Control method and system of plastic bag raw material processing device

Abstract

The embodiment of the invention provides a control method and system for a plastic bag raw material processing device, and relates to the technical field of plastic bag raw material processing, and the method comprises the steps: obtaining historical data of a plurality of key parts in the plastic bag raw material processing device, so as to establish an operation state reference mode of the key parts; in the operation period of the plastic bag raw material processing device, operation data of the multiple key components are obtained in real time, and whether operation state deviation exists in all the key components or not is recognized according to the difference between the multiple operation data and the operation state reference mode; based on the operation state deviation, evaluating potential influence of the operation state of the corresponding key component on a production line of the plastic bag raw material processing device; and according to the potential influence, generating maintenance operation suggestions and adjusting operation parameters of the plurality of key components. The overall performance, production efficiency and reliability of the plastic bag raw material treatment device can be improved, and energy consumption can be reduced.

Description

Technical Field

[0001] This application relates to the field of plastic bag raw material processing technology, and in particular to a control method and system for a plastic bag raw material processing device. Background Technology

[0002] In the recycling and processing of waste plastic bags, the raw material processing stage is crucial to production. Traditional equipment often suffers from issues such as parameter dependence on manual labor and fluctuating energy consumption, affecting efficiency and quality. A factory's raw material processing unit, centered on crushing, washing, and drying, initially maintained stable operation based on the characteristics of PE and PP films. However, after changing raw material suppliers to reduce costs, the factory frequently mixed in non-target hard materials such as HDPE bottle caps and PET fragments with the waste plastics. These materials have significantly different characteristics from traditional raw materials and their mixing is irregular, causing fluctuations in feed characteristics. The existing control system struggles to cope. The entry of hard materials into the crusher causes a surge in motor current, resulting in cumulative motor damage, blade wear and chipping, and uneven particle size in the crushed products, producing large fragments and fine powder. This uneven particle size directly impacts the washing stage: fine powder increases the turbidity of the washing liquid, clogs the filter, and increases equipment wear; large fragments are not thoroughly cleaned. Finally, materials containing residual contaminants and uneven moisture content enter the drying stage, requiring the drying equipment to operate at high power, leading to a surge in energy consumption and accelerated component aging. Humidity detection devices cannot provide accurate feedback due to data fluctuations, making it difficult for the control system to adjust the drying process. This results in fluctuations in energy consumption, efficiency, and product quality throughout the production line, severely impacting production stability and economy. Summary of the Invention

[0003] This application aims to address at least one of the technical problems existing in the prior art. To this end, this application proposes a control method and system for a plastic bag raw material processing device, aiming to improve the overall performance, production efficiency, and reliability of the plastic bag raw material processing device while reducing energy consumption.

[0004] In a first aspect, embodiments of this application provide a control method for a plastic bag raw material processing device, applied to the plastic bag raw material processing device, comprising: Historical data of several key components in the plastic bag raw material processing device are acquired to establish a reference mode for the operating status of the key components, wherein the key components include a crusher motor, blades, a cleaning water pump, and a drying heating pipeline; During the operation of the plastic bag raw material processing device, the operating data of multiple key components are acquired in real time, and the operating status deviation of each key component is identified based on the difference between the multiple operating data and the operating status reference mode. Based on the deviation in operating status, assess the potential impact of the operating status of the corresponding key components on the production line of the plastic bag raw material processing device; Based on the potential impact, maintenance operation recommendations are generated and the operating parameters of several of the key components are adjusted.

[0005] According to some embodiments of this application, the step of acquiring historical data of multiple key components in the plastic bag raw material processing device to establish an operating status reference mode for the key components includes: The feed rate of the crusher motor, the rated speed of the cutter, the turbidity of the cleaning liquid of the cleaning water pump, and the drying temperature of the drying heating pipeline in the plastic bag raw material processing device are obtained. A reference mode for the operating status of the key components is established based on the feed speed of the crusher motor, the rated speed of the cutter, the turbidity of the cleaning liquid of the cleaning water pump, and the drying temperature of the drying heating pipeline.

[0006] According to some embodiments of this application, after establishing the operating status reference mode of the key components based on the feed rate of the crusher motor, the rated speed of the cutter, the turbidity of the cleaning liquid from the cleaning water pump, and the drying temperature of the drying heating pipeline, the method further includes: If it is confirmed that the plastic bag raw material processing device has no abnormal wear and is using standard raw materials, the operating status reference mode of the key components is recalibrated according to the first preset cycle.

[0007] According to some embodiments of this application, during the operation of the plastic bag raw material processing device, real-time acquisition of operating data of multiple key components, and identification of whether each key component deviates from its operating state based on the differences between the multiple operating data and the operating state reference mode, includes: During the operation of the plastic bag raw material processing device, the operating data of multiple key components are acquired in real time to obtain the unit output energy consumption. The operating data includes the real-time feeding speed of the crusher motor, the real-time rated speed of the cutter, the real-time turbidity of the cleaning liquid of the cleaning water pump, and the real-time drying temperature of the drying heating pipeline. Based on the differences between the energy consumption per unit output and the operating status reference mode, identify whether there is any deviation in the operating status of each of the key components.

[0008] According to some embodiments of this application, the step of acquiring real-time operating data of multiple key components during the operation of the plastic bag raw material processing device to obtain unit output energy consumption includes: During the operation of the plastic bag raw material processing device, the energy input, material output data and sampling time interval of each link of the production line of the plastic bag raw material processing device are acquired. The links include the crushing link of the crusher motor, the rotation link of the cutter, the cleaning link of the cleaning water pump and the heating link of the drying heating pipeline. The unit output energy consumption is obtained based on the real-time feeding speed of the crusher motor, the real-time rated speed of the cutter, the real-time turbidity of the cleaning liquid from the cleaning water pump, the real-time drying temperature of the drying heating pipeline, the energy input, the material output data, and the sampling time interval.

[0009] According to some embodiments of this application, the step of obtaining the unit output energy consumption based on the real-time feed speed of the crusher motor, the real-time rated speed of the cutter, the real-time turbidity of the cleaning liquid from the cleaning water pump, the real-time drying temperature of the drying heating pipeline, the energy input, material output data, and the sampling time interval includes: The instantaneous electrical power and instantaneous thermal power of each stage are obtained based on the energy input. The material output quality is obtained based on the material output data; The unit output energy consumption is obtained based on the real-time feeding speed of the crusher motor, the real-time rated speed of the cutter, the real-time turbidity of the cleaning liquid from the cleaning water pump, the real-time drying temperature of the drying heating pipeline, the instantaneous electrical power of each link, the instantaneous thermal power of each link, the material output quality, and the sampling time interval.

[0010] According to some embodiments of this application, generating maintenance operation recommendations and adjusting the operating parameters of multiple key components based on the potential impact includes: When the potential impact characterizes corrosive wear, maintenance operation recommendations are generated; Within the preset window, the feed speed of the crusher motor is reduced, the rated speed of the cutter is reduced, the operating power of the cleaning water pump is increased, and the operating parameters of the drying heating pipeline are adjusted.

[0011] According to some embodiments of this application, adjusting the operating parameters of the drying heating pipeline includes: For areas in the plastic bag raw material processing device where the moisture content is higher than a preset value, the hot air volume of the drying and heating pipeline is increased by a first preset proportion; For areas in the plastic bag raw material processing device where the moisture content is lower than a preset value, the hot air volume of the drying heating pipeline is reduced by a second preset ratio.

[0012] According to some embodiments of this application, adjusting the operating parameters of the drying heating pipeline includes: For areas in the plastic bag raw material processing device where the moisture content is higher than a preset value, the residence time of the drying heating pipeline for a first preset time is extended; For areas in the plastic bag raw material processing device where the moisture content is lower than a preset value, the residence time of the second preset time in the drying and heating pipeline is reduced.

[0013] Secondly, embodiments of this application provide a control system for a plastic bag raw material processing device, applied to the plastic bag raw material processing device, including: The acquisition module is used to acquire historical data of multiple key components in the plastic bag raw material processing device to establish a reference mode for the operating status of the key components, wherein the key components include a crusher motor, blades, a cleaning water pump, and a drying heating pipeline. The identification module is used to acquire the operating data of multiple key components in real time during the operation of the plastic bag raw material processing device, and to identify whether each key component has a deviation in operating status based on the difference between the multiple operating data and the operating status reference mode. An evaluation module is used to assess the potential impact of the operating status of the corresponding key components on the production line of the plastic bag raw material processing device based on the deviation of the operating status. An adjustment module is used to generate maintenance operation suggestions and adjust the operating parameters of multiple key components based on the potential impact.

[0014] The technical solution according to the embodiments of this application has at least the following beneficial effects: The control method for the plastic bag raw material processing device disclosed in this application establishes a reference mode for the operating status of key components by acquiring historical data of multiple key components in the plastic bag raw material processing device, and acquires operating data in real time during operation. It identifies deviations in operating status based on the differences between the operating data and the reference mode. Based on this, it assesses the potential impact of the deviation on the production line and generates maintenance operation suggestions and adjusts operating parameters. This method effectively solves the problems in the prior art, such as parameter adjustment relying on manual experience, large energy consumption fluctuations, unstable production efficiency, and insufficient monitoring of equipment operating status. By establishing a refined operating status reference mode and a real-time monitoring mechanism, abnormalities in equipment operation can be detected and corrected in a timely manner, avoiding sudden downtime. Simultaneously, by generating maintenance operation suggestions based on potential impacts and dynamically adjusting operating parameters, preventative maintenance and optimized control are achieved, significantly improving the overall performance, production efficiency, and reliability of the plastic bag raw material processing device, and reducing energy consumption.

[0015] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0016] The accompanying drawings are used to provide a further understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0017] Figure 1 A schematic flowchart illustrating the control method of a plastic bag raw material processing device according to an embodiment of this application; Figure 2 This is a schematic diagram of the control system of a plastic bag raw material processing device provided in one embodiment of this application. Detailed Implementation

[0018] To make the objectives, technical methods, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0019] It should be noted that the meaning of "multiple" (or "more than") in the description of the embodiments of this application refers to two or more, and "greater than," "less than," "exceeding," etc. are understood to exclude the number itself, while "above," "below," "within," etc. are understood to include the number itself. If "first," "second," etc. are used in the description, they are only for the purpose of distinguishing technical features and should not be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated or the order of the technical features indicated.

[0020] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, the simultaneous existence of A and B, or the existence of B alone. A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b, and c can represent: the existence of a alone, the existence of b alone, the existence of c alone, the simultaneous existence of a and b, the simultaneous existence of a and c, the simultaneous existence of b and c, or the simultaneous existence of a, b, and c, where a, b, and c can be single or multiple.

[0021] In the description of this application, unless otherwise expressly defined, terms such as "setup," "installation," and "connection" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this application in conjunction with the specific content of the technical solution.

[0022] Based on the above, this application proposes a control method and system for a plastic bag raw material processing device, aiming to improve the overall performance, production efficiency and reliability of the plastic bag raw material processing device and reduce energy consumption.

[0023] The control method for the plastic bag raw material processing device provided in this application embodiment can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, etc.; the server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms; the software can be an application that implements the control method for the plastic bag raw material processing device, etc., but is not limited to the above forms.

[0024] This application can be applied to numerous general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics devices, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via communication networks. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices. It should be noted that in various specific embodiments of this invention, when processing is required based on data related to the characteristics of an object (e.g., user attributes or sets of attribute information), permission or consent from the corresponding object is obtained first, and the collection, use, and processing of this data comply with relevant laws and standards. Furthermore, when the embodiments of the present invention need to obtain the attribute information of an object, they will obtain the separate permission or separate consent of the corresponding object through pop-up windows or redirection to a confirmation page. After obtaining the separate permission or separate consent of the corresponding object, they will then obtain the relevant data of the object necessary for the embodiments of the present invention to operate normally.

[0025] See Figure 1 , Figure 1 This is a schematic flowchart illustrating a control method for a plastic bag raw material processing device according to an embodiment of this application. The control method for a plastic bag raw material processing device provided in this embodiment includes, but is not limited to, steps S110 to S140, which will be described in detail below.

[0026] Step S110: Obtain historical data of multiple key components in the plastic bag raw material processing device to establish a reference mode for the operating status of key components. Key components include crusher motor, blades, cleaning water pump and drying heating pipeline. Step S120: During the operation of the plastic bag raw material processing device, real-time operating data of multiple key components are acquired, and based on the differences between the multiple operating data and the operating status reference mode, it is identified whether there is any deviation in the operating status of each key component. Step S130: Based on the deviation in operating status, assess the potential impact of the operating status of the corresponding key components on the production line of the plastic bag raw material processing device; Step S140: Based on the potential impact, generate maintenance operation recommendations and adjust the operating parameters of multiple key components.

[0027] It should be noted that during the operation of the plastic bag raw material processing unit, it is necessary to acquire real-time operating data of multiple key components. This can be achieved by installing sensors on the crusher motor to monitor parameters such as feed rate, current, and vibration; installing speed sensors on the cutters to monitor their rated speed; installing turbidity sensors and flow meters at the outlet of the cleaning water pump to monitor the turbidity and flow rate of the cleaning liquid; and installing temperature sensors and energy consumption monitoring equipment on the drying heating pipeline to monitor the drying temperature and energy consumption. This real-time acquired operating data is transmitted to the control system for processing. Subsequently, based on the differences between multiple operating data and the operating status reference mode, it is identified whether there are deviations in the operating status of each key component. The real-time feed rate of the crusher motor can be compared with the normal feed rate range in the reference mode; if the real-time feed rate exceeds this range, a deviation is considered to exist. Similarly, the differences between real-time rated cutter speed, real-time cleaning liquid turbidity, and real-time drying temperature and their respective reference modes can be compared. This identification of differences can be achieved through simple threshold judgment, statistical analysis, or machine learning models. Based on the operating status deviations, the potential impact of the corresponding key component's operating status on the plastic bag raw material processing unit production line is assessed. For example, if the crusher motor feed speed is too fast, it may cause overload, affecting crushing efficiency and even damaging the motor; if the blades are severely worn, it may lead to incomplete cutting, affecting subsequent cleaning effects; if the turbidity of the cleaning water pump is too high, it may lead to incomplete cleaning, affecting product quality; if the temperature of the drying heating pipeline is abnormal, it may lead to increased energy consumption or insufficient drying. Finally, based on the potential impacts, maintenance operation suggestions are generated and the operating parameters of several key components are adjusted. If the assessment results indicate that the crusher motor is at risk of overload, the system generates a maintenance suggestion to "reduce the feed speed" and automatically or manually adjusts the feed speed of the crusher motor. If the blades are severely worn, the system suggests "replacing the blades" or "reducing the blade speed". If the turbidity of the cleaning water pump is too high, the system suggests "replacing the cleaning fluid" or "increasing the pump power". If the temperature of the drying heating pipeline is abnormal, the system suggests "adjusting the heating power" or "checking for pipeline blockage". In this way, preventive maintenance and optimized control of the plastic bag raw material processing device can be achieved, thereby improving production efficiency, reducing energy consumption, and extending equipment life.

[0028] Specifically, the steps described above for acquiring historical data of multiple key components in the plastic bag raw material processing device to establish a reference model for the operating status of these key components include the following: The feed rate of the crusher motor, the rated speed of the cutter, the turbidity of the cleaning liquid of the cleaning water pump, and the drying temperature of the drying heating pipeline in the plastic bag raw material processing device are obtained. Establish a reference model for the operating status of key components based on the feed speed of the crusher motor, the rated speed of the cutter, the turbidity of the cleaning fluid from the cleaning water pump, and the drying temperature of the drying heating pipeline.

[0029] Specifically, when establishing reference models for the operating status of key components, the feed rate of the crusher motor is used to characterize its processing load and efficiency; changes in this value directly reflect the operating status of the crushing process. The rated speed of the cutters is used to assess the wear and cutting performance of the cutters; abnormal speeds may indicate cutter dulling or damage. The turbidity of the cleaning fluid from the cleaning water pump is used to monitor the cleaning effect and water cleanliness; high turbidity may indicate decreased cleaning efficiency or water contamination. The drying temperature of the drying heating pipeline is used to measure the energy consumption and efficiency of the drying process; temperature fluctuations may affect the moisture content of the final product. By collecting and analyzing these representative operating parameters, a comprehensive and accurate baseline description of the operating conditions of each key component can be obtained.

[0030] This application's solution, by specifically acquiring the feed rate of the crusher motor, the rated speed of the cutters, the turbidity of the cleaning fluid from the cleaning water pump, and the drying temperature of the drying heating pipeline, can establish a more refined and accurate operating status reference model for each key component of the plastic bag raw material processing device. These parameters are directly related to the core functions and potential failure modes of each component. The feed rate is closely related to the crushing load, the rated speed directly corresponds to the wear degree of the cutters, the turbidity of the cleaning fluid reflects the cleaning effect, and the drying temperature determines the drying efficiency. By analyzing and modeling historical data of these key parameters, a multi-dimensional, high-precision normal operating baseline can be constructed, thus providing a solid data foundation for subsequent identification of operating status deviations.

[0031] In response, this application further proposes that, after establishing a reference mode for the operating status of key components based on the feed rate of the crusher motor, the rated speed of the cutters, the turbidity of the cleaning fluid from the cleaning water pump, and the drying temperature of the drying heating pipeline, it also includes: After confirming that the plastic bag raw material processing device has no abnormal wear and is using standard raw materials, the operating status reference mode of the key components is recalibrated according to the first preset cycle.

[0032] Specifically, confirming that the plastic bag raw material processing device shows no abnormal wear and is using standard raw materials involves manual inspection, sensor data analysis (e.g., vibration, temperature, current), or a combination of historical maintenance records. This ensures that key components such as the crusher motor, blades, cleaning water pump, and drying heating pipelines show no signs of wear or damage exceeding normal limits, and that the currently processed plastic bag raw materials meet preset quality and type standards. The purpose is to ensure that recalibration is performed when the equipment is in a good and controlled baseline condition, avoiding distortion of calibration results due to equipment failure or abnormal raw materials. Specifically, according to the first preset cycle, the system automatically or manually triggers a calibration process at a pre-set time interval (weekly, monthly, or quarterly) to recalibrate the operating status reference mode of key components. During this calibration process, the operating data of key components is acquired again and compared and updated with the existing operating status reference mode to reflect normal drift or optimization that may occur during long-term operation. Dynamically adjusting and optimizing the operating status reference mode ensures it always maintains a high degree of consistency with the actual operating conditions of the equipment, thereby improving the accuracy and reliability of identifying operating status deviations.

[0033] In one embodiment, when the plastic bag raw material processing device has been operating stably for three months without any abnormal wear detected, and has consistently used standard plastic film raw materials from the same supplier, the system triggers a recalibration of the operating status reference mode according to a preset first cycle (once per quarter). During the calibration process, the system re-collects data such as the feed rate of the crusher motor, the rated speed of the cutters, the turbidity of the cleaning fluid from the cleaning water pump, and the drying temperature of the drying heating pipeline. This newly collected data is used to compare and update the current operating status reference mode. For example, if a slight increase in the normal operating current of the crusher motor at the same feed rate is found, this may indicate that the motor efficiency has slightly decreased after long-term operation, but is still within the normal range. Through recalibration, the new reference mode will include this subtle change, allowing subsequent real-time monitoring to make judgments based on a benchmark that is closer to the current actual condition of the equipment, thereby more accurately identifying the true operating status deviation, rather than misjudging normal performance drift as abnormal.

[0034] Specifically, in the above method, the steps for identifying whether there are deviations in the operating status of each key component can be further refined.

[0035] During the operation of the plastic bag raw material processing unit, real-time operational data from several key components is acquired to determine the energy consumption per unit output. This operational data includes the real-time feed rate of the crusher motor, the real-time rated speed of the cutters, the real-time turbidity of the cleaning fluid from the cleaning water pump, and the real-time drying temperature of the drying heating pipeline. Specifically, the real-time feed rate of the crusher motor refers to the actual speed at which the plastic bag raw material enters the crusher motor at a given moment or time interval, reflecting the load on the crushing process. The real-time rated speed of the cutters refers to the actual rotational speed of the cutters during operation, which is closely related to the cutting efficiency and wear of the cutters. The real-time turbidity of the cleaning fluid from the cleaning water pump refers to the actual turbidity of the cleaning fluid during the cleaning process, directly affecting the cleaning effect and the efficiency of water recycling. The real-time drying temperature of the drying heating pipeline refers to the actual temperature provided by the heating pipeline during the drying process, a key parameter affecting material drying efficiency and energy consumption. By comprehensively analyzing this real-time operational data, the energy consumption per unit output can be calculated. This energy consumption index comprehensively reflects the energy consumption level of the plastic bag raw material processing unit per unit output.

[0036] Subsequently, based on the differences between multiple unit output energy consumption and operational status reference models, it was identified whether there were deviations in the operational status of each key component. Unit output energy consumption, as a comprehensive performance indicator, can link the operational status of each key component with overall production efficiency and energy consumption performance. When there is a significant difference between the real-time acquired unit output energy consumption and the pre-established operational status reference model, it indicates that the operational status of the plastic bag raw material processing device may have deviated. This difference can be an abnormal increase or decrease in unit output energy consumption, reflecting a decline in system efficiency or potential failure risks.

[0037] Specifically, the steps described above for obtaining real-time operating data of multiple key components during the operation of the plastic bag raw material processing device to obtain the energy consumption per unit output can be further refined.

[0038] In one embodiment, during the operation of the plastic bag raw material processing device, it is necessary to acquire energy input, material output data, and sampling time intervals for each stage of the production line. Each stage specifically includes the crushing stage of the crusher motor, the rotation stage of the cutters, the cleaning stage of the cleaning water pump, and the heating stage of the drying and heating pipeline. Energy input refers to the electrical or thermal energy consumed in each stage, such as the electrical energy consumption of the crusher motor in the crushing stage and the thermal energy consumption of the drying and heating pipeline in the heating stage. Material output data refers to the mass or volume of processed plastic bag raw material within a specific sampling time interval. The sampling time interval refers to the frequency of data acquisition, such as per minute, per hour, or per batch. Based on the acquired real-time feed rate of the crusher motor, real-time rated speed of the cutters, real-time turbidity of the cleaning liquid from the cleaning water pump, real-time drying temperature of the drying and heating pipeline, energy input, material output data, and sampling time intervals, the unit output energy consumption can be calculated. Unit output energy consumption refers to the energy consumed in producing a unit mass or volume of plastic bag raw material and is a key indicator for measuring production efficiency and energy consumption levels.

[0039] This application's solution, by defining a detailed method for calculating unit output energy consumption, enables more accurate and quantifiable assessment of the operational status of key components. By acquiring energy input, material output data, and sampling time intervals for each stage of the production line, and combining this with real-time operational data of key components, the energy efficiency of the entire processing process can be comprehensively reflected. Energy input and material output data for the crushing stage of the crusher motor, the rotation stage of the cutters, the cleaning stage of the cleaning water pump, and the heating stage of the drying heating pipeline are directly related to the actual workload and efficiency of each stage. By combining this data with operating parameters such as real-time feed rate, rated speed, cleaning fluid turbidity, and drying temperature, unit output energy consumption can be accurately calculated, thus providing a solid data foundation for subsequent identification of deviations in operational status.

[0040] The above data, based on the real-time feed rate of the crusher motor, the real-time rated speed of the cutters, the real-time turbidity of the cleaning liquid from the cleaning water pump, the real-time drying temperature of the drying heating pipeline, energy input, material output data, and sampling time interval, yields the unit output energy consumption, including: The instantaneous electrical power and instantaneous thermal power of each stage are obtained based on the energy input; The material output quality is obtained based on the material output data; The unit output energy consumption is obtained based on the real-time feeding speed of the crusher motor, the real-time rated speed of the cutter, the real-time turbidity of the cleaning liquid from the cleaning water pump, the real-time drying temperature of the drying heating pipeline, the instantaneous electrical power of each stage, the instantaneous thermal power of each stage, the material output quality, and the sampling time interval.

[0041] Energy input refers to the electrical and thermal energy consumed by various key components of the plastic bag raw material processing device during operation. Instantaneous electrical power at each stage refers to the electrical power of power-consuming equipment such as the crusher motor and cleaning water pump at a specific moment, acquired in real-time by electrical energy metering devices installed on the corresponding equipment. Instantaneous thermal power at each stage refers to the thermal power of heating equipment such as drying and heating pipelines at a specific moment, estimated by heat sensors or based on the rated power and operating status of the heating equipment. These instantaneous power data form the basis for calculating the total energy input. Material output data refers to the quality information of the finished or semi-finished products obtained after processing plastic bag raw materials. The material output quality is measured in real-time by weighing sensors or flow meters installed at the end of the production line or at specific stages. Accurate material output quality is a key parameter for calculating unit output energy consumption, thereby quantifying processing efficiency. After obtaining the instantaneous electrical power, instantaneous thermal power, and material output mass at each stage, and combining this with the real-time feeding speed of the crusher motor, the real-time rated speed of the cutters, the real-time turbidity of the cleaning liquid from the cleaning water pump, the real-time drying temperature of the drying heating pipeline, and the sampling time interval, the unit output energy consumption can be accurately calculated using a preset calculation model or formula. Unit output energy consumption can be defined as the total energy input (the sum of electrical and thermal energy) divided by the material output mass during a specific sampling time interval. The solution in this application refines the energy input into the instantaneous electrical power and instantaneous thermal power of each stage, and explicitly defines the material output data as the material output mass, making the calculation of unit output energy consumption more precise and accurate. It is precisely because of the more specific and quantitative definition and measurement of energy input and output that the calculation of unit output energy consumption is no longer a rough estimate, but a precise calculation based on actual operating data and physical quantities. This refined data acquisition and calculation method can more accurately reflect the energy efficiency of plastic bag raw material processing equipment under different operating conditions, thus providing a more reliable basis for subsequent identification of deviations in operating conditions.

[0042] In this regard, this application further proposes that the method for generating maintenance operation suggestions and adjusting the operating parameters of multiple key components based on potential impacts includes: generating maintenance operation suggestions when the potential impacts indicate corrosive wear; reducing the feed speed of the crusher motor, reducing the rated speed of the cutters, increasing the operating power of the cleaning water pump, and adjusting the operating parameters of the drying heating pipeline within a preset window.

[0043] Specifically, when the assessed potential impact clearly indicates the presence of corrosive wear, the system is triggered to generate corresponding maintenance operation recommendations. Corrosive wear typically refers to material loss caused by prolonged friction, impact, or erosion between material and equipment surfaces. In the processing of plastic bag raw materials, incompletely cleaned hard impurities or high-hardness plastic particles may cause continuous wear to components such as the crusher motor and cutters. The generated maintenance operation recommendations may include, but are not limited to: recommending shutdown inspection of affected critical components, replacing worn parts, strengthening daily cleaning and maintenance, or adjusting material pretreatment processes. Furthermore, to promptly mitigate the further development of corrosive wear, after corrosive wear is identified, the system will automatically or semi-automatically adjust the operating parameters of several critical components within a preset window. This preset window can be a time period, such as several minutes to several hours, designed to provide a buffer period to reduce the wear rate by adjusting operating parameters before more thorough maintenance. This will reduce the feed rate of the crusher motor to decrease the amount of material entering the crushing chamber and the impact force, thereby reducing the load and wear on the crusher motor and cutters. Reducing the rated speed of the cutting tools decreases the relative speed and impact frequency between the tools and the material, further mitigating tool wear. Additionally, increasing the operating power of the cleaning water pump enhances the cleaning effect, ensuring that impurities and fine particles that could cause wear are more thoroughly removed before the material enters the drying stage. For the drying heating pipeline, its operating parameters are adjusted, which may include optimizing hot air temperature, airflow, or material residence time to ensure the material reaches optimal moisture content during drying, preventing material adhesion or embrittlement due to excessive moisture or dryness, which indirectly affects wear in subsequent processing stages.

[0044] In one embodiment, during the operation of a plastic bag raw material processing device, its identification module analyzes the operating data of the crusher motor and cutters (abnormal vibration frequency, torque fluctuations, and a significant increase in energy consumption per unit output) to determine the potential risk of corrosive wear. The assessment module further confirms that this wear may seriously affect the stability of the production line and the lifespan of components. At this point, the adjustment module immediately generates maintenance operation suggestions, such as prompting operators to check for hard foreign objects remaining inside the crushing chamber and suggesting that the cutters and liners be inspected or replaced during the next planned shutdown window. Simultaneously, the system automatically performs parameter adjustments within a preset 15-minute window: reducing the feed rate of the crusher motor from 2 tons per hour to 1.5 tons per hour, and reducing the rated speed of the cutters from 1500 RPM to 1200 RPM. In addition, the operating power of the cleaning water pump is increased by 10% to ensure enhanced circulation and flushing capacity of the cleaning fluid, thereby more effectively removing abrasive particles from the material surface. The operating parameters of the drying and heating pipelines are also fine-tuned. While maintaining the overall drying effect, the temperature in local areas is slightly reduced to prevent the material from becoming brittle due to over-drying, thus reducing the risk of generating more abrasive debris in subsequent processing. Through these coordinated adjustments, the increasing trend of corrosive wear is effectively curbed, buying time for subsequent maintenance and reducing the risk of sudden failures.

[0045] In this regard, this application further proposes the above-mentioned adjustment of the operating parameters of the drying and heating pipeline, specifically including: For areas in the plastic bag raw material processing device where the moisture content is higher than the preset value, increase the hot air volume of the drying and heating pipeline by the first preset ratio. For areas in the plastic bag raw material processing device where the moisture content is lower than the preset value, reduce the amount of hot air in the second preset ratio of the drying and heating pipeline.

[0046] Specifically, areas with moisture content higher than the preset value refer to specific physical areas in the drying stage of the plastic bag raw material processing device where the internal or surface moisture content exceeds a preset threshold, as monitored in real time by humidity sensors or infrared spectrometers. Inside the drying chamber, uneven airflow or material accumulation may cause localized moisture evaporation difficulties, resulting in areas with high moisture content. The first preset ratio refers to the percentage or fixed increment of additional hot air volume required relative to the current hot air volume when an area with high moisture content is detected. This value can be preset based on experimental data, material characteristics, and drying efficiency requirements to ensure sufficient drying energy for that area. Conversely, areas with moisture content lower than the preset value refer to specific physical areas in the drying stage of the plastic bag raw material processing device where the moisture content is lower than a preset threshold, as monitored by the same or similar detection equipment. This may occur in areas with overly concentrated airflow or where the material itself has a low moisture content. The second preset ratio refers to the percentage or fixed reduction of hot air volume required relative to the current hot air volume when an area with low moisture content is detected. This value can also be set according to actual needs to avoid over-drying and unnecessary energy consumption.

[0047] In one embodiment, the drying chamber of the plastic bag raw material processing device is divided into multiple independent drying zones, each equipped with an independent humidity sensor and an adjustable hot air valve. During system operation, if the system monitors in real time that the moisture content of the left-side zone of the drying chamber remains consistently higher than a preset value (above 5%), while the moisture content of the right-side zone is lower than a preset value (below 2%), the control system will adjust accordingly. For the left-side zone with higher moisture content, the control system will instruct the corresponding hot air valve to increase the hot air volume by a first preset proportion, increasing the hot air volume by 15%, to enhance the drying effect in that zone. Simultaneously, for the right-side zone with lower moisture content, the control system will instruct the corresponding hot air valve to decrease the hot air volume by a second preset proportion, reducing the hot air volume by 10%, to avoid over-drying and save energy. In this way, the raw materials within the entire drying chamber can achieve more uniform and efficient drying.

[0048] In response, this application further proposes adjusting the operating parameters of the aforementioned drying and heating pipeline, including: For areas in the plastic bag raw material processing device where the moisture content is higher than the preset value, extend the residence time of the first preset time in the drying and heating pipeline; For areas in the plastic bag raw material processing device where the moisture content is lower than the preset value, reduce the residence time of the second preset time in the drying and heating pipeline.

[0049] Specifically, the area in the plastic bag raw material processing device where the moisture content is higher than the preset value refers to the area where, during the drying process, the material moisture content measured by sensors or other detection methods exceeds the preset target moisture content upper limit. Extending the residence time of the first preset time in the drying heating pipeline can be understood as increasing the time the material receives hot air drying in the drying heating pipeline to ensure that the material in the high moisture content area is fully dried and reaches the target moisture content. The first preset time can be set according to factors such as the initial moisture content of the material, drying efficiency requirements, and equipment capacity. The area in the plastic bag raw material processing device where the moisture content is lower than the preset value refers to the area where, during the drying process, the measured material moisture content is lower than the preset target moisture content lower limit, or has reached or even fallen below the ideal dryness level. Reducing the residence time of the second preset time in the drying heating pipeline aims to avoid over-drying of the material, thereby saving energy, preventing performance degradation due to over-drying, and improving overall processing efficiency. The second preset time can also be flexibly adjusted according to actual conditions.

[0050] This application's solution achieves refined control of the drying process by real-time monitoring and judgment of the moisture content in different areas of the plastic bag raw material processing device, and differentiatedly adjusting the residence time of the drying heating pipeline based on the judgment results. When the moisture content of the material in a certain area is detected to be higher than the preset value, the residence time in that area is extended, allowing the material more time to contact the hot air, thereby effectively removing excess moisture. Conversely, when the moisture content of the material in a certain area is detected to be lower than the preset value, the residence time in that area is reduced, avoiding unnecessary energy consumption and over-drying of the material, ensuring that the material leaves the drying area promptly after reaching the appropriate moisture content. This dynamic residence time adjustment mechanism based on regional moisture content can effectively address the problem of uneven raw material moisture content and optimize the drying process.

[0051] In one embodiment, the drying heating pipeline of the plastic bag raw material processing device is divided into multiple independent drying zones, each equipped with an independent moisture content sensor and material conveying speed adjustment mechanism. When the system detects that the moisture content of the material in the first drying zone is consistently higher than a preset value (exceeding 5%), the control system instructs the material conveying mechanism in that zone to reduce its conveying speed, thereby extending the residence time of the material in that zone and allowing it to undergo a longer drying process. Simultaneously, if the system detects that the moisture content of the material in the second drying zone is lower than a preset value (below 1%), it instructs the material conveying mechanism in that zone to increase its conveying speed, reducing the residence time of the material in that zone to avoid over-drying and save energy. In this way, differentiated drying management of materials in different zones can be achieved, ensuring optimal overall drying results.

[0052] See Figure 2 , Figure 2 This is a schematic diagram of a control system for a plastic bag raw material processing apparatus according to one embodiment of this application. The control system 200 of the plastic bag raw material processing apparatus includes: The acquisition module 210 is used to acquire historical data of multiple key components in the plastic bag raw material processing device in order to establish a reference mode for the operating status of the key components. The key components include the crusher motor, blades, cleaning water pump and drying heating pipeline. The identification module 220 is used to acquire the operating data of multiple key components in real time during the operation of the plastic bag raw material processing device, and to identify whether there is a deviation in the operating status of each key component based on the difference between the multiple operating data and the operating status reference mode. Evaluation module 230 is used to evaluate the potential impact of the operating status of the corresponding key components on the production line of the plastic bag raw material processing device based on the deviation of the operating status. Adjustment module 240 is used to generate maintenance operation recommendations and adjust the operating parameters of multiple key components based on potential impacts.

[0053] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0054] It will be understood by those skilled in the art that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, as is known to those skilled in the art, communication media typically include computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0055] The foregoing has provided a detailed description of the preferred embodiments of this application. However, this application is not limited to the above-described embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of this application. All such equivalent modifications or substitutions are included within the scope defined in this application.

Claims

1. A control method for a plastic bag raw material processing device, characterized in that, Applications in plastic bag raw material processing equipment include: Historical data of several key components in the plastic bag raw material processing device are acquired to establish a reference mode for the operating status of the key components, wherein the key components include a crusher motor, blades, a cleaning water pump, and a drying heating pipeline; During the operation of the plastic bag raw material processing device, the operating data of multiple key components are acquired in real time, and the operating status deviation of each key component is identified based on the difference between the multiple operating data and the operating status reference mode. Based on the deviation in operating status, assess the potential impact of the operating status of the corresponding key components on the production line of the plastic bag raw material processing device; Based on the potential impact, maintenance operation recommendations are generated and the operating parameters of several of the key components are adjusted.

2. The method according to claim 1, characterized in that, The step of acquiring historical data of multiple key components in the plastic bag raw material processing device to establish an operational status reference mode for the key components includes: The feed rate of the crusher motor, the rated speed of the cutter, the turbidity of the cleaning liquid of the cleaning water pump, and the drying temperature of the drying heating pipeline in the plastic bag raw material processing device are obtained. A reference mode for the operating status of the key components is established based on the feed speed of the crusher motor, the rated speed of the cutter, the turbidity of the cleaning liquid of the cleaning water pump, and the drying temperature of the drying heating pipeline.

3. The method according to claim 2, characterized in that, After establishing the operating status reference mode of the key components based on the feed speed of the crusher motor, the rated speed of the cutter, the turbidity of the cleaning liquid from the cleaning water pump, and the drying temperature of the drying heating pipeline, the method further includes: If it is confirmed that the plastic bag raw material processing device has no abnormal wear and is using standard raw materials, the operating status reference mode of the key components is recalibrated according to the first preset cycle.

4. The method according to claim 1, characterized in that, During the operation of the plastic bag raw material processing device, real-time operating data of multiple key components are acquired, and based on the differences between the multiple operating data and the operating status reference mode, it is identified whether there is any deviation in the operating status of each key component, including: During the operation of the plastic bag raw material processing device, the operating data of multiple key components are acquired in real time to obtain the unit output energy consumption. The operating data includes the real-time feeding speed of the crusher motor, the real-time rated speed of the cutter, the real-time turbidity of the cleaning liquid of the cleaning water pump, and the real-time drying temperature of the drying heating pipeline. Based on the differences between the energy consumption per unit output and the operating status reference mode, identify whether there is any deviation in the operating status of each of the key components.

5. The method according to claim 4, characterized in that, The unit output energy consumption is obtained by acquiring real-time operating data of multiple key components during the operation of the plastic bag raw material processing device, including: During the operation of the plastic bag raw material processing device, the energy input, material output data and sampling time interval of each link of the production line of the plastic bag raw material processing device are acquired. The links include the crushing link of the crusher motor, the rotation link of the cutter, the cleaning link of the cleaning water pump and the heating link of the drying heating pipeline. The unit output energy consumption is obtained based on the real-time feeding speed of the crusher motor, the real-time rated speed of the cutter, the real-time turbidity of the cleaning liquid from the cleaning water pump, the real-time drying temperature of the drying heating pipeline, the energy input, the material output data, and the sampling time interval.

6. The method according to claim 5, characterized in that, The method of obtaining unit output energy consumption based on the real-time feed speed of the crusher motor, the real-time rated speed of the cutter, the real-time turbidity of the cleaning liquid from the cleaning water pump, the real-time drying temperature of the drying heating pipeline, the energy input, material output data, and sampling time interval includes: The instantaneous electrical power and instantaneous thermal power of each stage are obtained based on the energy input. The material output quality is obtained based on the material output data; The unit output energy consumption is obtained based on the real-time feeding speed of the crusher motor, the real-time rated speed of the cutter, the real-time turbidity of the cleaning liquid from the cleaning water pump, the real-time drying temperature of the drying heating pipeline, the instantaneous electrical power of each link, the instantaneous thermal power of each link, the material output quality, and the sampling time interval.

7. The method according to claim 1, characterized in that, The step of generating maintenance operation recommendations and adjusting the operating parameters of multiple key components based on the potential impact includes: When the potential impact characterizes corrosive wear, maintenance operation recommendations are generated; Within the preset window, the feed speed of the crusher motor is reduced, the rated speed of the cutter is reduced, the operating power of the cleaning water pump is increased, and the operating parameters of the drying heating pipeline are adjusted.

8. The method according to claim 7, characterized in that, Adjusting the operating parameters of the drying and heating pipeline includes: For areas in the plastic bag raw material processing device where the moisture content is higher than a preset value, the hot air volume of the drying and heating pipeline is increased by a first preset proportion; For areas in the plastic bag raw material processing device where the moisture content is lower than a preset value, the hot air volume of the drying heating pipeline is reduced by a second preset ratio.

9. The method according to claim 7, characterized in that, Adjusting the operating parameters of the drying and heating pipeline includes: For areas in the plastic bag raw material processing device where the moisture content is higher than a preset value, the residence time of the drying heating pipeline for a first preset time is extended; For areas in the plastic bag raw material processing device where the moisture content is lower than a preset value, the residence time of the second preset time in the drying and heating pipeline is reduced.

10. A control system for a plastic bag raw material processing device, characterized in that, Applications in plastic bag raw material processing equipment include: The acquisition module is used to acquire historical data of multiple key components in the plastic bag raw material processing device to establish a reference mode for the operating status of the key components, wherein the key components include a crusher motor, blades, a cleaning water pump, and a drying heating pipeline. The identification module is used to acquire the operating data of multiple key components in real time during the operation of the plastic bag raw material processing device, and to identify whether each key component has a deviation in operating status based on the difference between the multiple operating data and the operating status reference mode. An evaluation module is used to assess the potential impact of the operating status of the corresponding key components on the production line of the plastic bag raw material processing device based on the deviation of the operating status. An adjustment module is used to generate maintenance operation suggestions and adjust the operating parameters of multiple key components based on the potential impact.

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