Closed-loop vibration damping system and method using FBG sensing and piezoelectric stack driving

Abstract

The application provides a closed-loop vibration damping system and method using FBG sensing and piezoelectric stack driving. The system is used for a controlled structure, and the system comprises an FBG sensor, a wide-spectrum light source, a controller and a piezoelectric stack. The FBG sensor and the piezoelectric stack are both mounted on the controlled structure. The FBG sensor is connected to the controller, and the controller is connected to the piezoelectric stack. The wide-spectrum light source is connected to the FBG sensor. The FBG sensor is used for monitoring the vibration condition of the controlled structure and outputting a vibration signal. The controller comprises a Smith prediction module and a control algorithm module. After the vibration signal is compensated for time lag at least via the Smith prediction module, a control voltage signal is output via the control algorithm module. The piezoelectric stack generates a suppression force opposite to the current structure vibration phase under the driving of the control voltage signal. The system can improve the structure vibration suppression efficiency and the control stability.

Description

Technical Field

[0001] This invention relates to the field of structural vibration control technology, and more specifically to a closed-loop vibration reduction system and method employing FBG sensing and piezoelectric stack driving. Background Technology

[0002] With the increasing complexity of aerospace, precision manufacturing, and large-scale civil engineering structures, structural vibration control technology has become a key means to ensure system safety and reliability. Among them, active vibration control, due to its excellent suppression performance in the low-frequency and wide-frequency range, has become the core research direction.

[0003] In the field of sensors, fiber Bragg grating (FBG) sensors are widely used for dynamic strain monitoring of structures due to their advantages such as resistance to electromagnetic interference, small size, and ease of embedding within structures. However, in existing FBG active vibration damping systems, the output control voltage suffers from time lag. Specifically, practical active vibration damping systems involve multiple stages, including signal conditioning, A / D conversion, algorithm logic operations, and power amplification. The cumulative effect of these stages causes a lag in the control system's output signal, reducing the real-time performance and robustness of vibration control.

[0004] In view of this, the present invention is hereby proposed. Summary of the Invention

[0005] The present invention is proposed in view of the above-mentioned problems. According to one aspect of the present invention, a closed-loop vibration reduction system employing FBG sensing and piezoelectric stack driving is provided, characterized in that the system is used for a controlled structure, the system comprising: an FBG sensor, a broadband light source, a controller, and a piezoelectric stack; both the FBG sensor and the piezoelectric stack are mounted on the controlled structure; the FBG sensor is connected to the controller, and the controller is connected to the piezoelectric stack; the broadband light source is connected to the FBG sensor; The FBG sensor is used to monitor the vibration of the controlled structure and output a vibration signal. The controller includes a Smith prediction module and a control algorithm module. The vibration signal is compensated for time delay by the Smith prediction module and then outputs a control voltage signal via the control algorithm module. The piezoelectric stack generates a suppressive force that is opposite to the phase of the current structural vibration under the drive of the control voltage signal.

[0006] The above technical solution can achieve high-precision, low-latency active vibration reduction of structures. It relies on a broadband light source and FBG sensors deployed on the controlled structure to accurately collect the vibration state of the structure in real time and output a complete vibration signal. The Smith prediction module built into the controller can effectively eliminate the time delay interference caused by system lag and calculation time. Then, the control algorithm module calculates and generates a suitable control voltage signal to drive the piezoelectric stack, so that the piezoelectric stack outputs a reverse suppression force opposite to the real-time vibration of the controlled structure, forming a complete closed-loop vibration reduction control link. It not only gives full play to the advantages of FBG sensing in anti-interference and high measurement accuracy, but also solves the problem of time delay instability in active control with the help of the Smith prediction module, which significantly reduces the vibration amplitude of the controlled structure, significantly improves the vibration suppression efficiency and control stability of the structure, and is suitable for various vibration reduction scenarios of controlled structures with strict requirements for vibration control accuracy and timing response.

[0007] For example, the controller further includes a neural network module; the neural network module is used to linearize and denoise the nonlinear distortion of the vibration signal; the vibration signal is processed by the neural network module and then input to the Smith prediction module.

[0008] The above scheme uses a neural network module to linearize and denoise the nonlinear distortion of the vibration signal, which can eliminate nonlinear distortion and environmental temperature drift, effectively remove interference noise mixed in the vibration signal, optimize the signal waveform and data purity, and provide an accurate data foundation for the subsequent calculation of the Smith prediction module.

[0009] For example, the system further includes an analog demodulation unit and a signal conditioning unit, which are connected in series between the FBG sensor and the controller. The vibration signal output by the FBG sensor is converted into a continuous analog voltage signal by the analog demodulation unit, and then input to the controller after gain compensation and noise reduction by the signal conditioning unit.

[0010] The above solution forms a front-end signal processing link by sequentially connecting an analog demodulation unit and a signal conditioning unit between the FBG sensor and the controller. This accurately converts the raw vibration signal output by the FBG sensor into a continuous analog voltage signal. At the same time, the signal conditioning unit performs signal gain compensation and noise filtering. This not only solves the problem that the raw signal from the fiber optic grating sensor is not easily recognized and acquired by the controller, but also corrects signal amplitude loss and reduces clutter interference. This significantly improves the signal integrity, signal-to-noise ratio, and acquisition accuracy of the input controller, ensuring that the back-end controller can obtain stable, clear, and amplitude-appropriate effective vibration data, providing high-quality raw signal support for subsequent vibration suppression.

[0011] For example, the analog demodulation unit includes an edge filter and a photodetector. The vibration signal output by the FBG sensor is a center wavelength drift signal. The edge filter is used to linearly map the drift amount in the center wavelength drift signal into optical power fluctuations. The photodetector is used to convert the signal processed by the edge filter into a continuous analog voltage signal.

[0012] Traditional FBG demodulation devices often employ spectral scanning or digital peak-finding algorithms. When processing high-sampling-frequency signals, these devices are limited by their internal mechanical scanning speed or the processing bandwidth of the digital processor, typically resulting in significant signal update delays. In active control closed loops, this millisecond-level delay at the sensing end leads to a phase difference between the state information acquired by the controller and the actual physical state of the structure, severely limiting the system's ability to suppress high-frequency vibrations and potentially even causing system instability. The solution described in this invention uses edge-filtered analog demodulation instead of spectral scanning digital demodulation, reducing the sensing delay from milliseconds to microseconds. This effectively avoids the delay bottleneck of digital scanning demodulation, overcomes the digital delay problem in the sensing stage, significantly improves the system's ability to suppress high-frequency, minute vibrations, and achieves a closed-loop analog signal throughout the process, avoiding quantization errors introduced by digital sampling and further improving the overall accuracy of vibration suppression.

[0013] For example, the spectral slope range of the edge filter covers the wavelength drift range of the FBG sensor at maximum amplitude. This enables computationally delayed linear wavelength-to-voltage conversion at the physical layer.

[0014] For example, the FBG sensor is attached to the lower part of the piezoelectric stack to be indirectly mounted on the controlled structure through the piezoelectric stack. This co-positioning layout can eliminate spatial transmission hysteresis between the sensor and the actuator, ensure the instantaneity of the feedback signal, eliminate the time delay of vibration wave transmission in the structure at the physical layer, and achieve efficient control of structural vibration.

[0015] For example, the neural network module is further configured to acquire structural characteristic parameters of the controlled structure. Based on these structural characteristic parameters, the neural network module performs linearization correction and noise reduction on the nonlinear distortion of the vibration signal. The structural characteristic parameters include the first-order natural frequency of the controlled structure. This facilitates universal control across structures and, combined with the Smith prediction module, effectively solves the time-delay instability problem in closed-loop control.

[0016] For example, a high-voltage amplifier is connected in series between the controller and the piezoelectric stack, and the control voltage signal output by the controller is amplified by the high-voltage amplifier and then input to the piezoelectric stack.

[0017] The above solution, by connecting a high-voltage amplifier in series between the controller and the piezoelectric stack, can amplify the amplitude of the original control voltage signal output by the controller. This converts the small-amplitude control voltage output by the controller into a high-voltage drive signal that meets the driving requirements of the piezoelectric stack, effectively compensating for the insufficient amplitude of the controller's own output voltage. This ensures that the piezoelectric stack receives sufficient drive voltage to accurately generate the expected deformation displacement, improves the sensitivity and control accuracy of the piezoelectric stack's drive response, and stably achieves controllable adjustment of the piezoelectric stack's working state. This ensures stable output performance and accurate and reliable control of the entire piezoelectric drive system.

[0018] Exemplarily, the system also includes a vibrator and a control terminal, the control terminal being connected to the vibrator, which is mounted on the controlled structure. The vibrator helps simulate environmental excitation, providing a forced vibration environment for the controlled structure, thus facilitating offline system training, system calibration, and periodic self-testing.

[0019] According to another aspect of the present invention, a closed-loop vibration reduction method using FBG sensing and piezoelectric stack driving is provided, wherein the method uses the above-described system to control the vibration of the controlled structure.

[0020] Compared with existing technologies, the above-mentioned technical solution can achieve high-precision, low-latency active vibration reduction of structures. It relies on a broadband light source and FBG sensors deployed on the controlled structure to accurately collect the vibration state of the structure in real time and output a complete vibration signal. The Smith prediction module built into the controller can effectively eliminate the time delay interference caused by system lag and calculation time. Then, the control algorithm module calculates and generates an appropriate control voltage signal to drive the piezoelectric stack, so that the piezoelectric stack outputs a reverse suppression force opposite to the real-time vibration of the controlled structure, forming a complete closed-loop vibration reduction control link. It not only leverages the advantages of FBG sensing in anti-interference and high measurement accuracy, but also uses the Smith prediction module to solve the problem of time delay instability in active control, significantly reducing the vibration amplitude of the controlled structure, significantly improving the vibration suppression efficiency and control stability of the structure, and is suitable for various vibration reduction scenarios of controlled structures with strict requirements for vibration control accuracy and timing response.

[0021] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and in order to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0022] The above and other objects, features, and advantages of the present invention will become more apparent from the more detailed description of the embodiments of the invention in conjunction with the accompanying drawings. The drawings are provided to further illustrate the embodiments of the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings, the same reference numerals generally represent the same parts or steps.

[0023] Figure 1 A schematic diagram of the closed-loop vibration reduction system of Embodiment 1 of the present invention is shown; Figure 2 This diagram illustrates the demodulation principle of the edge filter in this embodiment.

[0024] Figure 1 In the middle: 1. Controlled structure; 2. Control terminal; 3. Power amplifier; 4. Exciter; 5. Broadband light source; 6. FBG sensor; 7. Analog demodulation unit; 8. Signal conditioning unit; 9. Controller; 10. High voltage amplifier; 11. Piezoelectric stack. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of the present invention more apparent, exemplary embodiments according to the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are merely a part of the embodiments of the present invention, and not all of the embodiments of the present invention. It should be understood that the present invention is not limited to the exemplary embodiments described herein. Based on the embodiments of the present invention described herein, all other embodiments obtained by those skilled in the art without inventive effort should fall within the protection scope of the present invention.

[0026] For ease of description, the present invention will be described below by way of embodiments.

[0027] Example 1 This embodiment provides a closed-loop vibration reduction system using FBG sensing and piezoelectric stack driving. The system is used for a controlled structure 1, which is the main controlled object in the actual scenario. The system includes: an FBG sensor 6, a broadband light source 5, a controller 9, and a piezoelectric stack 11; both the FBG sensor 6 and the piezoelectric stack 11 are mounted on the controlled structure 1. The FBG sensor 6 is connected to the controller 9, and the controller 9 is connected to the piezoelectric stack 11; the broadband light source 5 is connected to the FBG sensor 6. Figure 1As shown, in this embodiment, the FBG sensor 6 is attached to the lower part of the piezoelectric stack 11, so as to be indirectly installed on the controlled structure 1 through the piezoelectric stack 11. At this time, the two are installed together at the control point of the controlled structure 1. This co-positioning layout allows the FBG sensor 6 to instantly capture the strain state of the piezoelectric stack 11 acting on the structure, eliminating the time delay of vibration wave transmission in the structure from the physical layer, and realizing efficient control of structural vibration. The piezoelectric stack 11 can be installed in the preset damping hole or the surface force point of the controlled structure 1 through a flexible hinge mechanism. The flexible hinge mechanism is used to mechanically amplify the output displacement of the piezoelectric stack 11 and provide preload to prevent fatigue damage of the piezoelectric material under dynamic alternating stress.

[0028] The broadband light source 5 is used to provide a reference light field for the system. In this embodiment, the light emitted by the broadband light source 5 is transmitted to the FBG sensor 6 via optical fiber. The FBG sensor 6 is used to monitor the vibration of the controlled structure 1 and output a vibration signal. In actual use, the FBG sensor 6 can detect the vibration of the controlled structure 1 and generate a center wavelength drift signal.

[0029] The system in this embodiment also includes a vibrator 4 and a control terminal 2 (which can be a computer). The control terminal 2 is connected to the vibrator 4, and the vibrator 4 is mounted on the controlled structure 1. A power amplifier 3 is connected in series between the control terminal and the vibrator 4. The signal from the control terminal is amplified by the power amplifier 3 and then output to the vibrator 4 to control the vibrator 4 to simulate environmental excitation, providing a forced vibration environment for the controlled structure 1, thereby facilitating offline system training, system calibration, and periodic self-testing.

[0030] To facilitate the processing of the center wavelength drift signal by the controller 9, this embodiment further includes an analog demodulation unit 7 and a signal conditioning unit 8, which are connected in series between the FBG sensor 6 and the controller 9. The vibration signal output by the FBG sensor 6 is converted into a continuous analog voltage signal by the analog demodulation unit 7, and then input to the controller 9 after gain compensation and noise reduction by the signal conditioning unit 8. In this embodiment, the analog demodulation unit 7 adopts a non-scanning quasi-static architecture, including an edge filter and a photodetector. The spectral slope range of the edge filter covers the wavelength drift range of the FBG sensor 6 at its maximum amplitude, thereby achieving linear wavelength-to-voltage conversion without computational delay at the physical layer. In a practical scenario, the center wavelength drift signal (i.e., the vibration signal) output by the FBG sensor 6 is transmitted to the edge filter, which linearly maps the drift amount in the center wavelength drift signal to optical power fluctuations. The photodetector converts the signal processed by the edge filter into a continuous analog voltage signal.

[0031] Figure 2 This diagram illustrates the demodulation principle of the edge filter in this embodiment. Figure 2 As shown, the edge filter utilizes its spectral slope to reduce the small shift in the center wavelength of the FBG. Linear mapping to optical power fluctuation The high-speed photodetector captures the optical power fluctuations in real time and converts them into a continuous analog voltage signal. This process omits traditional digital sampling and peak finding operations, achieving microsecond-level sensing response.

[0032] The vibration signal output by FBG sensor 6 is converted into a continuous analog voltage signal by analog demodulation unit 7, and then processed by signal conditioning unit 8 for gain compensation and noise reduction before being input to controller 9. Controller 9 outputs a control voltage signal based on the processed vibration signal to drive piezoelectric stack 11. In this embodiment, the sampling frequency of controller 9 is set to no less than 10kHz, and the single-step calculation time of the control loop is less than 100μs to ensure that the phase difference between the control command and the displacement state of the controlled structure 1 is within the allowable convergence range under high-frequency vibration conditions.

[0033] The controller 9 includes a Smith prediction module and a control algorithm module. The Smith prediction module can offset the pure time delay of the system and improve the real-time performance of vibration reduction. The vibration signal is compensated for time delay by the Smith prediction module at least, and then the control algorithm module outputs a control voltage signal. The piezoelectric stack 11 generates a damping force that is opposite to the phase of the current structural vibration under the drive of the control voltage signal.

[0034] In this embodiment, the Smith prediction module comprises two branches: "delay-free estimation" and "pure time-delay simulation." It utilizes the pure time delay of the link identified by the system, and through a residual feedback mechanism, compensates for the phase delay caused by the high-voltage amplifier 10 and the mechanical actuator, as well as the calculation time of the controller 9. This allows it to calculate the true / leading state of the controlled structure 1 at the current moment, ensuring that the counteracting force generated by the piezoelectric stack 11 is phase-counteracted with the vibration of the controlled structure 1 in real time. The Smith prediction module also features online self-tuning, monitoring the phase residual between the output command of the control algorithm module and the feedback signal from the FBG sensor 6, and automatically fine-tuning the delay constant in the prediction model based on this residual, thereby improving the vibration reduction effect.

[0035] The pure time delay of the link can be obtained as follows: First, open-loop excitation is performed by sending a step signal or pulse signal through controller 9. Then, using FBG sensor 6 and analog demodulation unit 7, the moment when the piezoelectric stack 11 starts to operate and the moment when FBG sensor 6 receives the strain fluctuation are synchronously acquired. Finally, time delay calculation is performed: the difference between the moment the control command (i.e., the control voltage signal output by controller 9) is issued and the moment when FBG sensor 6 detects the response is calculated. This difference includes the composite pure time delay of each part, i.e., the pure time delay of the link.

[0036] Considering that traditional linear control algorithms struggle to accurately handle the nonlinear distortion of sensor outputs in complex environments, and the high model complexity due to uncertainties in system models caused by changes in structural dimensions and materials, simply introducing the Smith predictor control algorithm is insufficient to balance real-time performance and robustness. To address this issue, the controller 9 in this embodiment also includes a neural network module. This module linearizes and reduces noise in the nonlinear distortion of the vibration signal to eliminate nonlinear distortion and environmental temperature drift. The vibration signal, after processing by the neural network module, is input to the Smith predictor module. The neural network module can employ a lightweight feedforward neural network. To meet the microsecond-level computational requirements of the hardware simulation platform, the activation function of the neural network is optimized using piecewise linear approximation, avoiding extensive iterations of the transcendental function in hardware and achieving microsecond-level hardware-level acceleration of the network's forward pass.

[0037] The neural network module is also used to acquire the structural characteristic parameters of the controlled structure 1. Based on these parameters, the module performs linearization correction and noise reduction on the nonlinear distortion of the vibration signal. The structural characteristic parameters include the first-order natural frequency of the controlled structure 1. These parameters can be acquired through a control terminal. In some implementations, before system operation, the controlled structure 1 can be subjected to wideband sweep excitation by the exciter 4. The free decay signal or frequency response function is collected using the FBG sensor 6, and the first-order natural frequency is identified by a fast Fourier transform performed by the control terminal. This first-order natural frequency is then sent to the neural network module during system initialization to achieve universal control across structures. The neural network module receives signals from the signal conditioning unit 8 and structural characteristic parameters from the control terminal. It performs nonlinear correction and noise reduction on the feedback signal using preset weights, dynamically compensating for edge filter output drift caused by environmental disturbances, ensuring that the signal accurately reflects physical strain.

[0038] The neural network module in this embodiment can be pre-trained offline using experimental data of different sizes and structures, and the hidden layer weight parameters can be adjusted in real time via a control terminal during the online operation phase, thereby achieving adaptive perception calibration for controlled structures 1 with different materials and spans.

[0039] The control algorithm module receives the output of the Smith prediction module, calculates the optimal control quantity that minimizes the system energy function based on the output, and generates a control voltage signal according to the optimal control quantity. This control algorithm module can be implemented based on control algorithms such as LQR and pole placement. For example, the control algorithm module can solve the Riccati equation based on the output of the Smith prediction module and calculate the optimal control command in real time.

[0040] To ensure that the total delay of the control loop is lower than the structural response period of the system, the controller 9 in this embodiment can adopt a hardware simulation platform to realize microsecond-level cyclic operations of the neural network module, Smith prediction module and control algorithm module through its built-in high-speed signal processing unit.

[0041] A high-voltage amplifier 10 is connected in series between the controller 9 and the piezoelectric stack 11. The control voltage signal output by the controller 9 is amplified by the high-voltage amplifier 10 and then input to the piezoelectric stack 11. In this embodiment, the high-voltage amplifier 10 has a high-voltage slew rate characteristic, with a bandwidth of not less than 5kHz, and its output voltage range is adapted to the rated operating voltage of the piezoelectric stack 11, thereby ensuring that it can drive the piezoelectric stack 11 to generate a sufficient amount of suppressive force under high-frequency dynamic excitation. In actual scenarios, the high-voltage amplifier 10 amplifies the signal output by the controller 9, driving the piezoelectric stack 11 to generate mechanical deformation. Since the piezoelectric stack 11 and the FBG sensor 6 are in a co-positioning state, the canceling force generated by them can act precisely and instantaneously on the structural vibration source, achieving closed-loop suppression.

[0042] The system usage method of this embodiment is as follows: System initialization is performed, all hardware links are connected, and the physical parameters of the currently controlled structure 1 are input to the controller 9 via the computer. Simultaneously, the broadband light source 5 is turned on, and the reference light field emitted by the broadband light source 5 is transmitted via optical fiber to the FBG sensor arranged directly below the piezoelectric stack 11. The system enters standby monitoring state. After the external excitation terminal is turned on, the computer controls the power amplifier 3 to drive the exciter 4 to apply physical interference to the controlled structure 1, causing the controlled structure 1 to vibrate. Since the FBG sensor and the piezoelectric stack 11 are in a co-positioned layout, the FBG sensor senses the strain change of the controlled structure 1 at the moment of pressure and generates a center wavelength drift signal. The center wavelength drift signal reflected by the FBG sensor enters the analog demodulation unit 7. The edge filter uses the spectral slope to instantaneously map the wavelength signal into a light intensity signal, and then the high-speed photodetector converts the light intensity signal into a continuous analog voltage signal.

[0043] The analog voltage signal is scaled and denoised by the signal conditioning unit 8 before being input to the controller 9. The controller 9 first activates the neural network module, which linearizes the nonlinear distortion of the signal by combining the initial input structural feature parameters. Then, the Smith prediction module calculates the real-time motion state of the structure after offsetting the execution link delay based on the current and historical vibration states. Based on the predicted real-time motion state (i.e., the output of the Smith prediction module), the control algorithm module calculates the optimal control voltage value that minimizes the vibration energy of the controlled structure 1 and converts this digital command into a control electrical signal output. The high-voltage amplifier 10 receives the control electrical signal and amplifies it to the operating voltage range of the piezoelectric stack 11, driving the piezoelectric stack 11 to generate a suppressive force opposite to the phase of the structural vibration. This suppressive force is directly applied to the controlled structure 1 through the FBG sensor action point at the bottom of the piezoelectric stack 11, achieving real-time and precise suppression of vibration. Throughout the vibration reduction process, the computer monitors the residual vibration amplitude in real time. Controller 9 continuously fine-tunes its output based on the residual vibration feedback from the FBG sensor. If the vibration frequency shifts, controller 9 automatically updates the neural network weights or fine-tunes the delay parameters of the Smith prediction model until the vibration response of the controlled structure 1 is reduced to the preset range and the vibration amplitude is reduced to within the set safety threshold. In actual working scenarios, the exciter 4 is in the off state, and the vibration is an external, native disturbance, which will not be elaborated upon. Thus, by combining the hardware-level demodulation of the analog demodulation unit 7 with the software-level correction of the neural network module, real-time and precise suppression of high-frequency, small vibration amplitudes is achieved without the need for a digital demodulator.

[0044] This embodiment also provides a closed-loop vibration reduction method using FBG sensing and piezoelectric stack driving, which uses the above-described system to control the vibration of the controlled structure.

[0045] Those skilled in the art can easily understand the implementation principle and beneficial effects of the method by reading the above system. For the sake of brevity, further details will not be elaborated here.

[0046] Although exemplary embodiments have been described herein with reference to the accompanying drawings, it should be understood that the above exemplary embodiments are merely illustrative and are not intended to limit the scope of the invention. Various changes and modifications can be made therein by those skilled in the art without departing from the scope and spirit of the invention. All such changes and modifications are intended to be included within the scope of the invention as claimed in the appended claims.

[0047] Those skilled in the art will recognize that the units and algorithm steps of the various examples 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 implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0048] In the several embodiments provided by this invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed.

[0049] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0050] Similarly, it should be understood that, in order to streamline the invention and aid in understanding one or more of the various aspects of the invention, features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof in the description of exemplary embodiments of the invention. However, this approach should not be construed as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as reflected in the corresponding claims, its inventive point lies in solving the corresponding technical problem with fewer features than all of those in a single disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of the invention.

[0051] Those skilled in the art will understand that, apart from the mutual exclusion of features, all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or elements of any method or apparatus so disclosed may be combined in any combination. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0052] Furthermore, those skilled in the art will understand that although some embodiments described herein include certain features but not others included in other embodiments, combinations of features from different embodiments are intended to be within the scope of the invention and form different embodiments. For example, in the claims, any of the claimed embodiments can be used in any combination.

[0053] The various component embodiments of the present invention can be implemented in hardware, or as software modules running on one or more processors, or a combination thereof. Those skilled in the art will understand that microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some modules in the electronic device according to embodiments of the present invention. The present invention can also be implemented as an apparatus program (e.g., a computer program and computer program product) for performing some or all of the methods described herein. Such programs implementing the present invention can be stored on a computer-readable medium or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

[0054] It should be noted that the above embodiments are illustrative of the invention and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.

[0055] The above description is merely a specific embodiment of the present invention or an explanation of that embodiment. The scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. The scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A closed loop vibration damping system employing FBG sensing and piezoelectric stack actuation, characterized by, The system is used for a controlled structure and includes: an FBG sensor, a broadband light source, a controller, and a piezoelectric stack; both the FBG sensor and the piezoelectric stack are mounted on the controlled structure; the FBG sensor is connected to the controller, and the controller is connected to the piezoelectric stack; the broadband light source is connected to the FBG sensor. The FBG sensor is used to monitor the vibration of the controlled structure and output a vibration signal. The controller includes a Smith prediction module and a control algorithm module. The vibration signal is compensated for time delay by the Smith prediction module and then outputs a control voltage signal via the control algorithm module. The piezoelectric stack generates a suppressive force that is opposite to the phase of the current structural vibration under the drive of the control voltage signal.

2. The system of claim 1, wherein, The controller further includes a neural network module; the neural network module is used to linearize and denoise the nonlinear distortion of the vibration signal; the vibration signal is processed by the neural network module and then input to the Smith prediction module.

3. The system of claim 1, wherein, The system also includes an analog demodulation unit and a signal conditioning unit, which are connected in series between the FBG sensor and the controller. The vibration signal output by the FBG sensor is converted into a continuous analog voltage signal by the analog demodulation unit, and then input to the controller after gain compensation and noise reduction by the signal conditioning unit.

4. The system of claim 3, wherein, The analog demodulation unit includes an edge filter and a photodetector. The vibration signal output by the FBG sensor is a center wavelength drift signal. The edge filter is used to linearly map the drift amount in the center wavelength drift signal into optical power fluctuations. The photodetector is used to convert the signal processed by the edge filter into a continuous analog voltage signal.

5. The system of claim 4, wherein, The spectral slope range of the edge filter covers the wavelength drift range of the FBG sensor at maximum amplitude.

6. The system of claim 1, wherein, The FBG sensor is attached to the lower part of the piezoelectric stack so as to be indirectly mounted on the controlled structure through the piezoelectric stack.

7. The system of claim 2, wherein, The neural network module is also used to obtain the structural feature parameters of the controlled structure. The neural network module performs linearization correction and noise reduction processing on the nonlinear distortion of the vibration signal based on the structural feature parameters. The structural feature parameters include the first-order natural frequency of the controlled structure.

8. The system of claim 1, wherein, A high-voltage amplifier is connected in series between the controller and the piezoelectric stack. The control voltage signal output by the controller is amplified by the high-voltage amplifier and then input to the piezoelectric stack.

9. The system of claim 1, wherein, It also includes a vibrator and a control terminal, the control terminal being connected to the vibrator, and the vibrator being mounted on the controlled structure.

10. A closed loop vibration damping method using FBG sensing and piezoelectric stack driving, characterized by, The method uses the system described in any one of claims 1-9 to control the vibration of the controlled structure.

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