A phased array composite material ultrasonic flaw detector control method and system

Abstract

The application provides a phased array composite material ultrasonic flaw detector control method and system, relates to the ultrasonic detection technical field, and has the technical scheme points that: multiple point distance data between a phased array probe and a measured curved surface of a composite material component is acquired; based on the multiple point distance data, local geometric parameters of the measured curved surface below the phased array probe are solved; actual ultrasonic echo transit time from an internal feature reflector of the composite material component is acquired; according to the solved local geometric parameters and the acquired actual ultrasonic echo transit time, equivalent propagation sound velocity for representing ultrasonic wave propagation in the composite material component is determined; and according to the solved local geometric parameters and the determined equivalent propagation sound velocity, excitation delay time for each array element of the phased array probe is calculated. The phased array composite material ultrasonic flaw detector control method and system provided by the application have the advantages of improving detection sensitivity and the accuracy of defect evaluation.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of ultrasonic detection, in particular to a phased array composite material ultrasonic flaw detector control method and system. BACKGROUND

[0002] Composite materials have become the preferred material for manufacturing load-bearing structural components with complex shape characteristics, such as aircraft fuselage sections, wings, turbine engine blades, wind turbine blades, and high-pressure hydrogen storage bottles, due to their excellent physical properties, such as high specific strength, high specific modulus, corrosion resistance, and high designability, and are widely used in aerospace, wind power, rail transportation, and other fields. These structural components often have significant, irregular curved surfaces, such as aircraft fuselage sections, wings, turbine engine blades, wind turbine blades, and high-pressure hydrogen storage bottles. Effective non-destructive testing of these complex components, particularly accurate assessment of possible manufacturing defects (such as porosity, inclusions, delamination, and debonding) or in-service damage (such as impact damage and fatigue cracks), is a key technical link to ensure the structural integrity and service safety of these components.

[0003] Phased array ultrasonic flaw detection technology has become a commonly used technique for such detection tasks due to its unique beam electronic deflection, scanning, and focusing capabilities. By precisely controlling the excitation time and relative phase of multiple piezoelectric elements inside the probe, the phased array system can synthesize an ultrasonic beam with a specific propagation direction and focal length inside the material. When detecting a flat composite material plate, assuming the material speed is known and uniformly distributed, the ultrasonic beam can be accurately focused to a predetermined depth inside the material by established geometric acoustics principles and pre-set delay rules, thereby achieving high detection sensitivity and defect resolution.

[0004] However, when the detection object changes from a flat surface to a curved composite material with complex changes, the detection situation becomes extremely complex. First, when the probe is coupled to the curved workpiece, the actual sound path of different array elements to the material surface and the refraction angle of the ultrasonic wave after entering the material will change significantly due to the presence of the curved surface, which is significantly different from the ideal situation based on the flat surface assumption. If the focusing rules designed for flat workpieces are still used, the actual focal point of the ultrasonic beam inside the material will deviate from the pre-set position, and the focal spot size will also disperse, causing the ultrasonic image to become blurred, and even possibly causing missed detection of critical defects or incorrect judgment of their size.

[0005] To cope with the adverse effects of curved geometry, some phased array UT systems introduce compensation mechanisms based on the geometric parameters of the curved surface. The operator needs to input approximate geometric information of the measured workpiece surface, such as the local radius of curvature, before the test. The system adjusts the delay law according to these input geometric parameters in order to correct the propagation path of the sound beam. However, in practical applications, the curved surface of many composite components is not a regular spherical or cylindrical surface, but a complex and continuously changing free-form surface, such as the wing-body junction area of an aircraft or the twisted transition part of a large blade. In these areas, a single radius of curvature parameter cannot accurately describe the local geometry under the probe. If the detection system can only handle simplified curved surface models, or the geometric parameters input by the operator deviate from the actual local geometry, the effect of sound beam focusing compensation will be greatly reduced. Especially when the probe is continuously scanned along a complex curved surface, the local curvature under the probe may change every time it moves to a new position. If the compensation parameters cannot be accurately adjusted accordingly, the focusing accuracy will continue to fluctuate.

[0006] Further exacerbating this problem is the acoustic properties of composite materials. The sound speed inside the composite material is not always uniform and constant. The design of the material's layup structure, changes in fiber orientation, local differences in resin content, distribution of porosity, and inconsistencies in local curing levels can all lead to spatial inhomogeneity in sound speed. This inhomogeneity in sound speed further disrupts the propagation path of the sound beam within the material, making it difficult for compensation methods based solely on external geometry to achieve ideal focusing effects. When the sound beam passes through areas with varying sound speeds, its propagation direction and speed will change, similar to how light propagates in different refractive index media, further exacerbating the shift and dispersion of the focal point.

[0007] In some application scenarios that require high-precision quantitative evaluation of defects, such as evaluating the initiation and propagation of micro-cracks or accurately measuring the size and depth of delamination defects, the requirement for sound beam focusing accuracy is even more demanding. If the focusing is poor, not only will the defect echo signal amplitude be reduced, but the profile in the ultrasonic image will also be distorted, directly affecting the accuracy of subsequent structural integrity evaluation and remaining life prediction.

[0008] In addition, when different depths of the material need to be detected, the phased array system usually adjusts the focusing depth dynamically. If the compensation control method cannot accurately and in real time handle the combined effects of curved surface effects and potential sound speed inhomogeneity on different focusing depths, the advantages of dynamic focusing cannot be fully realized. For example, when testing a thick-walled curved pressure vessel, both near-surface micro-defects and internal defects in the deep region need to be detected, and the sound beam needs to maintain good focusing at a large depth range.

[0009] When the probe is continuously scanned on the curved surface of the composite material to obtain a C-scan or B-scan image, the relative position and posture of the probe and the material surface are constantly changing. Even for a regularly defined curved surface, the contact point of the probe at different scanning positions, the local normal direction and the curvature parameter can be different. This means that the ideal focusing delay rule needs to be dynamically updated according to the real-time position and posture of the probe. If the response speed of the compensation control is not fast enough, or the accuracy of the update is not enough, the focusing quality will be uneven during the scanning process, resulting in the phenomenon that clear and blurred areas appear alternately in the final detection imaging result, which seriously affects the reliability and consistency of the detection result. For example, when a large wind turbine blade leading edge or trailing edge with a dramatic change in curvature is automatically scanned, if the accuracy of the sound beam focusing cannot be accurately compensated in real time according to the change in the curvature, detection blind spots or signal distortion may occur in places with large curvature changes.

[0010] Therefore, in the specific scenario of phased array ultrasonic scanning detection of composite material components with complex and continuously changing curvature surfaces, when considering the local inhomogeneity of the sound speed in the composite material, the real-time requirement of the focusing parameter adjustment due to the rapid change of the curved surface geometry, the limitation of the compensation model accuracy due to the unknown actual sound speed distribution in the material, and the coupling effect of the curved surface effect and the sound speed inhomogeneity on the sound beam propagation path, it is difficult for the existing technology to provide an effective focusing compensation method that can comprehensively, in real time and adaptively solve the above problems. Adjust the focusing depth during the scanning process requires a compensation method that can calculate and apply the focusing rule that adapts to the current probe position, posture, target depth and potential sound speed change.

[0011] The existing technology needs to be improved in view of the above problems. SUMMARY

[0012] The purpose of the present application is to provide a phased array composite material ultrasonic flaw detector control method and system, which has the advantages of improving the detection sensitivity and the accuracy of defect evaluation.

[0013] In a first aspect, the present application provides a phased array composite material ultrasonic flaw detector control method, and the technical solution is as follows:

[0014] It includes:

[0015] Obtain multi-point distance data between the phased array probe and the measured curved surface of the composite material component;

[0016] Based on the multi-point distance data, solve the local geometric parameters of the measured curved surface under the phased array probe;

[0017] acquiring actual transit times of ultrasonic echoes from the internal features reflectors of the composite component;

[0018] determining, by iterative correction, an equivalent propagation speed for characterizing propagation of the ultrasonic waves in the composite component according to the determined local geometric parameters and the acquired actual transit times of the ultrasonic echoes;

[0019] calculating, for each array element of the phased array probe, a firing delay time for compensating focusing of the phased array ultrasonic beam in the composite component according to the determined local geometric parameters and the determined equivalent propagation speed.

[0020] Further, the application further proposes that the step of determining, by iterative correction, an equivalent propagation speed for characterizing propagation of the ultrasonic waves in the composite component according to the determined local geometric parameters and the acquired actual transit times of the ultrasonic echoes comprises:

[0021] smoothing the acquired actual transit times of the ultrasonic echoes to obtain target transit times;

[0022] determining, by iterative correction, an equivalent propagation speed for characterizing propagation of the ultrasonic waves in the composite component according to the determined local geometric parameters and the target transit times, wherein when an iteration calculation of the iterative correction reaches a preset resource limit condition, outputting the equivalent propagation speed based on the iteration calculation;

[0023] performing variation amplitude limiting processing on the equivalent propagation speed output by the iterative correction to obtain a final equivalent propagation speed.

[0024] Further, the application further proposes that the step of smoothing the acquired actual transit times of the ultrasonic echoes to obtain target transit times comprises:

[0025] detecting the acquired actual transit times of the ultrasonic echoes to identify transit time step changes in the transit time sequence to obtain identified transit time step changes;

[0026] dividing the acquired actual transit times of the ultrasonic echoes into step change sections corresponding to the transit time step changes and non-step change sections corresponding to non-step changes according to the identified transit time step changes;

[0027] performing smoothing processing on the transit time data of the non-step change sections to obtain smoothed transit time data of the non-step change sections;

[0028] combining the smoothed transit time data of the non-step change sections and the transit time data of the step change sections to generate target transit times.

[0029] Further, the application also proposes that the step of determining the equivalent propagation speed of the ultrasonic wave propagating in the composite component according to the calculated local geometric parameters and the target transit time comprises:

[0030] acquiring the ultrasonic echo signals of the plurality of feature reflectors in the composite component and the corresponding actual transit times;

[0031] for each acquired ultrasonic echo signal, evaluating the signal-to-noise ratio of the ultrasonic echo signal to obtain an evaluated signal-to-noise ratio;

[0032] for each acquired ultrasonic echo signal, determining a sensitivity index of the transit time of the ultrasonic echo signal to the change of the equivalent propagation speed to obtain a determined sensitivity index;

[0033] selecting at least one feature reflector from the plurality of feature reflectors according to the evaluated signal-to-noise ratio and the determined sensitivity index to obtain a selected feature reflector;

[0034] taking the actual transit time of the selected feature reflector as the target transit time for iterative correction, and performing iterative correction according to the calculated local geometric parameters and the target transit time for iterative correction to determine the equivalent propagation speed of the ultrasonic wave propagating in the composite component.

[0035] Further, the application also proposes that the step of determining the sensitivity index of the transit time of the ultrasonic echo signal to the change of the equivalent propagation speed comprises:

[0036] extracting an acoustic characteristic change indication parameter for characterizing the acoustic characteristic change of the ultrasonic propagation path of the ultrasonic echo signal from the ultrasonic echo signal corresponding to each acquired ultrasonic echo signal;

[0037] calculating an initial sensitivity index corresponding to the ultrasonic echo signal based on the geometric information of the ultrasonic propagation path corresponding to each acquired ultrasonic echo signal;

[0038] adjusting the initial sensitivity index according to the extracted acoustic characteristic change indication parameter and the calculated initial sensitivity index to determine the sensitivity index of the transit time of the ultrasonic echo signal to the change of the equivalent propagation speed.

[0039] Further, the application also proposes that the step of extracting an acoustic characteristic change indication parameter for characterizing the acoustic characteristic change of the ultrasonic propagation path of the ultrasonic echo signal from the ultrasonic echo signal corresponding to each acquired ultrasonic echo signal comprises:

[0040] The ultrasound echo signal corresponding to each acquired ultrasound echo signal is subjected to a section division process to identify noise-affected sections, signal pattern abnormal sections and echo overlapping sections within the ultrasound echo signal, to obtain an identification result of the section division process;

[0041] Based on the identification result of the section division process, at least one sub-echo section satisfying a preset criterion in terms of signal characteristics is selected from the ultrasound echo signal, to obtain the selected at least one sub-echo section;

[0042] For the selected at least one sub-echo section, a preliminary acoustic characteristic parameter is extracted from each selected sub-echo section, to obtain a preliminary acoustic characteristic parameter corresponding to each selected sub-echo section;

[0043] The preliminary acoustic characteristic parameter corresponding to each selected sub-echo section extracted from the selected at least one sub-echo section is subjected to data fusion, to obtain a data fusion result, and consistency evaluation and outlier data point removal are performed on the data fusion result, so as to obtain an acoustic characteristic change indicating parameter for characterizing the acoustic characteristic change of the ultrasound propagation path of the ultrasound echo signal.

[0044] Further, the present application also proposes that the step of subjecting the preliminary acoustic characteristic parameter corresponding to each selected sub-echo section extracted from the selected at least one sub-echo section to data fusion, obtaining a data fusion result, and performing consistency evaluation and outlier data point removal on the data fusion result, so as to obtain an acoustic characteristic change indicating parameter for characterizing the acoustic characteristic change of the ultrasound propagation path of the ultrasound echo signal comprises:

[0045] Receiving the preliminary acoustic characteristic parameter corresponding to each selected sub-echo section extracted from the selected at least one sub-echo section;

[0046] Data fusion is performed on the preliminary acoustic characteristic parameter, and a fusion algorithm with a computational complexity satisfying a preset condition is adopted to obtain a data fusion result;

[0047] Consistency evaluation is performed on the data fusion result, and a consistency evaluation method with a computational complexity satisfying a preset condition is adopted;

[0048] Outlier data point removal is performed on the data fusion result, and an outlier data point removal method with a computational complexity satisfying a preset condition is adopted;

[0049] During the process of performing data fusion, consistency evaluation and outlier data point removal, the use of computing resources or processing time is monitored;

[0050] When the preset resource limit condition is reached, output the current processing result as an acoustic characteristic change indication parameter for representing the acoustic characteristic change of the ultrasonic propagation path of the ultrasonic echo signal.

[0051] Further, the application further proposes that the step of performing consistency evaluation on the result of data fusion comprises:

[0052] analyzing the change characteristics of the result sequence of data fusion;

[0053] Based on the change characteristics, identify the segment in the result sequence of data fusion that meets the preset rapid change criterion;

[0054] For the segment in the result sequence of data fusion that does not meet the preset rapid change criterion, evaluate its data fluctuation;

[0055] Based on the relationship between the data fluctuation and the preset noise threshold, determine whether the result of data fusion is consistent.

[0056] Further, the application further proposes that based on the multi-point distance data, the step of solving the local geometric parameters of the measured surface under the phased array probe comprises:

[0057] Receiving multi-point distance data;

[0058] Performing data processing on the multi-point distance data to reduce noise and remove outliers to obtain processed multi-point distance data;

[0059] Analyzing the processed multi-point distance data to identify the local geometric characteristics of the measured surface to obtain the identified local geometric characteristics;

[0060] Based on the identified local geometric characteristics, selecting a calculation strategy for solving the local geometric parameters, to obtain the selected calculation strategy;

[0061] According to the selected calculation strategy and the processed multi-point distance data, solving the local geometric parameters of the measured surface under the phased array probe.

[0062] Further, the application further proposes a phased array composite material ultrasonic flaw detector control system, which comprises:

[0063] An acquisition module for acquiring multi-point distance data between a phased array probe and a measured surface of a composite material component;

[0064] A geometric solving module for solving local geometric parameters of the measured surface under the phased array probe based on the multi-point distance data;

[0065] An echo acquisition module for acquiring actual ultrasonic echo transit time from internal feature reflectors of the composite material component;

[0066] a sound speed determining module configured to determine an equivalent propagation sound speed for representing the propagation of the ultrasonic wave in the composite material component by iterative correction according to the calculated local geometric parameters and the actual transit time of the acquired ultrasonic echo;

[0067] a delay calculating module configured to calculate the firing delay time for each array element of the phased array probe according to the calculated local geometric parameters and the determined equivalent propagation sound speed, so as to compensate the focusing of the phased array ultrasonic beam in the composite material component.

[0068] As can be seen, the control method and system of the phased array composite material ultrasonic flaw detector provided by the application can accurately calculate the firing delay time by adaptively acquiring the local geometric parameters of the measured curved surface and determining the equivalent propagation sound speed, thereby improving the focusing accuracy of the ultrasonic beam in the complex curved surface composite material, and having the advantages of improving the detection sensitivity and the accuracy of defect evaluation. BRIEF DESCRIPTION OF DRAWINGS

[0069] Figure 1 The figure is a flowchart of the control method of the phased array composite material ultrasonic flaw detector provided by the application.

[0070] Figure 2 The figure is a structural schematic diagram of the control system of the phased array composite material ultrasonic flaw detector provided by the application.

[0071] In the figure: 1, distance acquisition module; 2, geometric calculation module; 3, echo acquisition module; 4, sound speed determining module; 5, delay calculating module. DETAILED DESCRIPTION

[0072] The technical solutions of the application will be clearly and completely described below with reference to the drawings in the application. Obviously, the described embodiments are only some of the embodiments of the application, but not all the embodiments. The components of the application described and shown in the drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the application provided in the drawings is not intended to limit the scope of the claimed application, but only represents selected embodiments of the application. Based on the embodiments of the application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of the application.

[0073] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. Meanwhile, in the description of the application, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0074] When a composite component with a complex, continuously changing curved surface is subjected to phased array ultrasonic scanning detection, it is difficult to adaptively and in real time effectively compensate the focusing accuracy of the phased array ultrasonic detector to ensure stable and accurate focusing effect at the entire scanning path and different detection depths, considering the possible local inhomogeneity of the sound speed inside the composite material, the real-time requirement of the rapid change of the curved surface geometry on the adjustment of the focusing parameters, the limitation of the unknown actual sound speed distribution inside the material on the accuracy of the compensation model, and the coupling effect of the curved surface effect and the sound speed inhomogeneity on the sound beam propagation path.

[0075] For example, assume that an automated phased array ultrasonic scanning is performed on a composite skin of an aircraft wing with a complex free-form surface. The probe moves along a preset path, with the local curvature and normal direction continuously changing underneath. At the same time, the sound speed inside the skin differs in different areas due to factors such as ply design, curing process, etc. The phased array system needs to calculate the excitation delay time of each array element in real time to make the ultrasonic beam form accurate focusing at a predetermined depth inside the material. If the calculation is performed only according to a simplified curved surface model or a preset average sound speed, the actual beam path will deviate from the expected one, resulting in focusing position deviation and focal spot dispersion. During the scanning process, this deviation will dynamically change with the probe position and the acoustic properties of the material inside, making the focusing quality unstable.

[0076] To this end, with reference to Figure 1 The present application proposes a phased array composite ultrasonic detector control method, comprising:

[0077] S110, acquiring multi-point distance data between the phased array probe and the measured curved surface of the composite component;

[0078] S120, based on the multi-point distance data, solving the local geometric parameters of the measured curved surface underneath the phased array probe;

[0079] S130, acquiring the actual transit time of the ultrasonic echo from the internal feature reflector of the composite component;

[0080] S140, according to the solved local geometric parameters and the acquired actual transit time of the ultrasonic echo, determining the equivalent propagation sound speed for representing the propagation of ultrasonic waves in the composite component through iterative correction;

[0081] S150, according to the solved local geometric parameters and the determined equivalent propagation sound speed, calculating the excitation delay time for each array element of the phased array probe to compensate the focusing of the phased array ultrasonic beam inside the composite component.

[0082] The acquiring of the multi-point distance data between the phased array probe and the measured curved surface of the composite component refers to collecting distance information of multiple spatial points between the phased array probe and the measured curved surface, which can be realized by using optical measurement technology, mechanical measurement technology or ultrasonic measurement technology, for example, using a laser sensor, a structured light scanner or a touch sensor on a mechanical arm.

[0083] The calculating of the local geometric parameters of the measured curved surface under the phased array probe based on the multi-point distance data refers to calculating parameters describing the characteristics of the curved surface under the current position of the probe according to the collected multi-point distance data, which can be realized by using a curved surface fitting algorithm, a local curvature calculation method or a normal vector calculation method, for example, using a least square method to fit a polynomial curved surface or calculating a local principal curvature.

[0084] The acquiring of the actual transit time of the ultrasonic echo from the internal feature reflector of the composite component refers to the time experienced by the ultrasonic wave from being emitted by the probe, propagating through the material, encountering the feature reflector and returning to the probe, which can be determined by detecting the time difference of a specific feature point of the ultrasonic echo signal relative to the emission time, for example, detecting the peak time or zero-crossing time of the echo envelope.

[0085] The determining of the equivalent propagation speed for representing the ultrasonic wave propagation in the composite component by iterative correction according to the calculated local geometric parameters and the acquired actual transit time of the ultrasonic echo refers to inversely calculating a parameter capable of describing the average propagation speed of the ultrasonic wave on the path according to the known geometric path information and the measured ultrasonic propagation time, which can be realized by using an optimization algorithm based on minimizing the error of the calculated transit time and the actual transit time or a parameter adjustment process based on a preset model and measured data.

[0086] The calculating of the excitation delay time for each array element of the phased array probe for compensating the focusing of the phased array ultrasonic beam in the composite component according to the calculated local geometric parameters and the determined equivalent propagation speed refers to determining an ultrasonic wave emission delay amount relative to a reference time for each array element of the phased array probe, which can be calculated according to the calculated local geometric parameters and the determined equivalent propagation speed by using acoustic propagation principles, for example, using the ray tracing method or the Huygens principle.

[0087] The core innovation of the present application is that the real-time acquired local curved surface geometric parameters are combined with the equivalent propagation speed determined based on the measured echo of the internal feature reflector, and an iterative correction method is used to adaptively determine the equivalent speed, so that the influence of complex curved surface geometry and material internal speed inhomogeneity on the ultrasonic beam focusing can be comprehensively compensated, and the effect of real-time and accurate adjustment of the focusing rule and maintenance of stable focusing effect during scanning is achieved.

[0088] Specifically, first, the system acquires multi-point distance data of the measured surface under the probe, which reflects the spatial relationship between the probe and the surface. Then, based on the multi-point distance data, the system calculates geometric parameters describing the local surface shape, such as the curvature and the normal direction. Meanwhile, the system receives ultrasonic echo signals from internal features of the material and extracts actual transit times from the signals. The actual transit times contain geometric information and sound speed information of the ultrasonic wave propagation path in the material. Then, using the calculated local geometric parameters and the acquired actual transit times, the system determines an equivalent propagation sound speed through an iterative correction process. The equivalent sound speed is a parameter that comprehensively reflects the current local geometry and material acoustic characteristics. Finally, based on the calculated local geometric parameters and the determined equivalent propagation sound speed, the system calculates the excitation delay times of each array element of the phased array probe. These delay times are applied to the array elements of the probe, so that the transmitted ultrasonic beams can be accurately focused at the predetermined position after passing through the surface and the material. The entire process forms a closed loop, so that the focusing rule can be adjusted in real time according to the probe position, surface changes, and material acoustic characteristics.

[0089] As a preferred embodiment, the scheme of the present application is implemented as follows:

[0090] An array of laser ranging sensors integrated in the phased array probe is used to collect distance data of multiple points on the measured composite material surface under the probe in real time. The collected distance data is input into a processing unit, which runs a surface fitting algorithm, such as a least squares-based quadratic surface fitting, to calculate the curvature radius and normal direction of the local surface under the probe. At the same time, the phased array probe transmits ultrasonic waves and receives echo signals from internal preset feature reflectors of the material (such as the bottom surface of the material or a known embedded reflector). The processing unit analyzes the echo signals to determine the actual transit times of the ultrasonic waves by detecting the peak time of the echo envelope. The processing unit then executes an iterative correction algorithm, which takes the calculated local surface geometric parameters and the acquired actual transit times as inputs, and repeatedly adjusts a sound speed parameter until the error between the theoretical transit time calculated based on the sound speed parameter and the geometric parameters and the actual transit time is less than a preset threshold, thereby determining the equivalent propagation sound speed. Finally, using the calculated local geometric parameters and the determined equivalent propagation sound speed, the system calculates the excitation delay times of each array element of the phased array probe according to the principle of ray tracing, and sends these delay times to the transmitter circuit of the flaw detector to control the excitation timing of each array element, thereby achieving focusing compensation of the ultrasonic beams in the material.

[0091] By the above scheme, the application can adaptively and in real time compensate for the influence of complex curved surface geometry and internal material sound speed inhomogeneity on phased array ultrasonic beam focusing. This makes it possible to obtain stable and accurate focusing effect when scanning and detecting composite components with complex and continuously changing curvature surfaces, regardless of where the probe is located and how the detection depth changes. Thus, the defect detection rate and the accuracy of quantitative evaluation are improved.

[0092] Specifically, in some of the above schemes of the application, an equivalent propagation speed for representing the propagation of ultrasonic waves in the composite component is determined by iterative correction according to the calculated local geometric parameters and the obtained actual ultrasonic echo transit time, to compensate for the focusing of the phased array ultrasonic beam in the composite component. However, in this process, the obtained actual ultrasonic echo transit time may contain noise or fluctuations, and direct use in iterative correction may result in a lack of accuracy or stability of the determined equivalent propagation speed, affecting the subsequent focusing compensation function.

[0093] To this end, the application further proposes a step of determining an equivalent propagation speed for representing the propagation of ultrasonic waves in the composite component according to the calculated local geometric parameters and the obtained actual ultrasonic echo transit time by iterative correction, which includes: performing smoothing processing on the obtained actual ultrasonic echo transit time to obtain a target transit time; determining the equivalent propagation speed for representing the propagation of ultrasonic waves in the composite component according to the calculated local geometric parameters and the target transit time by iterative correction, wherein when the iterative calculation of the iterative correction reaches a preset resource limitation condition, the equivalent propagation speed based on this iteration calculation is output; performing change amplitude limiting processing on the equivalent propagation speed output by the iterative correction to obtain a final equivalent propagation speed.

[0094] Specifically, this scheme aims to solve the technical problem of how to ensure that the output of the determined equivalent propagation speed meets the real-time operation requirements of the system and its numerical change is smooth in the scenario where the local geometric parameters change rapidly and the actual ultrasonic echo transit time fluctuates.

[0095] The acquired actual ultrasonic echo transit time is the measurement data reflecting the sound propagation characteristics in the material, but this data can contain discontinuous change values due to fluctuations in the signal acquisition process. If the transit time containing fluctuations is directly used for subsequent iterative correction, it is easy to cause the calculated equivalent propagation sound speed result to oscillate. Therefore, by performing smoothing processing on the acquired actual ultrasonic echo transit time, for example, using methods such as mean filtering or median filtering, these acquisition fluctuations can be filtered out or weakened, thereby obtaining the target transit time. Compared with the original acquired transit time, the numerical change of the target transit time has a gentle nature, and as the input of the iterative correction, it provides a data basis for subsequent determination of an equivalent propagation sound speed with a smooth change, contributing to solving the problem of oscillation of the calculated equivalent propagation sound speed result due to fluctuations in the transit time. The core of this step is to use the calculated local geometric parameter (which represents the geometric information related to the ultrasonic wave propagation path) and the target transit time obtained after smoothing processing in the previous step (which represents the actual propagation time of the ultrasonic wave under this geometric path, and the influence of fluctuations has been weakened), through iterative correction, a calculation means, to calculate the equivalent propagation sound speed that can make the theoretical transit time calculated based on the local geometric parameter and the sound speed match the target transit time.

[0096] In the process of phased array ultrasonic scan detection, especially when the local geometric parameters of the measured component change rapidly with the scan position, the calculation and update rate of the equivalent propagation sound speed has real-time operation requirements, that is, the iterative correction process needs to be completed within a limited time. Therefore, when the iterative calculation of the iterative correction reaches the preset resource limit condition (for example, the preset maximum number of iterations or the maximum allowed calculation time), the equivalent propagation sound speed based on this iteration calculation is output. This limitation ensures that even if the iterative process does not mathematically converge to the theoretical optimal solution, an equivalent propagation sound speed result for the current detection point can be obtained under the premise of meeting the system's requirements for processing time, avoiding the problem that the iterative calculation takes too long to meet the real-time operation requirements of scan detection, and contributing to solving the problem of completing the output of the iterative correction process within a limited time.

[0097] Although the pre-step improves the stability and real-time operability of the sound speed calculation by performing smoothing on the actual transit time and setting a resource limit condition in the iterative correction, the equivalent propagation sound speed output by the iterative correction may still have numerical jumps or short-term oscillations in continuous output due to residual fluctuations in the input data, truncation effects of iterative calculation, or characteristics of the iterative algorithm itself. In order to ensure that the equivalent propagation sound speed finally applied to the phased array focusing compensation has numerical stability, and to avoid the lack of stability of the focusing function or the disturbance to the subsequent control system caused by the dramatic or frequent changes in the sound speed parameter, it is necessary to perform a change amplitude limiting process on the equivalent propagation sound speed output by the iterative correction. This process can be, for example, limiting the maximum allowed change between the sound speed values of adjacent two updates, or performing further low-pass filtering on the output sound speed sequence, etc., the purpose of which is to make the sound speed change curve over time or scan position smooth, and to obtain the final equivalent propagation sound speed. The numerical change of the final equivalent propagation sound speed has continuity and smoothness, thereby guaranteeing the stability and continuity of the focusing compensation function, and contributing to solving the problem of the numerical stability of the equivalent propagation sound speed output.

[0098] Through the above scheme, the application can weaken the influence of noise and fluctuations in the actual transit time of the ultrasonic echo on the calculation of the equivalent propagation sound speed, ensure that usable sound speed results can still be output in the case of limited calculation resources or time, and make the numerical change of the output equivalent propagation sound speed stable, thereby improving the accuracy and stability of the phased array ultrasonic beam focusing compensation in the composite material member.

[0099] Specifically, in some of the above schemes of the application, the equivalent propagation sound speed for characterizing the propagation of ultrasonic waves in the composite material member is determined by iterative correction according to the calculated local geometric parameters and the obtained actual transit time of the ultrasonic echo. However, the obtained actual transit time of the ultrasonic echo may be affected by noise, measurement error, and sudden changes in the internal structure or geometry of the composite material, resulting in noise, outliers, or real step changes in the transit time sequence. If the original actual transit time is directly used for iterative correction, the determined equivalent propagation sound speed may be unstable or inaccurate, affecting the calculation of the subsequent excitation delay time and the accuracy of the sound beam focusing. Therefore, how to effectively process the obtained actual transit time of the ultrasonic echo to obtain more stable and accurate target transit time for sound speed iterative correction is a technical problem to be solved.

[0100] To this end, the application further proposes a step of performing smoothing on the obtained actual transit time of the ultrasonic echo to obtain a target transit time, which comprises:

[0101] detecting the obtained actual transit time sequence of the ultrasonic echo to identify the step change in the transit time sequence, to obtain the identified step change in the transit time;

[0102] According to the identified step change in the transit time, the obtained actual transit time sequence of the ultrasonic echo is divided into a step change section corresponding to the step change in the transit time and a non-step change section corresponding to the non-step change;

[0103] Smooth processing is performed on the transit time data of the non-step change section to obtain the transit time data of the non-step change section after the smooth processing;

[0104] The transit time data of the non-step change section after the smooth processing and the transit time data of the step change section are combined to generate a target transit time.

[0105] Specifically, the operation logic of the scheme is that first, the original actual transit time sequence of the ultrasonic echo is analyzed, and the purpose is to distinguish the real signal step caused by the sudden change of the material internal acoustic characteristics and the random fluctuation caused by noise and other factors in the sequence. By detecting and identifying these step changes, it can be determined which data points or data sections represent the signal characteristics (step change section) that need to be preserved, and which data points or data sections mainly contain noise (non-step change section) that need to be suppressed. Subsequently, for the identified non-step change section, a smooth processing algorithm is applied to effectively filter out the random noise in it, thereby improving the stability of this part of data. For the identified step change section, smooth processing that may blur or eliminate the step characteristics is avoided to preserve its original form. Finally, the non-step change section data after the smooth processing and the step change section data that preserve the original characteristics are re-integrated to form a target transit time sequence that suppresses noise and preserves key step information. This target transit time sequence as the input of the subsequent iterative correction of the equivalent propagation speed, compared with directly using the original data, can provide more stable and accurate transit time information, thereby improving the accuracy of the speed determination. The scheme provides high-quality input data for the subsequent speed determination step by performing targeted preprocessing on the original transit time data, thereby improving the performance of the entire flaw detection method.

[0106] As a preferred embodiment, the scheme of the present application is implemented as follows: in the present embodiment, the acquired actual ultrasonic echo time-of-flight sequence is input to a processing unit. The processing unit first performs step change detection, which can specifically be implemented by calculating the difference between adjacent data points in the sequence and setting a threshold value, when the difference exceeds the threshold value, it is considered that there is a time-of-flight step change at this position. Based on the detected step change position, the original time-of-flight sequence is divided into multiple segments, the data immediately adjacent to the step change point is divided into a step change segment, and the remaining data is divided into a non-step change segment. Then, for the data of each non-step change segment, a moving average filter is applied for smoothing processing, for example, using a fixed length window, the average value of the data in the window is calculated as the smoothing value of the center point, and the window slides along the data sequence. After completing the smoothing processing of all non-step change segments, these smoothed data segments and the original step change segment data are recombined according to their order in the original sequence to generate the final target time-of-flight sequence.

[0107] Through the above scheme, the present application can effectively process the random noise and the real step change existing in the actual ultrasonic echo time-of-flight sequence at the same time, suppress the noise while preserving the important step feature, obtain a more stable and accurate target time-of-flight, thereby improving the accuracy of subsequent iterative correction of equivalent propagation sound speed, and further ensuring the accuracy of excitation delay time calculation and sound beam focusing.

[0108] Specifically, in some of the above schemes of the present application, it is proposed to determine the equivalent propagation sound speed for characterizing the propagation of ultrasonic waves in the composite material member according to the calculated local geometric parameters and the acquired actual ultrasonic echo time-of-flight, through iterative correction, to compensate for the focusing of the phased array ultrasonic beam in the composite material member. However, in this process, the acquired actual ultrasonic echo time-of-flight may come from multiple feature reflectors inside the composite material member, and the signal quality and sensitivity of the equivalent propagation sound speed change of these feature reflectors may differ. If all actual time-of-flights are directly used or simply smoothed for iterative correction, interference of low-quality or insensitive signals may be introduced, affecting the accuracy of the determination of the equivalent propagation sound speed, and further affecting the calculation of the subsequent excitation delay time and the focusing compensation effect of the sound beam.

[0109] To this end, the application further proposes a step of determining the equivalent propagation speed of the ultrasonic wave in the composite material component based on the calculated local geometric parameters and the target transit time, comprising: obtaining the ultrasonic echo signals of each of the plurality of feature reflectors inside the composite material component and the corresponding actual transit time; for each obtained ultrasonic echo signal, evaluating the signal-to-noise ratio of the ultrasonic echo signal to obtain the evaluated signal-to-noise ratio; for each obtained ultrasonic echo signal, determining the sensitivity index of the transit time of the ultrasonic echo signal to the change of the equivalent propagation speed to obtain the determined sensitivity index; selecting at least one feature reflector from the plurality of feature reflectors according to the evaluated signal-to-noise ratio and the determined sensitivity index to obtain the selected feature reflector; taking the actual transit time of the selected feature reflector as the target transit time for iterative correction, and performing iterative correction based on the calculated local geometric parameters and the target transit time for iterative correction to determine the equivalent propagation speed of the ultrasonic wave in the composite material component.

[0110] Specifically, after obtaining the ultrasonic echo signals from the plurality of feature reflectors inside the composite material component and the corresponding actual transit time, the present scheme no longer simply smoothes all transit times, but evaluates the quality and sensitivity of each echo signal.

[0111] By evaluating the signal-to-noise ratio of each echo signal, reliable echoes with high signal strength and less noise interference can be identified. By determining the sensitivity index of each echo transit time to the change of the equivalent propagation speed, the effectiveness of the echo information for speed correction can be understood.

[0112] Subsequently, according to these evaluation results, at least one feature reflector with high signal quality and appropriate sensitivity to the change of the equivalent propagation speed is systematically selected from the plurality of feature reflectors. The actual transit time of these selected feature reflectors is taken as the target for iterative correction, and the theoretical transit time calculated based on the calculated local geometric parameters is compared. The equivalent propagation speed is adjusted through the iterative process until the theoretical transit time and the target transit time are sufficiently close.

[0113] This optimization strategy based on signal quality and sensitivity enables the iterative correction process to utilize the most reliable and effective echo information, thereby improving the accuracy and robustness of the equivalent propagation speed determination. Compared with the method of simply smoothing all echo transit times, this method can better cope with the differences in reflector signal quality from different depths or paths and the different responses to the change of the equivalent propagation speed, thereby more accurately determining the equivalent propagation speed in the detection of composite material components with complex curved surfaces and potential non-uniformity of the equivalent propagation speed, and further optimizing the excitation delay calculation to achieve more accurate beam focusing compensation.

[0114] In some of the above-mentioned schemes of the present application, it is proposed to determine the equivalent propagation speed of the ultrasonic wave in the composite material member by iterative correction according to the actual transit time of the acquired ultrasonic echo, and further to select at least one characteristic reflector from a plurality of characteristic reflectors by evaluating the signal-to-noise ratio of the ultrasonic echo signal and determining the sensitivity index of the transit time of the ultrasonic echo signal to the change of the equivalent propagation speed, taking the actual transit time of the selected characteristic reflector as the target transit time for iterative correction, so as to improve the accuracy of the equivalent propagation speed determination. However, in this process, simply determining the sensitivity index of the transit time to the change of the equivalent propagation speed may not fully consider the actual acoustic characteristic changes (such as attenuation, scattering, signal distortion, etc.) encountered by the ultrasonic wave on the complex propagation path inside the composite material, which will affect the quality and stability of the ultrasonic echo, and further affect the actual response of the transit time to the change of the speed, resulting in that the calculated sensitivity index cannot accurately reflect the reliability or effectiveness of the echo for speed determination, thereby possibly affecting the optimization effect of the characteristic reflector selection and limiting the accuracy of the equivalent propagation speed determination.

[0115] To this end, the present application further proposes that the step of determining the sensitivity index of the transit time of each acquired ultrasonic echo signal to the change of the equivalent propagation speed comprises: extracting an acoustic characteristic change indication parameter for characterizing the acoustic characteristic change of the ultrasonic propagation path from the ultrasonic echo signal corresponding to each acquired ultrasonic echo signal; calculating an initial sensitivity index corresponding to the ultrasonic echo signal based on the geometric information of the ultrasonic propagation path corresponding to each acquired ultrasonic echo signal; and adjusting the initial sensitivity index according to the extracted acoustic characteristic change indication parameter and the calculated initial sensitivity index to determine the sensitivity index of the transit time of the ultrasonic echo signal to the change of the equivalent propagation speed.

[0116] The acoustic characteristic change indication parameter indicates a quantitative value of the acoustic environmental change experienced by the ultrasonic wave on a specific propagation path. It can be extracted by analyzing the amplitude attenuation, spectral component change, pulse width broadening, phase distortion or signal-to-noise ratio of the ultrasonic echo signal. For example, the ratio of the peak amplitude of the echo signal to the peak amplitude of the transmitted signal can be calculated as an attenuation indication, or the center frequency offset of the echo signal can be calculated as an indication of spectral change caused by scattering or absorption.

[0117] The geometric information of the ultrasonic propagation path refers to the spatial form and size data of the complete path of the ultrasonic wave from the probe element, through the coupling layer, into the composite material, propagating to the characteristic reflector and returning. It can be characterized by local geometric parameters of the probe and the surface of the member, as well as the depth or position information of the characteristic reflector inside the material.

[0118] The initial sensitivity indicator refers to the theoretical sensitivity of the ultrasonic echo transit time to the change of the equivalent propagation sound speed of the material, which is calculated based on the geometric information of the ultrasonic propagation path in an ideal or simplified acoustic medium model. It can be calculated by the derivative of the ultrasonic propagation path length with respect to the sound speed or the rate of change of the transit time calculated based on the geometric acoustics model.

[0119] The adjusted initial sensitivity indicator refers to the process of modifying or weighting the initial sensitivity indicator calculated based on the geometric information according to the actual extracted acoustic characteristic change indicator. It can be implemented by using a pre-set correction function, a lookup table, a machine learning model, or a weighted average, etc., so that the finally determined sensitivity indicator can more accurately reflect the actual influence of the acoustic path on the transit time.

[0120] The sensitivity indicator of the transit time to the change of the equivalent propagation sound speed refers to the quantitative sensitivity of the ultrasonic echo transit time to the change of the equivalent propagation sound speed of the material, which is finally determined by comprehensively considering the geometric information of the ultrasonic propagation path and the actual acoustic characteristic change on the path. This indicator is used to evaluate the reliability or amplitude of the response of the transit time of a specific echo signal to the change of the sound speed.

[0121] Specifically, this technical solution processes each acquired ultrasonic echo signal. First, parameters are extracted from the corresponding ultrasonic echo signal, which indicate the acoustic characteristic change encountered by the ultrasonic wave along a specific propagation path, capturing the actual effects such as signal attenuation or distortion. At the same time, an initial sensitivity indicator is calculated based on the geometric information of the ultrasonic propagation path, which only reflects the theoretical influence of the path geometry on the transit time with respect to the change of the sound speed, assuming that the acoustic characteristics of the material are uniform.

[0122] The core of this solution is to adjust this initial sensitivity indicator based on the geometric information by using the extracted acoustic characteristic change indicator. This adjustment process modifies the initial indicator according to the actual acoustic conditions encountered by the ultrasonic pulse. For example, if the acoustic parameter indicates that the signal is severely degraded due to high attenuation or distortion, the adjustment process can reduce the calculated sensitivity, reflecting that the transit time measured from such a degraded signal may not be very reliable or accurately respond to the real change of the sound speed.

[0123] Conversely, a clear signal can result in less adjustment, making the geometry sensitivity dominant. By combining the geometry influence and the actual acoustic path conditions, the scheme determines a final sensitivity index that more accurately represents the actual reliability and sensitivity of the specific echo signal's transit time to the change in material equivalent propagation speed under real conditions. This optimized sensitivity index provides a more reliable basis for the subsequent selection of the most suitable feature reflector for the speed determination. The combination of acoustic property analysis and geometry calculation with subsequent adjustment enables the system to adapt to the complexity and non-uniformity of the composite material and its curved geometry, which is an important challenge in the prior art. This improved sensitivity calculation directly supports the selection process in the aforementioned steps, enabling the system to select the most reliable echo signal for iterative speed correction, thereby improving the accuracy and stability of the overall speed determination process.

[0124] In some of the above-described schemes of the present application, it is proposed to determine the equivalent propagation speed for characterizing the propagation of ultrasonic waves in the composite component based on the calculated local geometry parameters and the actual transit time of the acquired ultrasonic echoes through iterative correction, and to calculate the excitation delay time based on the speed and the local geometry parameters to compensate for the focusing of the ultrasonic beam. In order to improve the accuracy of the equivalent propagation speed determination, it is necessary to select at least one feature reflector from a plurality of feature reflectors, and the selection is based on the evaluated signal-to-noise ratio and the determined sensitivity index of the transit time to the change in equivalent propagation speed. An important step in determining the sensitivity index is to extract an acoustic property change indicator parameter for characterizing the acoustic property change of the ultrasonic propagation path of the ultrasonic echo signal. However, when performing phased array ultrasonic scanning detection on a composite component with a complex, continuously changing curvature surface, the speed inside the composite material can be locally non-uniform, and the surface geometry changes rapidly. These factors can cause the acquired ultrasonic echo signal to be adversely affected by noise, abnormal signal morphology, echo overlap, etc., making it difficult to accurately and reliably extract the indicator parameter for characterizing the acoustic property change of the ultrasonic propagation path directly from the original ultrasonic echo signal, which in turn affects the accuracy of the sensitivity index determination and ultimately reduces the precision of the equivalent propagation speed calculation and focusing compensation. Therefore, how to robustly extract the indicator parameter for characterizing the acoustic property change of the ultrasonic propagation path from the complex and disturbed ultrasonic echo signal is a key problem for improving the accuracy and reliability of the entire control method.

[0125] To this end, the application further proposes that the step of extracting an acoustic characteristic change indication parameter for characterizing the acoustic characteristic change of the ultrasonic propagation path of the ultrasonic echo signal from the ultrasonic echo signal corresponding to each acquired ultrasonic echo signal comprises: performing a section division process on the ultrasonic echo signal corresponding to each acquired ultrasonic echo signal to identify noise-affected sections, signal morphology abnormal sections and echo overlapping sections within the ultrasonic echo signal, to obtain the identification result of the section division process; based on the identification result of the section division process, selecting at least one sub-echo section from the ultrasonic echo signal that satisfies a preset criterion, to obtain the selected at least one sub-echo section; for the selected at least one sub-echo section, extracting a preliminary acoustic characteristic parameter from each selected sub-echo section respectively, to obtain the preliminary acoustic characteristic parameter corresponding to each selected sub-echo section; data fusion is performed on the preliminary acoustic characteristic parameters corresponding to each selected sub-echo section extracted from the selected at least one sub-echo section, to obtain the data fusion result, and consistency evaluation and outlier data point removal are performed on the data fusion result, so as to obtain the acoustic characteristic change indication parameter for characterizing the acoustic characteristic change of the ultrasonic propagation path of the ultrasonic echo signal.

[0126] The section division process refers to analyzing the ultrasonic echo signal, dividing it into different time or sample intervals, and classifying or labeling each interval.

[0127] The noise-affected section refers to the part of the signal whose main component is random noise, which can be identified by using signal amplitude threshold, spectral analysis or statistical methods.

[0128] The signal morphology abnormal section refers to the part of the signal whose waveform is significantly different from the normal echo signal waveform, which can be identified by using waveform correlation analysis, template matching or feature extraction and classification methods.

[0129] The echo overlapping section refers to the part where multiple independent echo signals are overlapped in time, which can be identified by using signal deconvolution, blind source separation or signal modeling based on prior knowledge.

[0130] The preset criterion refers to the standard for evaluating the signal quality or applicability of the sub-echo section, which can include but is not limited to signal-to-noise ratio threshold, waveform similarity threshold, energy concentration threshold or specific feature parameter value range.

[0131] The sub-echo section refers to one or more continuous or non-continuous time intervals selected from the complete ultrasonic echo signal, which are considered to contain useful echo information and have relatively high signal quality.

[0132] The preliminary acoustic characteristic parameter refers to a quantitative index extracted from a single sub-echo segment for describing the signal characteristics of the segment, which can include peak amplitude, integrated energy, dominant frequency, bandwidth, phase information, time of flight (such as the time of arrival of the first wave, the time of peak), or waveform shape parameters, etc.

[0133] Data fusion refers to the integration of the same type of data obtained from multiple sources or multiple measurements to obtain more accurate and reliable comprehensive results, which can be achieved by methods such as average calculation, median filtering, weighted average, Kalman filtering, or Bayesian estimation.

[0134] Consistency evaluation refers to analyzing a set of data or a data sequence to determine whether there are significant inconsistencies or abnormal fluctuations within it, which can be achieved by statistical methods (such as standard deviation, variance analysis), trend analysis, or comparison between model-based predictions and actual data.

[0135] Outlier data point removal refers to identifying and removing outliers in the data set that are significantly different from other data to purify the data set, which can be achieved by methods based on statistical distance (such as Z-score, IQR), clustering analysis, or model prediction error.

[0136] Acoustic characteristic change indication parameter refers to the final quantitative index obtained after processing and fusion, which can stably and accurately reflect the change of acoustic characteristics of ultrasonic waves in the propagation path. This parameter is used for subsequent sensitivity index adjustment.

[0137] Specifically, the method first analyzes the original ultrasonic echo signal, decomposes it into different segments, and identifies the parts affected by noise, waveform abnormalities, or echo overlap. Because the original signal may contain a large amount of interference information, directly extracting parameters from it will introduce errors. The identification result clearly identifies which parts of the signal are unreliable, providing guidance for subsequent processing. Then, based on the identification result, select sub-echo segments with good signal quality that meet the preset standards from the original signal. This selection process avoids signal parts affected by severe interference, ensuring that the original data used for parameter extraction has high effectiveness.

[0138] Then, for each selected sub-echo segment, its preliminary acoustic characteristic parameter is extracted. Since these parameters are extracted from preferred signal segments, their initial accuracy is relatively high. Finally, the preliminary parameters extracted from multiple preferred sub-echo segments are fused to comprehensively utilize information from different reliable signal segments and smooth random fluctuations.

[0139] Further, consistency evaluation and outlier data point removal are performed on the fusion result to identify and eliminate residual abnormal values that may occur in the fusion process, and finally obtain an indicator parameter for representing the change in acoustic characteristics of the ultrasonic propagation path after multiple purification and comprehensive processing. Compared with the parameter directly extracted from the original signal, the parameter has higher accuracy and robustness. Through this step-by-step processing and data optimization, the method can effectively extract reliable acoustic characteristic change indicator parameters from complex and disturbed ultrasonic echo signals. The accurate extraction of the parameter further improves the accuracy of the sensitivity index determination of the change in the equivalent propagation sound velocity, making the process of selecting feature reflectors based on the signal-to-noise ratio and the sensitivity index to perform iterative correction of the equivalent propagation sound velocity more reliable, and ultimately improving the accuracy of the calculation of the equivalent propagation sound velocity and the excitation delay time, which helps to achieve more accurate sound beam focusing compensation in the detection of complex curved composite components.

[0140] In some of the above schemes of the present application, the preliminary acoustic characteristic parameters extracted from the selected at least one sub-echo section are subjected to data fusion, consistency evaluation and outlier data point removal to obtain an acoustic characteristic change indicator parameter for representing the change in acoustic characteristics of the ultrasonic propagation path of the ultrasonic echo signal to represent the change in acoustic characteristics of the ultrasonic propagation path. However, in this process, the data fusion, consistency evaluation and outlier data point removal processing steps may consume a lot of computing resources and time, and in the real-time requirement of phased array ultrasonic scanning scene, it may not be able to obtain accurate acoustic characteristic change indicator parameters in time, affecting the real-time and accuracy of the subsequent sound velocity determination and focusing delay calculation.

[0141] To this end, the application further proposes a step of data fusion of the preliminary acoustic characteristic parameters corresponding to each selected sub-echo section extracted from the selected at least one sub-echo section, obtaining a data fusion result, and performing consistency evaluation and outlier data point removal on the data fusion result, so as to obtain the acoustic characteristic change indication parameter for characterizing the acoustic characteristic change of the ultrasonic propagation path of the ultrasonic echo signal, comprising: receiving the preliminary acoustic characteristic parameters corresponding to each selected sub-echo section extracted from the selected at least one sub-echo section; data fusion of the preliminary acoustic characteristic parameters, using a fusion algorithm with a computational complexity satisfying a preset condition, to obtain a data fusion result; performing consistency evaluation on the data fusion result, using a consistency evaluation method with a computational complexity satisfying a preset condition; performing outlier data point removal on the data fusion result, using an outlier data point removal method with a computational complexity satisfying a preset condition; monitoring the computational resource usage or processing time during the execution of data fusion, consistency evaluation and outlier data point removal; and outputting the current processing result as the acoustic characteristic change indication parameter for characterizing the acoustic characteristic change of the ultrasonic propagation path of the ultrasonic echo signal when a preset resource limit condition is reached.

[0142] Specifically, this scheme aims to solve the problem of how to optimize the algorithm to meet the real-time requirement when the system processing capacity or time window is limited and a large number of preliminary acoustic characteristic parameters need to be fused, evaluated and outlier points removed.

[0143] First, the preliminary acoustic characteristic parameters extracted from the selected sub-echo section are received, which are the basis for subsequent processing. Then, data fusion is performed on these preliminary parameters, and by using a fusion algorithm with a computational complexity satisfying a preset condition, the computational cost can be controlled while ensuring a certain fusion effect, and a preliminary data fusion result is obtained. Then, consistency evaluation is performed on the data fusion result, and by using a consistency evaluation method with a computational complexity satisfying a preset condition, the stationarity and reliability of the fusion result can be quickly checked. Subsequently, outlier data point removal is performed on the data fusion result, and by using an outlier data point removal method with a computational complexity satisfying a preset condition, abnormal values can be quickly removed, further purifying the data.

[0144] During the entire process of data fusion, consistency evaluation and outlier data point removal, the system continuously monitors the computational resource usage or processing time. Once the preset resource limit condition is reached, the system immediately outputs the current processing result as the acoustic characteristic change indication parameter. This mechanism ensures that even in the case of limited computational resources or limited time window, the system can provide a usable acoustic characteristic parameter output in time, thereby maintaining the real-time performance of subsequent sound speed determination and focusing delay calculation.

[0145] By using an algorithm with limited computational complexity and introducing resource monitoring and conditional output mechanisms, the scheme improves the stability and accuracy of the acoustic characteristic indication parameters as much as possible under the premise of ensuring real-time, provides more reliable input for the subsequent equivalent propagation sound speed determination, and further improves the focusing accuracy and detection efficiency of the phased array ultrasonic scan.

[0146] Specifically, in some of the above schemes of the present application, a consistency evaluation is performed on the data fusion result to judge the reliability of the fusion result. However, after data fusion of the preliminary acoustic characteristic parameters extracted from different sub-echo sections, the fusion result sequence may be affected by noise, local material property changes or signal quality fluctuations, resulting in that it is not completely stationary and may have normal fluctuations or local rapid changes. A simple consistency evaluation method cannot distinguish between these different types of changes, which may misjudge normal fluctuations as inconsistent or ignore real abnormal changes, thereby affecting the accuracy of subsequent outlier removal and final acoustic characteristic change indication parameters. In particular, in scenarios requiring fast processing to meet real-time requirements, how to design a method that can accurately distinguish between different types of changes and robustly judge consistency is a challenge.

[0147] To this end, the present application further proposes a step of performing consistency evaluation on the data fusion result, which includes:

[0148] analyzing the change characteristics of the data fusion result sequence;

[0149] based on the change characteristics, identifying a section in the data fusion result sequence that meets a preset rapid change criterion;

[0150] for the section in the data fusion result sequence that does not meet the preset rapid change criterion, evaluating the data fluctuation thereof;

[0151] based on the relationship between the data fluctuation and a preset noise threshold, judging whether the data fusion result is consistent.

[0152] The change characteristics refer to properties that describe the change of the data sequence values with their indexes or time, such as the change rate, change amplitude or specific change pattern of the values, which can be realized by calculating the difference, derivative, slope of the sequence, or analyzing the local maximum, minimum, average value and other statistics of the sequence.

[0153] The preset rapid change criterion refers to rules or standards for defining what kind of change in the data sequence is considered a rapid change, which can be defined by setting a change rate threshold, an amplitude jump threshold, or identifying a specific waveform pattern.

[0154] Data fluctuation refers to the dispersion or instability of a data sequence in a certain section, which can be evaluated by statistical indicators such as standard deviation, variance, mean absolute deviation, or the difference between the maximum and minimum values of the data in the section.

[0155] The preset noise threshold refers to a pre-set numerical limit for distinguishing acceptable fluctuations caused by noise from unacceptable fluctuations indicating inconsistency, which can be determined by statistical analysis based on system noise level or by experimental calibration.

[0156] Specifically, the scheme first analyzes the overall or local change properties of the data fusion result sequence to obtain information about how the sequence evolves with the scanning position or time. Based on these change properties, the system identifies regions in the sequence that exhibit rapid and rapid numerical changes, which may correspond to rapid changes in the actual material acoustic properties. For the remaining regions in the sequence that do not belong to the rapid change type, the scheme further quantifies the fluctuation degree of the internal data, which mainly reflects residual noise or slight instability. Finally, the quantified data fluctuation is compared with a pre-set noise tolerance limit, and if the fluctuation is within the noise threshold, the data in this section is considered consistent; otherwise, there may be other inconsistency factors.

[0157] Through this step-by-step processing, the scheme can distinguish between rapid changes caused by actual physical changes and fluctuations caused by noise, avoiding misjudgment of the former as inconsistent, while accurately assessing the impact of the latter, thereby improving the accuracy of consistency judgment. The consistency evaluation process acts on the preliminary acoustic property parameter sequence extracted from the sub-echo section and fused, providing a more reliable basis for subsequent outlier removal, helping to obtain more accurate acoustic property change indication parameters, and further supporting the determination of equivalent propagation sound speed.

[0158] Specifically, in some of the above schemes of the present application, a method is proposed for calculating the local geometric parameters of the measured surface under the phased array probe based on multi-point distance data to provide a basis for subsequent determination of equivalent propagation sound speed and calculation of excitation delay time. However, the original multi-point distance data may contain noise and outliers, and the local geometric features of complex surfaces are diverse. Direct calculation based on the original data may result in inaccurate local geometric parameters, which in turn affects the accuracy of subsequent focusing compensation.

[0159] To this end, the present application further proposes that the step comprises:

[0160] receiving multi-point distance data;

[0161] performing data processing on the multi-point distance data to reduce noise and remove outliers, obtaining processed multi-point distance data;

[0162] analyzing the processed multi-point distance data to identify local geometric features of the measured surface, to obtain the identified local geometric features;

[0163] selecting a calculation strategy for solving the local geometric parameters based on the identified local geometric features, to obtain the selected calculation strategy;

[0164] solving the local geometric parameters of the measured surface under the phased array probe according to the selected calculation strategy and the processed multi-point distance data.

[0165] wherein the data processing refers to the preprocessing of the originally collected multi-point distance data, which can be achieved by filtering algorithms (such as median filtering, moving average filtering) or outlier detection and removal methods based on statistical principles (such as methods based on standard deviation, interquartile range or cluster analysis).

[0166] wherein the analyzing the processed multi-point distance data to identify local geometric features of the measured surface refers to judging the surface morphology of the current region by calculating or evaluating the spatial distribution characteristics of the processed data points, which can be achieved by calculating local curvature, detecting edges (such as methods based on gradient or difference) or detecting corner points (such as methods based on eigenvalue or template matching).

[0167] wherein the selecting a calculation strategy for solving the local geometric parameters refers to determining the algorithm or model most suitable for the parameter solving of the identified local geometric feature type, which can be achieved by rule-based judgment logic or machine learning classifiers.

[0168] wherein the calculation strategy refers to the specific algorithm or mathematical model used to extract or fit the local geometric parameters from the processed multi-point distance data, which can be achieved by least squares fitting (such as plane fitting, quadratic surface fitting), straight line or curve fitting based on edge detection results, or parameterized solving methods for specific geometric features (such as cylinder, sphere).

[0169] Specifically, the scheme first receives raw multi-point distance data acquired from the probe or external sensors, which reflect the spatial positions of the measured surface under the probe. Due to interference or errors during acquisition, these raw data may contain noise or outliers, which directly affect the accuracy of subsequent calculations. Therefore, it is necessary to perform data processing on the raw data, to obtain higher-quality processed data by reducing noise and removing outliers, laying the foundation for accurate calculation. Then, the processed data is analyzed to identify the geometric features of the current local area, such as being relatively flat, smoothly curved, having sharp edges or corner points, etc. Identifying local geometric features is necessary because different morphologies of the surface require different mathematical methods to accurately describe their parameters. Based on the identified local geometric features, the most appropriate calculation strategy is selected, such as selecting a surface fitting strategy for smooth surfaces or a parameterization strategy based on edge detection for edge regions. Selecting the appropriate calculation strategy is necessary, as it ensures the optimal calculation method for the current local surface morphology. Finally, according to the selected calculation strategy and using the processed high-quality multi-point distance data, the specific calculation process is performed to obtain the local geometric parameters of the measured surface under the phased array probe, such as local curvature, normal direction, etc. Through this series of steps, even in the case of poor quality of raw data or complex and varied surface morphology, the local geometric parameters can be accurately and robustly determined. These accurate local geometric parameters are the key input for subsequent determination of equivalent propagation speed and calculation of excitation delay time, thereby enabling the entire phased array ultrasonic flaw detector control method to effectively compensate for surface effects and non-uniformity of sound speed, improving the accuracy of sound beam focusing.

[0170] In a second aspect, referring to Figure 2 The present application proposes a phased array composite material ultrasonic flaw detector control system, which comprises:

[0171] The distance acquisition module 1 is used to acquire multi-point distance data between the phased array probe and the measured surface of the composite material component;

[0172] The geometric calculation module 2 is used to calculate the local geometric parameters of the measured surface under the phased array probe based on the multi-point distance data;

[0173] The echo acquisition module 3 is used to acquire the actual transit time of the ultrasonic echo from the internal feature reflector of the composite material component;

[0174] The sound speed determination module 4 is used to determine the equivalent propagation speed for representing the propagation of ultrasonic waves in the composite material component through iterative correction based on the calculated local geometric parameters and the acquired actual transit time of the ultrasonic echo;

[0175] The computing delay module 5 is used to calculate the excitation delay time for each array element of the phased array probe according to the calculated local geometric parameters and the determined equivalent propagation speed, so as to compensate the focusing of the phased array ultrasonic beam in the composite member.

[0176] By adaptively acquiring the local geometric parameters of the measured surface and determining the equivalent propagation speed, the excitation delay time is accurately calculated, the focusing precision of the ultrasonic beam in the complex curved surface composite material is improved, and the detection sensitivity and the accuracy of defect evaluation are improved.

[0177] In addition, in some preferred embodiments, the phased array composite ultrasonic flaw detector control system provided by the application can execute any one step in the above method.

[0178] The above only describes the embodiments of the application and is not used to limit the protection scope of the application. For those skilled in the art, the application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the application shall be included in the protection scope of the application.

Claims

1. A method of controlling a phased array composite ultrasonic flaw detector, characterized in that, The method comprises: acquiring multi-point distance data between a phased array probe and a measured curved surface of a composite component; based on the multi-point distance data, solving local geometric parameters of the measured curved surface under the phased array probe; acquiring actual transit times of ultrasonic echoes from internal feature reflectors of the composite component; based on the solved local geometric parameters and the acquired actual transit times of ultrasonic echoes, determining an equivalent propagation speed for representing ultrasonic wave propagation in the composite component through iterative correction; based on the solved local geometric parameters and the determined equivalent propagation speed, calculating a firing delay time for each array element of the phased array probe to compensate for focusing of a phased array ultrasonic beam in the composite component.

2. The method of claim 1, wherein, The step of determining the equivalent propagation speed for representing ultrasonic wave propagation in the composite component through iterative correction based on the solved local geometric parameters and the acquired actual transit times of ultrasonic echoes comprises: performing smoothing processing on the acquired actual transit times of ultrasonic echoes to obtain target transit times; determining the equivalent propagation speed for representing ultrasonic wave propagation in the composite component through iterative correction based on the solved local geometric parameters and the target transit times, wherein when an iterative calculation of the iterative correction reaches a preset resource limit condition, an equivalent propagation speed based on this iteration calculation is output; performing variation amplitude limiting processing on the equivalent propagation speed output by the iterative correction to obtain a final equivalent propagation speed.

3. The method of claim 2, wherein, The step of performing smoothing processing on the acquired actual transit times of ultrasonic echoes to obtain target transit times comprises: detecting a sequence of the acquired actual transit times of ultrasonic echoes to identify transit time step changes in the sequence of transit times to obtain identified transit time step changes; based on the identified transit time step changes, dividing the sequence of the acquired actual transit times of ultrasonic echoes into step change sections corresponding to the transit time step changes and non-step change sections corresponding to non-step changes; performing smoothing processing on transit time data of the non-step change sections to obtain smoothed transit time data of the non-step change sections; combining the smoothed transit time data of the non-step change sections and transit time data of the step change sections to generate the target transit times.

4. The method of claim 2, wherein, The step of determining the equivalent propagation speed for representing ultrasonic wave propagation in the composite component through iterative correction based on the solved local geometric parameters and the target transit times comprises: acquiring ultrasonic echo signals and corresponding actual transit times of a plurality of feature reflectors inside the composite component; for each acquired ultrasonic echo signal, evaluating a signal-to-noise ratio of the ultrasonic echo signal to obtain an evaluated signal-to-noise ratio; for each acquired ultrasonic echo signal, determining a sensitivity index of the transit time of the ultrasonic echo signal to the equivalent propagation speed to obtain a determined sensitivity index; selecting at least one feature reflector from the plurality of feature reflectors according to the obtained evaluation of the signal-to-noise ratio and the determined sensitivity index, to obtain a selected feature reflector; taking the actual transit time of the selected feature reflector as a target transit time for the iterative correction, and performing the iterative correction according to the calculated local geometric parameters and the target transit time for the iterative correction, to determine an equivalent propagation speed of the ultrasonic wave in the composite material member.

5. The method of claim 4, wherein, The step of determining, for each acquired ultrasonic echo signal, a sensitivity index of a transit time of the ultrasonic echo signal to a change in the equivalent propagation speed comprises: extracting, from the ultrasonic echo signal corresponding to the each acquired ultrasonic echo signal, an acoustic characteristic change indicating parameter for characterizing a change in an acoustic characteristic of an ultrasonic propagation path of the ultrasonic echo signal; calculating, based on geometric information of the ultrasonic propagation path corresponding to the each acquired ultrasonic echo signal, an initial sensitivity index of the ultrasonic echo signal; adjusting the initial sensitivity index according to the extracted acoustic characteristic change indicating parameter and the calculated initial sensitivity index, to determine the sensitivity index of the transit time of the ultrasonic echo signal to the change in the equivalent propagation speed.

6. The method of claim 5, wherein, The step of extracting, from the ultrasonic echo signal corresponding to the each acquired ultrasonic echo signal, an acoustic characteristic change indicating parameter for characterizing a change in an acoustic characteristic of an ultrasonic propagation path of the ultrasonic echo signal comprises: performing, for the ultrasonic echo signal corresponding to the each acquired ultrasonic echo signal, a section division processing on the ultrasonic echo signal to identify a noise-affected section, a signal pattern abnormal section and an echo overlapping section in the ultrasonic echo signal, to obtain an identification result of the section division processing; selecting, based on the identification result of the section division processing, at least one sub-echo section from the ultrasonic echo signal in which a signal feature meets a preset criterion, to obtain at least one selected sub-echo section; extracting, for the at least one selected sub-echo section, a preliminary acoustic characteristic parameter from each selected sub-echo section, to obtain the preliminary acoustic characteristic parameter corresponding to each selected sub-echo section; performing data fusion on the preliminary acoustic characteristic parameter corresponding to each selected sub-echo section extracted from the at least one selected sub-echo section, to obtain a data fusion result, and performing consistency evaluation and outlier data point removal on the data fusion result, to obtain the acoustic characteristic change indicating parameter for characterizing the change in the acoustic characteristic of the ultrasonic propagation path of the ultrasonic echo signal.

7. The method of claim 6, wherein, The step of performing data fusion on the preliminary acoustic characteristic parameter corresponding to each selected sub-echo section extracted from the at least one selected sub-echo section, to obtain a data fusion result, and performing consistency evaluation and outlier data point removal on the data fusion result, to obtain the acoustic characteristic change indicating parameter for characterizing the change in the acoustic characteristic of the ultrasonic propagation path of the ultrasonic echo signal comprises: receiving the preliminary acoustic characteristic parameters extracted from the selected at least one sub-echo section corresponding to each selected sub-echo section; performing data fusion on the preliminary acoustic characteristic parameters to obtain a data fusion result using a fusion algorithm with a computational complexity satisfying a preset condition; performing consistency evaluation on the data fusion result using a consistency evaluation method with a computational complexity satisfying a preset condition; performing outlier data point removal on the data fusion result using an outlier data point removal method with a computational complexity satisfying a preset condition; monitoring computing resource usage or processing time during the performance of the data fusion, the consistency evaluation, and the outlier data point removal; outputting a current processing result as an acoustic characteristic change indication parameter for representing acoustic characteristic change of an ultrasonic propagation path of the ultrasonic echo signal when a preset resource limit condition is reached.

8. The method of claim 7, wherein, The step of performing consistency evaluation on the data fusion result comprises: analyzing variation characteristics of the data fusion result sequence; based on the variation characteristics, identifying a section of the data fusion result sequence that meets a preset rapid variation criterion; for a section of the data fusion result sequence that does not meet the preset rapid variation criterion, evaluating data fluctuation thereof; based on a relationship between the data fluctuation and a preset noise threshold, determining whether the data fusion result is consistent.

9. The method of claim 1, wherein, The step of calculating the local geometric parameters of the measured surface under the phased array probe based on the multi-point distance data comprises: receiving the multi-point distance data; performing data processing on the multi-point distance data to reduce noise and remove outliers to obtain processed multi-point distance data; analyzing the processed multi-point distance data to identify local geometric characteristics of the measured surface to obtain identified local geometric characteristics; based on the identified local geometric characteristics, selecting a calculation strategy for calculating the local geometric parameters to obtain a selected calculation strategy; calculating the local geometric parameters of the measured surface under the phased array probe according to the selected calculation strategy and the processed multi-point distance data.

10. A phased array composite ultrasonic inspection system control system, characterized by, The system comprises: an acquisition distance module configured to acquire multi-point distance data between a phased array probe and a measured surface of a composite component; a calculation geometry module configured to calculate local geometric parameters of the measured surface under the phased array probe based on the multi-point distance data; an acquisition echo module configured to acquire actual ultrasonic echo transit time from an internal feature reflector of the composite component; a determination sound velocity module configured to determine an equivalent propagation sound velocity for representing ultrasonic wave propagation in the composite component through iterative correction according to the calculated local geometric parameters and the acquired actual ultrasonic echo transit time; a calculation delay module configured to calculate firing delay time for each array element of the phased array probe to compensate for focusing of a phased array ultrasonic beam in the composite component according to the calculated local geometric parameters and the determined equivalent propagation sound velocity.

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