A high-speed impeller rotor modal suppression method, device and equipment

Abstract

The present application relates to the field of system control technology, and discloses a method, device and equipment for modal suppression of a high-speed impeller rotor. The method comprises: filtering a speed isofrequency signal and a speed multiplier signal in a control signal to obtain a target signal; wherein the target signal is used to characterize the sum of a modal component and a bias component; performing adaptive estimation of the modal frequency based on the target signal, the modal component and the bias component to obtain a modal frequency adaptive law, and performing iterative calculation according to the modal frequency adaptive law to obtain a modal frequency estimation value; and performing modal suppression on the control signal according to the modal frequency estimation value. The beneficial effect is that the modal frequency of the rotor system is adaptively estimated, and the control signal is modally suppressed according to the modal frequency estimation value to eliminate the influence of the mode on the control system, improve the adaptability to the modal frequency change, and improve the modal suppression effect on the high-speed impeller rotor.

Description

Technical Field

[0001] The present application relates to the field of system control technology, and in particular to a method, device and equipment for modal suppression of a high-speed impeller rotor. Background Art

[0002] Mode is the inherent vibration property of mechanical structure. When working at the modal frequency, the mechanical structure will produce a large resonance phenomenon, causing damage to the mechanical structure. In the control system, the modal vibration of the rotor system will be reflected in the feedback signal. If the controller parameters are not designed properly, the control signal output by the controller will contain modal components, causing resonance in the rotor system, resulting in power amplifier saturation, insufficient response or insufficient control in the control system, which greatly affects the stability of the control system.

[0003] The related technology usually utilizes a notch filter to filter the modal components in the control signal to perform modal suppression, but the modal suppression effect when the modal frequency changes needs to be improved. Summary of the invention

[0004] The present application provides a high-speed impeller rotor modal suppression method, device and equipment, which solves the technical problem in the related art that it is difficult to estimate the modal frequency, resulting in an unsatisfactory modal suppression effect. The modal frequency of the rotor system is adaptively estimated, and the control signal is modally suppressed according to the modal frequency estimation value to eliminate the influence of the mode on the control system, thereby achieving the technical effect of improving the adaptability to the modal frequency change and improving the modal suppression effect on the high-speed impeller rotor.

[0005] In order to achieve the above objectives, the main technical solutions adopted in this application include:

[0006] In a first aspect, an embodiment of the present application provides a high-speed impeller rotor modal suppression method, the method comprising:

[0007] Filtering the speed isochronous frequency signal and the speed multiplication frequency signal in the control signal to obtain a target signal; wherein the target signal is used to characterize the sum of the modal component and the bias component;

[0008] Performing adaptive estimation of modal frequency based on the target signal, the modal component and the bias component to obtain a modal frequency adaptive law, and performing iterative calculation according to the modal frequency adaptive law to obtain a modal frequency estimation value;

[0009] The control signal is modally suppressed according to the modal frequency estimation value.

[0010] The high-speed impeller rotor modal suppression method proposed in the embodiment of the present application performs adaptive estimation of the modal frequency according to the target signal, the modal component and the bias component, and determines the modal frequency estimation value close to the true value of the modal frequency through iterative calculation to determine the modal component contained in the control signal, thereby performing modal suppression on the rotor system and eliminating the influence of the modal on the control system. Compared with the related art that uses notch filters with different center frequencies for modal suppression, the present method can adaptively estimate the modal frequency according to the control signal and output the modal frequency estimation value in real time, thereby performing targeted modal suppression according to the modal frequency estimation value, improving the adaptability to the modal frequency change and effectively reducing the influence of the modal on the control system. In addition, the present method also uses the bias component in the control signal in the adaptive estimation of the modal frequency, reduces the interference of the bias component on the adaptive estimation of the modal frequency, improves the accuracy of the modal frequency estimation value, and improves the modal suppression effect on the rotor system.

[0011] Optionally, the performing adaptive estimation of modal frequency based on the target signal, the modal component and the bias component includes:

[0012] determining an estimate of the modal component, an estimate of the bias component, and an orthogonal value of the estimate of the modal component;

[0013] Calculating an error between the target signal and an estimated value of the modal component and an estimated value of the bias component;

[0014] Modal frequency adaptive estimation is performed based on the error and the orthogonal value of the estimated value of the modal component.

[0015] Optionally, the performing adaptive estimation of modal frequency according to the error and the orthogonal value of the estimated value of the modal component includes:

[0016] Based on the minimum mean square error principle, determining a cost function according to the error;

[0017] Using the steepest descent method, a component gradient function is obtained by derivation according to the cost function;

[0018] Substituting the component gradient function into the expression of the modal frequency to obtain the modal frequency gradient function;

[0019] The modal frequency adaptation law is determined based on the component gradient functions and the modal frequency gradient function.

[0020] Optionally, the modal frequency adaptation law is expressed according to the following formula:

[0021]

[0022] in, represents the estimated value of the modal component, A derivative representing an estimate of the modal component; represents the orthogonal values ​​of the estimated values ​​of the modal components, represents the derivative of the orthogonal value; represents the estimated value of the bias component, A derivative representing an estimate of the bias component; is the estimated value of the modal frequency, a derivative representing an estimate of the modal frequency; indicating the target signal; is the convergence factor,

[0023]

[0024] in, and is the convergence coefficient.

[0025] Optionally, the cost function is expressed according to the following formula:

[0026] .

[0027] Optionally, substituting the component gradient function into an expression of the modal frequency to obtain the modal frequency gradient function comprises:

[0028] According to the convergence form of the third-order generalized integrator, the expression of the modal frequency is obtained;

[0029] Substituting the component gradient function into an expression of the modal frequency to obtain a frequency error between the modal frequency and an estimated value of the modal frequency;

[0030] The frequency error is controlled by using an integral control formula to obtain the modal frequency gradient function.

[0031] Optionally, performing iterative calculation according to the modal frequency adaptive law to obtain the modal frequency estimation value includes:

[0032] Iteratively calculating the estimated value of the modal component, the estimated value of the bias component, and the orthogonal value of the estimated value of the modal component according to the component gradient function;

[0033] The modal frequency estimate is determined based on the modal frequency gradient function according to the estimate of the modal component, the estimate of the bias component, and an orthogonal value of the estimate of the modal component.

[0034] Optionally, performing modal suppression on the control signal according to the modal frequency estimation value includes:

[0035] Performing modal suppression on a control signal in a first direction according to an estimated value of the modal component; wherein the first direction is a direction corresponding to the modal component;

[0036] Modal suppression is performed on the control signal in the second direction according to the orthogonal value of the estimated value of the modal component; wherein the second direction is orthogonal to the first direction.

[0037] In a second aspect, an embodiment of the present application provides a high-speed impeller rotor modal suppression device, the device comprising:

[0038] A frequency conversion signal filtering module is used to filter the speed same frequency signal and the speed multiplication frequency signal in the control signal to obtain a target signal; wherein the target signal is used to characterize the sum of the modal component and the bias component;

[0039] A modal frequency calculation module, configured to perform adaptive estimation of the modal frequency based on the target signal, the modal component and the bias component to obtain a modal frequency adaptive law, and perform iterative calculation according to the modal frequency adaptive law to obtain a modal frequency estimation value;

[0040] A modal signal suppression module is used to perform modal suppression on the control signal according to the modal frequency estimation value.

[0041] In a third aspect, an embodiment of the present application provides a computer device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, computer instructions are stored in the memory, and the processor executes the method described in any one of the above embodiments by executing the computer instructions.

[0042] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which computer instructions are stored, and the computer instructions are used to enable a computer to execute any one of the methods in the above embodiments.

[0043] In a fifth aspect, an embodiment of the present application provides a computer program product, including computer instructions, and the computer instructions are used to enable a computer to execute any one of the methods in the above embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the specific implementation methods of the present application or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0045] Figure 1 A step diagram of a high-speed impeller rotor modal suppression method provided in an embodiment of the present application;

[0046] Figure 2 This is a structural block diagram of a notch filter in an embodiment of the present application;

[0047] Figure 3a A convergence comparison diagram of the frequency estimation of the control signal without bias component by the present method and related technologies;

[0048] Figure 3b A convergence comparison diagram of the frequency estimation of the control signal with bias component by the present method and related technologies;

[0049] Figure 4 A diagram showing the steps of performing adaptive estimation of modal frequency in an embodiment of the present application;

[0050] Figure 5 A diagram showing the steps of determining a modal frequency adaptive law in an embodiment of the present application;

[0051] Figure 6 A diagram showing the steps of obtaining a modal frequency gradient function in an embodiment of the present application;

[0052] Figure 7 A diagram showing steps for iteratively calculating each component and modal frequency in an embodiment of the present application;

[0053] Figure 8 This is a structural block diagram of the modal frequency adaptive law in an embodiment of the present application;

[0054] Fig. 9 A diagram showing steps for suppressing modal components in an embodiment of the present application;

[0055] Fig.10 This is a structural block diagram of a control system in an embodiment of the present application;

[0056] Fig.11a is a schematic diagram of a rotor displacement signal when the method is not used in an embodiment of the present application;

[0057] Fig.11b This is a schematic diagram of a rotor displacement signal when the method is used in an embodiment of the present application;

[0058] Fig.11c This is a schematic diagram of FFT of the rotor displacement signal in the BX direction in an embodiment of the present application;

[0059] Fig.12 A module diagram of a high-speed impeller rotor modal suppression system provided in an embodiment of the present application;

[0060] Fig.13A schematic diagram of the structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0062] Mode is the inherent vibration property of mechanical structure. When working at the modal frequency, the mechanical structure will produce a large resonance phenomenon, causing damage to the mechanical structure and damage to the connected equipment. In the control system, the modal vibration of the rotor system will be reflected in the feedback signal. When the mode of the rotor system is excited, the controller will output a high-frequency current with the same modal frequency, causing the power amplifier to enter the power amplifier saturation state, resulting in a decrease in the control effect of the rotor system, which greatly affects the stability of the control system.

[0063] At present, in the related technology, a plurality of notch filters with different center frequencies are usually set in the control system, and the center frequencies of the notch filters correspond to different modal frequencies, so as to use the notch filters to perform modal suppression on the control system. When the above scheme is used for modal suppression, it is necessary to obtain the modal frequency by frequently increasing and decreasing the speed during the operation of the rotor system, so as to use the notch filter with the corresponding center frequency to change the amplitude-frequency characteristics of the control signal, eliminate the excitation signal at the modal frequency in the control signal, and realize the modal suppression of the rotor system.

[0064] However, during the speed increase process of the rotor system, the modal frequency will change as the speed increases, and modal frequencies other than the frequency corresponding to the notch filter may appear. In addition, after the rotor system has been running for a long time, the stiffness and damping at the disk-shaft connection will also change, causing the modal frequency of the rotor system to change further. The above-mentioned related technologies have low adaptability to the changing modal frequencies.

[0065] Based on the above problems, the present application provides a high-speed impeller rotor modal suppression method, device and equipment, the method comprising: filtering the speed isofrequency signal and the speed multiplier signal in the control signal to obtain a target signal; wherein the target signal is used to characterize the sum of the modal component and the bias component; performing modal frequency adaptive estimation based on the target signal, the modal component and the bias component to obtain the modal frequency adaptive law, and performing iterative calculation according to the modal frequency adaptive law to obtain the modal frequency estimation value; performing modal suppression on the control signal according to the modal frequency estimation value.

[0066] The high-speed impeller rotor modal suppression method provided in this embodiment adaptively estimates the modal frequency based on the target signal, modal components and bias components, and determines the modal frequency estimate value close to the true value of the modal frequency through iterative calculation to determine the modal component contained in the control signal, thereby performing modal suppression on the rotor system and eliminating the influence of the mode on the control system.

[0067] Compared with the related art that uses notch filters with different center frequencies to perform modal suppression, the present method can adaptively estimate the modal frequency according to the control signal and output the modal frequency estimation value in real time, thereby performing targeted modal suppression based on the modal frequency estimation value, improving the adaptability to modal frequency changes and effectively reducing the impact of the mode on the control system.

[0068] In addition, this method also utilizes the bias component in the control signal in the modal frequency adaptive estimation, reduces the interference of the bias component on the modal frequency adaptive estimation, improves the accuracy of the modal frequency estimation value, and improves the modal suppression effect on the rotor system.

[0069] The high-speed impeller rotor modal suppression method provided in this specification can be applied to the control system for modal suppression, and the control system may include a controller, a power amplifier and a controlled system, and the controlled system may be a specific type of mechanical structure, including a magnetically suspended centrifugal compressor or other mechanical structures with high-speed impeller rotors. It is understandable that after adaptive modification, this method can also be applied to control other types of mechanical structures.

[0070] According to an embodiment of the present application, an embodiment of a high-speed impeller rotor modal suppression method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0071] In this embodiment, a high-speed impeller rotor modal suppression method is provided, which can be used in the above-mentioned control system. Figure 1 As shown, the method includes:

[0072] S100. Filter the rotation speed iso-frequency signal and the rotation speed multiplier frequency signal in the control signal to obtain a target signal; wherein the target signal is used to characterize the sum of the modal component and the bias component.

[0073] S200. Perform adaptive estimation of the modal frequency based on the target signal, the modal component and the bias component to obtain a modal frequency adaptive law, and perform iterative calculation according to the modal frequency adaptive law to obtain a modal frequency estimation value.

[0074] S300. Perform modal suppression on the control signal according to the modal frequency estimation value.

[0075] Specifically, the control signal can be a signal output by the controller in the control system after receiving the feedback signal of the rotor system, comparing the feedback signal with the expected signal, and iteratively calculating the output signal, which is used to control the rotor system. The control signal includes a speed frequency signal and a speed frequency multiplication signal, wherein the speed frequency signal is the same as the frequency of the rotor system, and the frequency of the speed frequency multiplication signal is an integer multiple of the frequency of the rotor system, such as a vibration signal with a frequency twice the angular frequency of the controlled motor. The speed frequency signal and the speed frequency multiplication signal will affect the estimation of the modal frequency, so it is necessary to remove the speed frequency signal and the speed frequency multiplication signal from the control signal to obtain a target signal containing only the modal component and the bias component in the control signal, so that the modal component, the bias component and the modal frequency can be estimated according to the target signal.

[0076] Furthermore, in this embodiment, the control signal is filtered by a notch filter to remove the speed same frequency signal and the speed double frequency signal. The notch filter is a band stop filter that can quickly attenuate the input signal at a certain frequency point to achieve a filtering effect that blocks the frequency signal from passing through. Figure 2 , Figure 2 The structural block diagram of the notch filter in the embodiment of the present application is shown in the figure. Represents the input control signal, The frequency of the rotor system times, Represents the output target signal. After filtering the control signal through the notch filter, the target signal obtained contains only the modal component, bias component and noise. At this time, the target signal can be considered as a simple harmonic vibration and can be expressed by the following formula:

[0077]

[0078] in, Indicates target signal; is the bias component; is the amplitude of the modal component; is the modal frequency; is the phase angle of the modal component. Target signal is a known quantity, and the bias component , the amplitude of the modal component , modal frequency and the phase angle of the modal components Is an unknown quantity.

[0079] Furthermore, the modal frequency is adaptively estimated based on the target signal, the modal component and the bias component to obtain the modal frequency adaptive law. The modal frequency adaptive law includes a component adaptive law and a frequency adaptive law, wherein the component adaptive law includes a component gradient function for iteratively calculating the modal component and the bias component to determine the estimated value of the modal component and the estimated value of the bias component; the frequency adaptive law is obtained based on the modal component and the bias component, and includes a modal frequency gradient function for calculating the modal frequency to determine the estimated value of the modal frequency.

[0080] It should be noted that the modal frequency adaptive law obtained by this method also uses the bias component in the control signal in the iterative calculation process, and iterative calculation is performed through the component adaptive law to determine the estimated value of the bias component, so that the bias component can be removed in the modal frequency estimation, and the influence of the bias component on the modal frequency adaptive estimation is reduced. Compared with the related art that only uses the modal component for modal frequency estimation, this method takes into account the interference of the bias component on the modal frequency estimation, and iterative calculation is performed according to the modal frequency adaptive law to obtain the estimated value of the bias component, so that when calculating the estimated value of the modal component, the accuracy of the error between the estimated value and the true value can be improved, and the actual signal characteristics of the modal component can be better reflected, thereby improving the accuracy of the obtained modal component estimate and the modal frequency estimate, and improving the effect of modal suppression.

[0081] The difference between this method and the related art is illustrated by way of example. Figure 3a For a control signal with a frequency of 1200 Hz without bias component, the initial value of the modal frequency estimation value is set to 800 Hz, and the modal frequency of the control signal is adaptively estimated using this method and related technologies. Figure 3a As shown in Figure 2, in this case, this method and related technologies can obtain modal frequency estimates close to the true value at around 0.6s. Figure 3b For a control signal with a bias component and a frequency of 1200 Hz, the initial value of the modal frequency estimation value is also set to 800 Hz, and the modal frequency of the control signal is adaptively estimated using this method and related technologies. Figure 3a As shown in the figure, in this case, the method can still obtain a modal frequency estimation value close to the true value at about 0.6s, while in the related art, due to the interference of the bias component, the result obtained is 0Hz and cannot converge to the true value of the modal frequency. By comparison, it can be seen that the method is still effective in adaptively estimating the modal frequency of the control signal with a bias component, ensuring the effect of modal suppression.

[0082] Furthermore, after determining the estimated value of the modal component and the estimated value of the bias component, the modal frequency estimated value is determined by the frequency adaptive law. The mode in the control signal can be determined according to the estimated value of the modal component and the estimated value of the modal frequency, so as to perform targeted modal suppression.

[0083] The high-speed impeller rotor modal suppression method provided in this embodiment performs adaptive estimation of the modal frequency according to the target signal, the modal component and the bias component, and determines the modal frequency estimation value close to the true value of the modal frequency through iterative calculation to determine the modal component contained in the control signal, thereby performing modal suppression on the rotor system and eliminating the influence of the modal on the control system. Compared with the related art that uses notch filters with different center frequencies to perform modal suppression, the present method can adaptively estimate the modal frequency according to the control signal and output the modal frequency estimation value in real time, thereby performing targeted modal suppression according to the modal frequency estimation value, improving the adaptability to the modal frequency change and effectively reducing the influence of the modal on the control system. In addition, the present method also uses the bias component in the control signal in the adaptive estimation of the modal frequency, reduces the interference of the bias component on the adaptive estimation of the modal frequency, improves the accuracy of the modal frequency estimation value, and improves the modal suppression effect on the rotor system.

[0084] Reference Figure 4 As shown, as an embodiment of the present application, adaptive estimation of modal frequency is performed based on the target signal, the modal component and the bias component, including:

[0085] S210. Determine an estimated value of a modal component, an estimated value of a bias component, and an orthogonal value of the estimated value of the modal component.

[0086] S220. Calculate the error between the target signal and the estimated value of the modal component and the estimated value of the bias component.

[0087] S230. Perform adaptive estimation of modal frequencies according to the errors and the orthogonal values ​​of the estimated values ​​of the modal components.

[0088] Specifically, the estimated value of the modal component, the estimated value of the bias component, and the orthogonal value of the estimated value of the modal component are determined, wherein the estimated value of the modal component represents the estimated form of the modal component; the orthogonal value of the estimated value of the modal component has the same amplitude as the estimated value of the modal component, but a phase difference of 90 degrees; the estimated value of the bias component represents the estimated form of the bias component. The estimated value of the modal component, the estimated value of the bias component, and the orthogonal value of the estimated value of the modal component are respectively expressed according to the following formulas:

[0089]

[0090] in, represents the estimated value of the modal component, represents the orthogonal values ​​of the estimated values ​​of the modal components, represents the estimated value of the bias component; and is the amplitude of the modal component; is the amplitude of the bias component; is the modal frequency.

[0091] Understandably, and are the estimated values ​​of the modal components of the rotor system in two directions. The two will not appear in the same direction. When the error between the target signal and the estimated value of the modal component and the estimated value of the bias component is calculated in the same first direction, the error can be expressed according to the following formula:

[0092]

[0093] in, Represents the error between the target signal and the estimated value of the modal component and the estimated value of the bias component. According to the above error, iterative calculation can be performed to update the estimated value of the modal component, the estimated value of the bias component and the orthogonal value of the estimated value of the modal component, so that the above estimated value is closer to the corresponding true value, and the modal frequency estimate is determined according to the estimation result, thereby realizing the adaptive estimation of the modal frequency.

[0094] Reference Figure 5 As shown, as an embodiment of the present application, adaptive estimation of modal frequency is performed according to the orthogonal value of the error and the estimated value of the modal component, including:

[0095] S240. Based on the minimum mean square error principle, determine the cost function according to the error.

[0096] S250. Using the steepest descent method, a component gradient function is obtained by taking the derivative according to the cost function.

[0097] S260. Substitute the component gradient function into the expression of the modal frequency to obtain the modal frequency gradient function.

[0098] S270. Determine a modal frequency adaptation law based on the component gradient function and the modal frequency gradient function.

[0099] As an embodiment of the present application, the modal frequency adaptation law is expressed according to the following formula:

[0100]

[0101] in, represents the estimated value of the modal component, represents the derivative of the estimated value of the modal component; represents the orthogonal values ​​of the estimated values ​​of the modal components, Derivatives representing orthogonal values; represents the estimated value of the bias component, represents the derivative of the estimate of the bias component; is the estimated value of the modal frequency, The derivative represents the estimate of the modal frequency; Indicates target signal; is the convergence factor,

[0102]

[0103] in, and is the convergence coefficient.

[0104] As an embodiment of the present application, the cost function is expressed according to the following formula:

[0105] .

[0106] Specifically, the minimum mean square error principle refers to the use of the minimum mean square error algorithm to minimize the mean square error between the estimated value and the true value. According to the minimum mean square error principle, the cost function for the modal component and the bias component is determined. It is understandable that the cost function is with in the same first direction; when In the same second direction, the cost function The formula does not change. When the first direction is adopted The formula is expressed according to the following formula:

[0107] .

[0108] Furthermore, the steepest descent method is used to obtain the component gradient function by taking the derivative of the cost function. First, the partial derivative of the cost function is taken to obtain the amplitude gradient function, which can be expressed according to the following formula:

[0109]

[0110] Secondly, the estimated values ​​of the modal component, the estimated values ​​of the bias component, and the orthogonal values ​​of the estimated values ​​of the modal component are calculated with respect to The derivative of can be expressed according to the following formula:

[0111]

[0112] Substituting the amplitude gradient function into the above formula, we can get the component gradient function, which is expressed according to the following formula:

[0113]

[0114] The component gradient function can be used to determine the relationship between the estimated value of the modal component, the estimated value of the bias component and the orthogonal value of the estimated value of the modal component and the corresponding gradient. Iterative calculation is performed according to the component gradient function, and the estimated value of the modal component, the estimated value of the bias component and the orthogonal value of the estimated value of the modal component are updated in each iteration round to approximate their respective true values.

[0115] Furthermore, when the modal frequency finally converges to the true value, the estimated value of the modal component, the estimated value of the bias component, and the orthogonal value of the estimated value of the modal component also converge to a certain form, and the expression of the modal frequency can be determined by the convergence form of the estimated value of the modal component and the orthogonal value of the estimated value of the modal component. Substituting the component gradient function into the expression of the modal frequency, the modal frequency gradient function can be obtained, and its form is expressed according to the following formula:

[0116]

[0117] in, is the convergence factor, which is expressed according to the following formula:

[0118]

[0119] in, and is the convergence coefficient, which jointly determines the size of the convergence factor to control the convergence speed of the modal frequency adaptive estimation. and The size of can be determined empirically.

[0120] Reference Figure 6 As shown, as an embodiment of the present application, the component gradient function is substituted into the expression of the modal frequency to obtain the modal frequency gradient function, including:

[0121] S262. Based on the convergence form of the third-order generalized integrator, the expression of the modal frequency is obtained.

[0122] S264. Substitute the component gradient function into the expression of the modal frequency to obtain the frequency error between the modal frequency and the estimated value of the modal frequency.

[0123] S266. Use the integral control formula to control the frequency error and obtain the modal frequency gradient function.

[0124] Specifically, the converged form of the third-order generalized integrator represents the output of the third-order generalized integrator when the modal frequency converges to the true value, which is used to represent the true form of the modal component, the orthogonal value of the modal component, and the bias component. The converged form of the third-order generalized integrator is expressed according to the following formula:

[0125]

[0126] According to the above formula, the expression of modal frequency can be obtained, and its form is expressed according to the following formula:

[0127]

[0128] in, Represents the true value of the modal frequency.

[0129] Furthermore, by substituting the component gradient function into the expression of the modal frequency for transformation, the frequency error between the modal frequency and the estimated value of the modal frequency can be obtained. The form of the frequency error is expressed according to the following formula:

[0130]

[0131] in, is the estimated value of the modal frequency. The frequency error represents the estimated error of the modal frequency. By controlling the frequency error, the error between the estimated value and the true value of the modal frequency is reduced, thereby determining the estimated value of the modal frequency closest to the true value.

[0132] Furthermore, the frequency error is controlled by an integral control formula, and the integral control formula is expressed according to the following formula:

[0133]

[0134] in, is a complex frequency variable, is the convergence coefficient, The frequency error is controlled according to the integral control formula to obtain the modal frequency gradient function, which is expressed according to the following formula:

[0135]

[0136] Because it is known The size of is always greater than zero, and the part about the convergence coefficient in the above formula can be extracted as the convergence factor , to simplify the modal frequency gradient function.

[0137] Reference Figure 7 As shown, as an embodiment of the present application, iterative calculation is performed according to the modal frequency adaptive law to obtain the modal frequency estimation value, including:

[0138] S280. Perform iterative calculations on the estimated value of the modal component, the estimated value of the bias component, and the orthogonal value of the estimated value of the modal component according to the component gradient function.

[0139] S290. Based on the modal frequency gradient function, determine the modal frequency estimate according to the estimated value of the modal component, the estimated value of the bias component, and the orthogonal value of the estimated value of the modal component.

[0140] Specifically, the relationship between the estimated value of the modal component and the corresponding gradient can be determined through the component gradient function, so that the estimated value of the modal component is updated through the iterative formula, so that the estimated value of the modal component gradually approaches the true value of the modal component, and the optimal estimated value of the modal component is obtained. Similarly, the estimated value of the bias component is iteratively updated to obtain the optimal estimated value of the bias component; the orthogonal value of the estimated value of the modal component is iteratively updated to obtain the optimal orthogonal value.

[0141] Furthermore, before the iterative calculation, initial values ​​may be set for the estimated values ​​of the modal components, the estimated values ​​of the bias components, and the orthogonal values ​​of the estimated values ​​of the modal components. Figure 8 , Figure 8 The structure block diagram of the modal frequency adaptive law in the embodiment of the present application is shown in the figure. According to the input target signal ,based on , and The initial value of the component gradient function , and Calculate and As The gradient change will As The gradient changes and As The gradient change of the modal component , the estimated value of the bias component and the orthogonal values ​​of the estimates of the modal components Update for the next iteration.

[0142] In some embodiments, before entering the next iteration round, the error is calculated using the formula of the cost function according to the target signal and the estimated value of the current modal component and the estimated value of the bias component. If the error is outside the preset error range, it is considered that the error between the current estimated value and the true value is large, and it is necessary to continue the iterative calculation; if the error is within the preset error range, it is considered that the current estimated value is close enough to the true value, and the estimated value is output to the control system for modal suppression. It can be understood that if the error remains the same in multiple iteration rounds, and the number of iteration rounds in which the error remains the same exceeds the preset number of times, it is considered that the current estimated value has converged and reached a stable state. At this time, the iteration can be stopped, and the estimated value is output to the control system for modal suppression.

[0143] Reference Fig. 9 As shown, as an embodiment of the present application, modal suppression is performed on the control signal according to the modal frequency estimation value, including:

[0144] S310. Perform modal suppression on the control signal in a first direction according to the estimated value of the modal component; wherein the first direction is the direction corresponding to the estimated value of the modal component.

[0145] S320. Perform modal suppression on the control signal in the second direction according to the orthogonal value of the estimated value of the modal component; wherein the second direction is orthogonal to the first direction.

[0146] Specifically, because the estimated value of the modal component and the orthogonal value of the estimated value of the modal component correspond to control signals in different directions respectively, the control signal in the first direction can be modally suppressed by the estimated value of the modal component, and the control signal in the second direction can be modally suppressed by the orthogonal value of the estimated value of the modal component.

[0147] Reference Fig.10 , Fig.10 The structural block diagram of the control system in the embodiment of the present application is shown in the figure. Indicates the expected signal, represents the feedback signal of the rotor system in the first direction, Represents the feedback signal of the rotor system in the second direction. The controller outputs a control signal according to the expected signal. After being filtered by the notch filter, the control signal is input into the modal frequency adaptive law and the modal frequency estimation value is output through iterative calculation. . Based on the estimated value of the modal frequency The center frequency of the notch filter in the first direction is adjusted so that the notch filter can remove the modal component in the control signal in the first direction, thereby achieving modal suppression. The center frequency of the notch filter in the second direction is adjusted so that the notch filter can remove the modal component in the control signal in the second direction, thereby achieving modal suppression.

[0148] This method is applied to a practical scenario, in which the rotor system is a magnetically suspended rotor system with a rotor speed of 85000 r / min. Figures 11a to 11c ,like Fig.11a As shown in Figure 2, when this method is not used, the maximum peak-to-peak value of the rotor displacement vibration exceeds 0.04 mm; Fig.11b As shown in the figure, after adopting this method, the maximum peak value of the rotor displacement vibration is less than 0.02mm, and the overall amplitude is reduced by half compared with that before adopting this method. Taking the rotor displacement signal in the BX direction as an example, Fig.11c As shown in the figure, before the use of this method, there is a modal component with a frequency of 1232 Hz in the FFT curve of the rotor displacement in the BX direction, and its amplitude is -19.3 dB. And due to the existence of the modal component, the power amplifier is close to saturation, and the amplitude of the mid-frequency signal is relatively high. After the use of this method, only the speed same frequency signal and the speed multiplier signal are retained in the FFT curve, and the amplitude of the mid-frequency signal is also reduced to below -50 dB, which significantly suppresses the modal component.

[0149] Accordingly, please refer to Fig.12 , an embodiment of the present application provides a high-speed impeller rotor modal suppression device, the device comprising:

[0150] The frequency conversion signal filtering module 100 is used to filter the rotation speed same frequency signal and the rotation speed double frequency signal in the control signal to obtain a target signal; wherein the target signal is used to characterize the sum of the modal component and the bias component.

[0151] The modal frequency calculation module 200 is used to perform modal frequency adaptive estimation based on the target signal, modal components and bias components to obtain a modal frequency adaptive law, and perform iterative calculation according to the modal frequency adaptive law to obtain a modal frequency estimation value.

[0152] The modal signal suppression module 300 is used to perform modal suppression on the control signal according to the modal frequency estimation value.

[0153] In some optional implementations, the modal frequency calculation module 200 includes:

[0154] The component estimation unit is used to determine the estimated value of the modal component, the estimated value of the bias component and the orthogonal value of the estimated value of the modal component.

[0155] The error calculation unit is used to calculate the error between the target signal and the estimated value of the modal component and the estimated value of the bias component.

[0156] The modal frequency estimation unit is used to perform adaptive estimation of the modal frequency according to the error and the orthogonal value of the estimated value of the modal component.

[0157] In some optional implementations, the modal frequency calculation module 200 further includes:

[0158] The cost function determination unit is used to determine the cost function according to the error based on the minimum mean square error principle.

[0159] The component gradient unit is used to obtain the component gradient function by derivation according to the cost function using the steepest descent method.

[0160] The modal frequency gradient unit is used to substitute the component gradient function into the expression of the modal frequency to obtain the modal frequency gradient function.

[0161] The adaptive law determination unit is used to determine the modal frequency adaptive law based on the component gradient function and the modal frequency gradient function.

[0162] In some optional implementations, the modal frequency adaptation law is expressed according to the following formula:

[0163]

[0164] in, represents the estimated value of the modal component, represents the derivative of the estimated value of the modal component; represents the orthogonal values ​​of the estimated values ​​of the modal components, Derivatives representing orthogonal values; represents the estimated value of the bias component, represents the derivative of the estimate of the bias component; is the estimated value of the modal frequency, The derivative represents the estimate of the modal frequency; Indicates target signal; is the convergence factor,

[0165]

[0166] in, and is the convergence coefficient.

[0167] In some optional implementations, the cost function is expressed according to the following formula:

[0168] .

[0169] In some optional embodiments, the frequency gradient unit includes:

[0170] The modal frequency expression subunit is used to obtain the expression of the modal frequency according to the convergence form of the third-order generalized integrator.

[0171] The frequency error calculation subunit is used to substitute the component gradient function into the expression of the modal frequency to obtain the frequency error between the modal frequency and the estimated value of the modal frequency.

[0172] The error control subunit is used to perform error control on the frequency error by using an integral control formula to obtain a modal frequency gradient function.

[0173] In some optional implementations, the modal frequency calculation module 200 further includes:

[0174] The component iterative calculation unit is used to iteratively calculate the estimated value of the modal component, the estimated value of the bias component and the orthogonal value of the estimated value of the modal component according to the component gradient function.

[0175] The modal frequency iteration calculation unit is used to determine the modal frequency estimate value based on the modal frequency gradient function according to the estimated value of the modal component, the estimated value of the bias component and the orthogonal value of the estimated value of the modal component.

[0176] In some optional implementations, the modal signal suppression module 300 includes:

[0177] The first modal suppression unit is used to perform modal suppression on the control signal in a first direction according to the estimated value of the modal frequency; wherein the first direction is a direction corresponding to the estimated value of the modal component.

[0178] The second modal suppression unit is used to perform modal suppression on the control signal in a second direction according to the modal frequency estimation value; wherein the second direction is orthogonal to the first direction.

[0179] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0180] The high-speed impeller rotor modal suppression device in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0181] See also Fig.13 , Fig.13It is a structural diagram of a computer device provided by an embodiment of the present application. As shown in the figure, the computer device includes: one or more processors 10, a memory 20, and an interface for connecting various components, including a high-speed interface and a low-speed interface. Each component uses different buses to communicate with each other, and can be installed on a common mainboard or installed in other ways as needed. The processor can process instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Fig.13 A processor 10 is taken as an example.

[0182] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0183] The memory 20 stores instructions executable by at least one processor 10, so that at least one processor 10 executes the method shown in the above embodiment.

[0184] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0185] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0186] The computer device further comprises a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0187] The embodiment of the present application also provides a computer-readable storage medium. The above method according to the embodiment of the present application can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0188] The embodiment of the present application provides a computer program product, which includes computer instructions, which are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the method of any embodiment of the present application.

[0189] Although the embodiments of the present application are described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present application, and such modifications and variations are all within the scope defined by the appended claims.

[0190] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0191] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0192] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0193] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0194] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0195] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0196] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0197] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0198] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

[0199] Although the embodiments of the present application have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present application, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A high-speed impeller rotor modal suppression method, characterized in that: The method comprises: Filtering the speed iso-frequency signal and the speed multiplier signal in the control signal to obtain a target signal; wherein the target signal is used to characterize the sum of the modal component and the bias component; Performing adaptive estimation of modal frequency based on the target signal, the modal component and the bias component to obtain a modal frequency adaptive law, and performing iterative calculation according to the modal frequency adaptive law to obtain a modal frequency estimation value; The control signal is modally suppressed according to the modal frequency estimation value.

2. The method according to claim 1, characterized in that The adaptively estimating the modal frequency based on the target signal, the modal component and the bias component comprises: determining an estimate of the modal component, an estimate of the bias component, and an orthogonal value of the estimate of the modal component; Calculating an error between the target signal and an estimated value of the modal component and an estimated value of the bias component; Modal frequency adaptive estimation is performed based on the error and the orthogonal value of the estimated value of the modal component.

3. The method according to claim 2, characterized in that The adaptively estimating the modal frequency according to the error and the orthogonal value of the estimated value of the modal component comprises: Based on the minimum mean square error principle, determining a cost function according to the error; Using the steepest descent method, a component gradient function is obtained by derivation according to the cost function; Substituting the component gradient function into the expression of the modal frequency to obtain the modal frequency gradient function; The modal frequency adaptation law is determined based on the component gradient functions and the modal frequency gradient function.

4. The method according to claim 3, characterized in that The modal frequency adaptation law is expressed according to the following formula: in, represents the estimated value of the modal component, a derivative representing an estimate of the modal component; represents the orthogonal values ​​of the estimated values ​​of the modal components, represents the derivative of the orthogonal value; represents the estimated value of the bias component, A derivative representing an estimate of the bias component; is the estimated value of the modal frequency, a derivative representing an estimate of the modal frequency; indicating the target signal; is the convergence factor, in, and is the convergence coefficient.

5. The method according to claim 4, characterized in that The cost function is expressed according to the following formula: 。 6. The method according to claim 3, characterized in that: Substituting the component gradient function into the expression of the modal frequency to obtain the modal frequency gradient function includes: According to the convergence form of the third-order generalized integrator, the expression of the modal frequency is obtained; Substituting the component gradient function into an expression of the modal frequency to obtain a frequency error between the modal frequency and an estimated value of the modal frequency; The frequency error is controlled by using an integral control formula to obtain the modal frequency gradient function.

7. The method according to any one of claims 3 to 6, characterized in that The iterative calculation is performed according to the modal frequency adaptive law to obtain the modal frequency estimation value, including: Iteratively calculating the estimated value of the modal component, the estimated value of the bias component, and the orthogonal value of the estimated value of the modal component according to the component gradient function; The modal frequency estimate is determined based on the modal frequency gradient function according to the estimate of the modal component, the estimate of the bias component, and an orthogonal value of the estimate of the modal component.

8. The method according to claim 7, characterized in that The performing modal suppression on the control signal according to the modal frequency estimation value comprises: Performing modal suppression on a control signal in a first direction according to an estimated value of the modal component; wherein the first direction is a direction corresponding to the modal component; Modal suppression is performed on the control signal in the second direction according to the orthogonal value of the estimated value of the modal component; wherein the second direction is orthogonal to the first direction.

9. A high-speed impeller rotor modal suppression device, characterized in that: The device comprises: A frequency conversion signal filtering module is used to filter the speed same frequency signal and the speed multiplication frequency signal in the control signal to obtain a target signal; wherein the target signal is used to characterize the sum of the modal component and the bias component; A modal frequency calculation module, configured to perform adaptive estimation of the modal frequency based on the target signal, the modal component and the bias component to obtain a modal frequency adaptive law, and perform iterative calculation according to the modal frequency adaptive law to obtain a modal frequency estimation value; A modal signal suppression module is used to perform modal suppression on the control signal according to the modal frequency estimation value.

10. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method according to any one of claims 1 to 8 by executing the computer instructions.

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