Focusing transducer focus searching system based on machine vision and optimization algorithm

Abstract

The invention provides a focusing transducer focus searching system based on machine vision and an optimization algorithm. The focusing transducer focus searching system based on the machine vision and the optimization algorithm comprises a machine vision processing module and a path optimization module. The geometric center of the transducer is moved to the position coaxial with the probe hydrophone through the machine vision processing module, the position serves as the initial focus measurement position, and then the optimal path is selected through the path optimization module by using an optimization algorithm for focus measurement. Compared with a traditional grid type scanning method for scanning the whole sound field, the machine vision processing module enables the geometric center of the transducer and the probe hydrophone to be coaxial, the scanning range is reduced, the path optimization module uses an optimization algorithm to reduce the number of collection points, data redundancy is avoided, and meanwhile time is saved.

Description

Technical Field

[0001] The invention relates to the technical field of ultrasonic measurement and testing, and in particular to a system for finding a focus of an ultrasonic focusing transducer based on machine vision and an optimization algorithm. Background Art

[0002] Ultrasonic transducer refers to an electroacoustic transducer, whose function is to realize the conversion between electrical energy and acoustic energy. Specifically, it is an energy converter that converts alternating electrical signals into acoustic signals within the ultrasonic frequency range or converts acoustic signals in an external sound field into electrical signals. As a type of ultrasonic transducer, focused ultrasonic transducer has been produced in the development of medical ultrasound in recent years. In the field of tumor treatment, high-intensity ultrasonic waves are required, and ultrasonic focused transducers can gather the energy of ultrasonic waves to form a small high-intensity area, which is called a focus or focal spot. The energy, sound pressure, and sound intensity at the focal spot can reach maximum.

[0003] In actual use, it is necessary to determine the position of the focus of the ultrasonic focusing transducer. The commonly used method is the grid scanning method. A hydrophone is a sensor for detecting acoustic signals underwater. Common hydrophones include probe hydrophones and thin film hydrophones. The grid scanning method uses a hydrophone to collect sound pressure signals at spatial positions in a fixed moving step length on the x, y, and z axes within a defined spatial range. After recording the signals collected at each spatial position, the area with the largest sound pressure is the focus. The advantage of this method is that it can accurately find the position of the focus, but due to the huge number of points that need to be collected, it takes a long time. Summary of the invention

[0004] In view of this, an object of the present invention is to provide a method for quickly finding the focus of an ultrasonic focusing transducer, thereby improving efficiency and reducing time cost.

[0005] Based on the above purpose, a focusing transducer focus finding system based on machine vision and optimization algorithm is characterized by comprising:

[0006] The water tank is used to build the entire system framework and create a sound field;

[0007] An ultrasonic focusing transducer for outputting ultrasonic waves and focusing them on a focal area;

[0008] A probe hydrophone, fixed to the water tank, for receiving acoustic signals and converting them into readable voltage signals;

[0009] A three-dimensional self-propelled mechanism, connected to the transducer, for moving the transducer and locating the spatial position of the transducer;

[0010] a camera, fixed to the water tank, for capturing a front image of the transducer for image processing;

[0011] A machine vision processing module, connected to the camera, used to locate the geometric center point of the front of the transducer, connected to the three-dimensional self-propelled mechanism, and move the geometric center of the transducer to a coaxial position with the probe hydrophone;

[0012] The path optimization module is connected to the three-dimensional self-propelled mechanism, and selects the optimal measurement path to find the sound pressure peak point through an optimization algorithm according to the instantaneous sound pressure values ​​of the current spatial position and the surrounding spatial positions within a set spatial range.

[0013] Optionally, in the focusing transducer focus search system, the process of locating the geometric center point of the front face of the transducer is as follows:

[0014] The camera is calibrated first. The reference point is determined, and the distance between the reference point and the tip of the probe hydrophone in the z direction is determined, and the reference point and the tip of the probe hydrophone are ensured to be coaxial in the z direction. The exposure is automatically adjusted to select the appropriate image, the outline of the focused ultrasonic transducer in the image is identified, the outline of the focused ultrasonic transducer found is fitted, and the coordinates of the geometric center are obtained by conversion based on the calibration data.

[0015] Optionally, in the focusing transducer focus search system, the process of moving the geometric center of the transducer to a coaxial position with the probe hydrophone is as follows:

[0016] The coordinates of the geometric center after machine vision processing are recorded, the y-axis coordinate is moved to make the geometric center of the ultrasonic focusing transducer consistent with the y-axis coordinate of the camera reference point, and then the z-axis coordinate is moved to make the geometric center of the ultrasonic focusing transducer consistent with the z-axis coordinate of the tip of the probe hydrophone.

[0017] Optionally, in the focusing transducer focus search system, the process of selecting the optimal measurement path to find the sound pressure peak point within the set spatial range according to the instantaneous sound pressure values ​​of the current spatial position and the surrounding spatial positions through an optimization algorithm is as follows:

[0018] A three-dimensional self-propelled mechanism is used to locate the geometric center of the ultrasonic focusing transducer processed by machine vision to a position coaxial with the probe hydrophone, and the distance between the two is placed at the theoretical focal distance.

[0019] The optimized path module is used to calculate the optimal path for sound field scanning based on the instantaneous sound pressure value around the current measurement point obtained by the probe hydrophone within the set range using the path optimization algorithm, and the optimal path is used as the planned measurement path for rapid focusing measurement of the actual sound field ultrasonic focus.

[0020] Optionally, in the focusing transducer focus search system, the optimization algorithm may be a hill climbing algorithm, a steepest algorithm, a simulated annealing algorithm, a particle swarm algorithm or the following algorithms:

[0021] First, start from the boundary of the set spatial range, collect sound field data along the y-axis, record the sound pressure value at each position, then start from the center of the two points with the highest sound pressure to collect sound field data within the set spatial range along the x-axis, record the sound pressure value at each position, and start from the center of the two points with the highest sound pressure to collect sound field data within the set spatial range along the y-axis. Repeat the above operation until the sound pressure value increase is lower than the set sound pressure increase, and complete the xy plane acquisition. Then move the z-axis within the set spatial range, select the point with the maximum sound pressure on the z-axis at this time as the focus, and complete the acquisition.

[0022] Optionally, in the focusing transducer focus search system, the three-dimensional self-propelled mechanism includes:

[0023] Three sliding rails are arranged above the water tank;

[0024] A rotating clamping component is arranged on the sliding track and can move along the sliding track to clamp and fix the ultrasonic focusing transducer and adjust the clamping direction;

[0025] The servo motor is connected to the rotating clamping component and the sliding track, and is used to drive the rotating clamping component to move along the moving direction of the sliding track and adjust the clamping direction to adjust the spatial position of the ultrasonic focusing transducer.

[0026] Optionally, in the focusing transducer focus-finding system, the three-dimensional self-propelled mechanism system has three rectangular coordinate translation axis degrees of freedom and two rotational degrees of freedom, and the ultrasonic focusing transducer remains coaxial or parallel to a translation axis of the three-dimensional self-propelled mechanism.

[0027] Optionally, in the focusing transducer focus-finding system, the three-dimensional self-propelled mechanism can be connected to a computer to realize automated operation, and the input coordinates can automatically move to a set spatial position. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The accompanying drawings are only used to provide a further understanding of the present invention and do not constitute a part of the specification.

[0029] The embodiments of the present invention are used to explain the present invention, but are not intended to limit the present invention.

[0030] Figure 1 Schematic diagram of the structure of a focusing transducer focus search system based on machine vision and optimization algorithm in an embodiment of the present invention;

[0031] Figure 2 A perspective view of a focusing transducer focus search system based on machine vision and optimization algorithm in an embodiment of the present invention;

[0032] Figure 3A reference point position diagram of a camera in a focusing transducer focus search system based on machine vision and optimization algorithm in an embodiment of the present invention;

[0033] Figure 4 It is a flow chart of a machine vision processing module in a focusing transducer focus search system based on machine vision and optimization algorithm in an embodiment of the present invention;

[0034] Figure 5 It is a flow chart of an optimization path module in a focusing transducer focus search system based on machine vision and optimization algorithm in an embodiment of the present invention;

[0035] Figure 6 Practical Figure 5 Schematic diagram of an optimization algorithm for a focusing transducer focus-finding system based on machine vision and optimization algorithm in one of the embodiments of the present invention. DETAILED DESCRIPTION

[0036] The following is a further detailed description of a focusing transducer focus search system based on machine vision and optimization algorithm proposed by the present invention in combination with the accompanying drawings and specific embodiments. The advantages and features of the present invention will become clearer according to the following description and claims. It should be noted that the accompanying drawings are not in precise proportions and are only used to conveniently and clearly assist in explaining the purpose of the embodiments of the present invention.

[0037] The following is an explanation of the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the present embodiment only illustrate the basic concept of the present invention in a schematic manner, and only the components related to the present invention are shown in the figure instead of being drawn according to the number, shape and size of the components in the actual implementation. The type, quantity and proportion of each component in the actual implementation can be a random change, and the component layout type may also be more complicated.

[0038] Certain terms are used throughout the specification and claims to refer to specific system components. As will be appreciated by those skilled in the art, different companies may refer to a component by different names. It is not intended herein to distinguish between components that have different names but the same function. In the specification and claims, the terms "include" and "comprising" are used in an open-ended manner and, therefore, should be interpreted as "including, but not limited to ...".

[0039] As shown in this application and claims, unless the context clearly indicates an exception, the words "a", "an", "an" and / or "the" do not refer to the singular and may also include the plural. Generally speaking, the terms "include" and "comprise" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0040] In addition, each embodiment of the following description has one or more technical features, but this does not mean that the user of the present invention must implement all the technical features in any embodiment at the same time, or can only implement part or all of the technical features in different embodiments separately. In other words, under the premise that implementation is possible, those skilled in the art can selectively implement part or all of the technical features in any embodiment according to the disclosure of the present invention and according to the design specifications or implementation requirements, or selectively implement a combination of part or all of the technical features in multiple embodiments, thereby increasing the flexibility of the implementation of the present invention.

[0041] In order to make the purpose and features of the present invention more obvious and understandable, the specific implementation methods of the present invention are further described below in conjunction with the accompanying drawings. However, the present invention can be implemented in different forms and should not be considered to be limited to the described embodiments.

[0042] This embodiment provides a focusing transducer focus search system based on machine vision and optimization algorithm, which uses a camera to perform machine vision processing to find the geometric center of the focusing transducer, uses a three-dimensional self-propelled mechanism to make the ultrasonic focusing transducer coaxial with the probe hydrophone, and then uses the optimization algorithm to determine the specific focus search route to find the focus of the ultrasonic focusing transducer. The system can conveniently and quickly realize the positioning of the focus position of the focusing transducer.

[0043] Figure 1 FIG. 1 is a structural schematic diagram of a focusing transducer focus search system based on machine vision and optimization algorithm of the present invention. Figure 1As shown, the focusing transducer focusing system based on machine vision and optimization algorithm includes: a water tank, a focused ultrasonic transducer, a probe hydrophone, a three-dimensional self-propelled mechanism, a camera, a machine vision processing module, and an optimization path module. The water tank is used to build the entire system framework to construct a sound field; the focused ultrasonic transducer is used to output ultrasonic waves and focus them on the focal area; the probe hydrophone is fixed to the water tank and is used to receive sound signals and convert them into readable voltage signals; the three-dimensional self-propelled mechanism is connected to the transducer and is used to move the transducer and locate the spatial position of the transducer; the camera is fixed to the water tank and is used to take the front image of the transducer for image processing; the machine vision processing module is connected to the camera and is used to locate the geometric center point position of the front of the transducer, and is connected to the three-dimensional self-propelled mechanism to move the geometric center of the transducer to a coaxial position with the probe hydrophone; the optimization path module is connected to the three-dimensional self-propelled mechanism and selects the optimal measurement path to find the sound pressure peak point according to the instantaneous sound pressure values ​​of the current spatial position and the surrounding spatial positions within the set spatial range through the optimization algorithm.

[0044] Figure 2 FIG. 1 is a perspective view of a focusing transducer focus search system based on machine vision and optimization algorithm of the present invention. Figure 2 As shown, the three-dimensional self-propelled mechanism includes: three sliding rails, a rotating clamping component, and a servo motor. The three sliding rails are arranged above the water tank; the rotating clamping component is arranged on the sliding rails and can move along the sliding rails to clamp and fix the ultrasonic focusing transducer and adjust the clamping direction; the servo motor is connected to the rotating clamping component and the sliding rails, and is used to drive the rotating clamping component to move along the movement direction of the sliding rails and adjust the clamping direction to adjust the spatial position of the ultrasonic focusing transducer.

[0045] Specifically, the three-dimensional self-propelled mechanism is capable of performing three rectangular coordinate translations and one rotational degree of freedom, and the ultrasonic focusing transducer remains coaxial or parallel to a certain translation axis of the three-dimensional self-propelled mechanism.

[0046] Figure 3 This is a reference point position diagram of a camera in a focusing transducer focus search system based on machine vision and optimization algorithm in an embodiment of the present invention. The reference point is coaxial with the tip of the probe hydrophone in the z direction and the distance is fixed and known.

[0047] Figure 4 This is a flow chart of a machine vision processing module in a focusing transducer focus search system based on machine vision and optimization algorithm in an embodiment of the present invention; the machine vision processing module can move the geometric center of the transducer to a coaxial position with the probe hydrophone. Figure 4As shown, the camera calibration is a pre-processing of coordinate transformation before analyzing and processing the image, and the intrinsic and extrinsic parameters of the camera, as well as the distortion parameters, are obtained to determine the accurate relationship between the 3D point in the real world and its corresponding 2D projection (pixel) in the image captured by the calibration camera. The automatic exposure adjustment can be based on a sector area grayscale average value and an image entropy threshold as the optimization conditions, and the camera exposure time is adjusted. When the image area where the transducer is located meets the optimal area grayscale average value interval and is greater than the specified image entropy threshold, the best image can be obtained, and then the circular contour of the ultrasonic focusing transducer is identified, the geometric center point of the transducer is fitted, and the spatial position of the geometric center point is recorded.

[0048] Figure 5 The present invention is a flow chart of a focusing transducer focus search system based on machine vision and optimization algorithm in an embodiment of the present invention. First, the coordinate position of the geometric center point of the transducer is determined by the machine vision processing module. Then, the y-axis coordinate is moved so that the geometric center of the ultrasonic focusing transducer is consistent with the y-axis coordinate of the camera reference point. Then, the z-axis coordinate is moved so that the geometric center of the ultrasonic focusing transducer is consistent with the z-axis coordinate of the tip of the probe hydrophone. At this time, the geometric center point of the transducer is coaxial with the probe hydrophone, and the distance between the two is placed at the theoretical focal distance. Then, through the optimization path module, according to the instantaneous sound pressure collected by the probe hydrophone at the spatial position point at this time and the instantaneous sound pressure of the surrounding points, the optimization algorithm is selected to obtain the optimal path for focus search. Finally, the ultrasonic focusing transducer position is moved according to the optimal path through the three-dimensional self-propelled mechanism to collect the current instantaneous sound pressure until the algorithm determines that the spatial position point at this time is the focus.

[0049] Specifically, the selected algorithm can be a hill climbing algorithm, a steepest algorithm, a simulated annealing algorithm, a particle swarm algorithm, or Figure 6 The algorithm.

[0050] Figure 6 Schematic diagram of an optimization algorithm for a focusing transducer focus-finding system based on machine vision and optimization algorithm in one of the embodiments of the present invention.

[0051] Specifically, start from the boundary of the set spatial range, collect sound field data along the y-axis, record the sound pressure value at each position, and then collect sound field data along the x-axis within the set spatial range from the center of the two points with the highest sound pressure, record the sound pressure value at each position, and collect sound field data along the y-axis within the set spatial range from the center of the two points with the highest sound pressure. Repeat the above operation until the sound pressure value increase is lower than the set sound pressure increase, and complete the xy plane acquisition. Then move the z-axis within the set spatial range, select the point with the maximum sound pressure on the z-axis at this time as the focus, and complete the acquisition.

[0052] The above description is only a description of the preferred embodiments of the present invention, and is not intended to limit the scope of the present invention. Any changes or modifications made by a person skilled in the art in the field of the present invention based on the above disclosure shall fall within the scope of protection of the claims.

Claims

1. A focusing transducer focus search system based on machine vision and optimization algorithm, characterized in that: include: The water tank is used to build the entire system framework and create a sound field; A focused ultrasound transducer for outputting ultrasound waves and focusing them on a focal area; A probe hydrophone, fixed to the water tank, for receiving acoustic signals and converting them into readable voltage signals; A three-dimensional self-propelled mechanism, connected to the transducer, for moving the transducer and locating the spatial position of the transducer; a camera, fixed to the water tank, for capturing a front image of the transducer for image processing; A machine vision processing module, connected to the camera, used to locate the geometric center point of the front of the transducer, connected to the three-dimensional self-propelled mechanism, and move the geometric center of the transducer to a coaxial position with the probe hydrophone; The path optimization module is connected to the three-dimensional self-propelled mechanism, and selects the optimal measurement path to find the sound pressure peak point through an optimization algorithm according to the instantaneous sound pressure values ​​of the current spatial position and the surrounding spatial positions within a set spatial range.

2. A focusing transducer focus search system based on machine vision and optimization algorithm as claimed in claim 1, characterized in that: The process of locating the geometric center point of the front face of the transducer is as follows: First, calibrate the camera, determine the reference point, determine the distance between the reference point and the tip of the probe hydrophone in the z direction, and ensure that the reference point and the tip of the probe hydrophone remain coaxial in the z direction. Automatically adjust the exposure to shoot and select the appropriate image, identify the outline of the focused ultrasonic transducer in the image, fit the found focused ultrasonic transducer outline, and convert it according to the calibration data to obtain the coordinates of the geometric center.

3. A focusing transducer focus search system based on machine vision and optimization algorithm as claimed in claim 1, characterized in that: The process of moving the geometric center of the transducer to a coaxial position with the probe hydrophone is as follows: The coordinates of the geometric center after machine vision processing are recorded, the y-axis coordinate is moved to make the geometric center of the ultrasonic focusing transducer consistent with the y-axis coordinate of the camera reference point, and then the z-axis coordinate is moved to make the geometric center of the ultrasonic focusing transducer consistent with the z-axis coordinate of the tip of the probe hydrophone.

4. A focusing transducer focus search system based on machine vision and optimization algorithm as claimed in claim 1, characterized in that: The process of selecting the optimal measurement path to find the sound pressure peak point within the set space range according to the instantaneous sound pressure values ​​of the current space position and the surrounding space positions through the optimization algorithm is as follows: A three-dimensional self-propelled mechanism is used to locate the geometric center of the ultrasonic focusing transducer processed by machine vision to a position coaxial with the probe hydrophone, and the distance between the two is placed at the theoretical focal distance. The optimized path module is used to calculate the optimal path for sound field scanning based on the instantaneous sound pressure values ​​of the current measurement point and surrounding measurement points obtained by the probe hydrophone within the set range, and the optimal path is used as the planned measurement path for rapid focusing measurement of the actual sound field ultrasonic focus.

5. The focusing transducer focus search system based on machine vision and optimization algorithm as claimed in claim 1, characterized in that: In the focusing transducer focus search system, the three-dimensional self-propelled mechanism comprises: Three sliding rails are arranged above the water tank; A rotating clamping component is arranged on the sliding track and can move along the sliding track to clamp and fix the ultrasonic focusing transducer and adjust the clamping direction; The servo motor is connected to the rotating clamping component and the sliding track, and is used to drive the rotating clamping component to move along the moving direction of the sliding track and adjust the clamping direction to adjust the spatial position of the ultrasonic focusing transducer.

6. A focusing transducer focus search system based on machine vision and optimization algorithm as claimed in claim 5, characterized in that: The three-dimensional self-propelled mechanism system has three rectangular coordinate translation axis degrees of freedom and two rotational degrees of freedom, and the ultrasonic focusing transducer is coaxial or parallel to a certain translation axis of the three-dimensional self-propelled mechanism.

7. A focusing transducer focus search system based on machine vision and optimization algorithm as claimed in claim 5, characterized in that: In the focusing transducer focus search system, the three-dimensional self-propelled mechanism can be connected to a computer to realize automatic operation, and the input coordinates can automatically move to the set spatial position.

8. The focusing transducer focus search system based on machine vision and optimization algorithm as claimed in claim 4, characterized in that: One of the optimization path algorithms is as follows: First, start from the boundary of the set spatial range, collect sound field data along the y-axis, record the sound pressure value at each position, then start from the center of the two points with the highest sound pressure to collect sound field data within the set spatial range along the x-axis, record the sound pressure value at each position, and start from the center of the two points with the highest sound pressure to collect sound field data within the set spatial range along the y-axis. Repeat the above operation until the sound pressure value increase is lower than the set sound pressure increase, and complete the xy plane acquisition. Then move the z-axis within the set spatial range, select the point with the maximum sound pressure on the z-axis at this time as the focus, and complete the acquisition.

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