Intelligent screen printing plate storage system and method

Abstract

The invention discloses an intelligent screen printing plate storage system and method, and the system comprises an intelligent goods shelf provided with a weight sensor, each screen printing plate is provided with a unique electronic tag, the information of the electronic tags is read through a card reader periodical polling mode, and the information of the electronic tags is uploaded to a server; the server is in communication connection with the intelligent goods shelf and the electronic tag system, and is used for receiving the screen identity label and the signal intensity data sent by the card reader and the sensing data sent by the weight sensor; generating a use record of each screen according to the received data, predicting the remaining service life of each screen, and outputting maintenance prompt information; and the user terminal is used for querying the screen information and receiving the life prediction result and the maintenance reminding information. Production stagnation caused by loss or misplacement of the screen printing plate is reduced, the stability of product quality is guaranteed, the intelligent level of the production process is improved, and the operation cost of an enterprise is reduced.

Description

Technical Field

[0001] This invention relates to the field of IoT smart manufacturing technology, and in particular to a smart screen printing storage system and method. Background Technology

[0002] With the continuous improvement of production efficiency and the increasing demand for quality management, screen printing plate management has become an indispensable part of the production line. In traditional screen printing plate storage and management methods, factory personnel manually write down part numbers to distinguish screen printing plates. However, in actual production, the accuracy and efficiency of finding screen printing plates are low, often requiring replacement. Especially when screen printing plates are lost or misplaced, replacing them not only wastes time and materials but also increases labor costs, significantly impacting production efficiency.

[0003] While existing automated management technologies reduce human intervention to some extent, automated tracking systems typically rely on barcode technology alone to manage inventory. This type of technology cannot simultaneously and efficiently address both the accuracy of screen printing plate storage and real-time monitoring. For example, barcode or RFID systems cannot provide real-time feedback on screen printing plate status, and they cannot automatically alert for improperly placed or lost plates, leading to frequent misoperations or missed detections during production. Furthermore, existing systems often fail to effectively integrate screen printing plate lifespan monitoring, failing to issue timely warnings before plate wear and tear, thus impacting production efficiency and the effectiveness of preventative maintenance.

[0004] Therefore, there is a need to propose an intelligent screen printing plate storage and management solution that can improve the accuracy and efficiency of screen printing plate storage and retrieval based on electronic tags and big data analysis technology, while reducing production stoppages caused by screen printing plate damage, and improving the overall efficiency of the production line and the level of intelligence in production management. Summary of the Invention

[0005] In view of this, the present invention provides an intelligent screen printing storage system and method to solve the technical problems of inaccurate storage, inefficient searching, material waste, and lack of real-time monitoring and early warning in existing screen printing management.

[0006] To achieve the above-mentioned technical objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides an intelligent screen printing storage system, comprising: The intelligent shelf is equipped with a weight sensor for storing screen printing plates, detecting the storage location and weight of the screen printing plates; The electronic tag system includes electronic tags set on each screen and card readers set on the smart shelf. The card readers are used to read electronic tag information by periodic polling and upload the electronic tag information to the server. The server is communicatively connected to the smart shelf and electronic tag system, and is used to receive the grid identification and signal strength data sent by the card reader, as well as the sensing data sent by the weight sensor; generate usage records for each grid based on the received data, predict the remaining service life of each grid, and output maintenance prompts. The user terminal communicates with the server and is used to query network version information, receive lifespan prediction results, and maintenance reminders.

[0007] Furthermore, the server includes a data access unit, an event recognition unit, and a lifetime prediction unit; The data access unit is used to encapsulate the network version identification and signal strength data reported by the card reader, as well as the sensor data uploaded by the weight sensor, into a standardized message according to the timestamp and write it into the message queue. The event recognition unit is used to perform sliding window analysis on instantaneous data in the message queue. When the same screen identifier is lost within two consecutive polling cycles and the difference between the weight difference and the weight of a single screen is within a preset range, it determines that a screen retrieval event has occurred and updates the usage record of the corresponding screen. The lifespan prediction unit is used to read the identity information and usage records in the usage records, output the remaining lifespan through a preset analysis model, and generate maintenance reminder data.

[0008] Furthermore, the event recognition unit includes a dynamic threshold calculation module and a trigger judgment module; The dynamic threshold calculation module is used to extract the energy value of a preset frequency band as an environmental interference index by decomposing the sensor signal through wavelet packet decomposition, dynamically adjust the weight difference threshold based on the environmental interference index, select the weight coefficient according to the screen material-sensitivity mapping table, and calculate the screen usage threshold according to the weight difference threshold, the weight coefficient and the signal attenuation compensation strategy. The trigger judgment module is used to perform multi-condition synchronous verification on the acquired data according to the screen version retrieval threshold. When the same screen version identity meets the electronic tag radio frequency signal loss and weight difference matching rules in two consecutive polling cycles, it is determined that a retrieval event has occurred and the usage record of the corresponding screen version is updated.

[0009] Furthermore, the signal attenuation compensation strategy is as follows: When the energy value of the preset frequency band extracted by wavelet packet decomposition exceeds the threshold and the attenuation rate of the RF signal of the electronic tag increases beyond the preset benchmark value per unit time, it is determined that a synchronization mutation has occurred. Based on the ratio of vibration energy to attenuation rate, a compensation coefficient is selected according to a preset ratio mapping rule, and the dynamic threshold is adjusted according to the compensation coefficient.

[0010] Furthermore, the method for calculating the radio frequency signal attenuation rate of the electronic tag is as follows: The RSSI sequence sent by the card reader is subjected to Kalman filtering to obtain a smooth signal; Calculate the signal gradient within a preset time window; Using the signal gradient as input to the exponentially weighted moving average model, the radio frequency signal attenuation rate is calculated using the following formula: in, λ represents the baseline decay rate, and λ represents the control weight. It is used to smooth the instantaneous gradient of a signal and to quantize the signal decay rate.

[0011] Furthermore, the lifespan prediction unit includes a feature extraction module, an analysis and reasoning module, and a maintenance reminder module; The feature extraction module is used to extract screen model, production batch, initial tension, cumulative number of uses and weight decay slope to form a multi-dimensional feature vector; The analysis and reasoning module is used to reason about the feature vector using the random forest regression algorithm to obtain the remaining lifetime and uncertainty. The maintenance reminder module is used to compare the remaining service life with the first cycle period and the second cycle period using two-level thresholds, generate maintenance reminder data of the corresponding level based on the comparison results, and send it to the user terminal.

[0012] Furthermore, the intelligent shelf is also equipped with temperature and humidity sensors to monitor the temperature and humidity data of the mesh storage environment; The feature extraction module is also used to extract the corrosion coefficient based on the feedback data from the temperature and humidity sensor and the screen material; the analysis and reasoning module dynamically adjusts the input weights based on the corrosion coefficient.

[0013] Furthermore, the weight sensor on the intelligent shelf is a strain gauge type weighing sensor, and a silicone buffer pad is installed between the weight sensor and the shelf panel to suppress high-frequency vibration noise.

[0014] Furthermore, the electronic tag system uses a multi-antenna reader, with one reader deployed independently on each floor; during data reading, each shelf is divided into multiple virtual grids, and the reader polls according to the numbering order of the virtual grids.

[0015] On the other hand, the present invention also provides a method for storing intelligent web pages, implemented using the system described in the above technical solution, comprising: Assign a unique electronic tag to each webpage and write its basic information into it; The screen printing plates are stored on a smart shelf, and the storage location of the screen printing plates is obtained through weight sensors; The reader automatically identifies the inbound and outbound operations of the screen printing plate and records the usage history. Based on the historical usage and status data of each web version, the server generates usage records for each web version, predicts the remaining lifespan of each web version, and outputs maintenance prompts. When the network interface card (NIC) is in an abnormal state or nearing the end of its lifespan, a maintenance or replacement reminder will be sent through the user terminal.

[0016] Compared with existing technologies, the intelligent screen printing storage system proposed in this invention has the following advantages: (1) Improve production efficiency: This system uses intelligent shelves and electronic tag system to achieve real-time positioning and accurate identification of screen printing plates, enabling production personnel to quickly obtain the required screen printing plates and reduce search and handling time. The system can automatically record the storage and usage information of screen printing plates, realize rapid scheduling and management, and improve the overall operating efficiency of the production line.

[0017] (2) Ensuring Quality Stability: The system can monitor the screen printing plate status in real time and, combined with the lifespan prediction function, promptly prompt maintenance or replacement to ensure that the screen printing plate used in each production run is in optimal condition. The combination of electronic tags and intelligent monitoring ensures the consistency of screen printing plate usage, thereby stabilizing product quality during the production process.

[0018] (3) Reduced production and management costs: Automated monitoring and management reduce manual intervention, improve the efficiency of screen printing plate usage, and reduce additional procurement and production downtime costs caused by misplacement, loss, or damage. The system extends the lifespan of screen printing plates through life prediction and maintenance prompts, reducing material waste and maintenance expenses, thereby reducing overall costs. Attached Figure Description

[0019] Figure 1 A schematic diagram of the intelligent screen printing storage system provided by the present invention; Figure 2 This is a schematic diagram of the server structure provided by the present invention; Figure 3 This is a schematic diagram of the structure of the event recognition unit provided by the present invention; Figure 4 This is a schematic diagram of the lifetime prediction unit provided by the present invention. Detailed Implementation

[0020] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0021] Please see Figure 1This embodiment provides an intelligent webpage storage system 100, including: The intelligent shelf 101 is equipped with a weight sensor for storing screen printing plates, detecting the storage location and weight of the screen printing plates; The electronic tag system 102 includes electronic tags set on each screen and a card reader set on the smart shelf 101. The card reader is used to read the electronic tag information by periodic polling and upload the electronic tag information to the server 103. Server 103 is communicatively connected to the smart shelf 101 and the electronic tag system 102. It is used to receive the grid identification and signal strength data sent by the card reader, as well as the sensing data sent by the weight sensor; generate usage records for each grid based on the received data, predict the remaining service life of each grid, and output maintenance prompts. User terminal 104 is communicatively connected to server 103 and is used to query network version information, receive lifespan prediction results and maintenance reminder information.

[0022] The system provided in this embodiment, through intelligent shelves and weight sensors, can monitor the storage location and weight of each screen in real time. An integrated electronic tag system automatically obtains the screen's identity information through periodic polling, avoiding manual searching and misplacement, effectively reducing manual data entry errors. The system can also upload data to a server in real time for analysis and storage, greatly improving the accuracy and timeliness of information. By predicting the screen's lifespan based on collected data, and sending maintenance reminders and lifespan prediction information to management personnel through user terminals, the system reduces production downtime caused by screen wear and tear, improving the overall efficiency of the production line and the level of intelligent production management.

[0023] In a preferred embodiment, the weight sensor on the intelligent shelf is a strain gauge type weighing sensor, and a silicone buffer pad is installed between the weight sensor and the shelf panel to suppress high-frequency vibration noise.

[0024] Specifically, the sensor range covers 1.5 times the calibrated weight of a single screen (e.g., if the screen weighs 1kg, the sensor range is ≥1.5kg), with an accuracy of ±0.5%; each screen's storage location corresponds to a unique grid code (e.g., A-1-3 represents the 3rd grid in the 1st layer of area A), and the screen center coordinates are calculated using the weight distribution ratio of the four-point sensors, with a positioning error ≤2cm.

[0025] All sensors are connected in parallel to the server's main control MCU via an RS-485 bus. Synchronous sampling is initiated using a hardware trigger signal (such as a rising edge interrupt), with clock jitter ≤1ms. The main control MCU periodically sends zeroing commands to control all sensors to automatically zero under no-load conditions, eliminating the effects of temperature drift.

[0026] In a preferred embodiment, the electronic tag system uses a multi-antenna reader, with one reader deployed independently on each floor. During data reading, each shelf floor is divided into multiple virtual grids, and the reader polls the grids in the order of their numbers.

[0027] In practical applications, to reduce the reading range attenuation caused by metal interference in the metal mesh tag, a ferrite antimagnetic patch is used on the metal mesh. For curved mesh, the tag antenna uses flexible PCB material with a bending radius ≥5mm. The reader adjusts the transmission power (20-30dBm) in real time based on the tag response strength index (RSSI) to ensure a reading success rate ≥99%. If three consecutive readings fail, the power is increased by 3dBm and the positioning sensor is triggered for auxiliary verification. The polling interval is set to 50ms-200ms as required.

[0028] As a preferred embodiment, such as Figure 2 As shown, the server 103 includes a data access unit 301, an event recognition unit 302, and a lifespan prediction unit 303; The data access unit 301 is used to encapsulate the network version identification and signal strength data reported by the card reader, as well as the sensor data uploaded by the weight sensor, into a standardized message according to the timestamp and write it into the message queue. The event recognition unit 302 is used to perform sliding window analysis on instantaneous data in the message queue. When the same screen identification is lost in two consecutive polling cycles and the difference between the weight difference and the weight of a single screen is within a preset range, it determines that a screen retrieval event has occurred and updates the usage record of the corresponding screen. The lifespan prediction unit 303 is used to read the identity information and usage records in the usage records, output the remaining lifespan through a preset analysis model, and generate maintenance reminder data.

[0029] As a preferred embodiment, such as Figure 3 As shown, the event recognition unit 302 includes a dynamic threshold calculation module 3021 and a trigger judgment module 3022; The dynamic threshold calculation module 3021 is used to extract the energy value of a preset frequency band as an environmental interference index by decomposing the sensor signal through wavelet packet decomposition, dynamically adjust the weight difference threshold based on the environmental interference index, select the weight coefficient according to the screen material-sensitivity mapping table, and calculate the screen usage threshold according to the weight difference threshold, the weight coefficient and the signal attenuation compensation strategy. The trigger judgment module 3022 is used to perform multi-condition synchronous verification on the acquired data according to the screen version retrieval threshold. When the same screen version identity meets the electronic tag radio frequency signal loss and weight difference matching rules in two consecutive polling cycles, it is determined that a retrieval event has occurred and the usage record of the corresponding screen version is updated.

[0030] Specifically, the vibration signal is decomposed using wavelet packets to extract energy in the 150-400Hz frequency band. As an indicator of environmental interference, the weight difference threshold is dynamically adjusted according to the interference level. : when >0.3 m 2 / s 4 When this occurs, the anti-interference mode is triggered, and the threshold is relaxed to 1.2. .

[0031] A pre-stored screen printing material-sensitivity mapping table is used. The weighting coefficient k is selected based on the material identifier embedded in the RFID tag (e.g., metal = 0x01). In practice, for metal screen printing, k = 0.8 to reduce high-frequency vibration sensitivity; for non-metal screen printing, k = 1.2 to increase sensitivity.

[0032] The final output threshold is: .

[0033] To address signal fluctuations caused by interference or operational differences in complex industrial environments, and to further reduce the false positive rate while avoiding false negatives, a signal attenuation compensation strategy is introduced into the calculation of the screen access threshold. As a preferred embodiment, the signal attenuation compensation strategy is as follows: When the energy value of the preset frequency band extracted by wavelet packet decomposition exceeds the threshold and the attenuation rate of the RF signal of the electronic tag increases beyond the preset benchmark value per unit time, it is determined that a synchronization mutation has occurred. Based on the ratio of vibration energy to attenuation rate, a compensation coefficient is selected according to a preset ratio mapping rule, and the dynamic threshold is adjusted according to the compensation coefficient.

[0034] The above method can avoid the following two situations: 1. False judgment: The RFID signal is briefly lost under high noise, but the screen is not used; 2. False judgment: The signal attenuates too quickly when it is used quickly and is ignored because it does not reach the fixed threshold.

[0035] By relaxing the threshold in high-interference environments, signal loss due to vibration and noise is avoided. In rapid access scenarios, a strict threshold is maintained to ensure that fast operations can be captured, further improving recognition accuracy.

[0036] For example, in a high-interference environment, the vibration energy in the 50-400Hz frequency band is E=0.8m. 2 / s4 , At this point, taking the compensation strength coefficient γ of the metal mesh as 0.5, we substitute it into the compensation formula: in, The base attenuation rate threshold is typically set to 0.3 dB / ms. The upper limit of vibrational energy, As a normalization factor, it limits the compensation range.

[0037] In some embodiments, the method for calculating the radio frequency signal attenuation rate of the electronic tag is as follows: Kalman filtering is applied to the RSSI sequence sent by the card reader to obtain a smooth signal. ; Calculate the signal gradient within a preset time window (e.g., 100 milliseconds). ; Using the signal gradient as input to the exponentially weighted moving average model, the radio frequency signal attenuation rate is calculated using the following formula: in, λ represents the baseline decay rate, and λ represents the control weight. It is used to smooth the instantaneous gradient of a signal and to quantize the signal decay rate.

[0038] In some embodiments, since metal mesh is susceptible to electromagnetic interference, the judgment result of RFID signal is given priority for metal mesh, while for non-metal mesh, since RFID is easily attenuated, the judgment result of weight sensor is given priority.

[0039] As a preferred embodiment, such as Figure 4 As shown, the lifespan prediction unit 303 includes a feature extraction module 3031, an analysis and reasoning module 3032, and a maintenance reminder module 3033; The feature extraction module 3031 is used to extract screen model, production batch, initial tension, cumulative number of uses and weight decay slope to form a multi-dimensional feature vector. The analysis and reasoning module 3032 is used to reason about the feature vector using the random forest regression algorithm to obtain the remaining lifetime and uncertainty; The maintenance reminder module 3033 is used to compare the remaining service life with the first cycle period and the second cycle period in a two-level threshold, generate maintenance reminder data of the corresponding level according to the comparison result, and send it to the user terminal.

[0040] In some embodiments, the smart shelf is also equipped with a temperature and humidity sensor to monitor the temperature and humidity data of the mesh storage environment; The feature extraction module is also used to extract the corrosion coefficient based on the feedback data from the temperature and humidity sensor and the screen material; the analysis and reasoning module dynamically adjusts the input weights based on the corrosion coefficient.

[0041] Specifically, corrosion coefficient In the formula, , , and All coefficients are material-related (the correlation coefficients differ between metal and non-metal screens). The corrosion coefficient, along with model, batch, initial tension, number of uses, and weight slope, are combined into a feature vector, which serves as input to the analytical inference model. The model uses the Gini coefficient to evaluate the importance ranking of features and employs a quantile random forest model for analysis, outputting a 10%-90% confidence interval for the remaining lifespan of the screen. For every 100 new usage records, the random forest weights are updated through incremental learning, prioritizing recent data (sliding window weight decay coefficient 0.9).

[0042] In some embodiments, a corresponding visualization application is installed on the user terminal, displaying the distribution of the shelving network panels and the remaining lifespan of each panel in the form of a heat map. Specific color gradients correspond to emergency (red), recommended (yellow), and normal (green) states; each state indicates the urgency of maintenance work.

[0043] This invention also provides a method for storing intelligent screen printing plates, implemented using the system described above, including: Assign a unique electronic tag to each webpage and write its basic information into it; The screen printing plates are stored on a smart shelf, and the storage location of the screen printing plates is obtained through weight sensors; The reader automatically identifies the inbound and outbound operations of the screen printing plate and records the usage history. Based on the historical usage and status data of each web version, the server generates usage records for each web version, predicts the remaining lifespan of each web version, and outputs maintenance prompts. When the network interface card (NIC) is in an abnormal state or nearing the end of its lifespan, a maintenance or replacement reminder will be sent through the user terminal.

[0044] The method in this embodiment achieves accurate storage, real-time monitoring, and efficient management of screen printing plates. It not only ensures accurate storage and usage records of the screen printing plates but also predicts their remaining lifespan through historical data analysis, issuing maintenance and replacement reminders in advance. This effectively avoids production stoppages and quality fluctuations caused by screen printing plate wear and tear or improper placement.

[0045] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. An intelligent net edition deposit system, characterized in that, The application relates to a system for monitoring the service life of a screen printing plate, which comprises the following parts: an intelligent shelf provided with a weight sensor for storing a screen printing plate, detecting the storage position of the screen printing plate and placing the weight; an electronic tag system, which comprises an electronic tag arranged on each screen printing plate and a card reader arranged on the intelligent shelf, the card reader being used for reading the electronic tag information in a periodic polling mode and uploading the electronic tag information to a server; the server is in communication connection with the intelligent shelf and the electronic tag system, and is used for receiving the screen printing plate identity and signal strength data sent by the card reader and the sensing data sent by the weight sensor; according to the received data, the service life of each screen printing plate is recorded and predicted, and maintenance prompt information is output; a user terminal is in communication connection with the server, and is used for inquiring the screen printing plate information, receiving the service life prediction result and the maintenance prompt information. The server comprises a data access unit, an event identification unit and a service life prediction unit; The data access unit is used for uniformly packaging the screen printing plate identity and signal strength data reported by the card reader and the sensing data uploaded by the weight sensor into a standardized message according to a time stamp and writing the standardized message into a message queue; The event identification unit is used for performing sliding window analysis on the instantaneous data in the message queue, determining that a screen printing plate taking event occurs when the same screen printing plate identity is lost in two continuous polling periods and the difference between the weight difference and the calibrated weight of a single screen printing plate is within a preset range, and updating the service record of the corresponding screen printing plate; The service life prediction unit is used for reading the identity information and the service record in the service record, outputting the residual service life through a preset analysis model, and generating the maintenance prompt information. The event identification unit comprises a dynamic threshold calculation module and a trigger judgment module; 2. The smart net version storage system according to claim 1, characterized in that, The dynamic threshold calculation module is used for decomposing the sensing signal through a wavelet packet, extracting the energy value of a preset frequency band as an environmental interference index, dynamically adjusting the weight difference threshold based on the environmental interference index, selecting a weight coefficient according to the screen printing plate material-sensitivity mapping table according to the screen printing plate identity, and calculating the screen printing plate taking threshold according to the weight difference threshold, the weight coefficient and a signal attenuation compensation strategy; The trigger judgment module is used for performing multi-condition synchronous verification on the acquired data according to the screen printing plate taking threshold, determining that a taking event occurs when the same screen printing plate identity satisfies the electronic tag radio frequency signal loss and the weight difference matching rule in two continuous polling periods, and updating the service record of the corresponding screen printing plate. The signal attenuation compensation strategy is as follows: When the energy value of the preset frequency band extracted through the wavelet packet decomposition exceeds the threshold value and the radio frequency signal attenuation rate of the electronic tag rises by more than a preset reference value within a unit time, it is determined that a synchronous mutation occurs; 3. The smart sheet music storage system of claim 2, wherein, According to the ratio of the vibration energy to the attenuation rate, a compensation coefficient is selected according to a preset ratio mapping rule, and the dynamic threshold is adjusted according to the compensation coefficient. The calculation method of the radio frequency signal attenuation rate of the electronic tag is as follows: The RSSI sequence sent by the card reader is subjected to Kalman filtering to obtain a smooth signal; 4. The smart sheet music storage system of claim 3, wherein, The signal gradient in a preset time window is calculated; ​ ​ 5. The smart sheet music storage system of claim 4, wherein, ​ ​ ​ The signal gradient is taken as an input of an exponential weighted moving average model to calculate a radio frequency signal attenuation rate, and a calculation formula is as follows: wherein denotes the reference decay rate, λ denotes the control weight, is the instantaneous gradient of the smoothed signal, which is used to quantify the signal decay rate.

6. The smart web storage system of claim 2, wherein, The life prediction unit comprises a feature extraction module, an analysis inference module and a maintenance reminding module; The feature extraction module is configured to extract screen model, manufacturing batch, initial tension, cumulative use frequency and weight attenuation slope to form a multi-dimensional feature vector; The analysis inference module is configured to infer the feature vector by using a random forest regression algorithm to obtain residual service life and uncertainty; The maintenance reminding module is configured to compare the residual service life with a first cycle period and a second cycle period by two-level threshold comparison, generate maintenance reminding data of a corresponding level according to a comparison result, and send the maintenance reminding data to a user terminal.

7. The smart sheet storage system of claim 6, wherein, The intelligent shelf is further provided with a temperature and humidity sensor for monitoring temperature and humidity data of a screen storage environment. The feature extraction module is further configured to extract a corrosion coefficient according to feedback data of the temperature and humidity sensor and screen material; and the analysis inference module dynamically adjusts an input weight according to the corrosion coefficient.

8. The smart web storage system of claim 1, wherein, The weight sensor on the intelligent shelf adopts a strain gauge type weighing sensor, and a silica gel buffer pad is additionally arranged between the weight sensor and a shelf panel to suppress high-frequency vibration noise.

9. The smart web storage system of claim 1, wherein, The card reader of the electronic tag system adopts a multi-antenna card reader, and one card reader is independently arranged on each layer; when data is read, each layer of the shelf is divided into multiple virtual grids, and the card reader is polled according to the numbering order of the virtual grids.

10. A method for storing intelligent network versions, implemented using the system according to any one of claims 1 to 9, characterized in that Comprise: A unique electronic tag is allocated to each screen, and basic information of the screen is written; The screen is stored on the intelligent shelf, and the storage position of the screen is obtained by the weight sensor; The in-out operation of the screen is automatically recognized by the reader-writer, and the use record is recorded; The server generates the use record of each screen based on the historical use data and state data of the screen, predicts the residual service life of each screen, and outputs the maintenance prompt information; When the screen state is abnormal or the service life is approaching, the user terminal sends a maintenance reminder or a replacement reminder.

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