Programmable vortex sound field multi-target stable control method and system

Abstract

The invention relates to the technical field of acoustic control and intelligent control, in particular to a programmable vortex sound field multi-target stable control method and a programmable vortex sound field multi-target stable control system. Multi-vortex acoustic beam generation with programmable regulation and control of the number, the position and the topological charge is realized, and independent or cooperative control can be implemented on a plurality of target particles; and the method supports multi-particle parallel capture and trajectory regulation and control, and has application potential in the fields of biomedicine, microfluidics, micro-nano manufacturing and the like.

Description

Technical Field

[0001] The present invention relates to the field of acoustic manipulation and intelligent control technology, and in particular to a programmable vortex sound field multi-target stable manipulation method and system. Background Art

[0002] In recent years, acoustic manipulation technology has shown important application value in the field of micro-nanoscale object manipulation due to its non-contact and non-destructive characteristics. Traditional acoustic manipulation methods mainly rely on a single vortex sound field to capture and move particles through the action of acoustic radiation force. However, such methods have obvious limitations in complex application scenarios, especially the difficulty in achieving independent or coordinated manipulation of multiple particles, and the lack of real-time control capabilities. With the rapid development of micro-nanotechnology, the demand for multi-target, high-precision acoustic manipulation is becoming increasingly urgent, which poses new challenges to existing technologies.

[0003] In the existing technology, the optical vortex manipulation method realizes multi-target manipulation through spiral phase space filtering, coaxial superposition of optical vortices and other technologies, but the optical method has problems such as complex equipment and high cost. In contrast, acoustic vortex technology has better biocompatibility and penetration depth. At present, there are two main ways to generate acoustic multi-vortices: one is to control the number and position of vortices by changing the phase delay of each element of the circular array, such as holographic acoustic tweezers (HAT) technology; the other is to use a large number of sound source arrays in conjunction with iterative backpropagation algorithms to generate multiple acoustic vortices. However, these methods still have the disadvantages of complex systems, high costs, and poor real-time performance, and it is difficult to meet the comprehensive requirements of flexibility, stability and economy in practical applications. Especially in dynamic environments, the existing technology lacks an effective feedback control mechanism and cannot optimize the sound field parameters in real time according to the target state, resulting in insufficient control accuracy and stability. Therefore, the development of a multi-vortex sound field manipulation method with intelligent feedback function and programmable control has important scientific significance and application value. Summary of the Invention

[0004] The main purpose of the present invention is to provide a programmable vortex acoustic field multi-objective stable control method and system to effectively solve the above-mentioned problems mentioned in the background technology.

[0005] The technical solutions of the present invention are as follows:

[0006] In the first aspect, a programmable vortex acoustic field multi-objective stable control method is proposed, which includes the following steps:

[0007] S1. Generate a multi-vortex sound field through an annular transducer array: Utilizing an annular array consisting of multiple transducers, the phase and amplitude of each transducer are independently controlled by a multi-channel drive system to generate multiple vortex sound beams with controllable spatial distribution;

[0008] S2, Adaptive Phase Coding Control: Based on the number and spatial distribution of target particles, an adaptive phase coding algorithm is used to generate the optimal phase coding matrix of the transducer, dynamically adjusting the sound pressure distribution of the vortex sound field;

[0009] S3. Real-time monitoring with visual feedback: A high-frame-rate visual inspection system is used to capture real-time motion images of particles within the control area, and the position and motion parameters of the particles are extracted through image processing algorithms.

[0010] S4. Closed-loop optimization and control: Based on the particle position deviation based on visual feedback, the phase, amplitude and excitation frequency of the transducer array are dynamically adjusted through an intelligent optimization algorithm to minimize target offset and achieve stable control of multiple target particles.

[0011] A further improvement of the present invention is that the annular transducer array in S1 is composed of at least 8 planar transducers arranged evenly, and the maximum number of vortices that can be generated is half the number of transducers.

[0012] A further improvement of the present invention is that S2 comprises the following specific steps:

[0013] S201, constructing a traditional acoustic vortex using a ring-shaped sound source array, and translating the center of the along-axis vortex sound beam radially to a preset off-axis vortex center;

[0014] S202, determine the additional phase delay of the transducer; obtain the phase required by the nth sound source Sn as φ through geometric calculation n '=φ n +k0ΔR n , where k0ΔR n is the additional phase of the sound source, ΔR n Represents the distance change of the sound propagation path;

[0015] S203, integrating the surface area of the sound source and superimposing the sound pressure of the sound field radiated by N phase-controlled sound sources to obtain the sound pressure of the off-axis vortex sound field:

[0016] S204. Using the linear superposition of multiple off-axis vortex sound fields, the expression of the sound pressure of the composite multi-vortex sound field is obtained:

[0017] S205. Automatically generate an optimal phase encoding matrix through iterative optimization, so that the main lobe position and topological characteristics of the sound pressure distribution approach the target configuration.

[0018] A further improvement of the present invention is that the visual detection system in S3 includes a high-speed CMOS camera with a frame rate of not less than 240fps and an image processing module, and the image processing module realizes particle position detection and real-time tracking through edge detection, contour analysis and Kalman filtering algorithm.

[0019] A further improvement of the present invention is that the intelligent optimization algorithm in S4 is a particle swarm optimization algorithm, which minimizes the deviation between the actual position of the particle and the target position by dynamically adjusting the phase and amplitude parameters of the transducer. The calculation formula of the target deviation error is: Δ i =(x i obs -x i tar ) 2 +(y i obs -y i tar ) 2 .

[0020] Secondly, a programmable vortex acoustic field multi-objective stable control system is proposed, which includes:

[0021] Ring transducer array module, signal generation and control module, visual feedback module, and central control unit;

[0022] The annular transducer array module is used to generate a multi-vortex sound field;

[0023] The signal generation and control module is used to independently control the phase and amplitude of each transducer;

[0024] The visual feedback module is used to monitor the particle motion state in real time;

[0025] The central control unit is used to coordinate signal transmission and control between modules.

[0026] A further improvement of the present invention is that the annular transducer array module adopts a multi-layer PCB board integrated design, the transducers are evenly distributed on the circumference, and the phase and amplitude are independently adjustable.

[0027] A further improvement of the present invention is that the visual feedback module includes a high-speed CMOS camera and a real-time image processing component, and the image processing component realizes high-precision extraction of particle positions and trajectory prediction based on the OpenCV library.

[0028] The technical effects of the present invention are as follows:

[0029] A programmable vortex acoustic field multi-target stable control method and system have been constructed, aiming to solve the problems of insufficient multi-target control capability, poor real-time performance and lack of feedback control mechanism in existing acoustic particle manipulation technology. The present invention achieves high-precision and stable control of multiple particles in the acoustic field by constructing a transducer array system with multi-vortex output capability, introducing an adaptive phase encoding algorithm and a real-time visual feedback mechanism, and meeting the higher requirements for flexibility, stability and intelligence in complex micro-operation scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Other features, objects and advantages of the present invention will become more apparent upon reading the detailed description of non-limiting embodiments made with reference to the following drawings:

[0031] Figure 1 This is a general structural diagram of a programmable vortex acoustic field multi-objective stable control system of the present invention;

[0032] Figure 2 This is the principle diagram of realizing multi-vortex sound beam based on annular sound source array;

[0033] Figure 3 Flowchart for adaptive phase encoding algorithm to control the sound field distribution;

[0034] Figure 4 The composition of the visual feedback module and the flow chart of the sound field dynamic optimization control based on feedback regulation;

[0035] Figure 5 This is a typical multi-target particle manipulation effect diagram. DETAILED DESCRIPTION

[0036] The present invention aims to propose a programmable vortex sound field multi-target stable control method and construct a programmable vortex sound field multi-target stable control system, aiming to solve the problems of insufficient multi-target control capability, poor real-time performance and lack of feedback control mechanism in existing acoustic particle control technology; the present invention realizes high-precision and stable control of multiple particles in the sound field by constructing a transducer array system with multi-vortex output capability, introducing an adaptive phase encoding algorithm and a real-time visual feedback mechanism, and meeting the higher requirements for flexibility, stability and intelligence in complex micro-operation scenarios.

[0037] Example 1:

[0038] This embodiment proposes a programmable vortex acoustic field multi-objective stable control method, including the following specific steps:

[0039] S1. Generate a multi-vortex sound field through an annular transducer array: Utilizing an annular array consisting of multiple transducers, the phase and amplitude of each transducer are independently controlled by a multi-channel drive system to generate multiple vortex sound beams with controllable spatial distribution;

[0040] In this embodiment, the annular transducer array in S1 is composed of at least 8 planar transducers arranged evenly, and the maximum number of vortices that can be generated is half of the number of transducers. In this embodiment, a multi-channel drive system is used to control the independent excitation of each transducer, and multiple spatially distinguishable vortex beams are constructed through phase and amplitude modulation to achieve flexible and programmable control of the vortex position, number, and intensity. In the process of realizing the off-axis focused multi-vortex sound field, the number of sound sources affects the formation of the sound field. The amplitude of each sound source that forms the off-axis focused multi-vortex can be expressed as The additional phase of each sound source can be expressed as Taking the centrally symmetric vortex array as the research object, it can be seen that the phase shift of each sound source is caused by the superposition of multiple vortices. Due to the central symmetry of M vortices and the circular symmetry of N sound sources, the propagation distance of sound waves to the vortex in all directions is the same, so the superposition effect of sound waves in different directions is similar. After the superposition of sound waves in different directions, obvious periodic changes are formed, and the period is exactly the same as the number of vortices. Therefore, the number of vortices and the transducer array should meet M max =N / 2, this conclusion ensures the accuracy of the phase and the effectiveness of vortex generation.

[0041] S2, Adaptive Phase Coding Control: Based on the number and spatial distribution of target particles, the optimal phase coding matrix of the transducer is calculated through an adaptive phase coding algorithm to dynamically adjust the sound pressure distribution of the vortex sound field;

[0042] In this embodiment, the adaptive phase encoding algorithm in S2 includes the following specific steps:

[0043] S201, determining the additional phase delay of each transducer through geometric calculation according to the target vortex position;

[0044] S202, constructing an objective function to measure the matching degree between the current sound field distribution and the expected sound field;

[0045] S203. Generate an optimal phase coding matrix through iterative optimization, so that the main lobe position and topological characteristics of the sound pressure distribution approach the target configuration.

[0046] In this embodiment, if Figure 3 As shown in the figure, an adaptive phase encoding algorithm is introduced to automatically calculate the optimal phase encoding matrix required for transducer excitation based on the number and spatial distribution characteristics of the target particles, generating a vortex acoustic field with the desired sound pressure distribution. The system can independently set the center positions of multiple vortices, supporting the simultaneous capture, independent control, or coordinated movement path planning and tracking of multiple target particles.

[0047] By calculating the position and distribution of target particles, an optimal phase matrix is generated in real time. An adaptive algorithm dynamically adjusts the phase and amplitude of each transducer based on the real-time particle motion and target position to generate the desired vortex acoustic field. This process first uses an image processing module to acquire the target particle's position information in real time. It then calculates the deviation error of the current particle relative to the predetermined target and adjusts the acoustic field parameters based on these deviations, enabling multiple vortex acoustic fields to act synchronously or independently on different particles. Through this optimization process, particles can accurately move along a predetermined trajectory or remain fixed in a designated position.

[0048] In this embodiment, the principle of multi-target sound field construction and control is as follows: a traditional sound vortex is constructed using a circular sound source array, and the center of the axial vortex sound beam is radially translated to the preset off-axis vortex center. To ensure that this point becomes the vortex center with a spiral phase singularity, each sound source must be given a corresponding additional phase delay, the size of which is determined by the distance change of the sound propagation path. Therefore, through geometric calculation, the phase required for the nth sound source Sn can be obtained as φ n '=φ n +k0ΔR n , where k0ΔR n is the additional phase of the sound source, ΔR n Represents the distance change of the sound propagation path. Then, the sound pressure of the off-axis vortex sound field is obtained by integrating the surface area of the sound source and superimposing the sound pressure of the sound field radiated by N phased sound sources: Further using the linear superposition of multiple off-axis vortex sound fields, the expression of the sound pressure of the composite multi-vortex sound field is obtained: This expression is used in subsequent sound field simulation calculations.

[0049] S3. Real-time monitoring with visual feedback: A high-frame-rate visual inspection system is used to capture real-time motion images of particles within the control area. The position and motion parameters of the particles are extracted through image processing algorithms to determine whether the target deviates from the preset trajectory.

[0050] In this embodiment, the visual detection system in S3 includes a high-speed CMOS camera with a frame rate of not less than 240fps and an image processing module. The image processing module realizes real-time tracking and prediction of particle trajectories through edge detection, contour analysis and Kalman filtering algorithm.

[0051] In this embodiment, a high-frame-rate visual inspection system is built to capture real-time information about the motion state of the particles being manipulated. Using image processing algorithms such as edge detection, feature extraction, and target recognition, key parameters such as particle position and velocity are extracted to determine whether the target deviates from the preset path, providing accurate feedback for subsequent sound field adjustments.

[0052] S4. Closed-loop optimization and control: Based on the particle position deviation based on visual feedback, the phase, amplitude and excitation frequency of the transducer array are dynamically adjusted through an intelligent optimization algorithm to minimize target offset and achieve stable control of multiple target particles.

[0053] In this embodiment, the intelligent optimization algorithm in S4 is a particle swarm optimization algorithm, which minimizes the deviation between the actual position of the particle and the target position by dynamically adjusting the phase and amplitude parameters of the transducer.

[0054] In this embodiment, the principles of vortex acoustic field feedback and optimization are as follows: the visual feedback module uses a high-speed CMOS camera (frame rate not less than 240fps) to collect dynamic images of particles in the control area in real time, and the image processing module uses the Canny edge detection algorithm provided in the OpenCV library to perform image preprocessing, extract the particle edge contour, and identify the particle center of mass coordinates through contour analysis and shape matching algorithm. Subsequently, the coordinate sequence of continuous frames is estimated by the Kalman filter to achieve smooth tracking and prediction of the particle trajectory and obtain the two-dimensional spatial position of the target particle at the current moment. The actual position of the obtained particle is calculated with the preset target position to obtain the target deviation error Δ i =(x i obs -x i tar ) 2 +(y i obs -y i tar ) 2 .

[0055] In this embodiment, the target deviation is used as the objective function and the particle swarm optimization (PSO) algorithm is used to optimize the sound field parameters. Particles update their speed and position in the parameter space, guide the search direction based on the individual historical optimal value and the group global optimal value, and iteratively calculate the optimal excitation parameter matrix: n opt =φ n prev +v n ,A n opt =A n prev +u n , where φ n and A n represent the optimal phase and amplitude of the nth transducer, v n and u nThe velocity term is dynamically adjusted by the particle swarm. Finally, the updated parameters are sent to the signal generation and control module, driving the annular transducer array to emit a new vortex acoustic field, ensuring stable convergence of the target particles to the preset position. This process continues in a cycle, forming a closed-loop control system of "visual acquisition - deviation calculation - parameter optimization - acoustic field update," enabling high-precision dynamic manipulation of multiple target particles.

[0056] Example 2:

[0057] This embodiment proposes a programmable vortex acoustic field multi-objective stable control system, including: a ring transducer array module, a signal generation and control module, a visual feedback module, and a central control unit;

[0058] The annular transducer array module is used to generate a multi-vortex sound field;

[0059] The signal generation and control module is used to independently control the phase and amplitude of each transducer;

[0060] The visual feedback module is used to monitor the particle motion state in real time;

[0061] The central control unit is used to coordinate signal transmission and control between modules.

[0062] In this embodiment, the annular transducer array module adopts a multi-layer PCB board integrated design, and the transducers are evenly distributed on the circumference, and the phase and amplitude are independently adjustable.

[0063] In this embodiment, the visual feedback module includes a high-speed CMOS camera and a real-time image processing component. The image processing component realizes high-precision extraction of particle positions and trajectory prediction based on the OpenCV library.

[0064] like Figure 1 As shown, in this embodiment, the system architecture mainly includes a ring transducer array module, a signal generation and control module, a visual feedback module and a central control unit. The ring transducer array module consists of 16 planar piston transducers, each with a diameter of 2.5 mm, evenly arranged on a circle with a radius of 30 mm. The center frequency of each transducer is 500 kHz, the surface vibration velocity of the sound source is u0 = 60 mm / s, and the vertical distance from the liquid surface to the transducer surface is controlled to be 200 mm. The signal generation and control module is responsible for generating and controlling the excitation signal of the transducer, so that each transducer can independently adjust the phase and amplitude.

[0065] The visual feedback module uses a high-speed CMOS camera to capture real-time dynamic images of particles within the control area. The image processing module extracts the particle position information and feeds it back to the central control unit. The system then adjusts the sound field parameters in real time based on this feedback. The central control unit coordinates the work of each module, executes the optimization algorithm, and adjusts the transducer excitation signal to ensure stable control of multiple target particles.

[0066] In this embodiment, if Figure 2 As shown in the figure, the annular transducer array generates multiple controllable vortex beams through phase control. The phase delay of each transducer is determined by geometric calculations, ensuring that multiple vortex beams produce precise vortex centers in the water and can adjust the number and topological charge of vortices according to control requirements. In the experiment, the centrosymmetric arrangement of the 16 transducers makes the phase delay of each sound source closely related to the distance change of the propagation path. The calculation formula is: n =ΔR n k. Through this phase adjustment, the system can generate multiple vortex acoustic beams in water, enabling independent or coordinated manipulation of multiple particles. The advantage of this method lies in its high flexibility and programmability, allowing the topology and parameters of the acoustic field to be adjusted according to actual application requirements.

[0067] In this embodiment, if Figure 4 As shown, the visual feedback system uses a high-speed CMOS camera to capture dynamic images of particles in real time, and uses image processing algorithms to extract the precise position and motion state of the particles. The image processing module performs edge detection, target recognition and shape analysis on the original image, and calculates the spatial coordinates of the particles in real time. The system uses a feedback control mechanism to update the excitation parameters of the vortex acoustic field in real time based on the deviation information of the particles. The feedback control part is implemented through the particle swarm optimization (PSO) algorithm, which calculates the deviation between the particle and the target position and adjusts the excitation signal of the transducer in real time to minimize the error and ensure that the particle is stable at the target position. This closed-loop control system ensures that the particles can move accurately to the target position and adjusts the path in real time to prevent the particles from deviating or colliding.

[0068] In this embodiment, if Figure 5 As shown in the figure, the experiment verified the effectiveness of the method of the present invention in multi-target manipulation. In the experiment, the manipulated particles were polyethylene spherical particles with a density slightly lower than that of water and a diameter between 0.6mm and 1.2mm. The manipulation effects of two groups (2 particles and 4 particles) in different vortex sound fields were tested separately. During the experiment, under the action of the vortex sound field, the particles were able to move precisely along the predetermined trajectory, and multiple particles could be manipulated independently or collaboratively at the same time, successfully avoiding interference and collision between particles.

[0069] The system uses visual feedback to monitor particles in real time and employs a feedback optimization algorithm to dynamically adjust the particles to ensure they remain at their target locations. Experimental results demonstrate that the method demonstrates excellent precision and stability in manipulating multiple target particles.

[0070] It should be noted here that by constructing a transducer array system with multi-vortex output capability, introducing an adaptive phase encoding algorithm and a real-time visual feedback mechanism, high-precision and stable control of multiple particles in the acoustic field can be achieved, meeting the higher requirements for flexibility, stability and intelligence in complex micro-operation scenarios.

Claims

1. A programmable vortex acoustic field multi-target stable control method, characterized by: The specific steps include: S1. Generate a multi-vortex sound field through an annular transducer array: Utilizing an annular array consisting of multiple transducers, the phase and amplitude of each transducer are independently controlled by a multi-channel drive system to generate multiple vortex sound beams with controllable spatial distribution; S2, Adaptive Phase Coding Control: Based on the number and spatial distribution of target particles, an adaptive phase coding algorithm is used to generate the optimal phase coding matrix of the transducer, dynamically adjusting the sound pressure distribution of the vortex sound field; S3. Real-time monitoring with visual feedback: A high-frame-rate visual inspection system is used to capture real-time motion images of particles within the control area, and the position and motion parameters of the particles are extracted through image processing algorithms. S4. Closed-loop optimization and control: Based on the particle position deviation based on visual feedback, the phase, amplitude and excitation frequency of the transducer array are dynamically adjusted through an intelligent optimization algorithm to minimize target offset and achieve stable control of multiple target particles.

2. The method for multi-objective stable control of a programmable vortex acoustic field according to claim 1, characterized in that: The annular transducer array in S1 is composed of at least 8 planar transducers arranged evenly, and the maximum number of vortices that can be generated is half of the number of transducers.

3. The method for multi-objective stable control of a programmable vortex acoustic field according to claim 2, characterized in that: The S2 includes the following specific steps: S201, constructing a traditional acoustic vortex using a ring-shaped sound source array, and translating the center of the along-axis vortex sound beam radially to a preset off-axis vortex center; S202, determine the additional phase delay of the transducer; obtain the phase required by the nth sound source Sn as φ through geometric calculation n '=φ n +k0ΔR n , where k0ΔR n is the additional phase of the sound source, ΔR n Represents the distance change of the sound propagation path; S203. Integrate the surface area of the sound source and superimpose the sound pressure of the off-axis vortex sound field by the sound pressure of the sound fields radiated by N phase-controlled sound sources to obtain: S204. Using the linear superposition of multiple off-axis vortex sound fields, the expression of the sound pressure of the composite multi-vortex sound field is obtained: S205. Automatically generate an optimal phase encoding matrix through iterative optimization, so that the main lobe position and topological characteristics of the sound pressure distribution approach the target configuration.

4. The method for multi-objective stable control of a programmable vortex acoustic field according to claim 3, characterized in that: The visual detection system in S3 includes a high-speed CMOS camera with a frame rate of not less than 240fps and an image processing module. The image processing module realizes particle position detection and real-time tracking through edge detection, contour analysis and Kalman filtering algorithm.

5. The method for multi-objective stable control of a programmable vortex acoustic field according to claim 4, characterized in that: The intelligent optimization algorithm in S4 is a particle swarm optimization algorithm, which minimizes the deviation between the actual position of the particle and the target position by dynamically adjusting the phase and amplitude parameters of the transducer. The calculation formula of the target deviation error is: Δ i =(x i obs -x i tar ) 2 +(y i obs -y i tar ) 2 . .

6. A programmable vortex acoustic field multi-objective stable control system, implemented based on a programmable vortex acoustic field multi-objective stable control method according to any one of claims 1 to 5, characterized in that: include: Ring transducer array module, signal generation and control module, visual feedback module, and central control unit; The annular transducer array module is used to generate a multi-vortex sound field; The signal generation and control module is used to independently control the phase and amplitude of each transducer; The visual feedback module is used to monitor the particle motion state in real time; The central control unit is used to coordinate signal transmission and control between modules.

7. The programmable vortex acoustic field multi-objective stable control system according to claim 6, characterized in that: The annular transducer array module adopts a multi-layer PCB board integrated design, and each transducer is evenly distributed on the circumference, and the phase and amplitude are independently adjustable.

8. The programmable vortex acoustic field multi-objective stable control system according to claim 6, characterized in that: The visual feedback module includes a high-speed CMOS camera and a real-time image processing component. The image processing component realizes high-precision extraction of particle positions and trajectory prediction based on the OpenCV library.

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