Underwater granulator hydraulic system based on pressure self-adaptive adjustment and control method

Abstract

The invention relates to the technical field of granulator, in particular to an underwater granulator hydraulic system based on pressure self-adaptive adjustment and a control method. Key parameters such as melt pressure, cutter pressure and cutter shaft rotating speed are monitored in real time, and a target pressure value of the hydraulic system is dynamically calculated in combination with a self-adaptive algorithm; an electro-hydraulic proportional valve and a synchronous control loop are used for achieving accurate adjustment of cutter pressure and displacement synchronization of a plurality of locking cylinders, meanwhile, a micro-flow adjusting valve is used for conducting accurate compensation on a lagging cylinder, and the defect that an existing fixed parameter control mode is difficult to adapt to production dynamic changes is effectively overcome. Therefore, the stability and consistency of cutting quality are remarkably improved, meanwhile, the self-adaptive capacity of equipment to material parameter fluctuation is enhanced, production efficiency is improved, downtime caused by synchronous errors is shortened, and the problems that in the prior art, a fixed parameter control mode is difficult to adapt to dynamic changes in the production process, and the production efficiency is poor are solved. And therefore, the cutting quality and the production efficiency are influenced.

Description

Technical Field

[0001] This invention relates to the field of pelletizer technology, and in particular to a hydraulic system and control method for an underwater pelletizer based on pressure adaptive adjustment. Background Technology

[0002] In the plastics processing industry, underwater pelletizers are key equipment for cutting molten plastic into pellets. Their operational stability and cutting quality directly affect the performance and market competitiveness of the final product. The hydraulic system, as the core drive and control component of the underwater pelletizer, plays a crucial role in providing stable pressure to the cutter and ensuring a tight fit between the cutter and the die for efficient cutting. Traditional underwater pelletizer hydraulic systems often employ fixed parameter control, meaning that parameters such as pressure and flow rate are preset based on experience and kept constant during operation.

[0003] However, in actual production, due to factors such as fluctuations in raw material properties, changes in the production environment, and wear and tear caused by long-term equipment operation, key parameters such as melt pressure and cutter pressure will constantly change. Fixed parameter control methods are difficult to adapt to these dynamic changes, thus affecting cutting quality and production efficiency. Summary of the Invention

[0004] The purpose of this invention is to provide a hydraulic system and control method for an underwater pelletizer based on pressure adaptive adjustment, which solves the technical problem that the fixed parameter control method in the prior art is difficult to adapt to the dynamic changes in the production process, thus affecting the cutting quality and production efficiency.

[0005] To achieve the above objectives, the present invention provides a control method for a hydraulic system of an underwater pelletizer based on pressure adaptive regulation, comprising the following: The system monitors the melt pressure, cutter pressure, cutter shaft speed and hydraulic system pressure of the underwater pelletizer in real time, and collects the water chamber temperature signal. At the same time, the displacement synchronization error is monitored in real time by displacement sensors installed on each locking cylinder. Based on the melt pressure, cutter pressure, cutter shaft speed, and preset material parameters, the target pressure value of the hydraulic system is calculated using an adaptive algorithm. Based on the target pressure value, the pressure output of the hydraulic cylinder is adjusted by the electro-hydraulic proportional valve to maintain the cutting pressure within the set range, while the synchronous control circuit ensures the synchronous displacement of multiple locking cylinders. At the same time, based on the aforementioned synchronous compensation amount, the hysteresis locking cylinder is precisely replenished or drained through an independently set micro-flow regulating valve.

[0006] Among them, the adaptive algorithm is a fuzzy PID control algorithm with an embedded pressure-flow coupling compensation model, wherein the PID parameters are dynamically adjusted according to the rate of change of melt pressure and the deviation of cutter pressure; Fuzzy PID control algorithms include: A three-dimensional fuzzy rule base is established with melt pressure change rate, cutter pressure deviation and cutter shaft speed deviation as inputs and PID parameter correction as output; The input variables are fuzzified based on real-time data, and the correction amount of the PID parameters is output through fuzzy inference. The output is defuzzified to obtain accurate PID parameter values.

[0007] The fuzzy input variables include: The melt pressure change rate is mapped to a preset universe of discourse, and its membership degree to each fuzzy set is calculated using a Gaussian membership function. The cutting pressure deviation is mapped to a preset universe of discourse, and its membership degree to each fuzzy set is calculated using a Gaussian membership function. The tool axis rotation speed deviation is mapped to a preset universe of discourse, and its membership degree to each fuzzy set is calculated using a Gaussian membership function.

[0008] The fuzzy reasoning employs the Mamdani reasoning method, which includes: Based on the fuzzy rule base and the membership degree of the input variables, the fuzzy set of the output variables is obtained through the minimum-maximum operation; Aggregate the fuzzy sets of output variables to generate fuzzy outputs of PID parameter correction values; The rule weights of the fuzzy rule base can be adaptively adjusted online according to different material types.

[0009] Among them, the centroid method is used for defuzzification, including: Calculate the centroid of the membership function of the fuzzy output of the PID parameter correction to obtain the accurate PID parameter correction. Based on the PID parameter correction amount, the proportional coefficient, integral time, and derivative time of the PID controller are updated in real time. The updated PID parameters are processed by the pressure-flow coupling compensation model before being output to the electro-hydraulic proportional valve.

[0010] Specifically, when the system detects a sudden increase in melt pressure exceeding the set safety threshold and a persistently low cutter pressure, it determines that the cutter may break and issues an emergency alarm and executes a shutdown sequence. When the system detects that the synchronous error of multiple locking cylinder displacements exceeds the set value, it automatically compensates for the pressure output and issues a maintenance warning.

[0011] The preset material parameters include melt viscosity, melt temperature and material type. The adaptive algorithm also dynamically adjusts the weight and domain of the fuzzy rule base according to the material parameters and the water chamber temperature signal, and automatically sets the safety threshold and dynamic response rate of the cutter pressure based on the material viscosity.

[0012] This invention also provides a hydraulic system for an underwater pelletizer based on adaptive pressure regulation, which is controlled using the control method for an underwater pelletizer hydraulic system based on adaptive pressure regulation as described above. include: The pressure monitoring module is used to monitor melt pressure, cutter pressure, and hydraulic system pressure in real time. The controller is used to calculate the target pressure value of the hydraulic system based on the monitored pressure, speed, temperature and preset material parameters, and to generate control signals by using an adaptive fuzzy PID algorithm with an embedded pressure-flow coupling compensation model. A hydraulic regulating module is used to regulate the pressure output of a hydraulic system according to a control signal, including an electro-hydraulic proportional valve that forms a closed-loop control with the controller; The hydraulic actuation module includes a main hydraulic motor that drives the cutter and multiple double-piston rod locking hydraulic cylinders that control the opening and closing of the water chamber. The oil circuit of the locking hydraulic cylinder is equipped with a synchronous control circuit. The human-machine interface is used to set the cutting pressure range, material parameters and adaptive algorithm parameters, and to display system status, alarm information and fault diagnosis results.

[0013] This invention discloses a hydraulic system and control method for an underwater pelletizer based on pressure adaptive regulation. By real-time monitoring of key parameters such as melt pressure, cutter pressure, and cutter shaft speed, and combining this with an adaptive algorithm to dynamically calculate the target pressure value of the hydraulic system, the invention utilizes an electro-hydraulic proportional valve and a synchronous control loop to achieve precise adjustment of the cutter pressure and synchronization of the displacement of multiple locking cylinders. Simultaneously, a micro-flow regulating valve provides precise compensation for lagging cylinders. This effectively overcomes the shortcomings of existing fixed-parameter control methods that are difficult to adapt to dynamic changes in production, thus significantly improving the stability and consistency of cutting quality. It also enhances the equipment's adaptability to material parameter fluctuations, increases production efficiency, and reduces downtime caused by synchronization errors. This method solves the technical problem in existing technologies where fixed-parameter control methods are unable to adapt to dynamic changes in the production process, thereby affecting cutting quality and production efficiency. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below.

[0015] Figure 1This is a flowchart of the control method for the hydraulic system of an underwater pelletizer based on pressure adaptive adjustment according to the present invention.

[0016] The embodiments of the present invention are described in detail below. Examples of the embodiments are shown in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, but should not be construed as limiting the present invention.

[0017] Please see Figure 1 , Figure 1 This is a flowchart of the control method for the hydraulic system of an underwater pelletizer based on pressure adaptive adjustment according to the present invention. Detailed Implementation

[0018] This invention provides a control method for a hydraulic system of an underwater pelletizer based on pressure adaptive regulation, comprising: S1. Real-time monitoring of melt pressure, cutter pressure, cutter shaft speed and hydraulic system pressure of the underwater pelletizer, and acquisition of water chamber temperature signal. At the same time, displacement synchronization error is monitored in real time by displacement sensors installed on each locking cylinder. S2. Based on the melt pressure, cutter pressure, cutter shaft speed and preset material parameters, calculate the target pressure value of the hydraulic system using an adaptive algorithm; For this specific implementation, the adaptive algorithm is a fuzzy PID control algorithm with an embedded pressure-flow coupling compensation model, wherein the PID parameters are dynamically adjusted according to the rate of change of melt pressure and the deviation of cutter pressure. Fuzzy PID control algorithms include: A three-dimensional fuzzy rule base is established with melt pressure change rate, cutter pressure deviation and cutter shaft speed deviation as inputs and PID parameter correction as output; The input variables are fuzzified based on real-time data, and the correction amount of the PID parameters is output through fuzzy inference. The output is defuzzified to obtain accurate PID parameter values.

[0019] The fuzzy input variables include: The melt pressure change rate is mapped to a preset universe of discourse, and its membership degree to each fuzzy set is calculated using a Gaussian membership function. The cutting pressure deviation is mapped to a preset universe of discourse, and its membership degree to each fuzzy set is calculated using a Gaussian membership function. The tool axis rotation speed deviation is mapped to a preset universe of discourse, and its membership degree to each fuzzy set is calculated using a Gaussian membership function.

[0020] The fuzzy reasoning employs the Mamdani reasoning method, which includes: Based on the fuzzy rule base and the membership degree of the input variables, the fuzzy set of the output variables is obtained through the minimum-maximum operation; Aggregate the fuzzy sets of output variables to generate fuzzy outputs of PID parameter correction values; The rule weights of the fuzzy rule base can be adaptively adjusted online according to different material types.

[0021] Among them, the centroid method is used for defuzzification, including: Calculate the centroid of the membership function of the fuzzy output of the PID parameter correction to obtain the accurate PID parameter correction. Based on the PID parameter correction amount, the proportional coefficient, integral time, and derivative time of the PID controller are updated in real time. The updated PID parameters are processed by the pressure-flow coupling compensation model before being output to the electro-hydraulic proportional valve.

[0022] S3. Based on the target pressure value, the pressure output of the hydraulic cylinder is adjusted by the electro-hydraulic proportional valve to maintain the cutting pressure within the set range, while the displacement of multiple locking cylinders is synchronized by the synchronous control circuit. S4. Simultaneously, based on the aforementioned synchronous compensation amount, the hysteresis locking cylinder is precisely replenished or drained using an independently configured micro-flow regulating valve.

[0023] For this specific implementation method, When the system detects a sudden increase in melt pressure exceeding the set safety threshold and a persistently low cutter pressure, it determines that the cutter may break and issues an emergency alarm and executes a shutdown sequence. When the system detects that the synchronous error of multiple locking cylinder displacements exceeds the set value, it automatically compensates for the pressure output and issues a maintenance warning.

[0024] The preset material parameters include melt viscosity, melt temperature and material type. The adaptive algorithm also dynamically adjusts the weight and domain of the fuzzy rule base according to the material parameters and the water chamber temperature signal, and automatically sets the safety threshold and dynamic response rate of the cutter pressure based on the material viscosity.

[0025] Blockchain technology is used to encrypt and distribute key data in this control process (such as target pressure values, synchronization errors, and control instructions) to establish an immutable production process record. Simultaneously, data mining algorithms (such as association rule analysis or time series pattern mining) are periodically applied to perform in-depth analysis of the massive amounts of historical data stored, uncovering multi-parameter coupling relationship vectors that affect cutting quality and equipment stability.

[0026] The key feature vectors mined from the data are fed back to the training module of the adaptive algorithm for continuous iteration and optimization of the control model. This enables the system to learn and evolve autonomously from historical experience, thereby achieving more precise and efficient control in the next production cycle or for similar materials.

[0027] Furthermore, by utilizing temporal deep learning algorithms such as Long Short-Term Memory (LSTM) networks, the remaining lifespan of critical components (such as spindle bearings and hydraulic seals) can be dynamically predicted, enabling a shift from passive response to predictive maintenance.

[0028] This embodiment employs a control method for an underwater pelletizer hydraulic system based on pressure adaptive regulation. The invention monitors key parameters such as melt pressure, cutter pressure, and cutter shaft speed in real time, and dynamically calculates the target pressure value of the hydraulic system using an adaptive algorithm. It utilizes an electro-hydraulic proportional valve and a synchronous control loop to achieve precise adjustment of the cutter pressure and synchronization of the displacement of multiple locking cylinders. Simultaneously, a micro-flow regulating valve provides precise compensation for lagging cylinders. This effectively overcomes the shortcomings of existing fixed-parameter control methods that struggle to adapt to dynamic changes in production, significantly improving the stability and consistency of cutting quality. It also enhances the equipment's adaptability to material parameter fluctuations, increases production efficiency, and reduces downtime caused by synchronization errors. This method solves the technical problem in existing technologies where fixed-parameter control methods are unable to adapt to dynamic changes in the production process, thus affecting cutting quality and production efficiency.

[0029] This invention also provides a hydraulic system for an underwater pelletizer based on adaptive pressure regulation, controlled by the control method for an underwater pelletizer hydraulic system based on adaptive pressure regulation as described above, including: The pressure monitoring module is used to monitor melt pressure, cutter pressure, and hydraulic system pressure in real time. The controller is used to calculate the target pressure value of the hydraulic system based on the monitored pressure, speed, temperature and preset material parameters, and to generate control signals by using an adaptive fuzzy PID algorithm with an embedded pressure-flow coupling compensation model. A hydraulic regulating module is used to regulate the pressure output of a hydraulic system according to a control signal, including an electro-hydraulic proportional valve that forms a closed-loop control with the controller; The hydraulic actuation module includes a main hydraulic motor that drives the cutter and multiple double-piston rod locking hydraulic cylinders that control the opening and closing of the water chamber. The oil circuit of the locking hydraulic cylinder is equipped with a synchronous control circuit. The human-machine interface is used to set the cutting pressure range, material parameters and adaptive algorithm parameters, and to display system status, alarm information and fault diagnosis results.

[0030] The above-disclosed embodiments are merely one or more preferred embodiments of this application and should not be construed as limiting the scope of this application. Those skilled in the art can understand that all or part of the processes for implementing the above embodiments and equivalent changes made in accordance with the claims of this application still fall within the scope of this application.

Claims

1. A control method for a hydraulic system of an underwater pelletizer based on pressure adaptive regulation, characterized in that, Including the following: The system monitors the melt pressure, cutter pressure, cutter shaft speed and hydraulic system pressure of the underwater pelletizer in real time, and collects the water chamber temperature signal. At the same time, the displacement synchronization error is monitored in real time by displacement sensors installed on each locking cylinder. Based on the melt pressure, cutter pressure, cutter shaft speed, and preset material parameters, the target pressure value of the hydraulic system is calculated using an adaptive algorithm. Based on the target pressure value, the pressure output of the hydraulic cylinder is adjusted by the electro-hydraulic proportional valve to maintain the cutting pressure within the set range, while the synchronous control circuit ensures the synchronous displacement of multiple locking cylinders. At the same time, based on the aforementioned synchronous compensation amount, the hysteresis locking cylinder is precisely replenished or drained through an independently set micro-flow regulating valve.

2. The control method for the hydraulic system of an underwater pelletizer based on pressure adaptive regulation as described in claim 1, characterized in that, The adaptive algorithm is a fuzzy PID control algorithm with an embedded pressure-flow coupling compensation model, in which the PID parameters are dynamically adjusted according to the rate of change of melt pressure and the deviation of cutter pressure. Fuzzy PID control algorithms include: A three-dimensional fuzzy rule base is established with melt pressure change rate, cutter pressure deviation and cutter shaft speed deviation as inputs and PID parameter correction as output; The input variables are fuzzified based on real-time data, and the correction amount of the PID parameters is output through fuzzy inference. The output is defuzzified to obtain accurate PID parameter values.

3. The control method for the hydraulic system of an underwater pelletizer based on pressure adaptive adjustment as described in claim 2, characterized in that, The fuzzy input variables include: The melt pressure change rate is mapped to a preset universe of discourse, and its membership degree to each fuzzy set is calculated using a Gaussian membership function. The cutting pressure deviation is mapped to a preset universe of discourse, and its membership degree to each fuzzy set is calculated using a Gaussian membership function. The tool axis rotation speed deviation is mapped to a preset universe of discourse, and its membership degree to each fuzzy set is calculated using a Gaussian membership function.

4. The control method for the hydraulic system of an underwater pelletizer based on pressure adaptive adjustment as described in claim 3, characterized in that, Fuzzy reasoning employs the Mamdani reasoning method, including: Based on the fuzzy rule base and the membership degree of the input variables, the fuzzy set of the output variables is obtained through the minimum-maximum operation; Aggregate the fuzzy sets of output variables to generate fuzzy outputs of PID parameter correction values; The rule weights of the fuzzy rule base can be adaptively adjusted online according to different material types.

5. The control method for the hydraulic system of an underwater pelletizer based on pressure adaptive regulation as described in claim 4, characterized in that, The centroid method is used to resolve fuzziness, including: Calculate the centroid of the membership function of the fuzzy output of the PID parameter correction to obtain the accurate PID parameter correction. Based on the PID parameter correction amount, the proportional coefficient, integral time, and derivative time of the PID controller are updated in real time. The updated PID parameters are processed by the pressure-flow coupling compensation model before being output to the electro-hydraulic proportional valve.

6. The control method for the hydraulic system of an underwater pelletizer based on pressure adaptive adjustment as described in claim 5, characterized in that, When the system detects a sudden increase in melt pressure exceeding the set safety threshold and a persistently low cutter pressure, it determines that the cutter may break and issues an emergency alarm and executes a shutdown sequence. When the system detects that the synchronous error of multiple locking cylinder displacements exceeds the set value, it automatically compensates for the pressure output and issues a maintenance warning.

7. The control method for the hydraulic system of an underwater pelletizer based on pressure adaptive regulation as described in claim 6, characterized in that, The preset material parameters include melt viscosity, melt temperature and material type. The adaptive algorithm also dynamically adjusts the weights and domain of the fuzzy rule base according to the material parameters and the water chamber temperature signal, and automatically sets the safety threshold and dynamic response rate of the cutter pressure based on the material viscosity.

8. A hydraulic system for an underwater pelletizer based on adaptive pressure regulation, controlled by the control method for an underwater pelletizer hydraulic system based on adaptive pressure regulation as described in claim 7, characterized in that... include: The pressure monitoring module is used to monitor melt pressure, cutter pressure, and hydraulic system pressure in real time. The controller is used to calculate the target pressure value of the hydraulic system based on the monitored pressure, speed, temperature and preset material parameters, and to generate control signals by using an adaptive fuzzy PID algorithm with an embedded pressure-flow coupling compensation model. A hydraulic regulating module is used to regulate the pressure output of a hydraulic system according to a control signal, including an electro-hydraulic proportional valve that forms a closed-loop control with the controller; The hydraulic actuation module includes a main hydraulic motor that drives the cutter and multiple double-piston rod locking hydraulic cylinders that control the opening and closing of the water chamber. The oil circuit of the locking hydraulic cylinder is equipped with a synchronous control circuit. The human-machine interface is used to set the cutting pressure range, material parameters and adaptive algorithm parameters, and to display system status, alarm information and fault diagnosis results.

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