Ris phased array antenna automatic test method, device, system and storage medium

Abstract

This invention provides an automated testing method, apparatus, system, and storage medium for RIS phased array antennas. The method includes: assessing the initial risk level of each element and setting a benchmark score based on the design simulation parameters of the RIS phased array antenna under test; generating a static priority sequence based on the initial risk level; retrieving historical test data of the same model and batch from a database; executing the test according to the static priority sequence when the number of historical test data sets is less than a preset threshold, and obtaining the element failure probability based on the historical test data when the number of historical test data sets is greater than or equal to the preset threshold; calculating the priority index of each element based on the risk level and failure probability and generating a dynamic priority sequence to execute the test; finally, judging the pass / fail status based on preset parameter thresholds, and interrupting or ending the test according to a preset stop strategy. This invention significantly improves the testing speed and consistency of RIS phased array antennas.

Description

Technical Field

[0001] This invention relates to the field of phased array antenna testing technology, and more particularly to an automated testing method, apparatus, system, and storage medium for RIS (Reconfigurable Intelligent Surface) phased array antennas. Background Technology

[0002] Reconfigurable smart surfaces (RIS) can optimize the transmission path of wireless signals by actively controlling the electromagnetic environment, thereby improving signal quality, reducing system interference, and reducing energy consumption. They have been widely used in scenarios such as indoor signal coverage, mobile communication signal coverage, and millimeter-wave propagation enhancement. With the cautious approach to large-scale 5G base station deployment and the deepening exploration of key 6G technologies, RIS, with its advantages of low cost, easy installation, and large-scale deployment, has become one of the important research directions in the field of wireless communication.

[0003] However, the mass production of RIS phased array antennas places high demands on the consistency of manufacturing processes. During the factory delivery stage, it is necessary to test the parameters of each element (including S11, S21, S22, etc.) and the relative relationships of parameters between element pairs to ensure that the overall array performance meets the design specifications.

[0004] Existing testing methods for RIS phased array antennas suffer from the following technical problems: First, traditional testing schemes employ a fixed-sequence, element-by-element, and codebook-by-codebook switching approach, resulting in lengthy testing cycles. For example, for a 4×4 2TR 2-bit phased array antenna, a fixed-sequence approach requires switching the matrix switch 32 times and the codebook 4 times. Assuming a single acquisition takes 1 second, the complete testing time for a single antenna is approximately 144 seconds, which is insufficient to meet the cycle requirements of mass production. Second, fixed-sequence testing cannot dynamically adjust the testing strategy based on historical failure data. Faults in high-risk elements, such as those in areas prone to process failures or impedance mismatch elements, cannot be detected quickly and efficiently, leading to a significant waste of testing time on low-risk elements. Third, there is a lack of a quantifiable traceability mechanism for test results, and feedback on test interruptions and non-conformities is not timely, limiting the overall production capacity of the production line.

[0005] Therefore, a new solution is needed. Summary of the Invention

[0006] This invention provides an automated testing method, apparatus, system, and storage medium for RIS phased array antennas, which addresses the shortcomings of existing technologies such as long testing cycles, lack of dynamic intelligent sorting, and poor traceability of RIS phased array antennas.

[0007] According to a first aspect of the present invention, an automated testing method for RIS phased array antennas is provided, the method comprising: S1. Based on the obtained design simulation parameters of the RIS phased array antenna under test, evaluate the initial risk level of each element in the RIS phased array antenna under test, and set a benchmark score for each risk level; S2. Generate a static priority sequence for the RIS phased array antenna under test based on the initial risk level of each element; S3. Obtain historical test data of the RIS phased array antenna under test from the database; S4. When the number of historical test data sets is less than a preset threshold, perform parameter testing on each set in sequence according to the static priority sequence; S5. When the number of historical test data sets is greater than or equal to the preset threshold, the failure probability of the cluster is obtained based on the historical test data, and the priority index of each cluster is calculated according to the risk level of the cluster and the failure probability. A dynamic priority sequence is generated according to the priority index, and the parameters of each cluster are tested sequentially according to the dynamic priority sequence. S6. Determine the pass / fail status of the parameters obtained from the test according to the preset parameter threshold, and interrupt or end the test according to the preset stop strategy, and output the test results.

[0008] In a preferred embodiment of the present invention, the design simulation parameters include at least one of impedance matching, power distribution, and process failure-prone regions.

[0009] In a preferred embodiment of the present invention, the priority index S of each array is calculated according to the following formula: S =α B +β P_norm Where B is the baseline score of the risk level of this period; P_norm is the value after normalizing the failure probability P to the same range as the baseline score; α and β are preset weight coefficients, satisfying α+β=1 and 0<α<1, 0<β<1.

[0010] In a preferred embodiment of the present invention, the fields of the historical test data include antenna batch number, product serial number, array number, array risk level, codebook serial number, test time, and test result; the failure probability of the array is obtained based on the historical test data, including: The failure probability is updated when a preset number of new sets of historical test data are added. Based on the statistical frequency method, the historical test data is grouped according to the antenna batch number, product serial number, and array number as grouping keys. The failure frequency of each group is counted, and the failure probability of each group is calculated as the ratio of the number of failures to the total number of tests. The array failure probability table is then generated and updated.

[0011] In a preferred embodiment of the present invention, the fields of the historical test data further include test type, which includes initial test and retest; the method further includes correction based on the failure probability P described by the following formula. P = w1p1 + w2p2, Where p1 = n1 / N1, p2 = n2 / N2, n1 is the number of failures in the first test, N1 is the total number of first tests, n2 is the number of failures in the retest, N2 is the total number of retests, p1 is the first failure rate, p2 is the retest failure rate, and w1 and w2 are preset weights, satisfying w 1> w2 and w1+w2=1.

[0012] In a preferred embodiment of the present invention, the method further includes: in each round of testing, updating the priority index or risk level of the cluster in descending order of priority, wherein the level adjustment is triggered only once for the same cluster in each round of testing: If the cumulative number of failures of a cluster in historical test data exceeds the preset failure threshold, the risk level of the corresponding cluster will be directly upgraded to the highest risk level, and the cluster will be prohibited from being downgraded based on the level exchange downgrade operation for the next L test update cycles, where L is a preset positive integer. Otherwise, if the parameter test result of the current test is invalid, then the priority index of the current test is updated to S' = min(N). B, B_max), where N is a preset multiple greater than 1, B is the baseline score corresponding to the current risk level, and B_max is the baseline score corresponding to the highest risk level; Otherwise, if the current priority index of a cluster is greater than the baseline score corresponding to its current risk level, the risk level of that cluster will be raised by one level; if the risk level after the increase is still lower than the highest risk level, the cluster with the lowest priority index among the clusters in the increased risk levels will be lowered by one level to the original risk level, and the reduced cluster will not be subject to further level adjustment in this round of testing; if the cluster is already at the highest risk level, or there are no other clusters in the increased risk levels available for reduction, only the increase operation will be performed.

[0013] In a preferred embodiment of the present invention, the preset stop strategy includes: When the number of historical test data sets is less than the preset threshold, the test will continue even if unqualified segments are found during the test, until all segments with the highest risk level are tested. Then, the user can choose to continue testing other levels or stop according to the user configuration. When the number of historical test data sets is greater than or equal to the preset threshold, if any unqualified interval occurs during the testing of the highest risk level interval, the test is immediately interrupted; if all intervals of the highest risk level are qualified, the remaining intervals are tested according to the dynamic priority sequence until all intervals are tested or if an unqualified interval occurs again, the above rules shall apply. The method further includes: When all tested elements pass the test, the printer automatically prints a label with traceability information, which includes at least the antenna model, batch number, product serial number, test time, operator number, test equipment number, and test result summary. When a defective element is detected, the host computer will display a prompt and output a list of defective items. The list of defective items shall include at least the element number, the defective code book number, the type of defective parameter, and the measured value.

[0014] According to a second aspect of the present invention, an automated testing apparatus for a RIS phased array antenna is also provided, for implementing the method described above, comprising: The initialization module is used to evaluate the initial risk level of each element in the RIS phased array antenna under test based on the obtained design simulation parameters of the RIS phased array antenna under test, set the baseline score of each risk level, and generate the static priority sequence of the RIS phased array antenna under test according to the initial risk level of each element. The data accumulation module is used to store the test data in a structured manner in the database and triggers automatic updates of the fault probability prediction whenever a preset number of groups of historical test data are added. The failure probability calculation module is used to calculate the failure probability of each cluster based on the historical test data, and to obtain the priority index of each cluster by weighted summing the baseline score of the risk level of each cluster and the failure probability. The dynamic sorting module is used to output the static priority sequence when the number of historical test data sets is less than a preset threshold, and to generate and output a dynamic priority sequence based on the priority index when the number of historical test data sets is greater than or equal to the preset threshold. The test execution module is used to control the test equipment to perform parameter tests on each element in sequence according to the static priority sequence or the dynamic priority sequence, determine whether the test results are qualified according to the preset threshold, interrupt or end the test according to the preset stop strategy, and output the final test results.

[0015] According to a third aspect of the present invention, an automated testing system for RIS phased array antennas is also provided, comprising a network analyzer, a first matrix switch, a second matrix switch, a main control board, a printer, a hub, and a host computer, wherein: The multiple output ports of the first matrix switch are respectively connected to the first group of ports of the RIS phased array antenna under test via RF lines, and the multiple output ports of the second matrix switch are respectively connected to the second group of ports of the RIS phased array antenna under test via RF lines; the first port of the network analyzer is connected to the input port of the first matrix switch via RF lines, and the second port of the network analyzer is connected to the input port of the second matrix switch via RF lines. The main control board is connected to the control interface of the RIS phased array antenna under test via a ribbon cable. The main control board is used to write codebooks to the RIS phased array antenna under test to switch the phase of the array elements. The host computer is connected to the debugging port of the main control board via a debugging cable; the host computer, the network analyzer, the first matrix switch, and the second matrix switch communicate via the hub. The host computer is used to execute the RIS phased array antenna automated testing method described above. It controls the first matrix switch and the second matrix switch to switch on and off, controls the main control board to input codebooks, controls the network analyzer to collect parameters, and stores the collected data in a structured manner in the database. When the test is passed, the printer prints a label with traceability information.

[0016] According to a fourth aspect of the present invention, a computer-readable storage medium is also provided, on which a computer program is stored, characterized in that, when the computer program is executed by a processor, it implements the steps of the RIS phased array antenna automated testing method as described above.

[0017] The automated testing method, apparatus, system, and storage medium for RIS phased array antennas implemented in this invention have the following beneficial effects: By integrating static risk classification, dynamic fault probability prediction, weighted priority ranking, and phased stopping strategy, this invention significantly improves the testing cycle speed of RIS phased array antennas in mass production environments and ensures testing consistency; This solution achieves priority and rapid verification of high-risk arrays without frequent manual intervention, can detect failed arrays and interrupt invalid testing processes in the shortest possible time, and at the same time ensures the integrity and traceability of test data. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort: Figure 1This is a flowchart illustrating the automated testing method for RIS phased array antennas provided by the present invention. Figure 2 This is a schematic diagram of the structure of the RIS phased array antenna automated testing device provided by the present invention; Figure 3 This is a schematic diagram of the RIS phased array antenna automated testing system provided by the present invention; Figure 4 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0020] Existing RIS phased array antenna testing technology measures the S-parameters of each phase and the relative values ​​of S-parameters between phase pairs in a fixed sequence. For a 4×4 2TR 2bit phased array antenna, this requires switching the switch 32 times, switching the codebook 4 times, and assuming each acquisition takes 1 second, resulting in a total time of 144 seconds. Furthermore, the lack of a priority verification mechanism for process-prone areas and impedance-mismatched phases makes it impossible to detect faulty phases in the shortest possible time. In addition, the testing equipment is highly heterogeneous, lacking a unified automated collaborative control framework between matrix switches, network analyzers, main control boards, and host computers, making it difficult to ensure test consistency. Moreover, the test results lack traceability labels, posing challenges to subsequent quality traceability and process improvement.

[0021] To address the aforementioned problems, this invention proposes an automated testing method for RIS phased array antennas. In this method, firstly, the initial risk level of each element is assessed based on the design simulation parameters of the RIS phased array antenna under test, and a benchmark score is assigned to each risk level. Then, a static priority sequence is generated based on the initial risk levels. Historical test data of the same model and batch are retrieved from a database. When the data volume is insufficient to meet a preset threshold, the test is executed according to the static priority sequence. When the data volume reaches the preset threshold, a priority index for each element is calculated based on a weighted sum of the failure probability and the risk level benchmark score, generating a dynamic priority sequence and executing the test. Finally, a pass / fail judgment is made based on preset parameter thresholds, and the test is interrupted or terminated according to a preset stop strategy.

[0022] The method provided in this invention firstly, uses an initial risk grading mechanism based on design simulation parameters to prioritize high-risk components such as process-prone failure areas, impedance mismatch areas, and high-power areas into the test sequence, effectively overcoming the low efficiency problem of traditional fixed-sequence testing. Secondly, by introducing a failure probability prediction model driven by historical test data, the priority of components can be dynamically adjusted according to actual production line yield feedback, and failure penalties and grade exchange rules ensure a constant number of grades and prioritize the exposure of high-risk components. Thirdly, through a phased stop strategy, while ensuring complete data accumulation, the non-conforming test process can be interrupted in a timely manner in dynamic mode, avoiding invalid tests occupying production line time. Finally, through a unified upper-computer automated control framework, heterogeneous devices such as network analyzers, matrix switches, main control boards, and printers are integrated, and tags with bound traceability information are automatically generated to achieve end-to-end traceable testing.

[0023] In summary, the method provided by the embodiments of the present invention significantly improves the test cycle speed and test consistency of RIS phased array antennas by integrating static risk classification, dynamic fault probability prediction, weighted priority sorting and phased stopping strategy. Compared with the traditional fixed sequence test scheme, the test time of a single unit can be shortened from 144 seconds to less than 48 seconds, and the efficiency is improved by nearly 3 times.

[0024] This invention can be applied to scenarios requiring mass testing of RIS phased array antennas, such as functional and performance verification of RIS antenna products before they leave the factory. The execution entity of this method can be an electronic device such as a host computer, terminal equipment, computer, server, server cluster, or specially designed automated testing equipment. It can also be an automated testing device for RIS phased array antennas installed within such electronic equipment, which can be implemented through software, hardware, or a combination of both.

[0025] In the description of the embodiments of the present invention, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of the embodiments of the present invention, "multiple" means two or more, unless otherwise explicitly specified.

[0026] Figure 1 This is one of the flowcharts illustrating the automated testing method for RIS phased array antennas provided by this invention, such as... Figure 1 As shown, the method includes the following steps S1-S6.

[0027] Step S1: Based on the obtained design simulation parameters of the RIS phased array antenna under test, assess the initial risk level of each element in the RIS phased array antenna under test, and set a benchmark score for each risk level; the risk level includes at least the highest risk level, the intermediate risk level, and the lowest risk level.

[0028] Specifically, the RIS phased array antenna under test refers to a phased array antenna product that requires factory functional and performance verification. It contains several elements arranged in an array, such as a 4×4 phased array antenna containing 16 elements. Design simulation parameters refer to the design specifications output after simulating the antenna model using electromagnetic simulation software, which can be obtained by retrieving the simulation result files provided by the design department.

[0029] In some possible implementations, the design simulation parameters include at least one of impedance matching, power distribution, and process-prone failure regions. Specifically: the impedance matching parameter is the simulated standing wave ratio (VSWR) or reflection loss value (S11, in dB); the power distribution parameter is the ratio of the power carried per unit element to the average power of the array surface; and the process-prone failure region parameter is an edge region, a densely viad region, or a metal layer intersection region pre-marked based on process simulation (e.g., PCB manufacturing simulation, SMT process simulation).

[0030] In some possible implementations, the rules for assessing the initial risk level are as follows: if any of the above indicators exceeds the preset normal range, the period is assessed as the highest risk level; if any one of them is within the warning range but does not exceed the normal range, the period is assessed as the intermediate risk level; and if all indicators are within the normal range, the period is assessed as the lowest risk level.

[0031] For example, for a 4×4 2TR RIS phased array antenna, the 16 elements can be divided into three levels according to the above rules: first priority (highest risk level, 6 elements), second priority (intermediate risk level, 5 elements), and third priority (lowest risk level, 5 elements). A baseline score is assigned to each level: 75 points for first priority, 50 points for second priority, and 30 points for third priority. The principle for setting the baseline scores is that higher priority baseline scores are greater than lower priority baseline scores, and there should be sufficient differentiation between each level of baseline score to clearly identify the level boundaries during subsequent dynamic adjustments.

[0032] Step S2: Generate a static priority sequence for the RIS phased array antenna under test based on the initial risk level of each element.

[0033] Specifically, the static priority sequence is a default test order generated based on the initial risk level. All elements are sorted from highest to lowest risk level, and within the same risk level, they are arranged in numerical order. For the 4×4 2TR antenna example above, the static priority sequence can be represented as: [P3, P5, P6, P9, P10, P11 (first priority element), P1, P2, P7, P12, P15 (second priority element), P4, P8, P13, P14, P16 (third priority element)], where Pi represents the i-th element. When historical test data is insufficient, tests will be performed sequentially according to this sequence.

[0034] Step S3: Obtain historical test data of the RIS phased array antenna under test from the database.

[0035] Specifically, historical test data is stored in the test system's database, and a structured record is written to the database after each complete test. In some possible implementations, the fields of the historical test data include antenna batch number, product serial number, array number, array risk level, codebook number, test time, and test result; furthermore, the fields of the historical test data may also include test type, which includes first test and retest, to distinguish the failure rate of the first test and the retest.

[0036] When querying data, the model number and batch number fields of the antenna under test can be used as query keys to retrieve the number of matching historical records from the historical data table. The model number field is used to ensure the consistency of the antenna design architecture, and the batch number field is used to ensure the homogeneity of material and process batches. The combination of the two can ensure that the historical data is statistically representative of the current antenna under test.

[0037] Step S4: When the number of historical test data sets is less than a preset threshold, parameter tests are performed on each set in sequence according to the static priority sequence.

[0038] Specifically, a preset threshold is used to distinguish the switching boundary between static and dynamic modes. In this embodiment, the preset threshold can be set to 100 sets. When the number of historical test data sets is less than 100 sets, it is considered that the statistical sample of fault probability is insufficient. At this time, the static priority sequence is directly used to execute the test, that is, the S-parameter test is performed step by step according to the initial risk level from high to low, and the same level is tested in the order of the numbering of the sub-sequences.

[0039] Step S5: When the number of historical test data sets is greater than or equal to the preset threshold, obtain the failure probability of the cluster based on the historical test data, calculate the priority index of each cluster according to the risk level of the cluster and the failure probability, generate a dynamic priority sequence according to the priority index, and perform parameter tests on each cluster in sequence according to the dynamic priority sequence.

[0040] Specifically, when the number of historical test data sets is greater than or equal to 100, dynamic mode is entered. The failure probability of the array is obtained based on the historical test data, including: When the historical test data is updated by a preset number of groups (e.g., every 100 groups), the failure probability is updated. Based on the statistical frequency method, the historical test data is grouped according to the antenna batch number, product serial number, and array number as grouping keys. The failure frequency of each group is counted, and the failure probability of each group is calculated as the ratio of the number of failures to the total number of tests. The array failure probability table is then generated and updated.

[0041] Furthermore, considering the difference in process significance between initial test failures and retest failures (initial test failures better reflect process stability, while retest failures may be affected by occasional factors such as test fixture contact and environmental noise), this embodiment introduces a test type field to correct for the failure probability: P = w1p1 + w2p2 Where p1 = n1 / N1, p2 = n2 / N2, n1 is the number of failures in the first test, N1 is the total number of first tests, n2 is the number of failures in the retest, N2 is the total number of retests, p1 is the first failure rate, p2 is the retest failure rate, and w1 and w2 are preset weights, satisfying w 1> w2 and w1+w2=1. For example, w1=0.7 and w2=0.3 can be set so that the first failure has a greater weight in the failure probability and more accurately reflects the actual failure situation of the process.

[0042] Then, the priority index S of each phase is calculated according to the following formula: S =α B +β P_norm Where B is the baseline score for the risk level of this event; P_norm is the value after normalizing the failure probability P to the same range as the baseline score (e.g., 0-100 points); α and β are preset weighting coefficients, satisfying α+β=1 and 0<α<1, 0<β<1. For example, α=0.7 and β=0.3 can be set so that the risk level baseline score dominates the priority sequence, and the failure probability serves as an auxiliary correction term.

[0043] In other embodiments, the method of the present invention further includes a dynamic adjustment mechanism for the priority index and risk level. In each round of testing, the priority index or risk level of the time period is updated in descending order of priority, and the level adjustment is triggered only once for the same time period in each round of testing: Rule 1 (Rapid Upgrade Rule): If a component's cumulative failure count in historical test data exceeds a preset failure count threshold (e.g., 3 times), the risk level of the corresponding component will be directly upgraded to the highest risk level. Furthermore, downgrading based on level exchange will be prohibited for the next L test update cycles, where L is a preset positive integer (e.g., L=5). This rule is used to lock components with obvious process weaknesses at the highest priority, preventing them from being downgraded due to occasional pass test results.

[0044] Rule 2 (Failure Penalty Rule): If a component fails the parameter test in this round of testing, its priority index will be updated to: S' = min(N B, B_max); Where N is a preset multiple greater than 1 (e.g., N=1.5), B is the baseline score corresponding to the current risk level of the current fault, and B_max is the baseline score corresponding to the highest risk level. This rule ensures that faulty faults in this round receive higher priority weight in the next round of testing, thus being verified first.

[0045] Rule 3 (Level Exchange Rule): If the current priority index of a segment is greater than the baseline score corresponding to its current risk level, the risk level of that segment will be increased by one level; if the risk level after the increase is still lower than the highest risk level, the segment with the lowest priority index from the increased risk levels (excluding the segment that was increased this time) will be reduced by one level to the original risk level, and the segment that was reduced will not be subject to level adjustment in this round of testing; if the segment is already at the highest risk level, or there are no other segments in the increased risk levels that can be reduced, then only the increase operation will be performed.

[0046] The core purpose of this risk level switching rule is to ensure that the number of elements in each risk level remains constant. For example, for a 4×42TR antenna, the first priority always maintains 6 elements, the second priority always maintains 5 elements, and the third priority always maintains 5 elements, avoiding imbalance caused by dynamic adjustments.

[0047] Through the synergistic effect of the above three rules, this embodiment achieves refined dynamic management of pair priorities: pairs with too many cumulative failures are quickly locked as the highest priority; pairs that failed in this round are prioritized for verification in the next round; and the remaining pairs are progressively adjusted in level according to the weighted score of the baseline score and the failure probability.

[0048] Step S6: Judge the parameters obtained from the test according to the preset parameter threshold, and interrupt or end the test according to the preset stop strategy, and output the test results.

[0049] Specifically, the preset parameter thresholds include the S-parameter threshold for a single element and the S-parameter threshold between elements. For example, for parameter S11, the threshold can be set to no more than -10dB; for parameter S21, the threshold can be set to the amplitude tolerance range (e.g., ±2dB) and phase tolerance range (e.g., ±10°) under a specified phase.

[0050] In some possible implementations, the preset stopping strategy includes: Phase A (when the number of data sets is less than a preset threshold): Even if unqualified segments are found during the test, the test continues until all segments with the highest risk level have been tested. Then, based on user configuration, users can choose to continue testing at other risk levels or stop. The purpose of this strategy is to ensure that the data at the highest risk level is completely collected, providing sufficient samples for subsequent failure probability statistics.

[0051] Phase B (when the number of data sets is greater than or equal to a preset threshold): If any substandard element is encountered during the testing of the highest-risk element, the test is immediately interrupted, a failure message is output, and the test cycle begins for the next antenna. If all elements of the highest-risk level are qualified, the remaining elements continue to be tested according to a dynamic priority sequence until all elements have been tested or a failure occurs again, at which point the above rules apply. The purpose of this strategy is to minimize subsequent testing time when sufficient statistical data is available.

[0052] In the test result output stage: when all tested antenna arrays pass the test, the printer automatically prints a label with traceability information, which includes at least the antenna model, batch number, product serial number, test time, operator number, test equipment number, and test result summary; when an unqualified antenna array is found, the host computer pops up a prompt and outputs a list of unqualified items, which includes at least the antenna array number, unqualified code book number, unqualified parameter type, and measured value, so that the operator can quickly locate the fault and carry out subsequent repair or rework.

[0053] The automated testing device for RIS phased array antennas provided by the present invention is described below. The automated testing device for RIS phased array antennas described below can be referred to in correspondence with the automated testing method for RIS phased array antennas described above.

[0054] Figure 2 This is a schematic diagram of the structure of the RIS phased array antenna automated testing device provided by the present invention, as shown below. Figure 2 As shown, the device includes: The initialization module 210 is used to evaluate the initial risk level of each element in the RIS phased array antenna under test based on the obtained design simulation parameters of the RIS phased array antenna under test, set the benchmark score of each risk level, and generate a static priority sequence of the RIS phased array antenna under test according to the initial risk level of each element. The data accumulation module 220 is used to store the test data in a structured manner in the database and trigger the automatic update of the fault probability prediction when a preset number of groups of historical test data are added. The failure probability calculation module 230 is used to calculate the failure probability of each cluster based on the historical test data, and to obtain the priority index of each cluster by weighted summing the baseline score of the risk level of each cluster and the failure probability. The dynamic sorting module 240 is used to output the static priority sequence when the number of historical test data sets is less than a preset threshold, and to generate and output a dynamic priority sequence based on the priority index when the number of historical test data sets is greater than or equal to the preset threshold. The test execution module 250 is used to control the test equipment to perform parameter tests on each element in sequence according to the static priority sequence or the dynamic priority sequence, determine whether the test results are qualified according to the preset threshold, interrupt or end the test according to the preset stop strategy, and output the final test results.

[0055] Based on the above embodiments, the initialization module is specifically used to: assess the initial risk level of each phase based on at least one of the impedance matching, power distribution, and process failure-prone areas in the design simulation parameters; wherein, if any indicator exceeds the preset normal range, the phase is assessed as the highest risk level; if any indicator is within the warning range but does not exceed the normal range, the phase is assessed as the intermediate risk level; and if all indicators are within the normal range, the phase is assessed as the lowest risk level.

[0056] Based on the above embodiments, the fault probability calculation module is specifically used to calculate the priority index S of each array according to the formula: S =α B +β P_norm; Where B is the baseline score of the risk level of the current period; P_norm is the value after normalizing the failure probability P to the same range as the baseline score (e.g., the range of 0 to 100 points); α and β are preset weight coefficients, satisfying α+β=1 and 0<α<1, 0<β<1.

[0057] Based on the above embodiments, the fault probability calculation module is also used to correct the fault probability based on a formula: P = w1p1 + w2p2 Where p1 = n1 / N1, p2 = n2 / N2, n1 is the number of failures in the first test, N1 is the total number of first tests, n2 is the number of failures in the retest, N2 is the total number of retests, p1 is the first failure rate, p2 is the retest failure rate, and w1 and w2 are preset weights, satisfying w 1> w2 and w1+w2=1.

[0058] Based on the above embodiments, the dynamic sorting module is also used to: update the priority index or risk level of the cluster in each round of testing according to the order of the rapid upgrade rule, the failure penalty rule, and the level exchange rule, and the same cluster is only triggered once in each round of testing; wherein the specific contents of the rapid upgrade rule, the failure penalty rule, and the level exchange rule are as described in step S5.

[0059] Based on the above embodiments, the test execution module is specifically used to: when the number of sets of historical test data is less than the preset threshold, continue execution even if unqualified segments are found during the test process, until all segments of the highest risk level are tested; when the number of sets of historical test data is greater than or equal to the preset threshold, if any unqualified segment occurs during the testing of the highest risk level segments, the test is immediately interrupted; if all segments of the highest risk level are qualified, continue testing the remaining segments according to the dynamic priority sequence.

[0060] Based on the above embodiments, the test execution module is also used to: control the printer to automatically print labels with traceability information when all the test results of the tested elements are qualified; and control the host computer to pop up a prompt and output a list of unqualified items when an unqualified element appears.

[0061] The following describes the specific implementation process of the RIS phased array antenna automated testing system provided by the present invention. Figure 3 This is a schematic diagram of the RIS phased array antenna automated testing system provided by the present invention.

[0062] like Figure 3 As shown, this embodiment of the invention provides an automated testing system for RIS phased array antennas, including a network analyzer 310, a first matrix switch 320, a second matrix switch 330, a main control board 340, a printer (not shown in the figure), a hub 360, and a host computer 370. Wherein: The multiple output ports of the first matrix switch are connected to the first group of ports (P1~PN) of the RIS phased array antenna under test via RF lines, and the multiple output ports of the second matrix switch are connected to the second group of ports (P1_1~PN_1) of the RIS phased array antenna under test via RF lines; the first port of the network analyzer is connected to the input port of the first matrix switch via an RF line, and the second port of the network analyzer is connected to the input port of the second matrix switch via an RF line. The main control board is connected to the 20-pin control interface of the RIS phased array antenna under test via a 20-pin ribbon cable. The main control board is used to write codebooks to the RIS phased array antenna under test to switch the phase of the array elements. The host computer is connected to the debugging port of the main control board via a debugging cable; the host computer, the network analyzer, the first matrix switch, and the second matrix switch communicate via the hub. The host computer is used to execute the RIS phased array antenna automated testing method described above. It controls the first matrix switch and the second matrix switch to switch on and off, controls the main control board to input codebooks, controls the network analyzer to collect parameters, and stores the collected data in a structured database. When the test is passed, the printer prints a label with traceability information.

[0063] Based on the above system, the specific testing implementation process provided by this embodiment of the invention is as follows: Step 1: Set up the test environment (1) Connect the 1~N ports of the RIS phased array antenna 350 to the 1~N ports of the first matrix switch 320 using radio frequency lines, and connect the 1_1~N_1 ports of the RIS phased array antenna 350 to the 1~N ports of the second matrix switch 330. (2) The 0PIN interface of the RIS phased array antenna 350 is connected to the 20PIN interface of the main control board 340 using a 20PIN ribbon cable; (3) The P1 port of the network analyzer 310 is connected to the input port of the first matrix switch 320 using an RF cable, and the P2 port of the network analyzer 310 is connected to the input port of the second matrix switch 330 using an RF cable. (4) The host computer 370 is connected to the debugging port of the main control board 340 via a debugging cable; (5) The host computer 370, network analyzer 310, first matrix switch 320 and second matrix switch 330 are connected to the hub 360 via network cables.

[0064] Step 2: Configure test parameters (1) Set the S-parameters for measurement, including S11, S21, and S22; (2) Set the codebook for traversal to codebook 1#, 2#, 3#, 4# (corresponding to 0°, 90°, 180°, 270° phase respectively); (3) Set the threshold for the S-parameters of a single element and the threshold for the S-parameters between elements.

[0065] Step 3: Run the test process (1) The 32-channel RF connection (including switch) is divided into 16 groups according to (P1&P1_1, P2&P2_1...), and calibration files 1~16 are saved respectively; (2) When there are 100 or more sets of historical test data, the automated program will formulate a dynamic test sequence based on the historical test data; when there are less than 100 sets of historical test data, it will be executed according to the static priority sequence. (3) The host computer switches the first matrix switch to connect to antenna P1 and the second matrix switch to connect to antenna P1_1; (4) The host computer controls the network analyzer to call the P1 & P1_1 calibration file, test the S21 (dB and phase) of P1_1 and record the data P1_S21_DB_1 and P1_S21_Ph_1; (5) The host computer controls the main control board to switch the phase of antenna P1 & P1_1 to 90°, 180°, and 270°, and executes step (4) repeatedly, and records the data P1_S21_DB_90, P1_S21_Ph_90, P1_S21_DB_180, P1_S21_Ph_180, P1_S21_DB_270, and P1_S21_Ph_270; (6) The host computer switches the first matrix switch to connect to antenna P2 and the second matrix switch to connect to antenna P2_1. It executes steps (3) to (5) in a loop according to the dynamic priority sequence until it is interrupted according to the preset stop strategy or all 16 test values ​​are tested.

[0066] Step 4: Output test results (1) The host computer makes a judgment according to the set threshold; (2) If the test fails, the test result will be displayed and the failed items will be output. At the same time, the test cycle for the next antenna will begin. If the test passes, the test result will be displayed and the printer will automatically print a label with traceability information. The complete cycle will end within 60 seconds.

[0067] Performance verification: Taking a 4×4 2TR 2bit phased array antenna as an example, the traditional test scheme requires 32 switching operations, 4 codebook switching operations, and a single acquisition time of 1 second, totaling 144 seconds; however, after adopting the intelligent sorting strategy of this embodiment, in dynamic mode, the failure array can be detected and the test can be interrupted within 48 seconds, improving the test efficiency by nearly 3 times.

[0068] Figure 4 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 4As shown, the electronic device may include: a processor 410, a communications interface 420, a memory 430, and a communication bus 440, wherein the processor 410, the communications interface 420, and the memory 430 communicate with each other via the communication bus 440. The processor 410 can call logical instructions in the memory 430 to execute an automated testing method for RIS phased array antennas, the method including: S1. Based on the obtained design simulation parameters of the RIS phased array antenna under test, assess the initial risk level of each element in the RIS phased array antenna under test, and set a benchmark score for each risk level; S2. Generate a static priority sequence for the RIS phased array antenna under test based on the initial risk level of each element; S3. Obtain historical test data of the RIS phased array antenna under test from the database; S4. When the number of historical test data sets is less than a preset threshold, perform parameter testing on each set in sequence according to the static priority sequence; S5. When the number of historical test data sets is greater than or equal to the preset threshold, the failure probability of the cluster is obtained based on the historical test data, and the priority index of each cluster is calculated according to the risk level of the cluster and the failure probability. A dynamic priority sequence is generated according to the priority index, and the parameters of each cluster are tested sequentially according to the dynamic priority sequence. S6. Determine the pass / fail status of the parameters obtained from the test according to the preset parameter threshold, and interrupt or end the test according to the preset stop strategy, and output the test results.

[0069] Furthermore, the logical instructions in the aforementioned memory 430 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. 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.

[0070] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer is able to execute the RIS phased array antenna automated testing method provided by the above methods.

[0071] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to perform the automated testing method for RIS phased array antennas provided by the methods described above.

[0072] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0073] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0074] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An automated testing method for RIS phased array antennas, characterized in that, The method includes: S1. Based on the obtained design simulation parameters of the RIS phased array antenna under test, evaluate the initial risk level of each element in the RIS phased array antenna under test, and set a benchmark score for each risk level; S2. Generate a static priority sequence for the RIS phased array antenna under test based on the initial risk level of each element; S3. Obtain historical test data of the RIS phased array antenna under test from the database; the same model and batch. S4. When the number of historical test data sets is less than a preset threshold, perform parameter testing on each set in sequence according to the static priority sequence; S5. When the number of historical test data sets is greater than or equal to the preset threshold, the failure probability of the cluster is obtained based on the historical test data, and the priority index of each cluster is calculated according to the risk level of the cluster and the failure probability. A dynamic priority sequence is generated according to the priority index, and the parameters of each cluster are tested sequentially according to the dynamic priority sequence. S6. Determine the pass / fail status of the parameters obtained from the test according to the preset parameter threshold, and interrupt or end the test according to the preset stop strategy, and output the test results.

2. The method according to claim 1, characterized in that, The design simulation parameters include at least one of impedance matching, power distribution, and areas prone to process failure.

3. The method according to claim 1, characterized in that, The priority index S for each phase is calculated using the following formula: S =a B +β P_norm Where B is the baseline score of the risk level of this period; P_norm is the value after normalizing the failure probability P to the same range as the baseline score; α and β are preset weight coefficients, satisfying α+β=1 and 0<α<1, 0<β<1.

4. The method according to claim 1, characterized in that, The fields of the historical test data include antenna batch number, product serial number, array number, array risk level, codebook serial number, test time, and test result; The failure probability of the array is obtained based on the historical test data, including: The failure probability is updated when a preset number of new sets of historical test data are added. Based on the statistical frequency method, the historical test data is grouped according to the antenna batch number, product serial number, and array number as grouping keys. The failure frequency of each group is counted, and the failure probability of each group is calculated as the ratio of the number of failures to the total number of tests. The array failure probability table is then generated and updated.

5. The method according to claim 4, characterized in that, The historical test data also includes fields for test type, which includes initial test and retest. The method further includes correction based on the failure probability P as described in the following formula. P = w1p1 + w2p2, Where p1 = n1 / N1, p2 = n2 / N2, n1 is the number of failures in the first test, N1 is the total number of first tests, n2 is the number of failures in the retest, N2 is the total number of retests, p1 is the first failure rate, p2 is the retest failure rate, and w1 and w2 are preset weights, satisfying w 1> w2 and w1+w2=1.

6. The method according to claim 1, characterized in that, Also includes: In each round of testing, the priority index or risk level of the cluster is updated in the following order from highest to lowest priority, and the level adjustment is triggered only once for the same cluster in each round of testing: If the cumulative number of failures of a cluster in historical test data exceeds the preset failure threshold, the risk level of the corresponding cluster will be directly upgraded to the highest risk level, and the cluster will be prohibited from being downgraded based on the level exchange downgrade operation for the next L test update cycles, where L is a preset positive integer. Otherwise, if the parameter test result of the current test is invalid, then the priority index of the current test is updated to S' = min(N). B, B_max), where N is a preset multiple greater than 1, B is the baseline score corresponding to the current risk level, and B_max is the baseline score corresponding to the highest risk level; Otherwise, if the current priority index of a cluster is greater than the benchmark score corresponding to its current risk level, the risk level of that cluster will be raised by one level. If the risk level after the increase is still lower than the highest risk level, then select the segment with the lowest priority index from the increased risk levels and reduce it by one level to the original risk level. The segment that is reduced will not be adjusted in the current test. If the current risk level is already at the highest level, or if there are no other risk levels available to be lowered after the risk level has been raised, then only the raising operation will be performed.

7. The method according to claim 1, characterized in that, The preset stop strategy includes: When the number of historical test data sets is less than the preset threshold, the test will continue even if unqualified segments are found during the test, until all segments with the highest risk level are tested. Then, the user can choose to continue testing other levels or stop according to the user configuration. When the number of historical test data sets is greater than or equal to the preset threshold, if any unqualified interval occurs during the testing of the highest risk level interval, the test is immediately interrupted; if all intervals of the highest risk level are qualified, the remaining intervals are tested according to the dynamic priority sequence until all intervals are tested or if an unqualified interval occurs again, the above rules shall apply. The method further includes: When all tested elements pass the test, the printer automatically prints a label with traceability information, which includes at least the antenna model, batch number, product serial number, test time, operator number, test equipment number, and test result summary. When a defective element is detected, the host computer will display a prompt and output a list of defective items. The list of defective items shall include at least the element number, the defective code book number, the type of defective parameter, and the measured value.

8. An automated testing device for RIS phased array antennas, used to implement the method according to any one of claims 1-7, characterized in that, include: The initialization module is used to evaluate the initial risk level of each element in the RIS phased array antenna under test based on the obtained design simulation parameters of the RIS phased array antenna under test, set the baseline score of each risk level, and generate the static priority sequence of the RIS phased array antenna under test according to the initial risk level of each element. The data accumulation module is used to store the test data in a structured manner in the database and triggers automatic updates of the fault probability prediction whenever a preset number of groups of historical test data are added. The failure probability calculation module is used to calculate the failure probability of each cluster based on the historical test data, and to obtain the priority index of each cluster by weighted summing the baseline score of the risk level of each cluster and the failure probability. The dynamic sorting module is used to output the static priority sequence when the number of historical test data sets is less than a preset threshold, and to generate and output a dynamic priority sequence based on the priority index when the number of historical test data sets is greater than or equal to the preset threshold. The test execution module is used to control the test equipment to perform parameter tests on each element in sequence according to the static priority sequence or the dynamic priority sequence, determine whether the test results are qualified according to the preset threshold, interrupt or end the test according to the preset stop strategy, and output the final test results.

9. An automated testing system for RIS phased array antennas, characterized in that, It includes a network analyzer, a first matrix switch, a second matrix switch, a main control board, a printer, a hub, and a host computer, among which: The multiple output ports of the first matrix switch are respectively connected to the first group of ports of the RIS phased array antenna under test via RF lines, and the multiple output ports of the second matrix switch are respectively connected to the second group of ports of the RIS phased array antenna under test via RF lines; the first port of the network analyzer is connected to the input port of the first matrix switch via RF lines, and the second port of the network analyzer is connected to the input port of the second matrix switch via RF lines. The main control board is connected to the control interface of the RIS phased array antenna under test via a ribbon cable. The main control board is used to write codebooks to the RIS phased array antenna under test to switch the phase of the array elements. The host computer is connected to the debugging port of the main control board via a debugging cable; the host computer, the network analyzer, the first matrix switch, and the second matrix switch communicate via the hub. The host computer is used to execute the RIS phased array antenna automated testing method as described in any one of claims 1 to 7. It controls the first matrix switch and the second matrix switch to switch on and off, controls the main control board to input codebooks, controls the network analyzer to collect parameters, and stores the collected data in a structured manner in the database. When the test is qualified, it prints a label with traceability information through the printer.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the RIS phased array antenna automated testing method as described in any one of claims 1 to 7.

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