Ultrasonic image processing method, automobile part processing equipment and medium program

Abstract

The invention provides an ultrasonic image processing method, automobile part processing equipment and a medium program, and is applied to the automobile part processing equipment which comprises an ultrasonic sensor. The method comprises the steps that target relative position parameters between the automobile part machining equipment and a target object are determined through the ultrasonic sensor; determining a first working parameter corresponding to the target relative position parameter; and controlling the ultrasonic sensor to work according to the first working parameter to obtain a first image of the target object. By adopting the method, the ultrasonic imaging effect of the automobile part machining equipment can be improved, so that the welding spot recognition accuracy is improved.

Description

Technical Field

[0001] The present application relates to the fields of automobile parts processing technology and image processing technology, and in particular to an ultrasonic image processing method, automobile parts processing equipment and a medium program. Background Art

[0002] In practical applications, ultrasound can not only be used for positioning, but also for ultrasonic imaging. At present, ultrasonic imaging technology is also widely used in life. However, the ultrasonic imaging effect is not good, especially in the processing of automotive parts. The poor ultrasonic imaging effect often leads to a low yield rate of automotive parts. For example, when identifying solder joints, the solder joint recognition accuracy is low, resulting in poor processing accuracy, which in turn causes the yield rate of automotive parts to be too low. Therefore, how to improve the ultrasonic imaging effect of automotive parts processing equipment to improve the accuracy of solder joint recognition needs to be solved urgently. Summary of the invention

[0003] The embodiments of the present application provide an ultrasonic image processing method, an automobile parts processing equipment, and a medium program, which can improve the ultrasonic imaging effect of the automobile parts processing equipment to improve the accuracy of welding point recognition.

[0004] In a first aspect, an embodiment of the present application provides an ultrasonic image processing method, which is applied to automobile parts processing equipment, wherein the automobile parts processing equipment includes an ultrasonic sensor, and the method includes: Determine the target relative position parameters between the automobile parts processing equipment and the target object by the ultrasonic sensor; the target object includes a suspected welding point or a position or area specified by the user; Determining a first operating parameter corresponding to the target relative position parameter; Controlling the ultrasonic sensor to operate with the first operating parameter to obtain a first image of the target object; determining a first low-frequency component portion and a first high-frequency component portion of the first image; determining a first energy value of the first low-frequency component portion and a second energy value of the first image; determining a target ratio between the first energy value and the second energy value; When the target ratio is not within the preset range, determining a first deviation between the target ratio and the preset range; Adjusting the first operating parameter according to the first deviation to obtain a second operating parameter; Controlling the ultrasonic sensor to operate with the second operating parameter to obtain a second image of the target object; determining a first characteristic distribution density according to the first high frequency component portion; Determining a first image enhancement processing parameter corresponding to the first feature distribution density; Performing image enhancement processing on the second image according to the first image enhancement processing parameters to obtain a target image; Performing image segmentation on the area where the target object is located in the target image to obtain a target area; A feature set of the target area is obtained, and welding spot recognition is performed according to the feature set.

[0005] In a second aspect, an embodiment of the present application provides an ultrasonic image processing device, which is applied to automobile parts processing equipment, wherein the automobile parts processing equipment includes an ultrasonic sensor, and the device includes: a determination unit, a control unit, an adjustment unit, and an enhancement unit, wherein: The determining unit is used to determine the target relative position parameter between the automobile parts processing equipment and the target object through the ultrasonic sensor; and determine the first working parameter corresponding to the target relative position parameter; The control unit is used to control the ultrasonic sensor to operate with the first operating parameter to obtain a first image of the target object; The determining unit is further configured to determine a first low-frequency component part and a first high-frequency component part of the first image; determine a first energy value of the first low-frequency component part and a second energy value of the first image; determine a target ratio between the first energy value and the second energy value; and when the target ratio is not within a preset range, determine a first deviation between the target ratio and the preset range; The adjustment unit is further used to adjust the first operating parameter according to the first deviation to obtain a second operating parameter; The control unit is further used to control the ultrasonic sensor to operate with the second operating parameter to obtain a second image of the target object; The determining unit is further used to determine a first characteristic distribution density according to the first high-frequency component part; and determine a first image enhancement processing parameter corresponding to the first characteristic distribution density; The enhancement unit is used to perform image enhancement processing on the second image according to the first image enhancement processing parameters to obtain a target image; The segmentation unit is used to perform image segmentation on the area where the target object is located in the target image to obtain the target area; The recognition unit is used to obtain a feature set of the target area and perform welding point recognition according to the feature set.

[0006] In the third aspect, an embodiment of the present application provides an automobile parts processing equipment, including a processor, a memory, a communication interface and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps in the first aspect of the embodiment of the present application.

[0007] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps described in the first aspect of the embodiment of the present application.

[0008] In a fifth aspect, an embodiment of the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps described in the first aspect of the embodiment of the present application. The computer program product may be a software installation package.

[0009] The implementation of the embodiments of the present application has the following beneficial effects: It can be seen that the ultrasonic image processing method and related devices described in the embodiments of the present application are applied to automobile parts processing equipment, which includes an ultrasonic sensor, and the target relative position parameters between the automobile parts processing equipment and the target object are determined by the ultrasonic sensor; the target object includes a suspected welding point or a position or area specified by the user; a first working parameter corresponding to the target relative position parameter is determined; the ultrasonic sensor is controlled to work with the first working parameter to obtain a first image of the target object; a first low-frequency component part and a first high-frequency component part of the first image are determined; a first energy value of the first low-frequency component part and a second energy value of the first image are determined; a target ratio between the first energy value and the second energy value is determined; when the target ratio is not within a preset range, a first deviation between the target ratio and the preset range is determined; the first working parameter is adjusted according to the first deviation to obtain a second working parameter; the ultrasonic sensor is controlled to work with the second working parameter to obtain a second image of the target object; a first feature distribution density is determined according to the first high-frequency component part; a first image enhancement processing parameter corresponding to the first feature distribution density is determined;The second image is enhanced according to the first image enhancement processing parameter to obtain a target image, the area where the target object is located in the target image is segmented to obtain the target area, the feature set of the target area is obtained, and the welding point is identified according to the feature set. First, the corresponding first working parameter can be configured based on the target relative position parameter between the ultrasonic sensor and the target object, so that the working parameter depth of the ultrasonic sensor conforms to the actual environment. Second, ultrasonic imaging is performed using the first working parameter to obtain a first image, wherein the first low-frequency component part reflects the basic structure of the image, and the first high-frequency component part reflects the detailed information of the image. If the energy proportion of the first low-frequency component part is too high, more details will be covered up. If the energy proportion of the first low-frequency component part is too low, the basic structure of the image will be unclear. Therefore, it is necessary to ensure that the first low-frequency component part is within a reasonable range, and the energy proportion of the first low-frequency component part is not within a reasonable range. If the first working parameter is within the reasonable range, it is necessary to dynamically adjust the first working parameter based on the degree of deviation so that the energy proportion of the low-frequency component of the image returns to a reasonable range. Then, after adjustment, the second working parameter is obtained. Third, the second working parameter is used for ultrasonic imaging to obtain a second image. Since the working parameter adjustment has a certain degree of influence on the high-frequency and low-frequency parts of the image, in order to suppress excessive image adjustment or under-enhancement, the second image is adjusted based on the characteristic distribution in the first high-frequency component of the first image to obtain the final target image, so that the final ultrasonic imaging depth conforms to the actual situation and prevents the image from being over-enhanced or under-enhanced. Fourth, since the ultrasonic imaging depth conforms to the actual situation, it can ensure that the depth of the regional image of the target object also conforms to the actual situation, which helps to ensure the accuracy of welding spot recognition. In this way, the ultrasonic imaging effect of automobile parts processing equipment can be improved to improve the accuracy of welding spot recognition. ; BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0011] Figure 1 It is a flowchart of an ultrasonic image processing method provided in an embodiment of the present application; Figure 2 It is a structural schematic diagram of an automobile parts processing equipment provided in an embodiment of the present application; Figure 3 It is a block diagram of the functional units of an ultrasonic image processing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0012] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but in a possible example also includes steps or units that are not listed, or in a possible example also includes other steps or units inherent to these processes, methods, products or devices.

[0013] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0014] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0015] The automobile parts processing equipment involved in the embodiments of the present application may include but is not limited to: automobile parts processing machine tools, ultrasonic welding guns, etc., which are not limited here.

[0016] For example, taking an automobile parts processing machine tool as an example, in actual applications, ultrasonic imaging is often required for weld spot detection. For example, whether there is a weld spot at a certain position or if there is a weld spot, whether the weld spot is a cold weld is identified. The accuracy of weld spot identification determines the processing accuracy of the automobile parts processing machine tool. The embodiment of the present application provides an ultrasonic image processing method, which is applied to automobile parts processing equipment, and the automobile parts processing equipment includes an ultrasonic sensor. The method includes: Determine the target relative position parameters between the automobile parts processing equipment and the target object by the ultrasonic sensor; the target object includes a suspected welding point or a position or area specified by the user; Determining a first operating parameter corresponding to the target relative position parameter; Controlling the ultrasonic sensor to operate with the first operating parameter to obtain a first image of the target object; determining a first low-frequency component portion and a first high-frequency component portion of the first image; determining a first energy value of the first low-frequency component portion and a second energy value of the first image; determining a target ratio between the first energy value and the second energy value; When the target ratio is not within the preset range, determining a first deviation between the target ratio and the preset range; Adjusting the first operating parameter according to the first deviation to obtain a second operating parameter; Controlling the ultrasonic sensor to operate with the second operating parameter to obtain a second image of the target object; determining a first characteristic distribution density according to the first high frequency component portion; Determining a first image enhancement processing parameter corresponding to the first feature distribution density; Performing image enhancement processing on the second image according to the first image enhancement processing parameters to obtain a target image; Performing image segmentation on the area where the target object is located in the target image to obtain a target area; A feature set of the target area is obtained, and welding spot recognition is performed according to the feature set.

[0017] Through the embodiments of the present application, firstly, the corresponding first working parameters can be configured based on the target relative position parameters between the ultrasonic sensor and the target object, so that the working parameter depth of the ultrasonic sensor conforms to the actual environment. Secondly, ultrasonic imaging is performed using the first working parameters to obtain a first image, wherein the first low-frequency component part reflects the basic structure of the image, and the first high-frequency component part reflects the detailed information of the image. If the energy proportion of the first low-frequency component part is too high, more details will be covered up. If the energy proportion of the first low-frequency component part is too low, the basic structure of the image will be unclear. Therefore, it is necessary to ensure that the first low-frequency component part is within a reasonable range. If the energy proportion of the first low-frequency component part is not within a reasonable range, it is necessary to dynamically adjust the first working parameters based on the degree of deviation so that the low-frequency component part of the image The energy proportion returns to a reasonable range, and then, after adjustment, a second working parameter is obtained. Thirdly, ultrasonic imaging is performed using the second working parameter to obtain a second image. Since the working parameter is adjusted, the high-frequency and low-frequency parts in the image are affected to a certain extent. In order to suppress excessive image adjustment or under-enhancement, the second image is adjusted based on the feature distribution in the first high-frequency component part of the first image to obtain the final target image, so that the final ultrasonic imaging depth conforms to the actual situation, and the image is prevented from being over-enhanced or under-enhanced. Fourthly, since the ultrasonic imaging depth conforms to the actual situation, it can ensure that the regional image of the target object also conforms to the actual situation in depth, which helps to ensure the accuracy of weld recognition. In this way, the ultrasonic imaging effect of automotive parts processing equipment can be improved to improve the accuracy of weld recognition.

[0018] See also Figure 1 , Figure 1 1 is a flow chart of an ultrasonic image processing method provided in an embodiment of the present application. As shown in the figure, the method is applied to automobile parts processing equipment. The automobile parts processing equipment includes an ultrasonic sensor. The ultrasonic image processing method includes: 101. Determine target relative position parameters between the automobile parts processing equipment and a target object by using the ultrasonic sensor; the target object includes a suspected welding point or a position or area specified by a user.

[0019] In the embodiment of the present application, the target relative position parameter may include a target relative distance and / or a target relative angle.

[0020] In a specific implementation, the target relative position parameters between the automobile parts processing equipment and the target object can be determined by the ultrasonic sensor, that is, the environment can be preliminarily identified to clarify the relative position relationship between the ultrasonic sensor and the target object.

[0021] The target object may include a suspected solder joint or a location or area specified by a user. For example, a user may select a location or area for solder joint identification.

[0022] 102. Determine a first working parameter corresponding to the target relative position parameter.

[0023] In the embodiment of the present application, the first operating parameter may include at least one of the following: the transmitting power of the ultrasonic sensor, the transmitting direction of the ultrasonic sensor, the operating current of the ultrasonic sensor, the operating voltage of the ultrasonic sensor, the operating power of the ultrasonic sensor, etc., which are not limited here.

[0024] In a specific implementation, a mapping relationship between preset relative position parameters and the working parameters of the ultrasonic sensor can be pre-stored, and a first working parameter corresponding to the target relative position parameter can be determined based on the mapping relationship. The corresponding first working parameter can be configured based on the target relative position parameter between the ultrasonic sensor and the target object, so that the working parameter depth of the ultrasonic sensor conforms to the actual environment.

[0025] 103. Control the ultrasonic sensor to operate with the first operating parameter to obtain a first image of the target object.

[0026] The first image may include the entire image, that is, the background area portion and the target area portion, or may include only the target area portion. The target area portion may be understood as a partial image of the area where the target object is located.

[0027] In a specific implementation, the ultrasonic sensor can be controlled to work with the first working parameter to obtain a first image of the target object, that is, the ultrasonic sensor is controlled to collect an image of the target object with the first working parameter to obtain the first image of the target object. Since the corresponding first working parameter is configured based on the target relative position parameter between the ultrasonic sensor and the target object, the working parameter depth of the ultrasonic sensor conforms to the actual environment, and the ultrasonic imaging effect is also preliminarily guaranteed.

[0028] 104. Determine a first low-frequency component part and a first high-frequency component part of the first image.

[0029] In the embodiment of the present application, the first image can be multi-scale decomposed to obtain a first low-frequency component part and a first high-frequency component part of the first image. The multi-scale decomposition algorithm may include at least one of the following: a wavelet transform algorithm, a pyramid transform algorithm, a neural network algorithm, a contourlet transform algorithm, a non-subsampled contourlet transform algorithm, etc., which are not limited here. The first low-frequency component part reflects the basic structure of the image, and the first high-frequency component part reflects the detailed information of the image.

[0030] 105. Determine a first energy value of the first low-frequency component part and a second energy value of the first image.

[0031] In a specific implementation, the first energy value of the first low-frequency component and the second energy value of the first image can be determined, and then the energy ratio between the two can be calculated. If the energy ratio of the first low-frequency component is too high, more details will be covered up, and if the energy ratio of the first low-frequency component is too low, the basic structure of the image will be unclear. Therefore, the first low-frequency component needs to be kept within a reasonable range.

[0032] 106. Determine a target ratio between the first energy value and the second energy value.

[0033] Among them, the target ratio = the first energy value / the second energy value. If the energy proportion of the first low-frequency component is too high, it will cover up more details. If the energy proportion of the first low-frequency component is too low, the basic structure of the image will be unclear. Therefore, it is necessary to ensure that the first low-frequency component is within a reasonable range, that is, it is necessary to ensure that the target ratio is within a reasonable range.

[0034] 107. When the target ratio is not within a preset range, determine a first deviation between the target ratio and the preset range.

[0035] The preset range may be preset or set by system default. The preset range may include an upper threshold and a lower threshold, and the upper threshold is greater than the lower threshold.

[0036] In a specific implementation, the target ratio can be compared with the upper threshold and the lower threshold to determine the deviation direction. The deviation direction is either that the target ratio is less than the lower threshold or that the target ratio is greater than the upper threshold. The target ratio less than the lower threshold can be defined as the first deviation direction, and the target ratio greater than the upper threshold can be defined as the second deviation direction. If the first deviation direction is reached, the first operating parameter needs to be increased. Conversely, if the second deviation direction is reached, the first operating parameter needs to be decreased.

[0037] For the first deviation direction, the first deviation degree=(lower threshold value-target ratio) / lower threshold value, and for the second deviation direction, the first deviation degree=(upper threshold value-target ratio) / upper threshold value.

[0038] 108. Adjust the first operating parameter according to the first deviation to obtain a second operating parameter.

[0039] In a specific implementation, the second working parameter = (1 + first deviation) * first working parameter. Thus, when the energy proportion of the first low-frequency component is not within a reasonable range, the first working parameter can be dynamically adjusted based on the degree of deviation so that the energy proportion of the low-frequency component of the image returns to a reasonable range. Then, after adjustment, the second working parameter is obtained.

[0040] 109. Control the ultrasonic sensor to operate with the second operating parameter to obtain a second image of the target object.

[0041] In the embodiment of the present application, while ensuring that the corresponding first working parameter is configured based on the target relative position parameter between the ultrasonic sensor and the target object, so that the working parameter depth of the ultrasonic sensor conforms to the actual environment, the first working parameter is dynamically adjusted again based on its deviation degree, so that the energy proportion of the low-frequency component part of the image returns to a reasonable range, and then, after adjustment, the second working parameter is obtained, so that the basic structure of the image is further guaranteed, which helps to ensure the ultrasonic imaging effect. That is, the ultrasonic sensor is controlled to collect images of the target object with the second working parameter to obtain a second image of the target object.

[0042] 110. Determine a first characteristic distribution density according to the first high-frequency component.

[0043] Among them, the first feature distribution density may refer to the feature point distribution density. In a specific implementation, feature extraction may be performed on the first high-frequency component to obtain at least one feature point, and the number of the at least one feature point may be determined. The area of ​​the first high-frequency component may also be determined. The first feature distribution density = number / area.

[0044] 111. Determine a first image enhancement processing parameter corresponding to the first feature distribution density.

[0045] Among them, the first image enhancement processing parameters may include an image enhancement processing algorithm and corresponding algorithm control parameters. The algorithm control parameters are used to control the image enhancement degree, algorithm speed, image enhancement area, image enhancement position, etc. of the image enhancement processing algorithm, which are not limited here.

[0046] 112. Perform image enhancement processing on the second image according to the first image enhancement processing parameters to obtain a target image.

[0047] In an embodiment of the present application, the second image can be enhanced according to the first image enhancement processing parameters to obtain a target image. After the working parameters are adjusted, the high-frequency and low-frequency parts of the image are affected to a certain extent. In order to suppress excessive image adjustment or under-enhancement, the second image is adjusted based on the feature distribution in the first high-frequency component part of the first image by dynamic feedback to obtain the final target image. This makes the final ultrasonic imaging depth consistent with the actual situation and prevents the image from being over-enhanced or under-enhanced. In this way, the ultrasonic imaging effect can be improved.

[0048] Optionally, the first image enhancement processing parameters include: a first image enhancement processing algorithm and a first algorithm control parameter; The above step 111, determining the first image enhancement processing parameter corresponding to the first feature distribution density, may include the following steps: Determining a first image enhancement processing algorithm corresponding to the first feature distribution density; Acquiring initial algorithm control parameters of the first image enhancement processing algorithm; determining a second high frequency component portion of the second image; determining a second characteristic distribution density according to the second high frequency component portion; determining a second deviation between the second characteristic distribution density and the first characteristic distribution density; determining a target feedback adjustment parameter corresponding to the second deviation; Feedback adjustment is performed on the initial algorithm control parameter according to the target feedback adjustment parameter to obtain a first algorithm control parameter.

[0049] Among them, the first feature distribution density reflects the feature sparsity, and different feature sparsity will have a certain impact on the accuracy of subsequent image recognition. Therefore, the mapping relationship between the preset first feature distribution density and the image enhancement processing algorithm can be pre-stored, and then, the first image enhancement processing algorithm corresponding to the first feature distribution density can be determined based on the mapping relationship, and the initial algorithm control parameters of the first image enhancement processing algorithm can be obtained. Different image enhancement processing algorithms can correspond to different algorithm control parameters. Usually, the initial algorithm control parameters can be configured based on experience.

[0050] Furthermore, the second image may be subjected to multi-scale decomposition to obtain a second low-frequency component part and a second high-frequency component part of the second image. The multi-scale decomposition algorithm may include at least one of the following: a wavelet transform algorithm, a pyramid transform algorithm, a neural network algorithm, a contourlet transform algorithm, a non-subsampled contourlet transform algorithm, etc., which are not limited here. The second low-frequency component part reflects the basic structure of the image, and the second high-frequency component part reflects the detailed information of the image.

[0051] Furthermore, the second feature distribution density can be determined based on the second high-frequency component part. The second feature distribution density can refer to the feature point distribution density. In a specific implementation, feature extraction can be performed on the second high-frequency component part to obtain at least one feature point, and the number of the at least one feature point can be determined. The area of ​​the second high-frequency component part can also be determined. The first feature distribution density = number / area. Next, the second deviation between the second characteristic distribution density and the first characteristic distribution density can be determined, the second deviation = (second characteristic distribution density-first characteristic distribution density) / (first characteristic distribution density+second characteristic distribution density), and the mapping relationship between the preset deviation and the feedback adjustment parameter can also be pre-stored, and then, the target feedback adjustment parameter corresponding to the second deviation can be determined based on the mapping relationship, and then some or all of the parameters in the initial algorithm control parameters are feedback-adjusted according to the target feedback adjustment parameter to obtain the first algorithm control parameter. Specifically, the first algorithm control parameter = (1+target feedback adjustment parameter)*initial algorithm control parameter. After the working parameters are adjusted, the high-frequency and low-frequency parts of the image are affected to a certain extent. In order to suppress excessive image adjustment or under-enhancement, the initial algorithm control parameters are feedback-adjusted based on the characteristic distribution in the first high-frequency component part of the first image and the characteristic distribution in the second high-frequency component part, so that the final ultrasonic imaging effect depth conforms to the actual situation, and also prevents the image from being over-enhanced or under-enhanced. In this way, the ultrasonic imaging effect can be improved.

[0052] Optionally, the above step of performing feedback adjustment on the initial algorithm control parameter according to the target feedback adjustment parameter to obtain the first algorithm control parameter includes: Performing feedback adjustment on the initial algorithm control parameter according to the target feedback adjustment parameter to obtain a reference algorithm control parameter; determining a second low-frequency component portion of the second image; determining a third deviation according to the second low-frequency component part and the first low-frequency component part; determining a target fine-tuning parameter corresponding to the third degree of deviation; The reference algorithm control parameter is fine-tuned according to the target fine-tuning parameter to obtain the first algorithm control parameter.

[0053] Among them, according to the target feedback adjustment parameters, some or all of the initial algorithm control parameters are feedback-adjusted to obtain reference algorithm control parameters. Specifically, the reference algorithm control parameters = (1 + target feedback adjustment parameters) * initial algorithm control parameters. After the working parameters are adjusted, the high-frequency and low-frequency parts of the image are affected to a certain extent. In order to suppress excessive image adjustment or under-enhancement, the initial algorithm control parameters are feedback-adjusted based on the feature distribution in the first high-frequency component part of the first image and the feature distribution in the second high-frequency component part, so that the final ultrasonic imaging effect depth conforms to the actual situation and prevents over-enhancement or under-enhancement of the image.

[0054] Next, the second low-frequency component part of the second image can be determined, and the third deviation can be determined according to the second low-frequency component part and the first low-frequency component part, that is, the third energy value of the second low-frequency component part can be determined, and the first energy value of the first low-frequency component part can be obtained. The third deviation = (third energy value-first energy value) / (third energy value+first energy value). The mapping relationship between the preset deviation and the fine-tuning parameter can also be pre-stored, and then, based on the mapping relationship, the target fine-tuning parameter corresponding to the third deviation can be determined. The energy of the low-frequency component part reflects the stability of the basic structure of the image to a certain extent, that is, the change in the stability of the basic structure of the image can be determined again based on the basic structure of the image, and the change in stability can be used to further optimize the algorithm control parameters, and then, the image over-adjustment can be deeply suppressed or the image under-enhancement can be prevented. The reference algorithm control parameters are fine-tuned according to the target fine-tuning parameters to obtain the first algorithm control parameters. Specifically, the first algorithm control parameters = (1 + target fine-tuning parameters) * reference algorithm control parameters. In this way, on the one hand, the initial algorithm control parameters are adjusted based on the feature distribution in the first high-frequency component part of the first image and the feature distribution in the second high-frequency component part, so that the final ultrasonic imaging effect depth conforms to the actual situation and prevents over-enhancement or under-enhancement of the image. On the other hand, based on the energy of the first low-frequency component part of the first image and the energy of the second low-frequency component part of the second image, that is, based on the basic structure of the image, the stability change of the basic structure of the image is determined, and the algorithm control parameters are further fine-tuned in depth, which can deeply suppress excessive image adjustment or prevent image under-enhancement, thereby deeply improving the ultrasonic imaging effect.

[0055] Optionally, the target relative position parameters include target relative distance and target relative angle; The first operating parameter includes a first transmitting power of the ultrasonic sensor and a first transmitting direction of the ultrasonic sensor; The above step 102, determining the first operating parameter corresponding to the target relative position parameter, may include the following steps: Determining a reference transmission power according to the relative distance of the target; Determine a reference emission direction according to the target relative angle; the reference emission direction is the direction in which the ultrasonic sensor points to the target object; Constructing a target vector according to the reference transmit power, the reference transmit direction and the target relative distance; Determining a first position of the target object, and determining a second position, a second transmission power, and a second transmission direction of a target interference source, and; constructing a first vector according to the first position, the second position, the second transmission power, and the second transmission direction; Determine a second vector according to the first vector and the target vector, wherein a resultant vector of the first vector and the second vector is the target vector; The first operating parameter is determined according to the second vector.

[0056] The target relative position parameter may include a target relative distance and a target relative angle. The first operating parameter includes a first transmitting power of the ultrasonic sensor and a first transmitting direction of the ultrasonic sensor.

[0057] In a specific implementation, a mapping relationship between a preset distance and a transmission power can be pre-stored, and then a reference transmission power corresponding to the target relative distance can be determined based on the mapping relationship. A reference transmission direction can also be determined according to the target relative angle, and the reference transmission direction is the direction in which the ultrasonic sensor points to the target object.

[0058] Next, a target vector may be constructed according to the reference transmit power, the reference transmit direction, and the target relative distance. Specifically, the size of the target vector = reference transmit power / target relative distance, and the direction of the target vector is the reference transmit direction.

[0059] Furthermore, the first position of the target object can be determined, as well as the second position, second transmission power and second transmission direction of the target interference source, and then a first vector can be constructed based on the first position, the second position, the second transmission power and the second transmission direction, wherein the reference distance between the first position and the second position is determined, the size of the first vector = second transmission power / reference distance, and the direction of the first vector is the second transmission direction.

[0060] Furthermore, the second vector can be determined based on the first vector and the target vector, and the resultant vector of the first vector and the second vector is the target vector. Since the resultant vector and a corresponding component vector are known, the other corresponding component vector, i.e., the second vector, can be quickly determined, and then the first working parameter is determined based on the second vector, wherein the vector direction of the second vector is the first transmission direction, and the first transmission power = the vector size of the second vector * the target relative distance. In this way, in the presence of an interference source, the working parameters of the ultrasonic sensor can be dynamically adjusted based on the relative position relationship between the interference source and the target object and the influence of the interference source on the ultrasonic imaging, so that the adjusted working parameters of the ultrasonic sensor can suppress the influence of the interference source, thereby ensuring the ultrasonic imaging effect.

[0061] Optionally, the following steps may also be included: When the target ratio is within the preset range, determining an image quality evaluation value of the first image; When the image quality evaluation value is greater than a first preset threshold, saving the first image; When the image quality evaluation value is less than or equal to the first preset threshold, determining a target difference between the preset threshold and the image quality evaluation value; When the target difference is greater than a second preset threshold, executing the step of controlling the ultrasonic sensor to operate with the first operating parameter; When the target difference is less than or equal to the second preset threshold, determining a target signal-to-noise ratio of the first image; Obtain the target magnetic field interference intensity parameters of the current environment; Determining a second image enhancement processing algorithm corresponding to the target magnetic field interference intensity parameter; Acquire default algorithm control parameters corresponding to the second image enhancement processing algorithm; Determining a target optimization coefficient corresponding to the target signal-to-noise ratio; Optimizing the default algorithm control parameters according to the target optimization coefficient to obtain second algorithm control parameters; Perform image enhancement processing on the first image according to the second image enhancement processing algorithm and the second algorithm control parameters to obtain a third image.

[0062] In the embodiment of the present application, when the target ratio is within the preset range, the image quality evaluation value of the first image can be determined. Specifically, at least one image quality evaluation index can be used to evaluate the image quality of the first image to obtain the image quality evaluation value of the first image. The image quality evaluation index may include at least one of the following: average grayscale, clarity, signal-to-noise ratio, edge preservation, average gradient, etc., which are not limited here.

[0063] In a specific implementation, when the image quality evaluation value is greater than the first preset threshold, it means that the image quality is good, and the first image can be saved. When the image quality evaluation value is less than or equal to the first preset threshold, it means that the image quality is average, and a target difference between the preset threshold and the image quality evaluation value can also be determined, that is, the target difference = preset threshold - image quality evaluation value, and the larger the target difference, the worse the image quality. When the target difference is greater than the second preset threshold, it means that the image quality is too poor, and the image needs to be recaptured, that is, the step of controlling the ultrasonic sensor to work with the first working parameter can be executed. When the target difference is less than or equal to the second preset threshold, it means that the image quality is not too bad, and the image quality can be improved by image enhancement by certain means, that is, the target signal-to-noise ratio of the first image can be determined, and the target magnetic field interference intensity parameter of the current environment can be obtained. The target magnetic field interference intensity parameter reflects the degree of influence of the environmental magnetic field on ultrasonic imaging. The mapping relationship between the preset magnetic field interference intensity parameter and the image enhancement processing algorithm can be pre-stored, and then, the second image enhancement processing algorithm corresponding to the target magnetic field interference intensity parameter can be determined based on the mapping relationship, and the default algorithm control parameter corresponding to the second image enhancement processing algorithm can also be obtained. Different image enhancement processing algorithms correspond to different algorithm control parameters. The algorithm control parameters are used to control the image enhancement degree, algorithm speed, image enhancement area, image enhancement position, etc. of the image enhancement processing algorithm, which are not limited here. That is, the corresponding image enhancement processing algorithm can be dynamically selected based on different magnetic field interferences, which helps to adapt the image enhancement effect to the current magnetic field environment, and can also overcome the interference of the external magnetic field to the image itself to a certain extent, thereby deeply improving the ultrasonic imaging effect.

[0064] Furthermore, different signal-to-noise ratios indicate that different degrees of image enhancement processing are required. Therefore, the mapping relationship between the preset signal-to-noise ratio and the optimization coefficient can be pre-stored, and then the target optimization coefficient corresponding to the target signal-to-noise ratio can be determined based on the mapping relationship, and then some or all of the parameters in the default algorithm control parameters are optimized according to the target optimization coefficient to obtain the second algorithm control parameters, that is, the second algorithm control parameters = (1 + target optimization coefficient) * default algorithm control parameters, and then the first image is enhanced according to the second image enhancement processing algorithm and the second algorithm control parameters to obtain the third image. In this way, when the image quality of ultrasonic imaging is good, the image can be directly saved, and when it is poor, it can be re-collected. In general, dynamically enhancing the image based on magnetic field interference and the signal-to-noise ratio of the image itself helps to improve the efficiency of ultrasonic imaging.

[0065] Optionally, the above step of obtaining the target magnetic field interference intensity parameter of the current environment may include the following steps: Determine a first magnetic field interference intensity parameter at a location of the ultrasonic sensor; Determine a second magnetic field interference intensity parameter at a location of the target object; Determine a target weight pair according to the target relative position parameter, the target weight pair comprising a first weight and a second weight, the first weight corresponds to the first magnetic field interference intensity parameter, and the second weight corresponds to the second magnetic field interference intensity parameter; A weighted operation is performed on the first magnetic field interference intensity parameter, the second magnetic field interference intensity parameter and the target weight to obtain the target magnetic field interference intensity parameter.

[0066] In the embodiment of the present application, the first magnetic field interference intensity parameter of the location where the ultrasonic sensor is located can be determined, and the second magnetic field interference intensity parameter of the location where the target object is located can be determined when the ultrasonic sensor is turned off.

[0067] Furthermore, a target weight pair can also be determined according to the target relative position parameter, the target weight pair includes a first weight and a second weight, the first weight corresponds to the first magnetic field interference intensity parameter, and the second weight corresponds to the second magnetic field interference intensity parameter, that is, the target relative position parameter can include a target relative distance, that is, according to a preset mapping relationship between the distance and the weight pair, the target weight pair corresponding to the target relative distance can be determined based on the mapping relationship. First weight + second weight = 1.

[0068] Furthermore, a weighted operation can be performed based on the first magnetic field interference intensity parameter, the second magnetic field interference intensity parameter and the target weight to obtain a target magnetic field interference intensity parameter, specifically as follows: target magnetic field interference intensity parameter = first weight * first magnetic field interference intensity parameter + second weight * second magnetic field interference intensity parameter. In this way, the magnetic field interference conditions at the location of the ultrasonic sensor and the magnetic field interference conditions at the location of the target object can be comprehensively considered, and the impact of the two on ultrasonic imaging can be dynamically evaluated. The final magnetic field interference condition can then be determined based on the magnetic field interference conditions of the two, so that the final magnetic field interference intensity parameter depth conforms to the actual environment, which helps to improve the ultrasonic imaging effect.

[0069] 113. Perform image segmentation on the area where the target object is located in the target image to obtain a target area.

[0070] In an embodiment of the present application, image segmentation can be performed on the area where the target object is located in the target image to obtain a target area related to the target object. Since the ultrasonic imaging depth conforms to the actual situation, it can be ensured that the regional image of the target object also conforms to the actual situation in depth, thereby helping to ensure the accuracy of weld spot recognition.

[0071] 114. Obtain a feature set of the target area, and perform welding point recognition according to the feature set.

[0072] In a specific implementation, the feature set may include at least one feature, and the feature may include at least one of the following: feature point, feature vector, feature value, area, width, thickness, perimeter, shape, etc., which are not limited here.

[0073] Specifically, a feature set of the target area may be obtained, and then solder joint recognition may be performed based on the feature set, that is, whether the target object is a solder joint, or whether the target object is a cold solder joint, etc., which is not limited here.

[0074] Optionally, the above step 114, identifying the solder joints according to the feature set, may include the following steps: Comparing the feature set with a preset feature set to obtain a target comparison result; The solder joint recognition result is determined according to the target comparison result.

[0075] The preset feature set may include at least one feature, and the feature may include at least one of the following: feature point, feature vector, feature value, area, width, thickness, perimeter, shape, etc., which are not limited here. The preset feature set may be a feature set of a normal solder joint, or a feature set of a cold solder joint, etc., which are not limited here.

[0076] In a specific implementation, the feature set can be compared with the preset feature set to obtain a target comparison result, and then the weld recognition result can be determined based on the target comparison result. For example, the mapping relationship between the preset comparison result and the weld recognition result can be pre-stored, and then the target comparison result can be determined based on the mapping relationship to determine the weld recognition result. In this way, it can be determined whether it is a weld or a cold weld based on different comparison results. Even when a weld is recognized, the quality of the weld can be identified. For example, the larger the comparison result, the better the quality of the weld. Since the ultrasonic imaging depth conforms to the actual situation, it can ensure that the regional image of the target object also conforms to the actual situation in depth, which helps to ensure the accuracy of weld recognition. In this way, the ultrasonic imaging effect of automotive parts processing equipment can be improved to improve the accuracy of weld recognition.

[0077] It can be seen that the ultrasonic image processing method described in the embodiment of the present application is applied to automobile parts processing equipment, and the automobile parts processing equipment includes an ultrasonic sensor, and the target relative position parameters between the automobile parts processing equipment and the target object are determined by the ultrasonic sensor; the target object includes a suspected welding point or a position or area specified by the user; a first working parameter corresponding to the target relative position parameter is determined; the ultrasonic sensor is controlled to work with the first working parameter to obtain a first image of the target object; a first low-frequency component part and a first high-frequency component part of the first image are determined; a first energy value of the first low-frequency component part and a second energy value of the first image are determined; a target ratio between the first energy value and the second energy value is determined; when the target ratio is not within a preset range, a first deviation between the target ratio and the preset range is determined; the first working parameter is adjusted according to the first deviation to obtain a second working parameter; the ultrasonic sensor is controlled to work with the second working parameter to obtain a second image of the target object; a first feature distribution density is determined according to the first high-frequency component part; a first image enhancement processing parameter corresponding to the first feature distribution density is determined;The second image is enhanced according to the first image enhancement processing parameter to obtain a target image, the area where the target object is located in the target image is segmented to obtain the target area, the feature set of the target area is obtained, and the welding point is identified according to the feature set. First, the corresponding first working parameter can be configured based on the target relative position parameter between the ultrasonic sensor and the target object, so that the working parameter depth of the ultrasonic sensor conforms to the actual environment. Second, ultrasonic imaging is performed using the first working parameter to obtain a first image, wherein the first low-frequency component part reflects the basic structure of the image, and the first high-frequency component part reflects the detailed information of the image. If the energy proportion of the first low-frequency component part is too high, more details will be covered up. If the energy proportion of the first low-frequency component part is too low, the basic structure of the image will be unclear. Therefore, it is necessary to ensure that the first low-frequency component part is within a reasonable range, and the energy proportion of the first low-frequency component part is not within a reasonable range. If the first working parameter is within the reasonable range, it is necessary to dynamically adjust the first working parameter based on the degree of deviation so that the energy proportion of the low-frequency component of the image returns to a reasonable range. Then, after adjustment, the second working parameter is obtained. Third, the second working parameter is used for ultrasonic imaging to obtain a second image. Since the working parameter adjustment has a certain degree of influence on the high-frequency and low-frequency parts of the image, in order to suppress excessive image adjustment or under-enhancement, the second image is adjusted based on the characteristic distribution in the first high-frequency component of the first image to obtain the final target image, so that the final ultrasonic imaging depth conforms to the actual situation and prevents the image from being over-enhanced or under-enhanced. Fourth, since the ultrasonic imaging depth conforms to the actual situation, it can ensure that the depth of the regional image of the target object also conforms to the actual situation, which helps to ensure the accuracy of welding spot recognition. In this way, the ultrasonic imaging effect of automobile parts processing equipment can be improved to improve the accuracy of welding spot recognition. ;

[0078] In accordance with the above embodiment, please refer to Figure 2 , Figure 2 : is a structural schematic diagram of an automobile parts processing equipment provided by an embodiment of the present application. As shown in the figure, the equipment includes a processor, a memory, a communication interface and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor. In the embodiment of the present application, the automobile parts processing equipment further includes an ultrasonic sensor, and the program includes instructions for executing the following steps: Determine the target relative position parameter between the automobile parts processing equipment and the target object by the ultrasonic sensor; Determining a first operating parameter corresponding to the target relative position parameter; Controlling the ultrasonic sensor to operate with the first operating parameter to obtain a first image of the target object; determining a first low-frequency component portion and a first high-frequency component portion of the first image; determining a first energy value of the first low-frequency component portion and a second energy value of the first image; determining a target ratio between the first energy value and the second energy value; When the target ratio is not within the preset range, determining a first deviation between the target ratio and the preset range; Adjusting the first operating parameter according to the first deviation to obtain a second operating parameter; Controlling the ultrasonic sensor to operate with the second operating parameter to obtain a second image of the target object; determining a first characteristic distribution density according to the first high frequency component portion; Determining a first image enhancement processing parameter corresponding to the first feature distribution density; The second image is enhanced according to the first image enhancement processing parameters to obtain a target image.

[0079] Optionally, the first image enhancement processing parameters include: a first image enhancement processing algorithm and a first algorithm control parameter; In terms of determining the first image enhancement processing parameter corresponding to the first feature distribution density, the program includes instructions for performing the following steps: Determining a first image enhancement processing algorithm corresponding to the first feature distribution density; Acquiring initial algorithm control parameters of the first image enhancement processing algorithm; determining a second high frequency component portion of the second image; determining a second characteristic distribution density according to the second high frequency component portion; determining a second deviation between the second characteristic distribution density and the first characteristic distribution density; determining a target feedback adjustment parameter corresponding to the second deviation; Feedback adjustment is performed on the initial algorithm control parameter according to the target feedback adjustment parameter to obtain a first algorithm control parameter.

[0080] Optionally, the target relative position parameters include target relative distance and target relative angle; The first operating parameter includes a first transmitting power of the ultrasonic sensor and a first transmitting direction of the ultrasonic sensor; In terms of determining the first operating parameter corresponding to the target relative position parameter, the program includes instructions for performing the following steps: Determining a reference transmission power according to the relative distance of the target; Determine a reference emission direction according to the target relative angle; the reference emission direction is the direction in which the ultrasonic sensor points to the target object; Constructing a target vector according to the reference transmit power, the reference transmit direction and the target relative distance; Determining a first position of the target object, and determining a second position, a second transmission power, and a second transmission direction of a target interference source; constructing a first vector according to the first position, the second position, the second transmission power, and the second transmission direction; Determine a second vector according to the first vector and the target vector, wherein a resultant vector of the first vector and the second vector is the target vector; The first operating parameter is determined according to the second vector.

[0081] Optionally, the program further includes instructions for executing the following steps: When the target ratio is within the preset range, determining an image quality evaluation value of the first image; When the image quality evaluation value is greater than a first preset threshold, saving the first image; When the image quality evaluation value is less than or equal to the first preset threshold, determining a target difference between the preset threshold and the image quality evaluation value; When the target difference is greater than a second preset threshold, executing the step of controlling the ultrasonic sensor to operate with the first operating parameter; When the target difference is less than or equal to the second preset threshold, determining a target signal-to-noise ratio of the first image; Obtain the target magnetic field interference intensity parameters of the current environment; Determining a second image enhancement processing algorithm corresponding to the target magnetic field interference intensity parameter; Acquire default algorithm control parameters corresponding to the second image enhancement processing algorithm; Determining a target optimization coefficient corresponding to the target signal-to-noise ratio; Optimizing the default algorithm control parameters according to the target optimization coefficient to obtain second algorithm control parameters; Perform image enhancement processing on the first image according to the second image enhancement processing algorithm and the second algorithm control parameters to obtain a third image.

[0082] Optionally, in terms of obtaining the target magnetic field interference intensity parameter of the current environment, the program includes instructions for executing the following steps: Determine a first magnetic field interference intensity parameter at a location of the ultrasonic sensor; Determine a second magnetic field interference intensity parameter at a location of the target object; Determine a target weight pair according to the target relative position parameter, the target weight pair comprising a first weight and a second weight, the first weight corresponds to the first magnetic field interference intensity parameter, and the second weight corresponds to the second magnetic field interference intensity parameter; A weighted operation is performed on the first magnetic field interference intensity parameter, the second magnetic field interference intensity parameter and the target weight to obtain the target magnetic field interference intensity parameter.

[0083] Optionally, in the aspect of performing solder joint identification according to the feature set, the program includes instructions for performing the following steps: Comparing the feature set with a preset feature set to obtain a target comparison result; The solder joint recognition result is determined according to the target comparison result.

[0084] It can be seen that the automobile parts processing equipment described in the embodiment of the present application includes an ultrasonic sensor. First, the corresponding first working parameter can be configured based on the target relative position parameter between the ultrasonic sensor and the target object, so that the working parameter depth of the ultrasonic sensor conforms to the actual environment. Second, ultrasonic imaging is performed using the first working parameter to obtain a first image, wherein the first low-frequency component part reflects the basic structure of the image, and the first high-frequency component part reflects the detailed information of the image. If the energy proportion of the first low-frequency component part is too high, more details will be covered up. If the energy proportion of the first low-frequency component part is too low, the basic structure of the image will be unclear. Therefore, it is necessary to ensure that the first low-frequency component part is within a reasonable range. If the energy proportion of the first low-frequency component part is not within a reasonable range, it is necessary to dynamically adjust the first low-frequency component part based on the degree of deviation. First, a working parameter is set to make the energy proportion of the low-frequency component of the image return to a reasonable range, and then, after adjustment, a second working parameter is obtained. Third, the second working parameter is used to perform ultrasonic imaging to obtain a second image. Since the working parameter is adjusted, the high-frequency and low-frequency parts in the image are affected to a certain extent. In order to suppress excessive image adjustment or under-enhancement, the second image is adjusted based on the feature distribution in the first high-frequency component of the first image to obtain the final target image, so that the final ultrasonic imaging depth is consistent with the actual situation, and the image is prevented from being over-enhanced or under-enhanced. Fourth, since the ultrasonic imaging depth is consistent with the actual situation, it can ensure that the regional image of the target object is also in depth. It helps to ensure the accuracy of weld spot recognition. In this way, the ultrasonic imaging effect of automotive parts processing equipment can be improved to improve the accuracy of weld spot recognition.

[0085] Figure 3300 is a functional unit composition block diagram of an ultrasonic image processing device 300 involved in an embodiment of the present application, which is applied to automobile parts processing equipment. The automobile parts processing equipment includes an ultrasonic sensor. The ultrasonic image processing device 300 includes: a determination unit 301, a control unit 302, an adjustment unit 303, an enhancement unit 304, a segmentation unit 305 and a recognition unit 306, wherein: The determination unit 301 is used to determine the target relative position parameters between the automobile parts processing equipment and the target object through the ultrasonic sensor; the target object includes a suspected welding point or a position or area specified by the user; The control unit 302 is used to control the ultrasonic sensor to operate with the first operating parameters to obtain a first image of the target object; The determining unit 301 is further configured to determine a first low-frequency component part and a first high-frequency component part of the first image; determine a first energy value of the first low-frequency component part and a second energy value of the first image; determine a target ratio between the first energy value and the second energy value; and when the target ratio is not within a preset range, determine a first deviation between the target ratio and the preset range; The adjusting unit 303 is further configured to adjust the first operating parameter according to the first deviation to obtain a second operating parameter; The control unit 302 is further configured to control the ultrasonic sensor to operate with the second operating parameter to obtain a second image of the target object; The determining unit 301 is further configured to determine a first characteristic distribution density according to the first high-frequency component portion; and determine a first image enhancement processing parameter corresponding to the first characteristic distribution density; The enhancement unit 304 is used to perform image enhancement processing on the second image according to the first image enhancement processing parameters to obtain a target image; The segmentation unit 305 is used to perform image segmentation on the area where the target object is located in the target image to obtain the target area; The identification unit 306 is used to obtain a feature set of the target area and perform welding point identification according to the feature set.

[0086] Optionally, the first image enhancement processing parameters include: a first image enhancement processing algorithm and a first algorithm control parameter; In terms of determining the first image enhancement processing parameter corresponding to the first feature distribution density, the determining unit 301 is specifically configured to: Determining a first image enhancement processing algorithm corresponding to the first feature distribution density; Acquiring initial algorithm control parameters of the first image enhancement processing algorithm; determining a second high frequency component portion of the second image; determining a second characteristic distribution density according to the second high frequency component portion; determining a second deviation between the second characteristic distribution density and the first characteristic distribution density; determining a target feedback adjustment parameter corresponding to the second deviation; Feedback adjustment is performed on the initial algorithm control parameter according to the target feedback adjustment parameter to obtain a first algorithm control parameter.

[0087] Optionally, the target relative position parameters include target relative distance and target relative angle; The first operating parameter includes a first transmitting power of the ultrasonic sensor and a first transmitting direction of the ultrasonic sensor; In terms of determining the first operating parameter corresponding to the target relative position parameter, the determining unit 301 is specifically configured to: Determining a reference transmission power according to the relative distance of the target; Determine a reference emission direction according to the target relative angle; the reference emission direction is the direction in which the ultrasonic sensor points to the target object; Constructing a target vector according to the reference transmit power, the reference transmit direction and the target relative distance; Determining a first position of the target object, and determining a second position, a second transmission power, and a second transmission direction of a target interference source; constructing a first vector according to the first position, the second position, the second transmission power, and the second transmission direction; Determine a second vector according to the first vector and the target vector, wherein a resultant vector of the first vector and the second vector is the target vector; The first operating parameter is determined according to the second vector.

[0088] Optionally, the ultrasonic image processing device 300 is further specifically used for: When the target ratio is within the preset range, determining an image quality evaluation value of the first image; When the image quality evaluation value is greater than a first preset threshold, saving the first image; When the image quality evaluation value is less than or equal to the first preset threshold, determining a target difference between the preset threshold and the image quality evaluation value; When the target difference is greater than a second preset threshold, executing the step of controlling the ultrasonic sensor to operate with the first operating parameter; When the target difference is less than or equal to the second preset threshold, determining a target signal-to-noise ratio of the first image; Obtain the target magnetic field interference intensity parameters of the current environment; Determining a second image enhancement processing algorithm corresponding to the target magnetic field interference intensity parameter; Acquire default algorithm control parameters corresponding to the second image enhancement processing algorithm; Determining a target optimization coefficient corresponding to the target signal-to-noise ratio; Optimizing the default algorithm control parameters according to the target optimization coefficient to obtain second algorithm control parameters; Perform image enhancement processing on the first image according to the second image enhancement processing algorithm and the second algorithm control parameters to obtain a third image.

[0089] Optionally, in terms of obtaining the target magnetic field interference intensity parameter of the current environment, the ultrasonic image processing device 300 is specifically used for: Determine a first magnetic field interference intensity parameter at a location of the ultrasonic sensor; Determine a second magnetic field interference intensity parameter at a location of the target object; Determine a target weight pair according to the target relative position parameter, the target weight pair comprising a first weight and a second weight, the first weight corresponds to the first magnetic field interference intensity parameter, and the second weight corresponds to the second magnetic field interference intensity parameter; A weighted operation is performed on the first magnetic field interference intensity parameter, the second magnetic field interference intensity parameter and the target weight to obtain the target magnetic field interference intensity parameter.

[0090] Optionally, in the aspect of performing solder joint identification according to the feature set, the identification unit 306 is specifically used for: Comparing the feature set with a preset feature set to obtain a target comparison result; The solder joint recognition result is determined according to the target comparison result.

[0091] It can be seen that the ultrasonic image processing device described in the embodiment of the present application, Applied to automobile parts processing equipment, the automobile parts processing equipment includes an ultrasonic sensor. First, a corresponding first working parameter can be configured based on a target relative position parameter between the ultrasonic sensor and the target object, so that the working parameter depth of the ultrasonic sensor conforms to the actual environment. Second, ultrasonic imaging is performed using the first working parameter to obtain a first image, wherein the first low-frequency component part reflects the basic structure of the image, and the first high-frequency component part reflects the detailed information of the image. If the energy proportion of the first low-frequency component part is too high, more details will be covered up. If the energy proportion of the first low-frequency component part is too low, the basic structure of the image will be unclear. Therefore, it is necessary to ensure that the first low-frequency component part is within a reasonable range. If the energy proportion of the first low-frequency component part is not within a reasonable range, it is necessary to dynamically adjust the first working parameter based on the degree of deviation. The energy proportion of the low-frequency component of the image returns to a reasonable range, and then, after adjustment, a second working parameter is obtained. Thirdly, ultrasonic imaging is performed using the second working parameter to obtain a second image. Since the working parameter is adjusted, the high-frequency and low-frequency parts in the image are affected to a certain extent. In order to suppress excessive image adjustment or under-enhancement, the second image is adjusted based on the characteristic distribution in the first high-frequency component of the first image to obtain the final target image, so that the final ultrasonic imaging depth conforms to the actual situation, and the image is prevented from being over-enhanced or under-enhanced. Fourthly, since the ultrasonic imaging depth conforms to the actual situation, it can ensure that the regional image of the target object also conforms to the actual situation in depth, which helps to ensure the accuracy of weld recognition. In this way, the ultrasonic imaging effect of automotive parts processing equipment can be improved to improve the accuracy of weld recognition.

[0092] It can be understood that the functions of each program module of the ultrasonic image processing device of this embodiment can be specifically implemented according to the method in the above method embodiment. The specific implementation process can refer to the relevant description of the above method embodiment, which will not be repeated here.

[0093] An embodiment of the present application also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps of any method recorded in the above method embodiments, and the above computer includes automobile parts processing equipment.

[0094] The present application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps of any method described in the method embodiment. The computer program product may be a software installation package, and the computer includes an automotive parts processing device.

[0095] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0096] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0097] In the several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the above-mentioned units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0098] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0099] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0100] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the above-mentioned methods in each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0101] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable memory, which may include a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0102] The embodiments of the present application are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. An ultrasonic image processing method, characterized in that: Applied to automobile parts processing equipment, the automobile parts processing equipment includes an ultrasonic sensor, and the method includes: Determine the target relative position parameters between the automobile parts processing equipment and the target object by the ultrasonic sensor; the target object includes a suspected welding point or a position or area specified by the user; Determining a first operating parameter corresponding to the target relative position parameter; Controlling the ultrasonic sensor to operate with the first operating parameter to obtain a first image of the target object; determining a first low-frequency component portion and a first high-frequency component portion of the first image; determining a first energy value of the first low-frequency component portion and a second energy value of the first image; determining a target ratio between the first energy value and the second energy value; When the target ratio is not within the preset range, determining a first deviation between the target ratio and the preset range; Adjust the first operating parameter according to the first deviation to obtain a second operating parameter; Controlling the ultrasonic sensor to operate with the second operating parameter to obtain a second image of the target object; determining a first characteristic distribution density according to the first high frequency component portion; Determining a first image enhancement processing parameter corresponding to the first feature distribution density; Performing image enhancement processing on the second image according to the first image enhancement processing parameters to obtain a target image; Performing image segmentation on the area where the target object is located in the target image to obtain a target area; A feature set of the target area is obtained, and welding spot recognition is performed according to the feature set.

2. The method according to claim 1, characterized in that The first image enhancement processing parameters include: a first image enhancement processing algorithm and a first algorithm control parameter; The determining of a first image enhancement processing parameter corresponding to the first feature distribution density includes: Determining a first image enhancement processing algorithm corresponding to the first feature distribution density; Acquiring initial algorithm control parameters of the first image enhancement processing algorithm; determining a second high frequency component portion of the second image; determining a second characteristic distribution density according to the second high frequency component portion; determining a second deviation between the second characteristic distribution density and the first characteristic distribution density; determining a target feedback adjustment parameter corresponding to the second deviation; Feedback adjustment is performed on the initial algorithm control parameter according to the target feedback adjustment parameter to obtain the first algorithm control parameter.

3. The method according to claim 1 or 2, characterized in that: The target relative position parameters include target relative distance and target relative angle; The first operating parameter includes a first transmitting power of the ultrasonic sensor and a first transmitting direction of the ultrasonic sensor; The determining of a first operating parameter corresponding to the target relative position parameter comprises: Determining a reference transmission power according to the relative distance of the target; Determine a reference emission direction according to the target relative angle; the reference emission direction is the direction in which the ultrasonic sensor points to the target object; Constructing a target vector according to the reference transmit power, the reference transmit direction and the target relative distance; Determining a first position of the target object, and determining a second position, a second transmission power, and a second transmission direction of a target interference source; constructing a first vector according to the first position, the second position, the second transmission power, and the second transmission direction; Determine a second vector according to the first vector and the target vector, wherein a resultant vector of the first vector and the second vector is the target vector; The first operating parameter is determined according to the second vector.

4. The method according to claim 1 or 2, characterized in that: The method further comprises: When the target ratio is within the preset range, determining an image quality evaluation value of the first image; When the image quality evaluation value is greater than a first preset threshold, saving the first image; When the image quality evaluation value is less than or equal to the first preset threshold, determining a target difference between the preset threshold and the image quality evaluation value; When the target difference is greater than a second preset threshold, executing the step of controlling the ultrasonic sensor to operate with the first operating parameter; When the target difference is less than or equal to the second preset threshold, determining a target signal-to-noise ratio of the first image; Obtain the target magnetic field interference intensity parameters of the current environment; Determining a second image enhancement processing algorithm corresponding to the target magnetic field interference intensity parameter; Acquire default algorithm control parameters corresponding to the second image enhancement processing algorithm; Determining a target optimization coefficient corresponding to the target signal-to-noise ratio; Optimizing the default algorithm control parameters according to the target optimization coefficient to obtain second algorithm control parameters; Perform image enhancement processing on the first image according to the second image enhancement processing algorithm and the second algorithm control parameters to obtain a third image.

5. The method according to claim 1 or 2, characterized in that: The step of obtaining the target magnetic field interference intensity parameter of the current environment includes: Determine a first magnetic field interference intensity parameter at a location of the ultrasonic sensor; Determine a second magnetic field interference intensity parameter at a location of the target object; Determine a target weight pair according to the target relative position parameter, the target weight pair comprising a first weight and a second weight, the first weight corresponds to the first magnetic field interference intensity parameter, and the second weight corresponds to the second magnetic field interference intensity parameter; A weighted operation is performed according to the first magnetic field interference intensity parameter, the second magnetic field interference intensity parameter and the target weight value to obtain the target magnetic field interference intensity parameter.

6. The method according to claim 1 or 2, characterized in that: The step of identifying solder joints according to the feature set includes: Comparing the feature set with a preset feature set to obtain a target comparison result; The solder joint recognition result is determined according to the target comparison result.

7. An ultrasonic image processing device, characterized in that: Applied to automobile parts processing equipment, the automobile parts processing equipment includes an ultrasonic sensor, the device includes: a determination unit, a control unit, an adjustment unit, an enhancement unit, a segmentation unit and a recognition unit, wherein: The determination unit is used to determine the target relative position parameters between the automobile parts processing equipment and the target object through the ultrasonic sensor; the target object includes a suspected welding point or a position or area specified by a user; The control unit is used to control the ultrasonic sensor to operate with the first operating parameter to obtain a first image of the target object; The determining unit is further configured to determine a first low-frequency component part and a first high-frequency component part of the first image; determine a first energy value of the first low-frequency component part and a second energy value of the first image; determine a target ratio between the first energy value and the second energy value; and when the target ratio is not within a preset range, determine a first deviation between the target ratio and the preset range; The adjustment unit is further used to adjust the first operating parameter according to the first deviation to obtain a second operating parameter; The control unit is further used to control the ultrasonic sensor to operate with the second operating parameter to obtain a second image of the target object; The determining unit is further used to determine a first characteristic distribution density according to the first high-frequency component part; and determine a first image enhancement processing parameter corresponding to the first characteristic distribution density; The enhancement unit is used to perform image enhancement processing on the second image according to the first image enhancement processing parameters to obtain a target image; The segmentation unit is used to perform image segmentation on the area where the target object is located in the target image to obtain the target area; The recognition unit is used to obtain a feature set of the target area and perform welding point recognition according to the feature set.

8. An automobile parts processing equipment, characterized in that: The automobile parts processing equipment includes a processor and a memory, wherein the memory is used to store one or more programs and is configured to be executed by the processor, and the program includes instructions for executing the steps in the method according to any one of claims 1 to 6.

9. A computer storage medium, characterized in that: The computer storage medium is used to store one or more programs and is configured to be executed by the processor, wherein the programs include instructions for executing the steps in the method according to any one of claims 1 to 6.

10. A computer program product, characterized in that The computer program product comprises instructions for executing the steps of the method according to any one of claims 1-6.

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