Micro-vibration transfer characteristic identification and quantitative characterization method

Abstract

The invention provides a micro-vibration transmission characteristic identification and quantitative characterization method. The method comprises the following steps: identifying a disturbance vibration signal characteristic frequency at a controlled target area; obtaining a function coefficient estimation value of the control signal transfer function through nominal identification of the control signal transfer function by an LMS method, and determining the control signal transfer function; performing pull deviation identification on the control signal transfer function through an LMS method, obtaining a function coefficient estimation value of the control signal transfer function, and determining the control signal transfer function; and selecting a control signal transfer function obtained by nominal identification or pulling deviation identification, and implementing micro-vibration transfer characteristic identification and quantitative characterization. A linear model is provided by using an adaptive wave trap, an estimated value of an unknown system transfer function is obtained when the system is in a black box state, a parameter simplification transfer characteristic quantitative characterization mode is designed based on a sine and cosine function superposition idea, and accurate compensation is realized by directly combining with an active control strategy. And the micro-vibration characteristic identification and compensation control precision is effectively improved.

Description

Technical Field

[0001] The present invention belongs to the field of on-orbit vibration control of spacecraft, and in particular relates to a method for identifying and quantifying micro-vibration transfer characteristics. Background Art

[0002] At present, with the further improvement of the performance indicators of high-precision and high-stability spacecraft, the observation payload has increasingly stringent requirements for on-orbit micro-vibration suppression. Vibration reduction and isolation technology based on active micro-vibration control has gradually begun to be applied to micro-vibration suppression of high-precision and high-stability spacecraft. The delay, amplification or attenuation effects caused by the amplitude-frequency characteristics and phase-frequency characteristics of the micro-vibration signal and the control signal transmission process directly affect the active micro-vibration control effect. Since the influence of the amplitude-frequency characteristics of the transfer function can be comprehensively considered through the control gain, only the influence of its phase-frequency characteristics, that is, the influence of the phase delay caused by the transfer function, can be considered. Accurate identification and quantitative characterization of micro-vibration transfer characteristics can further improve the active micro-vibration control effect and improve the performance indicators of active micro-vibration control.

[0003] In the existing spacecraft active micro-vibration control system, there are still problems such as difficulty in identifying the micro-vibration transmission of the unknown system (mathematical model of the spacecraft structure) and complex quantitative characterization, which makes it difficult to further improve the effect of spacecraft active micro-vibration control. The identification and quantitative characterization methods of micro-vibration transmission characteristics have the following shortcomings:

[0004] 1. Lack of effective identification of micro-vibration transfer characteristics of unknown system models

[0005] Existing methods for identifying micro-vibration transfer characteristics of spacecraft mostly rely on known models of the identified system. However, due to the large number of different types of disturbance sources on spacecraft, high disturbance frequencies, and wide spectrum distribution, the complex structure of spacecraft and its connection links, and the differences in the ground-earth environment, it is impossible to establish an accurate system model. Therefore, it is necessary to study a universal micro-vibration transfer characteristics identification method for the black box state of the unknown system model to compensate for the influence of time delay characteristics on the active micro-vibration control effect.

[0006] 2. It is impossible to achieve a simplified and quantitative characterization of the parameters of micro-vibration transmission characteristics

[0007] The current quantitative characterization methods for spacecraft micro-vibration transfer characteristics often require multiple parameters to fully characterize the micro-vibration characteristics. Each additional parameter requires an additional identification calculation, and the characterization formula is complex. Therefore, it is necessary to design a parameter-simplified quantitative characterization method for micro-vibration transfer characteristics, and characterize the spacecraft micro-vibration transfer characteristics through the identification and calculation of as few key parameters as possible. Summary of the invention

[0008] In order to overcome the deficiencies in the prior art, the inventors have conducted intensive research and provided a method for identifying and quantitatively characterizing micro-vibration transfer characteristics. An adaptive notch filter is used to provide a linear model. When the system is in a black box state, an estimated value of the unknown system transfer function is obtained. Based on the idea of ​​sine and cosine function superposition, a parameter-simplified transfer characteristic quantitative characterization method is designed, which can be directly combined with an active control strategy to achieve precise compensation, thereby effectively improving the accuracy of micro-vibration characteristic identification and compensation control.

[0009] The technical solution provided by the present invention is as follows:

[0010] In a first aspect, a method for identifying and quantifying micro-vibration transfer characteristics comprises:

[0011] Identify the characteristic frequency of the disturbance signal at the controlled target area;

[0012] According to the identified characteristic frequency of the disturbance signal at the controlled target area, the control signal transfer function is nominally identified by the LMS method, the function coefficient estimation value of the control signal transfer function is obtained, and the control signal transfer function is determined;

[0013] According to the identified characteristic frequency of the disturbance signal at the controlled target area, the control signal transfer function is identified by the LMS method, the function coefficient estimation value of the control signal transfer function is obtained, and the control signal transfer function is determined;

[0014] Select the control signal transfer function obtained by nominal identification or pull-bias identification to implement the identification and quantitative characterization of micro-vibration transfer characteristics.

[0015] In a second aspect, a micro-vibration transfer characteristic identification and quantitative characterization device includes:

[0016] one or more processors;

[0017] a storage device for storing one or more programs,

[0018] When the one or more programs are executed by the one or more processors, the one or more processors implement the micro-vibration transfer characteristic identification and quantitative characterization method described in the first aspect.

[0019] In a third aspect, a readable storage medium stores a computer program, which, when executed by a processor, implements the method for identifying and quantifying micro-vibration transfer characteristics described in the first aspect.

[0020] In a fourth aspect, a computer program product is provided, the computer program product comprising: a computer program (also referred to as code, or instruction), which, when executed, executes the method for identifying and quantifying micro-vibration transfer characteristics described in the first aspect.

[0021] A micro-vibration transfer characteristic identification and quantitative characterization method provided by the present invention has the following beneficial effects:

[0022] (1) The present invention provides a method for identifying and quantifying micro-vibration transfer characteristics, and establishes a method for identifying micro-vibration transfer characteristics of an unknown system model. Currently available methods for identifying micro-vibration transfer characteristics mostly rely on known models of the system to be identified. However, there are many different types of disturbance sources on spacecraft, the disturbance frequency is high, the spectrum distribution is wide, the spacecraft structure and its connection links are complex, and there are differences in the ground-air environment, making it impossible to establish an accurate system model. The present invention uses an adaptive notch filter to provide a linear model. When the system is in a black box state, the estimated value AP_es of the unknown system transfer function AP is obtained, thereby fitting the unknown system to the greatest extent.

[0023] (2) The present invention provides a method for identifying and quantifying micro-vibration transfer characteristics, which can achieve a simplified quantitative characterization of micro-vibration transfer characteristics. Current methods for quantifying the transfer characteristics of spacecraft micro-vibration often require multiple parameters to fully characterize the micro-vibration characteristics. Each additional parameter requires an additional identification calculation, and the characterization formula is complex. The present invention is based on the idea of ​​superposition of sine and cosine functions, and designs a parameter-simplified quantitative characterization method for micro-vibration transfer characteristics. The tap coefficients are quickly updated by iterative calculation within a limited time to approximate the expected value, that is, the vibration signal characteristics can be characterized only by the tap coefficients Ws and Wc, and the obtained Ws, Wc, and eff can be directly transmitted back to the active micro-vibration controller as telemetry parameters for active vibration control. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is the flow chart of identifying characteristic frequency dis_f of disturbance signal;

[0025] Figure 2 It is the block diagram of the nominal identification algorithm based on LMS;

[0026] Figure 3 It is the block diagram of the positive pull bias identification algorithm based on LMS;

[0027] Figure 4 This is the block diagram of the negative pull bias identification algorithm based on LMS. DETAILED DESCRIPTION

[0028] The following detailed description of the present invention will make the features and advantages of the present invention more clear and explicit.

[0029] The word “exemplary” is used exclusively herein to mean “serving as an example, example, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.

[0030] In view of the problems of unknown system model and parameter simplification in the identification and characterization of micro-vibration characteristics of spacecraft on-orbit, the present invention provides a method for identifying and quantifying micro-vibration transfer characteristics, assuming that the vibration signal of the disturbance source at point A of the spacecraft at point B of a sensitive element of the spacecraft is a sinusoidal signal of a specific frequency; and the active suppression of micro-vibration of the spacecraft on-orbit requires that the actuator installed at point C generates a sinusoidal signal with the same amplitude and frequency but opposite phase at point B. Among them, due to the complex structure of the spacecraft, if the micro-vibration response transfer model between point C and point B is unknown, it is possible to consider using a least mean square adaptive notch filter (LMS) to provide a linear model, and identify and obtain an estimated value of the unknown system transfer function when the system model is in a black box state; and when calculating the estimated value of the transfer function, it is possible to consider that the vibration signal expected to be output by the actuator is a superposition of a sine function and a cosine function containing specific amplitude coefficients Ws, Wc and frequency, and the vibration signal characteristics can be characterized using only Ws and Wc.

[0031] The micro-vibration transfer characteristic identification and quantitative characterization method comprises the following steps:

[0032] The characteristic frequency dis_f of the disturbance signal at the controlled target area (point B) is identified in the following steps:

[0033] Before applying control, only under the action of the disturbance source, the original disturbance signal dis_ori is transferred to the controlled target area through the disturbance source signal transfer function DP, and the actual disturbance signal dis_des is subjected to FFT analysis to obtain the measured value of the characteristic frequency of the disturbance signal. After correction, the estimated value dis_f_es of the characteristic frequency dis_f of the disturbance signal that actually needs to be actively suppressed in the controlled target area is obtained. The purpose of the correction is to mathematically correct the actual frequency of the disturbance signal transferred from the disturbance source to the controlled target area based on the prior knowledge of the error.

[0034] Among them: dis_f is the actual value of the characteristic frequency of the disturbance signal at the controlled target area, which is determined by the characteristics of the disturbance source; dis_ori is the original disturbance signal of the disturbance source itself (without considering the influence of the installation boundary and the transmission link factors); DP is the actual transfer function of the disturbance source signal transmitted to the controlled target area; dis_f_es is the estimated value of the characteristic frequency of the disturbance signal at the controlled target area. The initial value is the ground identification result and can be updated through autonomous identification on orbit.

[0035] (2) The control signal transfer function AP is identified based on the LMS algorithm. The control signal transfer function AP represents the vibration effect generated by the actuator at point C (used to suppress disturbances) and transmitted to the controlled target area (point B). The steps are as follows:

[0036] When the system disturbance source is not turned on and all structures and their connections on the satellite are fully deployed, the actual frequency of the control signal at the controlled target area during active identification is exactly the same as the estimated value (dis_f_es) of the characteristic frequency of the disturbance source in the controlled target area in orbit obtained in advance. The estimated value of the function coefficient AP_es is obtained by the nominal identification of the control signal transfer function AP, and is characterized by the sine tap coefficient Ws, cosine tap coefficient Wc and transfer phase delay in the frequency domain. The estimated value of the transfer function AP is a linear model.

[0037] Wherein: AP is the actual value of the transfer function from the active control signal to the controlled target area; AP_es is the estimated value of the function coefficient of the control signal transfer function, and its initial value is the ground identification result and can be autonomously identified and updated on orbit.

[0038] (3) The control signal transfer function AP is identified based on the LMS algorithm. The steps are as follows:

[0039] When the system disturbance source has been turned on and all the structures and their connecting links on the satellite are fully deployed and in place, the actual frequency of the control signal at the controlled target area during active identification is obtained by performing positive and negative deviation on the estimated value (dis_f_es) of the characteristic frequency of the disturbance source in the on-orbit controlled target area; the positive deviation estimate of the function coefficient AP_esp is obtained by identifying the positive deviation of the control signal transfer function AP, and the negative deviation estimate of the function coefficient AP_esn is obtained by identifying the negative deviation of the control signal transfer function AP. The function coefficient estimate AP_es is obtained by taking a weighted average of the positive deviation estimate AP_esp and the negative deviation estimate AP_esn, and is characterized by the sine tap coefficient Ws, the cosine tap coefficient Wc and the transfer phase delay in the frequency domain.

[0040] Wherein: AP_esp is the estimated value of the positive deviation of the function coefficient of the control signal transfer function, and AP_esn is the estimated value of the negative deviation of the function coefficient of the control signal transfer function.

[0041] When the control signal transfer function AP is nominally identified in step (2), or when the control signal transfer function AP is biased identified in step (3), the identification method based on the LMS algorithm is:

[0042] The first step is to perform self-check iterative calculations in combination with the LMS algorithm, self-check for x seconds, and identify quantitative characterization:

[0043]

[0044] In the formula: DA represents the control signal output to the actuator, that is, the expected output voltage; n represents the nth iterative calculation; v represents the actuator driving voltage amplitude; f represents the characteristic frequency estimation value of the disturbance signal dis_f_es during nominal identification at the controlled target area, dis_f_es+δf during positive deviation identification, and dis_f_es-δf during negative deviation identification, δf represents the signal frequency deviation; e represents the error signal; AD represents the actual collected signal at the controlled target area; y represents the estimated value of the collected signal at the controlled target area after the actuator is actuated; μ represents the gain constant used to control the adaptive speed and stability; Ws represents the sine tap coefficient, and Wc represents the cosine tap coefficient, which together represent the transfer amplitude amplification / attenuation coefficient.

[0045] The second step is to calculate the root mean square of the error signal e for a period of time m seconds before the self-test begins, recorded as rms 0 ;

[0046] In the third step, after the self-check is completed for x seconds, the error signal e is taken for a period of time and the root mean square calculation is performed, which is recorded as rms 1 , calculate the recognition accuracy eff=rms 1 / rms 0 , save the final Ws and Wc.

[0047] The present invention also provides a micro-vibration transfer characteristic identification and quantitative characterization device, comprising:

[0048] one or more processors;

[0049] a storage device for storing one or more programs,

[0050] When the one or more programs are executed by the one or more processors, the one or more processors implement the micro-vibration transfer characteristic identification and quantitative characterization method described in the first aspect.

[0051] The present invention also provides a readable storage medium having a computer program stored thereon, and when the program is executed by a processor, the method for identifying and quantifying micro-vibration transfer characteristics described in the first aspect is implemented.

[0052] The readable storage medium includes, but is not limited to, various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0053] The present invention also provides a computer program product, which includes: a computer program (also referred to as code, or instruction), which, when executed, executes the micro-vibration transfer characteristic identification and quantitative characterization method described in the first aspect.

[0054] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, microwave, etc.) mode to another website site, computer, server or data center.

[0055] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0056] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the products and devices described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here.

[0057] The present invention has been described in detail above in conjunction with specific implementations and exemplary examples, but these descriptions cannot be understood as limiting the present invention. Those skilled in the art understand that, without departing from the spirit and scope of the present invention, a variety of equivalent substitutions, modifications or improvements may be made to the technical solution of the present invention and its implementation methods, all of which fall within the scope of the present invention. The scope of protection of the present invention shall be subject to the attached claims.

[0058] The contents not described in detail in the specification of the present invention belong to the common knowledge of those skilled in the art.

Claims

1. A method for identifying and quantifying micro-vibration transfer characteristics, characterized in that: include: Identify the characteristic frequency of the disturbance signal at the controlled target area; According to the identified characteristic frequency of the disturbance signal at the controlled target area, the control signal transfer function is nominally identified by the LMS method, the function coefficient estimation value of the control signal transfer function is obtained, and the control signal transfer function is determined; According to the identified characteristic frequency of the disturbance signal at the controlled target area, the control signal transfer function is identified by the LMS method, the function coefficient estimation value of the control signal transfer function is obtained, and the control signal transfer function is determined; Select the control signal transfer function obtained by nominal identification or pull-bias identification to implement the identification and quantitative characterization of micro-vibration transfer characteristics.

2. The method for identifying and quantifying micro-vibration transfer characteristics according to claim 1, characterized in that: The step of identifying the characteristic frequency of the disturbance signal at the controlled target area includes: Before applying control, only under the action of the disturbance source, the original disturbance signal dis_ori is transferred to the controlled target area through the disturbance source signal transfer function, and the actual disturbance signal dis_des is subjected to FFT analysis to obtain the measured value of the characteristic frequency of the disturbance signal. After correction, the estimated value dis_f_es of the characteristic frequency of the disturbance signal that actually needs to be actively suppressed in the controlled target area is obtained.

3. The micro-vibration transfer characteristic identification and quantitative characterization method according to claim 1, characterized in that: The step of obtaining the estimated value of the function coefficient of the control signal transfer function by performing nominal identification of the control signal transfer function by the LMS method according to the identified characteristic frequency of the disturbance signal at the controlled target area comprises: When the system disturbance source is not turned on and all the structures and their connecting links on the satellite are fully deployed, the characteristic frequency of the disturbance signal at the controlled target area is taken as input, and the nominal identification of the control signal transfer function is performed through the LMS method to obtain the estimated value of its function coefficient and obtain the control signal transfer function.

4. The method for identifying and quantifying micro-vibration transfer characteristics according to claim 1, characterized in that: The step of obtaining the estimated value of the function coefficient of the control signal transfer function by performing pull-off identification of the control signal transfer function by the LMS method according to the identified characteristic frequency of the disturbance signal at the controlled target area comprises: When the system disturbance source has been turned on and all the structures and their connecting links on the satellite are fully deployed and in place, the characteristic frequencies of the disturbance signals at the positive and negative deflection controlled target areas are taken as input, and the positive deflection estimation value of the function coefficient is obtained by identifying the positive deflection of the control signal transfer function through the LMS method, and the negative deflection estimation value of the function coefficient is obtained by identifying the negative deflection of the control signal transfer function. The function coefficient estimation value is obtained by weighted averaging the positive deflection estimation value and the negative deflection estimation value of the function coefficient, and the control signal transfer function is obtained.

5. The method for identifying and quantifying micro-vibration transfer characteristics according to claim 3 or 4, characterized in that: When the control signal transfer function is nominally identified, or when the control signal transfer function is pulled to identify, the identification method based on the LMS algorithm is: The first step is to perform self-check iterative calculations in combination with the LMS algorithm, self-check for x seconds, and identify quantitative characterization: Where: DA represents the control signal output to the actuator, that is, the expected output voltage; n represents the nth iterative calculation; v represents the actuator driving voltage amplitude; f represents the characteristic frequency estimation value of the disturbance signal dis_f_es during nominal identification at the controlled target area, dis_f_es+δf during positive deviation identification, and dis_f_es-δf during negative deviation identification, δf represents the signal frequency deviation; e represents the error signal; AD represents the actual collected signal at the controlled target area; y represents the estimated value of the collected signal at the controlled target area after the actuator is actuated; μ represents the gain constant used to control the adaptive speed and stability; Ws represents the sine tap coefficient, and Wc represents the cosine tap coefficient, which together represent the transfer amplitude amplification / attenuation coefficient; The second step is to calculate the root mean square of the error signal e for a period of time m seconds before the start of the self-test, which is recorded as rms0; The third step is to calculate the root mean square of the error signal e after the self-check is completed for x seconds, record it as rms1, calculate the identification accuracy eff = rms1 / rms0, and save the final Ws and Wc.

6. A device for identifying and quantifying micro-vibration transfer characteristics, characterized in that: include: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the micro-vibration transfer characteristic identification and quantitative characterization method according to any one of claims 1 to 5.

7. A readable storage medium, characterized in that: A computer program is stored thereon, and when the program is executed by a processor, the method for identifying and quantifying micro-vibration transfer characteristics as claimed in any one of claims 1 to 5 is implemented.

8. A computer program product, characterized in that The computer program product comprises: a computer program, and when the computer program is run, the method for identifying and quantifying micro-vibration transfer characteristics according to any one of claims 1 to 5 is executed.

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