A low-energy consumption hybrid isolation method based on ΔE effect of magnetostrictive material

Abstract

This invention relates to a low-energy-consumption hybrid vibration isolation method based on the ΔE effect of magnetostrictive materials. In hybrid vibration isolation, the ΔE effect of magnetostrictive materials is utilized, and a method based on the energy consumption function W is proposed. hybrid =W act +W bias =∫U act I act dt+U bias I bias and the energy function E = E act +E bias =f(A,I act )+g(A,I bias The low-energy-consumption hybrid vibration isolation decision function is minG=aW. hybrid +bE, based on the vibration source characteristics, dynamically adjusts the optimal stiffness operating point of the GMA, and on this basis, uses GMA for active vibration isolation, thereby achieving low-energy semi-active-active hybrid vibration isolation. Experimental tests have demonstrated that this invention has the advantages of low power consumption and good vibration isolation effect compared with traditional vibration isolation methods.

Description

Technical Field

[0001] This invention relates to the field of vibration isolation using giant magnetostrictive materials. Background Technology

[0002] In recent years, with the improvement of smart material performance and automatic control levels, multi-degree-of-freedom active vibration isolation systems based on smart material actuators have become a research hotspot in the field of spacecraft vibration isolation due to their advantages such as high load-bearing capacity, compact structure, and high power-to-weight ratio. They are also highly effective in suppressing low-frequency and ultra-low-frequency micro-vibrations. Giant magnetostrictive materials (GMMs), as a type of smart actuation material, possess characteristics such as high energy conversion efficiency, large magnetostriction coefficient, good frequency response, and high energy density, and are widely used in vibration isolation. However, the elastic modulus of GMMs changes significantly under different loading environments and cannot be approximated as a constant; this phenomenon is called the ΔE effect. While the ΔE effect enhances the stress-strain nonlinearity of GMMs, it also gives them broad application prospects in variable stiffness semi-active vibration isolation and active resonant frequency control. Current vibration isolation technologies involving Giant Magnetostrictive Actuators (GMAs) mainly fall into three categories: active vibration isolation, passive vibration isolation, and semi-active vibration isolation. Among these, only active vibration isolation utilizes GMAs, specifically by providing a control signal that is opposite to the vibration to eliminate low-frequency and mid-to-low-frequency vibrations. However, the ΔE effect makes GMAs a variable stiffness and variable damping device, which also has great application value in the field of semi-active vibration isolation, although research on related applications is currently limited. Summary of the Invention

[0003] In view of the above problems, based on the ΔE effect of GMM, a low-energy hybrid vibration isolation method based on the ΔE effect of magnetostrictive materials is designed:

[0004] By adjusting the bias magnetic field strength of the GMA for variable stiffness semi-active control, resonance peaks can be effectively suppressed, achieving high-frequency vibration attenuation over a wide frequency range. Simultaneously, by dynamically adjusting the magnetic field strength for active control, low-frequency vibration interference can be effectively isolated. Thus, controlling the GMA with the same variable enables hybrid semi-active / active vibration isolation. This not only allows for dynamic adjustment of the GMA's optimal stiffness operating point based on the vibration source characteristics but also reduces energy input through coordinated semi-active and active vibration isolation control, achieving low-energy-consumption, wide-frequency-range, and high-efficiency vibration isolation.

[0005] The GMA vibration isolation system can be simplified into a single-degree-of-freedom second-order system, whose vibration transfer function is:

[0006]

[0007] in , This shows that changing the stiffness can alter the natural frequency and damping of the vibration isolation system, causing the transfer function to shift on the Bode plot. This achieves a system tuning effect, significantly attenuating vibrations near the system's harmonic peaks. This process does not require complex active vibration isolation; it can be achieved simply by adjusting the optimal stiffness operating point. This process is known as semi-active vibration isolation based on stiffness adjustment.

[0008] For GMA (Gross Magnetostrictive Magnetostrictive) materials, variable stiffness semi-active vibration isolation can be achieved by controlling the bias current of the excitation coil to change the bias magnetic field strength, or active vibration isolation can be achieved by dynamically controlling the current to track displacement or force. Therefore, semi-active / active hybrid vibration isolation can be achieved by controlling the current. In this process, semi-active vibration isolation is used to suppress resonance peaks and attenuate high-frequency vibrations, while active vibration isolation can theoretically suppress vibration interference across the entire frequency domain. The working process of the GMA hybrid vibration isolation system can be considered as follows: after the vibration signal is transmitted, semi-active vibration isolation first attenuates a portion of the vibration energy, and then active vibration isolation suppresses the remaining vibration energy interference. Compared with existing vibration isolation methods, the low-energy hybrid vibration isolation method based on the ΔE effect of magnetostrictive materials proposed in this invention has the characteristics of low energy consumption and high precision, which is more in line with the future development needs of the field of vibration isolation for spacecraft equipment.

[0009] Next, a hybrid vibration isolation decision method is proposed:

[0010] To achieve low-energy hybrid vibration isolation, it is necessary to make semi-active / active vibration isolation decisions based on functions of energy consumption and energy, that is, to select the optimal bias current so that the system has the best vibration isolation effect and the lowest energy consumption.

[0011] For GMM active vibration isolation, its energy consumption can be expressed in terms of electrical work, that is:

[0012]

[0013] The smaller the input voltage and current and the shorter the duration, the lower the system energy consumption.

[0014] The low-energy hybrid vibration isolation method based on the ΔE effect of magnetostrictive materials proposed in this invention consists of two parts: semi-active vibration isolation and active vibration isolation. Its energy consumption can be expressed by equation (3):

[0015]

[0016] In the formula Indicates the application of a bias magnetic field The energy consumption of semi-active vibration isolation This indicates the energy consumption for active vibration isolation based on a bias magnetic field. and These represent the time-domain voltage and current signals for active vibration isolation, respectively. and These represent the bias voltage and bias current, respectively. It should be noted that the bias voltage and bias current here refer to the offset from the GMA base bias voltage and current, and therefore can be negative.

[0017] The attenuation energy of hybrid vibration isolation is related to the power density spectrum of the vibration source and the vibration isolation control current. Its attenuation energy function can be expressed by equation (4):

[0018]

[0019] In the formula, A is the power density spectrum of the input vibration. For time-sequential active vibration isolation control current, This is the bias current. Therefore, the decision-making method for hybrid vibration isolation is a multi-objective optimization problem, with the objective function being:

[0020]

[0021] In the formula, a and b are weighting coefficients, which can be determined according to the actual vibration isolation requirements. Hybrid vibration isolation decision-making involves finding a suitable weighting coefficient. This minimizes the objective function G. The optimal bias current is then obtained. This ensures the system achieves the best vibration isolation effect and the lowest energy consumption. Equation (5) is the hybrid vibration isolation decision function.

[0022] The core objective of this method is to attenuate vibrations in stages through reasonable decision-making using hybrid vibration isolation, resulting in lower overall energy consumption compared to active vibration isolation, and the active vibration isolation component is easier to control and has a better vibration isolation effect.

[0023] In summary, the low-energy hybrid vibration isolation method based on the ΔE effect of magnetostrictive materials proposed in this invention has a good vibration isolation effect. At the same time, compared with other vibration isolation methods, it has lower energy consumption output near the natural frequency and better vibration isolation effect. Attached Figure Description

[0024] Figure 1 This is a flowchart of a low-energy hybrid vibration isolation method based on the ΔE effect of magnetostrictive materials proposed in this invention.

[0025] Figure 2 Bode plot of the transfer function change after semi-active tuning;

[0026] Figure 3 This is a test bench for evaluating vibration isolation in GMA systems.

[0027] Figure 4 Comparison of time-domain signals showing the effect of semi-active tuning under simple harmonic excitation near the harmonic peak;

[0028] Figure 5 A time-domain signal comparison of the semi-active tuning effect under composite excitation;

[0029] Figure 6 This is a time-domain signal diagram of hybrid vibration isolation under composite excitation. Detailed Implementation

[0030] The present invention will now be described in detail with reference to the accompanying drawings and embodiments:

[0031] like Figure 1 As shown, a low-energy hybrid vibration isolation method based on the ΔE effect of magnetostrictive materials includes the following steps:

[0032] S1, Schematic diagram of the vibration isolation system structure as shown below Figure 3 As shown, the vibration signal of the vibration source is collected by the laser vibration sensor probe 2, and the vibration power density spectrum is obtained by performing spectral analysis on it.

[0033] S2, input the vibration spectrum into the hybrid vibration isolation decision function To obtain the optimal bias control current. ;

[0034] S3, Current controller output bias current Adjusting the GMA stiffness allows for semi-active tuning vibration isolation, causing the transfer function of the isolation system to change as follows: Figure 2 The changes shown eliminate vibrations near harmonic peaks and high-frequency vibrations, and pre-attenuate the overall vibration signal;

[0035] S4. For the remaining low-frequency vibration signals, active vibration isolation is used to eliminate them based on the force sensor signal.

[0036] S5: Collect data from laser vibration sensor probe 1 and determine whether the vibration isolation effect meets the requirements. If it does not meet the requirements, return to S4. If it does meet the requirements, the vibration isolation program ends.

[0037] To verify the practical application effect of this vibration isolation method, a test platform was built as follows: Figure 3 The GMA vibration isolation evaluation test bench shown consists of two GMAs. The lower GMA is responsible for generating excitation vibration, while the upper GMA is responsible for verifying the vibration isolation method. Laser sensor probe 1 measures the load vibration, and laser sensor probe 2 measures the vibration source vibration. A force sensor is used for active vibration isolation control. The controller collects data from the three sensors and uploads it to the data acquisition and control board. After receiving the data from the data acquisition and control board, the host computer generates a control signal and sends it to the driver. The driver then drives the two GMAs to operate.

[0038] Experimental results show that: Figure 4 As shown, when a simple harmonic excitation with a frequency near the harmonic peak is applied, the system will generate resonant gain without semi-active tuning, resulting in a deterioration in vibration isolation. However, after semi-active tuning, the vibration energy is attenuated by more than 50%, while still maintaining a good vibration isolation effect. Figure 5 As shown, when a composite excitation containing frequencies near the harmonic peak is applied, the system will still generate resonant gain without semi-active tuning, while the vibration energy is significantly attenuated after semi-active tuning; for composite excitation, after semi-active / active hybrid vibration isolation, as shown... Figure 6 As shown, most of the vibration energy is attenuated, and the system achieves a good vibration isolation effect.

Claims

1. A semi-active-active hybrid vibration isolation method based on the ΔE effect of magnetostrictive materials, characterized in that, Includes the following steps: S1, The vibration isolation system consists of two GMAs. The lower GMA is responsible for generating excitation vibration, while the upper GMA is responsible for verifying the vibration isolation method. Laser sensor probe one is responsible for measuring load vibration, and laser sensor probe two is responsible for measuring vibration source vibration. Force sensor is used for active vibration isolation control. The controller collects data from the three sensors and uploads it to the data acquisition and control board. After receiving the data returned by the data acquisition and control board, the host computer generates a control signal and sends it to the driver. The driver drives the two GMAs to operate. The laser vibration sensor probe two collects the vibration signal of the vibration source and performs spectral analysis to obtain the vibration power density spectrum A. S2, input the vibration spectrum into the hybrid vibration isolation decision function To obtain the optimal bias control current. ,in This indicates that energy consumption consists of two parts: semi-active vibration isolation and active vibration isolation. In the formula... Indicates the application of a bias magnetic field The energy consumption of semi-active vibration isolation This indicates the energy consumption for active vibration isolation based on a bias magnetic field. and These represent the time-domain voltage and current signals for active vibration isolation, respectively. and Let V represent the bias voltage and bias current, respectively, and E be the decay energy function. In the formula, A is the power density spectrum of the input vibration, and a and b are weighting coefficients. S3, Current controller output bias current Adjusting the stiffness of the GMA and performing semi-active tuning vibration isolation changes the transfer function of the vibration isolation system, eliminating vibrations near the harmonic peaks and high-frequency vibrations, and pre-attenuating the overall vibration signal. S4. For the remaining low-frequency vibration signals, active vibration isolation is used to eliminate them based on the force sensor signal. S5: Collect data from the laser vibration sensor probe and determine whether the vibration isolation effect meets the requirements. If it does not meet the requirements, return to S4; if it does meet the requirements, the vibration isolation program ends.

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