PCB flying probe test path optimization method based on electrical characteristics

Abstract

The application relates to the technical field of probe testing, in particular to a PCB flying probe test path optimization method based on electrical characteristics, which comprises the following steps: determining the risk type of a test point according to the accessibility score of the test point and the distribution of the test point and elements, and determining the risk area grade corresponding to a grid unit according to the accessibility score and a potential shadow area; optimizing the test path of a probe according to the risk area grade corresponding to the grid unit, and adjusting the initial moving speed of the test path of the probe in different grid units; for the same moving timing sequence of different probe groups, determining overlapping grids according to the initial probe angle and the test path corresponding to the probe, and determining whether there is a collision risk between the probes according to the initial moving speed of the probes in different grid units; when there is a collision risk between the probes, corresponding adjustment measures are taken according to the number of overlapping grids. The application combines multidimensional optimization of a test path based on the electrical characteristics and testability design of a board.

Description

Technical Field

[0001] This invention relates to the field of probe testing technology, and in particular to a method for optimizing PCB flying probe test paths based on electrical characteristics. Background Technology

[0002] Flying probe testing is a PCB electrical testing technique that does not require the fabrication of a dedicated bed of needles fixture. It verifies the electrical characteristics of a PCB, such as short circuits, open circuits, and component values, by controlling the movement of multiple precision probes to contact test points. It is widely used in PCB prototype verification, small-batch production, and high-reliability product testing.

[0003] The testing efficiency of a flying probe tester directly depends on the quality of the probe movement path planning. The goal of path planning is to minimize the total testing time while ensuring test coverage, and the testing time mainly consists of the probe's idle travel time and test switching time.

[0004] Currently, the mainstream flying needle test path optimization methods in existing technologies mainly focus on the geometric path planning level. The core of this method is to abstract the problem into a Traveling Salesman Problem (TSP) or a Multiple Traveling Salesman Problem (mTSP).

[0005] Chinese Patent Publication No. CN117890766A discloses a path optimization method for a two-layer structured flying probe tester based on clustering, comprising the following steps: S1, importing network data from a network with test points, and dividing the network into single-sided or double-sided networks according to whether the test points are set on one or both sides of the PCB board; then, determining the linkage mode of the flying probes based on the number of test points on the single-sided or double-sided network, wherein the flying probes include left and right flying probes; S2, using the DBSCAN algorithm to cluster all the networks on the PCB board, calculating the center coordinates of each cluster, and determining the... The flying probe needs to traverse clusters when testing the connectivity of a PCB board; S3, calculate the shortest distance point pairs between different clusters using the two-pointer method, and use the shortest distance point pairs as the inter-cluster distance; S4, determine the cluster detection order of the flying probe for different clusters using a preset first algorithm; S5, determine the test point detection order of the flying probe for the test points within each cluster using a preset second algorithm; S6, divide the path using the network as a boundary to obtain the movement path of the flying probe; S7, determine whether the movement path causes a collision between the left and right flying probes. If so, return to step S6; if not, output the movement path as the path optimization result. Therefore, the path optimization method for the two-layer structure flying probe tester based on clustering has the following problems:

[0006] Treating test points merely as abstract geometric points and optimizing solely to minimize total travel distance fails to address the fundamental nature of PCB testing: electrical verification. Different electrical networks and test types (such as continuity, insulation, and four-wire measurements) impose inherent constraints and requirements on probe coordination and sequence. Existing designs fail to grasp electrical principles like "star testing" and "common ground testing," resulting in numerous unnecessary probe movements and switching, thus failing to improve efficiency at the root of the testing logic.

[0007] The path planning did not fully consider the physical characteristics of the PCB layout, component height, and test point accessibility. For high-density boards or boards with tall components blocking the way, the planned path may not be feasible and requires manual intervention to avoid obstacles, which increases the complexity of the project. Summary of the Invention

[0008] To address this, the present invention provides a PCB flying probe test path optimization method based on electrical characteristics, which overcomes the problems of neglecting the single dimension of electrical characteristic optimization and being disconnected from testability design in the prior art.

[0009] To achieve the above objectives, this invention provides a PCB flying probe test path optimization method based on electrical characteristics, comprising:

[0010] The board surface is divided into several grid cells according to the initial resolution. The grid cells in the potential shadow area are identified based on the grid cell label values ​​and the probe test parameters. The initial probe angle corresponding to the test point in the grid cell is determined by combining the interval distance between the test points.

[0011] High-density test points are identified based on the proximity distance between several test points and adjacent test points. Region types are divided based on whether several grid cells contain high-density test points. The region types include high-density regions and low-density regions. The test order of several test points in different region types is determined based on the region types.

[0012] Different probe group testing and movement methods are determined based on whether there is a need for ground detection at the test point, and the corresponding test point is determined based on the board image to determine whether it is in the board surface contamination area, and the judgment criteria for whether the probe group measures the continuity of the test point are adjusted accordingly.

[0013] Based on the distribution of test points and components on the board, the accessibility score of several test points is calculated to determine the risk type of the test points. Based on the accessibility score and the potential shadow area, the risk level of several grid cells is determined.

[0014] The probe's test path is optimized based on the risk zone level corresponding to several grid cells, and the initial movement speed of the probe's test path in different grid cells is adjusted.

[0015] For the same movement sequence of different probe groups, the overlapping grid is determined according to the initial probe angle and test path of the probe, and the collision risk between probes is determined by combining the initial movement speed of the probe in different grid cells.

[0016] When there is a risk of collision between probes, the initial probe angle or movement parameters corresponding to the probes are determined based on the number of overlapping grids.

[0017] Furthermore, the process of identifying mesh cells within potential shadowed areas includes:

[0018] The simulated probe approaches the plate surface at an initial probe angle. Centered on the coordinates of the test point, within a rectangular area with parameters of probe arm diameter and initial probe angle, if there is a grid cell with a height higher than the grid cell where the test point is located, the grid cells within this rectangular area are marked as potential shadow areas.

[0019] Furthermore, the process of determining the initial probe angle corresponding to the test point within the grid cell includes:

[0020] When the probe moves to a test point in a grid cell within a potential shaded area, the initial probe angle is increased based on the labeled value of the grid cell within the rectangular area, and the initial probe angle corresponding to the probe is decreased based on the theoretical interval distance between test points that cannot be in the same measurement sequence.

[0021] Furthermore, the process of determining the testing order of several test points based on the region type includes:

[0022] Calculate the proximity distance between several test points and adjacent test points based on the coordinates of several test points;

[0023] When the neighbor spacing is less than the minimum density evaluation threshold, the test point and its neighboring test points are determined to be high-density test points, and the corresponding test point and the grid cells where the neighboring test points are located are merged.

[0024] The region consisting of several grids containing all high-density test points is divided into a high-density region, and the region consisting of the remaining connected grid cells is divided into a low-density region.

[0025] The testing order priority for high-density areas is higher than that for low-density areas.

[0026] Furthermore, pixel-level difference calculation is performed between the image of the grid cell where the test point is located and the reference image. If the difference between the regional difference comparison results of the grid images is greater than the difference evaluation value, it is determined that the test point is located in the contaminated area of ​​the board surface.

[0027] Furthermore, the process of adjusting the criteria for determining whether the probe group measures the continuity at the test points includes:

[0028] If the test point is located in a contaminated area on the board, change the resistance threshold to the threshold range.

[0029] When the measured value is below the threshold range, it is determined that the test point is conductive and the line connection is good;

[0030] When the measured value exceeds the threshold range, it is determined that the test point is open-circuited and the line between the test points is broken.

[0031] When the measured value is within the threshold range, it is determined that the measured value of the test point is affected by the contamination of the board surface, and the circuit connection is good or slightly open.

[0032] Furthermore, the process of determining the risk zone level corresponding to several grid cells includes:

[0033] A circular analysis area is defined with the test point as the center and a specific radius. The accessibility score of several test points is calculated based on the distribution parameters of the components within the area.

[0034] When the risk factor in the shaded area is one or the accessibility score is less than or equal to the first accessibility threshold, the grid cell is judged to have component occlusion or extreme crowding, and the grid cell is marked as a high-risk area.

[0035] When the risk factor in the shaded area is zero and the accessibility score is greater than the first accessibility threshold but less than the second accessibility threshold, the grid cell is judged to be unobstructed but spatially cramped, and the grid cell is marked as a medium-risk area.

[0036] When the risk factor in the shaded area is zero and the accessibility score is greater than or equal to the second accessibility threshold, the grid cell is judged to be open and easy to access, and the grid cell is marked as a low-risk area.

[0037] Furthermore, the total movement cost of the grid cell is calculated based on the risk cost level of the risk zone where the grid cell is located, and the total movement cost is the movement reference value of the test path;

[0038] In low-risk areas, the probe moves at its initial speed; in medium-risk areas, the initial speed is reduced based on the ratio of the accessibility score to a second accessibility threshold; and in high-risk areas, the initial speed is reduced based on the ratio of the accessibility score to a first accessibility threshold.

[0039] Furthermore, the process of determining the overlapping grid includes:

[0040] The initial probe angles of probes from different probe groups in the same moving sequence are obtained to determine the grid cells through which the probe projection passes, and the overlapping grids are determined based on whether the grid cells overlap.

[0041] For several overlapping grid cells, the time difference between probes from different probe groups passing through the overlapping grid is determined. If the time difference is less than or equal to the critical time difference, it is determined that there is a risk of collision between the probes.

[0042] When the time difference is greater than the critical time difference, it is determined that there is no risk of collision between the probes.

[0043] Furthermore, when there is a risk of collision between probes, appropriate adjustment measures are taken based on the number of overlapping grids;

[0044] When the ratio of the number of overlapping grids to the number of grids occupied by probe projections from different probe groups is less than the projection ratio threshold, and the initial probe angle corresponding to the overlapping grid is greater than the standard angle, it is determined that the collision risk between probes is low, and the initial probe angle corresponding to the probe is adjusted.

[0045] When the ratio of the number of overlapping grids to the number of grids occupied by probe projections of different probe groups is greater than or equal to the projection ratio threshold, or when the initial probe angle corresponding to the overlapping grid is greater than or equal to the standard angle, the movement path or movement sequence of any probe is adjusted.

[0046] Compared with existing technologies, the advantages of this invention are as follows: The probes themselves have certain physical dimensions, and collisions may occur in extremely dense areas. Therefore, constraints are necessary; the distance between probes cannot be less than the probe arm diameter. If the distance between adjacent test points is too small, the detection angle of the two probes can be adjusted to avoid collisions. However, if the distance between adjacent test points is too small, the probe arm may hit adjacent components or pads when contacting a point, leading to short circuit risks or collisions. This method achieves accurate prediction and intelligent control of the probe movement path by meshing the PCB board surface and marking three-dimensional height information. It automatically identifies "potential shadow areas" formed by tall components and dynamically adjusts the probe approach angle to avoid collisions. Simultaneously, by calculating the theoretical interval distance between test points, the measurement sequence and attitude of the probes are intelligently planned, prioritizing the safe distance between probes. This collaborative optimization method based on three-dimensional spatial perception significantly improves the path efficiency and reliability of flying probe testing while ensuring absolute safety, effectively solving the collision risk and access difficulties in high-density PCB testing.

[0047] Furthermore, the vertical approach distance is used as a scoring factor to ensure the probe has sufficient Z-axis travel for a safe descent; neighborhood congestion is used as a scoring factor to reflect the risk of lateral collisions to the probe arm; and the attenuation coefficient controls the rate at which the score decreases with increasing Ci. This scheme quantitatively analyzes the vertical space and neighborhood congestion of test points, and uses a weighted scoring model and exponential mapping function to transform complex physical accessibility issues into accurate accessibility scores. It can automatically and objectively identify high-risk test points, providing reliable data support for subsequent path planning and probe attitude adjustment, thereby significantly improving the automation, safety, and testing efficiency of flying probe testing.

[0048] Furthermore, surface contamination can affect test accuracy and reliability. This method utilizes a vision camera integrated on the probe to acquire in-situ images of the test points and combines image differential technology to intelligently identify surface contamination. When a high risk of surface contamination is detected, the threshold of the continuity test resistance is automatically increased. By dynamically adjusting the resistance threshold to a conservative range of 10-30Ω, it can effectively distinguish between true open circuits and poor contact caused by contamination, significantly reducing the false alarm rate. This method improves the robustness and reliability of flying probe testing under non-ideal conditions without affecting the true positive detection rate.

[0049] Furthermore, traditional path planning algorithms such as A* and genetic algorithms only optimize geometric distances. This invention improves upon this by transforming grid risk levels into movement costs. This scheme constructs a refined grid risk map by integrating shaded area risk and accessibility scores. Based on dynamically configuring movement cost weights according to different risk levels, the path planning algorithm can automatically avoid high-risk areas, generating a globally optimal path that is not only short but also traverses low-risk areas as much as possible. Simultaneously, the probe movement speed is adjusted in real-time according to the risk level, achieving an optimal balance between testing efficiency and safety in complex PCB environments, significantly improving the intelligence and reliability of flying probe testing.

[0050] Furthermore, during the probe group's movement to the next test point, collisions may occur between probes due to conflicting test paths. However, changing the probe's movement path or inserting waiting sequences when there is a risk of collision will increase the probe's movement time, thereby reducing the overall detection efficiency. This method predicts the collision risk by calculating several intersecting movement paths under the current movement trajectory, and determines the level of collision risk by the number of overlapping grids and the size of the probe's projected area. It predicts the overlapping area of ​​the probe's movement trajectory and quantifies the collision risk by combining time step analysis. The system can intelligently select adjustment strategies based on the overlapping grid ratio and probe angle; it fine-tunes the probe angle for low-risk scrapes and uses path avoidance or timing delays for high-risk collisions. This hierarchical control mechanism minimizes the impact on testing efficiency while ensuring absolute safety, achieving refined intelligent control of multi-probe collaborative operation. Attached Figure Description

[0051] Figure 1 This is a flowchart illustrating the PCB flying probe test path optimization method based on electrical characteristics in an embodiment of the present invention.

[0052] Figure 2 This is a schematic diagram of the pin structure of the PCB flying probe test chip in an embodiment of the present invention;

[0053] Figure 3 This is a flowchart illustrating the determination criteria for whether the probe group measures the continuity of the test points in an embodiment of the present invention.

[0054] Figure 4 This is a flowchart illustrating the process of determining the risk zone level corresponding to several grid units in an embodiment of the present invention.

[0055] In the diagram, 1-probe, 2-probe arm, 3-sensor rod, 4-chip, 5-test point. Detailed Implementation

[0056] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0057] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0058] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0059] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0060] Please see Figures 1-4 As shown, Figure 1This is a flowchart illustrating the PCB flying probe test path optimization method based on electrical characteristics in an embodiment of the present invention. Figure 2 This is a schematic diagram of the pin structure of the PCB flying probe test chip in an embodiment of the present invention; Figure 3 This is a flowchart illustrating the determination criteria for whether the probe group measures the continuity of the test points in an embodiment of the present invention. Figure 4 This is a flowchart illustrating the process of determining the risk zone level corresponding to several grid units in an embodiment of the present invention.

[0061] This invention provides a method for optimizing PCB flying probe test paths based on electrical characteristics, comprising:

[0062] Step S1: Divide the board surface into several grid units according to the initial resolution, and label each grid unit according to the height information of the board surface;

[0063] Step S2: Identify the grid cells in the potential shadow area based on the grid cell labeling value and the probe test parameters, and determine the initial probe angle corresponding to the test point in the grid cell by combining the interval distance between test points;

[0064] Step S3: Identify high-density test points based on the proximity distance between several test points and neighboring test points; classify region types based on whether several grid cells contain high-density test points; the region types include high-density regions and low-density regions; and determine the test order of several test points in different region types based on the region types.

[0065] Step S4: Based on whether there is a ground detection requirement at the test point, determine the different probe group test movement methods, and determine whether the corresponding test point is in the contaminated area of ​​the board surface based on the board surface image, and adjust the judgment criteria for whether the probe group measures the continuity of the test point accordingly.

[0066] Step S5: Calculate the accessibility score of several test points based on the distribution of test points and components on the board to determine the risk type of the test points, and determine the risk zone level of several grid cells based on the accessibility score and the potential shadow area.

[0067] Step S6: Optimize the probe's test path and adjust the probe's initial movement speed in different grid cells according to the risk zone level corresponding to several grid cells.

[0068] Step S7: For the same movement sequence of different probe groups, determine the overlapping grid according to the initial probe angle and test path corresponding to the probe, and determine whether there is a risk of collision between probes by combining the initial movement speed of the probe in different grid cells.

[0069] Step S8: When there is a risk of collision between probes, take appropriate adjustment measures based on the number of overlapping grids.

[0070] The test parameters are the probe arm diameter and the initial probe angle.

[0071] In this embodiment, four probes are used to detect short circuits and open circuits between several test points on the PCB board.

[0072] Before testing, import PCB board data containing test networks and test points, and obtain the coordinates, network types, and network connection relationships of all test points.

[0073] The network types include GND network, power network, and signal network.

[0074] The steps of a flying needle test include:

[0075] Step S11: Fix the board. Place the PCB to be tested on the fixed platform of the testing machine. Precise positioning is usually achieved through a vision positioning system.

[0076] In step S12, automatic testing is performed. The probe moves to the first test point according to the program instructions. The probe descends and makes reliable electrical contact with the test point. The tester applies test signal voltage, current, etc. and measures the response to determine the circuit characteristics. The probe then lifts up and quickly moves to the next test point, repeating this process.

[0077] Step S13 Result Determination: The testing system compares the measured value with the preset acceptable range and records the pass / fail result.

[0078] The judgment criteria for several test points include continuity, open circuit and short circuit. If the resistance value is lower than a set threshold such as 10Ω~50Ω, the connection between the test points is considered to be good.

[0079] If the resistance value is higher than a set threshold, such as 1MΩ, the line is considered to be open circuit. If the resistance value measured between two or more networks that should not be connected is very low, a short circuit is considered to have occurred between the test points.

[0080] Flying probe testers use 2-8 high-speed moving precision probes to contact test points on PCB printed circuit boards to measure the electrical characteristics of components, such as resistance, capacitance, inductance, diode characteristics, short circuit / open circuit, etc.

[0081] In asynchronous linkage, only one flying needle moves to the next point in each action cycle, and the movement sequence of the flying needle can be represented as (A, B), (C, B), (C, D); while in synchronous linkage, two flying needles move to the next point at the same time, and the movement sequence can be represented as (A, D), (B, E), (C, F).

[0082] Using the PCB substrate surface as a plane, obtain the precise three-dimensional coordinates and height information of all test point pads, traces, and mounted components;

[0083] The PCB board surface is divided into several grid cells according to the initial resolution. Each grid cell is labeled according to the three-dimensional coordinates and height information. The value of each grid cell represents the height (Z value) of the highest point on the surface at that location.

[0084] The simulated probe approaches the board surface at an initial probe angle. For any grid cell with a test point, it is compared whether the surrounding area is blocked by a taller component under the vertical projection of the probe.

[0085] Specifically, with the coordinates of the test point as the center, within a rectangular area with the probe arm diameter and initial probe angle as parameters, check whether there are any grid cells with a height higher than the grid cell where the test point is located.

[0086] If there is a grid cell with a height higher than the grid cell where the test point is located, the grid cells within that rectangular area are marked as potential shaded areas;

[0087] Adjust the probe orientation for test points in grid cells located in potential shadow areas;

[0088] When the probe moves to the test point of a grid cell in the potential shadow area, the probe adjusts the initial probe angle, or adjusts the vector of the initial probe angle according to the distribution of the test point and the grid cells in the potential shadow area.

[0089] The initial probe angle is 90° when the probe is perpendicular to the plate surface, and the initial resolution is 1mm×1mm in practice.

[0090] Specifically, the initial probe angle is increased by the absolute value of the difference between the height of the highest grid cell within the rectangular area and the angle between the line formed by the test point and the plate surface, and the ratio of 90 degrees to one.

[0091] Alternatively, with the coordinates of the test point as the center, the probe can be adjusted to the vector of the initial probe angle to the other end of the grid cell relative to the test point in the potential shadow area.

[0092] The theoretical interval distance is calculated based on the coordinates of the test points. If the theoretical interval distance between any two test points is less than the safety threshold, it is determined that the two test points cannot be in the same measurement sequence of the two probes.

[0093] The initial probe angle of the probe relative to the corresponding two test points is reduced according to the ratio of the theoretical interval distance between the two test points to the safety threshold.

[0094] In practice, the priority of reducing the initial probe angle corresponding to the probe based on the theoretical interval distance of test points that cannot be in the same measurement sequence is greater than the priority of increasing the initial probe angle based on the labeled value of the grid cell within the rectangular area.

[0095] When the theoretical interval between any two test points is greater than or equal to the safety threshold, it is determined that the two test points can be in the same measurement sequence of the two probes.

[0096] The safety threshold is the sum of the probe arm diameter and the safety margin. The safety margin can be adjusted according to requirements, and in practice, the safety margin is 1.5 mm.

[0097] Specifically, probes have a certain physical size, and collisions may occur in extremely dense areas. Therefore, constraints are necessary to ensure that the distance between probes is not less than the probe arm diameter. If the distance between adjacent test points is too small, the detection angle of the two probes can be adjusted to avoid probe arm collisions. However, if the distance between adjacent test points is too small, the probe arm may hit adjacent components or pads when contacting a point, leading to short circuit risks or collisions. This method achieves accurate prediction and intelligent control of the probe movement path by meshing the PCB board surface and marking it with three-dimensional height information. It also automatically identifies "potential shadow areas" formed by tall components and dynamically adjusts the probe approach angle to avoid collisions. At the same time, by calculating the theoretical interval distance between test points, the measurement sequence and attitude of the probes are intelligently planned, prioritizing the safe distance between probes. This collaborative optimization method based on three-dimensional spatial perception significantly improves the path efficiency and reliability of flying probe testing while ensuring absolute safety, effectively solving the collision risk and access difficulties in high-density PCB testing.

[0098] A circular analysis area is defined with the test point Pi as the center. The specific radius R of the circle is set according to the physical size and safety requirements of the probe arm 2.

[0099] Accessibility score = Wd × F(Di) + Wc × F(Ci), where Wd and Wc are the weight coefficients of each factor, and Wd + Wc = 1.

[0100] The weighting coefficients can be adjusted according to the testing strategy. For example, if more attention is paid to collision risk, Wc can be increased. F(Di) and F(Ci) are normalization functions that map the raw data to the score values.

[0101] In the formula, Di is the vertical proximity distance of the test point, and Ci is the neighborhood crowding degree of the test point.

[0102] Specifically, the mapping normalization process for rating mappings F(Di) and F(Ci) includes:

[0103] The scoring mapping F(Di) is as follows: a test point Pi scores full marks if the vertical distance from its test point Pi to the nearest obstacle (component body or probe) directly above it is greater than the absolute safety threshold, and scores 0 marks if the vertical distance is less than the absolute minimum safety distance. The absolute safety threshold and the absolute minimum safety distance are interpolated by a linear function.

[0104] In practice, the absolute safety threshold is 5mm, and the absolute minimum safety distance is 1mm.

[0105] The scoring mapping F(Ci) calculates the average height of the standard values ​​of the grid cells or the height of the highest obstacle within the circular analysis area. A full score is given for an open area, while a low score is given for an area with tall and dense elements.

[0106] The calculation process for determining the neighborhood crowding degree Ci based on the height and density of other elements within a specific radius R around the test point Pi:

[0107] Ci= ;

[0108] In the formula, N is the total number of components within the neighborhood radius R, Hj is the height of the j-th component (unit: mm), Aj is the projected area of ​​the j-th component on the PCB plane (unit: mm²), and α is the density weighting index.

[0109] In practice, α is usually ≥ 1, used to adjust the influence of the component density factor. The larger α is, the more severe the system's penalty for the density of components.

[0110] The calculation process of the rating map F(Ci):

[0111] The calculated congestion level Ci (theoretically ranging from 0 to infinity) is converted into a score between 0 and 100 through a mapping function, where 100 represents the best (most spacious) and 0 represents the worst (most crowded).

[0112] F(Ci) = 100 × In the formula, e is the base of the natural logarithm, and λ is the attenuation coefficient;

[0113] Specifically, the attenuation coefficient λ is calculated by setting a congestion threshold. When Ci = congestion threshold, F(Ci) is the passing score.

[0114] In practice, the congestion threshold is set to 0.5, and λ = −ln(0.6) / 0.5 ≈ 1.022.

[0115] When Ci = 0 (completely empty), F(Ci) = 100 × e 0 =100 points;

[0116] When Ci = 0.5, F(Ci) = 100 × e −1.022×0.5 ≈100×e−0.511 ≈60 points;

[0117] When Ci = 1.0, F(Ci) = 100 × e −1.022 ≈36 points.

[0118] If the accessibility score of a test point is less than the preset accessibility threshold, the test point will be marked as a high-risk point. In practice, the preset accessibility threshold is 60 points.

[0119] Specifically, vertical approach distance is used as a scoring factor to ensure the probe has sufficient Z-axis travel for a safe descent; neighborhood congestion is used as a scoring factor to reflect the risk of lateral collisions to the probe arm; and the attenuation coefficient controls the rate at which the score decreases with increasing Ci. This solution quantifies the vertical space and neighborhood congestion of test points and uses a weighted scoring model and exponential mapping function to transform complex physical accessibility issues into accurate accessibility scores. It can automatically and objectively identify high-risk test points, providing reliable data support for subsequent path planning and probe attitude adjustment, thereby significantly improving the automation, safety, and efficiency of flying probe testing.

[0120] Cluster the electrical network to obtain and identify GND test points and power test points in all GND networks, power networks, and signal networks, and select the optimal common reference point (such as the GND point with the most connection points).

[0121] The test tasks for several test points are grouped, and all components (capacitors, diodes) tested to ground are grouped with the selected GND reference points;

[0122] For a group of test points that are grouped with the GND reference point, an asynchronous testing method is used when testing the probe group;

[0123] For the remaining test points, a synchronous testing method is used when testing the probe group.

[0124] To ensure stable power supply and heat dissipation for the chip, the chip's power (VCC / VDD) and ground (GND / GND) networks are typically connected internally to a large exposed metal area on top of the package or to the pads of decoupling capacitors via planar layers or vias on the substrate.

[0125] The metal area or capacitor pads on top of the chip package on the board are directly connected to the internal power / ground network; these points are called "mapping points" or "proxy test points".

[0126] The process of performing a flying probe test on test point 5 of the ground pin of chip 4 includes: a probe 1 contacting the power network test point (point A) on the PCB that supplies power to the chip, a sensing rod 3 contacting the VCC mapping point (point B) on the top of the chip, and a tester connected to the probe measuring the resistance between points A and B.

[0127] If the resistance value is very low, such as a few ohms or less, it proves that the VCC path from the PCB to the top of the chip is connected, that is, the VCC solder balls of the BGA are well soldered and there are no open circuits in the internal substrate traces. Conversely, it is an open circuit.

[0128] In practice, the probe handle is equipped with a vision camera at the same angle as the probe. The vision camera acquires a plate surface image of the test point and several surrounding grids when the probe falls and contacts the test point.

[0129] Perform pixel-level difference calculation between the image of the grid cell where the test point is located and the reference image. If the difference between the regional difference comparison results of the grid images is greater than the difference evaluation value, it is determined that the test point is located in the contaminated area of ​​the board surface.

[0130] If the difference in the regional difference comparison results of the grid image is less than or equal to the difference evaluation value, then it is determined that the test point is not located in the contaminated area of ​​the board surface.

[0131] The difference in the region difference comparison results of the grid image is the gray value, and the value of the difference evaluation value is in the range of 15-30.

[0132] If the test point is located in a contaminated area on the board, adjust the resistance threshold to the threshold range.

[0133] When the measured value is below the threshold range, it is determined that the test point is conductive and the line connection is good;

[0134] When the measured value exceeds the threshold range, it is determined that the test point is open-circuited and the line between the test points is broken.

[0135] When the measured value is within the threshold range, it is determined that the measured value of the test point is affected by the contamination of the board surface, the circuit connection is good or slightly open;

[0136] In practice, the threshold range is 10-30Ω.

[0137] Specifically, contamination on the board surface can affect testing accuracy and reliability. This method uses a vision camera integrated on the probe to acquire in-situ images of the test points and combines image differential technology to intelligently identify board surface contamination. When a high risk of board surface contamination is detected, the threshold of the continuity test resistance is automatically increased. By dynamically adjusting the resistance threshold to a conservative range (10-30Ω), it can effectively distinguish between true open circuits and poor contact caused by contamination, significantly reducing the false alarm rate. This method improves the robustness and reliability of flying probe testing under non-ideal conditions without affecting the true positive detection rate.

[0138] Set a minimum density evaluation threshold, and calculate the proximity distance between several test points and neighboring test points based on the coordinates of several test points;

[0139] When the neighbor spacing is less than the minimum density evaluation threshold, the test point and its neighboring test points are determined to be high-density test points, and the corresponding test point and the grid cells where the neighboring test points are located are merged.

[0140] The region consisting of several grid cells containing all high-density test points is classified as a high-density region, and the region consisting of the remaining connected grid cells is classified as a low-density region.

[0141] High-density areas are divided according to the spacing between several test points. Two sets of probes prioritize the detection of several high-density areas, and the two sets of probes detect high-density areas separately to reduce the risk of collision.

[0142] When one set of probes is in a high-density region and another set of probes has finished testing the last set of test points in the high-density region, the other set of probes measures test points in another high-density region or measures test points in a low-density region.

[0143] Specifically, this solution achieves intelligent division of the test area by automatically identifying and merging high-density test point regions. Upon identifying high-density areas, the "collision cost" weight is significantly increased, making the path planning algorithm more inclined to generate conservative and safe paths. By prioritizing and coordinating the detection of high-density areas by two sets of probes, the interference risk of multiple probes in confined spaces is effectively avoided, while fully utilizing the parallel capabilities of the probes. This spatial density-aware task allocation strategy significantly improves the overall testing efficiency of high-density PCBs while ensuring safety.

[0144] Calculate the core risk factors of several grid cells based on whether any grid cell is within a potential shadow zone and the accessibility score of the test points within the grid cell;

[0145] The core risk factors for a grid cell include the shaded area risk factor and the accessibility score. The risk level of the grid cell is determined based on these core risk factors.

[0146] In practice, if a grid cell is located in a potential shadow area, the shadow area risk factor of the grid cell is 1; otherwise, it is 0. The accessibility score is a value of 0-100.

[0147] Specifically, when the risk factor of the shaded area is one or the accessibility score is less than or equal to the first accessibility threshold, the grid cell is judged to have component occlusion or extreme crowding, and the grid cell is marked as a high-risk area.

[0148] When the risk factor in the shaded area is zero and the accessibility score is greater than the first accessibility threshold but less than the second accessibility threshold, the grid cell is judged to be unobstructed but spatially cramped, and the grid cell is marked as a medium-risk area.

[0149] When the risk factor of the shaded area is zero and the accessibility score is greater than or equal to the second accessibility threshold, the grid cell is judged to be open and easy to access, and the grid cell is marked as a low-risk area.

[0150] The risk cost is set according to the risk level of the grid cell. The total cost of moving the grid cell = β1 × geometric distance + β2 × risk cost, where the geometric distance is the distance the probe moves across the corresponding grid cell to the next test point.

[0151] β1 and β2 are pre-set weighting coefficients for geometric distance and risk cost, used to determine the priority of test efficiency and safety in the current PCB flying probe test based on the magnitude of β1 and β2;

[0152] The risk cost of the grid cells in the high-risk area is greater than that in the medium-risk area, which is greater than that in the low-risk area. In practice, the risk cost of the grid cells in the high-risk area is 10 per unit distance (mm), the risk cost of the grid cells in the medium-risk area is 5 per unit distance (mm), and the risk cost of the grid cells in the low-risk area is 1 per unit distance (mm).

[0153] In low-risk areas, the probe moves at its initial speed; in medium-risk areas, the initial speed is reduced based on the ratio of the accessibility score to a second accessibility threshold; and in high-risk areas, the initial speed is reduced based on the ratio of the accessibility score to a first accessibility threshold.

[0154] The first accessibility threshold is 70, and the second accessibility threshold is 30.

[0155] Specifically, traditional path planning algorithms (such as A* and genetic algorithms) only optimize geometric distance. This invention improves upon this by converting grid risk levels into movement costs. This scheme constructs a refined grid risk map by integrating shaded area risk and accessibility scores. Based on dynamically configuring movement cost weights according to different risk levels, the path planning algorithm can automatically avoid high-risk areas, generating a globally optimal path that is not only short but also traverses low-risk areas as much as possible. Simultaneously, the probe movement speed is adjusted in real-time according to the risk level, achieving an optimal balance between testing efficiency and safety in complex PCB environments, significantly improving the intelligence and reliability of flying probe testing.

[0156] In the same movement sequence of different probe groups, the overlapping grid is determined based on whether the projection of the probes of different probe groups overlaps with several grid cells under the current adjusted initial probe angle.

[0157] Specifically, the initial probe angles of different probe groups are obtained after adjustment during the movement sequence. Taking the coordinates corresponding to the probe tip during the movement as the center, the projection of the probe on the plate is circular or approximately rectangular according to the corresponding adjusted initial probe angles.

[0158] In practice, the projection of a vertical (θ=0°) cylindrical probe arm is a circle. However, the projection of a probe arm tilted at an angle θ is approximately a slender rectangle or ellipse with the tip as its vertex.

[0159] Based on the initial probe angle of the probes in the movement sequence and the diameter of the probe arm, the rasterization algorithm determines the number of grid cells through which the probe projection passes, and defines the number of grid cells through which more than one probe passes as overlapping grids.

[0160] Furthermore, by combining the probe's moving speed, the specific time difference of probes from different probe groups passing through the overlapping grid is determined to determine whether a collision will occur.

[0161] When the probe group changes to a high-density region or moves within the same low-density region, the movement sequence is divided into several time steps.

[0162] Based on the initial moving speed corresponding to several grid cells, calculate the theoretical time steps for probes of different probe groups to pass through the overlapping grid;

[0163] It is understandable that, based on the initial moving speed corresponding to several grid cells, the theoretical time step for probes of different probe groups to pass through the overlapping grid can be calculated using the distance-velocity-time calculation formula, which will not be elaborated here.

[0164] For several overlapping grid cells, the time difference between probes from different probe groups passing through the overlapping grid is determined. If the time difference is less than or equal to the critical time difference, it is determined that there is a risk of collision between the probes; if the time difference is greater than the critical time difference, it is determined that there is no risk of collision between the probes.

[0165] When there is a risk of collision between probes, appropriate adjustment measures should be taken based on the number of overlapping grids.

[0166] Specifically, when the ratio of the number of overlapping grids to the number of grids occupied by probe projections of different probe groups is less than the projection ratio threshold, and the initial probe angle corresponding to the overlapping grid is greater than the standard angle, it is determined that the collision risk between probes is low, and the initial probe angle corresponding to the probe is adjusted.

[0167] Specifically, when the initial probe angle corresponding to the probe is greater than the standard angle, the probe is almost perpendicular to the plate surface. The collision risk lies in the slight scraping between the probes at the beginning or end. The initial probe angle corresponding to the probe should be reduced or increased on the other side of the probe projection and the overlapping grid.

[0168] When the ratio of the number of overlapping grids to the number of grids occupied by probe projections of different probe groups is greater than or equal to the projection ratio threshold, or when the initial probe angle corresponding to the overlapping grid is greater than or equal to the standard angle, adjust the movement path or movement sequence of any probe.

[0169] Specifically, simulated obstacle avoidance points are inserted in the overlapping area to change the probe's movement path, or waiting sequences are inserted into the movement sequence and the duration of the inserted waiting sequence is determined according to the ratio of the number of overlapping grids to the number of grids occupied by the probe projection.

[0170] The critical time difference is 50ms, the projection ratio threshold is 2%, and the standard angle is 85°.

[0171] Specifically, during the movement of the probe group to the next test point, collisions may occur between probes due to conflicting test paths. However, changing the probe's movement path or inserting waiting sequences when there is a risk of collision will increase the probe's movement time and reduce the overall detection efficiency. This method predicts the collision risk by calculating several intersecting movement paths under the current movement trajectory, and determines the level of collision risk by the number of overlapping grids and the size of the probe's projected area. It predicts the overlapping area of ​​the probe's movement trajectory and quantifies the collision risk by combining time step analysis. The system can intelligently select adjustment strategies based on the overlapping grid ratio and probe angle; it fine-tunes the probe angle for low-risk scrapes and uses path avoidance or timing delays for high-risk collisions. This hierarchical control mechanism minimizes the impact on testing efficiency while ensuring absolute safety, achieving refined intelligent control of multi-probe collaborative operation.

[0172] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0173] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for optimizing PCB flying probe test paths based on electrical characteristics, characterized in that, include: Based on the grid cell annotation values ​​and probe test parameters, each grid cell divided according to the initial resolution is identified, and the initial probe angle corresponding to the test point in each grid cell is determined by combining the interval distance between the test points based on the identification results. The adjacent spacing between several test points is obtained to determine the test point density type to merge the corresponding grid cells, and the region type is divided based on the distribution of several test points in the grid cells to determine the test order of the probe group for several test points; The probe group test movement method is determined according to whether there is a need for ground detection at the test point, and the judgment criteria for whether the probe group measures the test point for continuity are adjusted accordingly based on the identification of the contaminated area on the board surface image. Based on the distribution of test points and components on the board, accessibility scores of several test points are obtained, and the risk zone level corresponding to each grid cell is determined by combining the identification results of each grid cell. The test path of the probe is optimized based on the risk zone level corresponding to each grid cell, and the initial moving speed of the probe corresponding to the grid cell where the optimized test path is located is adjusted in combination with the accessibility score. For the same movement sequence of different probe groups, an overlapping grid is determined based on the initial probe angle and test path corresponding to the probe, and the initial moving speed of the probe in each grid cell is combined to determine whether there is a risk of collision between probes; In response to the risk of collision between probes, the initial probe angle or movement parameters corresponding to the adjusted probes are determined based on the number of overlapping grids.

2. The PCB flying probe test path optimization method based on electrical characteristics according to claim 1, characterized in that, The process of identifying each grid cell divided according to the initial resolution includes: The simulated probe approaches the plate surface at an initial probe angle. Centered on the coordinates of the test point, within a rectangular area with parameters of probe arm diameter and initial probe angle, if there is a grid cell with a height higher than the grid cell where the test point is located, the grid cell within this rectangular area is marked as a potential shaded area.

3. The PCB flying probe test path optimization method based on electrical characteristics according to claim 2, characterized in that, The process of determining the initial probe angle corresponding to the test point within each grid cell includes: When the probe moves to a test point in a grid cell within a potential shaded area, the initial probe angle is increased based on the labeled value of the grid cell within the rectangular area, and the initial probe angle corresponding to the probe is decreased based on the theoretical interval distance between test points that cannot be in the same measurement sequence.

4. The PCB flying probe test path optimization method based on electrical characteristics according to claim 3, characterized in that, The process of determining the testing order of the probe group for several test points includes: Calculate the proximity distance between several test points and adjacent test points based on the coordinates of several test points; When the neighbor spacing is less than the minimum density evaluation threshold, the test point and its neighboring test points are determined to be high-density test points, and the corresponding test point and the grid cells where the neighboring test points are located are merged. The region consisting of several grids containing all high-density test points is divided into a high-density region, and the region consisting of the remaining connected grid cells is divided into a low-density region. The testing order priority for high-density areas is higher than that for low-density areas.

5. The PCB flying probe test path optimization method based on electrical characteristics according to claim 4, characterized in that, Perform pixel-level difference calculation between the image of the grid cell where the test point is located and the reference image. If the difference between the regional difference comparison results of the grid images is greater than the difference evaluation value, then the test point is determined to be in the contaminated area of ​​the board surface.

6. The PCB flying probe test path optimization method based on electrical characteristics according to claim 5, characterized in that, The process of adjusting the criteria for determining whether the probe group measures the continuity at the test points includes: If the test point is located in a contaminated area on the board, change the resistance threshold to the threshold range. When the measured value is below the threshold range, it is determined that the test point is conductive and the line connection is good; When the measured value exceeds the threshold range, it is determined that the test point is open-circuited and the line between the test points is broken. When the measured value is within the threshold range, it is determined that the measured value of the test point is affected by the contamination of the board surface, and the circuit connection is good or slightly open.

7. The PCB flying probe test path optimization method based on electrical characteristics according to claim 6, characterized in that, The process of determining the risk level of each grid cell includes: A circular analysis area is defined with the test point as the center and a specific radius. The accessibility score of several test points is calculated based on the distribution parameters of the components within the area. When the risk factor in the shaded area is one or the accessibility score is less than or equal to the first accessibility threshold, the grid cell is judged to have component occlusion or extreme crowding, and the grid cell is marked as a high-risk area. When the risk factor in the shaded area is zero and the accessibility score is greater than the first accessibility threshold but less than the second accessibility threshold, the grid cell is judged to be unobstructed but spatially cramped, and the grid cell is marked as a medium-risk area. When the risk factor in the shaded area is zero and the accessibility score is greater than or equal to the second accessibility threshold, the grid cell is judged to be open and easy to access, and the grid cell is marked as a low-risk area.

8. The PCB flying probe test path optimization method based on electrical characteristics according to claim 7, characterized in that, The total movement cost of a grid cell is calculated based on the risk level of the risk zone where the grid cell is located, and the total movement cost is a reference value for the movement of the test path. In low-risk areas, the probe moves at its initial speed; in medium-risk areas, the initial speed is reduced based on the ratio of the accessibility score to a second accessibility threshold; and in high-risk areas, the initial speed is reduced based on the ratio of the accessibility score to a first accessibility threshold.

9. The PCB flying probe test path optimization method based on electrical characteristics according to claim 8, characterized in that, The process of determining overlapping grids includes: The initial probe angles of probes from different probe groups in the same moving sequence are obtained to determine the grid cells through which the probe projection passes, and the overlapping grids are determined based on whether the grid cells overlap. For several overlapping grid cells, the time difference between probes from different probe groups passing through the overlapping grid is determined. If the time difference is less than or equal to the critical time difference, it is determined that there is a risk of collision between the probes. When the time difference is greater than the critical time difference, it is determined that there is no risk of collision between the probes.

10. The PCB flying probe test path optimization method based on electrical characteristics according to claim 9, characterized in that, When there is a risk of collision between probes, appropriate adjustment measures should be taken based on the number of overlapping grids. When the ratio of the number of overlapping grids to the number of grids occupied by probe projections from different probe groups is less than the projection ratio threshold, and the initial probe angle corresponding to the overlapping grid is greater than the standard angle, it is determined that the collision risk between probes is low, and the initial probe angle corresponding to the probe is adjusted. When the ratio of the number of overlapping grids to the number of grids occupied by probe projections of different probe groups is greater than or equal to the projection ratio threshold, or when the initial probe angle corresponding to the overlapping grid is greater than or equal to the standard angle, the movement path or movement sequence of any probe is adjusted.

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