A CT tube positive rotation control optimization method based on temperature model prediction

Abstract

The application relates to a CT tube positive rotation control optimization method based on temperature model prediction, and relates to the technical field of motor control; the method comprises the following steps: setting an experimental environment and establishing a temperature prediction model, wherein setting the experimental environment comprises setting a reference environment temperature; dynamically compensating the driving voltage of a positive rotation winding according to model predicted temperature; acquiring an actual temperature value of the positive rotation winding; optimizing the temperature prediction model, and readjusting the driving voltage of the positive rotation winding according to the optimized temperature prediction model. The application has the effect of improving the control precision of CT tube anode rotation.

Description

Technical Field

[0001] This application relates to the technical field of motor control, and in particular to an optimization method for CT tube vortex control based on temperature model prediction. Background Technology

[0002] Before high-power CT tubes are used for exposure, the anode target disk needs to be rotated at a certain speed to prevent damage to the target disk.

[0003] Currently, target disk motors mostly adopt an asynchronous motor design, using a three-phase bridge arm inverter drive. In order to quickly rotate the target disk before exposure, the drive voltage and frequency parameters during the startup process are often carefully designed and adjusted.

[0004] However, this parameter is often most suitable for the initial start-up of the X-ray tube when it is cold. In actual use, as the cyclone starts, runs, and brakes continuously, the temperature of the cyclone winding will rise significantly, affecting the winding resistance. This makes the originally carefully designed parameters unsuitable, causing the cyclone to fail to achieve the target acceleration effect. In subsequent exposures, the stress on the target plate increases, resulting in a reduction in the lifespan of the X-ray tube and poor exposure inspection results. Summary of the Invention

[0005] In order to improve the control accuracy of CT tube anode rotation, this application provides a CT tube anode rotation control optimization method based on temperature model prediction.

[0006] The CT X-ray tube vortex control optimization method based on temperature model prediction provided in this application adopts the following technical solution:

[0007] A method for optimizing the vortex control of a CT X-ray tube based on temperature model prediction includes the following steps:

[0008] Set up the experimental environment and establish a temperature prediction model, wherein setting up the experimental environment includes setting a reference ambient temperature;

[0009] The driving voltage of the anode winding is predicted based on the model to dynamically compensate for temperature.

[0010] Obtain the actual temperature value of the male rotary winding;

[0011] The temperature prediction model is optimized, and the driving voltage of the anode winding is readjusted based on the optimized temperature prediction model.

[0012] By adopting the above technical solution, through the establishment of a temperature prediction model, dynamic compensation of driving voltage, actual temperature feedback and model iterative optimization, stable acceleration of the anode winding under different temperature conditions is achieved, and performance degradation caused by overheating or undercompensation is avoided.

[0013] As a preferred option, a temperature prediction model is established, including the following steps:

[0014] After the anode winding is shut down, the temperature change of the winding over time is monitored in real time, and the temperature-time curve is recorded.

[0015] Piecewise linear fitting is performed on the temperature-time curve, dividing the temperature-time curve into n consecutive time periods, and the slope of the corresponding straight line segment for each time period is obtained.

[0016] By adopting the above technical solution, the complex nonlinear heat dissipation process is simplified into multiple slope parameters by fitting the temperature-time curve in a piecewise linear manner, making the model easy to store and compute in embedded systems and reducing hardware resource requirements.

[0017] Preferably, the formula for calculating the driving voltage of the dynamically compensated anode winding is:

[0018] ;

[0019] in, and These represent the corrected driving voltage and the initial driving voltage, respectively. T is the reference ambient temperature, T' is the predicted temperature value obtained through the temperature prediction model, C is the temperature constant, and β is the driving voltage compensation coefficient.

[0020] By adopting the above technical solution, the mathematical formula for driving voltage compensation was clarified.

[0021] Preferably, after the start-up process of the anode winding ends, the detection results of the maximum current and anode rotation speed during the start-up process are collected. If both the maximum current and anode rotation speed are less than the test results under cold conditions, the value of β is increased; if the maximum current exceeds the test results under cold conditions, the value of β is decreased; otherwise, the current value of β is maintained unchanged.

[0022] By adopting the above technical solution, the driving effect can be enhanced according to the actual situation by adjusting the value of β, or the damage to the vortex caused by excessive current can be prevented.

[0023] Preferably, the actual temperature value of the male winding is obtained, including the following:

[0024] The formula for calculating the temperature of the anode winding is: ;

[0025] Where c is a temperature constant. For reference to ambient temperature, This is the winding temperature conversion factor;

[0026] The calculation formula is: ;

[0027] in, This represents the effective value of the driving voltage per phase of the rotating coil. This represents the effective value of the driving current per phase of the anode. This is the driving frequency of the male-rotating stator. is the inductance per phase of the cyclone equivalent circuit, and S is the slip. For ambient temperature Below, the stator resistance value per phase of the cyclone equivalent circuit; For ambient temperature Below, the rotor resistance value of each phase in the equivalent circuit of the cyclone is given.

[0028] By adopting the above technical solution and utilizing the equivalent circuit model, sensorless temperature monitoring can be achieved.

[0029] Preferably, the optimized temperature prediction model includes the following steps:

[0030] The actual temperature value Tact and the predicted temperature value Tpre obtained through the temperature prediction model at the same time are obtained, and the temperature ratio r is calculated, r = Tact / Tpre;

[0031] Set the temperature ratio range, and set the corresponding slope adjustment coefficient according to the temperature ratio range. A slope adjustment coefficient table will be established.

[0032] The temperature prediction model is corrected based on the established slope adjustment coefficient table.

[0033] By adopting the above technical solution, and through graded correction of the temperature ratio r, over-adjustment can be avoided.

[0034] Preferably, correcting the slope of the temperature prediction model includes the following steps;

[0035] Obtain the winding temperature Ts and the corresponding time ts at the moment of braking and stopping;

[0036] The predicted temperature Tx,pred at a future time tx is calculated using a temperature prediction model.

[0037] After the cyclone starts and enters a steady state, the actual temperature value Tx,actual at time tx is obtained;

[0038] Calculate the temperature ratio r and determine the correction factor by referring to the slope adjustment factor table;

[0039] The slope of the relevant straight line segment from the shutdown time ts to tx is corrected based on the determined correction factor.

[0040] By adopting the above technical solution, the scope and logic of slope correction are limited, ensuring that only the slope related to the error time period is adjusted, while preserving the accuracy of other segments; and by coordinating the correction of multiple slope segments, the continuity of the temperature curve can be maintained.

[0041] In summary, this application includes at least one of the following beneficial technical effects:

[0042] 1. By dynamically adjusting the drive voltage compensation coefficient, the winding resistance changes under different temperature conditions are automatically adapted, so that the cyclone system can maintain consistent starting performance under various working conditions.

[0043] 2. A dynamically adjustable temperature prediction model is adopted, and the prediction accuracy is continuously optimized through a real-time feedback mechanism. This model can adapt to individual differences in different equipment and changes in environmental conditions, significantly improving the accuracy of temperature control. Attached Figure Description

[0044] Figure 1 This is a flowchart illustrating the steps of an embodiment of this application;

[0045] Figure 2 This is a heat dissipation temperature curve of the CT tube anode winding in an embodiment of this application;

[0046] Figure 3 This is an equivalent circuit diagram of each phase of the male spiral winding according to an embodiment of this application;

[0047] Figure 4 This is an optimized startup acceleration process curve diagram in the embodiments of this application;

[0048] Figure 5 This is an optimized heat dissipation temperature curve of the CT tube anode winding in an embodiment of this application. Detailed Implementation

[0049] The following combination Figures 1-5 This application will be described in further detail.

[0050] This application discloses an optimization method for CT tube vortex control based on temperature model prediction.

[0051] Reference Figure 1 A method for optimizing the vortex control of a CT X-ray tube based on temperature model prediction includes the following steps:

[0052] S1: Establish a temperature prediction model;

[0053] S2: Dynamically compensate the driving voltage of the anode winding based on the temperature predicted by the model;

[0054] S3: Iterative optimization of drive voltage compensation coefficient;

[0055] S4: Obtain the actual temperature value of the male winding;

[0056] S5: Iterative optimization of the temperature prediction model.

[0057] Step S1, establish a temperature prediction model, including the following steps:

[0058] S11: Experimental Environment Setup. Select the X-ray tube model and set the operating heat dissipation conditions. The operating heat dissipation environment includes the reference ambient temperature, cooling air velocity, and heat dissipation performance. Furthermore, the X-ray tube model should be widely used, and the operating heat dissipation conditions should closely match the application scenario of the X-ray tube to simulate real-world usage.

[0059] S12: After the anode winding is stopped, monitor the change in winding temperature over time in real time and record the temperature-time curve. The horizontal axis of the temperature-time curve is time t, and the vertical axis is the temperature value T.

[0060] S13: Perform piecewise linear fitting on the temperature-time curve. Since the temperature-time curve is non-linear, direct storage and computation would consume significant chip resources and be inefficient. Therefore, the temperature-time curve is divided into n consecutive time intervals, approximated by straight line segments, and the slope of the temperature change in each segment is recorded. Specifically, t1 is the initial time and the temperature at time t1 is T1, the temperature at time t2 is T2, and so on, with tn being the initial time and the temperature at time tn being Tn. The slope of the straight line segment between t1 and t2 is k1_2, the slope of the straight line segment between t2 and t3 is k2_3, and so on, with the slope of the straight line segment between t(n-1) and tn being k(n-1)_n. The number of time intervals can be set according to the required accuracy. (Reference) Figure 2 The embodiments of this application are illustrated by dividing the temperature-time curve into four time periods.

[0061] S14: Model parameter storage. The slope and corresponding time period parameters are stored in the control chip's memory (such as Flash or EEPROM) for subsequent real-time control calls.

[0062] Step S2, dynamically compensate the driving voltage of the anode winding based on the model-predicted temperature, including the following:

[0063] refer to Figure 3The equivalent circuit of the positive-swivel winding includes a power supply Vphase, multiple resistors, and multiple inductors. The resistors include resistors R1, Rn, R2', and Rm, and the inductors include inductors X1, Xn, X2, and Xm. The voltage output terminal of the power supply Vphase is connected to the negative terminal of the power supply Vphase in sequence through resistors Rn, Xn, Rm, and Xm. The voltage output terminal of the power supply Vphase is also connected to the negative terminal of the power supply Vphase in sequence through resistors R1, X1, X2, and R2'.

[0064] On the stator side, resistor R1 and inductor X1 represent the copper loss and leakage flux effects of the stator windings. On the rotor side, resistor Rn and inductor Xn are used to equivalently reflect the rotor bar resistance and leakage flux, and resistor R2' and inductor X2 are used to equivalently reflect the rotor bar impedance characteristics. Furthermore, resistor Rm and inductor Xm characterize core losses and the energy storage of the main magnetic field. The equivalent rotor resistance in the equivalent circuit is R2' / s, where s is the slip.

[0065] The inductance of an inductor is minimally affected by temperature changes and can be ignored, while the resistance of a resistor is significantly affected by temperature. The formula for the effect of temperature on resistance is:

[0066] ;

[0067] Where T is the reference ambient temperature, T' is the predicted temperature value obtained through the temperature prediction model, R and R' represent the corresponding winding resistance values ​​at temperatures T and T', respectively, and C represents the temperature constant, for example, C is 235 when copper is used as the conductor material.

[0068] Reference Figure 4 In the initial startup phase, s≈1, and the impedance is dominated by the inductive reactance X1+X2', with little impact from changes in resistor value. The drive voltage remains consistent with the initial strategy. In the later stages of operation, s approaches 0, and the rotor's equivalent resistance R2' / s increases significantly. The resistor value becomes the primary influencing factor, and the drive voltage needs to increase along with the resistor value to maintain the drive current and torque. According to Ohm's law, the final corrected drive voltage is:

[0069] ;

[0070] in, and These represent the corrected drive voltage and the initial drive voltage, respectively. β is the drive voltage compensation coefficient to avoid excessively high drive voltage due to overcompensation. The value of β ranges from 0 to 1, and the initial value of β is set to 0.5. In subsequent operation, the value of β will be continuously adjusted through feedback.

[0071] Step S3, iteratively optimize the driving voltage compensation coefficient, including the following:

[0072] After the startup process is completed, the maximum current and anode rotation speed detection results during the startup process are collected. If both the maximum current and anode rotation speed are less than the test results under cold conditions, the value of β is increased to enhance the driving effect. If the maximum current exceeds the test results under cold conditions, the value of β is decreased to prevent excessive current from damaging the anode. Otherwise, the current value of β is maintained.

[0073] S4: Obtain the actual temperature value of the male spiral winding.

[0074] When the anode winding enters steady-state operation, the driving voltage, current, frequency, and slip of the anode winding are obtained, and the actual temperature of the anode winding at this time is calculated.

[0075] The formula for calculating the temperature of the male-side winding is: ;

[0076] Where c is a temperature constant. For reference to ambient temperature, This is the winding temperature conversion factor.

[0077] The calculation formula is: ;

[0078] in, This represents the effective value of the driving voltage per phase of the rotating coil. This represents the effective value of the driving current per phase of the anode. This is the driving frequency of the male-rotating stator. is the inductance per phase of the cyclone equivalent circuit, and S is the slip. For ambient temperature Below, the stator resistance value per phase of the cyclone equivalent circuit; For ambient temperature Below, the rotor resistance value of each phase in the equivalent circuit of the cyclone is given.

[0079] S5: Iterative optimization of the temperature prediction model.

[0080] S51: Set the slope adjustment coefficient.

[0081] Obtain the actual temperature value Tact and the predicted temperature value Tpre at the same time, and calculate the temperature ratio r, r = Tact / Tpre. When r > 1, it indicates that the actual heat dissipation conditions are worse than those in the temperature prediction model, therefore the temperature drop slope in the temperature prediction model needs to be reduced. When r < 1, it indicates that the actual heat dissipation conditions are better than those in the temperature prediction model, therefore the temperature drop slope in the temperature prediction model needs to be increased.

[0082] Set the temperature ratio range, and set the corresponding slope adjustment coefficient according to the temperature ratio range. A slope adjustment coefficient table will be created, for example:

[0083] Temperature ratio range <0.8 0.8-0.9 0.9-1.1 1.1-1.2 >1.2 Slope adjustment coefficient 1.1 1.05 1 0.95 0.9

[0084] The adjustment coefficient table for different X-ray tube models can be customized to suit individual differences.

[0085] S52: Slope correction.

[0086] Obtain the winding temperature Ts and the corresponding time ts at the moment of braking and stopping.

[0087] The predicted temperature Tx,pred at a future time tx is calculated using a temperature prediction model.

[0088] After the cyclone starts and enters a steady state, the actual temperature value Tx,actual at time tx is obtained.

[0089] Calculate the ratio and determine the correction factor by looking up a table.

[0090] The slope of the relevant straight line segment between the shutdown time ts and tx needs to be adjusted.

[0091] refer to Figure 5 For example, if the winding temperature is T2 when the machine stops due to braking, the predicted winding temperature at time t4 can be calculated using the model after a period of time and is T4. In the above process, the actual measured winding temperature at time t4 is 1.15*T4. Therefore, by looking up the table, the slopes k2_3 and k3_4 are both corrected and slowed down to 0.95 times their original values.

[0092] After step S5 is completed, return to step S2 and start the loop. Based on the optimized temperature prediction model, the driving voltage compensation parameters for the startup process are continuously optimized to achieve the best cyclone startup acceleration effect and realize the rolling optimization of the temperature prediction model.

[0093] The implementation principle of the CT tube positive spiral control optimization method based on temperature model prediction in this application embodiment is as follows: a temperature prediction model of the CT tube positive spiral winding is established, and the driving voltage is compensated by the model to optimize the acceleration effect; in the actual operation process, the model parameters and compensation parameters are continuously optimized to achieve better results.

[0094] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A method for optimizing the vortex control of a CT X-ray tube based on temperature model prediction, characterized in that: Includes the following steps: Set up the experimental environment and establish a temperature prediction model, wherein setting up the experimental environment includes setting a reference ambient temperature; The driving voltage of the anode winding is predicted based on the model to dynamically compensate for temperature. Obtain the actual temperature value of the male rotary winding; Optimize the temperature prediction model, and readjust the driving voltage of the anode winding based on the optimized temperature prediction model; establish the temperature prediction model, including the following steps: After the anode winding is shut down, the temperature change of the winding over time is monitored in real time, and the temperature-time curve is recorded. Piecewise linear fitting is performed on the temperature-time curve, dividing the temperature-time curve into n consecutive time periods, and the slope of the corresponding straight line segment for each time period is obtained; The actual temperature value Tact and the predicted temperature value Tpre obtained through the temperature prediction model at the same time are obtained, and the temperature ratio r is calculated, r = Tact / Tpre; Set the temperature ratio range, and set the corresponding slope adjustment coefficient according to the temperature ratio range, and establish a slope adjustment coefficient table; The temperature prediction model is corrected based on the established slope adjustment coefficient table; Correcting the slope of the temperature prediction model includes the following steps: Obtain the winding temperature Ts and the corresponding time ts at the moment of braking and stopping; The predicted temperature Tx,pred at a future time tx is calculated using a temperature prediction model. After the cyclone starts and enters a steady state, the actual temperature value Tx,actual at time tx is obtained; Calculate the temperature ratio r and determine the correction factor by referring to the slope adjustment factor table; The slope of the relevant straight line segment from the shutdown time ts to tx is corrected based on the determined correction factor.

2. The CT X-ray tube vortex control optimization method based on temperature model prediction according to claim 1, characterized in that: The formula for calculating the driving voltage of the dynamically compensated anode winding is as follows: ； in, and These represent the corrected driving voltage and the initial driving voltage, respectively. T is the reference ambient temperature, T' is the predicted temperature value obtained through the temperature prediction model, C is the temperature constant, and β is the driving voltage compensation coefficient.

3. The CT X-ray tube vortex control optimization method based on temperature model prediction according to claim 1, characterized in that: After the start-up process of the anode winding is completed, the detection results of the maximum current and anode rotation speed during the start-up process are collected. If both the maximum current and the anode rotation speed are less than the test results under cold conditions, the value of β is increased; if the maximum current exceeds the test results under cold conditions, the value of β is decreased; otherwise, the current value of β is maintained unchanged.

4. The CT X-ray tube vortex control optimization method based on temperature model prediction according to claim 1, characterized in that: Obtain the actual temperature value of the male winding, including the following: The formula for calculating the temperature of the anode winding is: ; Where c is a temperature constant. For reference to ambient temperature, This is the winding temperature conversion factor; The calculation formula is: ; in, This represents the effective value of the driving voltage per phase of the rotating coil. This represents the effective value of the driving current per phase of the anode. This is the driving frequency of the male-rotating stator. is the inductance per phase of the cyclone equivalent circuit, and S is the slip. For ambient temperature Below, the stator resistance value per phase of the cyclone equivalent circuit; For ambient temperature Below, the rotor resistance value of each phase in the cyclone equivalent circuit.

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