Bag storage intelligent sorting and management system based on RFID

Abstract

The invention discloses an RFID-based bag storage intelligent sorting and management system, and relates to the technical field of bag sorting control, and the system comprises a material information extraction module which is used for extracting material composition information in an RFID tag signal when receiving the RFID tag signal, and obtaining a metal proportion; the accuracy calculation module is used for calculating the signal receiving accuracy through the metal proportion; the conveyor belt speed control module is used for adjusting the speed of the conveyor belt according to the signal receiving accuracy and carrying out classification and sorting according to the production batch of the RFID tag signals; judging whether a standby information matching module is triggered or not through a judgment strategy; and the standby information matching module is used for obtaining a standby information matching rate according to the other information of the RFID tag signal and the matching rate in the information base, and then carrying out classification and sorting. According to the invention, the problem that signal capture is incomplete or reading time is insufficient due to the fact that a conveyor belt and carrying equipment which operate at a high speed enable labels to enter an induction area of a reader-writer in a short window is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of bag sorting control, and in particular to an RFID-based bag storage intelligent sorting and management system. Background Art

[0002] With the rapid development of e-commerce, intelligent manufacturing, and warehousing and logistics, the circulation frequency of bagged goods is increasing, and the variety of products is expanding. The efficiency and accuracy of warehousing and sorting have become key factors restricting the efficiency of the entire supply chain system. In bag warehousing management, in particular, due to the wide variety and complex shapes of bags, and the extensive use of metal accessories such as metal zippers, rivets, and decorative parts in the design of many products, traditional barcode recognition methods have problems such as manual reliance, low efficiency, and easy obstruction. Radio Frequency Identification (RFID) technology, with its advantages of non-contact, high recognition rate, and batch reading, is gradually becoming the core sensing method of intelligent warehousing systems.

[0003] However, despite the theoretical superiority of RFID technology, practical applications still face numerous technical bottlenecks, particularly in bag sorting scenarios where metal is complex and signals are susceptible to interference. High-speed conveyor belts and handling equipment allow tags to enter the reader's sensing area within a brief window. The metal material can cause the RFID tag signal to be reflected, absorbed, or shielded, seriously affecting the stability and accuracy of signal reception. Furthermore, due to the constant speed of conveyor belts in warehousing systems, RFID tags only stay in the reader's sensing area for a short time, further increasing the risk of recognition failure. Furthermore, most current sorting systems lack effective backup recognition mechanisms when RFID read failures occur, which can easily lead to sorting errors, reduced efficiency, and even complete process interruptions.

[0004] Therefore, there is an urgent need to build an intelligent sorting system that can sense and evaluate the intensity of metal interference in real time, dynamically adjust the sorting speed, and have backup recognition capabilities in extreme situations. To this end, the present invention provides an RFID-based intelligent sorting and management system for bag storage. Summary of the Invention

[0005] The purpose of the present invention is to provide an RFID-based bag storage intelligent sorting and management system to solve the existing problems raised in the above background technology.

[0006] To achieve the above objectives, the present invention provides the following technical solutions: an RFID-based bag storage intelligent sorting and management system, comprising:

[0007] The material information extraction module is used to extract the material composition information in the RFID tag signal when receiving the RFID tag signal to obtain the metal ratio;

[0008] Accuracy calculation module, used to calculate the signal reception accuracy based on the metal ratio;

[0009] The conveyor belt speed control module adjusts the conveyor belt speed according to the signal reception accuracy, and classifies and sorts according to the production batch of the RFID tag signal; and determines whether to trigger the backup information matching module through the judgment strategy;

[0010] The spare information matching module is used to obtain the spare information matching rate according to the matching rate between the remaining information of the RFID tag signal and the information database, and then perform classification and sorting.

[0011] A further improvement of the present invention is that the material information extraction module includes a basic information extraction unit and a metal proportion extraction unit;

[0012] The basic information extraction unit is implemented by deploying fixed RFID readers on conveyor belts and key sorting nodes; the basic information of RFID tag signals includes tag ID, production batch, product category and tag signal characteristics; the metal proportion extraction unit includes separating metal characteristic signals, setting a sampling period, and extracting the total amplitude Sto of all information characteristic signals read within a sampling period, and obtaining the metal proportion mp by calculating the ratio of the sum of the metal characteristic signal amplitudes Sme to the total amplitude of all information characteristic signals.

[0013] A further improvement of the present invention is that the conveyor belt speed control module includes a conveyor belt speed adjustment unit and a strategy judgment unit;

[0014] The conveyor belt speed adjustment unit is implemented by designing a conveyor belt speed control model, which includes a control input subunit and a loss correction subunit;

[0015] The control input subunit includes taking the difference between the signal reception accuracy and the target signal reception accuracy as the model error e(t), calculating the error change rate ce(t) within time t, and taking the model error e(t), the error change rate ce(t), the metal proportion mp and the current conveyor belt speed v as input vectors and sending them into the PID controller.

[0016] The present invention is further improved in that the loss correction subunit includes calculating the mean square error L between the expected conveyor belt speed and the actual conveyor belt speed. V (t), the mean square error L between the signal reception accuracy and the target signal reception accuracy A (t), and assume that the output of the PID controller at the previous moment is u(t-1), and the current PID controller output is u(t), then calculate the mean square error between u(t-1) and u(t) as the output jitter term L J (t); then L V (t), LA (t) and L J (t) is weightedly summed to obtain the comprehensive penalty function aL(t); the comprehensive penalty function aL(t) is used as the objective function, the gradient is calculated through the back propagation algorithm, and the Adam optimizer is used to adjust the neural network weights. At this time, the output PID correction value ΔK is used to update the PID parameters, and the updated PID parameters are immediately applied to the conveyor belt speed controller to adjust the conveyor belt speed.

[0017] A further improvement of the present invention is that the strategy judgment unit includes the judgment strategy, when the conveyor belt speed output by the PID controller is less than the minimum conveyor belt speed, the conveyor belt speed takes the set minimum conveyor belt speed; the judgment strategy also includes extracting the time window T, calculating the weighted average of the CRC test success rate, RSSI signal strength and signal-to-noise consistency, and obtaining the tag confidence; when the tag confidence is less than the set confidence threshold or the conveyor belt speed output by the PID controller is less than the minimum conveyor belt speed, the backup information matching module is triggered.

[0018] A further improvement of the present invention is that the backup information matching module includes a backup information extraction unit and a backup information matching unit;

[0019] The backup information extraction unit is used to extract the tag ID and production batch of the RFID tag received from the conveyor belt speed control module, list them in the backup information field sequence, and vectorize all data in the backup information field sequence to form a backup information feature vector;

[0020] The backup information matching unit includes taking the feature vector of the backup information field sequence of the historical RFID tag as the historical information feature vector and sending it to the historical information feature database; and calculating the cosine similarity set sim between the backup information feature vector and all the historical information feature vectors recorded in the historical information feature database. i =(sim1,sim2,,sim n ), where n represents the number of all historical information feature vectors recorded in the historical information feature database, sim i Represents the cosine similarity between the i-th backup information feature vector and the historical information feature vector.

[0021] A further improvement of the present invention is that the backup information matching unit further includes an information similarity calculation strategy; if the tag confidence of any RFID tag is less than a set confidence threshold, the signal reception accuracy rate asr of the RFID tag is extracted. j , and its cosine similarity set Then the information similarity set of the RFID tag is expressed as If the conveyor belt speed output by the PID controller corresponding to the RFID tag is less than the minimum conveyor belt speed v min When the conveyor belt speed v is extracted from the PID controller output ret , at this time the information similarity set of the RFID tag is expressed as Extract the maximum information similarity of the data in the information similarity set of the RFID tag The product category information of the corresponding RFID tag is used as an alternative product category for sorting.

[0022] The present invention is further improved in that the metal ratio extraction unit includes a baseband amplitude S obtained by a baseline calibration method. free and metal amplitude S metal , calculate the relative amplitude ratio RS = S metal / S free , extract all the information characteristic signals read within a sampling period. When the amplitude ratio of any frequency band in the characteristic signal to the amplitude of the previous frequency band is greater than RS, it is recorded as the metal characteristic signal amplitude.

[0023] The present invention is further improved in that the accuracy calculation module sets the signal reception accuracy in the absence of metal interference to A. max , the signal reception accuracy under extreme metal interference is A min , calculate the accuracy attenuation coefficient The signal receiving accuracy of the current bag RFID tag is

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] 1. The present invention first separates and quantifies the metal characteristic signals in the RFID signal through the material information extraction module, which can evaluate the degree of metal interference in real time, providing a reliable basis for subsequent accuracy calculation and sorting decision-making, and significantly reducing the reading error rate in metal environments;

[0026] 2. Combining a PID controller and a loss correction sub-unit, including a multi-objective loss function for speed error, accuracy error, and output jitter, and online adjustment of PID parameters, the system can adaptively adjust the conveyor belt speed based on real-time signal quality and sorting requirements, ensuring sorting accuracy while improving overall throughput.

[0027] 3. When the primary signal fails or is of insufficient quality, alternative fields such as tag ID and production batch are extracted, vectorized, and efficiently matched with the historical information feature library using cosine similarity. This ensures accurate positioning of product categories even in the presence of severe metal interference, thereby improving system robustness. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a framework diagram of the RFID-based bag storage intelligent sorting and management system of the present invention;

[0029] Figure 2 This is a framework diagram of the information similarity calculation strategy of the backup information matching module of the present invention. DETAILED DESCRIPTION

[0030] The technical solution of the present invention is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations on the technical solution of the present invention. In the absence of conflict, the embodiments of the present invention and the technical features in the embodiments can be combined with each other.

[0031] The term "and / or" simply describes a relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can mean: A exists alone, A and B exist simultaneously, or B exists alone. Additionally, the character " / " generally indicates an "or" relationship between the related objects.

[0032] Example 1

[0033] Figure 1 The framework diagram of the RFID-based bag storage intelligent sorting and management system disclosed in this embodiment is shown, including:

[0034] The material information extraction module is used to extract the material composition information from the RFID tag signal and obtain the metal ratio due to the interference of the metal signal when receiving the RFID tag signal;

[0035] Accuracy calculation module, used to calculate the signal reception accuracy based on the metal ratio;

[0036] The conveyor belt speed control module adjusts the conveyor belt speed according to the signal reception accuracy and classifies and sorts the products according to the production batch of the RFID tag signal; to ensure efficiency, the judgment strategy is used to determine whether to trigger the backup information matching module;

[0037] The spare information matching module is used to obtain the spare information matching rate according to the matching rate between the remaining information of the RFID tag signal and the information database, and then perform classification and sorting.

[0038] The material information extraction module includes a basic information extraction unit and a metal proportion extraction unit;

[0039] The basic information extraction unit continuously scans the RFID tags of bags by deploying fixed RFID readers on the conveyor belt and key sorting nodes. The basic information of the RFID tag signal includes the tag ID, production batch, product category and tag signal characteristics.

[0040] The metal ratio extraction unit includes separating the metal characteristic signal, setting the sampling period, and extracting the total amplitude Sto of all information characteristic signals read within a sampling period. The baseband amplitude Sto is obtained by the baseline calibration method. free and metal amplitude S metal The line calibration method is to attach the same type of RFID tag to the plastic plate and record its echo signal strength as the baseband amplitude S free Then attach the tag to the metal workpiece to be tested and measure the same signal as the metal amplitude S metal , calculate the relative amplitude ratio RS = S metal / S free , extract all the information characteristic signals read within a sampling period. When the amplitude ratio of any frequency band in the characteristic signal to the amplitude of the previous frequency band is greater than RS, it is recorded as the metal characteristic signal amplitude; the metal proportion mp is obtained by calculating the proportion of the sum of the metal characteristic signal amplitudes Sme in the total amplitude of all information characteristic signals.

[0041] The accuracy calculation module sets the signal reception accuracy to A when there is no metal interference. max , the signal reception accuracy under extreme metal interference is A min , calculate the accuracy attenuation coefficient Used to ensure that when mp = 100%, asr = A, A max and A min Through experimental calibration, in this embodiment, A max =100%, A min =50%; the signal receiving accuracy of the current bag RFID tag is

[0042] The conveyor belt speed control module includes a conveyor belt speed adjustment unit and a strategy judgment unit;

[0043] The conveyor belt speed adjustment unit is implemented by designing a conveyor belt speed control model, which includes a control input subunit and a loss correction subunit;

[0044] The control input subunit includes taking the difference between the signal reception accuracy and the target signal reception accuracy as the model error e(t), calculating the error change rate ce(t) within time t, and taking the model error e(t), the error change rate ce(t), the metal proportion mp and the current conveyor belt speed v as input vectors and sending them into the PID controller.

[0045] The loss correction subunit includes calculating the mean square error L between the expected conveyor belt speed and the actual conveyor belt speed V (t), the calculation formula is expressed as LV (t)=(V des -V(t)) 2 , which can reflect the degree to which the conveyor belt speed deviates from the expected state, the mean square error L between the signal reception accuracy and the target signal reception accuracy A (t), the calculation formula is expressed as L A (t)=(A set -A(t)) 2 The loss of signal reception accuracy reflects the gap between RFID information collection and target accuracy. Taking into account the impact of conveyor belt speed, RFID accuracy and output jitter on the overall system performance, multi-objective optimization is achieved through weight adjustment. In order to avoid system instability caused by rapid fluctuations in controller output, a jitter penalty term is added. Suppose the PID controller output at the previous moment is u(t-1), and the current PID controller output is u(t), then the mean square error between u(t-1) and u(t) is calculated as the output jitter term L J (t); then L V (t), L A (t) and L J (t) is weighted and summed to obtain the comprehensive penalty function aL(t); the comprehensive penalty function aL(t) is used as the objective function, the gradient is calculated by the back propagation algorithm, and the Adam optimizer is used to adjust the neural network weight. At this time, the output PID correction value ΔK is used to update the PID parameters. The update process is expressed as K P (t+1)=K P (t)+ΔK P , K I (t+1)=K I (t)+ΔK I and K D (t+1)=K D (t)+ΔK D , the updated PID parameters are immediately applied to the conveyor belt speed controller to adjust the conveyor belt speed;

[0046] By minimizing the comprehensive penalty function, the final output PID parameters can minimize the error between the target state and the actual state, while smoothing the controller output, reducing jitter, and improving the robustness of the entire system.

[0047] The strategy judgment unit includes the judgment strategy. When the conveyor belt speed output by the PID controller is less than the minimum conveyor belt speed, it indicates that the interference is too large. At this time, the conveyor belt speed takes the set minimum conveyor belt speed. The judgment strategy also includes calculating the CRC test success rate, RSSI signal strength and signal-to-noise consistency within the extraction time window T.

[0048] The CRC check success rate is obtained by extracting the CRC check field of the RFID tag at each reading. A pass in the check is counted as a "success", and a failure in the check is counted as a "failure". The number of "successes" N in a time window is counted. crc and the total number of attempts N tot , then the CRC test success rate is expressed as:

[0049]

[0050] The RSSI signal strength is obtained by extracting the RSSI measurement value given by the reader, and the maximum readable RSSI measured by the system is set as RSSI max , and normalize to get the RSSI signal strength R;

[0051] The signal-to-noise consistency is calculated by calculating whether the ID read by the same RFID tag in a time window is consistent, and the number of IDs with the highest number of occurrences is recorded as N. max , then the signal-noise consistency

[0052]

[0053] The weighted average of the CRC test success rate, RSSI signal strength, and signal-to-noise consistency is calculated to obtain the tag confidence. When the tag confidence is less than the set confidence threshold or the conveyor belt speed output by the PID controller is less than the minimum conveyor belt speed, the backup information matching module is triggered.

[0054] Example 2

[0055] Based on the technical solution of Example 1, this embodiment provides a construction process of the backup information matching module. Figure 2 The following diagram shows the information similarity calculation strategy framework of the backup information matching module disclosed in this embodiment, including:

[0056] The backup information matching module includes a backup information extraction unit and a backup information matching unit;

[0057] The backup information extraction unit is used to extract the tag ID and production batch of the RFID tag received from the conveyor belt speed control module, list them in the backup information field sequence, and vectorize all data in the backup information field sequence to form a backup information feature vector;

[0058] The backup information matching unit includes taking the feature vector of the backup information field sequence of the historical RFID tag as the historical information feature vector and sending it to the historical information feature database; and calculating the cosine similarity set sim between the backup information feature vector and all the historical information feature vectors recorded in the historical information feature database. i =(sim1,sim2,,sim n), where n represents the number of all historical information feature vectors recorded in the historical information feature database, sim i Represents the cosine similarity between the i-th backup information feature vector and the historical information feature vector.

[0059] The backup information matching unit also includes an information similarity calculation strategy; if the tag confidence of any RFID tag is less than the set confidence threshold, the signal reception accuracy rate asr of the RFID tag is extracted. j , and its cosine similarity set Then the information similarity set of the RFID tag is expressed as If the conveyor belt speed output by the PID controller corresponding to the RFID tag is less than the minimum conveyor belt speed v min When the conveyor belt speed v is extracted from the PID controller output ret , at this time the information similarity set of the RFID tag is expressed as Extract the maximum information similarity of the data in the information similarity set of the RFID tag The product category information of the corresponding RFID tag is used as an alternative product category for sorting.

[0060] The thresholds, weights and other setting values may be set by default according to the present invention, or may be set by an operator.

[0061] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0062] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0063] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0064] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0065] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the purpose of the present invention and the claims, which are all protected by the present invention.

Claims

1. RFID-based bag storage intelligent sorting and management system, characterized by: include: The material information extraction module is used to extract the material composition information in the RFID tag signal when receiving the RFID tag signal to obtain the metal ratio; Accuracy calculation module, used to calculate the signal reception accuracy based on the metal ratio; The conveyor belt speed control module adjusts the conveyor belt speed according to the signal reception accuracy, and classifies and sorts according to the production batch of the RFID tag signal; and determines whether to trigger the backup information matching module through the judgment strategy; The spare information matching module is used to obtain the spare information matching rate according to the matching rate between the remaining information of the RFID tag signal and the information database, and then perform classification and sorting.

2. The RFID-based bag storage intelligent sorting and management system according to claim 1, characterized in that: The material information extraction module includes a basic information extraction unit and a metal proportion extraction unit; The basic information extraction unit is implemented by deploying fixed RFID readers on conveyor belts and key sorting nodes; the basic information of RFID tag signals includes tag ID, production batch, product category and tag signal characteristics; The metal proportion extraction unit includes separating the metal characteristic signal, setting a sampling period, and extracting the total amplitude Sto of all information characteristic signals read within a sampling period, and obtaining the metal proportion mp by calculating the ratio of the sum of the metal characteristic signal amplitudes Sme to the total amplitude of all information characteristic signals.

3. The RFID-based bag storage intelligent sorting and management system according to claim 1, characterized in that: The conveyor belt speed control module includes a conveyor belt speed adjustment unit and a strategy judgment unit; The conveyor belt speed adjustment unit is implemented by designing a conveyor belt speed control model, which includes a control input subunit and a loss correction subunit; The control input subunit includes taking the difference between the signal reception accuracy and the target signal reception accuracy as the model error e(t), calculating the error change rate ce(t) within time t, and taking the model error e(t), the error change rate ce(t), the metal proportion mp and the current conveyor belt speed v as input vectors and sending them into the PID controller.

4. The RFID-based bag storage intelligent sorting and management system according to claim 3, characterized in that: The loss correction subunit includes calculating the mean square error L between the expected conveyor belt speed and the actual conveyor belt speed V (t), the mean square error L between the signal reception accuracy and the target signal reception accuracy A (t), and assume that the output of the PID controller at the previous moment is u(t-1), and the current PID controller output is u(t), then calculate the mean square error between u(t-1) and u(t) as the output jitter term L J (t); then L V (t), L A (t) and L J (t) is weightedly summed to obtain the comprehensive penalty function aL(t); the comprehensive penalty function aL(t) is used as the objective function, the gradient is calculated through the back propagation algorithm, and the Adam optimizer is used to adjust the neural network weights. At this time, the output PID correction value ΔK is used to update the PID parameters, and the updated PID parameters are immediately applied to the conveyor belt speed controller to adjust the conveyor belt speed.

5. The RFID-based bag storage intelligent sorting and management system according to claim 2, characterized in that: The strategy judgment unit includes the judgment strategy. When the conveyor belt speed output by the PID controller is less than the minimum conveyor belt speed, the conveyor belt speed takes the set minimum conveyor belt speed; the judgment strategy also includes extracting the time window T, calculating the weighted average of the CRC test success rate, RSSI signal strength and signal-to-noise consistency, and obtaining the tag confidence; when the tag confidence is less than the set confidence threshold or the conveyor belt speed output by the PID controller is less than the minimum conveyor belt speed, the backup information matching module is triggered.

6. The RFID-based bag storage intelligent sorting and management system according to claim 1, characterized in that: The backup information matching module includes a backup information extraction unit and a backup information matching unit; The backup information extraction unit is used to extract the tag ID and production batch of the RFID tag received from the conveyor belt speed control module, list them in the backup information field sequence, and vectorize all data in the backup information field sequence to form a backup information feature vector; The backup information matching unit includes taking the feature vector of the backup information field sequence of the historical RFID tag as the historical information feature vector and sending it to the historical information feature database; and calculating the cosine similarity set sim between the backup information feature vector and all the historical information feature vectors recorded in the historical information feature database. i =(sim1,sim2,,sim n ), where n represents the number of all historical information feature vectors recorded in the historical information feature database, sim i Represents the cosine similarity between the i-th backup information feature vector and the historical information feature vector.

7. The RFID-based bag storage intelligent sorting and management system according to claim 6, characterized in that: The backup information matching unit also includes an information similarity calculation strategy; if the tag confidence of any RFID tag is less than the set confidence threshold, the signal reception accuracy rate asr of the RFID tag is extracted. j , and its cosine similarity set Then the information similarity set of the RFID tag is expressed as If the conveyor belt speed output by the PID controller corresponding to the RFID tag is less than the minimum conveyor belt speed v min When the conveyor belt speed v is extracted from the PID controller output ret , at this time the information similarity set of the RFID tag is expressed as Extract the maximum information similarity of the data in the information similarity set of the RFID tag The product category information of the corresponding RFID tag is used as an alternative product category for sorting.

8. The RFID-based bag storage intelligent sorting and management system according to claim 2, characterized in that: The metal ratio extraction unit includes obtaining the baseband amplitude S by a baseline calibration method. free and metal amplitude S metal , calculate the relative amplitude ratio RS = S metal / S free , extract all the information characteristic signals read within a sampling period. When the amplitude ratio of any frequency band in the characteristic signal to the amplitude of the previous frequency band is greater than RS, it is recorded as the metal characteristic signal amplitude.

9. The RFID-based bag storage intelligent sorting and management system according to claim 8, characterized in that: The accuracy calculation module sets the signal reception accuracy to A when there is no metal interference. max , the signal reception accuracy under extreme metal interference is A min , calculate the accuracy attenuation coefficient The signal receiving accuracy of the current bag RFID tag is

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