A multi-source parameter-based material retention control system and method

Abstract

The application discloses a kind of material retention control system and method based on multi-source parameters, it is related to industrial control technical field, the system is collected by data acquisition module the multi-source operating parameter of material processing process;Trend estimation module estimates the output capacity trend of first processing unit and the trend of the second processing unit's acceptance capacity, and generates the material inventory trend data of intermediate transmission section according to the deviation of both;Feature extraction module extracts low-frequency fluctuation characteristics, generates charge and discharge feature data;Exponent generation module generates retention state index;State judging module determines material retention state grade;Coordinated control module generates at least one control quantity in first processing unit operating speed, second processing unit operating speed, material input quantity and intermediate transmission section temperature, the application solves the problem that material inventory accumulates, periodic charge and discharge and retention are difficult to suppress in time, improves operating stability and product quality consistency.

Description

Technical Field

[0001] This application relates to the field of industrial control technology, and in particular to a material retention control system and method based on multi-source parameters. Background Technology

[0002] In industrial production processes such as continuous material handling, continuous mixing, continuous extrusion, continuous conveying, and reaction processing, materials typically need to pass through multiple processing units sequentially. Intermediate transfer sections or connecting sections are usually set up between different processing units to achieve material transition, pressure buffering, flow matching, and process state connection. For two-stage continuous material handling equipment, if the conveying capacity, carrying capacity, and thermal state of the first and second processing units are not coordinated, hidden material inventory or localized stagnation can easily form in the intermediate transfer sections.

[0003] Taking the two-stage extrusion process in the production of PVG solid woven flame-retardant conveyor belts as an example, a two-stage extrusion method is usually adopted to improve plasticization uniformity and devolatilization stability. The first-stage processing unit is mainly responsible for material plasticization, melting, and mixing, while the second-stage processing unit is mainly responsible for degassing, stable conveying, and pressure building. The connecting section between the first and second stages is both a material transition area and a buffer area for matching the conveying capacities of the two stages. When the output capacity of the first stage does not match the receiving capacity of the second stage, slow material accumulation, periodic filling and releasing, or local stagnation may occur in the connecting section. This type of stagnation does not necessarily manifest as obvious pressure over-limit, but may only manifest as low-frequency pressure fluctuations in the middle section, uncoordinated upstream and downstream drive loads, fluctuations in outlet material temperature, decreased discharge stability, or periodic defects on the surface of the product.

[0004] Existing control methods for continuous material handling equipment typically rely on a single or limited number of process parameters for adjustment. These parameters include actuator speed, material input rate, barrel or connecting section temperature, average connecting section pressure, and outlet pressure. Feedback adjustments are made based on these parameters. When pressure increases, the operating speed of the upstream processing unit is reduced or the operating speed of the downstream processing unit is increased; when temperature is too high, the heating power is reduced or the cooling intensity is adjusted. While these methods can maintain apparent stability to some extent, they primarily focus on whether single-point parameters such as pressure, temperature, or speed exceed limits. They fail to reflect the changing trends of material inventory within the intermediate transmission section, the dynamic characteristics of material filling and discharging, and the matching status between upstream and downstream processing capacities. Summary of the Invention

[0005] To address the aforementioned shortcomings, this application provides a material retention control system and method based on multi-source parameters. This solves the problem in existing continuous material handling processes that over-rely on single pressure, temperature, or actuator speed for control, making it difficult to promptly identify hidden material inventory and local retention states in intermediate transport sections. By performing trend estimation, dynamic feature extraction, and state index generation on multi-source process operating parameters, this application can obtain a retention state index reflecting the degree of material retention. Based on this retention state index, closed-loop coordinated control is performed to reduce the risks of thermal degradation, component migration, black spots, gelation, uneven plasticization, or discharge fluctuations caused by excessively long local residence times.

[0006] In a first aspect, this application provides a material retention control system based on multi-source parameters, comprising: The data acquisition module is used to collect multi-source operating parameters of the material handling process, including the operating speed of the first processing unit, the operating speed of the second processing unit, the material input, the driving load of the first processing unit, the driving load of the second processing unit, the pressure of the intermediate transmission section, the output pressure of the second processing unit, and the temperature of the intermediate transmission section. The trend estimation module is used to estimate the output capacity trend of the first processing unit and the receiving capacity trend of the second processing unit based on the multi-source operating parameters, and generate material inventory trend data of the intermediate transmission segment according to the deviation between the output capacity trend and the receiving capacity trend. The feature extraction module is used to perform time-series processing on the pressure of the intermediate transmission section, extract low-frequency pressure fluctuation features, and generate filling and discharging feature data. The index generation module is used to generate a stagnation state index based on the material inventory trend data, the material filling and discharging characteristic data, the load deviation between the first processing unit drive load and the second processing unit drive load, and the intermediate transmission section temperature. The status determination module is used to determine the material retention status level based on the retention status index; The coordination control module is used to generate at least one of the following control quantities based on the material retention state level, under preset load constraints, pressure constraints, and temperature constraints: the operating speed of the first processing unit, the operating speed of the second processing unit, the material input amount, and the temperature of the intermediate transmission section.

[0007] Optionally, the multi-source operating parameters of the material processing process include: The operating speed of the first processing unit, the operating speed of the second processing unit, the material input, the driving load of the first processing unit, the driving load of the second processing unit, the pressure of the intermediate transmission section, the output pressure of the second processing unit, and the temperature of the intermediate transmission section are collected synchronously according to the preset sampling cycle. Add time stamps to the data collected within the same sampling period to form a multi-source operating parameter sequence corresponding to the same time window.

[0008] Optionally, before performing trend estimation, the multi-source operating parameter sequence further includes: The multi-source operating parameter sequence is subjected to outlier removal, missing value imputation, and moving average processing to obtain a preprocessed multi-source operating parameter sequence. The outlier removal includes removing data that exceeds the preset upper or lower limit of the corresponding parameter from the multi-source operating parameter sequence, and the missing value filling includes filling missing data with data from adjacent sampling periods.

[0009] Optionally, estimating the output capability trend of the first processing unit includes: Extract the operating speed of the first processing unit, the material input amount, the driving load of the first processing unit, and the pressure of the intermediate transmission section from the preprocessed multi-source operating parameter sequence; Calculate the rate of change of the operating speed of the first processing unit, the rate of change of the material input, the rate of change of the driving load of the first processing unit, and the rate of change of the pressure in the intermediate transmission section, respectively. The output capacity trend of the first processing unit is obtained by weighted summing of the rate of change of the operating speed of the first processing unit, the rate of change of the material input, the rate of change of the driving load of the first processing unit, and the rate of change of the pressure of the intermediate transmission section.

[0010] Optionally, estimating the throughput trend of the second processing unit includes: Extract the second processing unit's operating speed, the second processing unit's driven load, the intermediate transmission section pressure, and the second processing unit's output pressure from the preprocessed multi-source operating parameter sequence. Calculate the rate of change of the operating speed of the second processing unit, the rate of change of the load driven by the second processing unit, the rate of change of the pressure in the intermediate transmission section, and the rate of change of the pressure at the output end of the second processing unit, respectively. The carrying capacity trend of the second processing unit is obtained by weighted summing of the operating speed change rate of the second processing unit, the driving load change rate of the second processing unit, the pressure change rate of the intermediate transmission section, and the pressure change rate of the output end of the second processing unit.

[0011] Optionally, the generation of material inventory trend data for intermediate transport segments includes: Calculate the trend difference between the output capability trend of the first processing unit and the capacity trend of the second processing unit to obtain the trend difference of the current sampling period; The cumulative inventory change is obtained by summing the trend differences over multiple consecutive sampling periods. Based on the trend difference and the cumulative inventory change, material inventory trend data for the intermediate transmission segment is generated.

[0012] Optionally, the step of performing time-series processing on the pressure in the intermediate transmission segment to extract low-frequency pressure fluctuation features includes: The pressure of the intermediate transmission segment is captured according to a preset time window to obtain pressure timing data; The pressure time series data is subjected to mean removal processing to obtain pressure fluctuation data; The pressure fluctuation data is low-pass filtered to obtain low-frequency pressure fluctuation data; Calculate the low-frequency pressure amplitude and low-frequency pressure period based on the low-frequency pressure fluctuation data; The pressure fluctuation data is subjected to frequency domain transformation, and the ratio between the frequency domain energy in the preset low frequency band and the frequency domain energy of the whole frequency band is calculated to obtain the low frequency energy ratio. The low-frequency pressure amplitude, the low-frequency pressure period, and the low-frequency energy ratio are used as the low-frequency pressure fluctuation characteristics.

[0013] Optionally, the generation of filling and discharging characteristic data includes: Based on the low-frequency pressure fluctuation characteristics, calculate the pressure rise interval and pressure fall interval of the intermediate transmission section within the preset time window; The duration of the pressure rise interval is calculated to obtain the rise duration; the duration of the pressure fall interval is calculated to obtain the fall duration. The pressure fluctuation amplitude is obtained based on the difference between the maximum and minimum pressure values ​​in the low-frequency pressure fluctuation data. The rising duration, falling duration, pressure fluctuation amplitude, and low-frequency energy ratio are combined to obtain the filling and discharging characteristic data.

[0014] Optionally, generating the retention status index includes: The material inventory trend data, the material filling and discharging characteristic data, the load deviation, and the intermediate transmission section temperature are normalized to obtain normalized values ​​for inventory trend, material filling and discharging characteristics, load deviation, and temperature. The normalized values ​​of inventory trend, filling and discharging characteristics, load deviation, and temperature are weighted and summed according to preset weights to obtain the stagnation state index.

[0015] Optionally, determining the material retention status level based on the retention status index includes: The stagnation state index is compared with a first state threshold, a second state threshold, and a third state threshold, respectively, wherein the first state threshold is less than the second state threshold, and the second state threshold is less than the third state threshold; In response to the retention state index being less than the first state threshold, the material retention state level is determined to be the first level; In response to the retention state index being greater than or equal to the first state threshold and less than the second state threshold, the material retention state level is determined to be the second level. In response to the retention state index being greater than or equal to the second state threshold and less than the third state threshold, the material retention state level is determined to be the third level. In response to the retention state index being greater than or equal to the third state threshold, the material retention state level is determined to be the fourth level.

[0016] Optionally, the generation of at least one control quantity among the operating speed of the first processing unit, the operating speed of the second processing unit, the material input amount, and the temperature of the intermediate transfer section includes: The control quantity combination is determined based on the material retention state level. The control quantity combination includes at least one of the following: the first processing unit operating speed adjustment, the second processing unit operating speed adjustment, the material input adjustment, and the intermediate transmission temperature adjustment. The control quantity combination is compared with the preset load constraint, pressure constraint and temperature constraint respectively; In response to the control quantity combination satisfying the preset load constraint, pressure constraint and temperature constraint, the control quantity combination is output.

[0017] Optionally, determining the control quantity combination based on the material retention state level includes: In response to the material retention state level being the first level, the adjustment amount of the first processing unit operating speed, the adjustment amount of the second processing unit operating speed, the adjustment amount of the material input amount, and the adjustment amount of the intermediate transmission section temperature are set to zero. When the material retention state level is the second level, a second processing unit operating speed adjustment amount is generated. When the material retention state level is the third level, the first processing unit operating speed adjustment amount, the second processing unit operating speed adjustment amount, and the material input amount adjustment amount are generated; When the material retention state level is the fourth level, the operating speed adjustment amount of the first processing unit, the operating speed adjustment amount of the second processing unit, the material input amount adjustment amount, and the temperature adjustment amount of the intermediate transmission section are generated.

[0018] Secondly, this application provides a material retention control method based on multi-source parameters, including: Collect multi-source operating parameters of the material handling process, including the operating speed of the first processing unit, the operating speed of the second processing unit, the material input, the driving load of the first processing unit, the driving load of the second processing unit, the pressure of the intermediate transmission section, the output pressure of the second processing unit, and the temperature of the intermediate transmission section. Based on the multi-source operating parameters, the output capacity trend of the first processing unit and the receiving capacity trend of the second processing unit are estimated respectively, and the material inventory trend data of the intermediate transmission segment is generated according to the deviation between the output capacity trend and the receiving capacity trend. The pressure in the intermediate transmission section is processed in a time sequence to extract low-frequency pressure fluctuation characteristics and generate filling and discharging characteristic data. Based on the material inventory trend data, material filling and discharging characteristic data, load deviation between the first processing unit drive load and the second processing unit drive load, and intermediate transmission section temperature, a retention state index is generated; the material retention state level is determined based on the retention state index. Based on the material retention state level, under preset load constraints, pressure constraints, and temperature constraints, at least one of the following control quantities is generated: the operating speed of the first processing unit, the operating speed of the second processing unit, the material input amount, and the temperature of the intermediate transmission section.

[0019] Compared with the prior art, the beneficial effects of the present invention are: This application comprehensively identifies the material retention status in a two-stage material handling process by integrating multiple operating parameters, including the operating speed of the first and second processing units, material input, drive load, pressure, and temperature. By estimating the output capacity trend of the first and second processing units respectively, the matching relationship between upstream and downstream processing capacities can be reflected, and potential hidden material inventory in the intermediate transmission section can be detected in a timely manner. By performing time-series processing on the pressure in the intermediate transmission section and extracting low-frequency pressure fluctuation characteristics, periodic filling and releasing and localized retention phenomena that are difficult to detect using traditional pressure over-limit judgment methods can be identified.

[0020] This application integrates material inventory trends, filling and discharging characteristics, load deviation, and temperature to generate a retention state index, and determines the material retention state level accordingly, making the assessment of retention risk more intuitive and accurate. Based on the retention state level, operating speed, material input, or temperature control values ​​are generated under load, pressure, and temperature constraints to achieve closed-loop regulation of material retention. This reduces the risks of thermal degradation, gelation, black spots, uneven plasticization, and discharge fluctuations caused by excessive local residence time, thereby improving the stability of continuous material processing and the consistency of product quality. Attached Figure Description

[0021] Figure 1A schematic diagram of a material retention control system based on multi-source parameters provided in an embodiment of this application; Figure 2 A flowchart of a material retention control method based on multi-source parameters provided in this application embodiment. Detailed Implementation

[0022] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0023] Example 1: See Figure 1 The diagram shown is a schematic of a material retention control system based on multi-source parameters provided in an embodiment of this application, including: Data acquisition module 10 is used to collect multi-source operating parameters of the material handling process, including the operating speed of the first processing unit, the operating speed of the second processing unit, the material input amount, the driving load of the first processing unit, the driving load of the second processing unit, the pressure of the intermediate transmission section, the output pressure of the second processing unit, and the temperature of the intermediate transmission section. The trend estimation module 20 is used to estimate the output capacity trend of the first processing unit and the receiving capacity trend of the second processing unit based on the multi-source operating parameters, and generate material inventory trend data of the intermediate transmission segment according to the deviation between the output capacity trend and the receiving capacity trend. Feature extraction module 30 is used to perform time-series processing on the pressure of the intermediate transmission section, extract low-frequency pressure fluctuation features, and generate filling and discharging feature data; Index generation module 40 is used to generate a stagnation state index based on the material inventory trend data, material filling and discharging characteristic data, load deviation between the first processing unit drive load and the second processing unit drive load, and intermediate transmission section temperature. Status determination module 50 is used to determine the material retention status level based on the retention status index; The coordination control module 60 is used to generate at least one of the following control quantities based on the material retention state level, under preset load constraints, pressure constraints, and temperature constraints: the operating speed of the first processing unit, the operating speed of the second processing unit, the material input amount, and the temperature of the intermediate transmission section.

[0024] Example 2: See Figure 2 The diagram shown is a flowchart of a material retention control method based on multi-source parameters provided in an embodiment of this application, including steps S101 to S105, wherein: S101 collects multi-source operating parameters of the material handling process, including the operating speed of the first processing unit, the operating speed of the second processing unit, the material input amount, the driving load of the first processing unit, the driving load of the second processing unit, the pressure of the intermediate transmission section, the pressure at the output end of the second processing unit, and the temperature of the intermediate transmission section. S102, based on the multi-source operating parameters, estimate the output capacity trend of the first processing unit and the receiving capacity trend of the second processing unit respectively, and generate material inventory trend data of the intermediate transmission segment according to the deviation between the output capacity trend and the receiving capacity trend. S103, perform time-series processing on the pressure of the intermediate transmission section, extract the low-frequency fluctuation characteristics of the pressure, and generate filling and discharging characteristic data; S104, Based on the material inventory trend data, material filling and discharging characteristic data, load deviation between the first processing unit drive load and the second processing unit drive load, and intermediate transmission section temperature, generate a retention state index; determine the material retention state level based on the retention state index; S105, based on the material retention state level, under preset load constraints, pressure constraints and temperature constraints, generate at least one of the following control quantities: the operating speed of the first processing unit, the operating speed of the second processing unit, the material input amount and the temperature of the intermediate transmission section.

[0025] Regarding the above S101: As an optional implementation method, multi-source operating parameters of the material handling process are collected, including: The operating speed of the first processing unit, the operating speed of the second processing unit, the material input, the driving load of the first processing unit, the driving load of the second processing unit, the pressure of the intermediate transmission section, the output pressure of the second processing unit, and the temperature of the intermediate transmission section are collected synchronously according to the preset sampling cycle. Add time stamps to the data collected within the same sampling period to form a multi-source operating parameter sequence corresponding to the same time window.

[0026] In this embodiment, the first processing unit is an upstream material processing mechanism in the two-stage material processing process, which may be a first-stage extruder, a first-stage mixer, a first-stage conveying screw mechanism, or other processing mechanisms used to plasticize, melt, mix, and convey the input material. The second processing unit is a downstream material processing mechanism, which may be a second-stage extruder, a second-stage conveying screw mechanism, an exhaust conveying mechanism, or a pressure-reducing discharge mechanism. The intermediate transmission section is a material transition channel connecting the first and second processing units, which may include a connecting cylinder, a transition cavity, a connecting pipeline, a connecting barrel, or a buffer channel disposed between the two processing units. The operating speed of the first processing unit is the rotational speed or linear speed of the actuator of the first processing unit, used to characterize the conveying state of the material by the first processing unit; the operating speed of the second processing unit is the rotational speed or linear speed of the actuator of the second processing unit, used to characterize the receiving state of the material from the intermediate transmission section by the second processing unit. The driving load of the first and second processing units are the load current, load torque, or load percentage output by the corresponding drive motor, frequency converter, or servo drive device, respectively.

[0027] In specific implementation, the screw speed and drive load percentage of the first processing unit can be read from the drive device of the first processing unit as the operating speed and drive load of the first processing unit, respectively. Similarly, the screw speed and drive load percentage of the second processing unit can be read from the drive device of the second processing unit as the operating speed and drive load of the second processing unit, respectively. Material input is obtained from the feeding device, weighing feeder, metering pump, or feeding controller. A pressure sensor is placed in the intermediate transmission section to obtain the pressure of the intermediate transmission section. A pressure sensor is also placed at the output end of the second processing unit to obtain the output pressure. A thermocouple, RTD, or infrared temperature detection element is placed in the intermediate transmission section to obtain the temperature of the intermediate transmission section. These sensors or controllers can be connected to the data acquisition module via fieldbus, industrial Ethernet, serial communication interface, or PLC internal registers. The data acquisition module can be a PLC, industrial computer, edge controller, or embedded controller, with an internal sampling trigger clock, and simultaneously reads the data address or input channel corresponding to each parameter according to a preset sampling period. The preset sampling period is the time interval between two adjacent sampling actions, which can be set according to the equipment control cycle, sensor response time, and material residence time, for example, 0.1s, 0.5s, 1s, 2s, or 5s.

[0028] In the When each sampling period arrives, the data acquisition module triggers a synchronous acquisition action to read the running speed of the first processing unit. Second processing unit operating speed Material input quantity The first processing unit drives the load. The second processing unit drives the load. Intermediate transmission section pressure Pressure at the output of the second processing unit and the temperature of the intermediate transmission section To ensure that data within the same sampling period can be used by subsequent modules as status data at the same time, the data acquisition module adds a time stamp to the data after completing the reading. , forming the first Data records for each sampling period The timestamp refers to the sampling time number or timestamp written by the acquisition controller, PLC, industrial computer, or data acquisition module for data within the same sampling period.

[0029] Continuous within the preset time window Data records for each sampling period are time-stamped. The parameters are arranged in a specific order to form a multi-source operating parameter sequence. ,in, The number of sampling periods included within a preset time window can be determined by the preset time window length and the preset sampling period. If the preset time window length is... The preset sampling period is ,but Desirable For example, with a preset time window length of 60 seconds and a preset sampling period of 1 second, It is 60.

[0030] After forming a multi-source operating parameter sequence, it can be preprocessed before trend estimation. Preprocessing first includes outlier removal. Specifically, preset upper and lower limits can be set for each type of parameter. For example, the preset lower limit for the operating speed of the first processing unit is 0 r / min, and the preset upper limit is the maximum allowable speed of the equipment; the preset lower limit for the drive load is 0%, and the preset upper limit is 120% of the rated load; the preset upper limits for the pressure in the intermediate transmission section and the output pressure of the second processing unit can be determined based on the pressure sensor range and the process allowable range; the preset upper and lower limits for the temperature in the intermediate transmission section can be determined based on the material processing temperature range. For any parameter within any sampling period, if the parameter value is less than the corresponding preset lower limit or greater than the corresponding preset upper limit, the parameter value is marked as an outlier and removed from the multi-source operating parameter sequence. The removal method can be either marking the parameter position as null or removing the outlier value of the corresponding parameter in the sampling point while retaining other valid parameters within the same sampling point.

[0031] Next, missing data in the multi-source operating parameter sequence is filled in. Missing data includes null values ​​caused by sensor communication interruptions, null values ​​resulting from outlier removal, and invalid values ​​caused by data read failures. For a certain parameter in the... Missing values ​​in the first sampling period can be filled in using data from adjacent sampling periods. When this parameter is in the first... The sampling period and the first When valid data exists in all sampling periods, the average of the two values ​​is used as the first value. The padding value for the first sampling period; when only the first sampling period When valid data exists in the sampling period, the first sampling period is used. The data from the first sampling period is used as the padding value; when only the first sampling period is used... When valid data exists in the sampling period, the first sampling period is used. The data from each sampling period is used as the padding value.

[0032] Finally, a moving average is applied to the completed multi-source operating parameter sequence. The moving average processing can be performed separately for each type of parameter, with the moving average window length set to 1. ,in This is an integer greater than 1, representing the number of sampling points involved in a single average calculation. In offline processing or when data before and after the current sampling point is permitted, a centered moving average can be used. Taking the operating speed of the first processing unit as an example, when... When =5, the first The smoothing value of the first sampling period can be determined according to the first sampling period. The, the The, the The, the The and the first The speed of the first processing unit in the first sampling cycle is calculated. If the... If a sampling period is located at the beginning or end of a sequence, resulting in insufficient available sampling points before and after it, then the existing valid sampling points near that position are used for averaging. In real-time online processing scenarios, to avoid using future data that has not yet been collected, a causal moving average method can be used, that is, using the current sampling point and the data before it. The average was calculated from each sampling point.

[0033] Following the same method, smoothed values ​​of the second processing unit's operating speed, material input, first processing unit's driving load, second processing unit's driving load, intermediate transmission section pressure, second processing unit's output pressure, and intermediate transmission section temperature can be obtained respectively. These smoothed values ​​are then used to reassemble the pre-processed multi-source operating parameter sequence. , among which, the The data record for each sampling period can be represented as: , For the first Time marker for each sampling period For the first preprocessed The operating speed of the first processing unit in each sampling cycle For the first preprocessed The second processing unit's operating speed per sampling cycle This refers to the input quantity of pre-treated materials. For the first preprocessed The first processing unit in each sampling cycle drives the load. For the first preprocessed The second processing unit drives the load for each sampling cycle. For the pressure of the intermediate transmission section after preprocessing, The output pressure of the second processing unit after pretreatment. This refers to the temperature of the intermediate transmission section after preprocessing.

[0034] Regarding S102 above: As an optional implementation, estimating the output capability trend of the first processing unit includes: Extract the operating speed of the first processing unit, the material input amount, the driving load of the first processing unit, and the pressure of the intermediate transmission section from the preprocessed multi-source operating parameter sequence; Calculate the rate of change of the operating speed of the first processing unit, the rate of change of the material input, the rate of change of the driving load of the first processing unit, and the rate of change of the pressure in the intermediate transmission section, respectively. The output capacity trend of the first processing unit is obtained by weighted summing of the rate of change of the operating speed of the first processing unit, the rate of change of the material input, the rate of change of the driving load of the first processing unit, and the rate of change of the pressure of the intermediate transmission section.

[0035] In practical implementation, the operating speed of the first processing unit, the material input amount, the driving load of the first processing unit, and the pressure of the intermediate transmission section are extracted from the preprocessed multi-source operating parameter sequence. For the first... For each sampling period, calculate the above parameters relative to the first sampling period. The rate of change per sampling period. To avoid the influence of different parameters having different units on the weighted summation, a normalized rate of change is preferred. Specifically, the rate of change of the operating speed of the first processing unit. Material input change rate The first processing unit drives the load change rate. Pressure change rate in intermediate transmission section .in, , , , These are the normalized reference values ​​for the corresponding parameters, which can be the rated values, process settings, historical stable operating averages, or preset range values ​​of the corresponding parameters.

[0036] We take a weighted sum of the above rates of change to obtain the first... Trend of the first processing unit output capability in each sampling period Specifically, it can be expressed as ,in, , , , The first set of weighting coefficients can be preset based on equipment type, material characteristics, and process experience, and should preferably meet the following criteria. In a two-stage extrusion implementation, the operating speed and material input rate of the first processing unit are typically positively correlated with the upstream output capacity. and Positive values ​​are acceptable; an increase in the load driven by the first processing unit usually indicates increased conveying resistance or material filling status in the first processing unit, which can be determined based on process calibration. The symbol and magnitude; an increase in pressure in the intermediate transport section can reflect enhanced material pressure or accumulation in the intermediate transport section, and is used to characterize the pushing effect of upstream output on the intermediate transport section. Positive values ​​are acceptable. As an feasible setting, positive values ​​are acceptable. =0.35, =0.30, =0.20, =0.15.

[0037] As an optional implementation, estimating the throughput trend of the second processing unit includes: Extract the second processing unit's operating speed, the second processing unit's driven load, the intermediate transmission section pressure, and the second processing unit's output pressure from the preprocessed multi-source operating parameter sequence. Calculate the rate of change of the operating speed of the second processing unit, the rate of change of the load driven by the second processing unit, the rate of change of the pressure in the intermediate transmission section, and the rate of change of the pressure at the output end of the second processing unit, respectively. The carrying capacity trend of the second processing unit is obtained by weighted summing of the operating speed change rate of the second processing unit, the driving load change rate of the second processing unit, the pressure change rate of the intermediate transmission section, and the pressure change rate of the output end of the second processing unit.

[0038] Furthermore, the operating speed of the second processing unit, the load driven by the second processing unit, the pressure of the intermediate transmission section, and the output pressure of the second processing unit are extracted from the preprocessed multi-source operating parameter sequence. For the first... Calculate the rate of change of the second processing unit's operating speed for each sampling period. The second processing unit drives the load change rate. Pressure change rate in intermediate transmission section Pressure change rate at the output of the second processing unit ,in, , , , These are the normalized baseline values ​​for the corresponding parameters.

[0039] We take a weighted sum of the above rates of change to obtain the first... Trend of the processing capacity of the second processing unit in each sampling cycle Specifically, it can be expressed as ,in, , , , The second set of weighting coefficients can be preset based on the conveying capacity, outlet resistance, and material flow characteristics of the second processing unit, and preferably meet the following requirements. In a two-stage extrusion implementation, an increased operating speed of the second processing unit typically indicates enhanced accepting capacity. Positive values ​​are acceptable; an increase in the load driven by the second processing unit within a certain range can indicate an increase in the amount of material being conveyed. Positive values ​​are acceptable; an increase in pressure in the intermediate transmission section may indicate an increase in the inlet pressure available for the second processing unit. Positive values ​​are acceptable; an increase in pressure at the output of the second processing unit may indicate increased downstream discharge resistance and limited receiving capacity. Negative values ​​are allowed. As an implementable setting, negative values ​​are allowed. =0.40, =0.20, =0.20, =-0.20.

[0040] As an optional implementation, generating material inventory trend data for intermediate transport segments includes: Calculate the trend difference between the output capability trend of the first processing unit and the capacity trend of the second processing unit to obtain the trend difference of the current sampling period; The cumulative inventory change is obtained by summing the trend differences over multiple consecutive sampling periods. Based on the trend difference and the cumulative inventory change, material inventory trend data for the intermediate transmission segment is generated.

[0041] In specific implementation, the first Trend of the first processing unit output capability in each sampling period Trend of the second processing unit's capacity Then, calculate the trend difference between the two. , .like A value greater than 0 indicates that during the current sampling period, the trend of the first processing unit outputting materials to the intermediate transmission section is stronger than the trend of the second processing unit receiving materials, suggesting a tendency for material accumulation in the intermediate transmission section; if... A value less than 0 indicates that the second processing unit's tendency to accept material is stronger than the first processing unit's tendency to output material, suggesting a tendency for material reduction in the intermediate transmission section; if... A value close to 0 indicates that the upstream and downstream processing capabilities are relatively matched within the current sampling period.

[0042] Subsequently, the trend differences over multiple consecutive sampling periods are accumulated to obtain the cumulative inventory change. Specifically, a fixed-length sliding accumulation window can be used, where the sliding accumulation window contains... Then up to the sampling period, Cumulative inventory changes over a sampling period It can be represented as ,in from to ; For the first The trend difference between the output capacity trend of the first processing unit and the receiving capacity trend of the second processing unit within a sampling period is used to characterize the deviation between the trend amount of the material input intermediate transmission section and the trend amount of the material output intermediate transmission section within that sampling period. Considering the influence of the sampling period length on the cumulative result, it can also be expressed as... .in, The value can be determined based on the volume of the intermediate transfer section, the average residence time of the material, and the control response speed. For example, when the preset sampling period is 1 second and changes in the material state in the intermediate transfer section typically occur within 30 seconds, 30 is acceptable.

[0043] Furthermore, the first Trend difference over each sampling period and cumulative inventory changes Component material inventory trend data ,Right now ,in, Used to reflect the real-time inventory change direction during the current sampling period. It is used to reflect the level of inventory accumulation over multiple consecutive sampling periods.

[0044] Regarding the above S103: As an optional implementation, the pressure in the intermediate transmission section is subjected to time-series processing to extract low-frequency pressure fluctuation characteristics, including: The pressure of the intermediate transmission segment is captured according to a preset time window to obtain pressure timing data; The pressure time series data is subjected to mean removal processing to obtain pressure fluctuation data; The pressure fluctuation data is low-pass filtered to obtain low-frequency pressure fluctuation data; Calculate the low-frequency pressure amplitude and low-frequency pressure period based on the low-frequency pressure fluctuation data; The pressure fluctuation data is subjected to frequency domain transformation, and the ratio between the frequency domain energy in the preset low frequency band and the frequency domain energy of the whole frequency band is calculated to obtain the low frequency energy ratio. The low-frequency pressure amplitude, the low-frequency pressure period, and the low-frequency energy ratio are used as the low-frequency pressure fluctuation characteristics.

[0045] In specific implementation, step S103 takes the preprocessed multi-source operating parameter sequence obtained in step S101 as input, and for the parameter sequence of the first... The sampling period is a preset time window for the current sampling period, which includes the first sampling period. The sampling period up to the first Continuous sampling periods Data from each sampling period. Therefore, by extracting the pressure from the intermediate transmission segment according to a preset time window, pressure time-series data is obtained. Specifically, it can be expressed as If the current sampling period Less than This indicates that the system has not yet accumulated complete data within the preset time window during the initial startup phase. In this case, the data from the first sampling period to the second sampling period can be used. Calculations are performed using existing pressure data within each sampling period, or after accumulating... The complete feature extraction for this step will be initiated after one sampling period.

[0046] Furthermore, the pressure time series data is processed to remove the mean, yielding pressure fluctuation data. Specifically, the pressure fluctuation data is first calculated using the data from the first... The average pressure within a preset time window with each sampling period as the endpoint. , ,in, from Take to , Indicates the first The pressure values ​​of the intermediate transmission segment are collected in each sampling period. Then, the average pressure value is subtracted from the pressure value of each sampling period within the preset time window to obtain the pressure fluctuation data. .in, , , This indicates a local sequence number within the preset time window. Corresponding to the Each sampling period, Corresponding to the Each sampling period. This mean-reduction process eliminates the influence of stable back pressure and process set pressure within the current preset time window on subsequent fluctuation analysis, allowing subsequent low-frequency feature extraction to focus on the dynamic changes in pressure.

[0047] Furthermore, the pressure fluctuation data is low-pass filtered to obtain low-frequency pressure fluctuation data. Low-pass filtering can employ first-order digital low-pass filters, FIR digital low-pass filters, IIR digital low-pass filters, or other filters capable of preserving low-frequency components and suppressing high-frequency noise. Low-frequency pressure fluctuation data can be represented as... As one possible implementation, a first-order digital low-pass filter can be used, making... As the initial filter value, then according to Calculate the first The low-frequency pressure fluctuation values ​​corresponding to each window number, among which... These are the filter coefficients, and As another possible implementation method, the sampling frequency can be adjusted accordingly. Set cutoff frequency And use FIR or IIR low-pass filters for Filtering is performed. If the typical filling and discharging cycle in the equipment is 10s to 100s, the corresponding frequency is approximately 0.01Hz to 0.1Hz. Set it to 0.1Hz or slightly above 0.1Hz to preserve pressure variations within this low-frequency range.

[0048] Furthermore, based on low-frequency pressure fluctuation data Calculate low-frequency pressure amplitude Specifically, take , The larger the value, the stronger the low-frequency fluctuations in pressure in the intermediate transmission section within the preset time window, and the more obvious the dynamic changes in material filling, accumulation, release, or intermittent propulsion within the intermediate transmission section.

[0049] Based on low-frequency pressure fluctuation data When calculating low-frequency pressure cycles, it is possible to identify The peaks or troughs in the waveform are realized. As one possible implementation, the adjacent difference sign change method can be used to identify peaks and troughs. If... ,and Then the serial number in the window will be... The corresponding position is identified as a peak; if ,and Then the serial number in the window will be... The corresponding location is identified as a trough. Among them, To preset the differential threshold and avoid false identification due to minor noise, it can be determined based on the pressure sensor's measurement accuracy, the noise level of low-frequency pressure fluctuation data, and the sampling period length. Specifically, when the equipment is operating stably without significant filling or discharging fluctuations, a segment of low-frequency pressure fluctuation data can be collected, and the absolute value of the difference between adjacent sampling points can be calculated. The standard deviation, and Set it to 2 to 3 times the standard deviation. As an optional method, when the pressure unit is MPa, The value range can be from 0.001 MPa to 0.05 MPa; preferably, it can be from 0.003 MPa to 0.02 MPa. If in If at least two valid peaks are identified, the average sampling interval between adjacent valid peaks is calculated, and this average sampling interval is multiplied by a preset sampling period. The low-frequency pressure cycle is obtained. .

[0050] Pressure fluctuation data A frequency domain transformation is performed to calculate the ratio of the frequency domain energy within the preset low-frequency band to the frequency domain energy across the entire frequency band, thus obtaining the proportion of low-frequency energy. Specifically, this can be done by... Perform Discrete Fourier Transform or Fast Fourier Transform to obtain the spectral amplitudes corresponding to different frequency components. Let the frequency components be... The corresponding spectral amplitude is Then the energy corresponding to this frequency component can be taken as .in, Indicates the first The frequency corresponding to each frequency point This indicates the amplitude of the pressure fluctuation data at this frequency point. The preset low-frequency band is... ,in, This is a preset lower limit frequency for the low-frequency band, used to eliminate DC components, extremely slow drift components, or non-periodic changes caused by sensor zero-point drift. The preset low-frequency band upper limit frequency is used to limit the frequency range of pressure fluctuations related to the periodic filling, discharging, or retention fluctuations in the intermediate transmission section. and The sampling frequency and the typical filling and discharging cycle of the equipment can be predetermined. For example, when the preset sampling cycle is... When the sampling frequency is 1 second, The frequency is 1Hz, and 0.01Hz to 0.1Hz can be set as the preset low frequency band.

[0051] Calculate the frequency domain energy within the preset low-frequency band The summation range only includes frequency points. Falling into the preset low frequency band Frequency components within; calculate the frequency domain energy across the entire frequency band. ,in The effective frequency range represents the set of all effective frequency points used for energy statistics in the frequency domain transformation result. The effective frequency range is the range of pressure fluctuation data at the sampling frequency. The following non-negative frequency range can be analyzed, and can be taken as... When it is necessary to eliminate the influence of the DC component, it can also be taken as follows: ,in, The Nyquist frequency. Low-frequency energy percentage. It can be represented as ,when When it is 0 or close to 0, it can be Set to 0.

[0052] After completing the above processing, the low-frequency pressure amplitude will be... Low-frequency pressure cycle and the proportion of low-frequency energy As a characteristic of low-frequency pressure fluctuations, it can be expressed as .

[0053] As an optional implementation, generating filling and discharging characteristic data includes: Based on the low-frequency pressure fluctuation characteristics, calculate the pressure rise interval and pressure fall interval of the intermediate transmission section within the preset time window; The duration of the pressure rise interval is calculated to obtain the rise duration; the duration of the pressure fall interval is calculated to obtain the fall duration. The pressure fluctuation amplitude is obtained based on the difference between the maximum and minimum pressure values ​​in the low-frequency pressure fluctuation data. The rising duration, falling duration, pressure fluctuation amplitude, and low-frequency energy ratio are combined to obtain the filling and discharging characteristic data.

[0054] In practical implementation, based on low-frequency pressure fluctuation data Calculate the pressure rise and fall intervals within a preset time window. Specifically, for... Difference is performed on data corresponding to adjacent serial numbers within a medium time window to obtain adjacent difference data. ,in, , This indicates the local index within the window corresponding to adjacent difference data.

[0055] ,in This indicates the sequence number of the data point within the preset time window. When differencing adjacent data points, the number of difference values ​​obtained is: indivual.

[0056] When the continuous is not less than indivual Greater than the preset positive threshold When the continuous difference value is not less than a certain value, the time interval corresponding to the pressure rise interval is determined; when the continuous difference value is not less than a certain value, the time interval corresponding to the pressure rise interval is determined. indivual Less than the preset negative threshold When this continuous difference value is used, the time interval corresponding to it is defined as the pressure decrease interval. Among these, The minimum number of consecutive points required to determine the pressure rise range. The minimum number of consecutive points required to determine the pressure drop range. As one possible implementation method, and The values ​​can range from 2 to 10, with 3 to 6 being preferred. A preset positive threshold is used. Used to filter out minute positive fluctuations caused by noise, with a preset negative threshold. Used to filter out tiny negative fluctuations caused by noise. and The appropriate method can be determined based on the pressure sensor's measurement accuracy, the noise level of the low-frequency pressure fluctuation data, and the sampling period length. Specifically, low-frequency pressure fluctuation data can be collected under stable operating conditions, the standard deviation of the absolute values ​​of adjacent differences can be calculated, and then... and Set to 2 to 3 times the standard deviation; for example, and The value range can be from 0.001MPa to 0.05MPa, preferably from 0.003MPa to 0.02MPa.

[0057] The sum of the durations of all pressure rise intervals within a preset time window is used to obtain the rise duration. The sum of the durations of all pressure drop intervals within a preset time window is used to obtain the duration of the drop. .

[0058] Based on low-frequency pressure fluctuation data The difference between the maximum and minimum pressure values ​​yields the pressure fluctuation amplitude. ,Right now In the specific implementation, It can be compared with the aforementioned low-frequency pressure amplitude Taking the same value can also be used as an independent field record for the total filling and discharging characteristic data.

[0059] Then, the duration of the rise. Duration of descent Pressure fluctuation amplitude and the proportion of low-frequency energy Combined, the filling and discharging characteristic data are obtained. .

[0060] Regarding S104 above: As an optional implementation, generating a residence status index includes: The material inventory trend data, the material filling and discharging characteristic data, the load deviation, and the intermediate transmission section temperature are normalized to obtain normalized values ​​for inventory trend, material filling and discharging characteristics, load deviation, and temperature. The normalized values ​​of inventory trend, filling and discharging characteristics, load deviation, and temperature are weighted and summed according to preset weights to obtain the stagnation state index.

[0061] In specific implementation, the material inventory trend data output in step S102 Including the Trend difference over each sampling period and cumulative inventory changes ,Right now When normalizing material inventory trend data, the following steps are performed: and Normalization is performed.

[0062] For trend difference It can be based on the preset trend difference lower limit. Upper limit of the difference between the preset trend and the target value Calculate the normalized value of the trend difference : ; in, Indicates when the variable When less than 0, take 0; when When it is greater than 1, take 1; when When greater than or equal to 0 and less than or equal to 1, take itself. The initial threshold used to characterize the trend difference as a starting point for evaluating the degree of anomaly can be the upper limit of the allowable fluctuation range of the trend difference during normal and stable operation, or a benchmark value close to 0. The threshold used to characterize when the trend difference reaches a significant anomaly can be the upper limit of the trend difference anomaly determined by equipment debugging, historical operating data, or process safety boundaries.

[0063] For cumulative inventory changes Then it can be based on the preset lower limit of inventory change. and preset inventory change limit Normalize it to obtain the inventory trend normalized value. Specifically, a limiting and normalization method can be adopted: ; in, The baseline or lower limit of the cumulative inventory change allowed during normal and stable operation can be taken. The allowable material accumulation in the intermediate transmission section, the cumulative inventory change corresponding to historical retention samples, or the upper limit of cumulative inventory change determined by equipment debugging can be selected.

[0064] Then, according to the sub-weight of inventory trend, and Synthesized into inventory trend normalized value : ; in, For trend difference sub-weights, Accumulate sub-weights for inventory, and For example, 0.4 is acceptable. A value of 0.6 can be chosen so that the cumulative change in inventory contributes slightly more to the risk of sequestration than the instantaneous trend difference for a single sampling period.

[0065] Secondly, the filling and discharging characteristic data are normalized to obtain normalized values ​​of the filling and discharging characteristics. According to step S103, the filling and discharging characteristic data... Since a longer charging / discharging duration usually reflects continuous accumulation in the intermediate transmission section, a larger pressure fluctuation amplitude usually reflects increased charging / discharging intensity, and a higher proportion of low-frequency energy usually reflects that the pressure fluctuation is mainly dominated by the slow charging / discharging process, the normalized value of the rise duration can be calculated separately. Normalized value of pressure fluctuation amplitude and the normalized value of low-frequency energy proportion Specifically, it can be ordered that: ; ; ; in, The preset time window length, This is the lower limit of the pressure fluctuation amplitude, used to characterize the allowable pressure fluctuation benchmark level under normal and stable operating conditions. It can be determined based on the mean, standard deviation, or preset quantile of the pressure fluctuation amplitude in the equipment's normal operating history data. This is the upper limit of the pressure fluctuation amplitude, used to characterize the pressure fluctuation amplitude threshold corresponding to when the pressure fluctuation reaches a significant anomaly or the evaluation value saturates. It can be determined based on equipment commissioning data, historical abnormal operation data, process safety boundaries, or pressure sensor range. As one possible implementation, if the average pressure fluctuation amplitude under normal stable operating conditions is... Standard deviation is It is acceptable ,in This is the normal pressure fluctuation margin coefficient, used to adjust the degree of deviation of the normalized lower limit of the pressure fluctuation amplitude relative to the mean of the normal pressure fluctuation. It can be set according to the noise level of the pressure sensor, the fluctuation characteristics of the normal operation of the equipment, and the sensitivity requirements for abnormal detection. For example, it can be set to 0 to 3, and preferably to 1 to 2. You can take the 90th to 99th percentile of the historical abnormal pressure fluctuation amplitude sample, or take the maximum pressure fluctuation amplitude allowed by the process.

[0066] For the duration of the descent While this may represent a release process and not necessarily increase the risk of retention, when the duration of the rise and fall alternates and the proportion of low-frequency energy is relatively high, it can characterize periodic charging and discharging. Therefore, the normalized value of the charging and discharging imbalance can be further calculated. : ; Then, the above normalized values ​​are combined into normalized values ​​of filling and releasing characteristics according to the preset filling and releasing material weights. : ; Among them, the preset filling and discharging material weights include , , and , Weighted by the duration of the pressure rise. As the weight of pressure fluctuation amplitude, Weighting for the proportion of low-frequency energy. For the unbalanced weighting of the duration of rise and fall, and For example, 0.25 is acceptable. 0.35 is acceptable. 0.3 is acceptable. A value of 0.1 is acceptable. At this value, the pressure fluctuation amplitude and the proportion of low-frequency energy contribute significantly to the normalized value of the filling and discharging characteristics, making it suitable for scenarios where periodic filling and discharging in the intermediate transmission section can be identified through low-frequency pressure fluctuations.

[0067] Next, the load deviation between the load driven by the first processing unit and the load driven by the second processing unit is calculated, and this load deviation is normalized. Specifically, the load deviation can be calculated first. : ; According to the preset load deviation lower limit and preset load deviation limit Calculate the normalized value of load deviation. : ; in, The allowable fluctuation difference between upstream and downstream drive loads during normal and stable operation can be taken as, for example, 5%; A load difference value that indicates a significant difference in processing capacity between upstream and downstream can be used, such as 20% or 25%.

[0068] Then, the temperature of the intermediate transmission section is normalized to obtain a normalized temperature value. Specifically, a temperature reference value is set according to the allowable temperature range of the material process. and upper temperature limit .in The normal process setting temperature for the intermediate transfer section can be used, or the upper limit of the allowable range of the normal process temperature can be used. For example, if the normal process temperature range for a certain material in the intermediate transfer section is 150℃ to 170℃, then... 170℃ is acceptable; if the equipment's target temperature is 160℃ and the allowable fluctuation is ±5℃, then... 165℃ is recommended. The maximum allowable control temperature for the material during intermediate transport can be taken as the upper limit of the temperature at which the material undergoes thermal degradation, gelation, black spots, increased volatility, or a significant increase in the risk of performance fluctuations. For example, if a material should not exceed 190°C, then... 190℃ can be used. To ensure effective normalization, Should be greater than Temperature normalized value It can be represented as: ; when Less than or equal to hour, A value of 0 indicates that the current temperature contributes little to the risk of being stranded; when Approaching or reaching hour, A value close to 1 indicates a higher likelihood of material clumping, deterioration, mixing, or other quality risks due to prolonged local storage when there is inventory accumulation or fluctuations in material supply and demand.

[0069] After normalizing the inventory trend, material filling and discharging characteristics, load deviation, and temperature, the data are weighted and summed according to preset weights to obtain the retention state index. : ; in, As the inventory trend weight, For the filling and discharging characteristic weights, As the load deviation weight, Temperature weighting, and In practice, the weights can be pre-set based on equipment structure, material thermal sensitivity, and process control objectives. For example, for equipment with a large intermediate transfer section volume that is prone to forming hidden inventory, the weights can be increased. For equipment where low-frequency pressure fluctuations can clearly reflect the filling and discharging process, it can improve... For heat-sensitive materials, it can improve... For equipment with significant changes in upstream and downstream drive loads, it can improve... For example, 0.35 is acceptable. 0.3 is acceptable. 0.2 is acceptable. A value of 0.15 is acceptable. This value allows inventory trend data and material filling / discharging characteristics to make the main contribution to the retention index, while load deviation and temperature serve as auxiliary correction factors in the calculation. Retention Index The value can be controlled between 0 and 1. The larger the value, the higher the risk of material stagnation during intermediate transport.

[0070] As an optional implementation, determining the material retention status level based on the retention status index includes: The stagnation state index is compared with a first state threshold, a second state threshold, and a third state threshold, respectively, wherein the first state threshold is less than the second state threshold, and the second state threshold is less than the third state threshold; In response to the retention state index being less than the first state threshold, the material retention state level is determined to be the first level; In response to the retention state index being greater than or equal to the first state threshold and less than the second state threshold, the material retention state level is determined to be the second level. In response to the retention state index being greater than or equal to the second state threshold and less than the third state threshold, the material retention state level is determined to be the third level. In response to the retention state index being greater than or equal to the third state threshold, the material retention state level is determined to be the fourth level.

[0071] In practical implementation, the stagnation index is obtained. Then, compare them with the first state threshold respectively. Second state threshold and the third state threshold Comparison, among which The first state threshold, the second state threshold, and the third state threshold are used to classify different degrees of material retention. Used to distinguish between normal state and slight stagnation state Used to distinguish between mild and moderate states of confinement. Used to distinguish between moderate and severe detention. , and The residence status index can be determined based on the distribution of the residence status index under normal and stable operating conditions, historical residence-related abnormal operating data, equipment commissioning data, process safety boundaries, and quality risk control requirements. As one possible implementation method, when the residence status index is normalized to 0 to 1, A value of 0.3 to 0.5 is acceptable. A value of 0.5 to 0.7 is acceptable. A value of 0.7 to 0.9 is acceptable; preferably, a value of 0.7 is acceptable. , , .

[0072] when When the material retention status is determined to be Level 1, it indicates that the current inventory trend, material filling and discharging fluctuations, load deviation, and temperature in the intermediate transmission section are within a low-risk range, and the risk of material retention is low. When the material retention status is determined to be Level 2, it indicates that there is slight inventory accumulation, slight fluctuations in material filling and discharging, or slight load mismatch in the intermediate transmission section, requiring gentle adjustments in subsequent control. When the material retention status is determined to be Level 3, it indicates that there is significant inventory accumulation, periodic filling and releasing of materials, or uncoordinated load between upstream and downstream in the intermediate transmission section, requiring coordinated adjustment of the operating speed of the first processing unit, the operating speed of the second processing unit, or the material input. When the material retention status is determined to be Level 4, it indicates that the risk of material retention during intermediate transport is high and may be accompanied by significant low-frequency pressure fluctuations, load deviations, or temperature risks, requiring stronger coordination and control in subsequent steps.

[0073] Regarding the above S105: As an optional implementation, generating at least one control quantity among the operating speed of the first processing unit, the operating speed of the second processing unit, the material input amount, and the temperature of the intermediate transfer section includes: The control quantity combination is determined based on the material retention state level. The control quantity combination includes at least one of the following: the first processing unit operating speed adjustment, the second processing unit operating speed adjustment, the material input adjustment, and the intermediate transmission temperature adjustment. The control quantity combination is compared with the preset load constraint, pressure constraint and temperature constraint respectively; In response to the control quantity combination satisfying the preset load constraint, pressure constraint and temperature constraint, the control quantity combination is output.

[0074] In practical implementation, the material retention status level determined in step S104 is used as input, combined with the multi-source operating parameters collected in step S101, including the operating speed of the first processing unit. Second processing unit operating speed Material input quantity The first processing unit drives the load. The second processing unit drives the load. Intermediate transmission section pressure Pressure at the output of the second processing unit and the temperature of the intermediate transmission section Generate control quantity combination , can be represented as ,in, This is the speed adjustment amount for the first processing unit. This is the adjustment amount for the operating speed of the second processing unit. Adjustment amount for material input. This refers to the intermediate transmission temperature adjustment amount. The adjusted operating speed of the first processing unit. Second processing unit operating speed Material input quantity and the temperature of the intermediate transmission section They are respectively: ; ; ; ; When the material retention status level is Level 1, it indicates that the retention status index is below the first status threshold, and the intermediate transmission section is in normal condition. At this time, the operating speed adjustment of the first processing unit, the operating speed adjustment of the second processing unit, the material input adjustment, and the temperature adjustment of the intermediate transmission section are all set to 0. ; ; ; At this point, the control quantity combination is: This setting is used to avoid frequent adjustments to equipment parameters under normal operating conditions, thus maintaining a stable production process.

[0075] When the material retention status level is Level 2, it indicates a slight risk of retention in the intermediate transmission section. The priority is to enhance downstream handling capacity by increasing the operating speed of the second processing unit. At this time, an adjustment amount for the operating speed of the second processing unit is generated, and other adjustment amounts are set to 0. ; ; The operating speed adjustment of the second processing unit can be based on the stagnation index. With the first state threshold Second state threshold The positions between them are determined.

[0076] Let the adjustment intensity coefficient corresponding to the second level be... ,but: ; Let the maximum allowable speed increment of the second processing unit at the second level be... ,but For example, The speed can be 0.03 to 0.08 times the rated operating speed of the second processing unit. In this way, only a mild downstream capacity enhancement is performed in the second stage, avoiding significant disturbance to the upstream plasticizing and feeding processes.

[0077] When the material retention status level is level three, it indicates that there is significant inventory accumulation, periodic filling and releasing of materials, or a mismatch between upstream and downstream processing capacities in the intermediate transmission section. It is necessary to simultaneously adjust the operating speed of the first processing unit, the operating speed of the second processing unit, and the material input quantity. At this time, [the following is generated / generated / etc.]. , and and will Set to 0. The adjustment intensity coefficient corresponding to the third level can be expressed as: ; Let the maximum allowable deceleration of the first processing unit under the third level be: The maximum allowable speed increase for the second processing unit is The maximum allowable reduction in material input is ,but ; ; ; In this context, a negative sign indicates a reduction in the operating speed of the first processing unit or a reduction in the material input, while a positive sign indicates an increase in the operating speed of the second processing unit. For example, The speed can be 3% to 8% of the rated operating speed of the first processing unit. The speed can be 5% to 10% of the rated operating speed of the second processing unit. It can be taken as 3% to 10% of the current material input.

[0078] When the material retention status level is level four, it indicates a high risk of retention in the intermediate transport section. Simultaneously, adjustments to the operating speed of the first processing unit, the operating speed of the second processing unit, the material input quantity, and the temperature of the intermediate transport section need to be generated. The adjustment intensity coefficient corresponding to level four can be determined based on the degree to which the retention status index exceeds the threshold of level three. ; Let the maximum allowable deceleration of the first processing unit under the fourth level be: The maximum allowable speed increase for the second processing unit is The maximum allowable reduction in material input is The maximum allowable temperature adjustment range for the intermediate transmission section is ,but ; ; The temperature adjustment amount for the intermediate transmission section can be based on the current temperature of the intermediate transmission section. Compared with the temperature reference value in step S104 Upper limit of temperature Confirmed. When Greater than or equal to When the temperature of the intermediate transmission section has entered the risk assessment range for stagnation, it indicates that the temperature of the intermediate transmission section has entered the range for which stagnation is likely to occur. In this case, priority should be given to reducing the temperature setpoint of the intermediate transmission section or enhancing cooling. The temperature adjustment amount can be [missing value]. ; Less than At that time, it can be Set to 0 to avoid unnecessary temperature control disturbances when the temperature has not reached the risk assessment range for lingering patients. For example, The speed can be taken as 8% to 15% of the rated operating speed of the first processing unit. The speed can be 8% to 15% of the rated operating speed of the second processing unit. It can be taken as 8% to 15% of the current material input. A temperature range of 3°C to 10°C can be used, for example, 5°C. For materials with high heat sensitivity, the temperature adjustment amount can be appropriately increased.

[0079] After generating candidate control quantity combinations, these combinations are compared with preset load constraints, pressure constraints, and temperature constraints. The preset load constraints may include the upper limit of the drive load of the first processing unit, the upper limit of the drive load of the second processing unit, and the upper limit of the load change rate. Based on the current drive load and the adjustment amount, the adjusted drive load is estimated, and it is determined whether the candidate control quantities meet the load constraints. As one possible implementation, linear incremental estimation can be used. ; ; in, and The adjusted first and second processing units predict the drive load, respectively. , , , and The load response coefficient, determined based on equipment commissioning or historical operating data, can be obtained through a single-factor step test under stable equipment operating conditions. Specifically, keeping other parameters constant, each parameter is slightly changed... , or Record the changes before and after and The stable change in load is used, and the ratio of the load change to the corresponding control change is used as the load response coefficient. For example, Increase by 5 rpm An increase of 2.0% would mean... =0.40% / rpm; Increasing by 20 kg / h An increase of 3.0% would mean... =0.15% / (kg / h). As an example, a value of [missing value] can be taken as [missing value]. =0.40% / rpm =0.15% / (kg / h) =0.30% / rpm =0.10% / (kg / h) =0.20% / rpm.

[0080] Preset pressure constraints may include an upper limit on the pressure of the intermediate transmission section. Lower limit of pressure in intermediate transmission section Upper limit of output pressure of the second processing unit And the upper limit of the rate of change of pressure. To determine whether the candidate control variable meets the pressure constraint, the adjusted pressure can be estimated based on the current pressure and the adjustment amount. As one possible implementation method, linear incremental estimation can be used: ; ; in, Predicting pressure for the adjusted intermediate transmission section, Predict the pressure at the output of the adjusted second processing unit. , , , and The pressure response coefficient is determined based on step tests, historical operating data, or process experience. Specifically, keeping other parameters constant, each parameter is slightly changed. , or Record the changes before and after and The stable change in pressure is used, and the ratio of the pressure change to the corresponding control change is taken as the pressure response coefficient. For example, Increase by 5 rpm An increase of 0.40 MPa, then =0.08MPa / rpm; Increase by 5 rpm If the pressure is reduced by 0.30 MPa, then =0.06MPa / rpm. As an example, a value of... =0.08MPa / rpm =0.06MPa / rpm =0.01MPa / (kg / h) =0.05MPa / rpm =0.008MPa / (kg / h).

[0081] In the above formula, increasing the operating speed of the first processing unit and increasing the material input usually increases the pressure in the intermediate transmission section, while increasing the operating speed of the second processing unit usually enhances the carrying capacity and reduces the pressure in the intermediate transmission section. Therefore, in China Negative influence is employed. The conditions under which candidate control variables satisfy the pressure constraint may include... ; .

[0082] Preset temperature constraints may include the lower limit of the intermediate transmission section temperature. Upper limit of temperature in intermediate transmission section and the upper limit of the single temperature adjustment step size Candidate temperature setpoint Should meet .in, The lowest temperature required for the material to maintain normal flow and plasticization. The maximum allowable control temperature for the material can be selected. If The absolute value exceeds the upper limit of the single temperature adjustment step size. Then limit its amplitude to This is to avoid significant fluctuations in material viscosity and pressure caused by abrupt temperature setpoint changes. The upper limit of the single temperature adjustment step size limits the maximum change in the intermediate transmission section temperature setpoint within a control cycle and can be set according to the material's thermosensitivity and temperature control response speed. For highly thermosensitive materials, A temperature of 1°C to 2°C is acceptable; for materials with good thermal stability, A temperature of 2°C to 5°C is acceptable. For example, when the control cycle is 10 to 30 seconds, A temperature of 2℃ is acceptable; when the control cycle is 60 seconds, 3℃ is acceptable.

[0083] When a candidate control quantity combination simultaneously satisfies preset load constraints, pressure constraints, and temperature constraints, the control quantity combination is output and sent to at least one of the first processing unit drive controller, the second processing unit drive controller, the material input controller, and the intermediate transmission section temperature controller. When a candidate control quantity combination does not satisfy any constraint, the control quantity combination is limited or downgraded and then compared again. As one implementation method, the adjustment amount can be reduced sequentially according to priority, first limiting the speed increase of the second processing unit that may cause load or pressure to exceed limits, then limiting the speed decrease of the first processing unit and the reduction of the material input, and finally limiting the temperature adjustment amount of the intermediate transmission section. Alternatively, a proportional scaling method can be used, where the non-zero adjustment amount in the candidate control quantity combination is multiplied by a scaling factor. ,in and gradually reduce This continues until the predicted load, predicted pressure, and candidate temperature setpoints all meet the constraints.

[0084] Scaling factor This is used to proportionally reduce non-zero regulation when the candidate control variable combination does not meet load constraints, pressure constraints, or temperature constraints. Specifically, it can be set first... =1, if the constraint is not satisfied, then take in turn The values ​​are checked using 0.9, 0.8, 0.7, 0.6, and 0.5 until all constraints are met. The scaled control variable combination is as follows: As an example, The initial value is set to 1, the scaling step size is set to 0.1, and the minimum scaling factor is set to 0.5. If the constraint is still not met after scaling to 0.5, the control value of the previous sampling period or the output zero adjustment value is maintained.

[0085] In this way, by converting the stagnation status identification result into coordinated control quantities for the operating speed of the first processing unit, the operating speed of the second processing unit, the material input quantity, and the temperature of the intermediate transmission section, this application enables the timely suppression of material inventory accumulation and periodic charging and discharging in the intermediate transmission section, while avoiding overload, overpressure, or overtemperature caused by control actions, thereby improving the operational stability and product quality consistency of the continuous material processing process.

[0086] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A material retention control system based on multi-source parameters, characterized in that, include: The data acquisition module is used to collect multi-source operating parameters of the material handling process, including the operating speed of the first processing unit, the operating speed of the second processing unit, the material input, the driving load of the first processing unit, the driving load of the second processing unit, the pressure of the intermediate transmission section, the output pressure of the second processing unit, and the temperature of the intermediate transmission section. The trend estimation module is used to estimate the output capacity trend of the first processing unit and the receiving capacity trend of the second processing unit based on the multi-source operating parameters, and generate material inventory trend data of the intermediate transmission segment according to the deviation between the output capacity trend and the receiving capacity trend. The feature extraction module is used to perform time-series processing on the pressure of the intermediate transmission section, extract low-frequency pressure fluctuation features, and generate filling and discharging feature data. The step of performing time-series processing on the pressure in the intermediate transmission section to extract low-frequency pressure fluctuation features includes: The pressure of the intermediate transmission segment is captured according to a preset time window to obtain pressure timing data; The pressure time series data is subjected to mean removal processing to obtain pressure fluctuation data; The pressure fluctuation data is low-pass filtered to obtain low-frequency pressure fluctuation data; Calculate the low-frequency pressure amplitude and low-frequency pressure period based on the low-frequency pressure fluctuation data; The pressure fluctuation data is subjected to frequency domain transformation, and the ratio between the frequency domain energy in the preset low frequency band and the frequency domain energy of the whole frequency band is calculated to obtain the low frequency energy ratio. The low-frequency pressure amplitude, the low-frequency pressure period, and the low-frequency energy ratio are used as the low-frequency pressure fluctuation characteristics. The generated filling and discharging characteristic data includes: Based on the low-frequency pressure fluctuation characteristics, calculate the pressure rise interval and pressure fall interval of the intermediate transmission section within the preset time window; The duration of the pressure rise interval is calculated to obtain the rise duration; the duration of the pressure fall interval is calculated to obtain the fall duration. The pressure fluctuation amplitude is obtained based on the difference between the maximum and minimum pressure values ​​in the low-frequency pressure fluctuation data. The rising duration, falling duration, pressure fluctuation amplitude, and low-frequency energy ratio are combined to obtain the filling and discharging characteristic data; The index generation module is used to generate a stagnation state index based on the material inventory trend data, the material filling and discharging characteristic data, the load deviation between the first processing unit drive load and the second processing unit drive load, and the intermediate transmission section temperature. The generation of the retention state index includes: The material inventory trend data, the material filling and discharging characteristic data, the load deviation, and the intermediate transmission section temperature are normalized to obtain normalized values ​​for inventory trend, material filling and discharging characteristics, load deviation, and temperature. The normalized values ​​of inventory trend, filling and discharging characteristics, load deviation, and temperature are weighted and summed according to preset weights to obtain the stagnation state index. The status determination module is used to determine the material retention status level based on the retention status index; The coordination control module is used to generate at least one of the following control quantities based on the material retention state level, under preset load constraints, pressure constraints, and temperature constraints: the operating speed of the first processing unit, the operating speed of the second processing unit, the material input amount, and the temperature of the intermediate transmission section.

2. The material retention control system based on multi-source parameters according to claim 1, characterized in that, The multi-source operating parameters of the material processing process are collected, including: The operating speed of the first processing unit, the operating speed of the second processing unit, the material input, the driving load of the first processing unit, the driving load of the second processing unit, the pressure of the intermediate transmission section, the output pressure of the second processing unit, and the temperature of the intermediate transmission section are collected synchronously according to the preset sampling cycle. Add time stamps to the data collected within the same sampling period to form a multi-source operating parameter sequence corresponding to the same time window.

3. The material retention control system based on multi-source parameters according to claim 2, characterized in that, Before trend estimation, the multi-source operating parameter sequence also includes: The multi-source operating parameter sequence is subjected to outlier removal, missing value imputation, and moving average processing to obtain a preprocessed multi-source operating parameter sequence. The outlier removal includes removing data that exceeds the preset upper or lower limit of the corresponding parameter from the multi-source operating parameter sequence, and the missing value filling includes filling missing data with data from adjacent sampling periods.

4. The material retention control system based on multi-source parameters according to claim 3, characterized in that, The estimated output capability trend of the first processing unit includes: Extract the operating speed of the first processing unit, the material input amount, the driving load of the first processing unit, and the pressure of the intermediate transmission section from the preprocessed multi-source operating parameter sequence; Calculate the rate of change of the operating speed of the first processing unit, the rate of change of the material input, the rate of change of the driving load of the first processing unit, and the rate of change of the pressure in the intermediate transmission section, respectively. The output capacity trend of the first processing unit is obtained by weighted summing of the rate of change of the operating speed of the first processing unit, the rate of change of the material input, the rate of change of the driving load of the first processing unit, and the rate of change of the pressure of the intermediate transmission section.

5. The material retention control system based on multi-source parameters according to claim 4, characterized in that, Estimating the trend of the processing capacity of the second processing unit includes: Extract the second processing unit's operating speed, the second processing unit's driven load, the intermediate transmission section pressure, and the second processing unit's output pressure from the preprocessed multi-source operating parameter sequence. Calculate the rate of change of the operating speed of the second processing unit, the rate of change of the load driven by the second processing unit, the rate of change of the pressure in the intermediate transmission section, and the rate of change of the pressure at the output end of the second processing unit, respectively. The carrying capacity trend of the second processing unit is obtained by weighted summing of the operating speed change rate of the second processing unit, the driving load change rate of the second processing unit, the pressure change rate of the intermediate transmission section, and the pressure change rate of the output end of the second processing unit.

6. The material retention control system based on multi-source parameters according to claim 5, characterized in that, The material inventory trend data for generating the intermediate transmission segment includes: Calculate the trend difference between the output capability trend of the first processing unit and the capacity trend of the second processing unit to obtain the trend difference of the current sampling period; The cumulative inventory change is obtained by summing the trend differences over multiple consecutive sampling periods. Based on the trend difference and the cumulative inventory change, material inventory trend data for the intermediate transmission segment is generated.

7. The material retention control system based on multi-source parameters according to claim 1, characterized in that, The determination of the material retention status level based on the retention status index includes: The stagnation state index is compared with a first state threshold, a second state threshold, and a third state threshold, respectively, wherein the first state threshold is less than the second state threshold, and the second state threshold is less than the third state threshold; In response to the retention state index being less than the first state threshold, the material retention state level is determined to be the first level; In response to the retention state index being greater than or equal to the first state threshold and less than the second state threshold, the material retention state level is determined to be the second level. In response to the retention state index being greater than or equal to the second state threshold and less than the third state threshold, the material retention state level is determined to be the third level. In response to the retention state index being greater than or equal to the third state threshold, the material retention state level is determined to be the fourth level.

8. The material retention control system based on multi-source parameters according to claim 7, characterized in that, The control quantity generated includes at least one of the following: the operating speed of the first processing unit, the operating speed of the second processing unit, the material input amount, and the temperature of the intermediate transfer section: The control quantity combination is determined based on the material retention state level. The control quantity combination includes at least one of the following: the first processing unit operating speed adjustment, the second processing unit operating speed adjustment, the material input adjustment, and the intermediate transmission temperature adjustment. The control quantity combination is compared with the preset load constraint, pressure constraint and temperature constraint respectively; In response to the control quantity combination satisfying the preset load constraint, pressure constraint and temperature constraint, the control quantity combination is output.

9. A material retention control system based on multi-source parameters according to claim 8, characterized in that, The determination of the control quantity combination based on the material retention status level includes: In response to the material retention state level being the first level, the adjustment amount of the first processing unit operating speed, the adjustment amount of the second processing unit operating speed, the adjustment amount of the material input amount, and the adjustment amount of the intermediate transmission section temperature are set to zero. When the material retention state level is the second level, a second processing unit operating speed adjustment amount is generated. When the material retention state level is the third level, the first processing unit operating speed adjustment amount, the second processing unit operating speed adjustment amount, and the material input amount adjustment amount are generated; When the material retention state level is the fourth level, the operating speed adjustment amount of the first processing unit, the operating speed adjustment amount of the second processing unit, the material input amount adjustment amount, and the intermediate transmission section temperature adjustment amount are generated.

10. A material retention control method based on multi-source parameters, implemented based on the material retention control system based on multi-source parameters according to any one of claims 1-9, characterized in that, include: Collect multi-source operating parameters of the material handling process, including the operating speed of the first processing unit, the operating speed of the second processing unit, the material input, the driving load of the first processing unit, the driving load of the second processing unit, the pressure of the intermediate transmission section, the output pressure of the second processing unit, and the temperature of the intermediate transmission section. Based on the multi-source operating parameters, the output capacity trend of the first processing unit and the receiving capacity trend of the second processing unit are estimated respectively, and the material inventory trend data of the intermediate transmission segment is generated according to the deviation between the output capacity trend and the receiving capacity trend. The pressure in the intermediate transmission section is processed in a time sequence to extract low-frequency pressure fluctuation characteristics and generate filling and discharging characteristic data. Based on the material inventory trend data, material filling and discharging characteristic data, load deviation between the first processing unit drive load and the second processing unit drive load, and intermediate transmission section temperature, a retention state index is generated; the material retention state level is determined based on the retention state index. Based on the material retention state level, under preset load constraints, pressure constraints, and temperature constraints, at least one of the following control quantities is generated: the operating speed of the first processing unit, the operating speed of the second processing unit, the material input amount, and the temperature of the intermediate transmission section.

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