Detection path planning method and device, equipment and storage medium

Abstract

The application discloses a kind of detection path planning method, equipment and storage medium, wherein method includes: S1, the coordinate position of all measurement points required to be detected by semiconductor detection equipment is determined, and path search space is defined;S2, initialize temperature parameter and randomly generate a current candidate path including all measurement points;S3, the candidate path is processed based on preset field operation, and new candidate path is generated;S4, the total time consumption between the total time consumption of completing new candidate path and the total time consumption of completing current candidate path is calculated Time consumption difference;S5, based on simulated annealing algorithm, according to time consumption difference update current candidate path, and according to preset cooling strategy, reduce temperature parameter;Step S3 to step S5 are cyclically executed until termination condition is satisfied, and the optimal path is output.The application breaks through the limitation of traditional shortest path by taking time optimization as target, filters the optimal path with the shortest total time consumption, and significantly improves the yield of semiconductor quantity detection equipment.

Description

Technical Field

[0001] This application relates to the field of semiconductor manufacturing technology, and in particular to a detection path planning method, apparatus and storage medium. Background Technology

[0002] In the semiconductor manufacturing industry, wafer quality control is a crucial step in ensuring chip yield. Inspection equipment needs to move quickly and accurately across hundreds of measurement points on the wafer surface to complete the inspection. The quality of its path planning directly affects the inspection time per wafer and the overall yield (WPH). Traditional path planning algorithms, such as nearest neighbor and genetic algorithms, often use the "shortest geometric path" as their optimization objective, i.e., finding the movement sequence that minimizes the sum of Euclidean distances.

[0003] However, in the actual operation of semiconductor testing equipment, the "shortest path" is not equivalent to the "shortest testing time." The movement of the equipment's stage is subject to complex physical constraints, including the acceleration limits of the mechanical system, motion smoothness requirements (jerk limits), and motor response characteristics. These factors mean that path planning based on pure geometric distance often fails to achieve the expected time efficiency in actual execution. For example, for a path containing multiple testing points, a path with a shorter geometric distance may contain many short segments requiring frequent acceleration and deceleration, while a slightly longer path with smoother motion may have a shorter actual execution time.

[0004] Current technologies lack path planning solutions that directly optimize based on "actual execution time." Most optimization algorithms remain at the spatial geometry level, failing to establish a precise mapping model from path sequences to actual time consumption. This results in the underutilization of the capacity potential of semiconductor metrology equipment, failing to meet the extreme efficiency demands of advanced manufacturing processes. Summary of the Invention

[0005] In view of this, this application provides a detection path planning method, apparatus, device and storage medium to solve the problem that existing path planning only considers the shortest distance and does not consider the actual detection time.

[0006] To solve the above-mentioned technical problems, this application adopts the following technical solution: a detection path planning method is provided, which includes: S1, determining the coordinate positions of all measurement points to be detected by the semiconductor detection device, and defining a path search space; S2, initializing temperature parameters and randomly generating a current candidate path containing all measurement points; S3, processing the candidate path based on preset neighborhood operations to generate a new candidate path; S4, calculating the time difference between the total time taken to complete the new candidate path and the total time taken to complete the current candidate path; S5, updating the current candidate path based on the time difference using a simulated annealing algorithm, and reducing the temperature parameters according to a preset cooling strategy; cyclically executing steps S3 to S5 until the termination condition is met, and outputting the optimal path.

[0007] As a further improvement of this application, based on the simulated annealing algorithm, the current candidate path is updated according to the time difference, and the temperature parameter is reduced according to a preset cooling strategy. This includes: determining the relationship between the total time of the new candidate path and the total time of the current candidate path based on the time difference; if the total time of the new candidate path is less than the total time of the current candidate path, then the new candidate path is adopted as the new current candidate path; if the total time of the new candidate path is greater than or equal to the total time of the current candidate path, then the update probability is calculated, and the new candidate path is adopted as the new current candidate path based on the update probability; otherwise, the original current candidate path is retained. The probability calculation process is expressed as follows: ,in, Represents probability. This represents the time difference. The temperature parameter is represented by exp(), which represents an exponential function. The temperature parameter is reduced according to a preset cooling strategy. The calculation process of the preset cooling strategy is as follows: ,in, This indicates the temperature parameter for the next iteration. This represents the temperature parameter in the current iteration. This indicates the preset cooling coefficient.

[0008] As a further improvement to this application, the total time includes the motion time and the total integration time required to measure all measurement points.

[0009] As a further improvement to this application, the motion time includes the path motion time of the semiconductor testing equipment and / or the synchronous compensation time of the rotating motor of the semiconductor testing equipment.

[0010] As a further improvement of this application, the calculation process of the path movement time of the semiconductor testing equipment includes: using a trapezoidal acceleration and deceleration algorithm, based on the maximum speed, maximum acceleration, maximum jerk of the semiconductor testing equipment, and the path segment between two adjacent measurement points in the path, calculating the stage time of the semiconductor testing equipment in each path segment of acceleration, uniform speed and deceleration; summing the stage time of all stages of the entire path to obtain the path movement time of the semiconductor testing equipment.

[0011] As a further improvement of this application, the calculation process of the synchronous compensation time of the rotary motor of the semiconductor testing equipment includes: confirming the measurement angle of the semiconductor testing equipment corresponding to each measurement point; calculating the target angle required for the motor to drive the semiconductor testing equipment to rotate based on the measurement angle of the current measurement point and the measurement angle of the previous measurement point; calculating the angle adjustment time according to the preset rotational angular velocity of the motor and the target angle; and summing the angle adjustment times of all measurement points to obtain the synchronous compensation time of the rotary motor of the semiconductor testing equipment.

[0012] As a further improvement of this application, the calculation process for the total integration time required to measure all measurement points includes: querying the integration time corresponding to each pre-set measurement point; summing the integration times corresponding to all measurement points to obtain the total integration time required to measure all measurement points.

[0013] As a further improvement of this application, the processing of candidate paths based on preset domain operations includes at least one of the following: based on the exchange method, randomly exchanging the positions of two measurement points in the candidate path; based on the insertion method, randomly selecting a measurement point and inserting it into another random position in the candidate path; based on the reversal method, randomly selecting multiple consecutive measurement points in the candidate path and then reversing their order.

[0014] To address the aforementioned technical problems, another technical solution adopted in this application is: providing a detection path planning device, comprising: a determination module for determining the coordinate positions of all measurement points to be detected by the semiconductor detection equipment and defining a path search space; an initialization module for initializing temperature parameters and randomly generating a current candidate path containing all measurement points; a generation module for processing the candidate path based on a preset domain operation to generate a new candidate path; a calculation module for calculating the time difference between the total time taken to complete the new candidate path and the total time taken to complete the current candidate path; and an update module for updating the current candidate path based on the time difference using a simulated annealing algorithm and reducing the temperature parameters according to a preset cooling strategy; the generation module, calculation module, and update module operate in a loop until a termination condition is met, and the optimal path is output.

[0015] To solve the above-mentioned technical problems, another technical solution adopted in this application is: to provide a computer device, the computer device including a processor and a memory coupled to the processor, the memory storing program instructions, and when the program instructions are executed by the processor, causing the processor to perform the steps of the detection path planning method as described above.

[0016] To solve the above-mentioned technical problems, another technical solution adopted in this application is to provide a storage medium storing program instructions capable of implementing any of the above-mentioned detection path planning methods.

[0017] The beneficial effects of this application are as follows: The detection path planning method of this application calculates and compares the total time of candidate paths, using the time difference as the decision basis for the simulated annealing algorithm. Throughout the iterative optimization process, it consistently focuses on minimizing the actual execution time, overcoming the limitation of traditional path planning that only considers geometric distance. It can identify high-quality paths that are slightly longer but offer smoother movement and shorter total time. Simultaneously, the probabilistic acceptance mechanism of the simulated annealing algorithm, combined with neighborhood operations and temperature control strategies, effectively prevents getting trapped in local optima, ensuring that a globally optimal solution is found in the complex search space. Finally, by outputting the optimal path with the shortest actual execution time, the single-wafer detection time is significantly shortened, directly improving the overall yield of the equipment. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating an embodiment of the detection path planning method of the present invention; Figure 2 This demonstrates the principle of elliptic polarization. Figure 3 This is a functional module schematic diagram of an embodiment of the detection path planning device of the present invention; Figure 4 This is a schematic diagram of the structure of a computer device according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the structure of the storage medium according to an embodiment of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0020] The terms "first," "second," and "third" in this application are for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first," "second," or "third" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified. All directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of this application are only used to explain the relative positional relationships and movements between components in a specific orientation (as shown in the figures). If the specific orientation changes, the directional indications also change accordingly. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices.

[0021] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0022] Figure 1 This is a flowchart illustrating the detection path planning method according to an embodiment of the present invention. It should be noted that if substantially the same result is obtained, the method of the present invention is not necessarily identical. Figure 1 The illustrated process sequence is limited. For example... Figure 1 As shown, the detection path planning method includes the following steps: Step S1: Determine the coordinates of all measurement points that the semiconductor testing equipment needs to detect, and define the path search space.

[0023] Specifically, the detection path planning method of this invention is applicable to semiconductor inspection equipment and can be used to inspect wafers. The coordinate positions of the measurement points are typically derived from upstream wafer inspection formulation documents. These documents are pre-defined by process engineers and clearly specify the distribution of the feature structures to be inspected on the wafer. The coordinates are usually defined in the equipment coordinate system or the wafer coordinate system. For example, a Cartesian coordinate system can be established with the wafer center as the origin, and each measurement point... The coordinates are represented as The measurement points are specifically divided into a starting point, a set of measurement points, and an ending point. The starting point is typically the safe waiting position of the equipment or the ending position of the previous wafer; the set of measurement points includes the positions of all n points that must be measured; the ending point can be the same position as the starting point, or a specific safe position that the equipment needs to return to after measurement. These coordinate positions will be stored in a list or matrix as direct input to the detection path planning method. Mathematically, the path search space is the set of all permutations of all measurement points, i.e., it consists of all possible sequences of measurement points. The set consisting of, where yes A permutation. This search space represents all possible combinations of motion sequences of the stage and rotary motor of the semiconductor testing equipment.

[0024] Step S2: Initialize the temperature parameters and randomly generate a current candidate path containing all measurement points.

[0025] Specifically, the temperature parameter is the core control variable of the simulated annealing algorithm. It endows the system with high "energy" in the early stages of the algorithm, enabling it to accept inferior solutions with a higher probability, thus conducting extensive global exploration and avoiding premature entrapment in local optima. The initial temperature parameter is typically set using one of the following strategies: setting it to a large fixed value, such as 1000 or 5000, depending on the problem size; or calculating the variance of the objective function (total time) through a small number of pre-runs and dynamically setting the initial temperature based on the variance to ensure a high initial acceptance probability (e.g., above 0.8). The candidate path is a sequence that must completely contain all the measurement points defined in step S1. and starting point and end point A typical path sequence is as follows: ,in It is a random permutation of the measurement points. This path sequence can be generated by creating a system containing all measurement points. A list; shuffle the list randomly using a random number generator, breaking its order; set the starting point... Place it at the beginning of the sequence, and set the end point. Placed at the end of the sequence, forming the complete current candidate path. .

[0026] Step S3: Process the candidate paths based on preset domain operations to generate new candidate paths.

[0027] Specifically, neighborhood operations refer to rules that make small perturbations to the current path sequence to generate new paths. These perturbations must be "small" to ensure that the new paths are strongly correlated with the old paths, which is consistent with the characteristics of local search.

[0028] Furthermore, processing candidate paths based on preset domain operations includes at least one of the following: 1. Based on the exchange method, randomly exchange the positions of two measurement points in the candidate path.

[0029] Specifically, the swapping method refers to randomly selecting the position indices of two different measurement points in the current path sequence (excluding fixed start and end points) and swapping their positions. For example: Current candidate path: Randomly select and swap P2 and P4 to generate new candidate paths: .

[0030] 2. Based on the insertion method, a measurement point is randomly selected and inserted into another random position in the candidate path.

[0031] Specifically, the insertion method involves randomly selecting a measurement point, removing it from its current location, and then inserting it into another randomly selected location. For example: Current path: Randomly insert P2 after P4 to generate new candidate paths: .

[0032] 3. Based on the reversal method, multiple consecutive measurement points are randomly selected from the candidate path and then their order is reversed.

[0033] Specifically, the reversal method refers to randomly selecting a continuous subsequence in the path sequence and completely reversing the order of the points in that subsequence. For example: Current path: Randomly select the reversed subsequence Generate new candidate paths .

[0034] Step S4: Calculate the time difference between the total time taken to complete the new candidate path and the total time taken to complete the current candidate path.

[0035] It should be noted that the total time includes the motion time and the total integration time required to measure all measurement points.

[0036] In some embodiments, the motion time includes the path motion time of the semiconductor testing device, and the total time includes the path motion time of the semiconductor testing device and the total integration time required to measure all measurement points. The calculation process for the total time is expressed as follows: .in, Indicates the total time elapsed. This indicates the path travel time of the semiconductor testing equipment. This represents the total integration time required to measure all measurement points.

[0037] In other embodiments, the motion time includes the synchronization compensation time of the rotary motor of the semiconductor testing equipment, and the total time includes the synchronization compensation time of the rotary motor of the semiconductor testing equipment and the total integration time required to measure all measurement points. The calculation process for the total time is expressed as follows: .in, Indicates the total time elapsed. This indicates the synchronous compensation time of the rotary motor in the semiconductor testing equipment. This represents the total integration time required to measure all measurement points.

[0038] In other embodiments, the motion time includes the path motion time of the semiconductor testing equipment and the synchronization compensation time of the rotating motor of the semiconductor testing equipment. The total time includes the path motion time of the semiconductor testing equipment, the synchronization compensation time of the rotating motor of the semiconductor testing equipment, and the total integration time required to measure all measurement points. The calculation process for the total time is expressed as follows: .in, Indicates the total time elapsed. This indicates the path travel time of the semiconductor testing equipment. This indicates the synchronous compensation time of the rotary motor in the semiconductor testing equipment. This represents the total integration time required to measure all measurement points.

[0039] Furthermore, the calculation process for the path movement time of the semiconductor testing equipment includes: 1. Using a trapezoidal acceleration / deceleration algorithm, the time consumed by the semiconductor testing equipment in each stage of acceleration, uniform speed and deceleration is calculated based on the maximum speed, maximum acceleration, maximum jerk of the semiconductor testing equipment and the path segment between two adjacent measurement points in the path.

[0040] 2. Sum the time taken for all stages of the entire path to obtain the path movement time of the semiconductor testing equipment.

[0041] It should be noted that the trapezoidal acceleration and deceleration algorithm divides the motion of the device between two adjacent measurement points into three typical stages: acceleration stage: starting from rest or the last velocity of the previous stage, the acceleration is smoothly increased to the maximum value under the jerk limit, so that the speed increases from the initial value; constant speed stage: maintaining constant speed at the maximum speed reached (not exceeding the device limit); deceleration stage: smoothly decreasing speed under the jerk limit until the target speed is reached.

[0042] Specifically, the summation calculation of the total movement time along the entire path includes: a) Path segmentation: dividing the complete path sequence Divide the path into n+1 segments, each segment corresponding to the linear motion between two adjacent points: .

[0043] b) Time accumulation: (k ranges from 1 to m, where m is the total number of path segments), where each All based on the distance of that segment Calculate independently of equipment parameters.

[0044] Furthermore, the calculation process for the path movement time of the semiconductor testing equipment is expressed as follows: ; in, Indicates the total number of path segments. Indicates the maximum speed. Indicates the maximum acceleration. Indicates the maximum jerk. Indicates the first The distance of each path segment This represents the trapezoidal acceleration function.

[0045] Furthermore, it should be noted that you may refer to [link / reference needed]. Figure 2 , Figure 2 The principle of elliptic polarization is demonstrated. Natural light emitted from light source 1 is first converted to linearly polarized light by polarizer 2; then, it is adjusted to a specific polarization state by the first rotation compensator 3, causing the electric vector of the incident light to be decomposed into a p-component parallel to the incident plane and an s-component perpendicular to the incident plane; when the polarized light has an incident angle of... When the light is irradiated onto the surface of sample 4, the p and s components undergo multiple reflections and interferences at the interface of sample 4. Due to the different Fresnel reflection coefficients of the p and s components at the interface, the amplitude attenuation and phase shift of the two components after reflection will differ. The final reflected light will change from the polarization state at incidence to elliptically polarized light. The change in polarization state (amplitude ratio, phase difference) is determined only by the optical parameters of the sample (film thickness d, refractive index n, extinction coefficient k, etc.). After the reflected light passes through the second rotating compensator 5, its polarization state is analyzed by the analyzer 6, and finally the light intensity is recorded by the detector 7. It is possible to set only the first rotating compensator 3, only the second rotating compensator 5, or both the first rotating compensator 3 and the second rotating compensator 5.

[0046] By measuring the ellipsometric parameters of the reflected light and combining them with optical models (such as Fresnel's formula and multi-beam interference theory), parameters such as the film thickness and refractive index of the sample can be obtained by inversion. In semiconductor testing equipment, this is used to accurately measure key parameters such as film thickness and refractive index, which is fundamental to formula detection. In this elliptic polarization method, the rotating compensator is the core component of phase modulation. Periodic modulation of the polarization state is achieved through rotation, requiring the rotating motor to precisely control the angle of the compensator to achieve the conversion from phase information to light intensity signal. Therefore, in this embodiment, the rotating motor drives the compensator to rotate, ensuring rapid adjustment to a preset angle at each measurement point to guarantee the efficiency and accuracy of polarization modulation. Therefore, the calculation process for the synchronous compensation time of the rotating motor in the semiconductor testing equipment includes: 1. Confirm the measurement angle of the semiconductor testing equipment corresponding to each measurement point.

[0047] 2. Calculate the target angle required for the motor to drive the semiconductor detection equipment to rotate, based on the measurement angle of the current measurement point and the measurement angle of the previous measurement point.

[0048] 3. Calculate the angle adjustment time based on the motor's preset rotational angular velocity and the target angle.

[0049] 4. Sum the angle adjustment times of all measurement points to obtain the synchronous compensation time of the rotary motor of the semiconductor testing equipment.

[0050] Specifically, the detection angle at each measurement point Pre-stored in the test recipe, the angle definition is typically based on the wafer coordinate system or device coordinate system. The angle value represents the angle that the test probe (such as an electron beam or optical lens) needs to rotate relative to the reference direction. This occurs when the device moves from the previous measurement point... Move to the current measurement point At that time, the rotary motor needs to be rotated from the previous angle. Adjust to the angle required at present The target angle is the difference between the two.

[0051] The calculation process for the synchronous compensation time of the rotary motor in semiconductor testing equipment is expressed as follows: ; in, This indicates the total number of measurement points. Indicates the measured angle of the current measurement point. This indicates the measured angle at the previous measurement point. This indicates the preset rotational angular velocity of the motor.

[0052] Furthermore, the calculation process for the total integration time required to measure all measurement points includes: 1. Query the integration time corresponding to each pre-set measurement point; 2. Sum the integration times for all measurement points to obtain the total integration time required to measure all measurement points.

[0053] Specifically, the integration time for each measurement point is pre-stored, and the integration time for each measurement point is set independently according to the detection task type and accuracy requirements of that measurement point. The calculation process for the total integration time required to measure all measurement points is expressed as follows: ; in, This represents the integration time for each measurement point.

[0054] Step S5: Based on the simulated annealing algorithm, update the current candidate path according to the time difference, and reduce the temperature parameter according to the preset cooling strategy.

[0055] Repeat steps S3 to S5 until the termination condition is met, and output the optimal path.

[0056] Furthermore, step S5 specifically includes: 1. Determine the relationship between the total time of the new candidate path and the total time of the current candidate path based on the time difference.

[0057] Specifically, after calculating the total time of the new candidate path and the total time of the current candidate path, the total time of the new candidate path is subtracted from the total time of the current candidate path. The relationship between the total time of the new candidate path and the total time of the current candidate path is determined based on the result. When the result is less than 0, it means that the total time of the new candidate path is less than the total time of the current candidate path. When the result is equal to 0, it means that the total time of the new candidate path is equal to the total time of the current candidate path. When the result is greater than 0, it means that the total time of the new candidate path is greater than the total time of the current candidate path.

[0058] 2. If the total time of the new candidate path is less than the total time of the current candidate path, then the new candidate path shall be used as the new current candidate path.

[0059] Specifically, if the total time of the new candidate path is less than the total time of the current candidate path, it means that the new candidate path is better than the current candidate path. Therefore, the new candidate path is retained and used as the new current candidate path.

[0060] 3. If the total time of the new candidate path is greater than or equal to the total time of the current candidate path, then calculate the update probability and use the new candidate path as the new current candidate path based on the update probability; otherwise, retain the original current candidate path. The probability calculation process is expressed as follows: ,in, Represents probability. This represents the time difference. This represents the temperature parameter, and exp() represents the exponential function.

[0061] Specifically, if the total time of the new candidate path is greater than or equal to the total time of the current candidate path, it means that the current candidate path is better than the new candidate path. In order to avoid getting trapped in a local optimum, in this embodiment, the time difference between the total time of the new candidate path and the total time of the current candidate path is used to calculate the probability and obtain the update probability. Then, a random number uniformly distributed in the range [0,1] is generated. The update probability and the random number are compared. When the update probability is greater than the random number, the new candidate path is used as the new current candidate path. Otherwise, the original current candidate path is retained.

[0062] 4. Reduce the temperature parameters according to the preset cooling strategy. The calculation process of the preset cooling strategy is expressed as follows: ,in, This indicates the temperature parameter for the next iteration. This represents the temperature parameter in the current iteration. This indicates the preset cooling coefficient.

[0063] Specifically, in simulated annealing algorithms, when the temperature parameter is high, even if the time difference is large, The calculated result is still close to 1, indicating that the algorithm has a high probability of accepting inferior solutions, thus promoting global exploration. This is especially true when the temperature parameter is low. The calculation result is still close to 0. The algorithm mainly accepts the optimized solution and performs local fine search. Through this probabilistic acceptance mechanism, the contradiction between global search and local optimization is effectively balanced.

[0064] The detection path planning method in this invention calculates and compares the total time of candidate paths, using the time difference as the decision basis for the simulated annealing algorithm. Throughout the iterative optimization process, it consistently focuses on minimizing the actual execution time. This overcomes the limitation of traditional path planning, which only considers geometric distance, and can identify high-quality paths that are slightly longer but offer smoother movement and shorter total time. Simultaneously, the probabilistic acceptance mechanism of the simulated annealing algorithm, combined with neighborhood operations and temperature control strategies, effectively prevents getting trapped in local optima, ensuring that a globally optimal solution is found in a complex search space. Ultimately, by outputting the optimal path with the shortest actual execution time, the single-wafer detection time is significantly shortened, directly improving the overall equipment yield.

[0065] Figure 3 This is a schematic diagram of the functional modules of the detection path planning device according to an embodiment of the present invention. Figure 3 As shown, the detection path planning device 20 includes: a determination module 21, an initialization module 22, a generation module 23, a calculation module 24, and an update module 25.

[0066] The determination module 21 is used to determine the coordinate positions of all measurement points that the semiconductor testing equipment needs to detect, and to define the path search space; Initialization module 22 is used to initialize temperature parameters and randomly generate a current candidate path containing all measurement points; The generation module 23 is used to process the candidate paths based on preset domain operations and generate new candidate paths; Calculation module 24 is used to calculate the time difference between the total time taken to complete the new candidate path and the total time taken to complete the current candidate path; The update module 25 is used to update the current candidate path based on the time difference according to the simulated annealing algorithm, and reduce the temperature parameter according to the preset cooling strategy. The generation module 23, calculation module 24 and update module 25 run in a loop until the termination condition is met and the optimal path is output.

[0067] Optionally, the update module 25 performs an operation based on the simulated annealing algorithm, updating the current candidate path according to the time difference, and reducing the temperature parameter according to a preset cooling strategy. Specifically, this includes: determining the relationship between the total time of the new candidate path and the total time of the current candidate path based on the time difference; if the total time of the new candidate path is less than the total time of the current candidate path, then the new candidate path is adopted as the new current candidate path; if the total time of the new candidate path is greater than or equal to the total time of the current candidate path, then the update probability is calculated, and the new candidate path is adopted as the new current candidate path based on the update probability; otherwise, the original current candidate path is retained. The probability calculation process is expressed as follows: ,in, Represents probability. This represents the time difference. The temperature parameter is represented by exp(), which represents an exponential function. The temperature parameter is reduced according to a preset cooling strategy. The calculation process of the preset cooling strategy is as follows: ,in, This indicates the temperature parameter for the next iteration. This represents the temperature parameter in the current iteration. This indicates the preset cooling coefficient.

[0068] Optionally, the total time includes motion time and the total integration time required to measure all measurement points.

[0069] Optionally, the motion time includes the path motion time of the semiconductor testing equipment and / or the synchronization compensation time of the rotating motor of the semiconductor testing equipment.

[0070] Optionally, the calculation module 24 performs the operation of calculating the path movement time of the semiconductor testing equipment, specifically including: using a trapezoidal acceleration and deceleration algorithm, based on the maximum speed, maximum acceleration, maximum jerk of the semiconductor testing equipment, and the path segment between two adjacent measurement points in the path, calculating the stage time of the semiconductor testing equipment in each path segment of acceleration, uniform speed and deceleration; summing the stage time of all stages of the entire path to obtain the path movement time of the semiconductor testing equipment.

[0071] Optionally, the calculation module 24 performs the operation of calculating the synchronous compensation time of the rotating motor of the semiconductor testing equipment, specifically including: confirming the measurement angle of the semiconductor testing equipment corresponding to each measurement point; calculating the target angle required for the motor to drive the semiconductor testing equipment to rotate based on the measurement angle of the current measurement point and the measurement angle of the previous measurement point; calculating the angle adjustment time according to the preset rotational angular velocity of the motor and the target angle; and summing the angle adjustment times of all measurement points to obtain the synchronous compensation time of the rotating motor of the semiconductor testing equipment.

[0072] Optionally, the calculation module 24 performs the operation of calculating the total integration time required to measure all measurement points, specifically including: querying the integration time corresponding to each pre-set measurement point; summing the integration times corresponding to all measurement points to obtain the total integration time required to measure all measurement points.

[0073] Optionally, the generation module 23 performs the following operations to process the candidate path based on the preset domain operation: based on the exchange method, randomly exchange the positions of two measurement points in the candidate path; based on the insertion method, randomly select a measurement point and insert it into another random position in the candidate path; based on the reversal method, randomly select multiple consecutive measurement points in the candidate path and then reverse their order.

[0074] For other details regarding the implementation techniques of each module in the detection path planning device of the above embodiments, please refer to the description in the detection path planning method of the above embodiments, which will not be repeated here.

[0075] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For apparatus embodiments, since they are basically similar to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0076] Please see Figure 4 , Figure 4 This is a schematic diagram of the structure of a computer device according to an embodiment of the present invention. Figure 4As shown, the computer device 30 includes a processor 31 and a memory 32 coupled to the processor 31. The memory 32 stores program instructions. When the program instructions are executed by the processor 31, the processor 31 performs the detection path planning method steps described in any of the above embodiments.

[0077] The processor 31 can also be referred to as a Central Processing Unit (CPU). The processor 31 may be an integrated circuit chip with signal processing capabilities. The processor 31 can also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. A general-purpose processor can be a microprocessor or any conventional processor.

[0078] See Figure 5 , Figure 5 This is a schematic diagram of the structure of the storage medium according to an embodiment of the present invention. The storage medium of this embodiment stores program instructions 41 capable of implementing the above-described detection path planning method. These program instructions 41 can be stored in the storage medium in the form of a software product, including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks, or computer devices such as computers, servers, mobile phones, and tablets.

[0079] In the several embodiments provided in this application, it should be understood that the disclosed computer devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between devices or units, and may be electrical, mechanical, or other forms.

[0080] Furthermore, the functional units in the various embodiments of this invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units described above can be implemented in hardware or as software functional units. The above are merely embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made based on the description and drawings of this application, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A method for detecting path planning, characterized in that, It includes: S1. Determine the coordinates of all measurement points that the semiconductor testing equipment needs to detect, and define the path search space; S2. Initialize the temperature parameters and randomly generate a current candidate path containing all measurement points; S3. Process the candidate paths based on preset domain operations to generate new candidate paths; S4. Calculate the time difference between the total time taken to complete the new candidate path and the total time taken to complete the current candidate path; S5. Based on the simulated annealing algorithm, update the current candidate path according to the time difference, and reduce the temperature parameter according to the preset cooling strategy; Repeat steps S3 to S5 until the termination condition is met, and output the optimal path.

2. The detection path planning method according to claim 1, characterized in that, The method based on simulated annealing algorithm, updating the current candidate path according to the time difference, and reducing the temperature parameter according to a preset cooling strategy, includes: The total time of the new candidate path and the total time of the current candidate path are determined based on the time difference. If the total time of the new candidate path is less than the total time of the current candidate path, then the new candidate path is used as the new current candidate path. If the total time of the new candidate path is greater than or equal to the total time of the current candidate path, then an update probability is calculated, and the new candidate path is used as the new current candidate path based on the update probability; otherwise, the original current candidate path is retained. The probability calculation process is expressed as follows: ,in, Represents probability. This represents the time difference. The parameter represents temperature, and exp() represents an exponential function. The temperature parameter is reduced according to a preset cooling strategy, and the calculation process of the preset cooling strategy is expressed as follows: ,in, This indicates the temperature parameter for the next iteration. This represents the temperature parameter in the current iteration. This indicates the preset cooling coefficient.

3. The detection path planning method according to claim 1, characterized in that, The total time includes the motion time and the total integration time required to measure all measurement points.

4. The detection path planning method according to claim 3, characterized in that, The motion time includes the path motion time of the semiconductor testing equipment and / or the synchronous compensation time of the rotating motor of the semiconductor testing equipment.

5. The detection path planning method according to claim 4, characterized in that, The calculation process for the path movement time of the semiconductor detection device includes: Using a trapezoidal acceleration / deceleration algorithm, the time consumed by the semiconductor detection device in each stage of acceleration, uniform speed and deceleration is calculated based on the maximum speed, maximum acceleration, maximum jerk of the semiconductor detection device and the path segment between two adjacent measurement points in the path. The path movement time of the semiconductor detection device is obtained by summing the time consumed at all stages of the entire path.

6. The detection path planning method according to claim 4, characterized in that, The calculation process for the synchronous compensation time of the rotary motor in the semiconductor testing equipment includes: Confirm the measurement angle of the semiconductor testing equipment corresponding to each measurement point; Calculate the target angle required for the motor to drive the semiconductor testing equipment to rotate based on the measurement angle of the current measurement point and the measurement angle of the previous measurement point; The angle adjustment time is calculated based on the preset rotational angular velocity of the motor and the target angle; The synchronous compensation time of the rotary motor of the semiconductor testing equipment is obtained by summing the angle adjustment times of all measurement points.

7. The detection path planning method according to claim 3, characterized in that, The calculation process for the total integration time required to measure all measurement points includes: Query the integration time corresponding to each pre-set measurement point; The total integration time required to measure all measurement points is obtained by summing the integration times corresponding to all measurement points.

8. The detection path planning method according to claim 1, characterized in that, The processing of the candidate path based on the preset domain operation includes at least one of the following: Based on the exchange method, the positions of two measurement points in the candidate path are randomly exchanged; Based on the insertion method, a measurement point is randomly selected and inserted into another random position in the candidate path; Based on the reversal method, multiple consecutive measurement points are randomly selected from the candidate path and then their order is reversed.

9. A path planning detection device, characterized in that, It includes: The determination module is used to determine the coordinate positions of all measurement points that the semiconductor testing equipment needs to detect, and to define the path search space; The initialization module is used to initialize temperature parameters and randomly generate a current candidate path containing all measurement points; The generation module is used to process the candidate paths based on preset domain operations to generate new candidate paths; The calculation module is used to calculate the time difference between the total time taken to complete the new candidate path and the total time taken to complete the current candidate path; The update module is used to update the current candidate path based on the time difference according to the simulated annealing algorithm, and reduce the temperature parameter according to the preset cooling strategy; The generation module, the calculation module, and the update module run in a loop until the termination condition is met, and the optimal path is output.

10. A computer device, characterized in that, The computer device includes a processor and a memory coupled to the processor, the memory storing program instructions that, when executed by the processor, cause the processor to perform the steps of the detection path planning method as described in any one of claims 1-8.

11. A storage medium, characterized in that, It stores program instructions capable of implementing the detection path planning method as described in any one of claims 1-8.

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