Non-contact detection system for internal quality of large-size thin-wall reinforced structure

Abstract

The invention discloses a non-contact detection system for the internal quality of a large-size thin-wall reinforced structure. The non-contact detection system comprises a laser ultrasonic detection module, a 3D dynamic vision imaging module, a mechanical motion module and a signal processing and control module. The laser ultrasonic detection module detects surface vibration of a detected object and obtains detailed information of internal defects of the detected object. The 3D dynamic vision imaging module scans and obtains three-dimensional information of a measured object and generates a three-dimensional model. And the mechanical motion module drives the laser ultrasonic detection module and the 3D dynamic vision imaging module through self movement, so that the omnibearing detection of a detected object is realized. And the signal processing and control module sets a motion path of the mechanical motion module, controls the laser ultrasonic detection module to detect a detected object, obtains defect information in a scanning range of the detected object, marks a defect position on a generated three-dimensional model, and completes in-situ detection of the internal quality of the large-size thin-wall reinforced structure.

Description

Technical Field

[0001] The invention relates to a non-contact detection system for the internal quality of a large-size thin-walled reinforced structure, and belongs to the field of internal damage defect detection of metals and composite materials. Background Art

[0002] Thin-walled reinforced structures are widely used in aerospace, automotive, shipbuilding and other fields due to their excellent light weight and high strength characteristics. Traditional contact ultrasonic testing methods have detection blind spots when dealing with complex geometric shapes, and it is difficult to fully cover the inspected area. In addition, although the X-ray detection method can penetrate the material and provide images of internal defects, it needs to be carried out in a specific site, which is very limited, has strict requirements on the operating environment, and is inconvenient to detect complex structures such as internal attachment loads. There are certain limitations in the detection methods of the internal quality of thin-walled reinforced structures with a size of more than 2 meters and a thickness of less than 5mm. Summary of the invention

[0003] The technical problem solved by the present invention is: to overcome the deficiencies of the prior art and to propose a non-contact detection system for the internal quality of a large-sized thin-walled reinforced structure, which can perform in-situ detection of the internal quality of the large-sized thin-walled reinforced structure.

[0004] The technical solution of the present invention is:

[0005] A non-contact detection system for the internal quality of a large-sized thin-walled reinforced structure, comprising a laser ultrasonic detection module, a 3D dynamic visual imaging module, a mechanical motion module, and a signal processing and control module;

[0006] The laser ultrasonic detection module detects the surface vibration of the object being tested and obtains detailed information on the internal defects of the object being tested;

[0007] The 3D dynamic visual imaging module scans and obtains the three-dimensional information of the object to be measured and generates a three-dimensional model, providing guidance for the mechanical motion module so that the laser ultrasonic detection module can accurately scan the object to be measured;

[0008] The mechanical motion module is connected to the laser ultrasonic detection module and the 3D dynamic visual imaging module, and drives the laser ultrasonic detection module and the 3D dynamic visual imaging module through its own movement to achieve all-round detection of the object being detected;

[0009] The signal processing and control module is connected to the laser ultrasonic detection module, the 3D dynamic visual imaging module and the mechanical motion module. The motion path of the mechanical motion module is set through the three-dimensional information provided by the 3D dynamic visual imaging module, and the laser ultrasonic detection module is controlled to detect the object to be detected, so as to obtain the defect information within the scanning range of the object to be detected and mark the defect position on the generated three-dimensional model.

[0010] Furthermore, the laser ultrasonic detection module includes a laser excitation module and a laser vibration measurement module;

[0011] The laser excitation module is used to generate an excitation signal, which acts on the surface of the object to be measured to generate ultrasonic waves;

[0012] The laser vibration measurement module is used to detect the ultrasonic response of the object being measured and send the change in the measured surface vibration to the signal processing and control module.

[0013] Furthermore, the mechanical motion module includes a robotic arm and an AGV platform transfer vehicle; the AGV platform transfer vehicle is equipped with a robotic arm and a signal processing and control module; the end of the robotic arm is connected to a laser ultrasonic detection module and a 3D dynamic visual imaging module.

[0014] Further, the 3D dynamic visual imaging module includes an industrial camera and an image processing unit;

[0015] Industrial cameras are used to capture high-resolution images of the objects being measured. The resolution of industrial cameras is greater than 1024×576, the frame rate is ≤30FPS, and the detection angle is not less than 130°×105°;

[0016] The image processing unit processes the captured images to generate a three-dimensional model.

[0017] Furthermore, the signal processing and control module includes a signal processing unit, an automation control unit and an FPGA module;

[0018] The FPGA module receives the ultrasonic response information and forwards it to the signal processing unit, and sends the motion path output by the automation control unit to the mechanical motion module;

[0019] The signal processing unit performs noise reduction processing on the ultrasonic detection A-scan and C-scan signals in the ultrasonic response information, determines different ultrasonic modes through the frequency characteristics of the flight time data, calculates the thin wall thickness at different positions, and obtains the internal defect information within the scanning range of the object being tested;

[0020] The automation control unit controls the movement of the robotic arm and the AGV platform transfer vehicle, sets the movement path according to the shape of the object to be tested and the detection requirements, and sends it to the FPGA module.

[0021] The method of non-contact detection of internal quality of large-size thin-walled reinforced structure using non-contact detection system of internal quality includes:

[0022] S1: The AVG platform transfer vehicle is controlled by the automated control unit to move the non-contact detection system for the internal quality of large-size thin-walled reinforced structures to the vicinity of the object to be tested, and the posture of the industrial robotic arm is adjusted so that the laser ultrasonic detection module is located at the detection starting position of the object to be tested;

[0023] S2: Design path scanning parameters, plan scanning paths, and complete parameter settings based on the imaging task characteristics and accuracy requirements of the object being measured;

[0024] S3: The 3D dynamic visual imaging module starts to reconstruct the 3D model of the local area of ​​the object being tested. After completing the scanning of a single local area, the industrial robotic arm moves along the set planning path; the laser ultrasonic detection module moves under the drive of the industrial robotic arm, and the industrial robotic arm sends an excitation instruction to the laser excitation module. After receiving the instruction, the laser excitation module starts to excite, and at the same time, the laser vibration measurement module starts to work and transmits the data to the information processing unit through the FPGA module;

[0025] S4: After completing the local area detection, the information processing unit will accurately determine the spatial position and size of the defect based on the area of ​​ultrasonic field emission distortion, resonance or scattering, and analyze the size, shape and depth information of the defect by combining the multi-physics field finite element model and the time-frequency domain characteristics of the ultrasonic field to obtain the internal defect information of the object under test;

[0026] S5: After all defects have been dealt with, the automation control unit continues to send instructions to the industrial robot arm to move the industrial robot arm to the next local area for inspection, and repeats steps S3 to S5 until the inspection of all areas is completed.

[0027] Furthermore, in step S5, after all defect problems have been dealt with, the automation control unit continues to send instructions to the industrial robot arm, so that the industrial robot arm moves to the next local area for inspection, and the overlapping width of two adjacent local areas is not less than 10 cm.

[0028] Furthermore, before executing step S1, a series of position and orientation markers are placed in the field of view of the robotic arm and the 3D dynamic vision imaging module, the positions of the markers observed by the 3D dynamic vision imaging module under different postures of the robotic arm are recorded, and the transformation matrix is ​​iteratively optimized to achieve coordinate system alignment.

[0029] Furthermore, in step S4, after obtaining the internal defect information of the object to be tested, the human-computer interaction interface will display all defect positions and size information on the C-scan image and mark them accordingly in the three-dimensional model; click on the defect location in the three-dimensional model, and the automation control unit controls the industrial robot arm to drive the laser ultrasonic detection module to move to the defect location, and the laser excitation module emits a laser to mark the actual defect location.

[0030] The advantages of the present invention compared with the prior art are:

[0031] (1) The present invention can realize the automatic detection of the object by the robotic arm driving the laser detection module through the coordinate system registration of the robotic arm, the laser detection module and the 3D dynamic visual imaging module, and has the function of synchronously marking the defect position of the model and the real object, thereby realizing the tracking of the defect position.

[0032] (2) The present invention uses a laser to perform defect detection on the object to be detected by combining a laser ultrasonic detection module, a robotic arm and an AGV platform cart, thereby solving the problem that traditional ultrasonic detection has blind spots and is difficult to detect for complex geometric shapes. It realizes non-contact and all-round internal defect detection of large-sized thin-walled reinforced structures, and can be used for structures of different configurations. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0034] Figure 1 This is a schematic diagram of a laser vibration measurement module according to an embodiment of the present invention;

[0035] Figure 2 Schematic diagram of a non-contact detection system for the internal quality of a large-size thin-walled reinforced structure according to an embodiment of the present invention. DETAILED DESCRIPTION

[0036] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0037] The present invention proposes a non-contact detection system for the internal quality of a large-size thin-walled reinforced structure, which can be applied to the detection of spacecraft cabin structure products.

[0038] The detection system is Figure 2 As shown, it includes a laser ultrasonic detection module 1, a 3D dynamic visual imaging module 2, a mechanical motion module, and a signal processing and control module.

[0039] (1) Laser ultrasonic detection module 1

[0040] The laser ultrasonic detection module 1 does not need to directly contact the object to be tested, avoiding the defects of traditional contact ultrasonic detection. It can detect the surface vibration of the object to be tested with high precision and obtain detailed information of internal defects. The ultrasonic imaging resolution is better than 0.1mm; the laser ultrasonic detection bandwidth covers 1kHz~200MHz; the vibration displacement resolution (noise equivalent displacement resolution) of ultrasonic detection is better than 4×10 -7 nm(W / Hz) 1 / 2 ; Data sampling rate ≥ 1GS / s. The laser ultrasonic detection module 1 includes a laser excitation module and a laser vibration measurement module.

[0041] The laser excitation module has an IP65 waterproof and dustproof rating and is used to generate excitation signals. The pulse laser acts on the surface of the detection object through short, high-energy laser pulses to generate ultrasonic waves. The pulse width of the module is ≤10ns, the single pulse laser energy is ≥50mJ, the repetition frequency is ≥400Hz, the energy stability is ≤1%, and the divergence angle is ≤2mrad. In this embodiment, the nanosecond pulse laser uses a 1064nm nanosecond pulse laser as the light source, which can achieve a gain of more than 100 times the laser pulse energy, and ultimately can meet the high-power, high-repetition-rate laser output of >40mJ.

[0042] The laser vibration measurement module is used to detect the ultrasonic response of the structure under test. By measuring the changes in surface vibration, information about the internal defects of the structure can be obtained. It is based on the principle of dual-wave mixing laser vibration measurement of photorefractive crystal dynamic holographic diffraction grating, such as Figure 1 As shown, the inherent vibration suppression and high sensitivity characteristics of this method are used to resist the influence of environmental interference on the measurement performance. In this embodiment, the laser vibration measurement module uses a laser light source with a wavelength of 1550nm as the light source, and its power is above 3W, which can be applicable to the detection of structural parts under different reflective conditions.

[0043] (2) 3D dynamic visual imaging module 2

[0044] The 3D dynamic visual imaging module 2 can generate a high-precision three-dimensional model of the object being tested; it can communicate with the laser ultrasonic testing module 1 in real time to obtain defect information of the object being tested, and provide guidance for laser ultrasonic surface scanning and timely detection and positioning of defects.

[0045] The 3D dynamic visual imaging module 2 includes an industrial camera and an image processing unit. The industrial camera has a resolution greater than 1024×576, a frame rate ≤30FPS, and a detection angle of not less than 130°×105°, and is used to capture high-resolution images of the object being measured. The image processing unit is responsible for processing the captured images and generating a high-precision 3D model.

[0046] (3) Mechanical motion module

[0047] The mechanical motion module is responsible for carrying the laser ultrasonic detection module 1 and the 3D dynamic visual imaging module 2 to achieve all-round scanning and detection of large-scale thin-walled reinforced structures. The laser ultrasonic detection module 1 and the 3D dynamic visual imaging module 2 are physically integrated through the mechanical motion module to ensure the high accuracy of laser emission and reception during the detection process, as well as the integrity of 3D imaging.

[0048] The mechanical motion module includes an AGV platform transfer vehicle 8 and an industrial robot arm 9. The AGV platform transfer vehicle 8 carries the industrial robot arm 9 and the signal processing and control module, with a rated load of ≥1.5t, and can achieve a load scanning motion of more than 40kg when the industrial robot arm 9 is straightened. The driving wheel group is 4 Mecanum wheels, with a mobile positioning accuracy of ±5mm, a running speed of 0-20m / min, and a single-point micro-motion amount of ≤0.5mm.

[0049] The industrial robot arm 9 has high-precision, multi-degree-of-freedom motion capabilities, and can flexibly move the laser ultrasonic detection module 1 and the 3D dynamic visual imaging module 2 to ensure that the laser ultrasonic detection module 1 can cover every corner of the object being measured. In this embodiment, the industrial robot arm 9 has six axes, a maximum load of 85kg, a rated load of 70kg, a working range of 2100mm, and a posture repeatability of ±0.05mm.

[0050] (4) Signal processing and control module

[0051] The signal processing and control module is responsible for collecting and processing the detection signals, and controlling and managing the entire detection process. The module has functions such as host computer, analog input, external trigger and external clock drive.

[0052] The signal processing and control module includes a signal processing unit 4, an automatic control unit 5, an FPGA module 6 and a human-machine interaction interface 7. The laser ultrasonic detection module 1 is connected to the automatic control unit 5 and the FPGA module 6 for communication via an optical fiber and a light guide 3.

[0053] The signal processing unit 4 processes the collected signals through a variety of algorithms, including wavelet transform, adaptive filtering, noise reduction, etc., to improve the signal-to-noise ratio. Different ultrasonic modes can be determined by the frequency characteristics of the flight time data, so as to calculate the thickness of the thin wall at different positions. And according to the results of ultrasonic testing, the thickness data at different positions of the object under test can be obtained and drawn into a thickness map. Further data analysis and processing can be performed, such as calculating statistical quantities such as the average value and standard deviation to determine the quality status of the variable thickness structure.

[0054] The automatic control system 5 is closely integrated with the mechanical motion module, the laser ultrasonic detection module 1, and the 3D dynamic visual imaging module 2, and is responsible for the automatic control of the entire detection process, including path planning, parameter setting, data collection, etc. It can control the movement of the mechanical arm and the AGV platform transfer vehicle to ensure the accuracy of the scanning path and the high efficiency of the detection. According to the shape of the object to be detected and the detection requirements, the optimized path planning is carried out to improve the detection efficiency.

[0055] FPGA module 6 can realize high-speed triggering and synchronization interface, ensuring high-performance synchronous signal acquisition and processing.

[0056] The human-machine interface 7 provides an interactive interface between the operator and the system, which is convenient for setting up and monitoring the system. The entire system can be fully controlled and managed through the human-machine interface 7. The scanning path can be optimized according to the detection requirements and the shape of the object to improve the detection efficiency.

[0057] The specific operation of the non-contact detection system for the internal quality of large-size thin-walled reinforced structures is as follows:

[0058] Step 1: Place a series of markers of position and direction in the field of view of the industrial robot arm 9 and the 3D dynamic visual imaging module 2, record the position of the markers observed by the 3D dynamic visual imaging module 2 under different postures of the industrial robot arm 9, and perform iterative optimization of the transformation matrix to achieve coordinate system alignment. Then, the AVG platform transfer vehicle 8 is controlled by the automated control unit 5 to move a non-contact detection system for the internal quality of a large-sized thin-walled reinforced structure to the vicinity of the object to be measured, and adjust the posture of the industrial robot arm 9 so that the laser ultrasonic detection module 1 it carries is located at the detection starting position of the object to be measured.

[0059] Step 2: According to the imaging task characteristics and accuracy requirements of the object to be measured, design the path scanning parameters in the human-computer interaction interface 7, plan the optimal scanning path, and complete the parameter setting.

[0060] Step 3: The 3D dynamic visual imaging module 2 starts to reconstruct the 3D model of the local area of ​​the object being measured. After completing the scanning of a single small area, the industrial robot arm 9 moves along the set planning path.

[0061] Step 4: The laser ultrasonic detection module 1 moves according to a pre-designed trajectory driven by the industrial robot arm 9. The industrial robot arm 9 sends an excitation instruction to the laser excitation module. After receiving the instruction, the laser excitation module starts to excite. At the same time, the laser vibration measurement module starts working and transmits the data to the information processing unit 4 through the FPGA module 6.

[0062] Step 5: After completing the local area detection, the information processing unit 4 will accurately determine the spatial position and size of the defect based on the area of ​​ultrasonic field emission distortion, resonance or scattering, and combine the multi-physics field finite element model and the time / frequency domain characteristics of the ultrasonic field to analyze the size, shape, depth and other information of the defect, and quickly obtain the internal defect information of the object under test. Finally, the human-computer interaction interface 7 will display all the defect positions and size information on the C-scan map and mark them in the three-dimensional model accordingly. The inspection personnel can control the industrial robot arm 9 through the automation control unit 5 to drive the laser ultrasonic detection module 1 to move to the defect position, and the laser excitation module will emit a laser to mark the actual defect location.

[0063] Step 6: After all defects have been dealt with, the automation control unit 5 continues to send instructions to the industrial robot 9 to move it to the next position for inspection. The overlapping area width of adjacent shooting areas is not less than 10 cm. Repeat steps 3 to 5 until all areas are inspected.

[0064] Step 7: The inspector determines whether the result is qualified based on the acquired defect information and the location map of the 3D model where the defect is located. If qualified, a qualified inspection report is issued. If abnormal, an unqualified inspection report with defect information is output.

[0065] The above-described embodiments are only preferred specific implementations of the present invention. Common changes and substitutions made by those skilled in the art within the scope of the technical solution of the present invention should be included in the protection scope of the present invention.

Claims

1. A non-contact detection system for the internal quality of a large-sized thin-walled reinforced structure, characterized in that: It includes laser ultrasonic detection module, 3D dynamic visual imaging module, mechanical motion module and signal processing and control module; The laser ultrasonic detection module detects the surface vibration of the object being tested and obtains detailed information on the internal defects of the object being tested; The 3D dynamic visual imaging module scans and obtains the three-dimensional information of the object to be measured and generates a three-dimensional model, providing guidance for the mechanical motion module so that the laser ultrasonic detection module can accurately scan the object to be measured; The mechanical motion module is connected to the laser ultrasonic detection module and the 3D dynamic visual imaging module, and drives the laser ultrasonic detection module and the 3D dynamic visual imaging module through its own movement to achieve all-round detection of the object being detected; The signal processing and control module is connected to the laser ultrasonic detection module, the 3D dynamic visual imaging module and the mechanical motion module. The motion path of the mechanical motion module is set through the three-dimensional information provided by the 3D dynamic visual imaging module, and the laser ultrasonic detection module is controlled to detect the object to be detected, so as to obtain the defect information within the scanning range of the object to be detected and mark the defect position on the generated three-dimensional model.

2. The non-contact detection system for internal quality of large-size thin-walled reinforced structures according to claim 1 is characterized in that: The laser ultrasonic detection module includes a laser excitation module and a laser vibration measurement module; The laser excitation module is used to generate an excitation signal, which acts on the surface of the object to be measured to generate ultrasonic waves; The laser vibration measurement module is used to detect the ultrasonic response of the object being measured and send the change in the measured surface vibration to the signal processing and control module.

3. The non-contact detection system for internal quality of large-size thin-walled reinforced structures according to claim 1 is characterized in that: The mechanical motion module includes a robotic arm and an AGV platform transfer vehicle; the AGV platform transfer vehicle is equipped with a robotic arm and a signal processing and control module; the end of the robotic arm is connected to a laser ultrasonic detection module and a 3D dynamic visual imaging module.

4. The non-contact detection system for internal quality of large-size thin-walled reinforced structures according to claim 1 is characterized in that: The 3D dynamic visual imaging module includes an industrial camera and an image processing unit; Industrial cameras are used to capture high-resolution images of the objects being measured. The resolution of industrial cameras is greater than 1024×576, the frame rate does not exceed 30FPS, and the detection angle is not less than 130°×105°; The image processing unit processes the captured images to generate a three-dimensional model.

5. The non-contact detection system for internal quality of large-size thin-walled reinforced structures according to claim 3 is characterized in that: The signal processing and control module includes a signal processing unit, an automation control unit and an FPGA module; The FPGA module receives the ultrasonic response information and forwards it to the signal processing unit, and sends the motion path output by the automation control unit to the mechanical motion module; The signal processing unit performs noise reduction processing on the ultrasonic detection A-scan and C-scan signals in the ultrasonic response information, determines different ultrasonic modes through the frequency characteristics of the flight time data, calculates the thin wall thickness at different positions, and obtains the internal defect information within the scanning range of the object being tested; The automation control unit controls the movement of the robotic arm and the AGV platform transfer vehicle, sets the movement path according to the shape of the object to be tested and the detection requirements, and sends it to the FPGA module.

6. A method for non-contact detection of internal quality of a large-sized thin-walled reinforced structure using the non-contact detection system for internal quality of claim 5, characterized in that: include: S1: The AVG platform transfer vehicle is controlled by the automated control unit to move the non-contact detection system for the internal quality of large-size thin-walled reinforced structures to the vicinity of the object to be tested, and the posture of the industrial robotic arm is adjusted so that the laser ultrasonic detection module is located at the detection starting position of the object to be tested; S2: Design path scanning parameters, plan scanning paths, and complete parameter settings based on the imaging task characteristics and accuracy requirements of the object being measured; S3: The 3D dynamic visual imaging module starts to reconstruct the 3D model of the local area of ​​the object being tested. After completing the scanning of a single local area, the industrial robotic arm moves along the set planning path; the laser ultrasonic detection module moves under the drive of the industrial robotic arm, and the industrial robotic arm sends an excitation instruction to the laser excitation module. After receiving the instruction, the laser excitation module starts to excite, and at the same time, the laser vibration measurement module starts to work and transmits the data to the information processing unit through the FPGA module; S4: After completing the local area detection, the information processing unit will accurately determine the spatial position and size of the defect based on the area of ​​ultrasonic field emission distortion, resonance or scattering, and analyze the size, shape and depth information of the defect by combining the multi-physics field finite element model and the time-frequency domain characteristics of the ultrasonic field to obtain the internal defect information of the object under test; S5: After all defects have been dealt with, the automation control unit continues to send instructions to the industrial robot arm to move the industrial robot arm to the next local area for inspection, and repeats steps S3 to S5 until the inspection of all areas is completed.

7. The method for non-contact detection of internal quality according to claim 6, characterized in that: In step S5, after all defect problems have been dealt with, the automation control unit continues to send instructions to the industrial robot arm to move the industrial robot arm to the next local area for inspection. The overlapping width of two adjacent local areas is not less than 10 cm.

8. The method for non-contact detection of internal quality according to claim 6, characterized in that: Before executing step S1, place a series of markers of position and direction in the field of view of the robotic arm and the 3D dynamic vision imaging module, record the positions of the markers observed by the 3D dynamic vision imaging module under different postures of the robotic arm, and perform iterative optimization of the transformation matrix to achieve coordinate system alignment.

9. The method for non-contact detection of internal quality according to claim 6, characterized in that: In step S4, after obtaining the internal defect information of the object to be tested, the human-computer interaction interface will display all defect positions and size information on the C-scan image and mark them accordingly in the three-dimensional model; click on the defect location in the three-dimensional model, and the automation control unit controls the industrial robot arm to drive the laser ultrasonic detection module to move to the defect location, and the laser excitation module emits a laser to mark the actual defect location.

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