A Smart Error-Proofing Method and System for Preparing Tobacco Leaf Additives and Sugars

Abstract

This invention discloses an intelligent error-proofing method and system for preparing tobacco leaf feeding sugar. The method includes: collecting the material access information of the target sugar and comparing it with preset process standards; after screening, collecting the status data of the target equipment and confirming that it meets the material extraction readiness conditions; before extraction, unlocking the extraction permission by verifying the deviation between the accumulated weight data and the standard weight of the first work order; after extraction, confirming the feeding accuracy by verifying the actual weight and the standard weight of the second work order; collecting the sugar temperature and confirming that it meets the stability conditions; and simultaneously verifying the flow matching degree and pipeline sealing during the pre-filling process. This can ensure the sugar delivery accuracy, detect hidden pipeline faults in a timely manner, and avoid the expansion of faults that could cause production interruptions. Through progressive detection and data verification at each stage, a full-process quality protection chain is formed, reducing the uncertainty caused by human intervention and achieving high-quality and high-stability output in the material preparation process, thus ensuring the quality consistency of subsequent tobacco leaf feeding processes.

Description

Technical Field

[0001] This invention relates to the field of tobacco preparation and cigarette production automation technology, and in particular to an intelligent error-proofing method and system for preparing tobacco leaf additives and sugars. Background Technology

[0002] In tobacco processing, the addition of additives to tobacco leaves is a crucial step that determines the consistency of the product's intrinsic quality and style. It requires the precise and even application of sugars, flavorings, and other materials to the surface of the tobacco leaves according to a precise formula. Sugar preparation, as a critical pre-addition step, plays a vital role in safely, accurately, and without loss transporting the barrelled raw materials to the buffer tank of the addition system. Its operational reliability directly affects the precision and stability of subsequent addition processes, thus determining the level of homogeneity in the final tobacco product's quality.

[0003] Currently, the industry typically conducts reliability testing of sugar raw material preparation around work order execution and single-point monitoring: the Manufacturing Execution System (MES) issues electronic work orders based on the production plan, and operators scan the barcodes of raw material barrels with a barcode scanner to compare the obtained batch and weight information with the work order; operators place the raw material barrels on a weighing scale with a weighing module, and the system records the weight changes before and after extraction and verifies them with the theoretical values ​​in the work order; temperature, flow, or pressure sensors are installed on the heating tank, buffer tank, and conveying pipelines, and the relevant parameters are displayed in real time on the monitoring screen for manual monitoring; the programmable logic controller (PLC) controls the start and stop of pumps, valves, and other equipment according to a preset sequence to complete the extraction, heating, and conveying actions.

[0004] Although basic automation of the material preparation process has been achieved, its verification is limited to basic information such as material batch and weight, and relies on manual confirmation of alarm information. It cannot rigidly prevent erroneous operations and has insufficient error prevention depth. For hidden faults such as progressive pipe blockage and micro-leakage at joints, it relies only on single-point monitoring of end flow or pressure. Often, the fault is only discovered after it has expanded and caused production interruption or batch quality accident. Fault detection is one-sided and delayed. The detection points such as barcode scanning, weighing, and temperature monitoring are isolated from each other. Quality risks can easily penetrate local checkpoints, reducing the reliability of detection. It is essentially a passive response system for monitoring and alarms. All abnormalities require manual intervention for judgment and handling. Not only is the response speed slow, but it is also affected by operating experience, making it difficult to ensure consistency in handling. Ultimately, this leads to problems such as low level of intelligence, inability to prevent hidden faults, and high maintenance costs. Summary of the Invention

[0005] This invention provides an intelligent error prevention method and system for preparing tobacco leaf feed and sugar, which solves the problems of insufficient error prevention depth, difficulty in identifying hidden faults, small fault detection range, low detection timeliness, low reliability, low level of intelligence and high maintenance cost in the process of preparing tobacco leaf feed and sugar.

[0006] According to one aspect of the present invention, a quality control method for preparing tobacco leaf additives and sugars is provided, comprising: Collect the material access information of the target sugar and compare it with the preset process standards to screen out the target sugar that has passed the material access test; After screening out the target sugar that has passed the material access test, collect the target equipment status data, and after confirming that the target equipment status data meets the preset ready conditions, confirm that the target equipment is in the material extraction ready state. Before performing the material extraction operation on the target sugar that has passed the material access detection through the target equipment that is in the material extraction ready state, collect the cumulative weight data and perform the first deviation verification with the standard weight of the first work order. After the verification is passed, unlock the extraction permission of the target equipment. After the target sugar that has passed the material access test is extracted by the target equipment with extraction authority, the actual weight data of the tank after extraction is collected and the second deviation is checked with the standard weight of the second work order. After the verification meets the preset accuracy requirements, the feeding accuracy test is confirmed to be passed. After confirming that the feeding accuracy test has passed, the temperature of the sugar material in the tank after extraction is collected. After confirming that the temperature after extraction meets the stability condition, the parameter standard test is confirmed to be passed and the sugar material pre-filling operation is performed. During the sugar prefilling process, the prefilling flow rate and the weight of the prefilling tank are collected simultaneously. The prefilling flow rate is matched with the reference flow rate for flow rate verification. The pipeline sealing is verified based on the change in the weight of the prefilling tank and the pipeline parameters. When the flow rate matching verification and the pipeline sealing verification are passed, sugar that meets the quality requirements is obtained.

[0007] According to another aspect of the present invention, a quality control device for preparing tobacco leaf processing materials is provided, comprising: The access screening module is used to collect the material access information of the target sugar and compare it with the preset process standards to screen out the target sugar that has passed the material access test. The material extraction ready module is used to collect target equipment status data after screening out target sugar materials that have passed the material access detection, and to confirm that the target equipment is in the material extraction ready state after confirming that the target equipment status data meets the preset ready conditions. The material extraction permission module is used to collect cumulative weight data and perform a first deviation verification with the standard weight of the first work order before performing the material extraction operation on the target sugar that has passed the material access detection through the target equipment that is in the material extraction ready state. After the verification is passed, the material extraction permission of the target equipment is unlocked. The accuracy detection module is used to collect the actual weight data of the tank after the material access detection is completed by the target equipment with the material extraction permission, and to perform a second deviation verification with the standard weight of the second work order. After the verification meets the preset accuracy requirements, the feeding accuracy detection is confirmed to be passed. The temperature detection module is used to collect the temperature of the sugar material in the tank after the feeding accuracy test is passed. After confirming that the temperature after feeding meets the stability condition, the module confirms that the parameters meet the standard and passes the test, and then performs the sugar material pre-filling operation. The pre-filling module is used to simultaneously collect the pre-filling flow rate and the weight of the pre-filling tank during the sugar pre-filling process, and to perform flow matching verification between the pre-filling flow rate and the reference flow rate, as well as to perform pipeline sealing verification based on the change in the weight of the pre-filling tank and pipeline parameters. When the flow matching verification and the pipeline sealing verification are passed, sugar that meets the quality requirements is obtained.

[0008] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising: At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the quality control method for preparing tobacco leaf feed and sugar as described in any embodiment of the present invention.

[0009] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions, the computer instructions being configured to cause a processor to execute and implement the quality control method for preparing tobacco leaf feed and sugar as described in any embodiment of the present invention.

[0010] According to another aspect of the present invention, a computer program product is also provided, including a computer program that, when executed by a processor, implements the steps of the method as described in any embodiment of the present invention.

[0011] The technical solution of this invention, by collecting the material access information of the target sugar and comparing it with preset process standards, can accurately screen out sugars that comply with the requirements of identity, weight, and timeliness, thus avoiding quality deviations caused by material misuse from the source and deepening the error prevention depth. After screening, the status data of the target equipment is collected and confirmed to meet the material extraction readiness conditions, which can eliminate potential equipment failures in advance and ensure the continuity of the material preparation process. Before extraction, the extraction permission is unlocked by verifying the deviation between the accumulated weight data and the standard weight of the first work order. After extraction, the feeding accuracy is confirmed by verifying the actual weight with the standard weight of the second work order. This dual control can improve the feeding accuracy and reduce the risk of formula distortion. After extraction, the temperature of the sugar is collected and its temperature is confirmed. Meeting stable conditions ensures the sugar material process meets standards, laying the foundation for subsequent feeding processes. During pre-filling, flow matching and pipeline sealing are simultaneously verified to obtain sugar material that meets quality requirements. This ensures sugar material delivery accuracy and timely detection of hidden faults such as pipeline blockages and leaks, improving the scope and timeliness of fault detection and preventing production interruptions caused by escalating faults. The entire process forms a comprehensive quality protection chain through progressive testing and data verification at each stage, reducing the uncertainty and maintenance costs associated with manual intervention. This achieves high-quality, high-reliability, and high-stability output in the material preparation process, improving the level of intelligence in material preparation and providing a reliable guarantee for the consistency of quality in subsequent tobacco leaf feeding processes.

[0012] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0013] 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.

[0014] Figure 1 This is a flowchart of a quality control method for preparing tobacco leaf additives and sugars according to Embodiment 1 of the present invention; Figure 2 This is a flowchart of another quality control method for preparing tobacco leaf additives and sugars according to Embodiment 2 of the present invention; Figure 3 This is a flowchart of another quality control method for preparing tobacco leaf additives and sugars according to Embodiment 3 of the present invention; Figure 4 This is a schematic diagram of the structure of a quality control device for preparing tobacco leaf additives and sugars according to Embodiment 4 of the present invention; Figure 5 This is a schematic diagram of the structure of an electronic device for implementing the quality control method for tobacco leaf feeding and sugar preparation according to an embodiment of the present invention. Detailed Implementation

[0015] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0016] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0017] Example 1 Figure 1 This is a flowchart of a quality control method for preparing tobacco leaves with added sugar and feed, provided in Embodiment 1 of the present invention. This embodiment is applicable to the preparation of tobacco leaves with added sugar and feed. This method can be executed by a quality control device for preparing tobacco leaves with added sugar and feed. This quality control device can be implemented in hardware and / or software and is generally configured in an electronic device. Figure 1 As shown, the method includes: S110. Collect the material access information of the target sugar and compare it with the preset process standards to screen out the target sugar that has passed the material access test.

[0018] In this embodiment of the invention, material access inspection can be specifically understood as: verifying the compliance of sugar materials through multiple dimensions to ensure that unqualified sugar materials do not enter subsequent processes, which is the first inspection step in sugar material preparation. Preset process standards can be specifically understood as: pre-set criteria for determining the qualification of sugar materials, which may include indicators such as standard grade, standard batch, standard weight, and standard expiration date.

[0019] Specifically, material access information of the target sugar can be collected. For example, by scanning the identification code of the sugar barrel with a barcode scanner, the actual brand, purity, composition content, actual batch (i.e., identification information), actual preparation weight (i.e., weight data), and actual preparation time (i.e., preparation time) of the sugar can be extracted. Alternatively, relevant data can be obtained by reading the information of the chip built into the sugar barrel through RFID (Radio Frequency Identification) technology.

[0020] The collected information is compared one by one with the corresponding indicators in the preset process standards. For example, if the consistency of identity information, the accuracy of weight data, and the timeliness of preparation time all meet the requirements of the preset process standards, the target sugar is determined to have passed the material access test and completed the screening. If any indicator does not meet the requirements, it is determined to have failed and will not be included in the subsequent material preparation process.

[0021] During the comparison, indicators such as sugar purity and component content can also be added according to production needs to ensure that the selected sugar fully meets the requirements of subsequent material preparation and tobacco feeding processes.

[0022] S120. After screening out the target sugar material that has passed the material access test, collect the target equipment status data, and after confirming that the target equipment status data meets the preset ready conditions, confirm that the target equipment is in the material extraction ready state.

[0023] In this embodiment of the invention, the target equipment status data can be specifically understood as: key operating parameters of the equipment related to the material extraction operation, which may include quantitative data corresponding to the tank status, valve position, and pipeline sealing performance. Tank status can be specifically understood as: the empty-load condition of the tank before extraction. Valve position can be specifically understood as: the on / off status of extraction-related valves (such as the return valve), which directly affects the sealing performance and accuracy of the material conveying path. Pipeline sealing performance can be specifically understood as: the degree of tightness of the conveying pipeline, which can verify whether there is a risk of leakage and avoid material loss or contamination.

[0024] Preset ready conditions can be understood as: pre-defined qualification standards for the equipment to perform material extraction operations, which may include compliance requirements for material tanks, valves, and pipelines. Material extraction ready state can be understood as: the state in which the target equipment can start material extraction operations after meeting all preset ready conditions, and is a prerequisite for unlocking material extraction permissions.

[0025] Specifically, after the target sugar material that has passed the material access test is selected, the equipment readiness test is performed, and relevant status data such as the status of the target equipment tank, valve position and pipeline sealing are collected. For example, the valve opening and closing status is detected by visual recognition technology, the pipeline sealing is verified by ultrasonic testing technology, and the tank status and no-load status are determined by liquid level sensor data.

[0026] Each collected status data is checked against the corresponding standard in the preset ready conditions. When the tank status meets the no-load requirements, the valve position is in the correct open / closed state, and the pipeline sealing meets the standard, the target equipment status data is determined to meet the preset ready conditions, and the target equipment is confirmed to be in the material extraction ready state. If any status data does not meet the preset standard, the equipment is determined to be not ready, and the problem needs to be investigated and the test is repeated.

[0027] S130. Before performing the material extraction operation on the target sugar that has passed the material access detection through the target equipment in the material extraction ready state, collect the cumulative weight data and perform the first deviation verification with the standard weight of the first work order. After the verification is passed, unlock the material extraction permission of the target equipment.

[0028] In this embodiment of the invention, the cumulative weight data can be specifically understood as: the summary data of the theoretical weight of the target sugar obtained before extraction, which can be represented as W_scan. The first work order standard weight can be specifically understood as: the preset standard weight of the sugar issued by the work order, which serves as the benchmark for weight verification before extraction, and can be represented as W_standard1. The first deviation verification can be specifically understood as: calculating and judging the error between the cumulative weight data and the first work order standard weight before extraction, and the error must satisfy |W_scan-W_standard1| / W_standard1 is less than or equal to the corresponding preset threshold, such as 0.5%. Extraction permission can be specifically understood as: the permission for the target device to perform extraction operations, which is only unlocked by the system after the first deviation verification is passed.

[0029] S140. After the target sugar material that has passed the material access test is extracted by the target equipment with extraction authority, the actual weight data of the tank after extraction is collected and the second deviation is checked with the standard weight of the second work order. After the verification meets the preset accuracy requirements, the feeding accuracy test is confirmed to be passed.

[0030] In this embodiment of the invention, the actual weight data can be specifically understood as: the actual weight of the sugar in the tank collected after the material extraction is completed, which can be represented as W_real. The second work order standard weight can be specifically understood as: the work order preset standard weight, which serves as the benchmark for weight verification after extraction, and can be represented as W_standard2. The second deviation verification can be specifically understood as: calculating and judging the error between the actual weight data and the second work order standard weight after extraction. The error must satisfy |W_real-W_standard2| / W_standard2 is less than or equal to the corresponding preset threshold, such as 1%. The preset accuracy requirement can be specifically understood as: the allowable range of weight error corresponding to the second deviation verification is the basis for confirming that the material feeding accuracy test has passed.

[0031] Specifically, during the dual verification of material extraction weight, the first verification is performed before extraction. This involves collecting the cumulative weight data of the target sugar canister, for example, by parsing the target sugar canister's identification code using a barcode scanner or reading the information from the internal chip of the sugar canister using RFID, and extracting the cumulative weight value W_scan as the collected cumulative weight data. This data is then compared with the first work order's standard weight W_standard1 to perform a first deviation verification. If the error meets the first deviation verification condition, the system automatically unlocks the extraction permission for the target device, allowing the extraction operation to begin.

[0032] After the material extraction operation is completed, a second verification is performed. The actual weight data W_real of the sugar in the tank can be collected by a static scale and the deviation is calculated with the standard weight W_standard2 of the second work order. The error is verified to see if it meets the second deviation verification condition (i.e., the preset accuracy requirement). When the verification result meets the preset accuracy requirement, the feeding accuracy test is deemed to have passed, ensuring that the weight of the sugar feeding meets the process standard.

[0033] Among them, the error threshold of deviation verification can be flexibly adjusted according to the accuracy requirements of different production scenarios. The dual verification forms a progressive weight protection mechanism to avoid the problem of process formula distortion caused by weight deviation.

[0034] S150. After confirming that the feeding accuracy test has passed, the temperature of the sugar material in the tank after extraction is collected. After confirming that the temperature after extraction meets the stability condition, the parameter standard test is passed and the sugar material pre-filling operation is performed.

[0035] In this embodiment of the invention, parameter compliance testing can be specifically understood as a specific testing step for key process parameters (temperature) of the sugar material during the material preparation process, ensuring that the sugar material's process state meets the requirements for subsequent pre-filling and tobacco leaf feeding. Post-extraction temperature can be specifically understood as the actual temperature of the sugar material in the tank after the extraction operation, a parameter affecting the sugar material's viscosity, flowability, and integration with tobacco leaves. Stability conditions can be specifically understood as a comprehensive standard for determining whether the sugar material temperature meets the standards, which may include requirements such as temperature range, duration of sustained stability, and temperature distribution uniformity. Pre-filling operation can be specifically understood as the pre-transportation step after the parameter compliance test is passed, where qualified sugar material is transported to the buffer tank of the feeding system; this is the connecting step between sugar material preparation and tobacco leaf feeding.

[0036] Specifically, after confirming that the feeding accuracy test has passed, a parameter compliance test is performed. Temperature data of the sugar material after extraction is collected from the tank. This can be done by using multiple platinum resistance temperature sensors to collect temperature data at different monitoring points within the tank, or by using an infrared thermometer to monitor the sugar material temperature. Each set of collected temperature data is compared with a preset temperature range (e.g., the deviation from the set value is within 3 degrees Celsius). Simultaneously, the standard deviation of the temperature data from multiple monitoring points is calculated to verify the temperature distribution uniformity, and it is confirmed that the temperature stability time meets the preset duration (e.g., greater than or equal to 5 minutes). This is used to determine whether the temperature after extraction meets the stability conditions. The temperature range and duration in the stability conditions can be flexibly adjusted according to the sugar material type and tobacco feeding process requirements to ensure that the sugar material maintains good fluidity and blending properties during pre-filling and subsequent tobacco feeding.

[0037] When all temperature data are within the preset range, temperature uniformity meets the standard, and the duration of continuous stability meets the requirements, the parameter compliance test is passed and the sugar pre-filling operation is performed to ensure that the sugar process status is qualified for the next stage.

[0038] S160. During the sugar prefilling process, the prefilling flow rate and the weight of the prefilling tank are collected simultaneously. The prefilling flow rate is matched with the reference flow rate for flow rate verification. The pipeline sealing is verified based on the change in the weight of the prefilling tank and the pipeline parameters. When the flow rate matching verification and the pipeline sealing verification are passed, sugar that meets the quality requirements is obtained.

[0039] In this embodiment of the invention, the pre-filling flow rate can be specifically understood as: the actual conveying flow rate data collected in real time during the sugar pre-filling process, used to determine the conveying efficiency and formula compliance. The baseline flow rate can be specifically understood as: the standard flow rate F_base calculated based on the tobacco leaf flow rate and the preset feeding ratio, used as the benchmark for flow rate matching verification. For example, F_base = F_t × R, where F_t is the tobacco leaf flow rate and R is the feeding ratio. Flow rate matching verification can be specifically understood as: comparing the pre-filling flow rate with the baseline flow rate to verify whether the actual flow rate meets the process requirements.

[0040] The change in the weight of the pre-filled tank can be understood as the decrease in the tank's weight during the sugar transport process, expressed as ΔW, used to determine if there is a leak in the pipeline. Pipeline parameters can be understood as parameters related to the calculation of the pipeline's capacity, including the pipeline diameter D, pipeline length L, and sugar density ρ. Pipeline sealing verification can be understood as comparing the change in the tank's weight with the theoretical capacity of the pipeline to determine if there is a leak, where the theoretical capacity W_pipe = π × (D / 2). 2 ×L×ρ.

[0041] Specifically, the final inspection step in the material preparation process is a system integrity inspection. Through dual monitoring during the pre-filling process, the operational integrity and safety of the sugar conveying system are verified to ensure no risk of failure.

[0042] During system integrity testing, in the sugar pre-filling process, the pre-filling flow rate F_pre is simultaneously collected via a flow meter, and the weight data of the pre-filling tank is simultaneously collected via a static scale. The collected pre-filling flow rate F_pre is matched and verified with the baseline flow rate F_base to ensure that F_pre is greater than or equal to F_base. The weight change ΔW is calculated based on the weight data of the pre-filling tank, and the theoretical capacity W_pipe of the pipeline is calculated based on the pipeline parameters. Pipeline sealing is then verified. If the deviation between the actual conveyed sugar weight calculated from the weight change of the pre-filling tank and the corresponding change time, and the theoretical capacity W_pipe, and the weight change ΔW, is within the preset reasonable tolerance range, it indicates that almost all the sugar conveyed from the tank remains in the conveying pipeline, and there is no obvious leakage. Therefore, the pipeline sealing verification is considered passed. If the deviation exceeds the preset reasonable tolerance range, it indicates that some sugar leaked during the pre-filling conveying process. Therefore, the pipeline sealing verification is considered failed.

[0043] When the flow matching verification result meets the preset requirements and the pipeline sealing verification result shows no risk of leakage, the system integrity test is deemed to have passed, and sugar material that meets the quality requirements is obtained.

[0044] Furthermore, in the system integrity testing stage of sugar preparation, flow matching verification can also assist in the judgment by setting a reasonable threshold for flow fluctuation amplitude, and limit the instantaneous and continuous fluctuation range of flow during the pre-filling process; at the same time, pipeline sealing verification can also be combined with the real-time pressure data of the pipeline collected by the corresponding pressure sensor for collaborative verification. By comparing the stable state and change trend of pipeline pressure with the weight comparison results, the limitations of single data detection can be made up for, thereby further improving the accuracy and reliability of the two verification results in system integrity testing.

[0045] The technical solution of this invention, by collecting the material access information of the target sugar and comparing it with preset process standards, can accurately screen out sugars that comply with the requirements of identity, weight, and timeliness, thus avoiding quality deviations caused by material misuse from the source and deepening the error prevention depth. After screening, the status data of the target equipment is collected and confirmed to meet the material extraction readiness conditions, which can eliminate potential equipment failures in advance and ensure the continuity of the material preparation process. Before extraction, the extraction permission is unlocked by verifying the deviation between the accumulated weight data and the standard weight of the first work order. After extraction, the feeding accuracy is confirmed by verifying the actual weight with the standard weight of the second work order. This dual control can improve the feeding accuracy and reduce the risk of formula distortion. After extraction, the temperature of the sugar is collected and its temperature is confirmed. Meeting stable conditions ensures the sugar material process meets standards, laying the foundation for subsequent feeding processes. During pre-filling, flow matching and pipeline sealing are simultaneously verified to obtain sugar material that meets quality requirements. This ensures sugar material delivery accuracy and timely detection of hidden faults such as pipeline blockages and leaks, improving the scope and timeliness of fault detection and preventing production interruptions caused by escalating faults. The entire process forms a comprehensive quality protection chain through progressive testing and data verification at each stage, reducing the uncertainty and maintenance costs associated with manual intervention. This achieves high-quality, high-reliability, and high-stability output in the material preparation process, improving the level of intelligence in material preparation and providing a reliable guarantee for the consistency of quality in subsequent tobacco leaf feeding processes.

[0046] Example 2 Figure 2 This is a flowchart of another quality control method for preparing tobacco leaf sugar additives according to Embodiment 2 of the present invention. This embodiment is a refinement of the above embodiment's step of "collecting the material access information of the target sugar additive and comparing it with the preset process standard to screen out the target sugar additives that have passed the material access test." Figure 2 As shown, the method includes: S210. Scan the sugar barrel identification code with a fixed barcode scanner to obtain the actual brand, batch, weight, and preparation time of the sugar, which will serve as material access information.

[0047] In this embodiment of the invention, the fixed barcode scanning device can be specifically understood as: a dedicated device fixedly deployed at the material preparation station that can automatically or manually scan material identification codes, used to quickly collect material-related information, different from handheld barcode scanning devices, and adapted to station-based operation scenarios. The sugar bucket identification code can be specifically understood as: a unique identifier (such as a QR code or barcode) assigned to each sugar bucket, used to associate core information about sugar production and preparation, and serves as the carrier of information collection. The material access information can be specifically understood as: information determining whether sugar can enter the material preparation process, which may include sugar identification (such as brand and batch), quantitative parameters (prepared weight), and timeliness parameters (preparation time).

[0048] S220. The actual grade is compared with the preset standard grade in the preset process standard, and the actual batch is compared with the preset standard batch in the preset process standard. The actual prepared weight is compared with the preset standard weight in the preset process standard. The absolute value of the difference between the current time and the actual preparation time is compared with the preset standard time limit in the preset process standard. When all comparison items meet the preset process standard, the material access test is determined to be passed, and the target sugar that has passed the material access test is selected.

[0049] In this embodiment of the invention, consistency comparison can be specifically understood as: verifying the matching of the actual identification of the sugar material with the standard information in the preset process standard to ensure that the material identification is without deviation. Deviation comparison can be specifically understood as: calculating the percentage difference between the actual quantitative parameters of the sugar material and the standard parameters to verify whether the deviation between the actual parameters and the standard parameters is within the allowable range. Timeliness comparison can be specifically understood as: calculating the time difference between the sugar material preparation time and the current time to verify whether the sugar material is within the preset effective use period and to avoid exceeding the expiration date.

[0050] Specifically, by scanning the unique identification code of the sugar barrel with a fixed barcode scanner installed at the material preparation station, the system automatically extracts the actual sugar grade (Batch_actual), actual batch (Lot_actual), actual preparation weight (W_actual), and actual preparation time (T_actual) from the identification code, and uses these four types of information as material access information to determine whether the sugar can be admitted.

[0051] The system performs a triple comparison of sugar material information based on preset process standards, and uses rigid interlocking logic for verification. This rigid interlocking logic can be understood as follows: if any step in the process verification fails, the system will automatically trigger restrictive measures, forcibly locking the control logic of subsequent operations.

[0052] First, identity consistency verification is performed, requiring that the actual brand name Batch_actual and the actual batch name Lot_actual be completely consistent with the preset standard brand name Batch_standard and the standard batch name Lot_standard, i.e., Batch_actual = Batch_standard and Lot_actual = Lot_standard. Second, weight accuracy verification is performed, requiring that the relative deviation between the actual prepared weight W_actual and the preset standard weight W_standard0 meets the condition that |W_actual - W_standard0| / W_standard0 is less than or equal to the corresponding preset threshold, such as 0.5%. Finally, timeliness verification is performed, requiring that the absolute value of the time difference between the actual preparation time and the current time T_current does not exceed the preset shelf life, i.e., |T_actual - T_current| is less than or equal to the shelf life. When all three comparison items pass the verification, the material access test of the sugar is determined to be passed, and the target sugar is selected to enter the subsequent material preparation process. If any comparison item fails the verification, the system will immediately and automatically lock the subsequent operation permissions of the target sugar to prevent unqualified sugar from entering the process, and at the same time issue an alarm prompt to remind the operator to handle it in time. Alarm notifications can be simultaneously pushed to multiple terminals such as workstation terminals and central control systems, further improving the flexibility of material access detection and the timeliness of early warning, and preventing material risks such as misuse of sugar grades, batch confusion, weight deviation, and overdue use from the source.

[0053] S230. After screening out the target sugar material that has passed the material access test, collect the target equipment status data, and after confirming that the target equipment status data meets the preset ready conditions, confirm that the target equipment is in the material extraction ready state.

[0054] Optionally, based on the above embodiments, collecting target device status data and confirming that the target device is in a material extraction ready state after confirming that the target device status data meets preset ready conditions may include: The initial weight data of the target material tank is collected by a static scale as the target equipment status data, and it is verified whether the initial weight data meets the weight requirements corresponding to the empty material tank state. The position signal of the material discharge manual valve is collected by a valve position sensor as the target equipment status data, and it is verified whether the valve is in a fully closed state. The pressure data of the pipeline system is collected by a pressure sensor as the target equipment status data, and it is verified whether the pipeline sealing meets the standard. When the initial weight data meets the weight requirements corresponding to the empty material tank state, the valve is in a fully closed state, and the pipeline sealing meets the standard, it is determined that the target equipment status data meets the preset ready conditions, and the target equipment is confirmed to be in the material extraction ready state.

[0055] Specifically, in the equipment readiness test, the system reads three types of status data of the target equipment: the initial weight data of the target tank is collected by a static scale as the status data of the target equipment, and the initial weight data is verified to meet the weight requirements corresponding to the empty tank state, that is, to verify whether the data is zero (or allow a certain error, such as 0.1 kg), thereby confirming that the tank is in the empty state.

[0056] The position signal of the unloading manual valve (such as valve opening percentage or on / off contact signal) is collected by the valve position sensor as the target equipment status data to verify whether the valve is in a fully closed state. The collected position signal is compared with the preset standard signal of fully closed state. If the collected signal matches the standard signal perfectly (such as opening percentage of 0% or contact signal showing closed), the unloading manual valve is verified to be in a fully closed state. If the signal does not match (such as opening percentage greater than 0% or contact signal showing open), the valve is determined to be not fully closed, and material leakage or backflow during the material extraction process needs to be prevented.

[0057] Pressure data from the pipeline system is collected by pressure sensors as status data for the target equipment to verify the pipeline's sealing performance and prevent leaks during material transport. The pipeline can be pre-pressurized or kept at static pressure, and the pressure data trend is continuously monitored. The pressure change is compared with a preset sealing performance threshold. If the pressure data remains stable within a preset time and the pressure drop does not exceed the threshold range, the pipeline sealing performance is verified. If the pressure data drops rapidly and exceeds the threshold, it indicates a leak in the pipeline, and the sealing performance is deemed substandard. The system must then prohibit the material extraction operation and trigger an alarm to prevent material leakage during subsequent material transport, avoiding material loss, environmental pollution, and distortion of process parameters.

[0058] When the initial weight data meets the emptying requirements, the valve is fully closed, and the pipeline sealing meets the standards, and all three conditions are met simultaneously, the target equipment status data is determined to meet the preset ready conditions. The system confirms that the target equipment is in the material extraction ready state and unlocks the material extraction operation permission. If any verification fails, the equipment is not ready for material extraction and needs to be investigated and retested.

[0059] By collecting the initial weight data of the target material tank using a static scale and verifying whether it meets the weight requirements for an empty state, the system can accurately check for residual materials in the tank, preventing residual materials from mixing with newly added sugar and causing distortion of the formula ratio, thus ensuring the purity of the prepared materials from the perspective of equipment material load capacity; by collecting the position signal of the discharge manual valve using a valve position sensor and verifying whether it is completely closed, it can effectively prevent material leakage or backflow during the material extraction process due to valves not being closed tightly, reducing material loss and process contamination risks; by collecting the pressure data of the pipeline system using a pressure sensor and verifying whether the sealing meets the standards, it can... This mechanism can identify potential pipeline leaks in advance, avoiding environmental pollution and insufficient material input caused by material leakage during material extraction. Only when all three equipment status data meet the preset readiness conditions is the target equipment confirmed to be in the material extraction ready state. This multi-dimensional and progressive equipment readiness detection mechanism eliminates safety and quality risks at the equipment level from three dimensions: material residue, valve status, and pipeline sealing. It provides a reliable guarantee for the stable and accurate execution of subsequent material extraction operations, reduces production interruptions and process deviations caused by abnormal equipment status, and further improves the safety and reliability of the sugar preparation process.

[0060] S240. Before performing the material extraction operation on the target sugar that has passed the material access detection through the target equipment in the material extraction ready state, collect the cumulative weight data and perform the first deviation verification with the standard weight of the first work order. After the verification is passed, unlock the material extraction permission of the target equipment.

[0061] S250. After the target sugar that has passed the material access test is extracted by the target equipment with extraction authority, the actual weight data of the tank after extraction is collected and the second deviation is checked with the standard weight of the second work order. After the verification meets the preset accuracy requirements, the feeding accuracy test is confirmed to be passed.

[0062] S260. After confirming that the feeding accuracy test has passed, the temperature of the sugar material in the tank after extraction is collected. After confirming that the temperature after extraction meets the stability condition, the parameter standard test is confirmed to be passed and the sugar material pre-filling operation is performed.

[0063] Furthermore, based on the above embodiments, the quality control method for preparing tobacco leaf additives and sugar feed may further include: During the material extraction operation of the target sugar that has passed the material access inspection through the target equipment with extraction authority, the weight data of the tank is collected in real time by the static scale. When the weight data reaches the preset threshold, the working status detection of the heating device and the stirring device is triggered. During the status detection of the heating device, the heating current data of the heating device is collected by the current sensor, the temperature change data of the material tank is collected by the temperature sensor, the status of the steam valve is confirmed by the valve position sensor, and the compliance of the heating device operation is verified based on the heating current data, the temperature change data of the material tank and the status of the steam valve. During the status detection of the stirring device, the stirring current data of the stirring device is collected by the motor current sensor, and the vibration data of the stirring device is collected by the vibration sensor. The working status of the stirring device is verified based on the stirring current data and vibration data. When the operating status test results of both the heating device and the stirring device are compliant, the process condition test is deemed to have passed. Accordingly, based on the above embodiments, after confirming that the feeding accuracy test has passed, the temperature of the sugar material in the tank after extraction is collected. After confirming that the temperature after extraction meets the stability condition, the parameter compliance test is passed and the sugar material pre-filling operation is performed, which may include: After confirming that the feeding accuracy test and the process condition test have passed, the temperature of the sugar material in the tank after extraction is collected. After confirming that the temperature after extraction meets the stability condition, the parameter standard test is confirmed to be passed and the sugar material pre-filling operation is performed.

[0064] In this embodiment of the invention, process condition detection can be specifically understood as: a specific detection step during the material preparation process targeting the operating status of the heating and stirring devices. This is a prerequisite for ensuring the process characteristics of the sugar material (such as flowability and uniformity), and can specifically be considered as monitoring the heating and stirring thresholds. The compliance of the heating device operation can be specifically understood as: the operating status of the heating device meeting process requirements, which needs to be verified through multi-dimensional collaborative verification of heating current, tank temperature changes, and steam valve status. The operating status of the stirring device can be specifically understood as: the operational stability and effectiveness of the stirring device, determined through stirring current data (reflecting whether the load is normal) and vibration data (reflecting whether the operation is stable).

[0065] Specifically, when extracting sugar that has passed the material access test through the target equipment with extraction authority, process condition detection must be performed simultaneously. The weight of the tank W_tank is monitored in real time by a static scale. When this data reaches the preset threshold W_threshold, such as 50 kg, the working status detection of the heating device and the stirring device is automatically triggered.

[0066] When testing the heating device, a current sensor is deployed in the heating device circuit to monitor its operating current (to determine if the heating power is normal). This data is compared with the preset normal operating current range. If the current is within the range, the heating power is considered normal; otherwise, the heating power is considered abnormal. A temperature sensor installed on the material tank continuously monitors the temperature change trend of the sugar in the tank (to determine if the heating effect meets the standard). If the temperature rises steadily with the heating time and meets the preset heating rate requirement, the heating effect is considered to be compliant. If the temperature does not change or the heating rate is too slow or too fast, the heating effect is considered abnormal. A valve position sensor collects the position signal of the steam valve (to determine if the heating medium supply is normal). If the signal shows that the valve is fully open, the heating medium supply is considered to be normal. If the signal shows that the valve is not open or not fully open, the heating medium supply is considered abnormal. Finally, the operating current, temperature change trend, and steam valve opening status are combined for a joint judgment. Only when all three data meet the preset standards is the operation of the heating device verified as compliant. If any data is abnormal, the operation of the heating device is considered non-compliant.

[0067] When testing the mixing device, a motor current sensor is installed in the motor circuit to collect real-time mixing current data (to determine the stability of the mixing load). The stability and fluctuation range of the current are analyzed. If the current fluctuation is within the preset allowable range, the mixing load is considered stable. If the current fluctuates significantly, rises sharply, or falls sharply, the mixing load is considered abnormal. Vibration sensors are deployed on the mixing device to collect vibration data during operation, including vibration frequency and amplitude. This data is compared with preset normal vibration parameter ranges. If the vibration data is within the range, the device is considered to be operating stably without jamming, abnormal noise, or other abnormalities. If the vibration frequency or amplitude exceeds the preset range, the device is considered to be operating abnormally. Finally, the load condition reflected by the mixing current data and the operational stability data collected by the vibration sensors are analyzed and verified together. If both data meet the preset standards, the mixing device is considered to be operating normally. If either data is abnormal, the mixing device is considered to be operating abnormally.

[0068] When both test results are compliant, the process condition test is deemed passed. Correspondingly, the parameter compliance test must be initiated under the dual premise that the feeding accuracy test and the process condition test are both passed. The temperature of the sugar material in the tank after extraction is collected by multiple temperature sensors. After confirming that the temperature is within the preset range and the duration of stability meets the requirements, the parameter compliance test is confirmed to be passed and the sugar material pre-filling operation is performed.

[0069] In addition to using static scale weight threshold to trigger detection, the detection parameters thresholds of the heating and stirring devices (such as current fluctuation range and upper limit of vibration frequency) can be flexibly adjusted according to the type of sugar and process requirements, such as material extraction time and tank liquid level. This further adapts to the process requirements of different production scenarios and ensures that the sugar has a uniform temperature and stable physical properties before pre-filling.

[0070] By collecting real-time weight data of the material tank using a static scale during the material extraction process, the heating and stirring device status detection is automatically triggered when a preset threshold is reached. This ensures that the device starts verification when the amount of sugar in the tank matches the process requirements, avoiding distorted detection results due to insufficient or excessive sugar content, and making the device status detection more closely reflect actual production scenarios. When detecting the heating device, current sensors, temperature sensors, and valve position sensors collect and collaboratively verify data on operating current, tank temperature changes, and steam valve status. This comprehensively confirms the compliance of the heating device's operation from three dimensions: heating power, heating effect, and media supply, preventing problems such as substandard sugar temperature and decreased fluidity caused by abnormal heating. When detecting the stirring device, through... Motor current sensors and vibration sensors collect operating current and vibration data and make comprehensive judgments, which can accurately identify abnormalities such as unstable stirring load, equipment jamming or abnormal noise, ensuring the uniformity of sugar mixing. The process condition test is only deemed to have passed when both heating and stirring devices are compliant, and this is used as a prerequisite for parameter compliance testing. Combined with subsequent temperature stability testing, a pre-filling operation is performed, forming a dual process guarantee of compliant device status and temperature compliance. This effectively avoids sugar quality defects caused by abnormal process conditions, ensuring that sugar can be applied accurately and uniformly according to the formula in subsequent tobacco leaf feeding processes, improving the consistency of the intrinsic quality and style of tobacco products, and reducing production interruptions and material losses caused by device failures or process deviations.

[0071] S270. During the sugar prefilling process, the prefilling flow rate and the weight of the prefilling tank are collected simultaneously. The prefilling flow rate is matched with the reference flow rate for flow rate verification. The pipeline sealing is verified based on the change in the weight of the prefilling tank and the pipeline parameters. When the flow rate matching verification and the pipeline sealing verification are passed, sugar that meets the quality requirements is obtained.

[0072] The technical solution of this invention uses a fixed barcode scanner to scan the identification code of the sugar barrel and parse it to obtain the actual brand, batch, preparation weight, and preparation time. This replaces the manual verification of material information, avoiding errors and omissions in manual identification and improving the efficiency and accuracy of material information collection. The actual material information is compared with preset process standards for consistency in brand and batch, deviation in preparation weight, and timeliness of preparation time. A multi-dimensional verification mechanism for material access is constructed from three dimensions: compliance, weight accuracy, and timeliness. This achieves comprehensive compliance screening of sugar materials, accurately eliminating substandard sugar materials with misused brands, incorrect batches, inconsistent weights, or expired use from the source of material preparation. This avoids problems such as distorted tobacco leaf formulations and product quality deviations caused by non-compliant materials. By setting quantitative comparison standards and implementing a full-item compliance judgment principle, material access testing has a unified and rigid execution basis, eliminating standard fluctuations caused by manual experience judgment and ensuring the consistency and reliability of test results in the material access process. After screening, the status data of the target equipment is collected and it is confirmed that it meets the conditions for material extraction. Before extraction, the extraction permission is unlocked by verifying the deviation between the cumulative weight data and the standard weight of the first work order. After extraction, the feeding accuracy is confirmed by verifying the actual weight with the standard weight of the second work order. The temperature of the sugar material is collected and it is confirmed that it meets the stability conditions. During the pre-filling process, the flow matching degree and pipeline sealing are verified simultaneously to obtain sugar material that meets the quality requirements. This not only ensures the accuracy of sugar material delivery, but also detects hidden faults such as pipeline blockage and leakage in a timely manner, improving the fault detection range and timeliness, and avoiding the expansion of faults that may cause production interruptions. The entire process forms a full-process quality protection chain through progressive detection and data verification at each stage, reducing the uncertainty and maintenance costs caused by manual intervention, achieving high-quality, high-reliability, and high-stability output in the material preparation process, improving the level of intelligence in material preparation, and providing a reliable guarantee for the quality consistency of subsequent tobacco leaf feeding processes.

[0073] Example 3 Figure 3 This is a flowchart of another quality control method for preparing tobacco leaf sugar feed according to Embodiment 3 of the present invention. This embodiment is a refinement of the above embodiment's step of "collecting the temperature of the sugar feed in the tank after extraction, confirming that the temperature after extraction meets the stability condition, confirming that the parameters meet the standard and passing the test, and performing the sugar feed pre-filling operation." Figure 3 As shown, the method includes: S310. Collect the material access information of the target sugar and compare it with the preset process standards to screen out the target sugar that has passed the material access test.

[0074] S320. After screening out the target sugar material that has passed the material access test, collect the target equipment status data, and after confirming that the target equipment status data meets the preset ready conditions, confirm that the target equipment is in the material extraction ready state.

[0075] S330. Before performing the material extraction operation on the target sugar that has passed the material access detection through the target equipment that is in the material extraction ready state, collect the cumulative weight data and perform the first deviation verification with the standard weight of the first work order. After the verification is passed, unlock the material extraction permission of the target equipment.

[0076] S340. After the target sugar that has passed the material access test is extracted by the target equipment with extraction authority, the actual weight data of the tank after extraction is collected and the second deviation is checked with the standard weight of the second work order. After the verification meets the preset accuracy requirements, the feeding accuracy test is confirmed to be passed.

[0077] S350: After confirming that the feeding accuracy test has passed, the temperature data of the sugar material at the corresponding monitoring point in the tank is collected by multiple temperature sensors.

[0078] S360 compares each set of collected temperature data with the preset temperature range and calculates the standard deviation of temperature data from multiple monitoring points to verify temperature stability.

[0079] S370. When all temperature data are within the preset temperature range and the temperature remains stable for the preset stability time, the parameter compliance test is passed, and the sugar pre-filling operation is performed.

[0080] In this embodiment of the invention, the preset stability condition can be specifically understood as: the temperature must meet the requirement of continuous qualified duration to ensure that the temperature is stable rather than instantaneously meeting the standard.

[0081] Specifically, in the parameter compliance testing process, multiple temperature sensors (such as platinum resistance temperature sensors) are used to collect the temperature data (Temp_actual) of the sugar material after extraction from the corresponding monitoring points (such as the top, middle, bottom, and side wall perimeter) inside the tank, ensuring that the monitoring points cover the key areas of the sugar material inside the tank and avoid monitoring blind spots. Then, each set of collected temperature data is compared with the preset temperature range (e.g., T_set-3°C ≤Temp_actual ≤T_set+3°C, where T_set is the process set temperature) to ensure that the temperature of each monitoring point is within the qualified range.

[0082] Simultaneously, the standard deviations of temperature data from multiple monitoring points are calculated, i.e., the standard deviations of each set of temperature data, to verify the uniformity of the sugar material temperature distribution within the tank and avoid excessive local temperature differences. The calculated standard deviations are compared with a preset uniformity threshold. If the standard deviations are all less than or equal to the threshold, it indicates that the temperature differences between monitoring points are small, the sugar material temperature distribution within the tank is uniform, and there are no excessive local temperature differences. If any standard deviation exceeds the threshold, the temperature distribution is determined to be uneven, and optimization is required by extending the stirring time, adjusting the heating device power, etc. Subsequent pre-filling operations can only be performed after the temperature distribution meets the standard, thereby ensuring the consistency of the overall sugar material process state.

[0083] At the same time, the temperature status is continuously monitored to confirm whether the temperature remains stable within the acceptable range for the preset stability time (e.g., greater than or equal to 5 minutes), thereby ensuring the reliability of the process temperature.

[0084] When all temperature data are within the preset range, temperature stability meets the standard, and the duration of stability meets the requirements, the parameter compliance test is deemed passed, and the sugar pre-filling operation is then performed; if any condition is not met, it is necessary to investigate, adjust, and retest.

[0085] S380. During the sugar prefilling process, the prefilling flow rate and the weight of the prefilling tank are collected simultaneously, and the prefilling flow rate is matched with the reference flow rate for flow matching verification. The pipeline sealing is verified based on the change in the weight of the prefilling tank and the pipeline parameters. When the flow matching verification and the pipeline sealing verification are passed, sugar that meets the quality requirements is obtained.

[0086] Optionally, based on the above embodiments, during the sugar pre-filling process, the pre-filling flow rate and the weight of the pre-filling tank are simultaneously collected, and the pre-filling flow rate is compared with the reference flow rate for flow matching verification. Additionally, the pipeline sealing is verified based on the change in the weight of the pre-filling tank and the pipeline parameters. This may include: During the sugar prefilling process, the prefilling flow rate is collected by a mass flow meter and matched with the benchmark flow rate calculated based on the tobacco flow rate and the feeding ratio for flow rate matching verification. The weight data of the pre-filled tank is collected by a static scale at preset time intervals, the weight reduction value is calculated, and the pipeline sealing is verified by comparing it with the theoretical capacity of the pipeline calculated based on the pipeline size and sugar density.

[0087] Specifically, during the sugar filling process, flow rate monitoring and weight change monitoring are performed. Flow rate matching verification involves real-time acquisition of the pre-filling flow rate F_pre using a mass flow meter, comparing it with the baseline flow rate F_base calculated based on the tobacco leaf flow rate F_t and the feeding ratio R. Verification is made to ensure that F_pre is greater than or equal to F_base, guaranteeing that the flow rate meets process requirements. Since the baseline flow rate F_base is the minimum effective flow rate calculated based on the tobacco leaf flow rate F_t and the preset feeding ratio R (F_base = F_t × R), it directly corresponds to the standard sugar application amount required in subsequent tobacco leaf feeding processes. If F_pre is less than F_base, it means that the actual sugar flow rate delivered does not meet the process formula requirements, leading to insufficient sugar application on the tobacco leaf surface, compromising the consistency of the product's intrinsic quality and style. Simultaneously, insufficient flow may imply hidden fault risks such as pipeline blockage; if not identified in time, these risks can escalate as production progresses, potentially causing production interruptions or batch quality incidents. By verifying that F_pre≥F_base, we can ensure that the sugar delivery volume meets the process requirements and guarantee the feeding accuracy. Furthermore, by judging the conformity of the flow data, we can indirectly identify potential problems affecting the flow, such as pipeline blockage. This provides a basic guarantee for the stability and safety of the pre-filling process, which aligns with the goals of full-process quality protection and early identification of hidden faults.

[0088] Pipeline sealing verification involves collecting weight data from pre-filled tanks using a static scale at preset time intervals (e.g., 1-second intervals) for a preset duration (e.g., 3 minutes). The data is then processed using a moving average algorithm to calculate the weight reduction value ΔW. This involves setting a fixed-length continuous data window, averaging the weight data collected in real-time within the window, and using this average to replace the original data or the final instantaneous data within the window. This filters out random fluctuations and measurement noise, allowing the data to better reflect the true weight change trend. Specifically, the sliding window size is first determined (e.g., 5 data points corresponding to 5 seconds). Weight data is collected at preset time intervals. For each new data point, the oldest data point within the window is removed. The arithmetic mean of all data within the window is then calculated to generate a smoothed weight sequence. The smoothed weight difference between the initial and final times is selected as the weight reduction value ΔW. The preset time interval ensures high-density data collection, which can accurately capture subtle changes in weight while avoiding data redundancy. This provides sufficient raw data for the algorithm, and continuous monitoring for the preset duration ensures that the weight of the tank has a sufficient range of change, covering the stable sugar delivery stage. It also eliminates the interference of instantaneous fluctuations at the beginning of startup, making the ΔW calculation more accurate and thus improving the reliability of pipeline sealing verification.

[0089] Simultaneously, based on the pipe diameter D, pipe length L, and sugar density ρ, the formula W_pipe=π×(D / 2) is used. 2The theoretical material capacity of the pipeline is calculated using ×L×ρ. The pipeline sealing is then verified by combining the weight reduction value. For example, the verification is ΔW≤W_pipe+0.5 kg (0.5 kg is the detection tolerance, which can be set according to business needs to balance detection sensitivity and anti-interference ability. This avoids misjudging leakage when ΔW is slightly higher than W_pipe due to normal process fluctuations such as static scale weighing error, sugar residue, and minor adhesion to the pipeline. At the same time, it can accurately identify actual leakage by limiting the tolerance range).

[0090] Since the conveying path in the pre-filling stage is fixed (i.e., a specific pipe with known diameter D and length L), and there are no other diversion or conveying paths, the weight reduction value ΔW obtained by collecting data through a static scale and processing it using a moving average algorithm is essentially the actual total weight of the sugar flowing out of the tank and into the fixed pipe, which directly corresponds to the length L of this pipe.

[0091] If both verifications pass, the pipeline is considered to be operating normally and the system integrity test is considered passed.

[0092] By collecting the pre-filling flow rate using a mass flow meter during the sugar pre-filling process and matching it with the benchmark flow rate calculated based on the tobacco leaf flow rate and the feeding ratio, it is possible to accurately ensure that the actual delivery flow rate meets the process formula requirements, avoiding insufficient tobacco leaf feeding due to insufficient flow rate, ensuring the consistency of the product's intrinsic quality and style, and indirectly identifying hidden faults affecting flow rate such as pipeline blockage. By collecting tank weight data at preset time intervals using a static scale and calculating the weight reduction value, and then verifying the sealing performance against the theoretical material capacity of the pipeline obtained based on the pipeline size and sugar density, it is possible to accurately identify problems such as micro-leakage in the pipeline, preventing material loss and environmental pollution, and avoiding feeding accuracy deviations caused by leakage. This dual monitoring method of flow rate and weight coordination avoids the limitations of single parameter monitoring. By mutually verifying and coordinating the two data, the ability to identify hidden faults is improved, ensuring the stability and reliability of the pre-filling process, further improving the whole-process quality protection system, reducing production interruptions and quality accidents caused by system integrity issues, and improving the safety, accuracy, and efficiency of the sugar preparation process.

[0093] Furthermore, based on the above embodiments, after obtaining sugar that meets the quality requirements, the method further includes: Acquire time-series data of prefilling flow rate and prefilling tank weight during the sugar prefilling process, as well as time-series data of temperature of sugar in the tank after extraction during parameter compliance testing. The time series data is input into a preset multi-parameter collaborative analysis model. The multi-parameter collaborative analysis model calculates the deviation amplitude and fluctuation frequency between the pre-filled flow and the baseline flow based on the pre-filled flow time series data, and determines whether the pre-filled flow is abnormal according to the matching rules. The weight change is calculated based on the time series data of the prefill tank weight using a multi-parameter collaborative analysis model. The deviation and fluctuation frequency of the weight change from the pipeline parameters are also calculated. Based on the matching rules, it is determined whether the weight of the prefill tank is abnormal. The fault type is determined based on the output results of the multi-parameter collaborative analysis model. If the abnormal flow rate is determined to be abnormal and the abnormal weight is determined to be abnormal, then the fault is determined to be a pipe blockage or leakage. A multi-parameter collaborative analysis model was used to perform trend fitting analysis on the time series data of pre-filled flow rate, pre-filled tank weight, and post-extraction temperature to determine the trend analysis results of the data change slope and fluctuation amplitude. If the weight anomaly determination result is normal, the flow anomaly determination result is abnormal, and the trend analysis result shows that the deterioration trend of the flow time series data continues for more than the preset time, it is determined to be a potential pipeline fault.

[0094] In this embodiment of the invention, time-series data can be specifically understood as: dynamic data continuously collected at preset time intervals covering the entire period of pre-filling or parameter compliance detection (such as continuous collection data of pre-filling flow rate, tank weight and sugar temperature), which can reflect the changing trend of parameters over time and provide dynamic basis for fault analysis.

[0095] The multi-parameter collaborative analysis model can be understood as follows: it integrates multi-dimensional data such as flow rate, weight, and temperature, and realizes an algorithm model for fault identification through logic such as deviation calculation, fluctuation frequency analysis, and trend fitting. This model differs from single-parameter judgment and improves the accuracy of fault identification.

[0096] Deviation amplitude and fluctuation frequency can be specifically understood as follows: Deviation amplitude refers to the percentage or absolute difference between the actual parameter (such as the change in prefilled flow rate and weight) and the benchmark value (such as the benchmark flow rate and the theoretical capacity of the pipeline); fluctuation frequency refers to the number of times the parameter deviates from the normal range per unit time. The combination of the two can determine the severity and stability of the parameter abnormality.

[0097] Trend fitting analysis can be understood as follows: by processing time series data through mathematical modeling (such as linear fitting or nonlinear fitting), determining the trend of changes in the slope of data change (reflecting the rate of parameter change) and the amplitude of fluctuation, and identifying whether the parameters have dynamic characteristics of continuous deterioration or improvement.

[0098] Specifically, based on dynamic time-series data collected throughout the entire material preparation process, hidden faults are identified and managed hierarchically through multi-parameter collaborative analysis.

[0099] Acquire time-series data on prefill flow rate, prefill tank weight, and post-extraction temperature during parameter compliance testing. These data cover the entire testing period to ensure that dynamic changes in parameters can be captured.

[0100] Time-series data is input into a pre-built multi-parameter collaborative analysis model to determine anomalies in flow rate and weight, respectively.

[0101] During the process of determining abnormal flow, the deviation of the pre-filled flow from the baseline flow (such as the percentage difference between the actual flow and the baseline flow) and the fluctuation frequency (such as the number of times the flow exceeds the normal range per unit time) are calculated. If any of these conditions are not met (such as deviation exceeding ±5% and fluctuation frequency ≥ 3 times / minute), the flow is determined to be abnormal.

[0102] In the process of determining weight anomalies, the weight change is calculated based on the time series data of the pre-filled tank weight, and then the deviation value and fluctuation frequency of the theoretical material capacity of the pipeline determined based on the pipeline size and sugar density are calculated. If any of these conditions are not met (such as deviation value exceeding 0.5 kg and fluctuation frequency ≥ 2 times / minute), the weight is determined to be abnormal.

[0103] In the system integrity testing of sugar prefilling, flow rate and weight data are strongly correlated with the process. The prefilling flow rate directly reflects the sugar delivery rate in the pipeline, while the weight reduction in the tank corresponds to the actual total amount of sugar delivered in the pipeline. The two data mutually verify the material transport status of the pipeline from the perspectives of rate and total volume. If there is a blockage in the pipeline, it will directly lead to obstruction of sugar delivery, manifested as the prefilling flow rate collected by the mass flow meter being lower than the baseline flow rate (flow anomaly). At the same time, the sugar outflow velocity in the tank slows down, and the weight reduction is much lower than the theoretical capacity of the pipeline (weight anomaly). If there is a leak in the pipeline, the sugar will seep out during delivery. In this case, the flow rate may fluctuate or be lower due to the leak, and the actual weight reduction in the tank will be much greater than the actual amount of sugar that the pipeline can hold due to material loss (weight anomaly). Both types of faults will simultaneously cause dual data anomalies in flow rate and weight, with no possibility of a single parameter anomaly. In addition, an anomaly in either the flow rate or weight parameter alone may be caused by non-pipeline physical faults such as temporary sensor errors or short-term process fluctuations. However, dual anomalies can rule out such accidental factors and accurately point to a blockage or leak in the pipeline itself. Therefore, if the flow rate and weight are abnormal, it is determined to be a pipe blockage or leakage fault (such faults have already had a substantial impact on production and require urgent handling).

[0104] Preprocessing was performed on three types of time-series data: pre-filling flow rate, pre-filling tank weight, and post-extraction temperature. Abnormal noise was removed, and the data was standardized and aligned to ensure the comparability of the three types of data in both time and numerical dimensions. Subsequently, the preprocessed time-series data was input into a multi-parameter collaborative analysis model. The model applied appropriate trend fitting algorithms, such as linear or nonlinear fitting, to the data. For example, curve fitting was performed on continuous data points of each parameter changing over time to calculate the slope of change for each type of data within a preset time period. This quantified the rate of change of the parameters (such as the rate of continuous decrease in flow rate, steady decrease in weight, and slow increase in temperature). At the same time, by calculating the variance and extreme value difference of the data deviating from the fitted curve, the fluctuation range of each type of data within the corresponding time period was determined, thus determining the stability of parameter changes.

[0105] The model integrates the slopes and fluctuation amplitudes of the three types of data to establish a logical framework for the time-series correlation of the pre-filling process. It determines the theoretical synergistic relationship between flow rate, weight, and temperature at different process stages (start-up, stabilization, and termination) (e.g., in the stable pre-filling stage, flow rate should remain constant, weight should decrease at a uniform rate, and temperature should remain stable). The model compares the slopes of each parameter (e.g., flow rate decrease slope, weight decrease slope, and temperature fluctuation slope) with the fluctuation amplitudes (e.g., flow rate variance, weight extreme value difference, and temperature standard deviation) across parameters, calculating the correlation coefficients between parameters (e.g., the negative correlation between flow rate and weight, and the negative correlation between temperature and flow rate). (Independence of quantity or weight) to verify whether actual changes conform to theoretical synergistic logic; for time-series synchronization analysis, to determine whether the time nodes of abnormal changes in the three types of parameters are consistent (such as whether the sudden drop in flow rate and the sudden change in the rate of weight reduction occur synchronously, whether temperature fluctuation is accompanied by abnormal flow or weight), to identify isolated anomalies of single parameters and linkage anomalies of multiple parameters; to integrate the slope and amplitude characteristics of single parameters with the correlation and synchronization analysis results of multiple parameters, to mark the compliance range and abnormal deviation of parameter synergistic changes, and to form a complete trend analysis result that includes the dynamic characteristics of single parameters, cross-parameter synergistic laws and process adaptability assessment.

[0106] If the weight is normal but the flow rate is abnormal, but the trend analysis results show that the flow time series data shows a deteriorating trend (such as a continuous decrease in flow rate or a continuous increase in the fluctuation range) for more than the preset time (such as 5 minutes), it is judged as a potential pipeline fault. Such faults have not yet caused serious impacts, but there is a risk of deterioration, and early warning and control are required.

[0107] Understandably, a normal weight indicates that the actual total amount of sugar flowing out of the tank has not deviated from the theoretical capacity of the pipeline, and there are no substantial physical faults such as leaks or blockages in the pipeline. It also rules out problems such as weighing errors and large fluctuations in the process. However, the abnormal flow rate, which shows a deteriorating trend of continuous decline and increasing fluctuations and exceeds the preset time, is not caused by accidental factors such as temporary sensor errors or short-term process disturbances. Rather, it indicates that there are hidden problems inside the pipeline that have not yet affected the total material transport volume, such as slight scaling on the inner wall of the pipeline, early signs of local micro-blockage, or initial valve jamming. These problems have not yet caused substantial impact on production, but if they are not warned and controlled in time, they will continue to deteriorate as production progresses, eventually leading to serious faults such as pipeline blockage and leakage, resulting in both abnormal flow rate and weight. Therefore, this situation is identified as a potential pipeline fault, which can identify the fault signs in advance and avoid excessive intervention in normal production, achieving a balance between early fault warning and production continuity.

[0108] If the flow rate is abnormal but the weight is normal, and the trend analysis shows no continuous deterioration (e.g., the flow rate stabilizes after fluctuations and the slope of change becomes gentler), or the flow rate is normal but the weight is abnormal (this needs to be combined with temperature data for further judgment; if the temperature is normal and the weight fluctuation is within a reasonable range, it may be a weighing error or a short-term process fluctuation; if the temperature abnormality is accompanied by the weight abnormality, further investigation is needed to check for equipment heating or stirring system failures), or all three parameters are normal, then it is determined to be a fault-free or slightly fluctuating process, and the system will maintain normal operation and continuous monitoring.

[0109] Understandably, if the flow rate is abnormal but the weight is normal, and the trend analysis shows no continuous deterioration, it indicates that the temporary flow rate abnormality is caused by non-continuous factors such as instantaneous sensor error, process fluctuations at the initial stage of pre-filling, and temporary changes in the material's flow state. This does not have a substantial impact on the total amount of material transported through the pipeline, nor is there a risk of the fault worsening. When the flow rate is normal but the weight is abnormal, temperature data can be used to assist in the judgment. If the temperature is normal and the weight fluctuation is within a reasonable range, it indicates that the weight abnormality is not caused by a process system failure, but by normal process deviations such as the weighing error of the static scale and a small amount of sugar adhering to the wall. If the temperature abnormality is accompanied by the weight abnormality, it is necessary to investigate the heating and stirring system for failure, rather than the pipeline transport link. When all three parameters are normal, it indicates that the process status of each link in the pre-filling and parameter compliance testing meets the preset standards, with no abnormal characteristics. In all of the above situations, there is no substantial pipeline failure, nor is there any risk of potential worsening of the pipeline failure. There is no need to initiate rigid control measures such as shutdown or equipment locking. Therefore, it is determined to be a fault-free or minor process fluctuation. The system maintains normal operation and continuous monitoring, which can avoid production interruptions caused by misjudgment and capture any subsequent anomalies in a timely manner through continuous monitoring, thus balancing the sensitivity of fault identification with the continuity of production.

[0110] Accordingly, a tiered response can be executed based on the fault determination results: if the fault is confirmed to be a pipeline blockage or leakage, the system immediately triggers rigid interlock control (such as emergency shutdown and locking of pre-filling operation) and issues the highest level alarm; if the fault is a potential pipeline fault, the system issues an early warning and continuously monitors flow, weight and temperature data. If the deterioration trend does not ease, the control measures are upgraded; if there is no fault or slight fluctuation, the system records the data and continues to execute subsequent processes to ensure production continuity.

[0111] By acquiring full-time time-series data on pre-filling flow rate, tank weight, and post-extraction temperature, the dynamic changes of parameters in key material preparation stages can be fully captured, providing continuous and comprehensive raw data for fault analysis and avoiding misjudgments caused by the incompleteness of data from a single time point. Inputting the time-series data into a multi-parameter collaborative analysis model calculates the deviation amplitude and fluctuation frequency of flow rate and weight from corresponding benchmark values ​​and identifies parameter anomalies. This allows for accurate identification of anomalies from both numerical deviation and fluctuation characteristics, establishing a quantitative basis for preliminary fault assessment. Based on the abnormal results of flow rate and weight, pipeline blockage or leakage faults can be directly identified. The strong correlation between these two parameters in the process eliminates interference from accidental factors, enabling accurate identification of substantial pipeline faults and timely pinpointing of serious fault types. The model performs trend fitting analysis on three types of time-series data. By analyzing and determining the slope and fluctuation range of data changes, the system can quantify the trend and stable state of parameter changes, overcoming the limitations of static numerical judgment. Combined with the characteristics of normal weight, abnormal flow rate, and a flow rate deterioration trend exceeding a preset duration, it can identify potential pipeline faults, accurately identifying hidden problems such as minor scaling on the pipeline inner wall and valve jamming that have not yet caused substantial impact, achieving early warning of faults. It can quickly identify existing substantial pipeline faults and also detect potential faults in advance, achieving graded identification and precise control of faults. This avoids production interruptions, material losses, and product quality deviations caused by fault escalation, while reducing downtime due to misjudgment caused by occasional anomalies in a single parameter. It balances fault detection sensitivity and production continuity, further improving the quality protection system of the entire sugar raw material preparation process and enhancing the stability and reliability of the entire preparation process.

[0112] In a specific example, a quality control system for tobacco leaf processing and sugar preparation can consist of a full-process detection network, a rule engine decision center, a data fusion processing platform, an emergency control execution unit, and hardware configuration under a hierarchical distributed architecture.

[0113] The end-to-end detection network serves as the core of data acquisition, integrating fixed industrial barcode scanners (used to parse sugar barrel identification codes and collect material identity, weight, and timeliness information), high-precision static scales (0.05 kg resolution, enabling verification of empty tank status and accurate weighing before and after material extraction), platinum resistance temperature sensors (0.5 degrees Celsius accuracy, monitoring the temperature and temperature change trend of sugar in the tank), mass flow meters (0.5% accuracy, collecting pre-filling flow data), and valve position sensors (confirming the on / off status of manual valves, steam valves, etc.), comprehensively covering the data acquisition needs of all stages of material preparation.

[0114] The rule engine decision center adopts a four-layer architecture (data acquisition layer for real-time data acquisition and verification, rule matching layer for fast matching based on business rules, decision reasoning layer for integrating trend analysis algorithms to predict anomalies, and control output layer for generating control commands and alarm information). It is pre-configured with six detection logic algorithms and rigid interlocking control strategies for data processing, fault determination and decision output.

[0115] The data fusion processing platform is used for data synchronization, enabling data interconnection and interoperability between the manufacturing execution system (work order and recipe management), the programmable logic controller control system (equipment control and data acquisition), and the testing network.

[0116] The emergency control execution unit supports collaborative operation of multiple devices and performs graded safety responses based on the severity of the anomaly to ensure process stability.

[0117] In terms of hardware configuration, the central control unit adopts an industrial server, the data acquisition unit uses a programmable logic controller system, and the network communication adopts an industrial Ethernet switch and a process fieldbus, providing hardware support for the stable operation of the system.

[0118] This system constructs a progressive quality protection network through a six-fold detection system across the entire process, achieving end-to-end coverage from material access, equipment readiness, feeding accuracy, process conditions, parameter compliance to system integrity, thus solving the problem of breaks in the quality protection chain during traditional material preparation. A hidden fault identification mechanism, through coordinated monitoring of flow and weight, trend analysis and early warning, and multi-sensor data fusion, accurately identifies difficult-to-detect hidden faults such as pipe blockages and micro-leaks, improving hidden fault detection capabilities and preventing fault escalation that could lead to production interruptions or quality deviations. A rigid control system based on a rule engine, through strict condition constraints, process locking during anomalies, and tiered responses, transforms process execution from relying on human experience to following digital rules, improving quality control levels and process execution consistency. A layered distributed architecture and high-performance hardware configuration ensure system stability and real-time data transmission. A data fusion processing platform achieves multi-system information fusion, improving production efficiency. Simultaneously, through the comprehensive application of preventative, process, and corrective controls, it reduces quality accidents and unplanned downtime at the source, lowers maintenance costs, and comprehensively enhances system reliability.

[0119] The technical solution of this invention collects the material access information of the target sugar and compares it with preset process standards. After screening, it collects the status data of the target equipment and confirms that it meets the material extraction readiness conditions. Before extraction, the extraction permission is unlocked by verifying the deviation between the accumulated weight data and the standard weight of the first work order. After extraction, the feeding accuracy is confirmed by verifying the actual weight with the standard weight of the second work order. By deploying multiple temperature sensors in the tank to collect sugar temperature data at corresponding monitoring points, it is possible to achieve full-area, no-dead-angle monitoring of the sugar temperature in the tank, avoiding the drawback of single-point temperature measurement not being able to reflect the overall temperature state of the sugar, and accurately grasping the actual temperature of the sugar at different locations in the tank. By comparing each set of collected temperature data with the preset temperature range one by one, it can ensure from the basic level that the temperature of each monitoring point of the sugar meets the process requirements. Then, by calculating the standard deviation of the temperature data of multiple monitoring points, it verifies the temperature stability, and can further determine whether the sugar temperature in the tank is uniform and without local temperature differences, ensuring that the overall process state of the sugar meets the standards. Simultaneously, a preset condition for the duration of temperature stability is set and executed, avoiding situations where the temperature reaches the standard momentarily but then fluctuates subsequently. This ensures that the sugar material temperature remains in a consistently stable and qualified state. Based on this, the sugar material pre-filling operation is then performed, which can effectively avoid problems such as abnormal sugar material viscosity, poor conveying, and poor integration with tobacco leaves caused by inconsistent, uneven, or unstable sugar material temperatures. This ensures the smooth progress of the subsequent pre-filling process and lays the foundation for the uniform mixing and full integration of sugar material and tobacco leaves in the subsequent tobacco leaf feeding process. This improves the process effect of tobacco leaf feeding and ultimately ensures the consistency of the intrinsic quality and style of tobacco products. During the pre-filling process, the flow matching and pipeline sealing are verified simultaneously to obtain sugar materials that meet quality requirements. This ensures the accuracy of sugar material delivery and allows for the timely detection of hidden faults such as pipeline blockages and leaks, improving the scope and timeliness of fault detection and preventing production interruptions caused by the escalation of faults. The entire process forms a full-process quality protection chain through progressive testing and data verification at each stage, reducing the uncertainty and maintenance costs caused by manual intervention. This achieves high-quality, high-reliability, and high-stability output in the material preparation process, improves the level of intelligence in material preparation, and provides a reliable guarantee for the quality consistency of subsequent tobacco leaf feeding processes.

[0120] Example 4 Figure 4 This is a schematic diagram of a quality control device for preparing tobacco leaf additives and sugars, provided in Embodiment 4 of the present invention. Figure 4 As shown, the device includes: an admission screening module 410, a material extraction readiness module 420, a material extraction authorization module 430, a precision detection module 440, a temperature detection module 450, and a pre-filling module 460, wherein: The access screening module 410 is used to collect the material access information of the target sugar and compare it with the preset process standards to screen out the target sugar that has passed the material access test. The material extraction ready module 420 is used to collect target equipment status data after screening out target sugar materials that have passed the material access detection, and to confirm that the target equipment is in the material extraction ready state after confirming that the target equipment status data meets the preset ready conditions. The material extraction permission module 430 is used to collect cumulative weight data and perform a first deviation verification with the standard weight of the first work order before performing the material extraction operation on the target sugar that has passed the material access detection through the target device in the material extraction ready state. After the verification is passed, the material extraction permission of the target device is unlocked. The accuracy detection module 440 is used to collect the actual weight data of the tank after the material access detection is completed by the target equipment with the material extraction permission to extract the target sugar. The actual weight data is then compared with the standard weight of the second work order to perform a second deviation verification. After the verification meets the preset accuracy requirements, the feeding accuracy detection is confirmed to be passed. The temperature detection module 450 is used to collect the temperature of the sugar material in the tank after the feeding accuracy test is passed. After confirming that the temperature after feeding meets the stability condition, the parameter meets the standard test and the sugar material pre-filling operation is performed. The prefilling module 460 is used to simultaneously collect the prefilling flow rate and the weight of the prefilling tank during the sugar prefilling process, and to perform flow matching verification between the prefilling flow rate and the reference flow rate, as well as to perform pipeline sealing verification based on the change in the weight of the prefilling tank and the pipeline parameters. When the flow matching verification and the pipeline sealing verification are passed, sugar that meets the quality requirements is obtained.

[0121] The technical solution of this invention, by collecting the material access information of the target sugar and comparing it with preset process standards, can accurately screen out sugars that comply with the requirements of identity, weight, and timeliness, thus avoiding quality deviations caused by material misuse from the source and deepening the error prevention depth. After screening, the status data of the target equipment is collected and confirmed to meet the material extraction readiness conditions, which can eliminate potential equipment failures in advance and ensure the continuity of the material preparation process. Before extraction, the extraction permission is unlocked by verifying the deviation between the accumulated weight data and the standard weight of the first work order. After extraction, the feeding accuracy is confirmed by verifying the actual weight with the standard weight of the second work order. This dual control can improve the feeding accuracy and reduce the risk of formula distortion. After extraction, the temperature of the sugar is collected and its temperature is confirmed. Meeting stable conditions ensures the sugar material process meets standards, laying the foundation for subsequent feeding processes. During pre-filling, flow matching and pipeline sealing are simultaneously verified to obtain sugar material that meets quality requirements. This ensures sugar material delivery accuracy and timely detection of hidden faults such as pipeline blockages and leaks, improving the scope and timeliness of fault detection and preventing production interruptions caused by escalating faults. The entire process forms a comprehensive quality protection chain through progressive testing and data verification at each stage, reducing the uncertainty and maintenance costs associated with manual intervention. This achieves high-quality, high-reliability, and high-stability output in the material preparation process, improving the level of intelligence in material preparation and providing a reliable guarantee for the consistency of quality in subsequent tobacco leaf feeding processes.

[0122] Based on the above embodiments, the admission screening module 410 is specifically used for: By scanning the identification code of the sugar barrel with a fixed barcode scanner, the actual brand, batch, weight, and preparation time of the sugar are obtained as material access information. The actual brand is compared with the preset standard brand in the preset process standard, and the actual batch is compared with the preset standard batch in the preset process standard. The actual weight is compared with the preset standard weight in the preset process standard. The absolute value of the difference between the current time and the actual preparation time is compared with the preset standard time limit in the preset process standard. When all comparison items meet the preset process standard, the material access test is deemed to have passed, and the target sugar that has passed the material access test is selected.

[0123] Based on the above embodiments, the material extraction ready module 420 is specifically used for: The initial weight data of the target material tank is collected by a static scale as the target equipment status data, and it is verified whether the initial weight data meets the weight requirements corresponding to the empty material tank state. The position signal of the material discharge manual valve is collected by a valve position sensor as the target equipment status data, and it is verified whether the valve is in a fully closed state. The pressure data of the pipeline system is collected by a pressure sensor as the target equipment status data, and it is verified whether the pipeline sealing meets the standard. When the initial weight data meets the weight requirements corresponding to the empty material tank state, the valve is in a fully closed state, and the pipeline sealing meets the standard, it is determined that the target equipment status data meets the preset ready conditions, and the target equipment is confirmed to be in the material extraction ready state.

[0124] Furthermore, based on the above embodiments, the quality control device for preparing tobacco leaf feed and sugar can also include: a working detection module, a compliance detection module, a verification mixing module, and a process pass module, wherein: The working detection module is used to collect the weight data of the tank in real time through a static scale during the material access detection process of the target sugar material that has passed the material extraction operation through the target device with extraction permission. When the weight data reaches the preset threshold, the working status detection of the heating device and the stirring device is triggered. The compliance testing module is used to collect heating current data of the heating device through a current sensor, collect tank temperature change data through a temperature sensor, and confirm the steam valve status through a valve position sensor during the status testing of the heating device. Based on the heating current data, tank temperature change data, and steam valve status, the module verifies the compliance of the heating device's operation. The verification stirring module is used to collect the stirring current data of the stirring device through the motor current sensor and the vibration data of the stirring device through the vibration sensor during the status detection of the stirring device, and to verify the working status of the stirring device based on the stirring current data and vibration data. The process pass module is used to determine that the process condition test is passed when the working status test results of the heating device and the stirring device are both compliant. Accordingly, based on the above embodiments, the temperature detection module 450 is specifically used for: After confirming that the feeding accuracy test and the process condition test have passed, the temperature of the sugar material in the tank after extraction is collected. After confirming that the temperature after extraction meets the stability condition, the parameter standard test is confirmed to be passed and the sugar material pre-filling operation is performed.

[0125] Based on the above embodiments, the temperature detection module 450 is further used for: The temperature data of the sugar material at corresponding monitoring points inside the tank are collected by multiple temperature sensors; Each set of collected temperature data is compared with the preset temperature range, and the standard deviation of temperature data from multiple monitoring points is calculated to verify temperature stability. When all temperature data are within the preset temperature range and the temperature remains stable for the preset stability time, the parameter compliance test is passed, and the sugar pre-filling operation is performed.

[0126] Based on the above embodiments, the pre-filling module 460 is specifically used for: During the sugar prefilling process, the prefilling flow rate is collected by a mass flow meter and matched with the benchmark flow rate calculated based on the tobacco flow rate and the feeding ratio for flow rate matching verification. The weight data of the pre-filled tank is collected by a static scale at preset time intervals, the weight reduction value is calculated, and the pipeline sealing is verified by comparing it with the theoretical capacity of the pipeline calculated based on the pipeline size and sugar density.

[0127] Furthermore, based on the above embodiments, the quality control device for preparing tobacco leaf feed and sugar can also include: a temperature timing module, a flow rate detection module, a weight detection module, a first determination module, a trend fitting module, and a second determination module, wherein: The temperature timing module is used to acquire the pre-filling flow rate timing data and pre-filling tank weight timing data collected during the sugar pre-filling process after obtaining sugar that meets the quality requirements, as well as the temperature timing data of the sugar in the tank after being pumped out during the parameter compliance test. The flow detection module is used to input time-series data into a preset multi-parameter collaborative analysis model. Based on the pre-filled flow time-series data, the multi-parameter collaborative analysis model calculates the deviation amplitude and fluctuation frequency between the pre-filled flow and the baseline flow, and determines whether the pre-filled flow is abnormal according to the matching rules. The weight detection module is used to calculate the weight change based on the time series data of the prefill tank weight through a multi-parameter collaborative analysis model, and to calculate the deviation value and fluctuation frequency of the weight change from the pipeline parameters. Based on the matching rules, it determines whether the weight of the prefill tank is abnormal. The first judgment module is used to determine the fault type based on the output results of the multi-parameter collaborative analysis model. If the abnormal flow judgment result is abnormal and the abnormal weight judgment result is abnormal, then it is judged as a pipeline blockage or leakage fault. The trend fitting module is used to perform trend fitting analysis on the pre-filling flow rate time series data, pre-filling tank weight time series data, and post-extraction temperature time series data through a multi-parameter collaborative analysis model, and to determine the trend analysis results of the data change slope and fluctuation amplitude. The second judgment module is used to determine a potential pipeline fault if the weight anomaly judgment result is normal, the flow anomaly judgment result is abnormal, and the trend analysis result shows that the deterioration trend of the flow time series data continues for more than a preset time.

[0128] The quality control device for preparing tobacco leaf additives and sugars provided in this embodiment of the invention can execute the quality control method for preparing tobacco leaf additives and sugars provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0129] The collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in the technical solution disclosed herein comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0130] Example 5 Figure 5 A schematic diagram of an electronic device 10, which can be used to implement embodiments of the present invention, is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0131] like Figure 5 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0132] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0133] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, central processing unit (CPU), graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the quality control method for preparing tobacco leaf feed and sugar, i.e.: The process involves collecting material access information for target sugar materials and comparing it with preset process standards to screen out those that pass the material access test. After screening out the target sugar materials that pass the material access test, the process collects the status data of the target equipment. Once the status data of the target equipment meets the preset ready conditions, the process confirms that the target equipment is in the material extraction ready state. Before performing the material extraction operation on the target sugar materials that have passed the material access test using the target equipment in the material extraction ready state, the process collects cumulative weight data and performs a first deviation check against the standard weight of the first work order. After the check passes, the material extraction permission of the target equipment is unlocked. After performing the material extraction operation on the target sugar materials that have passed the material access test using the target equipment with extraction permission, the process collects... After the material extraction is completed, the actual weight data of the tank is collected and compared with the standard weight of the second work order for a second deviation verification. After the verification meets the preset accuracy requirements, the feeding accuracy test is confirmed to have passed. After confirming that the feeding accuracy test has passed, the temperature of the sugar material in the tank after extraction is collected. After confirming that the temperature after extraction meets the stability conditions, the parameter compliance test is confirmed to have passed and the sugar material pre-filling operation is performed. During the sugar material pre-filling process, the pre-filling flow rate and the weight of the pre-filling tank are collected simultaneously. The pre-filling flow rate is compared with the reference flow rate for flow matching verification. The pipeline sealing is verified based on the change in the weight of the pre-filling tank and the pipeline parameters. When the flow matching verification and the pipeline sealing verification are passed, sugar material that meets the quality requirements is obtained.

[0134] In some embodiments, the quality control method for preparing tobacco leaves with added sugar can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the quality control method for preparing tobacco leaves with added sugar described above can be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the quality control method for preparing tobacco leaves with added sugar by any other suitable means (e.g., by means of firmware).

[0135] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0136] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0137] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0138] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0139] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0140] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0141] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0142] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A quality control method for preparing raw materials for adding sugar to tobacco leaves, characterized in that, include: Collect the material access information of the target sugar and compare it with the preset process standards to screen out the target sugar that has passed the material access test; After screening out the target sugar that has passed the material access test, collect the target equipment status data, and after confirming that the target equipment status data meets the preset ready conditions, confirm that the target equipment is in the material extraction ready state. Before performing the material extraction operation on the target sugar that has passed the material access detection through the target equipment that is in the material extraction ready state, collect the cumulative weight data and perform the first deviation verification with the standard weight of the first work order. After the verification is passed, unlock the extraction permission of the target equipment. After the target sugar that has passed the material access test is extracted by the target equipment with extraction authority, the actual weight data of the tank after extraction is collected and the second deviation is checked with the standard weight of the second work order. After the verification meets the preset accuracy requirements, the feeding accuracy test is confirmed to be passed. After confirming that the feeding accuracy test has passed, the temperature of the sugar material in the tank after extraction is collected. After confirming that the temperature after extraction meets the stability condition, the parameter standard test is confirmed to be passed and the sugar material pre-filling operation is performed. During the sugar prefilling process, the prefilling flow rate and the weight of the prefilling tank are collected simultaneously. The prefilling flow rate is matched with the reference flow rate for flow rate verification. The pipeline sealing is verified based on the change in the weight of the prefilling tank and the pipeline parameters. When the flow rate matching verification and the pipeline sealing verification are passed, sugar that meets the quality requirements is obtained.

2. The method according to claim 1, characterized in that, Collect the material access information of the target sugar and compare it with the preset process standards to screen out the target sugar that has passed the material access test, including: By scanning the identification code of the sugar barrel with a fixed barcode scanner, the actual brand, batch, weight and preparation time of the sugar can be obtained as material access information. The actual grade is compared with the preset standard grade in the preset process standard, and the actual batch is compared with the preset standard batch in the preset process standard. The actual prepared weight is compared with the preset standard weight in the preset process standard. The absolute value of the difference between the current time and the actual preparation time is compared with the preset standard time limit in the preset process standard. When all comparison items meet the preset process standard, the material access test is deemed to have passed, and the target sugar that has passed the material access test is selected.

3. The method according to claim 1, characterized in that, Collecting target equipment status data, and confirming that the target equipment is in the material extraction ready state after confirming that the target equipment status data meets preset ready conditions, includes: The initial weight data of the target tank is collected by a static scale as the target equipment status data to verify whether the initial weight data meets the weight requirements corresponding to the empty tank state. The position signal of the unloading manual valve is collected by the valve position sensor as the target equipment status data, and the valve is verified to be in a fully closed state. Pressure data from the pipeline system is collected using pressure sensors as status data for the target equipment, and the pipeline sealing performance is verified to meet the standards. When the initial weight data meets the weight requirements corresponding to the empty tank state, the valve is in the fully closed state, and the pipeline sealing meets the standard, it is determined that the target equipment status data meets the preset ready conditions, and the target equipment is confirmed to be in the material extraction ready state.

4. The method according to claim 1, characterized in that, Also includes: During the material extraction operation of the target sugar that has passed the material access inspection through the target equipment with extraction authority, the weight data of the tank is collected in real time by the static scale. When the weight data reaches the preset threshold, the working status detection of the heating device and the stirring device is triggered. During the status detection of the heating device, the heating current data of the heating device is collected by the current sensor, the temperature change data of the material tank is collected by the temperature sensor, the status of the steam valve is confirmed by the valve position sensor, and the compliance of the heating device operation is verified based on the heating current data, the temperature change data of the material tank and the status of the steam valve. During the status detection of the stirring device, the stirring current data of the stirring device is collected by the motor current sensor, and the vibration data of the stirring device is collected by the vibration sensor. The working status of the stirring device is verified based on the stirring current data and vibration data. When the operating status test results of both the heating device and the stirring device are compliant, the process condition test is deemed to have passed. Accordingly, after confirming that the feeding accuracy test has passed, the temperature of the sugar material in the tank after extraction is collected. After confirming that the temperature after extraction meets the stability conditions, the parameter compliance test is passed, and the sugar material pre-filling operation is performed, including: After confirming that the feeding accuracy test and the process condition test have passed, the temperature of the sugar material in the tank after extraction is collected. After confirming that the temperature after extraction meets the stability condition, the parameter standard test is confirmed to be passed and the sugar material pre-filling operation is performed.

5. The method according to claim 1, characterized in that, The temperature of the sugar in the tank after extraction is collected. After confirming that the temperature after extraction meets the stability condition, the parameter meets the standard and the test is passed. Then, the sugar pre-filling operation is performed, including: The temperature data of the sugar material at corresponding monitoring points inside the tank are collected by multiple temperature sensors; Each set of collected temperature data is compared with the preset temperature range, and the standard deviation of temperature data from multiple monitoring points is calculated to verify temperature stability. When all temperature data are within the preset temperature range and the temperature remains stable for the preset stability time, the parameter compliance test is passed, and the sugar pre-filling operation is performed.

6. The method according to claim 1, characterized in that, During the sugar prefilling process, the prefilling flow rate and the weight of the prefilling tank are collected simultaneously. The prefilling flow rate is then compared with the baseline flow rate for flow matching verification. Additionally, pipeline sealing is verified based on changes in the prefilling tank weight and pipeline parameters, including: During the sugar prefilling process, the prefilling flow rate is collected by a mass flow meter and matched with the benchmark flow rate calculated based on the tobacco flow rate and the feeding ratio for flow rate matching verification. The weight data of the pre-filled tank is collected by a static scale at preset time intervals, the weight reduction value is calculated, and the pipeline sealing is verified by comparing it with the theoretical capacity of the pipeline calculated based on the pipeline size and sugar density.

7. The method according to claim 1, characterized in that, After obtaining sugar that meets quality requirements, the process also includes: Acquire time-series data of prefilling flow rate and prefilling tank weight during the sugar prefilling process, as well as time-series data of temperature of sugar in the tank after extraction during parameter compliance testing. The time series data is input into a preset multi-parameter collaborative analysis model. The multi-parameter collaborative analysis model calculates the deviation amplitude and fluctuation frequency between the pre-filled flow and the baseline flow based on the pre-filled flow time series data, and determines whether the pre-filled flow is abnormal according to the matching rules. The weight change is calculated based on the time series data of the prefill tank weight using a multi-parameter collaborative analysis model. The deviation and fluctuation frequency of the weight change from the pipeline parameters are also calculated. Based on the matching rules, it is determined whether the weight of the prefill tank is abnormal. The fault type is determined based on the output results of the multi-parameter collaborative analysis model. If the abnormal flow rate is determined to be abnormal and the abnormal weight is determined to be abnormal, then the fault is determined to be a pipe blockage or leakage. A multi-parameter collaborative analysis model was used to perform trend fitting analysis on the time series data of pre-filled flow rate, pre-filled tank weight, and post-extraction temperature to determine the trend analysis results of the data change slope and fluctuation amplitude. If the weight anomaly determination result is normal, the flow anomaly determination result is abnormal, and the trend analysis result shows that the deterioration trend of the flow time series data continues for more than the preset time, it is determined to be a potential pipeline fault.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the quality control method for preparing tobacco leaf feed and sugar as described in any one of claims 1-7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the quality control method for preparing tobacco leaf feed and sugar materials as described in any one of claims 1-7.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the quality control method for preparing tobacco leaf feed and sugar additives according to any one of claims 1-7.

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