Casting machine flow control system based on multi-parameter feedback and PID dynamic adjustment

Abstract

The invention discloses a pouring machine flow control system based on multi-parameter feedback and PID dynamic adjustment, and relates to the technical field of automatic control of mold pouring, the system comprises a tilting parameter module, a liquid level dynamic modeling module, a flow adaptive control module and an execution mechanism module; the tilting parameter module collects the angular velocity and angle data of a casting ladle in real time, the liquid level dynamic modeling module calculates the liquid level height according to the angular velocity, the angle data and the geometrical shape of the casting ladle, and the flow self-adaptive control module dynamically calculates the current flow value. And the preset flow target and the real-time flow difference value are input into a PID controller to generate a tilting adjustment signal to drive an execution mechanism module to adjust the flow of the casting machine. The liquid level height and the flow are calculated through mechanical motion parameters, the problem that the sensor is in direct contact with liquid in the high-temperature and high-pressure environment and fails is solved, and stable operation in the severe environment is guaranteed; and adaptive PID control and a multi-parameter fusion model are used for cooperative work, so that the steady-state error is reduced, and the response speed is increased.

Description

Technical Field

[0001] This invention relates to the field of automated control technology for mold casting, and in particular to a flow control system for casting machines based on multi-parameter feedback and PID dynamic adjustment. Background Technology

[0002] In the field of industrial automation, fully automatic casting machines, as specialized equipment for pouring molten iron in the metal casting industry, have the core requirement of achieving precise flow control to ensure product quality and production efficiency. Pouring is a crucial step in the casting production process, directly affecting the stability of casting quality and production efficiency, and having a decisive impact on product performance and process control.

[0003] Traditional flow control technology for casting machines mainly relies on two methods. The first method uses contact or non-contact sensors to monitor parameters such as liquid level in real time, combined with a PID controller with fixed parameters for adjustment. This method is prone to sensor damage or signal interference under high temperature and closed conditions, leading to measurement failure. Furthermore, it requires direct contact with the liquid or immersion in the container, which imposes constraints on liquid flowability and container design. The second method often treats the tilting motion control and flow regulation of the casting machine as independent processes, lacking modeling and connection of the dynamic coupling effect between the two. This method has limitations such as flow estimation error changing with the cumulative changes in operating conditions, and the inability of traditional control strategies to compensate for the interference of mechanical motion on flow output in real time during repeated tilting, leading to control instability. Summary of the Invention

[0004] To address the above issues, this invention proposes a flow control system for a casting machine based on multi-parameter feedback and PID dynamic adjustment. The system uses an encoder to collect real-time mechanical motion parameters (angular velocity and angle data) of the tilting device. By combining these parameters with a fluid dynamics model, the liquid level and flow rate are dynamically calculated. This avoids sensor failure due to direct contact with the liquid under high temperature and pressure conditions, ensuring stable system operation in harsh environments. An adaptive PID control system is used to achieve closed-loop optimization control, resulting in a faster response speed than traditional PID systems. The equipment is easy to maintain and use; simply inputting a preset target flow rate enables fully automatic and stable flow casting. This solves problems such as strong sensor dependence, low model accuracy, and dynamic response lag, providing an innovative solution for precise casting in high-temperature, enclosed, and highly dynamic industrial scenarios.

[0005] The flow control system for a casting machine based on multi-parameter feedback and PID dynamic adjustment includes a tilt parameter acquisition module, a liquid level dynamic modeling module, a flow adaptive control module, and an actuator module.

[0006] The tilt parameter acquisition module collects the angular velocity and angle data of the ladle in real time;

[0007] The liquid surface dynamic modeling module uses angular velocity data, angle data, and mathematical modeling of the ladle's geometry to dynamically calculate the liquid surface height information of the ladle.

[0008] The adaptive flow control module calculates the estimated actual flow rate based on the liquid level information and inputs the difference between the preset target flow rate and the real-time estimated flow rate into the PID controller to generate a tilt adjustment signal.

[0009] The actuator module drives a high-precision tilting mechanism based on the tilting adjustment signal, which in turn causes the pouring ladle to tilt to adjust the pouring flow rate.

[0010] Preferably, the dynamic calculation of the liquid level height information in the ladle using angular velocity data, angle data, and mathematical modeling of the ladle's geometry is as follows:

[0011] A dynamic model of the liquid level height is constructed using mathematical modeling based on angular velocity, angle data, and the geometry of the ladle, and is expressed as follows:

[0012]

[0013] Where h(t) represents the liquid level; ω(t) represents the angular velocity; θ(t) represents the angle θ with t as a parameter; A(θ) represents the effective cross-sectional area of ​​the container at angle θ; V s (θ(t)) represents the reference volume of the container at angle θ; q(t) represents the actual flow rate; t represents time;

[0014] The change curve of the liquid level is obtained by integrating the dynamic model of the liquid level.

[0015] Preferably, the calculation of the estimated actual flow rate based on the liquid level information is as follows:

[0016] The flow rate variation formula is obtained by transforming Bernoulli's equation. Substituting the liquid level information into the flow rate variation formula yields the actual flow rate variation curve; the actual flow rate variation curve is expressed as:

[0017]

[0018] Where q(t) represents the estimated actual flow rate; c represents the flow coefficient; L represents the orifice width; g represents the gravitational acceleration; and h(t) represents the liquid level.

[0019] Preferably, the tilt adjustment signal is represented as:

[0020]

[0021] Where u(t) represents the tilt adjustment signal; K p Ki and K d These represent the proportional, integral, and derivative parameters of the PID controller, respectively; e(t) represents the difference between the preset flow target value and the real-time flow estimate.

[0022] Preferably, the flow adaptive control module further includes: using a fuzzy logic algorithm to adaptively adjust the proportional parameter K of the PID controller based on the real-time difference between the preset target flow and the actual flow value and its rate of change. p Integral parameter K i and differential parameter K d This enables dynamic optimization of control parameters.

[0023] Preferably, the high-precision tilting mechanism includes a servo motor, a servo motor support, a tilting shaft, and a bearing support; the servo motor is fixed to the servo motor support; the bearing support has a built-in bearing to support the free rotation of the tilting shaft; the output shaft of the servo motor is rigidly connected to the drive end of the tilting shaft through a reducer; the servo motor support is rigidly connected to the main frame of the casting machine, the bearing support is rigidly connected to the main frame of the casting machine, and the tilting shaft is rigidly connected to the ladle; the rotation of the servo motor drives the tilting shaft to rotate through the reducer, thereby causing the ladle to tilt.

[0024] Preferably, the angular velocity and angle data of the ladle are collected in real time by several sensors set on the tilting axis.

[0025] Preferably, the sensor is a photoelectric encoder or magnetic encoder with a resolution of not less than 17 bits and a sampling frequency of not less than 1kHz; the coaxiality error between the sensor's rotation axis and the tilt axis mechanical axis is within 0.05mm.

[0026] Preferably, the flow adaptive control module further includes a load change prediction model based on historical data; the load change prediction model generates a feedforward compensation signal input to the high-precision tilting mechanism to offset external disturbances, and activates a steady-state holding mechanism when the flow relative error is less than ±0.5%, thereby reducing frequent adjustments of the mechanical system.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] (1) This invention calculates the liquid level height and flow rate through mechanical motion parameters, and is activated in high-temperature environments without direct liquid level sensors. It relies on mathematical models to achieve indirect liquid level measurement, avoiding the problem of sensor failure due to direct contact with liquid in high-temperature and high-pressure environments, and ensuring stable operation of the system in harsh environments.

[0029] (2) This invention reduces the reliance on high-cost sensors, and the modular design supports rapid fault diagnosis and component replacement; the equipment is easy to maintain and use, and can achieve fully automatic stable flow casting simply by manually inputting the preset target flow rate;

[0030] (3) The present invention works in collaboration with adaptive PID control and multi-parameter fusion model, and the response speed is faster than that of traditional PID; it is suitable for high-precision flow control of various metal castings, and is especially suitable for non-contact measurement of high temperature and corrosive fluids. Attached Figure Description

[0031] The present invention will now be described in further detail with reference to the accompanying drawings;

[0032] Figure 1 This is a schematic diagram of the framework of the casting machine flow control system based on multi-parameter feedback and PID dynamic adjustment according to an embodiment of the present invention;

[0033] Figure 2 This is a structural diagram of the fully automatic casting machine casting process of the casting machine flow control system based on multi-parameter feedback and PID dynamic adjustment according to an embodiment of the present invention.

[0034] Figure 3 This is an algorithm flowchart of the casting machine flow control system based on multi-parameter feedback and PID dynamic adjustment according to an embodiment of the present invention;

[0035] Reference numerals: 1. Casting fluid; 2. Sprue; 3. Ladle shell; 4. Liquid inside the ladle; 5. Tilting angle; 6. Liquid level; 7. Tilting axis. Detailed Implementation

[0036] The present invention will be further described below through specific embodiments.

[0037] like Figure 1 As shown, the flow control system for a casting machine based on multi-parameter feedback and PID dynamic adjustment includes: a tilt parameter acquisition module, a liquid level dynamic modeling module, a flow adaptive control module, and an actuator module, as detailed below.

[0038] like Figure 2 As shown, the casting fluid begins to flow when the tilt angle is greater than 16 degrees. The tilt parameter acquisition module is installed in key parts of the casting machine (such as...). Figure 2 Multiple sensors (shown at point 7 on the tilt axis) collect the tilt angle and acceleration of the casting machine in real time. The analog signals collected by the sensors are converted from analog to digital and then sent to the centralized control system. Through filtering, correction, and preprocessing of the collected data, accurate tilt parameters are obtained, providing crucial data for subsequent liquid level model prediction.

[0039] Specifically, the tilt parameter acquisition module is installed coaxially on the tilt shaft of the casting machine, and acquires the angular velocity ω(t) and angle θ(t) of the tilt shaft in real time through a high-precision encoder. The tilt parameter acquisition module uses a photoelectric encoder or magnetic encoder with a resolution of no less than 17 bits, and is fixedly installed coaxially with the tilt shaft of the casting machine. The sampling frequency is no less than 1kHz, and the coaxiality error is controlled within 0.05mm to ensure the accuracy of the angle and angular velocity data acquisition.

[0040] Unlike traditional methods that directly measure liquid level using level sensors, this system utilizes angle and angular velocity parameters collected by sensors such as a 17-bit resolution encoder. These parameters are then input into a pre-established mathematical model of liquid level height in the dynamic modeling module to calculate the liquid level in the container in real time. This mathematical model considers the relationship between tilt angle, angular velocity, and the characteristics of the liquid geometry container, accurately reflecting the dynamic changes in the liquid level as the equipment tilts, thus providing precise liquid level data for the flow control system.

[0041] Specifically, by receiving real-time angular velocity ω(t) and angle θ(t) data from sensors, and using the lowest point of the spout 2 structure as a reference point, a dynamic calculation model for the liquid level height h(t) is established, taking into account the container's geometric parameters and the influence of factors such as liquid inertia and centrifugal force. Here, the liquid level height h(t) is defined as the vertical distance between the free surface of the liquid inside the container and the spout reference point. Based on Bernoulli's equation and the continuity equation, a flow rate calculation model is constructed. By using real-time monitoring of fluid density, viscosity, container tilt angle, and tilt angular velocity parameters, a dynamic correction mechanism considering fluid characteristics is established to achieve accurate calculation of the liquid level height and flow rate.

[0042] Specifically, the liquid surface dynamic modeling module adopts the following steps:

[0043] By combining angular velocity ω(t) and angle θ(t), a geometric model of the liquid level height h(t) is constructed based on the analysis of the container geometry.

[0044] The dynamic model of the liquid level height is expressed as: Where h(t) represents the liquid level; ω(t) represents the angular velocity; θ(t) represents the angle θ with t as a parameter; A(θ) represents the effective cross-sectional area of ​​the container at angle θ; V s (θ(t)) represents the reference volume of the container at angle θ; q(t) represents the actual flow rate; and t represents time. Integrating this model yields the curve of the change in liquid level h(t).

[0045] The adaptive flow control system, as the core of the entire system, primarily employs a PID control algorithm to achieve adaptive flow regulation. The control system uses a preset stable flow rate as the target value, and takes real-time collected tilt parameters and liquid level as feedback inputs. The error between these parameters and the target value is processed by the PID algorithm to obtain the control output. By dynamically adjusting the PID parameters (proportional, integral, and derivative parameters), rapid and accurate regulation of the liquid flow rate is achieved.

[0046] Specifically, the flow adaptive control system employs the following steps:

[0047] Obtained through the transformation of Bernoulli's equation The formula for flow rate change is used to obtain the curve of the actual flow rate q(t) by substituting the liquid level height h(t).

[0048] The PID controller receives the preset flow target value q. target The difference e(t) between the actual flow rate q(t) and the actual flow rate q(t) generates the adjustment signal. Model predictive control (MPC) is used to dynamically adjust K. p K i and K d It adapts to nonlinear disturbances.

[0049] In this embodiment, the flow adaptive control module employs a fuzzy logic algorithm to adaptively adjust the proportional coefficient K of the PID controller based on the real-time difference between the preset target flow rate and the actual flow rate, as well as the rate of change. p Integral coefficient K i and differential coefficient K d This enables dynamic optimization of control parameters.

[0050] In addition, the flow adaptive control module also includes a load change prediction model based on historical data. This model generates a feedforward compensation signal to offset external disturbances and activates a steady-state holding mechanism when the flow relative error is less than ±0.5%, reducing the frequent adjustments of the mechanical system.

[0051] The regulation signal output by the PID controller, after signal processing and amplification, is transmitted to the actuator module. The actuator module mainly includes precision regulating devices such as solenoid valves, hydraulic regulators, servo motors, and reducers. The signal received by the actuator directly controls the tilting speed of the casting machine, thereby affecting the flow rate (e.g.,...). Figure 2 Fine-tuning is performed on the injection fluid at point 1 (as shown) to achieve stable control of the entire system. Furthermore, to ensure rapid response and high reliability, the actuator module also integrates redundancy protection and fault alarm functions.

[0052] The actuator module adopts a high-precision servo motor system with a zero-backlash reducer. The servo motor is rigidly connected to the tilting shaft of the casting machine through the reducer, achieving a tilting angle adjustment accuracy better than ±0.1 degrees. The dynamic response characteristics of the system are ensured through multiple position feedbacks.

[0053] Specifically, the actuator module includes a high-precision tilting mechanism and a closed-loop feedback mechanism. The high-precision tilting mechanism consists of a servo motor, a servo motor support, a tilting shaft, and a bearing support. The servo motor is bolted to the servo motor support, which is further rigidly connected to the main frame of the casting machine. A bearing support is installed on one side of the tilting shaft, and the bearing support contains a high-precision crossed roller bearing to support the free rotation of the tilting shaft. The output shaft of the servo motor and the drive end of the tilting shaft are coaxially connected by a zero-backlash coupling to ensure that the coaxiality error of the power transmission is ≤0.02mm, thereby ensuring the accuracy of the tilting angle adjustment and the smoothness of the movement.

[0054] The closed-loop feedback optimization records the changes in liquid level and angular velocity fluctuations after flow rate adjustment; it updates PID parameters through algorithmic learning until the error converges. The closed-loop feedback mechanism consists of a sensor unit, a control unit, an execution unit, and a data processing module. The sensor unit collects tilting data via an encoder, the control unit uses a PLC controller, the execution unit receives signals from a servo motor to drive the tilting mechanism, and the data processing module calculates the preset target flow rate value q. target With actual traffic q (t) The difference e (t) The movement of the device is adjusted by the difference.

[0055] The specific implementation process of the system in this embodiment is as follows: During system initialization, each module starts synchronously, first completing data acquisition and parameter calibration; the tilt parameter acquisition module collects parameters such as the angle and angular velocity of the equipment in real time, and obtains information through sensors such as encoders; the liquid level dynamic modeling system inputs the collected angular velocity and angle data into the mathematical model to calculate the real-time liquid level height information; the flow adaptive control system compares the real-time liquid level height with the preset target flow rate, and calculates the control error through the PID algorithm; the output signal is adjusted according to the error, and the adjustment signal is transmitted to the actuator module to complete the dynamic adjustment of the flow rate; the system continuously corrects the control error under closed-loop feedback to ensure that the pouring flow rate is always stable within the preset range.

[0056] In summary, this embodiment calculates liquid level and flow rate using mechanical motion parameters, avoiding sensor failure due to direct contact with liquid under high temperature and high pressure, thus ensuring stable system operation in harsh environments. The adaptive PID control system works in conjunction with a multi-parameter fusion model, achieving a steady-state error of ≤1% and a faster response speed than traditional PID. It reduces reliance on high-cost sensors, and the modular design supports rapid fault diagnosis and component replacement. The equipment is easy to maintain and use; fully automatic and stable flow rate pouring can be achieved simply by manually inputting a preset target flow rate.

[0057] This embodiment employs a multi-sensor collaborative acquisition of device tilt parameters and calculates the real-time liquid level height using a mathematical model, overcoming the potential environmental influences that can affect direct liquid level measurement. The adaptive adjustment using a combined PID algorithm effectively improves the response speed and accuracy of flow control. Furthermore, the modular system structure facilitates maintenance and expansion, offering high application flexibility and robustness.

[0058] The flow adaptive control system in this embodiment adjusts the tilting angular velocity of the pouring machine by driving a servo motor to control precise pouring; it records liquid level fluctuations and angular velocity data in real time through closed-loop feedback, optimizes and updates PID parameters until the flow error converges to within ±1%.

[0059] Figure 3 A flow control method for a casting machine based on multi-parameter feedback and PID regulation is demonstrated. The specific steps are as follows:

[0060] S1, real-time acquisition of angular velocity and angle data of the ladle;

[0061] S2 uses angular velocity data, angle data, and mathematical modeling of the ladle's geometry to dynamically calculate the liquid level height information in the pouring container;

[0062] S3, calculates the estimated actual flow rate based on the liquid level information, and inputs the difference between the preset flow target value and the real-time flow estimate into the PID controller to generate a tilt adjustment signal;

[0063] S4 drives the high-precision tilting mechanism of the casting machine according to the tilting adjustment signal, which drives the casting machine ladle to tilt to adjust the casting flow rate.

[0064] The above are merely specific embodiments of the present invention, but the design concept of the present invention is not limited thereto. Any non-substantial modifications made to the present invention using this concept shall be considered as infringing upon the protection scope of the present invention.

Claims

1. A flow control system for a casting machine based on multi-parameter feedback and PID dynamic adjustment, characterized in that, It includes a tilt parameter acquisition module, a liquid level dynamic modeling module, a flow adaptive control module, and an actuator module; The tilt parameter acquisition module collects the angular velocity and angle data of the ladle in real time; The liquid surface dynamic modeling module uses angular velocity data, angle data, and mathematical modeling of the ladle's geometry to dynamically calculate the liquid surface height information of the ladle. The adaptive flow control module calculates the estimated actual flow rate based on the liquid level information and inputs the difference between the preset target flow rate and the real-time estimated flow rate into the PID controller to generate a tilt adjustment signal. The actuator module drives a high-precision tilting mechanism based on the tilting adjustment signal, which in turn causes the pouring ladle to tilt to adjust the pouring flow rate.

2. The casting machine flow control system based on multi-parameter feedback and PID dynamic adjustment according to claim 1, characterized in that, The method of dynamically calculating the liquid level height information in the ladle using mathematical modeling based on angular velocity data, angle data, and the geometry of the ladle is as follows: A dynamic model of the liquid level height is constructed using mathematical modeling based on angular velocity, angle data, and the geometry of the ladle, and is expressed as follows: Where h(t) represents the liquid level; ω(t) represents the angular velocity; θ(t) represents the angle θ with t as a parameter; A(θ) represents the effective cross-sectional area of ​​the container at angle θ; V s (θ(t)) represents the reference volume of the container at angle θ; q(t) represents the actual flow rate; t represents time; The change curve of the liquid level is obtained by integrating the dynamic model of the liquid level.

3. The casting machine flow control system based on multi-parameter feedback and PID dynamic adjustment according to claim 1, characterized in that, The calculation of the estimated actual flow rate based on the liquid level information is as follows: The flow rate variation formula is obtained by transforming Bernoulli's equation. Substituting the liquid level information into the flow rate variation formula yields the actual flow rate variation curve; the actual flow rate variation curve is expressed as: Where q(t) represents the estimated actual flow rate; c represents the flow coefficient; L represents the orifice width; g represents the gravitational acceleration; and h(t) represents the liquid level.

4. The casting machine flow control system based on multi-parameter feedback and PID dynamic adjustment according to claim 1, characterized in that, The tilt adjustment signal is represented as follows: Where u(t) represents the tilt adjustment signal; K p K i and K d These represent the proportional, integral, and derivative parameters of the PID controller, respectively; e(t) represents the difference between the preset flow target value and the real-time flow estimate.

5. The casting machine flow control system based on multi-parameter feedback and PID dynamic adjustment according to claim 1, characterized in that, The adaptive flow control module further includes: using a fuzzy logic algorithm to adaptively adjust the proportional parameter K of the PID controller based on the real-time difference between the preset target flow and the actual flow value and its rate of change. p Integral parameter K i and differential parameter K d This enables dynamic optimization of control parameters.

6. The casting machine flow control system based on multi-parameter feedback and PID dynamic adjustment according to claim 1, characterized in that, The high-precision tilting mechanism includes a servo motor, a servo motor support, a tilting shaft, and a bearing support. The servo motor is fixed to the servo motor support. The bearing support has a built-in bearing to support the free rotation of the tilting shaft. The output shaft of the servo motor is rigidly connected to the drive end of the tilting shaft through a reducer. The servo motor support is rigidly connected to the main frame of the casting machine, the bearing support is rigidly connected to the main frame of the casting machine, and the tilting shaft is rigidly connected to the ladle. The rotation of the servo motor drives the tilting shaft to rotate through the reducer, thereby causing the ladle to tilt.

7. The casting machine flow control system based on multi-parameter feedback and PID dynamic adjustment according to claim 6, characterized in that, The angular velocity and angle data of the ladle are collected in real time by several sensors set on the tilting axis.

8. The casting machine flow control system based on multi-parameter feedback and PID dynamic adjustment according to claim 7, characterized in that, The sensor is a photoelectric encoder or magnetic encoder with a resolution of not less than 17 bits and a sampling frequency of not less than 1kHz; the coaxiality error between the sensor's rotation axis and the tilt axis mechanical axis is within 0.05mm.

9. The casting machine flow control system based on multi-parameter feedback and PID dynamic adjustment according to claim 1, characterized in that, The flow adaptive control module also includes a load change prediction model based on historical data; the load change prediction model generates a feedforward compensation signal to input to the high-precision tilting mechanism to offset external disturbances, and activates a steady-state holding mechanism when the flow relative error is less than ±0.5%, thereby reducing the frequent adjustment of the mechanical system.

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