Quality detection method, device and equipment for automobile PCBA

Abstract

The present application relates to a kind of quality detection method, device and equipment of automobile PCBA, belong to PCBA detection technical field, method steps: utilize middle wave infrared thermal imager to collect the thermal field video stream of PCBA positive and negative two sides under the condition of load power on, construct three-dimensional temperature field and extract heat conduction gradient component, generate heat flux density tensor matrix, analyze and locate positive and negative surface abnormal heating node;Adopt axial flip registration, accurately match positive and negative surface abnormal node in three-dimensional space, form point location registration area;Extract the absolute difference of the heat flux density component of the area positive and negative surface Z axis direction, only when the difference exceeds preset threshold, start wideband ultrasonic excitation, synchronously collect positive and negative surface acoustic surface wave group velocity dispersion curve, calculate cross-correlation function peak value;According to whether the peak value is lower than the metallurgical continuity determination benchmark, output the cross-face metallurgical defect information with double-face topological abnormal coordinates, and identify virtual welding, microcrack defect type through dispersion curve abnormal frequency band.

Description

Technical Field

[0001] This invention relates to the field of PCBA testing technology, and in particular to a quality testing method, apparatus, and equipment for automotive PCBAs. Background Technology

[0002] Currently, quality inspection of automotive electronic PCBAs primarily relies on X-ray tomography and automated optical inspection (AOI) technologies. X-rays can detect internal defects but cannot assess metallurgical continuity, resulting in a high rate of missed detections for cold solder joints. While AOI technology can quickly scan surface solder joints, its two-dimensional imaging limitation prevents the detection of bottom solder joints in BGA packages and internal defects in through-hole components. Traditional thermal imaging technology can locate fault areas through temperature field anomalies, but single-sided inspection suffers from high false alarm rates due to heat dissipation path interference and cannot distinguish whether heat conduction anomalies originate from solder joint failures on the front or back. Especially for double-sided high-density PCBAs, existing technologies lack spatial registration methods for front and back thermal field data and methods for cross-surface metallurgical defect correlation analysis, leading to insufficient inspection of critical automotive PCBAs such as engine control units. Summary of the Invention

[0003] The main objective of this invention is to provide a quality inspection method, apparatus, and equipment for automotive PCBAs, enabling high-precision detection of hidden defects such as solder joint voids and incomplete soldering in PCBAs, thereby significantly improving inspection efficiency and accuracy.

[0004] To achieve the above objectives, the present invention provides a quality inspection method for automotive PCBAs, comprising the following steps:

[0005] Acquire the front thermal field data of the PCBA under test under load power-on state, and identify the front abnormal nodes in the first topology carried in the front thermal field data.

[0006] The PCBA under test is axially flipped to obtain reverse thermal field data, and the reverse abnormal nodes of the second topology carried in the reverse thermal field data are identified.

[0007] Spatial coordinate registration is performed on the front and back abnormal nodes to obtain the point registration area;

[0008] Extract the heat flux density gradient difference between the front thermal field data and the back thermal field data from the point registration area, and determine whether the heat flux density gradient difference exceeds a preset threshold.

[0009] If so, then apply broadband ultrasonic excitation in the normal direction of the plate surface to the registration area, and simultaneously collect the surface acoustic wave group velocity dispersion curves of the front and back sides of the registration area under ultrasonic excitation, and calculate the peak value of the cross-correlation function of the front and back sides of the registration area of ​​the surface acoustic wave group velocity dispersion curve.

[0010] When the peak value of the cross-correlation function is determined to be lower than the criterion for metallurgical continuity, cross-plane metallurgical defect information with two-sided topological anomaly coordinates is output.

[0011] Further, the step of acquiring the front thermal field data of the PCBA under test under load power-on state and identifying the front abnormal nodes in the first topology carried in the front thermal field data includes:

[0012] A mid-wave infrared thermal imager is used to capture thermal field video stream data of the PCBA under test after it is powered on and in a steady state. The thermal field video stream data is then identified to obtain the front three-dimensional temperature field information of the PCBA under test.

[0013] Extract the heat conduction gradient component along the X / Y / Z axis of each pixel in the frontal three-dimensional temperature field information, thereby generating a heat flux density tensor matrix based on the heat conduction gradient component and generating a first topology using the information of each pixel on the X / Y / Z axis;

[0014] Positive anomalous nodes in the first topology are identified from the heat flux density tensor matrix using a preset analysis method.

[0015] Further, the step of axially flipping the PCBA under test to obtain reverse thermal field data and identifying reverse anomalous nodes of the second topology carried in the reverse thermal field data includes:

[0016] The adsorption head is used to adsorb any position on the front of the PCBA to be tested, and the adsorption head is rotated to flip it over;

[0017] By adopting the same abnormal node identification method as the front side of the PCBA under test, the three-dimensional temperature field information, second topology, and abnormal nodes on the reverse side are obtained.

[0018] Further, the step of performing spatial coordinate registration on the front and back anomaly nodes to obtain the point registration area includes:

[0019] By combining the X / Y / Z axes of the front and back three-dimensional temperature field information, a two-dimensional coordinate system of X / Y / Z / -Z is obtained;

[0020] Each pixel obtained from the thermal field video stream data is labeled in the two-dimensional coordinate system, and the pixel distance per unit of the two-dimensional coordinate system is determined.

[0021] Based on the pixel distance, the front abnormal node and the back abnormal node are calibrated in the double-sided coordinate system, and the overlapping parts of the front and back abnormal nodes in the double-sided coordinate system are registered.

[0022] After filtering and registration, other pixels and noise abnormal nodes on the dual-plane coordinate system are used to obtain the point registration area.

[0023] Further, the step of extracting the heat flux density gradient difference between the front thermal field data and the back thermal field data from the point registration area, and determining whether the heat flux density gradient difference exceeds a preset threshold, includes:

[0024] Extract the Z-axis heat flux density component of the registered point area in the front three-dimensional temperature field information, and simultaneously extract the -Z-axis heat flux density component of the same spatial coordinate position in the reverse three-dimensional temperature field information.

[0025] The absolute difference between the two Z-axis heat flux density components is calculated, and the absolute difference is compared with a preset heat flux density gradient threshold. When the absolute difference is greater than the heat flux density gradient threshold, it is determined that the preset threshold has been exceeded.

[0026] Further, the step of applying broadband ultrasonic excitation in the normal direction of the plate surface to the point registration region, and simultaneously acquiring the surface acoustic wave group velocity dispersion curves of the front and back surfaces of the point registration region under ultrasonic excitation, and calculating the peak value of the cross-correlation function of the front and back surfaces of the surface acoustic wave group velocity dispersion curve of the point registration region, includes:

[0027] Based on the plate surface normal vector of the point registration area in the dual-plane coordinate system, the beam focusing direction of the ultrasonic transducer array is adjusted, and a broadband ultrasonic pulse with adjustable pulse width is applied to the point registration area.

[0028] During the broadband ultrasonic pulse excitation,

[0029] By symmetrically deploying laser vibration probe groups on the front and back of the PCBA, the surface vibration waveforms of the registration area at the point are simultaneously acquired on the front and back. The surface acoustic wave group velocity dispersion curve is extracted from the surface vibration waveform. The signal similarity comparison calculation is performed on the surface acoustic wave group velocity dispersion curves of the front and back of the same registration area, and the peak value of the cross-correlation function characterizing the consistency of sound wave propagation on the front and back is output.

[0030] Furthermore, the step of outputting cross-plane metallurgical defect information with bi-plane topological anomaly coordinates when the peak value of the cross-correlation function is determined to be lower than the metallurgical continuity determination benchmark includes:

[0031] When the peak value of the cross-correlation function is lower than the preset judgment benchmark, the three-dimensional spatial coordinates of the point registration area with respect to that point are extracted and marked as two-sided topological anomaly coordinates.

[0032] Identify the anomalous frequency bands of the surface acoustic wave group velocity dispersion curves for the two-sided topological anomaly coordinates:

[0033] When the group velocity deviation in the 0.5-1.5MHz band is greater than 10%, the defect type is marked as a cold solder joint.

[0034] When the group velocity fluctuation in the 1.5-3MHz band is greater than 15%, the defect type is marked as microcrack.

[0035] This invention proposes a quality inspection device for automotive PCBAs, the device comprising:

[0036] The first identification unit is used to acquire the front thermal field data of the PCBA under test under load power-on state, and identify the front abnormal node in the first topology carried in the front thermal field data.

[0037] The second identification unit is used to axially flip the PCBA under test to obtain reverse thermal field data and identify the reverse abnormal nodes of the second topology carried in the reverse thermal field data.

[0038] The registration unit is used to register the spatial coordinates of the front abnormal node and the back abnormal node to obtain the point registration area.

[0039] The judgment unit is used to extract the heat flux density gradient difference between the front thermal field data and the back thermal field data from the point registration area, and to determine whether the heat flux density gradient difference exceeds a preset threshold.

[0040] The excitation unit is used to apply broadband ultrasonic excitation in the normal direction of the plate surface to the point registration area if the condition is met, and simultaneously acquire the surface acoustic wave group velocity dispersion curves of the front and back surfaces of the point registration area under ultrasonic excitation, and calculate the peak value of the cross-correlation function of the front and back surfaces of the point registration area of ​​the surface acoustic wave group velocity dispersion curve.

[0041] The reporting unit is used to output cross-plane metallurgical defect information with two-sided topological anomaly coordinates when the peak value of the cross-correlation function is lower than the judgment benchmark for metallurgical continuity.

[0042] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described quality inspection method for automotive PCBA.

[0043] The quality inspection method, apparatus, and equipment for automotive PCBAs provided by this invention have the following beneficial effects:

[0044] (1) The detection rate of cold solder joints / microcracks is improved through double-sided thermal field topology registration and thermo-acoustic verification process;

[0045] (2) Based on the point registration area, selective ultrasonic excitation is applied to shorten the single-board detection time. Attached Figure Description

[0046] Figure 1 This is a flowchart illustrating a quality inspection method for automotive PCBA according to an embodiment of the present invention;

[0047] Figure 2 This is a structural block diagram of a quality inspection device for automotive PCBA according to an embodiment of the present invention;

[0048] Figure 3 This is a schematic block diagram of the structure of a computer device according to an embodiment of the present invention.

[0049] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0051] Reference Figure 1 This is a flowchart illustrating a quality inspection method for automotive PCBAs proposed in this invention. The invention uses a computer device as the executing entity to perform the quality inspection method for automotive PCBAs, which includes the following steps:

[0052] S101, acquire the front thermal field data of the PCBA under test under load power-on state, and identify the front abnormal node in the first topology carried in the front thermal field data.

[0053] S102, axially flip the PCBA under test to obtain reverse thermal field data, and identify the reverse abnormal nodes of the second topology carried in the reverse thermal field data;

[0054] S200, Spatial coordinate registration is performed on the front abnormal node and the back abnormal node to obtain the point registration area;

[0055] S300, extract the heat flux density gradient difference between the front thermal field data and the back thermal field data from the point registration area, and determine whether the heat flux density gradient difference exceeds a preset threshold.

[0056] S400, if so, apply broadband ultrasonic excitation in the normal direction of the plate surface to the point registration area, and simultaneously collect the surface acoustic wave group velocity dispersion curves of the front and back surfaces of the point registration area under ultrasonic excitation, and calculate the peak value of the cross-correlation function of the front and back surfaces of the point registration area of ​​the surface acoustic wave group velocity dispersion curve.

[0057] S500, when the peak value of the cross-correlation function is determined to be lower than the determination benchmark for metallurgical continuity, output cross-plane metallurgical defect information with double-sided topological anomaly coordinates.

[0058] The core of steps S101, S102 to S500 lies in constructing a dual-sided thermo-acoustic cross-modal verification system to solve the long-standing industry challenge of detecting hidden defects. First, the thermal characteristics of the PCBA are excited by an energized load, and infrared thermal imaging data from both sides are collected. Thermodynamic topology analysis is then used to locate abnormal heating nodes on both sides. Subsequently, an innovative axial flipping collaborative spatial registration mechanism is employed to precisely match the abnormal nodes on both sides in three-dimensional space, forming key detection areas (i.e., point registration areas). For these key areas, the difference in heat flux density gradient between the two sides is further extracted for initial screening. Only when the difference exceeds an engineering experience threshold is high-cost acoustic detection initiated. At this point, directional broadband ultrasound is applied to the target area, and the propagation characteristics of surface acoustic waves on both sides are simultaneously collected. The metallurgical continuity quality is quantified by calculating the peak value of the cross-correlation function of the acoustic wave signals from both sides. Finally, based on strict judgment criteria, a defect report with spatial coordinates is output, achieving a technical closed loop from "thermal anomaly location" to "acoustic verification" and then to "metallurgical defect judgment."

[0059] In one embodiment, the step of acquiring front thermal field data of the PCBA under test under load and identifying front anomalous nodes in the first topology carried in the front thermal field data includes:

[0060] A mid-wave infrared thermal imager is used to capture thermal field video stream data of the PCBA under test after it is powered on and in a steady state. The thermal field video stream data is then identified to obtain the front three-dimensional temperature field information of the PCBA under test.

[0061] Extract the heat conduction gradient component along the X / Y / Z axis of each pixel in the frontal three-dimensional temperature field information, thereby generating a heat flux density tensor matrix based on the heat conduction gradient component and generating a first topology using the information of each pixel on the X / Y / Z axis;

[0062] Positive anomalous nodes in the first topology are identified from the heat flux density tensor matrix using a preset analysis method.

[0063] In practice:

[0064] The steps for acquiring thermal field video stream data of the PCBA under test after it has reached a steady state following power-on using a mid-wave infrared thermal imager, and for identifying the frontal three-dimensional temperature field information of the PCBA under test from the thermal field video stream data, specifically involve: A mid-wave infrared thermal imager (operating wavelength 3-5μm) fixed directly above the PCBA continuously acquires thermal radiation video stream data after the PCBA reaches thermal equilibrium. This operating wavelength is selected based on the characteristic radiation spectrum of silicon-based materials used in automotive electronic components, which can significantly reduce environmental thermal noise interference. Based on the continuous frame thermal radiation data stream acquired by the infrared thermal imager, a heat conduction differential equation model is then established for each pixel. By solving the boundary conditions and heat source distribution of this model in three-dimensional space, the temperature gradient field perpendicular to the board surface (Z-axis) is inverted. This process integrates the physical constraints of surface thermal radiation intensity distribution and material thermal conductivity, ultimately constructing a temperature field matrix containing X / Y / Z three-dimensional coordinates.

[0065] In the steps of extracting the heat conduction gradient components along the X / Y / Z axes of each pixel in the frontal three-dimensional temperature field information, and generating a heat flux density tensor matrix based on the heat conduction gradient components, and generating a first topology using the information of each pixel on the X / Y / Z axes, the specific steps are as follows: For each spatial voxel point (i.e., containing X / Y / Z coordinates after 3D reconstruction) in the frontal three-dimensional temperature field, high-precision calculation of the heat conduction gradient components is performed along the three orthogonal axes of the Cartesian coordinate system: In the X-axis direction, the lateral heat conduction rate is calculated based on the temperature difference between adjacent pixels and the spatial step size ratio. In the Y-axis direction, an adaptive sliding window method is used to track the slope of temperature change along the copper foil trace direction. In the Z-axis direction, by solving the second-order partial derivative of the Fourier heat conduction equation in the thickness direction, the temperature gradient perpendicular to the plate surface inside the substrate can be derived. Where T is temperature. This represents the unloaded temperature of the PCBA; this process introduces the material's anisotropic thermal conductivity tensor. (i,j=x,y,z) serves as a physical constraint to ensure that the gradient component calculation conforms to the actual heat conduction characteristics of the PCBA. After obtaining the gradient components for each axis, they are vectorized as follows: Then, the global heat flux density tensor matrix Q is constructed. The matrix has an n×3 structure (n is the total number of voxels). Each element Q corresponds to the heat flux density component of the m-th voxel on the k-th axis (k=1,2,3→x,y,z), where the negative sign indicates that the direction of heat flux is opposite to the direction of temperature increase. The heat flux continuity equation is embedded in the matrix operations. • Q=0 is used as a boundary condition to eliminate energy non-conservation errors caused by measurement noise. Finally, a thermodynamic topology network is generated based on this tensor matrix: voxel points are abstracted into nodes using graph theory algorithms, and the cosine of the angle between the heat flux density vectors of adjacent nodes is used as the boundary condition. Connection weights are calculated, and strong connections (representing continuous heat conduction paths) are established when |cosθ|>0.95. Points where |cosθ|<0.3 are identified as heat conduction interruptions (corresponding to solder joint failures or voids). The Floyd-Warshall shortest path algorithm is used to identify the main paths from critical heat sources to heat dissipation ends. Combined with node degree distribution analysis, abnormally high thermal resistance regions are located, thus generating a hierarchical first topology structure—represented as a 3D point cloud. Highlighted topology nodes correspond to actual solder joint locations, edge weights map heat flux, and topology break zones precisely identify potential defect locations.

[0066] The step of identifying positive anomalous nodes in the first topology from the heat flux density tensor matrix using a preset analysis method specifically involves: normalizing the heat flux density tensor matrix Q to construct a density-like matrix. ,in `tr` represents the conjugate transpose operation, and `tr` represents the matrix trace operation. This density matrix satisfies the fundamental properties of quantum mechanics. Then, the preset calculations are performed: ,in, For trace normalization, when S approaches 0, it is determined that heat conduction is ordered; when S approaches 1, it is determined that heat conduction is ordered. At time n, thermal conduction is disordered between adjacent voxel points in the first topology. Voxel points with disordered thermal conduction are identified as positive abnormal nodes.

[0067] In one embodiment, the step of axially flipping the PCBA under test to obtain reverse thermal field data and identifying reverse anomalous nodes of the second topology carried in the reverse thermal field data includes:

[0068] The adsorption head is used to adsorb any position on the front of the PCBA to be tested, and the adsorption head is rotated to flip it over;

[0069] By adopting the same abnormal node identification method as the front side of the PCBA under test, the three-dimensional temperature field information, second topology, and abnormal nodes on the reverse side are obtained.

[0070] In one embodiment, the step of spatial coordinate registration of the frontal and back anomaly nodes to obtain the point registration area includes:

[0071] By combining the X / Y / Z axes of the front and back three-dimensional temperature field information, a two-dimensional coordinate system of X / Y / Z / -Z is obtained;

[0072] Each pixel obtained from the thermal field video stream data is labeled in the two-dimensional coordinate system, and the pixel distance per unit of the two-dimensional coordinate system is determined.

[0073] Based on the pixel distance, the front abnormal node and the back abnormal node are calibrated in the double-sided coordinate system, and the overlapping parts of the front and back abnormal nodes in the double-sided coordinate system are registered.

[0074] After filtering and registration, other pixels and noise abnormal nodes on the dual-plane coordinate system are used to obtain the point registration area.

[0075] In practical implementation:

[0076] The specific steps to obtain the X / Y / Z / -Z biplane coordinate system by combining the X / Y / Z axes of the front and back three-dimensional temperature field information are as follows: Millimeter-level precise positioning of the front and back temperature fields is achieved through six-degree-of-freedom spatial reference reconstruction technology. The core lies in establishing a globally unified biplane orthogonal coordinate system to eliminate spatial errors introduced during the flipping process. The specific execution flow is as follows: First, during the front thermal field acquisition stage, with the PCBA geometric center as the origin O, an initial right-handed coordinate system is established based on the board's physical edge—the X-axis points along the length direction to the board-end connector, the Y-axis is parallel to the memory slot along the width direction, and the Z-axis is perpendicular to the board surface pointing to the component mounting side (defined as the front direction). At this time, all temperature field data are bound to this (X,Y,Z) coordinate system. After the PCBA completes a 180° axial flip, the flip trajectory is tracked in real time by a high-precision laser displacement sensor. Combined with encoder feedback from the motion control system, the spatial orientation vector and rotation angle of the flip axis are accurately calculated. The thermal field data of the reverse side is transformed from a temporary coordinate system to a mirror coordinate system (-Z') with the same origin O as the reference. The key correction steps include: 1) Axial deviation compensation - using the least squares method to fit the deviation between the actual flip axis and the ideal axis, and aligning the coordinate axis direction through a rotation transformation matrix; 2) Translation error elimination - setting reference markers at the corners of the PCBA based on the three-point positioning principle to compensate for the micron-level displacement caused by clamping. Finally, a six-dimensional coordinate system (X,Y,Z,-Z) shared by both sides is formed, with the following characteristics: the positive Z-axis and the negative -Z-axis are strictly collinear and opposite (angle 180°±0.1°), the positive X-axis and the negative -X-axis are completely coincident in the XY plane projection (position deviation ≤0.03mm), and the magnitude of all axial unit vectors is normalized (scale error <0.01%). This coordinate system allows the spatial coordinates of any solder joint on both sides to be expressed as a precise correspondence between (x, y, z) and (x, y, - z).

[0077] Each pixel acquired from the thermal field video stream data is calibrated in the dual-plane coordinate system, and the pixel distance per unit in the dual-plane coordinate system is determined. Based on the pixel distance, the front and back abnormal nodes are calibrated in the dual-plane coordinate system, and the overlapping parts of the front and back abnormal nodes in the dual-plane coordinate system are registered. Other pixels and noise abnormal nodes after registration are filtered in the dual-plane coordinate system to obtain the point registration area. Specifically, the original thermal field video stream data acquired by the infrared thermal imager is first mapped to the dual-plane coordinate system, where each pixel (u,v) is converted into a specific position in six-dimensional coordinates (X,Y,Z,-Z) based on its PCBA spatial pose at the imaging time, and the unit pixel distance d is determined based on the calibration board reference. Subsequently, spatial calibration was performed on the identified front and back abnormal nodes: the coordinate set {P_front} of the front abnormal node and the set {P_back} of the back abnormal node were extracted in the two-sided coordinate system, and a point-to-point mapping relationship was established through a bidirectional nearest neighbor search algorithm. When two points satisfy the spatial distance condition ‖P_front - P_back‖≤√3·d and the included normal angle <5°, they are determined to be coincident nodes.

[0078] In one embodiment, the step of extracting the heat flux density gradient difference between the front thermal field data and the back thermal field data from the point registration area, and determining whether the heat flux density gradient difference exceeds a preset threshold, includes:

[0079] Extract the Z-axis heat flux density component of the registered point area in the front three-dimensional temperature field information, and simultaneously extract the -Z-axis heat flux density component of the same spatial coordinate position in the reverse three-dimensional temperature field information.

[0080] The absolute difference between the two Z-axis heat flux density components is calculated, and the absolute difference is compared with a preset heat flux density gradient threshold. When the absolute difference is greater than the heat flux density gradient threshold, it is determined that the preset threshold has been exceeded.

[0081] In this embodiment, the heat flux density component along the Z-axis (perpendicular to the PCBA board surface and pointing towards the component mounting side) in the front three-dimensional temperature field information is extracted from the point registration area. This component reflects the intensity of heat conduction from the inside of the PCBA to the front component side, and is obtained by solving the product of the temperature gradient and thermal conductivity of the substrate material in the Z-axis direction. Simultaneously, the heat flux density component along the -Z-axis (collinear with the front Z-axis and pointing towards the other side of the substrate after the PCBA is rotated 180° axially) in the reverse three-dimensional temperature field information at the same spatial coordinate position is extracted, forming a bidirectional characterization of the cross-plane heat conduction path. Subsequently, the absolute difference between the heat flux density components in these two directions was calculated. This difference directly reflects the continuity of heat flow conduction on both sides of the PCBA at the same spatial location: when the metallurgical structure, such as solder joints or metallized vias, is intact, heat can form a smooth conduction path across both sides of the substrate, resulting in a small difference in the absolute values ​​of the heat flux density components on both sides; however, when there are hidden defects such as solder joint voids, poor solder joints, or broken metallized vias, heat flow is obstructed during cross-plane conduction, preventing effective transfer of heat flow in the Z-axis direction from the front side to the back side. This leads to a significant reduction in the heat flux density in the Z-axis direction on the back side, ultimately resulting in a significant increase in the absolute difference between the two. The calculated absolute difference was compared with a preset heat flux density gradient threshold, which was set based on actual operating conditions and engineering experience of automotive PCBAs to distinguish between normal heat conduction and abnormal defect states. When the absolute difference exceeds a preset threshold, it is determined that there is an abnormal heat flow conduction in the registration area at that point, requiring the initiation of subsequent broadband ultrasonic excitation testing. The continuity of the metallurgical structure is further verified using the surface acoustic wave group velocity dispersion curve. If the difference does not exceed the threshold, it indicates that the heat flow conduction in that area is normal, and costly acoustic testing is unnecessary. This step, through cross-surface difference analysis of heat flow conduction, achieves efficient screening of defect areas, avoiding the waste of resources in full-area testing and providing a precise target area for subsequent acoustic verification, ensuring the economy and accuracy of the testing process.

[0082] In one embodiment, the step of applying broadband ultrasonic excitation in the normal direction of the plate surface to the registration area and simultaneously acquiring the surface acoustic wave group velocity dispersion curves of the front and back surfaces of the registration area under ultrasonic excitation, and calculating the peak value of the cross-correlation function of the front and back surfaces of the surface acoustic wave group velocity dispersion curves of the registration area includes:

[0083] Based on the plate surface normal vector of the point registration area in the dual-plane coordinate system, the beam focusing direction of the ultrasonic transducer array is adjusted, and a broadband ultrasonic pulse with adjustable pulse width is applied to the point registration area.

[0084] During the broadband ultrasonic pulse excitation,

[0085] By symmetrically deploying laser vibration probe groups on the front and back of the PCBA, the surface vibration waveforms of the registration area at the point are simultaneously acquired on the front and back. The surface acoustic wave group velocity dispersion curve is extracted from the surface vibration waveform. The signal similarity comparison calculation is performed on the surface acoustic wave group velocity dispersion curves of the front and back of the same registration area, and the peak value of the cross-correlation function characterizing the consistency of sound wave propagation on the front and back is output.

[0086] In practical implementation, based on the previously established dual-plane coordinate system (with the PCBA geometric center as the origin and the Z-axis perpendicular to the board surface), the normal vector of the board surface in the registration area is first determined (i.e., the positive direction of the Z-axis or the reversed -Z-axis direction, both collinear and opposite). The ultrasonic transducer array integrates 6 independently controllable phased array units, each containing 128 miniature piezoelectric ceramic wafers. The normal angle of the target area is calculated in real time using an industrial-grade motion control card, and the excitation timing of each wafer is dynamically adjusted (accuracy up to 10ns) to ensure that the main lobe direction of the ultrasonic beam is strictly aligned with the board surface normal (deviation ≤0.5°), ensuring that the energy is concentrated on the path that vertically penetrates the solder joint or metallized via. The excitation signal uses a linear frequency modulated (LFM) pulse with adjustable pulse width (50-500ns), covering a frequency range of 2-10MHz. The wideband mode was chosen because low-frequency components (2-5MHz) can penetrate thicker substrates (such as 2mm FR-4 boards) to detect deep solder joint defects; high-frequency components (5-10MHz) are sensitive to surface microcracks (≥50μm). The excitation power is maintained at 50-150mW / mm² through closed-loop feedback control to avoid damage to PCBA components due to excessive energy. Three sets of confocal laser Doppler vibrometers (LDDV) are fixed 200mm above the front of the PCBA. Each set includes X / Y / Z triaxial sensors with a focused spot diameter of 50μm, capable of accurately capturing amplitude changes at the 0.1nm level. Vibration probes of the same specifications are symmetrically arranged below the back side, and rigid supports ensure that the spatial coordinates of the front and back sensor arrays are strictly mirrored (positional deviation ≤10μm). The synchronous triggering system uses a 100MHz crystal oscillator clock to ensure that the timestamp error of the front and back acquisition cards (24-bit ADC, sampling rate 10MS / s) is <100ns, achieving nanosecond-level synchronous acquisition of vibration signals. The acquired raw vibration signal (time-domain waveform) is first filtered by a 500Hz-15MHz bandpass filter to remove environmental noise, and then subjected to a short-time Fourier transform (STFT, using a Hann window with a window length of 512 points) to generate a time-frequency distribution matrix. Considering the typical dispersion characteristics of surface acoustic waves (Rayleigh waves) (group velocity decreases with increasing frequency), the energy centroid method is used to extract the group velocity at each frequency point: for a frequency fk, the energy-weighted average time delay τk of that frequency component in the time-frequency matrix is ​​calculated, and the group velocity vg(fk) = d / τk (where d is the distance between detection points, pre-calibrated as a known quantity using a two-dimensional coordinate system). Finally, a two-dimensional frequency-group velocity curve is generated, i.e., the surface acoustic wave group velocity dispersion curve, whose shape reflects the uniformity of the elastic modulus of the material's surface and subsurface layers (0-500μm depth). The dispersion curves of the same detection point on both sides are truncated in the frequency range (uniformly set to 2-8MHz) and resampled (at 0.1MHz intervals) to eliminate frequency misalignment caused by slight differences in excitation bandwidth. The curve was baseline corrected using the least squares method to remove systematic bias caused by temperature drift (drift rate ≤ 0.05% / ℃).Subsequently, a phase consistency algorithm is used to take the starting frequency point (2MHz) of the curve as a reference to ensure that the frequency axes of the positive and negative curves are strictly aligned (error ≤0.02MHz).

[0087] In one embodiment, when the peak value of the cross-correlation function is determined to be lower than the metallurgical continuity determination benchmark, the step of outputting cross-plane metallurgical defect information with two-sided topological anomaly coordinates includes:

[0088] When the peak value of the cross-correlation function is lower than the preset judgment benchmark, the three-dimensional spatial coordinates of the point registration area with respect to that point are extracted and marked as two-sided topological anomaly coordinates.

[0089] Identify the anomalous frequency bands of the surface acoustic wave group velocity dispersion curves for the two-sided topological anomaly coordinates:

[0090] When the group velocity deviation in the 0.5-1.5MHz band is greater than 10%, the defect type is marked as a cold solder joint.

[0091] When the group velocity fluctuation in the 1.5-3MHz band is greater than 15%, the defect type is marked as microcrack.

[0092] In practical implementation, based on the previously established double-sided six-dimensional coordinate system (X,Y,Z,-Z), the coordinates of each detection point within the registration area on the front side are \((x, y, z)\), and the corresponding mirror coordinates on the back side after a 180° axial flip are \((x, y, -z)\). The two are strictly aligned through the board surface normal vector (Z-axis). When the peak value of the cross-correlation function is lower than the judgment benchmark, the coordinate extraction module is automatically triggered to retrieve the three-dimensional coordinate parameters of the detection point from the double-sided coordinate system database, forming double-sided topological anomaly coordinates containing the spatial positions of the front and back sides (format: front \((x, y, z)\) / back \((x, y, -z)\)). This coordinate not only marks the two-dimensional position of the defect on the PCBA board surface (X / Y axis) but also accurately represents its depth information in the thickness direction (Z-axis). The synchronous output of double-sided coordinates solves the problem that traditional single-sided inspection cannot accurately locate cross-sided defects. For example, when there is a break in the metallized hole between the front solder joint and the back pad, the front anomaly coordinate corresponds to the center of the solder joint \((10mm, 15mm, 0.8mm)\), and the back anomaly coordinate corresponds to the center of the pad \((10mm, -15mm, -0.8mm)\). The two coordinates directly reflect the spatial distribution of the defect through the coordinate difference in the Z-axis thickness direction (1.6mm, i.e., the substrate thickness), avoiding the positioning ambiguity caused by a single front or back inspection.

[0093] The 0.5-1.5MHz low-frequency band corresponds to wavelengths of 3-6mm (group velocity approximately 3000m / s). In this band, acoustic energy primarily affects the interface between the solder joint and the substrate, making it sensitive to a decrease in interfacial bonding strength. Poor solder joint defects (solder joint to pad metallurgical bonding area <50%) can lead to interfacial acoustic impedance mismatch, causing a regular deviation in group velocity at low frequencies.

[0094] 1.5-3MHz mid-frequency band: corresponding to wavelengths of 1-2mm, acoustic wave penetration depth of approximately 0.5-1mm, sensitive to local elastic modulus changes caused by microcracks (length ≥100μm). When microcracks exist inside the solder joint, the stiffness inhomogeneity of the acoustic wave propagation path leads to intensified group velocity fluctuations.

[0095] Calculate the measured group velocity within the target frequency band Frequency group velocity corresponding to standard defect-free samples Relative deviation: When any frequency point within the 0.5-1.5MHz band When the frequency fluctuation is greater than 15% in the 1.5-3MHz band, it is identified as a cold solder joint. When the group velocity fluctuation is greater than 15%, the defect type is marked as a microcrack.

[0096] Reference Appendix Figure 2 This is a structural block diagram of a quality inspection device for automotive PCBA proposed in this invention. The device includes:

[0097] The first identification unit is used to acquire the front thermal field data of the PCBA under test under load power-on state, and identify the front abnormal node in the first topology carried in the front thermal field data.

[0098] The second identification unit is used to axially flip the PCBA under test to obtain reverse thermal field data and identify the reverse abnormal nodes of the second topology carried in the reverse thermal field data.

[0099] The registration unit is used to register the spatial coordinates of the front abnormal node and the back abnormal node to obtain the point registration area.

[0100] The judgment unit is used to extract the heat flux density gradient difference between the front thermal field data and the back thermal field data from the point registration area, and to determine whether the heat flux density gradient difference exceeds a preset threshold.

[0101] The excitation unit is used to apply broadband ultrasonic excitation in the normal direction of the plate surface to the point registration area if the condition is met, and simultaneously acquire the surface acoustic wave group velocity dispersion curves of the front and back surfaces of the point registration area under ultrasonic excitation, and calculate the peak value of the cross-correlation function of the front and back surfaces of the point registration area of ​​the surface acoustic wave group velocity dispersion curve.

[0102] The reporting unit is used to output cross-plane metallurgical defect information with two-sided topological anomaly coordinates when the peak value of the cross-correlation function is lower than the judgment benchmark for metallurgical continuity.

[0103] Reference Figure 3 This invention also provides a computer device, which can be a server, and its internal structure can be as follows: Figure 3 As shown, the computer device includes a processor, memory, display screen, input device, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores the data corresponding to this embodiment. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements the above-described method.

[0104] Those skilled in the art will understand that Figure 3 The structures shown are merely block diagrams of some structures related to the present invention and do not constitute a limitation on the computer devices on which the present invention is applied.

[0105] In summary, this invention discloses a quality inspection method for automotive PCBAs, which solves the problem of detecting hidden defects by constructing a dual-sided thermo-acoustic cross-modal verification system. The method steps are as follows: First, a mid-wave infrared thermal imager is used to collect thermal field video streams of the front and back sides of the PCBA under load, constructing a three-dimensional temperature field and extracting the heat conduction gradient component to generate a heat flux density tensor matrix. Abnormal heating nodes on the front and back sides are located through thermodynamic topology analysis. Second, an axial flip-coordinated six-dimensional coordinate system registration technique is used to accurately match the abnormal nodes on the front and back sides in three-dimensional space, forming a point registration area. Then, the absolute difference of the heat flux density components in the Z-axis direction of the front and back sides in this area is extracted. Only when the difference exceeds a preset threshold is broadband ultrasonic excitation initiated, and the dispersion curves of surface acoustic wave group velocity on the front and back sides are acquired simultaneously, and the peak value of the cross-correlation function is calculated. Finally, based on whether the peak value is lower than the metallurgical continuity judgment benchmark, a cross-sided metallurgical defect report with dual-sided topological anomaly coordinates is output, and defect types such as cold solder joints and microcracks are identified through the abnormal frequency band of the dispersion curve. This invention achieves high-precision detection of hidden defects such as voids and cold solder joints in PCBA through a closed-loop technology of "thermal anomaly location - thermal flow screening - acoustic verification", which significantly improves detection efficiency and accuracy and provides key technical support for the reliability of automotive electronics.

[0106] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the present invention and embodiments can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual-rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM, etc.

[0107] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, apparatus, article, or method. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, apparatus, article, or method that includes that element.

[0108] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A quality detection method of an automobile PCBA, characterized in that, The method comprises the following steps: Obtaining the front thermal field data of the PCBA under load and power-on state, and identifying the front abnormal nodes in the first topological structure carried in the front thermal field data; Axially flipping the PCBA to obtain the back thermal field data, and identifying the back abnormal nodes in the second topological structure carried in the back thermal field data; Spatial coordinate registration is performed on the front abnormal nodes and the back abnormal nodes to obtain a point registration area; The heat flux density gradient difference of the front thermal field data and the back thermal field data is extracted from the point registration area, and it is determined whether the heat flux density gradient difference exceeds a preset threshold value; If yes, a plate normal wideband ultrasonic excitation is applied to the point registration area, and the surface acoustic wave group velocity dispersion curves of the front and back surfaces of the point registration area under ultrasonic excitation are synchronously collected, and the peak value of the cross-correlation function of the surface acoustic wave group velocity dispersion curves of the front and back surfaces of the point registration area is calculated; When the peak value of the cross-correlation function is lower than the determination benchmark of metallurgical continuity, the cross-surface metallurgical defect information with double-surface topological abnormal coordinates is output.

2. The method of claim 1, wherein, The step of obtaining the front thermal field data of the PCBA under load and power-on state, and identifying the front abnormal nodes in the first topological structure carried in the front thermal field data, comprises: A middle-wave infrared thermal imager is used to collect thermal field video stream data of the PCBA after power-on and steady state, and the front three-dimensional temperature field information of the PCBA is obtained by identifying the thermal field video stream data; The thermal conduction gradient components of each pixel point along the X / Y / Z axes are extracted from the front three-dimensional temperature field information, so as to generate a heat flux density tensor matrix according to the thermal conduction gradient components, and generate a first topological structure by using the information of each pixel point on the X / Y / Z axes; The front abnormal nodes in the first topological structure are calibrated from the heat flux density tensor matrix by a preset analysis method.

3. The method of claim 2, wherein, The step of axially flipping the PCBA to obtain the back thermal field data, and identifying the back abnormal nodes in the second topological structure carried in the back thermal field data, comprises: Any position of the front of the PCBA is adsorbed by an adsorption head, and the adsorption head is rotated to realize flipping; The same abnormal node identification method as the front of the PCBA is used to obtain the back three-dimensional temperature field information, the second topological structure, and the back abnormal nodes.

4. The method of claim 3, wherein, The step of performing spatial coordinate registration on the front abnormal nodes and the back abnormal nodes to obtain a point registration area, comprises: The X / Y / Z axes in the front three-dimensional temperature field information and the back three-dimensional temperature field information are combined to obtain a double-surface coordinate system of X / Y / Z / -Z; Each pixel point obtained by the thermal field video stream data is calibrated in the double-surface coordinate system to determine the pixel distance of the double-surface coordinate system unit; Based on the pixel distance, the front abnormal nodes and the back abnormal nodes are calibrated in the double-surface coordinate system, and the overlapping parts of the front and back abnormal nodes in the double-surface coordinate system are registered; Other pixel points and noise abnormal nodes on the double-surface coordinate system after registration are filtered to obtain the point registration area.

5. The method of claim 4, wherein, The step of extracting the heat flux density gradient difference of the front and back thermal field data from the point registration area and judging whether the heat flux density gradient difference exceeds a preset threshold value, comprises: extracting the Z-axis direction heat flux density component of the point registration area in the front three-dimensional temperature field information, and synchronously extracting the -Z-axis direction heat flux density component of the same spatial coordinate position in the back three-dimensional temperature field information; calculating the absolute difference of the two Z-axis direction heat flux density components, and comparing the absolute difference with a preset heat flux density gradient threshold value, when the absolute difference is greater than the heat flux density gradient threshold value, it is determined that the preset threshold value is exceeded.

6. The method of claim 5, wherein the method further comprises: The step of applying a plate normal wideband ultrasonic excitation to the point registration area, and synchronously collecting the surface acoustic wave group velocity dispersion curve of the point registration area of the front and back surfaces under the ultrasonic excitation, and calculating the peak value of the cross-correlation function of the surface acoustic wave group velocity dispersion curve of the point registration area of the front and back surfaces, comprises: According to the plate normal vector of the point registration area in the double-face coordinate system, adjusting the beam focusing direction of the ultrasonic transducer array, and applying a pulse width adjustable wideband ultrasonic pulse excitation to the point registration area; During the action of the wideband ultrasonic pulse excitation, Through the laser vibration probe group symmetrically arranged on the front and back surfaces of the PCBA, the surface vibration waveforms of the point registration area on the front and back surfaces are synchronously collected, the surface acoustic wave group velocity dispersion curve is extracted from the surface vibration waveform, the signal similarity comparison calculation is performed on the surface acoustic wave group velocity dispersion curves of the front and back surfaces of the same point registration area, and the cross-correlation function peak value representing the consistency of the front and back surface acoustic wave propagation is output.

7. The method of claim 6, wherein the method further comprises: The step of outputting the cross-face metallurgical defect information with double-face topological abnormal coordinates when the cross-correlation function peak value is lower than the determination criterion of metallurgical continuity, comprises: When the cross-correlation function peak value is lower than the preset determination criterion, the three-dimensional spatial coordinates of the point registration area for the point are extracted, and are marked as double-face topological abnormal coordinates; Identify the abnormal frequency band of the surface acoustic wave group velocity dispersion curve of the double-face topological abnormal coordinates: When the group velocity deviation of the 0.5-1.5MHz frequency band is greater than 10%, mark the defect type as false welding; When the group velocity fluctuation of the 1.5-3MHz frequency band is greater than 15%, mark the defect type as micro-crack.

8. A quality detection device for an automobile PCBA, characterized in that, Comprise: The first identification unit is used for acquiring the front thermal field data of the PCBA under the load energized state, and identifying the front abnormal nodes in the first topological structure carried in the front thermal field data; The second identification unit is used for axially flipping the PCBA to obtain the back thermal field data, and identifying the back abnormal nodes of the second topological structure carried in the back thermal field data; The registration unit is used for spatial coordinate registration of the front abnormal nodes and the back abnormal nodes to obtain a point registration area; The judgment unit is used for extracting the heat flux density gradient difference of the front and back thermal field data from the point registration area, and judging whether the heat flux density gradient difference exceeds a preset threshold value; The excitation unit is configured to, if yes, apply a broad-frequency ultrasonic excitation in the plate normal direction to the point registration area, synchronously collect the surface acoustic wave group velocity dispersion curves of the front and back surfaces of the point registration area under the ultrasonic excitation, and calculate a cross-correlation function peak value of the surface acoustic wave group velocity dispersion curves of the front and back surfaces of the point registration area. The reporting unit is configured to output cross-surface metallurgical defect information with double-face topological abnormal coordinates when the cross-correlation function peak value is lower than the determination benchmark of metallurgical continuity. 9.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-8. The processor implements the steps of the quality detection method of the automobile PCBA in any one of claims 1 to 7 when executing the computer program.

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