Automatic control storage medium destroying machine and sorting system based on RFID and artificial intelligence

Abstract

The invention relates to the technical field of storage medium sorting, in particular to an automatic control storage medium destroying machine and sorting system based on RFID and artificial intelligence, and integrates core modules of automatic identification and intelligent sorting, multi-stage crushing and adjusting, effect evaluation and optimization and the like. The system realizes rapid identification and accurate classification of the storage medium through RFID, and improves the sorting automation and safety. The multi-stage crushing and adjusting module can monitor the mechanical state of the primary knife roll in real time and perform self-adaptive adjustment for abnormity, so that stable operation and energy consumption optimization of the equipment are effectively guaranteed; the system gives full play to the advantages of RFID and AI algorithms, realizes efficient, intelligent and stable storage medium sorting and crushing treatment, remarkably improves the operation automation level and the safety protection capability, reduces the risk of manual intervention and equipment failure, and improves the working efficiency. Good popularization and application prospects are realized.

Description

Technical Field

[0001] This invention relates to the field of storage medium sorting technology, and in particular to an automatic control storage medium destruction machine and sorting system based on RFID and artificial intelligence. Background Technology

[0002] In existing technologies, the destruction of storage media such as paper materials, hard drives, solid-state drives, magnetic tapes, and optical discs often employs methods such as physical shredding, magnetic field demagnetization, and overwriting / erasing. Some solutions utilize RFID technology for identification and tracking of storage media, using RFID tags for information collection and management. Sorting systems can classify media manually or semi-automatically based on media type and security level, combining machine vision and artificial intelligence technologies to achieve automatic identification and sorting of media types. RFID identification results can be combined with AI algorithms to automatically allocate media to the corresponding destruction devices. Regarding destruction equipment, existing technologies have developed various types of physical destruction equipment such as hard drive shredders, solid-state drive shredders, and magnetic tape shredders, as well as equipment integrating demagnetization devices and automatic feeding / unloading structures, supporting automated and continuous destruction operations.

[0003] For example, Chinese invention patent application CN115254634A discloses an RFID-based airport baggage sorting management method, equipment, and storage medium, including the following steps: equipping each piece of baggage with an RFID tag, the RFID tag storing corresponding flight information; equipping sorting staff with wearable RFID transceivers, which store at least one flight information, reading the RFID signals fed back by the RFID tags on the baggage within range, determining whether the received flight information successfully matches any stored flight information, and issuing a prompt to the sorting staff; confirming that the sorting staff has picked up the baggage and then using the wearable RFID transceiver to transmit the current baggage's flight information in another frequency band; setting up several baggage check-in devices, each equipped with a first RFID reader storing the flight information corresponding to the baggage check-in device, used to read the RFID signals emitted by the wearable RFID transceiver, and determining whether the received flight information successfully matches the corresponding stored flight information, and issuing a prompt to the sorting staff.

[0004] For example, Chinese invention patent CN113499997B discloses a sorting method, a sorting control device, a sorting system, and a storage medium. The method includes: responding to a feeding operation and determining a target feeding device corresponding to the feeding operation; based on the matching relationship between the feeding device and a partition, determining a target partition in the sorting device that matches the target feeding device, wherein the sorting device includes at least two partitions, each partition including at least one sorting component and a reciprocating component corresponding to the at least one sorting component; and controlling a sorting component in the target partition to deliver the item provided by the target feeding device to a container carried by the reciprocating component corresponding to the sorting component.

[0005] The aforementioned technologies suffer from at least the following technical problems: Traditional automated sorting and destruction systems for storage media are susceptible to low reliability during the RFID identification phase due to factors such as metal shielding, tag damage, and signal interference. Furthermore, they rely solely on single tag data, lacking multi-parameter fusion analysis, making it difficult to detect anomalies promptly and leading to sorting errors or missed detections. Automated sorting processes generally rely on manual or semi-automatic operation, resulting in limited sorting efficiency and anomaly response capabilities, and a lack of real-time linkage and feedback mechanisms between systems. Additionally, the pulverization process typically operates with fixed parameters, lacking real-time acquisition and comprehensive monitoring of multi-dimensional mechanical parameters such as equipment vibration, speed, and displacement. This makes early detection and adaptive adjustment of equipment anomalies difficult, posing a risk of downtime. Moreover, pulverization effect evaluation largely depends on single sensor readings or human experience, lacking systematic and quantifiable evaluation methods and closed-loop optimization mechanisms. This makes it difficult to consistently achieve the required pulverized particle size, and overall safety and full-process traceability are difficult to guarantee due to the lack of automated data recording and risk linkage protection. Summary of the Invention

[0006] To address the technical problems of low sorting accuracy and difficulty in quantifying the crushing effect in existing technologies, this invention provides an automated storage media destruction machine and sorting system based on RFID and artificial intelligence. The technical solution is as follows: On the one hand, an automatic control storage medium sorting system based on RFID and artificial intelligence is provided, including: an automatic identification and intelligent sorting module, which is used to identify the storage medium after it has been identified by RFID, and to classify the storage medium based on the RFID identification results. The classification process includes normal sorting and abnormal sorting. The multi-stage crushing and adjustment module is used to crush the primary cutter rollers after normal sorting, while monitoring the crushing process parameters of the primary cutter rollers to determine whether there are mechanical abnormalities in the primary cutter rollers, and to adaptively adjust the primary cutter rollers with abnormalities. The effect evaluation and optimization module is used to evaluate the crushing effect of the storage medium after being crushed by the primary cutter roller, and to determine whether the crushing effect of the primary cutter roller meets the standard. If the crushing effect of the primary cutter roller does not meet the standard, the primary cutter roller and the next stage cutter roller are optimized and adjusted. At the same time, the crushing effect of the storage medium before the final cutter roller is predicted to determine whether the crushing effect of the storage medium can reach the target particle size. If the crushing effect of the storage medium cannot reach the target particle size, the final cutter roller is optimized and controlled.

[0007] On the other hand, an automated storage media destruction machine based on RFID and artificial intelligence is provided, including a sorting mechanism, multi-stage cutting rollers, and a control module. The sorting mechanism is used to automatically classify and sort storage media based on RFID identification and intelligent analysis, guiding different types of storage media into the corresponding processing channels. The multi-stage cutting rollers are used to perform step-by-step crushing of the sorted storage media, gradually pulverizing them to the target particle size for complete destruction. The control module is used to monitor and adaptively adjust the operating parameters of the multi-stage cutting rollers in real time based on the operating status parameters and anomaly detection results, so as to ensure the safety and stability of the crushing process.

[0008] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following: (1) This invention provides an automated storage media destruction machine and sorting system based on RFID and artificial intelligence. Through RFID and artificial intelligence-driven automatic identification and sorting, it achieves batch, precise, and full-process traceability of storage media without human intervention, effectively preventing abnormal media from flowing into subsequent processing stages. The multi-level crushing and adaptive adjustment strategy, based on real-time physical quantity monitoring and abnormal threshold judgment, ensures that the cutting roller always operates stably and efficiently under different media and load conditions, significantly reducing the probability of equipment malfunction and downtime. Combined with multi-parameter intelligent effect evaluation and closed-loop optimization control, it not only greatly improves the crushing quality and target particle size compliance rate, but also further realizes dynamic response and self-protection for complex working conditions. The system greatly improves the automation, intelligence, and security of storage media processing, and has significant engineering promotion and industrial application value.

[0009] (2) The automatic identification and intelligent sorting module uses RFID technology to accurately identify each storage medium and automatically acquire its physical and logical attributes. Combined with artificial intelligence algorithms, it judges the medium category, status and risk characteristics in real time to realize batch automatic sorting and status traceability. When RFID identifies special marks or abnormal information, the system automatically diverts the storage medium to the abnormal processing channel, effectively avoiding high-risk media from mixing into the normal process, greatly improving the sorting accuracy and the security of the whole process, while significantly reducing the pressure of manual verification and the probability of misoperation.

[0010] (3) The multi-stage crushing and adjustment module adopts a multi-stage series design of cutter rollers, which can crush different types and structures of storage media layer by layer. The system dynamically calculates the mechanical anomaly index by collecting multi-dimensional physical quantities such as impact power spectral density, motor drive current harmonic energy ratio and motor flux fluctuation in real time on the primary cutter roller. Once an anomaly is detected in the cutter roller (such as exceeding the first mechanical anomaly threshold), the speed, feeding speed and reversal time are immediately adjusted adaptively to actively avoid the risk of equipment overload or damage and ensure the continuous and efficient operation of the whole machine. Compared with traditional set value control, it significantly improves the system's adaptability to complex working conditions and media differences.

[0011] (4) The effect evaluation and optimization module calculates the primary crushing effect index in real time for the storage medium after primary crushing by integrating the impact power spectral density ratio factor, the motor drive current harmonic energy ratio ratio factor, and the motor flux fluctuation ratio factor, and compares it with the primary crushing effect threshold. When the primary crushing effect is found to be substandard, the intelligent linkage increases the feeding speed, the rotation speed of the next stage cutter roller and the primary cutter roller, and the reversal time. At the same time, it monitors the mechanical risk index of the primary cutter roller throughout the process and dynamically adjusts the optimization range to avoid the equipment exceeding the limit. This closed-loop evaluation and parameter adaptive adjustment mechanism enables the system to cope with different media states and feeding fluctuations, continuously ensuring that the final crushed particle size meets the target, improving the consistency of output and production stability. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a schematic diagram of the structure of an automatic control storage medium sorting system based on RFID and artificial intelligence provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the RFID identification and primary cutter roller abnormality classification processing flow provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the primary pulverization effect evaluation and adaptive optimization process provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of the final stage crushing effect prediction and rigid target achievement closed-loop control process provided in the embodiments of the present invention; Figure 5 This is a schematic diagram of the display screen of the automatic control storage medium destruction machine provided in an embodiment of the present invention; Figure 6 This is a schematic diagram of the main structure of the first destruction mechanism provided in an embodiment of the present invention.

[0014] The reference numerals in the attached figures include: First cutter roller 1; second cutter roller 2; third cutter roller 3; fourth cutter roller 4. Detailed Implementation

[0015] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0016] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0017] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0018] On the one hand, embodiments of the present invention provide an automated control storage medium sorting system based on RFID and artificial intelligence, such as... Figure 1 The schematic diagram shown is of an automated control storage media sorting system based on RFID and artificial intelligence, which includes: an automatic identification and intelligent sorting module, a multi-stage crushing and adjustment module, an effect evaluation and optimization module, and a control database.

[0019] The automatic identification and intelligent sorting module is connected to the multi-stage crushing and adjustment module, and the multi-stage crushing and adjustment module is connected to the effect evaluation and optimization module. The automatic identification and intelligent sorting module, the multi-stage crushing and adjustment module, and the effect evaluation and optimization module are all connected to the control database. The control database is used to store various parameters involved in the automatic control storage medium sorting system based on RFID and artificial intelligence.

[0020] like Figure 5 As shown in the schematic diagram of the display screen of the automatic control storage medium destruction machine provided in this embodiment of the invention, the automatic control storage medium destruction machine is currently displayed in paper destruction mode. There are manual mode buttons and return buttons at the bottom. The default state is automatic mode. Clicking can switch between automatic and manual modes.

[0021] Specifically, the storage medium is classified based on the RFID identification results. The specific analysis process is as follows: Key parameters for RFID identification of the storage medium are obtained, including tag return signal strength, signal reading phase, and consistency of multiple tag reading results. The RFID identification confidence level is obtained by weighted fusion calculation of the tag return signal strength, signal reading phase, and consistency of multiple tag reading results. The RFID identification confidence level represents the reliability and trustworthiness of the target tag's successful identification and accurate classification. The tag return signal strength characterizes the strength and stability of the tag signal transmission, directly reflecting the coupling state and physical integrity between the tag and the reader, and can be obtained by the RFID reader in real time after each response. The signal reading phase refers to the RFID reader's response when receiving the radio frequency signal reflected back from the tag. The phase difference of this signal relative to the carrier wave transmitted by the reader is used to analyze the spatial state and environmental interference of the tag's response signal, reflecting minute changes in the tag's distance and angle. This can be directly obtained through an RFID reader that supports phase acquisition. The consistency of multiple tag readings is used to measure the stability of the tag's data return in multiple identifications. It can effectively detect potential problems such as tag anomalies and environmental changes. This is obtained by statistically analyzing the ratio of the number of times the tag is successfully identified to the total number of attempts within a set time window. The RFID identification confidence level is obtained by weighted fusion calculation. This refers to the normalization of the tag's returned signal strength, the signal reading phase, and the consistency of multiple tag readings, and then summing them according to set weights. The weight values ​​can be adjusted according to different scenario requirements, thereby achieving a quantitative evaluation of the tag's actual identifiability and reliability.

[0022] The RFID identification confidence level is compared with the preset RFID identification confidence level threshold in the control database to determine whether there is any abnormal tag data in the RFID identification storage medium. The RFID identification confidence level threshold represents the minimum allowable value of the RFID identification confidence level within the specified range. When the RFID identification confidence level is not lower than the RFID identification confidence level threshold, it is determined that there is no abnormal tag data in the RFID identification storage medium, and normal sorting is performed. When the RFID identification confidence level is lower than the RFID identification confidence level threshold, it is determined that there is abnormal tag data in the RFID identification storage medium, and anomaly handling is performed.

[0023] The aforementioned normal sorting process refers to the system automatically classifying media according to the attributes corresponding to the tags (such as media type, security level, storage batch, etc.) and guiding the media into subsequent standardized processing flows (such as multi-stage shredding, standardized transmission, statistical warehousing, etc.), achieving unmanned, efficient, and accurate sorting operations. This process ensures the automation and batch processing efficiency of sorting, effectively reducing the risk of human error and misjudgment. The aforementioned abnormal handling refers to the system automatically diverting the storage media to the abnormal handling channel and suspending its entry into subsequent automatic processes. For data with abnormal tags, the system can automatically trigger emergency measures such as manual review, supplementary scanning, manual registration, and secondary identification. If necessary, it can generate an abnormal report and issue an alarm to prevent unqualified or suspicious media from flowing into the normal processing link, ensuring system security and data integrity from the source.

[0024] Through the aforementioned hierarchical sorting and processing mechanism, the system can significantly improve the accuracy and robustness of RFID automatic sorting, achieve early identification and isolation of abnormal tags, and comprehensively ensure the safety and efficient management of media throughout the entire process.

[0025] Specifically, the crushing process parameters of the primary cutter roller are monitored, and the analysis process is as follows: These parameters include the high-frequency vibration acceleration of the primary cutter roller, the micro-displacement of the bearing housing, and the instantaneous rotational speed deviation. A weighted average fusion algorithm is used to synthesize a mechanical anomaly index for the primary cutter roller, which quantifies the degree of mechanical anomaly during the crushing process. The high-frequency vibration acceleration reflects the dynamic vibration intensity of the primary cutter roller under high-frequency impact and cutting anomalies, and can be obtained through acceleration sensors and frequency domain analysis. The micro-displacement of the bearing housing quantifies the relative displacement change between the primary cutter roller bearing housing and its mounting base. High-precision monitoring can be achieved through displacement sensors; instantaneous speed deviation is used to dynamically monitor the difference between the actual real-time speed of the primary cutter roller and the set target speed. This is obtained by measuring the actual real-time speed of the primary cutter roller using a rotary encoder and then performing difference processing with the set target speed. These three parameters together constitute important characteristic parameters for the mechanical health and anomaly detection of the primary cutter roller. The aforementioned synthesis of the primary cutter roller mechanical anomaly index using a weighted average fusion algorithm refers to normalizing the high-frequency vibration acceleration of the primary cutter roller, the micro-displacement of the bearing housing, and the instantaneous speed deviation, and then calculating the primary cutter roller mechanical anomaly index using a weighted average fusion algorithm. The weights of each characteristic parameter are set according to the sensitivity to mechanical anomalies and the actual failure rate. The three are weighted and summed to obtain the primary cutter roller mechanical anomaly index, which quantitatively characterizes the mechanical health status of the primary cutter roller, enabling sensitive detection and early warning of anomalies during the crushing process.

[0026] The mechanical anomaly index of the primary cutter roller is compared with the first mechanical anomaly threshold and the second mechanical anomaly threshold preset in the control database. The first mechanical anomaly threshold is used to distinguish between the smooth operation and the slight abnormal state of the primary cutter roller, and the second mechanical anomaly threshold is used to define the safety limit of the mechanical anomaly of the primary cutter roller.

[0027] Furthermore, adaptive adjustment is performed on the primary cutter roller exhibiting abnormalities. The specific adjustment process is as follows: when the mechanical abnormality index of the primary cutter roller is below the first mechanical abnormality threshold, the primary cutter roller is considered to be operating smoothly, and its current operating parameters are maintained without adaptive adjustment. When the mechanical abnormality index of the primary cutter roller is not lower than the first mechanical abnormality threshold but is lower than the second mechanical abnormality threshold, the primary cutter roller is considered to be in a slightly abnormal state, and adaptive adjustment is performed simultaneously. When the mechanical abnormality index of the primary cutter roller is not lower than the second mechanical abnormality threshold, the degree of mechanical abnormality of the primary cutter roller is considered to have reached the safety limit, and mandatory safety protection measures are automatically executed. These automatic mandatory safety protection measures include, but are not limited to: automatic shutdown, disconnection of power supply, locking of control circuits, issuance of audible and visual alarms and remote alarms, saving of abnormal data, and prohibition of equipment restart, until manual safety review and unlocking. This measure effectively prevents equipment damage, personal injury, or process loss due to severe mechanical abnormalities, ensuring the inherent safety of the system operation.

[0028] The primary cutter roller is adaptively adjusted as follows: based on the mechanical abnormality index of the primary cutter roller and the first mechanical abnormality threshold, the abnormal deviation value is obtained. At the same time, based on the abnormal deviation value, the rotation speed of the primary cutter roller is reduced, and the sorting feed speed and the reversal time of the primary cutter roller are reduced simultaneously. The rotation speed, sorting feed speed and reversal time are linked parameters and are integrated adaptively adjusted.

[0029] The aforementioned acquisition of abnormal deviation values ​​refers to subtracting the first mechanical abnormality threshold from the primary cutter roller mechanical abnormality index. The specific adjustment process for the aforementioned integrated adaptive adjustment is as follows: ; ; In the formula, a is the downward adjustment coefficient, D is the abnormal deviation value, and D max The result of subtracting the first mechanical anomaly threshold from the second mechanical anomaly threshold, a max The maximum allowable adjustment range coefficient of the system, the specific value of which shall be determined by professionals in the field, n0 is the current rotational speed of the primary cutter roller, v0 is the current sorting feed speed, t0 is the current reversal time of the primary cutter roller, and n new v is the rotational speed of the primary cutter roller after adjustment. new To adjust the sorting feed rate, t newThe reverse rotation time after adjusting the primary cutter roller is given. Substituting the obtained abnormal deviation value into the formula yields the adjusted sorting feed speed, primary cutter roller speed, and reverse rotation time. The parameter reduction range is automatically adjusted based on the abnormal deviation value. The three key operating parameters—speed, sorting feed speed, and reverse rotation time—are linked together, which can effectively suppress mechanical abnormalities in the early stage and improve system stability. This significantly reduces the risk of misadjustment, overadjustment, and secondary abnormalities, and improves the level of equipment automation and intelligent operation and maintenance. It has extremely high engineering practicality and innovative value.

[0030] like Figure 2 As shown in the schematic diagram of the RFID identification and primary cutter roller anomaly classification processing flow provided in this embodiment of the invention, the RFID identification confidence level is first obtained, and it is determined whether it is lower than a preset RFID identification confidence level threshold. If the RFID identification confidence level is lower than the RFID identification confidence level threshold, the system directly enters the anomaly processing flow to prevent unreliable tag identification storage media from mistakenly entering subsequent stages; otherwise, the system performs normal sorting processing. After entering the sorting flow, the system further obtains the primary cutter roller mechanical anomaly index and compares it with the first mechanical anomaly threshold and the second mechanical anomaly threshold. If the primary cutter roller mechanical anomaly index is lower than the first mechanical anomaly threshold, it is determined that the primary cutter roller is running smoothly and the current operating parameters remain unchanged; if the primary cutter roller mechanical anomaly index is between the first mechanical anomaly threshold and the second mechanical anomaly threshold, it is identified as a mild anomaly state, and the system intelligently reduces the sorting feed speed, the primary cutter roller rotation speed, and the reversal time based on the anomaly deviation value to achieve adaptive anomaly control; if the primary cutter roller mechanical anomaly index is not lower than the second mechanical anomaly threshold, it is determined that the safety limit has been reached, and the system immediately executes mandatory safety protection measures.

[0031] Specifically, the pulverization effect of the storage medium after primary pulverization is evaluated. The evaluation process is as follows: the impact power spectral density ratio factor, motor drive current harmonic energy ratio ratio factor, and motor flux fluctuation ratio factor of the primary pulverization roller are obtained. By pre-setting the effect coefficients corresponding to the impact power spectral density ratio factor, motor drive current harmonic energy ratio ratio factor, and motor flux fluctuation ratio factor in the control database, their weight contribution values ​​to the primary pulverization effect index are quantified. Finally, a weighted average fusion algorithm is used to synthesize the primary pulverization effect index, where the primary pulverization effect index indicates whether the pulverization effect of the storage medium after primary pulverization by the primary pulverization roller has reached the target primary pulverization effect.

[0032] The impact power spectral density scaling factor represents the ratio of the impact power spectral density to the defined impact power spectral density; the motor drive current harmonic energy ratio scaling factor represents the ratio of the motor drive current harmonic energy ratio to the defined motor drive current harmonic energy ratio; and the motor flux linkage fluctuation scaling factor represents the ratio of the motor flux linkage fluctuation value to the defined motor flux linkage fluctuation value.

[0033] The aforementioned impact power spectral density refers to the distribution intensity of high-frequency energy in the vibration signal of the cutter roller, reflecting abnormal events such as mechanical impact and agglomerate passage during the crushing process. Vibration data can be continuously collected in real time using an accelerometer, and then the signal is decomposed into different frequency bands using spectral analysis. The mean power spectral density is obtained by selecting the high-frequency region (e.g., above 100Hz). The harmonic energy of the motor drive current is used to reflect the stability of the motor load and impact anomalies. Higher harmonic energy indicators can be obtained through current transformers and harmonic decomposition. The motor flux fluctuation value refers to the amplitude of the motor flux change over a period of time, used to characterize the stability of the motor load. The value of the main motor flux is output in real time by a vector control inverter, and the standard deviation of the flux within a time window (e.g., 1 second) can be used to reflect the magnitude of the motor flux fluctuation. The combination of these three factors can quantify the dynamic anomalies of the primary cutter roller crushing process from multiple dimensions, providing basic data support for subsequent crushing effect evaluation and intelligent optimization. The impact power spectral density, motor drive current harmonic energy, and motor flux fluctuation value reflect the stability and uniformity of the crushing process from three dimensions: mechanical vibration, electrical disturbance, and electromagnetic load, respectively. The real-time monitoring and joint judgment of these three systems can sensitively detect process abnormalities, sudden load changes, and equipment health status, ensuring that the pulverization effect is always in the optimal range. This is the core parameter support for achieving high-quality intelligent pulverization and process compliance.

[0034] The above definition of impact power spectral density indicates the maximum allowable value of impact power spectral density within the specified range; the above definition of motor drive current harmonic energy ratio indicates the maximum allowable value of motor drive current harmonic energy ratio within the specified range; the above definition of motor flux linkage fluctuation value indicates the maximum allowable value of motor flux linkage fluctuation value within the specified range.

[0035] Impact power spectral density, motor drive current harmonic energy, and motor flux linkage fluctuation are closely related during the primary roller crushing process. Specifically, when the roller encounters large pieces of material, agglomerates, or abnormal mechanical impacts, the mechanical system generates high-frequency vibrations, leading to an increase in impact power spectral density. Simultaneously, sudden changes in mechanical load significantly enhance the high-order harmonic components in the motor output current, resulting in increased harmonic energy in the motor drive current. Load fluctuations further affect the electromagnetic state inside the motor, causing a corresponding increase in flux linkage fluctuation. These three parameters often increase synchronously under abnormal operating conditions such as mechanical impact and load disturbance. By jointly analyzing these three parameters, multi-angle, end-to-end high-sensitivity detection of crushing anomalies can be achieved, thereby improving the equipment's intelligent diagnostic and anomaly response capabilities.

[0036] When the cutting roller encounters large pieces of material, agglomerates, or experiences mechanical impact during the crushing process, the impact power spectral density proportionality factor increases significantly, directly reflecting abnormal vibration and uneven cutting in the mechanical system. Simultaneously, sudden changes in mechanical load lead to an increase in the motor output current harmonic energy proportionality factor, indicating that the electrical system is affected by the impact and generates higher-order harmonics. Furthermore, this load fluctuation also causes dynamic fluctuations in the motor flux linkage, causing the motor flux linkage fluctuation proportionality factor to rise synchronously. These three factors often exhibit synchronicity and positive correlation; they collectively affect the primary crushing effect index: an increase in any one of these proportionalities will decrease the primary crushing effect index.

[0037] The specific evaluation process for the primary pulverization effect index is as follows: ; In the formula, PCEI is the primary crushing effect index, IPSDR is the impact power spectral density proportionality factor, MDCH is the motor drive current harmonic energy ratio proportionality factor, MFLF is the motor flux fluctuation proportionality factor, gp is the effect coefficient corresponding to the impact power spectral density proportionality factor preset in the control database, gm is the effect coefficient corresponding to the motor drive current harmonic energy ratio proportionality factor preset in the control database, and gf is the effect coefficient corresponding to the motor flux fluctuation proportionality factor preset in the control database.

[0038] The effect coefficients corresponding to the aforementioned impact power spectral density scaling factor represent the magnitude change in the primary crushing effect index caused by a one-unit change in the impact power spectral density scaling factor, and are used to quantify the influence weight of the impact power spectral density scaling factor on the primary crushing effect index. Similarly, the effect coefficients corresponding to the aforementioned motor drive current harmonic energy ratio scaling factor represent the magnitude change in the primary crushing effect index caused by a one-unit change in the motor drive current harmonic energy ratio scaling factor, and are used to quantify the influence weight of the motor drive current harmonic energy ratio scaling factor on the primary crushing effect index. Finally, the effect coefficients corresponding to the aforementioned motor flux fluctuation scaling factor represent the magnitude change in the primary crushing effect index caused by a one-unit change in the motor flux fluctuation scaling factor, and are used to quantify the influence weight of the motor flux fluctuation scaling factor on the primary crushing effect index.

[0039] The control database stores the mapping relationships between the impact power spectral density scaling factor and its corresponding effect coefficient, the motor drive current harmonic energy ratio scaling factor and its corresponding effect coefficient, and the motor flux fluctuation scaling factor and its corresponding effect coefficient. In this embodiment, the mapping relationship is a mapping table. For example, when the impact power spectral density scaling factor, the motor drive current harmonic energy ratio scaling factor, and the motor flux fluctuation scaling factor are input into the control database, the control database can match the corresponding effect coefficients of the impact power spectral density scaling factor, the motor drive current harmonic energy ratio scaling factor, and the motor flux fluctuation scaling factor based on the preset mapping relationship table. The numerical range of each effect coefficient is strictly controlled between 0 and 1.

[0040] The primary crushing effect index is compared with the preset primary crushing effect threshold in the control database to determine whether the crushing effect of the primary crushing roller meets the standard. The primary crushing effect threshold represents the minimum value of the primary crushing effect index within the specified range.

[0041] Specifically, the process for determining whether the primary crushing effect of the primary cutter roller meets the standard is as follows: when the primary crushing effect index is lower than the primary crushing effect threshold, the primary cutter roller is deemed to have a substandard crushing effect, and the primary cutter roller and the next stage cutter roller are optimized and adjusted; when the primary crushing effect index is not lower than the primary crushing effect threshold, the primary cutter roller is deemed to have a standard crushing effect, and the crushing process proceeds normally.

[0042] Furthermore, the primary cutter roller and the next-stage cutter roller are optimized and adjusted. The specific adjustment process is as follows: The primary crushing effect index and the primary crushing effect threshold are used to obtain the primary crushing deviation value. The next stage cutter roller is then integrated and adaptively adjusted based on the primary crushing deviation value. Specifically, the rotation speed of the next stage cutter roller is increased, and the sorting feed speed and the reversal time of the next stage cutter roller are increased simultaneously. At the same time, the primary cutter roller is again integrated and adaptively adjusted based on the primary crushing deviation value. Specifically, the rotation speed and reversal time of the primary cutter roller are increased.

[0043] The aforementioned acquisition of the primary crushing deviation value refers to subtracting the primary crushing effect index from the primary crushing effect threshold; the aforementioned integrated adaptive adjustment of the next-stage cutter roller is specifically performed as follows: ; ; In the formula, b is the adjustment coefficient of the next-stage cutter roller, E is the primary crushing deviation value, RE is the primary crushing effect threshold, and b max The maximum adjustment range coefficient of the next-level cutter roller allowed by the system; the specific value shall be determined by professionals in this field, n. 01v is the current rotational speed of the next stage cutter roller. 01 t represents the current sorting and feeding speed. 01 n represents the current reversal time of the next stage cutter roller. new1 v is the rotational speed after adjustment of the next stage cutter roller. new1 To adjust the sorting feed rate, t new1 The reversal time after adjusting the next-stage cutter roller is given. Substituting the obtained primary crushing deviation value into the formula yields the adjusted sorting feed speed, the adjusted rotation speed of the next-stage cutter roller, and the reversal time. By performing integrated adaptive adjustment of the next-stage cutter roller, multiple key parameters of the next-stage cutter roller can be intelligently and synchronously improved as needed based on actual crushing effect differences. This significantly enhances the adaptability and automatic optimization capability of the crushing system, effectively ensuring that the particle size of the end product meets the standards and the processing consistency, reducing manual intervention and the occurrence rate of anomalies, and improving the system's intelligence and engineering promotion value.

[0044] During the optimization and adjustment of the primary cutter roller, the primary cutter roller mechanical anomaly index is monitored in real time and marked as the primary cutter roller mechanical risk index. If the primary cutter roller mechanical risk index is less than the second mechanical anomaly threshold, optimization is carried out normally. If the primary cutter roller mechanical risk index is greater than or equal to the second mechanical anomaly threshold, the optimization range of the primary cutter roller is limited to the maximum allowable value when the corresponding primary cutter roller mechanical risk index is equal to the second mechanical anomaly threshold, so as to ensure the safety of system operation.

[0045] Specifically: ; ; ; In the formula, c is the adjustment amplitude coefficient of the primary cutter roller, Q is the primary crushing deviation value, RQ is the primary crushing effect threshold, and c max This is the maximum allowable adjustment range coefficient for the system; the specific value shall be determined by those skilled in the art. safe c is the maximum adjustment range coefficient of the primary cutter roll when the primary cutter roll mechanical risk index equals the second mechanical anomaly threshold. actual The final adjustment range coefficient for the primary cutter roller is determined by professionals in the field based on different situations. n1 is the current rotational speed of the primary cutter roller, t1 is the current reversal time of the primary cutter roller, and n... n1 The rotational speed of the primary cutter roller after adjustment, t n1This refers to the reversal time after the primary cutter roller is adjusted. If the mechanical risk index of the primary cutter roller is less than the second mechanical anomaly threshold, the adjustment range coefficient c of the primary cutter roller is used normally. If the mechanical risk index of the primary cutter roller is greater than or equal to the second mechanical anomaly threshold, the maximum adjustment range coefficient c of the primary cutter roller when the mechanical risk index of the primary cutter roller is equal to the second mechanical anomaly threshold is used. safe By substituting the obtained primary crushing deviation value into the formula, the rotational speed and reversal time of the primary cutter roller after adjustment can be obtained. By integrating the primary crushing effect deviation and mechanical risk as dual criteria, the intelligent on-demand integrated optimization of the cutter roller operating parameters avoids equipment overload, wear or safety accidents caused by pursuing effect, ensuring the inherent safety of the system. At the same time, it continuously improves the crushing quality under the premise of ensuring system safety, and has extremely high engineering promotion value and intelligent manufacturing application potential.

[0046] like Figure 3 As shown in the schematic diagram of the primary crushing effect evaluation and adaptive optimization process provided in this embodiment of the invention, the primary crushing effect index is obtained to determine whether the current crushing effect of the primary crushing roller is not lower than the primary crushing effect threshold requirement. If the primary crushing effect index is higher than the primary crushing effect threshold, it indicates that the crushing effect of the primary crushing roller meets the standard, and the system maintains the normal crushing operation process; if the primary crushing effect index is lower than the primary crushing effect threshold, it is determined that the crushing effect of the primary crushing roller does not meet the standard, and optimization and adjustment of the primary crushing roller and the next-level crushing roller are required. Specifically, the system increases the rotation speed of the next-level crushing roller based on the primary crushing effect deviation value, and simultaneously increases the sorting feeding speed and the reversal time of the next-level crushing roller. At the same time, the system performs integrated adaptive adjustment of the primary crushing roller again based on the primary crushing deviation value, specifically by increasing the rotation speed and reversal time of the primary crushing roller to improve the overall crushing capacity. Meanwhile, the system monitors the mechanical risk index of the primary crushing roller in real time during the optimization process. If the mechanical risk index of the primary crushing roller is less than the second mechanical anomaly threshold, optimization can proceed normally; otherwise, the optimization range is limited by the maximum allowable value to ensure the safe operation of the equipment. The entire process achieves adaptive control through closed-loop feedback, effectively ensuring the efficiency and stability of the crushing process.

[0047] Specifically, the analysis process for predicting the pulverization effect of the storage medium before the final-stage cutter roller is as follows: The pulverization effect attainment prediction index is obtained by weighted averaging of the impact power spectral density ratio factor of the multi-stage cutter rollers, the harmonic energy ratio ratio factor of the motor drive current, and the motor flux linkage fluctuation ratio factor. The specific evaluation method is consistent with the evaluation method of the primary pulverization effect index mentioned earlier. The pulverization effect attainment prediction index indicates the degree to which the storage medium can reach the corresponding target particle size after pulverization by the final-stage cutter roller. The methods for obtaining the impact power spectral density of the multi-stage cutter rollers, the harmonic energy ratio of the motor drive current, and the motor flux linkage fluctuation value are consistent with the methods for obtaining the impact power spectral density of the primary cutter rollers, the harmonic energy ratio of the motor drive current, and the motor flux linkage fluctuation value mentioned earlier.

[0048] The crushing effect compliance prediction index is compared with the preset crushing effect compliance prediction threshold in the control database. The crushing effect compliance prediction threshold represents the minimum value of the crushing effect compliance prediction index within the specified range.

[0049] Furthermore, the final-stage cutter roller is optimized and controlled. The specific control process is as follows: when the crushing effect attainment prediction index is not lower than the crushing effect attainment prediction threshold, it is determined that the crushing effect of the storage medium can reach the target particle size, and no optimization and control is performed on the final-stage cutter roller; when the crushing effect attainment prediction index is lower than the crushing effect attainment prediction threshold, it is determined that the crushing effect of the storage medium cannot reach the target particle size, and the final-stage cutter roller is optimized and controlled. The specific control process is as follows: based on the crushing effect attainment prediction index and the crushing effect attainment prediction threshold, the crushing effect attainment deviation value is obtained, and the rotation speed of the final-stage cutter roller is increased based on the crushing effect attainment deviation value, while the sorting feeding speed and the reversal time of the final-stage cutter roller are increased simultaneously.

[0050] The aforementioned method for obtaining the deviation value for achieving the crushing effect standard refers to subtracting the crushing effect standard prediction index from the crushing effect standard prediction threshold. The specific optimization and control of the final stage cutter roller is as follows: ; In the formula, A is the deviation value of the crushing effect, s is greater than 1 and is the exponential amplification factor, f1 is the parameter sensitivity of the final stage cutter roller speed, f2 is the parameter sensitivity of the sorting feed speed, f3 is the parameter sensitivity of the final stage cutter roller reversal time, the specific values ​​of f1, f2 and f3 are all determined by professional technicians, n3 is the current speed of the final stage cutter roller, v3 is the current sorting feed speed, t3 is the current reversal time of the final stage cutter roller, and n n3 v is the rotational speed of the final stage cutter roller after adjustment. n3 To adjust the staged feed rate, t n3 n is the reversal time after the final stage cutter roller is adjusted. 3max v is the safe limit value for the speed of the final stage cutter roller. 3maxThe safe limit value for sorting feed speed, t 3max The safe limit value for the reversal time of the final stage cutter roller is given. Substituting the obtained deviation value of the crushing effect into this formula, the adjusted sorting feed speed and the adjusted speed and reversal time of the final stage cutter roller can be obtained. In the process of optimizing and controlling the final stage cutter roller, the front-end sorting feed speed is a key coupling parameter between the overall system feed rate and the capacity of the final stage. An adaptive exponential adjustment mechanism consistent with the speed and reversal time of the final stage cutter roller can be adopted to ensure dynamic matching of the production line's capacity from feeding to final crushing, prevent material blockage and production line bottlenecks, and effectively improve the system's processing efficiency, crushing compliance rate and overall operational stability.

[0051] like Figure 4 The schematic diagram of the final-stage crushing effect prediction and rigid target achievement closed-loop control process provided in this embodiment of the invention is shown. This process, targeting the storage medium before the final-stage cutter roller, first performs a predictive analysis of the crushing effect, obtains a crushing effect target achievement prediction index, and compares it with a preset crushing effect target achievement prediction threshold in the system. If the crushing effect target achievement prediction index is not lower than the crushing effect target achievement prediction threshold, it indicates that the storage medium can reach the target particle size, and the process can end smoothly. Conversely, it indicates that the crushing effect cannot reach the target particle size, and the system will implement optimized control of the final-stage cutter roller. Specifically, during the optimization process, the system dynamically increases the sorting feed speed and the rotational speed and reversal time of the final-stage cutter roller based on the crushing effect target achievement deviation value.

[0052] On the other hand, embodiments of the present invention provide an automatic control storage medium destruction machine based on RFID and artificial intelligence, including a sorting mechanism, a multi-stage cutting roller, and a control module; the sorting mechanism is used to automatically classify and sort storage media according to RFID identification and intelligent analysis, guiding different types of storage media into corresponding processing channels; the multi-stage cutting roller is used to perform step-by-step crushing of the sorted storage media, gradually pulverizing them to the target particle size for complete destruction; the control module is used to monitor and adaptively adjust the operating parameters of the multi-stage cutting roller in real time based on the operating status parameters and abnormal detection results of the multi-stage cutting roller to ensure the safety and stability of the crushing process.

[0053] The following will refer to the appendices in the embodiments of this application. Figure 6 The technical solutions in the embodiments of this application are clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0054] It should be noted that, in the description of this invention, the terms primary cutter roller, next-stage cutter roller, and final-stage cutter roller, for ease of description and generality of technical solutions, can all refer to cutter roller assemblies of adjacent levels within the equipment. In the specific embodiments shown in this specification and accompanying drawings, the structure is a two-stage cutter roller system, i.e., the final-stage cutter roller is the next-stage cutter roller; however, this invention is also applicable to complex structural scenarios with three, four, or more stages of cutter rollers, and the relevant adaptive adjustment and optimization methods are equally feasible and effective in multi-stage cutter roller systems, without being limited by the number of cutter roller stages.

[0055] In this embodiment of the invention, the primary cutter roller refers to the first cutter roller 1 and the second cutter roller 2 driven by the first drive mechanism; the final cutter roller refers to the third cutter roller 3 and the fourth cutter roller 4 driven by the second drive mechanism.

[0056] The storage medium solid waste destruction equipment of the present invention includes a sorting structure and a frame. A first destruction mechanism, a second destruction mechanism, and a third destruction mechanism are fixedly connected to the top of the frame. A first waste bin, a second waste bin, and a third waste bin are provided inside the frame. The first destruction mechanism is used to destroy a first storage medium, which is paper material. The second destruction mechanism is used to destroy a second storage medium, which is a mechanical hard disk drive core, a solid-state drive, a USB flash drive, an IC card, a storage chip, or a circuit board, etc. The third destruction mechanism is used to destroy a third storage medium, which is an optical disk medium.

[0057] Sorting structures, including but not limited to conveyor belts, diversion gates, pneumatic levers, and sorting robotic arms, are used to achieve high-speed diversion and intelligent classification of storage media.

[0058] Taking the first destruction mechanism as an example, the first destruction mechanism includes a first housing, which is rectangular in shape and has an internal receiving cavity. Two meshing elongated cylindrical first cutter rollers 1 are located at the upper part of the first housing for the first crushing of the first storage medium. Two meshing elongated cylindrical second cutter rollers 2 are located at the lower part of the first housing, corresponding to the first cutter rollers 1, for the second crushing of the first storage medium after the first crushing, forming first primary particles. Furthermore, the first cutter rollers 1 and 2 have first protruding teeth around their peripheral walls, and the second cutter rollers 2 have second protruding teeth around their peripheral walls. The size of the first protruding teeth is larger than the size of the second protruding teeth, thus progressively refining and crushing the first storage medium and preventing equipment jamming. Furthermore, the cross-sectional area of ​​the first primary particles is A, where A is less than 40 mm². 2 (that is,) It should be noted that the first storage medium is paper material.

[0059] A flat connecting plate is fixed to the bottom of the first housing. The connecting plate has an inclined first discharge chute that extends downwards from the middle to the ends, allowing the first storage medium, after secondary crushing, to slide down the first discharge chute to the third cutter roller 3, which will be described below. A second housing, rectangular in shape, is fixed to the lower end of the connecting plate. The second housing has an internal cavity. The bottom of the second housing is fixed to the frame. A long cylindrical magnetic roller, which is magnetic, is located near the end of the upper part of the second housing. The magnetic roller is positioned corresponding to the first discharge chute, and its rotation attracts ferrous impurities such as staples from the crushed first storage medium. Furthermore, in the state shown in the figure, the counterclockwise rotation of the magnetic roller carries the crushed first storage medium that has fallen from the first discharge channel onto the magnetic roller between the two third cutter rollers 3, which will be described below. Further still, the magnetic roller has multiple long, inclined storage slots along its axial direction to store the attracted ferrous impurities and also to block the primary crushed particles, making it easier for them to slide between the two third cutter rollers 3.

[0060] The second housing contains two interlocking elongated third cutter rollers 3 in its central part. The interlocking portions of the two third cutter rollers 3 correspond to the magnetic roller, serving to receive the first storage medium after its second crushing, and thus further crush it a third time, forming first-stage particles. Furthermore, the third cutter rollers 3 have third convex teeth around their peripheral walls. The size of the second convex teeth is larger than the size of the third convex teeth, further refining the first storage medium. The cross-sectional area of ​​the first-stage particles is B, where B is less than 6 mm². 2 (that is,) ).

[0061] The lower part of the second housing is equipped with two meshing elongated fourth cutter rollers 4, which are correspondingly arranged with the two third cutter rollers 3. These fourth cutter rollers 4 are used to perform a fourth crushing of the first storage medium after the third crushing, forming the first final particles. Furthermore, the fourth cutter rollers 4 have fourth convex teeth around their peripheral walls. The size of the third convex teeth is larger than the size of the fourth convex teeth, further refining the first storage medium. Additionally, the thickness of the fourth convex teeth is H, where H is less than 1 mm. The cross-sectional area of ​​the first final particles is C, where C is less than 2 mm². 2 (that is,) ).

[0062] The first waste bin is located in the lower part of the frame. The first waste bin is set in correspondence with the two fourth cutter rollers 4 and is used to collect the first final particles that have been crushed by the fourth cutter rollers 4.

[0063] Compared with existing technologies, this invention employs a structure consisting of a first cutter roller 1, a second cutter roller 2, a third cutter roller 3, and a fourth cutter roller 4, which progressively refines and crushes the first storage medium, resulting in uniformly pulverized particles that can be continuously pulverized for extended periods without easily jamming. Furthermore, the combination of a magnetic roller and a first discharge chute allows the magnetic roller to adsorb and separate ferrous impurities, protecting the cutter rollers within the second housing and preventing tooth breakage. It also prevents mixing with the pulverized particles of the first storage medium, enabling categorized storage.

[0064] As another embodiment of the first discharge chute, the upper end of the first discharge chute is hinged to the connecting plate. The upper part of the second housing is provided with a rotating component, which is long and strip-shaped with a triangular cross-section, or it can be quadrilateral. The rotating component is located below the end of the first discharge chute near the magnetic roller. The rotation of the rotating component causes the first discharge chute to vibrate up and down, so that the primary crushed particles on the first discharge chute fall more evenly onto the magnetic roller, making it easier for the magnetic roller to adsorb iron impurities.

[0065] Two first cutter rollers 1 are provided with two meshing first gears at their ends. A first transmission gear is provided at the outermost end of the first cutter roller 1 closest to the magnetic roller, and the first transmission gear is fitted with the first gear. Two second cutter rollers 2 are provided with two meshing second gears at their ends. A second transmission gear is provided at the outermost end of the second cutter roller 2 furthest from the magnetic roller, and the second transmission gear is fitted with the second gear. The first transmission gear meshes with the second transmission gear. A first drive gear is provided at the end of the first cutter roller with the first transmission gear furthest from the first drive gear. The first drive gear meshes with the output shaft of the first drive mechanism, thereby realizing variable speed transmission for the first cutter roller 1 and the second cutter roller 2, resulting in higher efficiency.

[0066] Furthermore, the size of the first driving gear is larger than the size of the first transmission gear, the size of the first transmission gear is greater than or equal to the size of the second transmission gear, the first transmission gear is larger than the first gear, and the size of the second transmission gear is larger than the size of the second gear.

[0067] Two third cutter rollers 3 have two meshing third gears at their ends. The outermost end of the third cutter roller 3 away from the magnetic roller is provided with a third transmission gear, which is fitted into the third gear. Two fourth cutter rollers 4 have two meshing fourth gears at their ends. The outermost end of the fourth cutter roller 4 near the magnetic roller is provided with a fourth transmission gear, which is fitted into the fourth gear. The third transmission gear meshes with the fourth transmission gear. A second drive gear is provided at the end of the third cutter roller 3 near the magnetic roller away from the third gear. The second drive gear meshes with the output shaft of the second drive mechanism, thereby achieving variable speed transmission for the third cutter roller 3 and the fourth cutter roller 4, resulting in higher efficiency.

[0068] Furthermore, the size of the second driving gear is greater than or equal to the size of the third transmission gear, the size of the third transmission gear is greater than the size of the fourth transmission gear, the size of the third transmission gear is greater than the third gear, and the size of the fourth transmission gear is greater than the size of the fourth gear.

[0069] The end of the magnetic roller near the third gear is equipped with a magnetic roller gear. The side wall of the second housing is rotatably connected to the magnetic roller drive gear, which is located below the magnetic roller gear. Both the magnetic roller gear and the third gear mesh with the magnetic roller drive gear, thereby driving the magnetic roller to rotate counterclockwise.

[0070] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0071] In this invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be a single item or multiple items.

[0072] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. An automated control storage media sorting system based on RFID and artificial intelligence, characterized in that, The system includes: The automatic identification and intelligent sorting module is used to identify the storage medium after it has been identified by RFID, and to classify the storage medium based on the RFID identification results. The classification process includes normal sorting and abnormal sorting. The multi-stage crushing and adjustment module is used to crush the primary cutter rollers after normal sorting, while monitoring the crushing process parameters of the primary cutter rollers to determine whether there are mechanical abnormalities in the primary cutter rollers, and to adaptively adjust the primary cutter rollers with abnormalities. The effect evaluation and optimization module is used to evaluate the crushing effect of the storage medium after being crushed by the primary cutter roller and to determine whether the crushing effect of the primary cutter roller meets the standard. Based on the impact power spectral density proportional factor, the motor drive current harmonic energy ratio proportional factor, and the motor flux fluctuation proportional factor, the primary crushing effect index is obtained. When the primary crushing effect index is lower than the primary crushing effect threshold, it is determined that the crushing effect of the primary cutter roller does not meet the standard. Then, the primary cutter roller and the next stage cutter roller are optimized and adjusted. At the same time, the crushing effect of the storage medium before the final cutter roller is predicted to determine whether the crushing effect of the storage medium can reach the target particle size. If the crushing effect of the storage medium cannot reach the target particle size, the final cutter roller is optimized and controlled.

2. The automatic control storage medium sorting system based on RFID and artificial intelligence according to claim 1, characterized in that, The specific analysis process for classifying storage media based on RFID identification results is as follows: Key parameters for obtaining RFID identification storage media include tag return signal strength, signal reading phase, and consistency of tag reading results across multiple readings. RFID identification confidence is obtained by weighted fusion calculation of tag return signal strength, signal reading phase, and consistency of tag reading results across multiple readings. The RFID identification confidence represents the reliability and trustworthiness of the actual successful identification and accurate classification of the target tag. The RFID identification confidence level is compared with the RFID identification confidence level threshold to determine whether there is any abnormal tag data in the RFID identification storage medium. The RFID identification confidence level threshold represents the minimum value allowed for the RFID identification confidence level to reach the specified range. When the RFID identification confidence level is not lower than the RFID identification confidence threshold, it is determined that there is no abnormal tag data in the RFID identification storage medium, and normal sorting processing is carried out. When the RFID identification confidence level is lower than the RFID identification confidence level threshold, it is determined that there is an anomaly in the tag data of the RFID identification storage medium, and anomaly handling is performed.

3. The automatic control storage medium sorting system based on RFID and artificial intelligence according to claim 1, characterized in that, The specific analysis process for monitoring the crushing process parameters of the primary cutter roller is as follows: The crushing process parameters include the high-frequency vibration acceleration of the primary cutter roller, the micro-displacement of the bearing seat, and the instantaneous rotational speed deviation. The primary cutter roller mechanical anomaly index is synthesized by a weighted average fusion algorithm, wherein the primary cutter roller mechanical anomaly index is used to quantify the degree of mechanical anomaly of the primary cutter roller during the crushing process. The primary cutter roller mechanical anomaly index is compared with a first mechanical anomaly threshold and a second mechanical anomaly threshold. The first mechanical anomaly threshold is used to distinguish between stable operation and slight abnormality of the primary cutter roller, and the second mechanical anomaly threshold is used to define the safety limit of mechanical anomalies of the primary cutter roller.

4. The automatic control storage medium sorting system based on RFID and artificial intelligence according to claim 1, characterized in that, The adaptive adjustment of the primary cutter roller with abnormalities is specifically performed as follows: When the mechanical abnormality index of the primary cutter roller is lower than the first mechanical abnormality threshold, it is determined that the primary cutter roller is running smoothly, and the current operating parameters are maintained without adaptive adjustment of the primary cutter roller. When the mechanical abnormality index of the primary cutter roller is not lower than the first mechanical abnormality threshold and is lower than the second mechanical abnormality threshold, the primary cutter roller is judged to be in a slightly abnormal state, and the primary cutter roller is adaptively adjusted. When the mechanical abnormality index of the primary cutter roller is not lower than the second mechanical abnormality threshold, it is determined that the mechanical abnormality of the primary cutter roller has reached the safety limit, and at the same time, mandatory safety protection measures are automatically executed. The adaptive adjustment of the primary cutter roller specifically involves: obtaining an abnormal deviation value based on the mechanical abnormality index of the primary cutter roller and the first mechanical abnormality threshold; simultaneously reducing the rotational speed of the primary cutter roller based on the abnormal deviation value; and simultaneously reducing the feeding speed and the reversal time of the primary cutter roller. The rotational speed, feeding speed, and reversal time are linked parameters and are adjusted in an integrated adaptive manner.

5. The automatic control storage medium sorting system based on RFID and artificial intelligence according to claim 1, characterized in that, The evaluation process for assessing the pulverization effect of the storage medium after primary roller pulverization is as follows: The impact power spectral density scaling factor, motor drive current harmonic energy ratio scaling factor, and motor flux fluctuation scaling factor of the primary cutter roller are obtained. By pre-setting the effect coefficients corresponding to the impact power spectral density scaling factor, motor drive current harmonic energy ratio scaling factor, and motor flux fluctuation scaling factor in the control database, their weight contribution values ​​to the primary crushing effect index are quantified. Finally, the primary crushing effect index is synthesized by a weighted average fusion algorithm. The primary crushing effect index indicates whether the crushing effect of the storage medium after being crushed by the primary cutter roller reaches the target primary crushing effect. The impact power spectral density scaling factor represents the ratio of the impact power spectral density to the defined impact power spectral density; the motor drive current harmonic energy ratio scaling factor represents the ratio of the motor drive current harmonic energy ratio to the defined motor drive current harmonic energy ratio; and the motor flux linkage fluctuation scaling factor represents the ratio of the motor flux linkage fluctuation value to the defined motor flux linkage fluctuation value. The primary crushing effect index is compared with the primary crushing effect threshold to determine whether the crushing effect of the primary crushing roller meets the standard. The primary crushing effect threshold represents the minimum value of the primary crushing effect index within a specified range.

6. The automatic control storage medium sorting system based on RFID and artificial intelligence according to claim 5, characterized in that, The specific process for determining whether the crushing effect of the primary cutter roller meets the standard is as follows: When the primary crushing effect index is lower than the primary crushing effect threshold, it is determined that the crushing effect of the primary cutter roller is not up to standard, and the primary cutter roller and the next stage cutter roller are optimized and adjusted. When the primary crushing effect index is not lower than the primary crushing effect threshold, the crushing effect of the primary cutter roller is deemed to be up to standard, and the crushing process can proceed normally.

7. The automatic control storage medium sorting system based on RFID and artificial intelligence according to claim 6, characterized in that, The optimization and adjustment of the primary cutter roller and the next-stage cutter roller is specifically performed as follows: The primary crushing effect index and the primary crushing effect threshold are used to obtain the primary crushing deviation value. Based on the primary crushing deviation value, the rotation speed of the next stage cutter roller is increased, and the reversal time of the next stage cutter roller is increased simultaneously with the sorting and feeding speed. At the same time, the rotation speed and reversal time of the primary cutter roller are increased based on the primary crushing deviation value. During the optimization and adjustment of the primary cutter roller, the primary cutter roller mechanical anomaly index is monitored in real time and marked as the primary cutter roller mechanical risk index. If the primary cutter roller mechanical risk index is less than the second mechanical anomaly threshold, optimization is carried out normally. If the primary cutter roller mechanical risk index is greater than or equal to the second mechanical anomaly threshold, the optimization range of the primary cutter roller is limited to the maximum allowable value when the corresponding primary cutter roller mechanical risk index is equal to the second mechanical anomaly threshold, so as to ensure the safety of system operation.

8. The automatic control storage medium sorting system based on RFID and artificial intelligence according to claim 1, characterized in that, The specific analysis process for predicting the crushing effect of the storage medium before the final stage cutter roller is as follows: The crushing effect compliance prediction index is obtained by weighted averaging of the impact power spectral density ratio factor of the multi-stage cutter roller, the harmonic energy ratio ratio factor of the motor drive current, and the motor flux fluctuation ratio factor. The specific evaluation method is the same as the primary crushing effect index evaluation method. The crushing effect compliance prediction index is compared with the crushing effect compliance prediction threshold, whereby the crushing effect compliance prediction threshold represents the minimum value of the crushing effect compliance prediction index within a specified range.

9. The automatic control storage medium sorting system based on RFID and artificial intelligence according to claim 1, characterized in that, The optimization and control of the final stage cutter roller is specifically performed as follows: When the prediction index for achieving the pulverization effect is not lower than the prediction threshold for achieving the pulverization effect, it is determined that the pulverization effect of the storage medium can achieve the target particle size, and no optimization or control is performed on the final stage cutter roller. When the crushing effect compliance prediction index is lower than the crushing effect compliance prediction threshold, it is determined that the crushing effect of the storage medium cannot reach the target particle size. The final stage cutter roller is then optimized and controlled. The specific control process for optimizing and controlling the final stage cutter roller is as follows: based on the crushing effect compliance prediction index and the crushing effect compliance prediction threshold, the crushing effect compliance deviation value is obtained. Based on the crushing effect compliance deviation value, the rotation speed and reversal time of the final stage cutter roller are increased, and the sorting and feeding speed is synchronized.

10. An automated storage media destruction machine based on RFID and artificial intelligence, employing the automated storage media sorting system based on RFID and artificial intelligence as described in any one of claims 1 to 9, characterized in that, The storage medium destruction machine includes a sorting mechanism, multi-stage blade rollers, and a control module; The sorting mechanism is used to automatically classify and sort storage media based on RFID identification and intelligent analysis, and guide different types of storage media into the corresponding processing channels. The multi-stage cutter roller is used to crush the sorted storage medium step by step, gradually pulverizing it to the target particle size to achieve complete destruction. The control module is used to monitor and adaptively adjust the operating parameters of the multi-stage cutter rollers in real time based on the operating status parameters and anomaly detection results, so as to ensure the safety and stability of the crushing process.

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