Fabric location positioning method and fabric warehouse management system

Abstract

The present invention relates to warehouse management, and in particular to a fabric location positioning method and a fabric warehouse management system, comprising the following steps performed in sequence: S1: respectively obtaining RSSI values of RFID fabric tags of fabrics read by four RFID readers on a shelf, and converting each RSSI value into a distance using a path loss model; S2: assuming that the distance between the RFID fabric tag of the fabric and the RFID reader with the largest distance is #imgabs0#, and the distance between the RFID fabric tag and the RFID reader with the smallest distance is #imgabs1#, if the ratio of #imgabs2# to #imgabs3# is less than or equal to a preset critical value, then using a centroid triangle positioning method to locate the fabric; otherwise, using a segmentation range positioning method based on the centroid triangle positioning method to locate the fabric, optimizing parameters of the segmentation range positioning method using a PSO algorithm, and outputting the positioning coordinates of the fabric; the present application uses the centroid triangle positioning method or the segmentation range positioning method based on the centroid positioning method to obtain the fabric position, thereby improving the positioning accuracy of the segmentation range positioning method.

Description

Technical Field

[0001] The present invention relates to warehouse management, and in particular to a fabric location positioning method and a fabric warehouse management system. Background Art

[0002] As modern warehouse management evolves toward intelligent and automated processes, efficient management and precise location of goods in warehouses have become key industry priorities. In the textile industry, fabric storage management is particularly crucial. Because fabrics are typically rolled, bulky, and require complex storage methods, traditional warehouse management models struggle to meet these requirements.

[0003] Furthermore, fabrics often involve multiple pieces being stored during the inbound and outbound processes, each difficult to distinguish by color and shape. Traditional methods of manually recording or systematically selecting storage locations have limitations. During the fabric inbound and outbound transfer process, workers frequently make handling errors, disrupting subsequent processing and outbound processes. Therefore, there is an urgent need for an efficient fabric storage management method that automatically updates the storage location of fabrics after they are put on the shelves, improving both accuracy and efficiency.

[0004] Currently, warehouse management primarily relies on barcodes, RFID (radio frequency identification), and positioning technologies based on wireless signals. Traditional RFID applications still present numerous challenges. For example, in complex warehouse environments, RFID signals are susceptible to interference from obstacles and multipath effects, leading to signal attenuation and misreading. Furthermore, existing warehouse positioning systems typically deploy positioning base stations around the warehouse and calculate the location of goods based on the distance between the tag and multiple base stations. While this approach is suitable for tracking goods over a large area, it increases computational complexity and reduces system response speed. In the specific application scenario of fabric storage, the core requirement of warehouse management is to determine the shelf on which the fabric is located and its specific location within the shelf. Traditional positioning algorithms often suffer from redundant calculations for such requirements. Summary of the Invention

[0005] The object of the present invention is to provide a fabric positioning method and a fabric storage management system capable of improving positioning accuracy.

[0006] In order to achieve the above object, the present invention adopts such technical solution:

[0007] A method for locating a fabric position comprises the following steps performed in sequence:

[0008] S1: Obtain the RSSI values of the RFID fabric tags of the fabrics read by four RFID readers located on the same plane on the shelf respectively, and convert each RSSI value into a distance using the path loss model;

[0009] S2: Assume that the distance between the fabric RFID tag and the RFID reader with the largest distance is , the distance between the RFID fabric tag and the RFID reader with the shortest distance is ,like and If the ratio is less than or equal to the preset critical value, the centroid triangle positioning method is used to locate the fabric. Otherwise, the segmentation range positioning method based on the centroid triangle positioning method is used to locate the fabric. The parameters of the segmentation range positioning method are optimized by the PSO algorithm, and the positioning coordinates of the fabric are output.

[0010] Preferably, the path loss model in step S1 uses the following formula to convert the RSSI value into distance :

[0011] ;

[0012] in, is the transmitting power of the RFID reader, indicating the signal strength received at 1 meter. is the path loss exponent, It is the distance between the RFID reader and the RFID fabric tag.

[0013] Preferably, the specific positioning steps of the centroid triangle positioning method in step S2 are as follows:

[0014] Sort the distances between the RFID fabric tag and four RFID readers on the same plane from small to large. Select the coordinates of the first three RFID readers as the center of a circle. Draw a circle with the distance between the RFID reader and the RFID fabric tag as the radius. The intersection of the three circles is the positioning range of the RFID fabric tag.

[0015] Connect the three vertices of the positioning range in sequence to form a triangle, and calculate the coordinates of the center of mass A of the triangle:

[0016] ;

[0017] in, are the coordinates of the three points of the triangle, .

[0018] Preferably, the specific steps of locating the fabric using the segmentation range positioning method based on the centroid triangle positioning method in step S2 are as follows:

[0019] The center of mass A is calculated using the triangle positioning method;

[0020] Calculate the foot of the perpendicular line from the center of mass A to any two vertices of the positioning range:

[0021] , ;

[0022] ;

[0023] ;

[0024] in, 、 Position two of the three vertices of the RFID fabric tag's range. for 、 The slope of the line connecting two points, are the coordinates of the center of mass A, is the center of mass A and 、 Two points form the foot of a perpendicular line;

[0025] Calculate the direction vector of movement and normalize it:

[0026] ;

[0027] ;

[0028] in, is the moving direction vector, is the magnitude of the direction vector, Normalize the direction vector to get the unit vector, that is, the final movement vector;

[0029] The private mobile ratio is generated using the following formula:

[0030] ;

[0031] ;

[0032] in, Indicates RFID fabric tag to The distance between the RFID readers, Indicates RFID fabric tag to The distance between the RFID readers, The first Private mobile ratio, Indicates the The normalized private mobile ratio, Indicates the number of RFID readers;

[0033] After segmenting the positioning range, the signal coverage range of the RFID reader closest to the RFID fabric tag is selected as the sub-range. The common movement ratio is adjusted so that the area of the sub-range meets the preset conditions. The PSO algorithm is used to optimize the common movement ratio. The specific optimization steps are as follows:

[0034] According to the current position of each particle, the following formula is used to determine the position of the current segmentation point:

[0035] ;

[0036] The line connecting the current segmentation point and the three vertices within the positioning range is used as the segmentation line, and the area of each sub-range is calculated using the following formula:

[0037] ;

[0038] in, is the split point To The distance between the edges, For the The length of the edge, To split point The sector area with as the vertex and the arc edge as the bottom line;

[0039] Establish the optimal fitness function for the target sub-range:

[0040] ;

[0041] in, Represents the fitness value in the PSO algorithm, Representative The position of the particles, For the largest private mobile ratio, To split point The sector area with the vertex as the center and the arc edge with the smallest radius as the bottom line, the larger the private proportional coefficient, the more it needs to move to achieve the smaller fitness value;

[0042] Initialize the population: Initialize individual particles based on the processed data. Each particle represents a common movement ratio. Each particle moves in a one-dimensional coordinate. The direction and speed of movement are affected by its own inertia, the individual optimal solution, and the global optimal solution.

[0043] Calculate the fitness function value: Calculate the fitness function value of each particle. The lower the fitness, the better the public movement ratio.

[0044] Update the population: Find the optimal public movement ratio through the movement of particles. Each particle calculates the fitness value through continuous movement, updates the individual optimal solution, and shares the optimal solution of each individual within the population. Individuals continue to refine the existing excellent positions, explore and update each position;

[0045] Iterative process: Repeat the steps of calculating the fitness function value and updating the population until the optimal common movement ratio is found or the preset number of iterations is reached. The population is updated according to the fitness value to ensure that the solution is continuously optimized and eventually converges to the optimal solution.

[0046] Output the optimal solution: Calculate the prediction results of the segmentation range positioning method: Output the optimal result of the PSO algorithm as the common moving ratio, and calculate the segmentation point coordinates based on the optimal common moving ratio:

[0047] ;

[0048] in, represents the optimal public mobility ratio, represents the coordinates of the split point, represents the coordinates of the center of mass A, Indicates the motion vectors The coordinates of Indicates the The proportion of private mobile

[0049] The connecting line between the optimized segmentation point and the three vertices in the positioning range is used as the segmentation line, and the center point of the sub-range with the largest area after segmentation is calculated as the prediction point B of the segmentation range point method.

[0050] A fabric storage management system, comprising a task list module, a warehousing module, a positioning display module, a fabric management module and a warehousing outgoing module;

[0051] The task list module is used to receive the fabric's warehousing information and generate an RFID fabric tag based on the warehousing information;

[0052] The warehousing module is used to receive the warehousing information obtained by scanning the RFID fabric tag by the PDA, and modify the warehousing status and shelf status of the fabric;

[0053] The positioning display module is used to locate the fabric position using the above fabric positioning method and display the positioning result;

[0054] The outbound module is used to receive the outbound information obtained by scanning the RFID fabric tag by the PDA, and to modify the fabric's storage status and shelf status.

[0055] Preferably, the warehousing information includes fabric code, fabric meter number, unique code, warehousing status and shelf status.

[0056] Preferably, the positioning display module is also used to determine whether the fabric is illegally removed from the shelf. If it is determined that the fabric is illegally removed from the shelf, the positioning display module sends a warning message to the RFID reader on the shelf where the fabric is located, and the corresponding RFID reader issues an alarm.

[0057] Preferably, the positioning display module determines whether the fabric is on the shelf in the following steps:

[0058] The following formula is used to calculate the area of each triangle formed by the RFID fabric tag and two adjacent RFID readers:

[0059] ;

[0060] ;

[0061] in, represents the distance between two RFID readers in the triangle, 、 Indicates the distance between the RFID fabric tag and two RFID readers. It represents the semi-perimeter of the triangle formed by the RFID fabric tag and two adjacent RFID readers. represents the area of a triangle;

[0062] Calculate the area of the rectangle with four RFID readers as vertices:

[0063] ;

[0064] in, Indicates the distance between RFID readers at the same level on the shelf, in meters. Indicates the distance between RFID readers at the same vertical height on the shelf, in meters. Indicates that the area of the rectangle enclosed by the four RFID readers is also the area of the shelf plane;

[0065] Compare the sum of the areas of the four triangles. If the difference between the sum of the areas and the area of the shelf plane is less than 10% of the area of the shelf plane, the fabric is considered to be on the shelf. Otherwise, it is considered that the fabric is not on the shelf or has been taken off the shelf.

[0066] By adopting the above-mentioned design scheme, the beneficial effects of the present invention are as follows: the present application determines whether the fabric is on the shelf by the distance relationship between the RFID fabric tag and the four RFID readers on the shelf, and selects the centroid triangle positioning method or the segmentation range positioning method based on the centroid positioning method to obtain the fabric position based on the distance relationship between the RFID fabric tag and the RFID reader, thereby reducing the situation where the centroid triangle positioning method has no solution when the distance difference between the RFID tag and each RFID reader is too large. The parameters in the segmentation range positioning method are optimized by the PSO algorithm, thereby improving the positioning accuracy of the segmentation range positioning method. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 This is a schematic diagram of the fabric positioning method of this application. DETAILED DESCRIPTION

[0068] To make the objectives, technical solutions, and advantages of the present invention more apparent, the present invention will be further described in detail below with reference to the accompanying drawings. It is apparent that the embodiments described are only some embodiments of the present invention, not all embodiments. All other embodiments obtained by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort are intended to fall within the scope of protection of the present invention.

[0069] The terms "first," "second," "third," and so on, in the description and claims of the present invention and the accompanying drawings are used to distinguish between different items, not to describe a specific order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to the process, method, product, or apparatus.

[0070] A fabric location positioning method is applied to fabric warehouse management. An RFID fabric tag is attached to one end of the fabric. Four RFID readers are located on the same plane at one end of a shelf for placing the fabric. The end of the fabric with the RFID fabric tag and the four RFID readers are located on the same plane, thereby reducing variables in the height direction and simplifying positioning calculations from three dimensions to two dimensions. The method includes the following steps, performed in sequence:

[0071] S1: Obtain the RSSI values of the RFID fabric tags of the fabrics read by four RFID readers located on the same plane on the shelf respectively, and convert each RSSI value into a distance using the path loss model;

[0072] In this embodiment, the path loss model in step S1 uses the following formula to convert the RSSI value into distance :

[0073] ;

[0074] in, It is the transmission power of the RFID reader, in milliwatts, indicating the signal strength received at 1 meter. is the path loss exponent, It is the distance between the RFID reader and the RFID fabric tag, in meters.

[0075] S2: Assume that the distance between the fabric RFID tag and the RFID reader with the largest distance is , the distance between the RFID fabric tag and the RFID reader with the shortest distance is ,like and If the ratio is less than or equal to the preset critical value, the centroid triangle positioning method is used to locate the fabric. Otherwise, the segmentation range positioning method based on the centroid triangle positioning method is used to locate the fabric, and the parameters of the segmentation range positioning method are optimized by the PSO algorithm, and the positioning coordinates of the fabric are output; the critical value here is an empirical value, usually 1.5-2.5.

[0076] In this embodiment, the specific positioning steps of the centroid triangle positioning method in step S2 are as follows:

[0077] like Figure 1 As shown, the distances between the RFID fabric tag and the four RFIDs on the same plane are sorted from small to large, the coordinates of the first three RFID readers are selected as the center of the circle, and a circle is drawn with the distance between the RFID reader and the RFID fabric tag as the radius. The intersection of the three circles is the positioning range of the RFID fabric tag;

[0078] Connect the three vertices of the positioning range in sequence to form a triangle. Due to the characteristics of the RFID reader, the RSSI signal is affected by the environment, which will weaken the RSSI signal value, resulting in the measured predicted distance being greater than the actual distance. Therefore, the three circles must intersect. The three vertices here are the three vertices of the common area where the three circles intersect. The coordinates of the center of mass of the triangle are the coordinates of the predicted RFID fabric tag. The coordinates of the center of mass A of the triangle are calculated using the following formula:

[0079] ;

[0080] in, are the coordinates of the three points of the triangle, .

[0081] When the fabric is on the shelf, the farther the RFID reader is from the RFID fabric tag, the greater the signal is affected by the environment and the error also needs to increase. Therefore, only the three RFID readers closest to the RFID fabric tag need to be selected as the positioning base stations of the positioning algorithm to reduce the algorithm complexity and improve the positioning accuracy.

[0082] In step S2, the fabric is positioned using the segmentation range positioning method based on the centroid triangle positioning method. This involves dividing the positioning range calculated from the three RFID reader signals based on the movement vector of the centroid A, the private movement ratio, and the public movement ratio, thereby narrowing the positioning range and reducing the error. The specific steps are as follows:

[0083] The center of mass A is calculated using the triangle positioning method;

[0084] Determine the movement vector: To segment the positioning range of the RFID fabric tag, you need to first find the segmentation points. The segmentation points are obtained by moving the center of mass A. The movement vector of the center of mass A is calculated based on its positional relationship with the positioning range boundary.

[0085] The motion vectors are generated as follows:

[0086] Calculate the foot of the perpendicular line from the center of mass A to any two vertices of the positioning range:

[0087] , ;

[0088] ;

[0089] ;

[0090] in, 、 Position two of the three vertices of the RFID fabric tag's range. for 、 The slope of the line connecting two points, are the coordinates of the center of mass A, is the center of mass A and 、 Two points form the foot of a perpendicular line;

[0091] Calculate the direction vector of movement and normalize it:

[0092] ;

[0093] ;

[0094] in, is the moving direction vector, is the magnitude of the direction vector, Normalize the direction vector to get the unit vector, that is, the final movement vector;

[0095] Determine the private motion ratio: Since the RSSI signal is affected by the environment, the closer the RFID fabric tag is to the RFID reader, the less the RSSI is affected by the environment and the closer it is to the actual value. Therefore, each motion vector has a private motion ratio. The size of the private motion ratio is related to the distance from the RFID fabric tag to the RFID reader:

[0096] The private mobile ratio is generated using the following formula:

[0097] ;

[0098] ;

[0099] in, Indicates RFID fabric tag to The distance between the RFID readers, Indicates RFID fabric tag to The distance between RFID readers, in meters, The first Private mobile ratio, Indicates the The normalized private mobile ratio, Indicates the number of RFID readers;

[0100] Determining the public movement ratio: After segmenting the positioning range, the signal coverage area of the RFID reader closest to the RFID fabric tag is selected as a sub-range. The public movement ratio is adjusted so that the area of this sub-range meets a preset condition. The preset condition here means that the ratio of the sub-range area to the total area of the positioning range is approximately equal to the normalized maximum private movement ratio. This optimizes the division of the positioning range and improves positioning accuracy. Because RSSI values are affected by the environment, the PSO algorithm is used to optimize the public movement ratio based on RSSI signal characteristics under different environmental conditions, improving the positioning accuracy of the segmented range positioning method.

[0101] The PSO algorithm is used to optimize the public movement ratio. The specific optimization steps are as follows:

[0102] According to the current position of each particle, the following formula is used to determine the position of the current segmentation point:

[0103] ;

[0104] The line connecting the current segmentation point and the three vertices within the positioning range is used as the segmentation line, and the area of each sub-range is calculated using the following formula:

[0105] ;

[0106] in, is the split point To The distance between the edges, For the The length of the edge, To split point The sector area with as the vertex and the arc edge as the bottom line;

[0107] Establish the optimal fitness function for the target sub-range:

[0108] ;

[0109] in, Represents the fitness value in the PSO algorithm, Representative The position of the particles, For the largest private mobile ratio, To split point The sector area with the vertex as the center and the arc edge with the smallest radius as the bottom line, the larger the private proportional coefficient, the more it needs to move to achieve the smaller fitness value;

[0110] Initialize the population: Initialize individual particles based on the processed data. Each particle represents a common movement ratio. Each particle moves in a one-dimensional coordinate. The direction and speed of movement are affected by its own inertia, the individual optimal solution, and the global optimal solution.

[0111] Calculate the fitness function value: Calculate the fitness function value of each particle. The lower the fitness, the better the public movement ratio.

[0112] Update the population: Find the optimal public movement ratio through the movement of particles. Each particle calculates the fitness value through continuous movement, updates the individual optimal solution, and shares the optimal solution of each individual within the population. Individuals continue to refine the existing excellent positions, explore and update each position;

[0113] Iterative process: Repeat the steps of calculating the fitness function value and updating the population until the optimal common movement ratio is found or the preset number of iterations is reached. The population is updated according to the fitness value to ensure that the solution is continuously optimized and eventually converges to the optimal solution.

[0114] Output the optimal solution: Calculate the prediction results of the segmentation range positioning method: Output the optimal result of the PSO algorithm as the common moving ratio, and calculate the segmentation point coordinates based on the optimal common moving ratio:

[0115] ;

[0116] in, represents the optimal public mobility ratio, represents the coordinates of the split point, represents the coordinates of the center of mass A, Indicates the motion vectors The coordinates of Indicates the The proportion of private mobile

[0117] The connecting line between the optimized segmentation point and the three vertices in the positioning range is used as the segmentation line, and the center point of the sub-range with the largest area after segmentation is calculated as the prediction point B of the segmentation range point method.

[0118] This embodiment also provides a fabric storage management system that applies the above-mentioned fabric positioning method.

[0119] A fabric storage management system, comprising a task list module, a warehousing module, a positioning display module, a fabric management module and a warehousing outgoing module;

[0120] The task order module is used to receive the incoming information of the fabric and generate an RFID fabric tag based on the incoming information; the incoming information includes the fabric code, fabric meter, unique code, incoming status and shelf status. At this time, the incoming status is 0 and the shelf status is -1.

[0121] The RFID fabric tag stores the warehousing information so that the fabric can be managed through the RFID fabric tag, and the RFID fabric tag is attached to one end of the fabric.

[0122] The warehousing module is used to receive the warehousing information obtained by the PDA scanning the RFID fabric tag, and modify the warehousing status and shelf status of the fabric; when the PDA scans the RFID fabric tag for warehousing operation, the warehousing module modifies the RFID fabric tag's warehousing status to 1 and the shelf status to 0; when the fabric is placed on the shelf, the warehousing module modifies the RFID fabric tag's shelf status to 1.

[0123] The positioning display module is used to locate the fabric position using the above fabric positioning method and display the positioning result;

[0124] The outbound module is used to receive the outbound information obtained by the PDA scanning the RFID fabric tag, and modify the fabric's inbound status and shelf status. At this time, the inbound status of the RFID fabric tag is -1 and the shelf status is 1. When the fabric is taken off the shelf, the outbound module modifies the shelf status of the RFID fabric tag to -1.

[0125] As a preferred method of this embodiment, the positioning display module is also used to determine whether the fabric is illegally removed from the shelf. If it is determined that the fabric is illegally removed from the shelf, the positioning display module sends a warning message to the RFID reader on the shelf where the fabric is located, and the corresponding RFID reader issues an alarm.

[0126] When the RFID fabric tag's storage status is 1 or 0, the positioning display module determines that the fabric does not meet the shelf relationship and is therefore deemed to have been illegally removed from the shelf. The shelf relationship determination here refers to the distance relationship between the four RFID readers and the RFID fabric tag. The determination steps are as follows:

[0127] Use Heron's formula to calculate the area of the four triangles: Use the following formula to calculate the area of each triangle formed by the RFID fabric tag and the two adjacent RFID readers:

[0128] ;

[0129] ;

[0130] in, represents the distance between two RFID readers in the triangle, 、 Indicates the distance between the RFID fabric tag and two RFID readers. It represents the semi-perimeter of the triangle formed by the RFID fabric tag and two adjacent RFID readers. represents the area of a triangle;

[0131] Calculate the area of the rectangle with four RFID readers as vertices:

[0132] ;

[0133] in, Indicates the distance between RFID readers at the same level on the shelf, in meters. Indicates the distance between RFID readers at the same vertical height on the shelf, in meters. Indicates that the area of the rectangle enclosed by the four RFID readers is also the area of the shelf plane;

[0134] Finally, the sum of the areas of the four triangles is compared. If the difference between the sum of the areas and the area of the shelf plane is less than 10% of the area of the shelf plane, the fabric is considered to be on the shelf. Otherwise, it is considered that the fabric is not on the shelf or has been taken off the shelf.

[0135] To summarize, this application determines whether the fabric is on the shelf by the distance relationship between the RFID fabric tag and the four RFID readers on the shelf, and uses the distance relationship between the RFID fabric tag and the RFID reader to select the centroid triangle positioning method or the segmentation range positioning method based on the centroid positioning method to obtain the fabric position. This reduces the situation where the centroid triangle positioning method has no solution when the distance difference between the RFID tag and each RFID reader is too large. The parameters in the segmentation range positioning method are optimized through the PSO algorithm, thereby improving the positioning accuracy of the segmentation range positioning method.

[0136] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A fabric storage management system, characterized by: It includes task list module, warehousing module, positioning display module, fabric management module and outbound module; The task list module is used to receive the fabric's warehousing information and generate an RFID fabric tag based on the warehousing information; The warehousing module is used to receive the warehousing information obtained by scanning the RFID fabric tag by the PDA, and modify the warehousing status and shelf status of the fabric; The positioning display module is used to locate the position of the fabric and display the positioning result; the positioning method adopted by the positioning display module includes the following steps performed in sequence: S1: Obtain the RSSI values of the RFID fabric tags of the fabrics read by four RFID readers located on the same plane on the shelf respectively, and convert each RSSI value into a distance using the path loss model; S2: Assume that the distance between the fabric RFID tag and the RFID reader with the largest distance is , the distance between the RFID fabric tag and the RFID reader with the shortest distance is ,like and If the ratio of is less than or equal to the preset critical value, the centroid triangle positioning method is used to locate the fabric. Otherwise, the segmentation range positioning method based on the centroid triangle positioning method is used to locate the fabric. The parameters of the segmentation range positioning method are optimized by the PSO algorithm, and the positioning coordinates of the fabric are output. The positioning display module is also used to determine whether the fabric is illegally removed from the shelf. If it is determined that the fabric is illegally removed from the shelf, the positioning display module sends a warning message to the RFID reader on the shelf where the fabric is located, and the corresponding RFID reader issues an alarm. The positioning display module determines whether the fabric is on the shelf in the following steps: The following formula is used to calculate the area of each triangle formed by the RFID fabric tag and two adjacent RFID readers: ； ； in, represents the distance between two RFID readers in the triangle, 、 Indicates the distance between the RFID fabric tag and two RFID readers. It represents the semi-perimeter of the triangle formed by the RFID fabric tag and two adjacent RFID readers. represents the area of a triangle; Calculate the area of the rectangle with four RFID readers as vertices: ； in, Indicates the distance between RFID readers at the same level on the shelf, in meters. Indicates the distance between RFID readers at the same vertical height on the shelf, in meters. Indicates that the area of the rectangle enclosed by the four RFID readers is also the area of the shelf plane; Compare the sum of the areas of the four triangles. If the difference between the sum of the areas and the area of the shelf plane is less than 10% of the area of the shelf plane, the fabric is considered to be on the shelf. Otherwise, the fabric is considered to be off the shelf or has been removed from the shelf. The outbound module is used to receive the outbound information obtained by scanning the RFID fabric tag by the PDA, and to modify the fabric's storage status and shelf status.

2. The fabric storage management system according to claim 1, characterized in that: The warehousing information includes fabric code, fabric meter, unique code, warehousing status and shelf status.

3. The fabric storage management system according to claim 1, characterized in that: The path loss model in step S1 uses the following formula to convert the RSSI value into distance : ； in, is the transmitting power of the RFID reader, indicating the signal strength received at 1 meter. is the path loss exponent, It is the distance between the RFID reader and the RFID fabric tag.

4. The fabric storage management system according to claim 3, characterized in that: The specific positioning steps of the centroid triangle positioning method in step S2 are as follows: Sort the distances between the RFID fabric tag and four RFID readers on the same plane from small to large. Select the coordinates of the first three RFID readers as the center of a circle. Draw a circle with the distance between the RFID reader and the RFID fabric tag as the radius. The intersection of the three circles is the positioning range of the RFID fabric tag. Connect the three vertices of the positioning range in sequence to form a triangle, and calculate the coordinates of the center of mass A of the triangle: ； in, are the coordinates of the three points of the triangle, .

5. The fabric storage management system according to claim 4, characterized in that: The specific steps of locating the fabric position using the segmentation range positioning method based on the centroid triangle positioning method in step S2 are as follows: The center of mass A is calculated using the triangle positioning method; Calculate the foot of the perpendicular line from the center of mass A to any two vertices of the positioning range: ， ； ； ； in, 、 Position two of the three vertices of the RFID fabric tag's range. for 、 The slope of the line connecting two points, are the coordinates of the center of mass A, is the center of mass A and 、 Two points form the foot of a perpendicular line; Calculate the direction vector of movement and normalize it: ； ； in, is the moving direction vector, is the magnitude of the direction vector, Normalize the direction vector to get the unit vector, that is, the final movement vector; The private mobile ratio is generated using the following formula: ； ； in, Indicates RFID fabric tag to The distance between the RFID readers, Indicates RFID fabric tag to The distance between the RFID readers, The first Private mobile ratio, Indicates the The normalized private mobile ratio, Indicates the number of RFID readers; After segmenting the positioning range, the signal coverage range of the RFID reader closest to the RFID fabric tag is selected as the sub-range. The common movement ratio is adjusted so that the area of the sub-range meets the preset conditions. The PSO algorithm is used to optimize the common movement ratio. The specific optimization steps are as follows: According to the current position of each particle, the following formula is used to determine the position of the current segmentation point: ； The line connecting the current segmentation point and the three vertices within the positioning range is used as the segmentation line, and the area of each sub-range is calculated using the following formula: ； in, is the split point To The distance between the edges, For the The length of the edge, To split point The sector area with as the vertex and the arc edge as the bottom line; Establish the optimal fitness function for the target sub-range: ； in, Represents the fitness value in the PSO algorithm, Representative The position of the particles, For the largest private mobile ratio, To split point The sector area with the vertex as the center and the arc edge with the smallest radius as the bottom line, the larger the private proportional coefficient, the more it needs to move to achieve the smaller fitness value; Initialize the population: Initialize individual particles based on the processed data. Each particle represents a common movement ratio. Each particle moves in a one-dimensional coordinate. The direction and speed of movement are affected by its own inertia, the individual optimal solution, and the global optimal solution. Calculate the fitness function value: Calculate the fitness function value of each particle. The lower the fitness, the better the public movement ratio. Update the population: Find the optimal public movement ratio through the movement of particles. Each particle calculates the fitness value through continuous movement, updates the individual optimal solution, and shares the optimal solution of each individual within the population. Individuals continue to refine the existing excellent positions, explore and update each position; Iterative process: Repeat the steps of calculating the fitness function value and updating the population until the optimal common movement ratio is found or the preset number of iterations is reached. The population is updated according to the fitness value to ensure that the solution is continuously optimized and eventually converges to the optimal solution. Output the optimal solution: Calculate the prediction results of the segmentation range positioning method: Output the optimal result of the PSO algorithm as the common moving ratio, and calculate the segmentation point coordinates based on the optimal common moving ratio: ； in, represents the optimal public mobility ratio, represents the coordinates of the split point, represents the coordinates of the center of mass A, Indicates the motion vectors The coordinates of Indicates the The proportion of private mobile The connecting line between the optimized segmentation point and the three vertices in the positioning range is used as the segmentation line, and the center point of the sub-range with the largest area after segmentation is calculated as the prediction point B of the segmentation range point method.

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