Simulation detection method for testing viscoelasticity of liquid based on intelligent servo motor

Abstract

The invention relates to the technical field of automatic control and liquid viscoelasticity testing, and particularly discloses a simulation detection method for testing liquid viscoelasticity based on an intelligent servo motor, and the method comprises the following steps: presetting a target value of a position; an operation instruction is sent to control the intelligent servo motor to operate; actual operation data are collected, the actual operation data are processed to obtain feedback quantity, and then the feedback quantity is transmitted to the central controller; checking the feedback quantity and a preset target value, and sending out a corresponding control instruction according to a checking error; the operation state is adjusted and corrected through the control instruction; the motion of the intelligent servo motor is monitored in real time, and a position-time curve is generated at the same time; and when the operation state is normal, the target value of the preset position is realized, the cup body circularly reciprocates, and environment simulation required by the liquid is realized. The problems that the structure is complex, the cost is high and a position time curve cannot be set at will due to matching of a gear motor and a cam mechanism can be solved.

Description

Technical Field

[0001] This invention relates to the technical field of automated control and liquid viscoelasticity testing, and specifically discloses a simulation testing method for testing liquid viscoelasticity based on an intelligent servo motor. Background Technology

[0002] In the process of liquid viscoelasticity testing, the cup needs to be made to move in a cyclical manner. Usually, a geared motor and a cam mechanism are used in combination to drive the movement of mechanical parts to achieve the movement of the cup.

[0003] A geared motor is an integrated unit combining a speed reducer and a motor, widely used in industries such as steel and machinery. As the drive source for most equipment, geared motors offer advantages such as high efficiency and reliability, long service life, easy maintenance, and wide applicability. However, in liquid viscoelasticity testing, geared motors have disadvantages including unstable speed, large size, high noise, and low motion accuracy. Furthermore, the cam mechanism specifically designed for viscoelasticity testing is difficult to manufacture, prone to wear, structurally complex, and costly. Most importantly, the position-time curve of the geared motor is determined by the cam mechanism, which cannot be changed once manufactured and cannot be arbitrarily set, thus presenting limitations.

[0004] With societal development, the advantages of servo motors have become increasingly apparent. Servo motors can control speed with extremely high positional accuracy, converting voltage signals into torque and speed to drive the controlled object. The rotor speed of a servo motor is controlled by the input signal and can respond quickly. In automatic control systems, it serves as an actuator and possesses characteristics such as a small electromechanical time constant and high linearity. It can convert received electrical signals into angular displacement or angular velocity output on the motor shaft. This invention provides a novel detection method for liquid viscoelasticity testing based on servo motors. Summary of the Invention

[0005] The present invention aims to provide a simulation detection method for testing the viscoelasticity of liquids based on an intelligent servo motor, in order to solve the problems of complex structure, high cost and inability to arbitrarily set position-time curves caused by the combination of a geared motor and a cam mechanism.

[0006] To achieve the above objectives, the basic solution of the present invention is as follows: A simulation detection method for testing the viscoelasticity of liquid based on an intelligent servo motor, comprising the following steps: S100: Pre-setting a target value for a position; S200: The central controller sends an operation command to the drive circuit, which controls the operation of the intelligent servo motor; S300: The signal conditioning circuit collects the actual operation data of the intelligent servo motor, processes the actual operation data to obtain a feedback quantity, and then transmits the feedback quantity to the central controller; S400: The central controller calibrates the feedback quantity with the preset target value and sends a corresponding control command to the intelligent servo motor according to the calibration error; S500: Adjustments are made through the control command to correct the operating state of the intelligent servo motor; S600: The central controller monitors the movement of the intelligent servo motor in real time and generates a position-time curve; S700: When the operating state of the intelligent servo motor is normal and the preset target value is achieved, the intelligent servo motor drives the cup of the liquid viscoelasticity testing device to perform cyclic reciprocating motion, causing the liquid in the cup to flow, thereby simulating the required environment of the liquid.

[0007] Furthermore, the steps also include: S301: The encoder collects the rotation information of the intelligent servo motor, and obtains the position and speed information of the rotor of the intelligent servo motor through the feedback of the encoder.

[0008] Furthermore, the steps also include: S302: The signal conditioning circuit collects the phase current of the intelligent servo motor, performs a mathematical transformation based on Clark transform on the phase current to obtain the phase current decoupling quantity, and synthesizes the feedback quantity based on the phase current information and the rotor position and speed information.

[0009] Furthermore, the steps also include: S401: Using a PID algorithm to process the feedback phase current information and the rotor position and speed information of the intelligent servo motor fed back by the encoder, thereby completing the processing of the feedback quantity.

[0010] Furthermore, the steps also include: S800: The central controller automatically alarms based on the abnormal operating status that occurs during the operation of the intelligent servo motor.

[0011] Beneficial technical effects:

[0012] 1. The intelligent servo motor runs according to the preset position-time curve, which can simulate various application scenarios.

[0013] 2. Through closed-loop control of current loop, speed loop, and position loop, the intelligent servo motor can be guaranteed to operate steplessly under various working conditions, and abnormal states can be monitored.

[0014] 3. The intelligent servo motor adopts a motion control algorithm to ensure that the intelligent servo motor can run smoothly, and the operating curve of the intelligent servo motor can be set arbitrarily.

[0015] 4. Detection based on intelligent servo motors can make the detection device simple in structure, with fewer parts and lower cost.

[0016] The above description is only used to illustrate the problem to be solved by the present invention, the technical means to solve the problem, and the effects produced, etc. The specific details of the present invention will be described in detail in the following embodiments and related drawings. Attached Figure Description

[0017] To make the above and other objects, features, advantages and embodiments of the present invention more apparent and understandable, the accompanying drawings are described below:

[0018] Figure 1 This is a flowchart of one embodiment of the present invention;

[0019] Figure 2 This is a position-time curve of a servo motor according to an embodiment of the present invention. Detailed Implementation

[0020] The following description, with reference to the accompanying drawings, discloses specific embodiments of the present invention. For clarity, many practical details will be described in conjunction with the following description. However, it should be understood that these practical details are not intended to limit the invention. That is, these practical details are not essential in the embodiments of the present invention. Furthermore, for the sake of simplicity, some conventional structures and elements will be illustrated in the drawings in a simple schematic manner.

[0021] Example 1

[0022] Please see Figure 1 As shown, a simulation testing method for liquid viscoelasticity based on an intelligent servo motor includes the following steps: S100: Pre-setting a target value for the position; S200: The central controller sends an operation command to the drive circuit, which controls the intelligent servo motor to operate; S300: The signal conditioning circuit collects the actual operating data of the intelligent servo motor, processes the actual operating data to obtain a feedback quantity, and then transmits the feedback quantity to the central controller; S400: The central controller calibrates the feedback quantity with the preset target value and sends a corresponding control command to the intelligent servo motor according to the calibration error; S500: Adjustments are made through the control command to correct the operating state of the intelligent servo motor; S600: The central controller monitors the movement of the intelligent servo motor in real time and generates a position-time curve; S700: When the intelligent servo motor operates normally and achieves the preset target value, the intelligent servo motor drives the cup of the liquid viscoelasticity testing device to perform cyclic reciprocating motion, causing the liquid in the cup to flow and simulating the required environment of the liquid.

[0023] The steps also include: S301: The encoder collects the rotation information of the intelligent servo motor, and obtains the position and speed information of the rotor of the intelligent servo motor through the feedback of the encoder.

[0024] The steps also include: S302: The signal conditioning circuit collects the phase current of the intelligent servo motor, performs a mathematical transformation based on Clark transform on the phase current to obtain the phase current decoupling quantity, and synthesizes the feedback quantity based on the phase current information and the rotor position and speed information.

[0025] This embodiment processes phase current information based on Clark transformations. The three-phase stationary coordinates of the Clark transformation represent the currents in the three-phase coils of the intelligent servo motor. Therefore, to facilitate control, the three-phase currents are converted into two-phase stationary coordinates. Specifically, regarding the decoupling of phase currents, this embodiment decouples the phase currents into excitation current and torque current; the decoupling quantities are excitation current and torque current. During this mathematical transformation, the rotor speed of the intelligent servo motor is determined by the magnetomotive force (MOF), and the magnitude and period of the MOF remain constant to ensure that the magnitude and period of the combined MOF from the final three-phase currents and the converted two-phase currents are consistent.

[0026] The steps also include: S401: Using a PID algorithm to process the feedback phase current information and the rotor position and speed information of the intelligent servo motor fed back by the encoder, thereby completing the processing of the feedback quantity.

[0027] The steps also include: S800: The central controller automatically alarms based on abnormal operating conditions that occur during the operation of the intelligent servo motor.

[0028] This embodiment employs FOC control technology, and the intelligent servo motor used is a permanent magnet synchronous motor. FOC control technology can efficiently control the permanent magnet synchronous motor, accurately control the magnitude and direction of the magnetic field, making the intelligent servo motor have stable torque, low noise, high efficiency, and high-speed dynamic response, thereby achieving precise position and speed control.

[0029] The FOC control system includes a controlled object, a controller, an actuator, and a feedback circuit. In this embodiment, the controlled object is an intelligent servo motor, the controller is a central controller (i.e., an MCU microcontroller), the actuator is a drive circuit, and the feedback circuit is a signal conditioning circuit. Under FOC control technology, the intelligent servo motor performs reciprocating cyclic motion to simulate the viscoelastic properties of liquids in different scenarios.

[0030] The central controller is used to preset the target value of the servo motor's movement position and issue the operation command to the drive circuit. After receiving the operation command, the drive circuit can generate pulse signals. The servo motor rotates by the angle corresponding to the received pulse signals, and the servo motor also emits a corresponding number of pulse signals, forming a closed loop with the pulse signals emitted by the drive circuit, thereby precisely controlling the rotation of the intelligent servo motor and achieving precise positioning.

[0031] The signal conditioning circuit acquires the rotor position and speed information of the servo motor through an encoder (in this embodiment, the encoder is a magnetoelectric encoder) installed on the side of the motor shaft. Simultaneously, the signal conditioning circuit can collect the phase current information of the servo motor, and obtain the decoupling quantity after performing a series of mathematical transformations and estimation algorithms on the phase current information. The actual operating data includes at least the phase current information and the rotor position and speed information. The decoupling quantity obtained from processing the actual operating data is the feedback quantity. The central controller dynamically adjusts based on the error between the feedback quantity and the target value, and finally outputs the corresponding current control command to correct the operating state of the servo motor.

[0032] During the operation of the intelligent servo motor, the central controller can monitor various abnormal operating conditions in real time and automatically provide alarms to ensure stable operation and accurate detection results. Abnormal conditions mainly include abnormal current, abnormal load, abnormal speed, abnormal position, motor stall, circuit fault, and communication abnormality.

[0033] In this embodiment, the user only needs to set the start and end positions. Through a motion algorithm, the intelligent servo motor can start and stop smoothly, running according to a pre-set position-time curve. Furthermore, the operating curve of the intelligent servo motor can be arbitrarily preset according to the application scenario, thereby demonstrating the viscoelasticity of liquids under specific environments. For example, Figure 2 The position-time curve simulates the flow of blood during the coagulation process for an intelligent servo motor. The horizontal axis is the time axis, and the vertical axis is the rotation angle of the intelligent servo motor rotor.

[0034] Powered by an intelligent servo motor, the liquid is moved. Intelligent control enables the liquid to achieve the required motion states for detection, facilitating the extraction of liquid parameters (such as liquid viscosity, blood clotting rate, and the strength of blood during and after clotting) from different motion states. This satisfies various testing needs (primarily the simulation of various motion curves; control parameters include rotation direction, rotation angle, rotation speed, and rotation frequency). In this embodiment, the cup is the reaction cup for placing the liquid (i.e., viscoelastic material) in the thromboelastography instrument.

[0035] Example 2

[0036] Based on Embodiment 1, the central controller in this embodiment has a built-in simulation prediction model, which has the following functions:

[0037] The control information of the servo motor is predicted, including the number of control operations, position deviation, and control time. Simultaneously, the actual control information during the control process is recorded, including the number of control operations to reach the target value, the position deviation for each operation, and the control time. Calculations are performed based on the predicted and actual control information, and error stability analysis is conducted.

[0038] The stability analysis process is as follows: if the position deviation is fixed each time, the problem may lie in the position detection; if the problem is over-adjustment or under-adjustment, and the position deviation value is not fixed, the problem may lie in algorithm mismatch. To address the issues identified during this analysis, the model evaluates the current control program to determine if re-matching is necessary. If the evaluation result exceeds a threshold, it indicates a low degree of matching between the current control program and the current device, leading to a significant difference in the final output. Re-matching is required, and a self-learning algorithm can be used to tune the control parameters. This threshold is obtained from a historical database containing historical data collected for the current application scenario. The historical data records the error for each detection and the final detection result. The model calculates and analyzes the detection results of similar samples in the historical data to ultimately obtain a reasonable threshold.

[0039] The above descriptions are merely embodiments of the present invention, and common knowledge such as specific structures and / or characteristics in the solutions are not described in detail here. It should be noted that those skilled in the art can make various modifications and improvements without departing from the principles and functions of the present invention, and these should also be considered within the scope of protection of the present invention. These modifications and improvements will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application shall be determined by the content of its claims, and the specific embodiments described in the specification are used to interpret the content of the claims.

Claims

1. A simulation detection method for testing liquid viscoelasticity based on intelligent servo motor, characterized in that, Includes the following steps: S100: Preset target value for the location; S200: The central controller sends operation commands to the drive circuit, and the drive circuit controls the intelligent servo motor to run. S300: The signal conditioning circuit collects the actual operating data of the intelligent servo motor, processes the actual operating data to obtain feedback, and then transmits the feedback to the central controller. S400: The central controller calibrates the feedback quantity with the preset target value and sends corresponding control commands to the intelligent servo motor according to the calibration error. S500: Adjusts and corrects the operating status of the intelligent servo motor through control commands; S600: The central controller monitors the movement of the intelligent servo motor in real time and generates position-time curves. S700: When the intelligent servo motor is operating normally and achieves the target value of the preset position, the intelligent servo motor drives the cup of the liquid viscoelasticity testing device to perform cyclic reciprocating motion, so that the liquid in the cup flows and realizes the environmental simulation required by the liquid.

2. The method of claim 1, wherein the method is characterized by: The steps also include: S301: The encoder collects the rotation information of the intelligent servo motor, and obtains the position and speed information of the rotor of the intelligent servo motor through the feedback of the encoder.

3. The method of claim 2, wherein the method is characterized by: The steps also include: S302: The signal conditioning circuit collects the phase current of the intelligent servo motor, performs a mathematical transformation based on Clark transform on the phase current to obtain the phase current decoupling quantity, and synthesizes the feedback quantity based on the phase current information and the rotor position and speed information.

4. The simulation detection method for testing the viscoelasticity of liquids based on an intelligent servo motor according to claim 3, characterized in that: The steps also include: S401: using a PID algorithm to process the feedback phase current information and the rotor position and speed information of the intelligent servo motor fed back by the encoder, thereby completing the processing of the feedback quantity.

5. A simulation detection method for testing the viscoelasticity of liquids based on an intelligent servo motor, as described in any one of claims 1-4, characterized in that: The steps also include: S800: The central controller automatically alarms based on the abnormal operating status that occurs during the operation of the intelligent servo motor.

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