global optimal health status position of the fixed asset group after updating in the tth iteration; H a (t) represents the health status position of the a-th fixed asset in the t-th iteration; ω represents the inertia weight; γ represents the update step size; ρ represents the fitness factor.

[0047] In this optional embodiment, based on the trend analysis algorithm, the key factors affecting the health status of fixed assets are analyzed to obtain the changing trend of the health status of fixed assets; and when optimizing the asset maintenance plan and operation strategy in combination with the changing trend and the real-time operation status of the fixed assets, the parent population, the variant population and the child population can be randomly initialized within a preset range according to the key factors of the health status, and the parameters of the trend analysis algorithm can be set; the root mean square error is used as the fitness function to calculate the health fitness of each fixed asset, and the parent population is sorted from high to low according to the fitness; each individual in the parent population is updated, and Generate a new offspring population through crossover and mutation operations; compare the fitness of the offspring and the parent generation. If the offspring is in a healthier state than the parent, replace the parent with the offspring; otherwise, adjust the parameters of the trend analysis algorithm; determine whether the maximum number of iterations has been reached. If so, output the optimal health fitness; if not, continue to update each individual in the parent population; use the optimal health fitness as the penalty parameter and kernel function parameter of the support vector regression machine to build a trend prediction model, and based on the trend prediction model, obtain the changing trend of the health status of fixed assets; optimize asset maintenance plans and operation strategies based on the changing trend and real-time operating status.

[0048] Specifically, the trend analysis algorithm is a gray wolf optimization algorithm, which simulates the hunting behavior of gray wolf groups, adopts the role division and cooperation of α, β, and δ wolves, and uses the strategy of encircling, approaching, and surrounding prey to gradually approach the optimal solution. In the present invention, the gray wolf algorithm simulates the hunting behavior of gray wolf groups, randomly initializes the parent generation, mutation group, and offspring group, and uses the root mean square error as the fitness function to calculate the health fitness of fixed assets. The offspring is generated through crossover and mutation operations, and the parent generation is updated according to the fitness, and the trend analysis parameters are optimized, so as to construct a trend prediction model, predict the changes in the health status of fixed assets, and then optimize the asset maintenance plan and operation strategy.

[0049] In this optional embodiment, when the optimal health fitness is used as the penalty parameter and kernel function parameter of the support vector regression machine to construct a trend prediction model, and based on the trend prediction model, the changing trend of the health status of fixed assets is obtained, the optimal fitness value of the health status of the fixed assets can be used as the penalty parameter and kernel function parameter of the support vector regression machine; the support vector regression machine model is constructed using the optimal health fitness parameters to fit the changing relationship between the health status of fixed assets and key influencing factors to form a trend prediction model; real-time data is input into the trend prediction model, and the trend prediction model is used to predict the changing trend of the health status of fixed assets in the future.

[0050] Figure 2 An embodiment of the fixed asset dynamic management system based on RFID tags of the present invention is shown.

[0051] In this optional embodiment, the fixed asset dynamic management system based on RFID tags includes: The data acquisition module 201 is used to acquire the enterprise fixed asset data using the radio frequency identification technology and to obtain the fixed asset characteristic data; The factor analysis module 202 is used to evaluate the fixed asset characteristic data based on the extracted fixed asset characteristic data using a state analysis algorithm to identify key factors affecting the health status of the fixed assets; The trend analysis and management module 203 is used to analyze the key factors affecting the health status of fixed assets based on the trend analysis algorithm, obtain the changing trend of the health status of fixed assets; and optimize the asset maintenance plan and operation strategy by combining the changing trend and the real-time operation status of fixed assets.

[0052] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 3As shown. The computer device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store static information and dynamic information data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the steps in the above method embodiment are implemented.

[0053] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0054] In addition, the present invention also provides a computer device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiment when executing the computer program.

[0055] In addition, the present invention further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps in the above method embodiment are implemented.

[0056] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0057] The present invention is not limited to the structures which have been described above and shown in the drawings, and various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A method for dynamic management of fixed assets based on RFID tags, characterized in that: include: Use radio frequency identification technology to obtain enterprise fixed asset data and propose fixed asset feature data; Use chaos mapping to generate the initial population of fixed asset characteristic data and set the parameters of the state analysis algorithm; Based on the extracted fixed asset characteristic data, the health fitness value of each fixed asset is calculated to evaluate its current health status; Based on the health fitness value of each fixed asset, the fixed asset characteristic data population is sorted using a sorting algorithm, the fixed asset characteristic data population is re-divided, and a hierarchy system is established; During the iteration process, according to the change of health fitness value, the global optimal health state position in the fixed asset group is updated, and the asset characteristics of the current optimal health state are recorded; By analyzing the fixed asset health status data updated during the iteration process, key features that affect the asset health status are identified; Based on the trend analysis algorithm, the key factors affecting the health status of fixed assets are analyzed to obtain the changing trend of the health status of fixed assets; And combine the change trends and real-time operating status of fixed assets to optimize asset maintenance plans and operating strategies.

2. The method for dynamic management of fixed assets based on RFID tags according to claim 1, characterized in that: The method of obtaining enterprise fixed asset data by using radio frequency identification technology and proposing fixed asset characteristic data includes: Randomly extract a number of fixed asset data points from the acquired enterprise fixed asset data, and build a preliminary asset operation characteristic model based on the data points of the fixed assets; Input all fixed asset data points into the preliminary asset operation characteristic model, calculate the difference between each fixed asset data point and the preliminary asset operation characteristic model, and set a threshold for classification; if a fixed asset data point is less than the threshold, it is classified as a normal fixed asset data point, otherwise, it is classified as an abnormal fixed asset data point; Determine whether to adopt a new asset operation characteristic model. If the number of data points of normal fixed assets is the largest, select the new asset operation characteristic model as the final asset operation characteristic model, and extract the fixed asset characteristic data based on the final asset operation characteristic model. Otherwise, abandon the current asset operation characteristic model and rebuild the asset operation characteristic model.

3. The method for dynamic management of fixed assets based on RFID tags according to claim 1, characterized in that: Based on the health fitness value of each fixed asset, the fixed asset feature data population is sorted using a sorting algorithm, the fixed asset feature data population is re-divided, and a hierarchy system is established, including: According to the health fitness value of each fixed asset, a triangular fuzzy number complementary judgment matrix is ​​constructed; The constructed triangular fuzzy number complementary judgment matrix is ​​checked for consistency. If the consistency meets the preset standard, the sorting value of the triangular fuzzy number complementary judgment matrix is ​​calculated. Otherwise, the triangular fuzzy number complementary judgment matrix is ​​corrected and recalculated according to the current fitness value. Sort the fixed asset group, and calculate the sorting weight value corresponding to each fixed asset according to the health fitness value of each fixed asset; Based on the sorting results and sorting weight values, the groups of fixed asset characteristic data are re-divided, and a hierarchy is established according to the health fitness values.

4. The method for dynamic management of fixed assets based on RFID tags according to claim 3 is characterized in that: The formula for calculating the ranking weight value corresponding to each fixed asset is: ； Where W i represents the ranking weight value of the i-th fixed asset; f i represents the health fitness value of the i-th fixed asset; r i represents the ranking rank of the i-th fixed asset; α represents the health fitness adjustment factor; β represents the ranking adjustment factor; N represents the total number of fixed asset groups; e represents the exponential decay function.

5. The method for dynamic management of fixed assets based on RFID tags according to claim 3 is characterized in that: The method of re-dividing the fixed asset characteristic data groups based on the sorting results and the sorting weight values, and establishing a hierarchy system according to the health fitness values ​​includes: According to the sorting results of fixed assets, the threshold of health fitness value is set, the fixed assets are sorted according to the fitness value, and the grouping standard is determined; According to the ranking weight value and health fitness value, the fixed assets are divided into several health levels according to the determined grouping criteria; According to the division results, a health level is assigned to each group of fixed asset characteristic data, with assets with high health fitness values ​​being classified as high levels and assets with low health fitness values ​​being classified as low levels.

6. The method for dynamic management of fixed assets based on RFID tags according to claim 1, characterized in that: The formula for updating the global optimal health status position in the fixed asset group is: ； In the formula, H global (t+1) represents the global optimal health status position of the fixed asset group after updating in the t+1th iteration; H global (t) represents the global optimal health status position of the fixed asset group after updating in the tth iteration; H a (t) represents the health status position of the a-th fixed asset in the t-th iteration; ω represents the inertia weight; γ represents the update step size; ρ represents the fitness factor.

7. The method for dynamic management of fixed assets based on RFID tags according to claim 1, characterized in that: The trend analysis algorithm is used to analyze the key factors affecting the health status of fixed assets and obtain the changing trend of the health status of fixed assets; In combination with the change trend and the real-time operating status of fixed assets, the asset maintenance plan and operation strategy are optimized, including: Randomly initialize the parent population, variant population, and offspring population according to the key factors of health status within the preset range, and set the parameters of the trend analysis algorithm; The root mean square error is used as the fitness function to calculate the health fitness of each fixed asset, and the parent population is sorted from high to low according to the fitness; Update each individual in the parent population and generate a new offspring population through crossover and mutation operations; Compare the fitness of the offspring and the parent. If the offspring is in a healthier state than the parent, replace the parent with the offspring; otherwise, adjust the parameters of the trend analysis algorithm. Determine whether the maximum number of iterations has been reached. If so, output the optimal health fitness; if not, continue to update each individual in the parent population; The optimal health fitness is used as the penalty parameter and kernel function parameter of the support vector regression machine to build a trend prediction model, and based on the trend prediction model, the changing trend of the health status of fixed assets is obtained; Optimize asset maintenance plans and operation strategies based on change trends and real-time operating status.

8. The method for dynamic management of fixed assets based on RFID tags according to claim 7, characterized in that: The optimal health fitness is used as the penalty parameter and kernel function parameter of the support vector regression machine to construct a trend prediction model, and based on the trend prediction model, the change trend of the health status of fixed assets is obtained, including: The optimal fitness value based on the health status of fixed assets is used as the penalty parameter and kernel function parameter of the support vector regression machine; The optimal health fitness parameters are used to construct a support vector regression model to fit the changing relationship between the health status of fixed assets and key influencing factors, forming a trend prediction model; Real-time data is input into the trend prediction model, and the trend prediction model is used to predict the changing trend of the health status of fixed assets at future moments.

9. A dynamic management system for fixed assets based on RFID tags, characterized in that: include: The data acquisition module is used to acquire the enterprise fixed asset data using the wireless radio frequency identification technology and to obtain the fixed asset characteristic data; The factor analysis module is used to evaluate the fixed asset characteristic data based on the extracted fixed asset characteristic data using the status analysis algorithm to identify the key factors affecting the health status of the fixed assets; The trend analysis and management module is used to analyze the key factors affecting the health status of fixed assets based on the trend analysis algorithm and obtain the changing trend of the health status of fixed assets; And combine the change trends and real-time operating status of fixed assets to optimize asset maintenance plans and operating strategies.

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