Intelligent file cabinet file query method based on RFID technology

Abstract

The invention discloses an intelligent file cabinet file query method based on the RFID technology, and relates to the technical field of intelligent file management.The internal space of a file cabinet is divided into small grid units through virtual grid modeling, each grid has a clear number, preliminary positioning of each RFID tag is achieved, and the file query efficiency is improved. According to the method, the file is not limited to an approximate area any more and is accurate to a specific grid, multi-antenna cooperative reading is combined with multiple reading and analysis of signal intensity and phase angles, the positioning accuracy is further improved, errors can be corrected according to signal differences and phase angles through a maximum likelihood estimation model, more accurate file position query is achieved, and the positioning accuracy is improved. According to the technical scheme, labels in a coverage area are read for multiple times in a multi-antenna cooperative reading mode, interference is reduced through signal calibration between the antennas, and errors caused by signal reflection, interference or overlapping are reduced by carrying out weighted average on signal strength and correcting differences between the antennas through a least square method.

Description

Technical Field

[0001] This invention relates to the field of intelligent archive management technology, and in particular to an intelligent archive cabinet archive retrieval method based on RFID technology. Background Technology

[0002] In file retrieval within filing cabinets, RFID (Radio Frequency Identification) technology effectively enhances the convenience and accuracy of file management. Through contactless identification, it automates the processes of file entry, borrowing, and return. RFID technology also enables rapid location and retrieval of specific files, significantly reducing search time. RFID technology provides a novel digital solution for file management, promoting its intelligentization.

[0003] In large-capacity, high-density filing cabinets, although RFID tags can identify whether a file exists, it is difficult to determine the file's exact location within the cabinet. Due to the large number of RFID tags in the filing cabinet, signal interference between tags and reflection of RFID signals by the cabinet body make it difficult for the reader to accurately and quickly capture all tag information.

[0004] To improve positioning accuracy, some existing solutions add RFID antennas or densely arrange tags in the filing cabinet to increase reading coverage and signal strength. However, excessively dense tags can cause signal collisions, which reduces reading efficiency. Some RFID systems use a single antenna to scan sequentially, reading tags in different areas multiple times to find the location of the file. However, the reading range is limited each time, and scanning the entire filing cabinet still takes a lot of time. Therefore, there is an urgent need for an intelligent filing cabinet file query method based on RFID technology to solve these problems. Summary of the Invention

[0005] In view of the aforementioned existing problems, the present invention is proposed.

[0006] Therefore, this invention provides a smart filing cabinet file query method based on RFID technology to solve the problems of inaccurate positioning, dense tag layout and the reflective effect of metal filing cabinets causing serious signal interference, and multiple reading methods requiring a lot of time to scan the entire filing cabinet.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0008] This invention provides a method for retrieving files from an intelligent filing cabinet based on RFID technology, including:

[0009] Step S1, grid modeling and partition layout: The interior of the filing cabinet is modeled as a virtual grid, dividing the cabinet space into multiple small virtual grids. Each grid represents an independent storage unit. The virtual grid modeling assigns a spatial location to each file, and the file corresponding to each RFID tag is assigned to a virtual grid, thus establishing a preliminary grid storage structure.

[0010] The virtual mesh modeling method is as follows:

[0011] Let the length, width, and height of the internal three-dimensional space of the filing cabinet be L, W, and H, respectively. Divide the entire cabinet space into N. x N y and N z Each grid cell is partitioned along the x, y, and z axes:

[0012] Where L represents the length of the filing cabinet along the x-axis, W represents the width of the filing cabinet along the y-axis, H represents the height of the filing cabinet along the z-axis, and N... x N represents the number of grid cells along the x-axis. y N represents the number of grid cells along the y-axis. z The z-axis represents the number of grid cells, and Δx, Δy, and Δz represent the lengths in the x, y, and z directions, respectively.

[0013] Each grid cell is represented by three-dimensional coordinates (i, j, k), where i, j, and k represent the position number of the grid cell along the x-axis, y-axis, and y-axis, respectively, with the following ranges:

[0014] i = 1, 2, ..., N x j = 1, 2, ..., N y k = 1, 2, ..., N z Each grid cell is uniquely identified by its number within the entire cabinet space;

[0015] The three-dimensional coordinates of the center point of each grid cell are defined as follows:

[0016] (x i y j , z k )=((i-0.5)·Δx, (j-0.5)·Δy, (k-0.5)·Δz), where, x i Represents the coordinates of the center point of the i-th grid along the x-axis, y j Z represents the coordinates of the center point of the j-th grid along the y-axis. k This represents the coordinates of the center point of the k-th grid along the z-axis, where Δx, Δy, and Δz are the lengths of each grid cell in the x, y, and z directions, respectively.

[0017] The total number of grids N in the cabinet space total For: N total =N x ×N y ×N z , where N total N represents the total number of grid cells inside the cabinet. x N y N z This indicates the number of grid cells in the x, y, and z directions;

[0018] Step S2, multi-antenna collaborative reading: Based on the virtual grid division structure in step S1, multiple antennas are deployed, each antenna is responsible for covering multiple grid areas within its effective range. Through multiple readings from multiple antennas and signal strength integration, errors caused by signal interference or overlapping areas are reduced.

[0019] The multi-antenna collaborative reading method is as follows:

[0020] Suppose there are M antennas inside the filing cabinet, and the positions of the antennas are A. m =(x m y m , z m ), where m = 1, 2, ..., M represents the antenna number, and each antenna is responsible for covering a certain area;

[0021] The signal strength S received by each antenna m From multiple tags inside the cabinet, when antenna m reads the nth RFID tag, the received signal strength S m，n Represented as: Among them, P t G represents the antenna transmit power. m G represents the gain of antenna m. n Let λ represent the gain of label n, and λ represent the wavelength of the signal. Where c is the speed of light, f is the signal frequency, and d m，n This represents the distance from antenna m to tag n, where d is the distance from antenna m to tag n. m，n This represents the geometric distance between antenna m and tag n, i.e.: Where, x tag，n y tag，n , z tag，n Let x be the three-dimensional coordinate position of label n. m y m , z m Let m be the three-dimensional coordinate position of antenna m;

[0022] Each antenna m reads the signal from tag n multiple times. Assuming each antenna performs K reads, let the signal read by antenna m on the k-th read be... The average value of the signal obtained from multiple readings is used as the initial reading result:

[0023] in, This represents the average signal strength of antenna m to tag n. This represents the reading signal of antenna m on tag n during the k-th acquisition, where K represents the number of reads by each antenna;

[0024] Multiple antennas read the same tag n, and the signal strength is used to perform a weighted average and integrated analysis.

[0025] Among them, S n w represents the integrated signal strength of tag n. m This represents the weight of antenna m;

[0026] The least squares method is used to correct the differences between antennas, minimizing the difference between the readouts of each antenna and the integrated signal S. n The difference between them, based on the integrated signal strength S n Based on the relative position of each antenna, a triangulation algorithm is used to initially estimate the position of tag n in three-dimensional space;

[0027] Step S3, Signal strength and phase angle analysis: Based on step S2, the signal strength and phase angle data of the preliminary reading results collected by each antenna are used to perform multi-antenna phase difference calibration. The position of the tag is finely corrected based on the preliminary estimation. The specific position of the tag is obtained through the joint analysis of signal strength and phase angle. Based on the cross analysis of signal strength and phase angle, the specific area and relative position of the tag in the grid are located.

[0028] The initial readings, i.e., the preliminary estimated positions, are then calibrated.

[0029] Let the phase of the signal received by each antenna m be φ. m，n :

[0030] Where, φ m，n λ represents the phase of the signal received by antenna m from tag n, and λ represents the signal wavelength. d m，n φ0 represents the distance between antenna m and tag n, and φ0 represents the initial phase of the signal;

[0031] Suppose that two antennas, m1 and m2, receive signals from the same tag, and their phase difference is... for:

[0032] This phase difference is used to correct the distance estimation between the two antennas to the tag's location, and a phase difference matrix Φ is constructed.

[0033] A joint probability model is constructed using maximum likelihood estimation:

[0034] in, S represents the specific location of label n obtained by maximum likelihood estimation. m，n σ represents the signal strength received by antenna m from tag n. 2 φ represents the variance of signal strength. m，n This indicates the phase of the signal received by antenna m from tag n. This represents the phase calculated theoretically. The variance of the phase measurement noise is represented.

[0035] Step S4, signal reflection optimization: absorbing material is placed in the internal grid area of ​​the filing cabinet to reduce signal reflection and interference, and improve signal quality and reading stability;

[0036] Step S5, Location Marking and Path Prompt: Based on the specific location of each RFID tag in the grid obtained in Step S3, the location is automatically marked on the electronic map of the virtual grid structure, and an electronic distribution map of the files in the filing cabinet is generated; the electronic map displays the exact location of each file and provides quick path prompts, and combined with the data update of signal reading, dynamically reflects the real-time distribution of the files in the filing cabinet;

[0037] The method for generating electron distribution maps is as follows:

[0038] The three-dimensional position of each RFID tag n is obtained based on step S3. Convert it to a grid number in the virtual grid (i grid j grid k grid ):

[0039] Where, x n y n , z n This represents the actual three-dimensional position of the RFID tag n, where Δx, Δy, and Δz represent the grid step size in the x, y, and z directions, respectively, i.e., the length of each grid cell. grid j grid k grid This indicates the coordinate number of label n in the virtual mesh structure.

[0040] Get the position i of the label grid j grid k grid Then, it is marked on the electronic map, and the virtual grid structure is defined as a three-dimensional array M[i, j, k], where each element represents a grid cell:

[0041] M[i grid j gridk grid ] = n, where the grid cell M[i grid j grid k grid ] is marked as containing label n, M[i grid j grid k grid ] represents the grid (i grid j grid k grid The storage status in ) , where n represents the RFID tag number;

[0042] The state M[i, j, k] of each grid cell is processed into two dimensions to display the cross-section of the cabinet with height z, i.e., k = k z ,but:

[0043] M 2D [i, j] = M[i, j, k] z At a fixed height k z In this case, the label number n, M of each grid unit inside the cabinet. 2D It is a two-dimensional representation of the electronic map, showing the labels stored in each grid at that altitude;

[0044] Assume the position of the cabinet door is (i door j door k door The target output is the label n in (i grid j grid k grid If the path is: Where, d path Indicates the distance from the cabinet door to the label, i door j door k door Indicates the position number of the cabinet door in the virtual grid, i grid j grid k grid Indicates the grid position of the target label.

[0045] Preferably, in step S2, a multi-antenna collaborative reading method is adopted to collect data from the RFID tag multiple times. Each antenna reads the tag in its coverage area multiple times and integrates the reading data with the reading data of other antennas. The data between the antennas are calibrated in real time to obtain the preliminary reading result.

[0046] Preferably, in step S2, it is assumed that the distance between the antennas is known, and the time difference Δt is used. m，n Estimate the initial position r of the label n :

[0047] Where, r nA represents the initial estimated position of label n. m The coordinates of antenna m represent the position of the antenna, v represents the signal propagation speed, and Δt represents the signal propagation speed. m，n This represents the time difference between the signal traveling from tag n to antenna m.

[0048] Preferably, in step S5, when the file is moved, the electronic map is dynamically updated, and the grid number of the tag is updated to the new grid cell based on the new location of the RFID tag.

[0049] M[i new j new k new ] = n, and at the same time mark the grid in the original position as unoccupied:

[0050] M[i old j old k old ] = 0;

[0051] Step S5: From the label coordinates (x...) n ,y n ,z n Starting with ), mapping to virtual mesh coordinates (i grid ,j grid ,k grid It generates an electronic map, outputs the optimal path by calculating the shortest distance from the cabinet door to the target label, and maintains the real-time status of the map by dynamically updating the label position.

[0052] The beneficial effects of this invention are:

[0053] This invention uses virtual grid modeling to divide the internal space of a filing cabinet into small grid units, each with a specific number, enabling preliminary positioning of each RFID tag. This allows files to be located precisely within a specific grid rather than in a general area. Furthermore, multi-antenna collaborative reading, combined with multiple readings and analyses of signal strength and phase angle, further improves positioning accuracy. The maximum likelihood estimation model can correct errors based on signal differences and phase angle, thus achieving more precise file location queries.

[0054] This invention uses a multi-antenna collaborative reading method to read tags within the coverage area multiple times, reduces interference through signal calibration between antennas, and corrects differences between antennas by weighted averaging of signal strength and using the least squares method. This reduces errors caused by signal reflection, interference, or overlap. For high-density RFID tags, it can significantly reduce collision problems and improve data acquisition efficiency.

[0055] This invention involves arranging wave-absorbing materials inside the filing cabinet to effectively reduce multipath interference caused by signal reflection.

[0056] This invention, through the coordinated operation of multiple antennas and real-time calibration between antennas, efficiently covers all grid areas. Compared with traditional RFID systems that collect signals multiple times and perform averaging, it reduces the randomness and error of a single read. Attached Figure Description

[0057] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0058] Figure 1 This is a schematic diagram of the intelligent filing cabinet file retrieval method of the present invention. Detailed Implementation

[0059] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0060] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0061] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0062] Example 1, referring to Figure 1 This embodiment provides a method for retrieving files in an intelligent filing cabinet based on RFID technology, including the following steps:

[0063] Step S1, Mesh modeling and partition layout,

[0064] The interior of the filing cabinet is modeled as a virtual grid, dividing the cabinet space into multiple small virtual grids, each grid representing an independent storage unit; in step S1, the files corresponding to each RFID tag are assigned to the virtual grid, establishing a preliminary gridded storage structure.

[0065] In step S1, the virtual mesh modeling method is as follows:

[0066] Let the length, width, and height of the internal three-dimensional space of the filing cabinet be L, W, and H, respectively. Divide the entire cabinet space into N. x N y and N z Each grid cell is partitioned along the x, y, and z axes:

[0067] Where L represents the length of the filing cabinet along the x-axis, W represents the width of the filing cabinet along the y-axis, H represents the height of the filing cabinet along the z-axis, and N... x N represents the number of grid cells along the x-axis. y N represents the number of grid cells along the y-axis. z The z-axis represents the number of grid cells, and Δx, Δy, and Δz represent the lengths in the x, y, and z directions, respectively.

[0068] Each grid cell is represented by three-dimensional coordinates (i, j, k), where i, j, and k represent the position number of the grid cell along the x-axis, y-axis, and y-axis, respectively, with the following ranges:

[0069] i = 1, 2, ..., N x j = 1, 2, ..., N y k = 1, 2, ..., N z Each grid cell is uniquely identified by its number within the entire cabinet space;

[0070] In step S1, the virtual mesh modeling method also includes:

[0071] The three-dimensional coordinates of the center point of each grid cell are defined as follows:

[0072] (x i ,y j ,z k )=((i-0.5)·Δx, (j-0.5)·Δy, (k-0.5)·Δz), where, x i Represents the coordinates of the center point of the i-th grid along the x-axis, y j Z represents the coordinates of the center point of the j-th grid along the y-axis. k This represents the coordinates of the center point of the k-th grid along the z-axis, where Δx, Δy, and Δz are the lengths of each grid cell in the x, y, and z directions, respectively.

[0073] The total number of grids N in the cabinet space total For: N total =N x ×N y ×N z , where N total N represents the total number of grid cells inside the cabinet. x N y Nz This indicates the number of grid cells in the x, y, and z directions;

[0074] Specifically, the three-dimensional space inside the filing cabinet is divided into grids, with each grid representing an independent storage unit. The grid structure greatly enhances the system's storage management capabilities and enables the initial positioning of RFID tags. Compared with traditional fuzzy storage and tag query methods, virtual grid modeling can accurately assign a spatial location to each file, greatly reducing the fuzziness and errors in file positioning.

[0075] Step S2, multi-antenna collaborative reading,

[0076] Based on the virtual grid division structure in step S1, multiple antennas are arranged, each antenna is responsible for covering multiple grid areas within its effective range, thereby reducing errors caused by signal interference or overlapping areas.

[0077] In step S2, a multi-antenna collaborative reading method is adopted to collect data from the RFID tag multiple times. Each antenna reads the tag in its coverage area multiple times and integrates the reading data with the reading data of other antennas. The data between the antennas are calibrated in real time to obtain the preliminary reading results.

[0078] The multi-antenna collaborative reading method in step S2 is as follows:

[0079] Suppose there are M antennas inside the filing cabinet, and the positions of the antennas are A. m =(x m ,y m ,z m ), where m = 1, 2, ..., M represents the antenna number, and each antenna is responsible for covering a certain area;

[0080] The signal strength S received by each antenna m From multiple tags inside the cabinet, when antenna m reads the nth RFID tag, the received signal strength S m，n Represented as: Among them, P t G represents the antenna transmit power. m G represents the gain of antenna m. n Let λ represent the gain of label n, and λ represent the wavelength of the signal. Where c is the speed of light, f is the signal frequency, and d m，n This represents the distance from antenna m to tag n, where d is the distance from antenna m to tag n. m，n This represents the geometric distance between antenna m and tag n, i.e.: Where, x tag，n y tag，n , z tag，n Let x be the three-dimensional coordinate position of label n. m ym , z m Let m be the three-dimensional coordinate position of antenna m;

[0081] Each antenna m reads the signal from tag n multiple times. Assuming each antenna performs K reads, let the signal read by antenna m on the k-th read be... The average value of the signal obtained from multiple readings is used as the initial reading result:

[0082] in, This represents the average signal strength of antenna m to tag n. This represents the reading signal of antenna m on tag n during the k-th acquisition, where K represents the number of reads by each antenna;

[0083] The multi-antenna collaborative reading method in step S2 also includes:

[0084] When multiple antennas read the same tag n, the signal strength obtained will vary spatially. By using the data acquired collaboratively by multiple antennas, a weighted average of the signal strength can be performed and integrated.

[0085] Among them, S n w represents the integrated signal strength of tag n. m This represents the weight of antenna m;

[0086] The least squares method is used to correct the differences between antennas, minimizing the difference between the readouts of each antenna and the integrated signal S. n The differences between them;

[0087] Based on the integrated signal strength S n Based on the relative positions of each antenna, a triangulation algorithm is used to initially estimate the position of tag n in three-dimensional space. Assuming the distance between antennas is known, the time difference Δt is used. m，n Estimate the initial position r of the label n :

[0088] Where, r n A represents the initial estimated position of label n. m The coordinates of antenna m represent the position of the antenna, v represents the signal propagation speed, and Δt represents the signal propagation speed. m，n This represents the time difference between the signal traveling from tag n to antenna m;

[0089] Specifically, multi-antenna collaborative reading technology effectively solves the problems of signal interference and multi-tag reading conflicts. By reading multiple times from multiple antennas and integrating signal strength, it improves the accuracy of reading signals and remains effective in high-density tag areas. Compared with traditional single-antenna reading methods, it significantly reduces errors caused by signal blind spots or reflections, achieving more efficient and accurate tag reading results.

[0090] Based on this, by combining signal strength and phase angle analysis, the positioning accuracy of the tag is further improved. The phase information of the signal received by the antenna is used to perform phase difference calibration. The position of the tag is finely corrected based on the preliminary estimate. Through the joint analysis of signal strength and phase angle, the accuracy of the tag position is greatly improved. Optimization is carried out for scenarios with high environmental noise or severe signal reflection, significantly reducing positioning errors.

[0091] Step S3, Signal strength and phase angle analysis,

[0092] Based on step S2, the signal strength and phase angle data of the preliminary reading results collected by each antenna are used to perform multi-antenna phase difference calibration to obtain the specific location of the tag. Based on the cross-analysis of signal strength and phase angle, the specific area and relative position of the tag in the grid are located more accurately.

[0093] In step 3, the preliminary reading results, i.e., the preliminary estimated position, are calibrated:

[0094] Let the phase of the signal received by each antenna m be φ. m，n :

[0095] Where, φ m，n λ represents the phase of the signal received by antenna m from tag n, and λ represents the signal wavelength. d m，n φ0 represents the distance between antenna m and tag n, and φ0 represents the initial phase of the signal;

[0096] Suppose that two antennas, m1 and m2, receive signals from the same tag, and their phase difference is... for:

[0097] This phase difference is used to correct the distance estimation between the two antennas to the tag's location, and a phase difference matrix Φ is constructed.

[0098] A joint probability model is constructed using maximum likelihood estimation:

[0099] in, S represents the specific location of label n obtained by maximum likelihood estimation. m，n σ represents the signal strength received by antenna m from tag n. 2 φ represents the variance of signal strength. m，n This indicates the phase of the signal received by antenna m from tag n. This represents the phase calculated theoretically. The variance of the phase measurement noise is represented.

[0100] Step S3, based on the preliminary estimation results of step S2, uses the phase angle information and signal strength of the signal to correct and optimize the position of the tag.

[0101] Step S4, signal reflection optimization,

[0102] In high-density metal environments, RFID signals are easily reflected and interfered with. To address this issue, absorbing materials are placed in the internal grid area of ​​the filing cabinet to reduce signal reflection and interference, and improve signal quality and reading stability.

[0103] Step S5, Location Marking and Path Hints,

[0104] Based on the specific location of each RFID tag in the grid obtained in step S3, the location is automatically marked on the electronic map of the virtual grid structure, and an electronic distribution map of the files in the filing cabinet is generated. The electronic map shows the exact location of each file and provides quick path prompts. Combined with the data update of signal reading, it dynamically reflects the real-time distribution of the files in the filing cabinet.

[0105] Step S5 generates an electronic distribution map based on the RFID tag locations obtained in step S3, in the following manner:

[0106] The three-dimensional position of each RFID tag n is obtained based on step S3. Convert it to a grid number in the virtual grid (i grid j grid k grid ):

[0107] Where, x n y n , z n This represents the actual three-dimensional position of the RFID tag n, where Δx, Δy, and Δz represent the grid step size in the x, y, and z directions, respectively, i.e., the length of each grid cell. grid j grid k grid This indicates the coordinate number of label n in the virtual mesh structure.

[0108] Get the position i of the label grid ,j grid ,k grid Then, it is marked on the electronic map, and the virtual grid structure is defined as a three-dimensional array M[i,j,k], where each element represents a grid cell:

[0109] M[i grid ,j grid ,k grid ] = n, where the grid cell M[i grid ,j grid,k grid ] is marked as containing label n, M[i grid ,j grid ,k grid ] represents the grid (i grid ,j grid ,k grid The storage status in ) , where n represents the RFID tag number;

[0110] In step S5, the method for generating the electron distribution map also includes:

[0111] The state M[i,j,k] of each grid cell is processed into two dimensions to display the cross-section of the cabinet with height z, i.e., k = k z ,but:

[0112] M 2D [i,j]=M[i,j,k z At a fixed height k z In this case, the label number n, M of each grid unit inside the cabinet. 2D It is a two-dimensional representation of the electronic map, showing the labels stored in each grid at that altitude;

[0113] Assume the position of the cabinet door is (i door j door k door The target output is the label n in (i grid j grid k grid If the path is: Where, d path Indicates the distance from the cabinet door to the label, i door j door k door Indicates the position number of the cabinet door in the virtual grid, i grid j grid k grid Indicates the grid position of the target label;

[0114] In the electronic map of step S5:

[0115] When the files are moved, the electronic map is dynamically updated, and the grid number of the tag is updated to the new grid cell based on the new location of the RFID tag.

[0116] M[i new ,j new ,k new ] = n, and at the same time mark the grid in the original position as unoccupied:

[0117] M[i old ,j old ,k old] = 0;

[0118] Step S5: From the label coordinates (x...) n ,y n ,z n Starting with ), mapping to virtual mesh coordinates (i grid ,j grid ,k grid It generates an electronic map, calculates the shortest distance from the cabinet door to the target label, outputs the optimal path, and dynamically updates the label position to keep the map real-time.

[0119] Specifically, the electronic map provides users with an intuitive way to locate and search for archives. Using the precise location obtained in step S3, the tag location is automatically marked on the electronic map with a virtual grid structure, and the real-time distribution of archives in the cabinet is dynamically displayed, greatly improving the efficiency of users searching for archives.

[0120] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for retrieving files in an intelligent filing cabinet based on RFID technology, characterized in that: include, Step S1, grid modeling and partition layout: The interior of the filing cabinet is modeled as a virtual grid, dividing the cabinet space into multiple small virtual grids. Each grid represents an independent storage unit. The virtual grid modeling assigns a spatial location to each file, and the file corresponding to each RFID tag is assigned to a virtual grid, thus establishing a preliminary grid storage structure. The virtual mesh modeling method is as follows: Let the length, width, and height of the internal three-dimensional space of the filing cabinet be L, W, and H, respectively. Divide the entire cabinet space into N. x N y and N z Each grid cell is partitioned along the x, y, and z axes: Where L represents the length of the filing cabinet along the x-axis, W represents the width of the filing cabinet along the y-axis, H represents the height of the filing cabinet along the z-axis, and N... x N represents the number of grid cells along the x-axis. y N represents the number of grid cells along the y-axis. z The z-axis represents the number of grid cells, and Δx, Δy, and Δz represent the lengths in the x, y, and z directions, respectively. Each grid cell is represented by three-dimensional coordinates (i, j, k), where i, j, and k represent the position number of the grid cell along the x-axis, y-axis, and y-axis, respectively, with the following ranges: i = 1, 2, ..., N x j = 1, 2, ..., N y k = 1, 2, ..., N z Each grid cell is uniquely identified by its number within the entire cabinet space; The three-dimensional coordinates of the center point of each grid cell are defined as follows: (x i y j , z k )=((i-0.5)·Δx, (j-0.5)·Δy, (k-0.5)·Δz), where, x i Represents the coordinates of the center point of the i-th grid along the x-axis, y j Z represents the coordinates of the center point of the j-th grid along the y-axis. k This represents the coordinates of the center point of the k-th grid along the z-axis, where Δx, Δy, and Δz are the lengths of each grid cell in the x, y, and z directions, respectively. The total number of grids N in the cabinet space total For: N total =N x ×N y ×N z , where N total N represents the total number of grid cells inside the cabinet. x N y N z This indicates the number of grid cells in the x, y, and z directions; Step S2, multi-antenna collaborative reading: Based on the virtual grid division structure in step S1, multiple antennas are deployed, each antenna is responsible for covering multiple grid areas within its effective range. Through multiple readings from multiple antennas and signal strength integration, errors caused by signal interference or overlapping areas are reduced. The multi-antenna collaborative reading method is as follows: Suppose there are M antennas inside the filing cabinet, and the positions of the antennas are A. m =(x m y m , z m ), where m = 1, 2, ..., M represents the antenna number, and each antenna is responsible for covering a certain area; The signal strength S received by each antenna m From multiple tags inside the cabinet, when antenna m reads the nth RFID tag, the received signal strength S m，n Represented as: Among them, P t G represents the antenna transmit power. m G represents the gain of antenna m. n Let λ represent the gain of label n, and λ represent the wavelength of the signal. Where c is the speed of light, f is the signal frequency, and d m，n This represents the distance from antenna m to tag n, where d is the distance from antenna m to tag n. m，n This represents the geometric distance between antenna m and tag n, i.e.: Where, x tag，n y tag，n , z tag，n Let x be the three-dimensional coordinate position of label n. m y m , z m Let m be the three-dimensional coordinate position of antenna m; Each antenna m reads the signal from tag n multiple times. Assuming each antenna performs K reads, let the signal read by antenna m on the k-th read be... The average value of the signal obtained from multiple readings is used as the initial reading result: in, This represents the average signal strength of antenna m to tag n. This represents the reading signal of antenna m on tag n during the k-th acquisition, where K represents the number of reads by each antenna; Multiple antennas read the same tag n, and the signal strength is used to perform a weighted average and integrated analysis. Among them, S n w represents the integrated signal strength of tag n. m This represents the weight of antenna m; The least squares method is used to correct the differences between antennas, minimizing the difference between the readouts of each antenna and the integrated signal S. n The difference between them, based on the integrated signal strength S n Based on the relative position of each antenna, a triangulation algorithm is used to initially estimate the position of tag n in three-dimensional space; Step S3, Signal strength and phase angle analysis: Based on step S2, the signal strength and phase angle data of the preliminary reading results collected by each antenna are used to perform multi-antenna phase difference calibration. The position of the tag is finely corrected based on the preliminary estimation. The specific position of the tag is obtained through the joint analysis of signal strength and phase angle. Based on the cross analysis of signal strength and phase angle, the specific area and relative position of the tag in the grid are located. The initial readings, i.e., the preliminary estimated positions, are then calibrated. Let the phase of the signal received by each antenna m be φ. m，n : Where, φ m，n λ represents the phase of the signal received by antenna m from tag n, and λ represents the signal wavelength. d m，n φ0 represents the distance between antenna m and tag n, and φ0 represents the initial phase of the signal; Suppose that two antennas, m1 and m2, receive signals from the same tag, and their phase difference is... for: This phase difference is used to correct the distance estimation between the two antennas to the tag's location, and a phase difference matrix Φ is constructed. A joint probability model is constructed using maximum likelihood estimation: in, S represents the specific location of label n obtained by maximum likelihood estimation. m，n σ represents the signal strength received by antenna m from tag n. 2 φ represents the variance of signal strength. m，n This indicates the phase of the signal received by antenna m from tag n. This represents the phase calculated theoretically. The variance of the phase measurement noise is represented. Step S4, signal reflection optimization: absorbing material is placed in the internal grid area of ​​the filing cabinet to reduce signal reflection and interference, and improve signal quality and reading stability; Step S5, Location Marking and Path Prompt: Based on the specific location of each RFID tag in the grid obtained in Step S3, the location is automatically marked on the electronic map of the virtual grid structure, and an electronic distribution map of the files in the filing cabinet is generated; the electronic map displays the exact location of each file and provides quick path prompts, and combined with the data update of signal reading, dynamically reflects the real-time distribution of the files in the filing cabinet; The method for generating electron distribution maps is as follows: The three-dimensional position of each RFID tag n is obtained based on step S3. Convert it to a grid number in the virtual grid (i grid j grid k grid ): Where, x n y n , z n This represents the actual three-dimensional position of the RFID tag n, where Δx, Δy, and Δz represent the grid step size in the x, y, and z directions, respectively, i.e., the length of each grid cell. grid j grid k grid This indicates the coordinate number of label n in the virtual mesh structure. Get the position i of the label grid j grid k grid Then, it is marked on the electronic map, and the virtual grid structure is defined as a three-dimensional array M[i, j, k], where each element represents a grid cell: M[i grid j grid k grid ] = n, where the grid cell M[i grid j grid k grid ] is marked as containing label n, M[i grid j grid k grid ] represents the grid (i grid j grid k grid The storage status in ) , where n represents the RFID tag number; The state M[i, j, k] of each grid cell is processed into two dimensions to display the cross-section of the cabinet with height z, i.e., k = k z ,but: M 2D [i, j] = M[i, j, k] z At a fixed height k z In this case, the label number n, M of each grid unit inside the cabinet. 2D It is a two-dimensional representation of the electronic map, showing the labels stored in each grid at that altitude; Assume the position of the cabinet door is (i door j door k door The target output is the label n in (i grid j grid k grid If the path is: Where, d path Indicates the distance from the cabinet door to the label, i door j door k door Indicates the position number of the cabinet door in the virtual grid, i grid j grid k grid Indicates the grid position of the target label.

2. The method for retrieving files in an intelligent filing cabinet based on RFID technology according to claim 1, characterized in that, In step S2, a multi-antenna collaborative reading method is adopted to collect data from the RFID tag multiple times. Each antenna reads the tag in its coverage area multiple times and integrates the reading data with the data from other antennas. The data between the antennas are calibrated in real time to obtain the preliminary reading results.

3. The method for retrieving files in an intelligent filing cabinet based on RFID technology according to claim 1, characterized in that, In step S2, assuming the distance between the antennas is known, the time difference Δt is used. m，n Estimate the initial position r of the label n : Where, r n A represents the initial estimated position of label n. m The coordinates of antenna m represent the position of the antenna, v represents the signal propagation speed, and Δt represents the signal propagation speed. m，n This represents the time difference between the signal traveling from tag n to antenna m.

4. The method for retrieving files in an intelligent filing cabinet based on RFID technology according to claim 1, characterized in that, In step S5, when the file is moved, the electronic map is dynamically updated. Based on the new location of the RFID tag, the tag's grid number is updated to the new grid cell. M[i new j new k new ] = n, and at the same time mark the grid in the original position as unoccupied: M[i old ,j old ,k old ]=0。

Images