Automatic test system and method for microwave assembly

Abstract

The invention relates to the technical field of electrical parameter testing, in particular to an automatic testing system and method for a microwave component, and the system comprises a node density recognition module, an energy level regulation and control module, a matching gradient extraction module, a dynamic test execution module and a calibration path switching module. According to the method, three-dimensional state coordinates are constructed through frequency injection response, and density classification labels are established by taking frequency block division as units, so that frequency domain state evolution has a visual identification basis, and then signal combination screening is performed through a minimum difference value and a maximum change rate of response fluctuation amplitude and phase deviation dynamic states. Adaptation of excitation granularity and energy levels of different frequency bands is completed, the problem of insufficient resolving power in previous frequency domain response adjustment is solved, step-by-step tuning of a microstructure device is executed in combination with judgment of a path frequency stepping direction and a response gradient direction after signal parameter matching, continuous acquisition of response parameters is ensured, and the accuracy of frequency domain response adjustment is improved. And path offset caused by misjudgment of the tuning direction is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of electrical parameter testing, and in particular to an automatic testing system and method for microwave components. Background Art

[0002] The field of electrical parameter testing technology includes technical means to measure, evaluate and detect various electrical properties of electrical equipment and its components. The core content of this technical field includes accurate measurement of parameters such as voltage, current, resistance, capacitance, inductance, power, impedance, etc., which is applicable to circuit elements, signal transmission paths, radio frequency components, high-frequency devices and other objects.

[0003] Among them, the microwave component automated test system refers to a test system that uses program control and automated measurement processes to complete the measurement of electrical performance parameters of electronic components that work within the radio frequency band and have specific microwave signal transmission characteristics. The system aims to obtain electrical parameters of microwave components under different working conditions, covering technical matters such as test signal source configuration, measurement port impedance matching, frequency scanning control, power setting, standing wave ratio detection, amplitude and phase response recording, etc. Specifically, the output frequency and power are controlled by a programmable signal source, the component port connection control is achieved through an automatic switching network, the amplitude and phase characteristic data are obtained through a vector network analyzer, and the measurement steps and data acquisition process are controlled by an automatic test program to ensure the continuity and accuracy of the test process.

[0004] In the existing technology, when scanning the entire frequency band at a fixed step frequency in the test process and recording the amplitude and phase responses and setting the power of the components, there is a lack of recognition and classification mechanism for the internal state density in the frequency domain, resulting in the inability to achieve regional clustering and classification management of frequency domain response feature changes. In the area where the response changes dramatically, the fluctuation boundary position cannot be automatically identified, and the signal configuration can only be adjusted based on the global average index, resulting in the problem of excessive excitation in the low-change area and insufficient excitation in the high-change area. In the section where the reflection coefficient and phase response change speed of the component are unstable, the path switching needs to be performed by manually preset judgment thresholds. In practice, due to the significant differences in responses in different frequency bands, the manually preset thresholds are not universal, and the path adjustment nodes are frequently misjudged, causing the tuning device to be misplaced, thereby affecting the continuity and effectiveness of the test results. In the process of multi-frequency point dynamic testing, this processing method based on fixed structural configuration cannot adapt to the frequency domain state evolution characteristics in real time, lacks a control channel in the response gradient direction, and is difficult to establish a synchronization mechanism for micro-step tuning operations and acquisition logic, limiting the practical ability of the system in high-frequency precision control scenarios. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings in the prior art and to propose a microwave component automatic testing system and method.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: The microwave component automatic testing system comprises: The node density identification module obtains the data of microwave components on the test platform, constructs a coordinate map and divides it into equally spaced blocks, calculates the state node distribution density in the block, and obtains the frequency band state distribution coordinate set; The energy level control module selects a signal parameter combination that meets the differentiation condition according to the state node distribution density of the frequency band state distribution coordinate set, and generates a partition signal excitation configuration group; The matching gradient extraction module implements signal injection for each frequency band of the microwave component according to the frequency step value and excitation energy level set for each block in the partition signal excitation configuration group, marks the frequency points that meet the conditions, and generates a frequency point tuning response annotation table; The dynamic test execution module performs micro-step value adjustment of the series inductor or the parallel capacitor based on the frequency points marked in the frequency point tuning response annotation table to generate a frequency point response matching data group.

[0007] As a further solution of the present invention, the frequency band state distribution coordinate set includes a frequency interval identifier, a corresponding block density level label, and a three-dimensional coordinate set of the state point; the partitioned signal excitation configuration group is specifically a signal frequency granularity, a signal energy level, and a block corresponding excitation parameter index; the frequency point tuning response annotation table includes a frequency point position label, a matching gradient direction identifier, and a signal parameter association index; the frequency point response matching data group specifically refers to a reflection coefficient record value, an amplitude response data column, and a phase response data column.

[0008] As a further solution of the present invention, the node density identification module includes: The state parameter construction submodule obtains the three types of parameter data of the response amplitude, phase offset, and temperature rise of the microwave component under each frequency injection in the test platform, divides it into multiple continuous frequency blocks according to the frequency step, and uses the three types of response parameters corresponding to each frequency block as the input variables of the amplitude axis, phase axis, and temperature rise axis respectively, constructs the coordinate representation of the state point in the three-dimensional response space, and marks each state point in the frequency block to which it belongs, and generates a state response coordinate set; The density calculation submodule extracts the amplitude response sequence and phase offset sequence of all state points in the block based on the number of state points in each frequency block in the state response coordinate set, using the formula: ; Calculation frequency block The normalized node density value of , sort the density values ​​by frequency blocks to obtain the normalized density sequence of frequency band nodes; in, It is a frequency block The number of state nodes within is the frequency block The standard deviation of the amplitude response sequence within is the maximum value of the standard deviation of the amplitude response among all frequency blocks is the frequency block In the phase response value of the is the frequency block In the phase response value of the is the frequency block The total number of state nodes within is the maximum value in the set of average phase change values among all frequency blocks is the index of the state point in the sequence is the total number of state nodes in the frequency block

[0009] The density classification sub-module extracts the density values at multiple positions in the sequence as the demarcation criteria to divide the corresponding density regions according to the normalized density values of each frequency block in the normalized density sequence of the frequency band nodes, and summarizes the frequency range, attribution level, and three-dimensional coordinates of the state points of each type of block to generate a frequency band state distribution coordinate set.

[0010] As a further solution of the present invention, the energy level control module includes: The amplitude difference calculation sub-module extracts the amplitude response values of all state points within the frequency range covered by each density block based on the frequency range and coordinate point distribution of the density blocks in the frequency band state distribution coordinate set, obtains the amplitude differences of each pair of state points, and identifies the minimum amplitude response difference in the amplitude difference set; The phase difference extraction sub-module reads the phase response values of the state points within each frequency block from the state coordinate points, compares the phase values of adjacent state points in ascending order of frequency to determine the maximum value, and obtains the maximum adjacent phase shift change value; The signal excitation screening sub-module calls all the signal energy level and frequency granularity combination items set in the signal library, compares the frequency granularity with the minimum amplitude response difference, screens out the combination items with granularity values greater than the minimum amplitude difference, makes an excitation threshold judgment on the signal energy level and phase difference with the maximum adjacent phase shift change value, screens out the combination items with excitation ability lower than the current maximum phase shift, and performs a normalization matching operation on the remaining combination items through the frequency and energy dimensions, using the formula: ; Calculate the excitation adaptation score of the th signal combination , sort the excitation adaptation scores, and establish a partition signal excitation configuration group; Among them, Indicates the difference between the frequency granularity term and the median frequency of the excitation frequency range in the th signal combination, Indicates the energy level value of the th signal in the th signal combination, Indicates the amplitude response difference of the th state point, Indicates the phase difference of the th state point,

[0011] As a further solution of the present invention, the matching gradient extraction module includes: The injection scanning sub-module performs signal injection operations on the microwave component frequency band according to the frequency step value and excitation energy level set for each block in the partitioned signal excitation configuration group, and collects the input impedance value and output impedance value of the corresponding frequency point in real time at a set time interval during the frequency point scanning process to obtain an impedance monitoring data set; The matching coefficient calculation sub-module, based on the impedance monitoring data set, sequentially calls the input impedance value and output impedance value of each frequency point according to the frequency point order, and uses the formula: ; Calculate the matching coefficient corresponding to the frequency point , and integrate to obtain a matching coefficient sequence; Among them, represents the input impedance value of the frequency point , represents the output impedance value of the frequency point , represents the input end attribute, represents the output end attribute; The tuning annotation generation sub-module, based on the matching coefficient sequence, extracts the difference between the matching coefficients between adjacent frequency points as the matching gradient value in the order of frequency points, classifies and organizes the matching gradient values by block to form a gradient sequence set, and compares the matching gradient value corresponding to each frequency point with a set tuning trigger threshold to mark the frequency points that meet the tuning trigger threshold condition, and generates a frequency point tuning response annotation table.

[0012] As a further solution of the present invention, the dynamic test execution module includes: The signal excitation configuration extraction sub-module extracts the signal excitation configuration parameters corresponding to the marked frequency points based on the frequency point tuning response annotation table, loads the signal source configuration, including information such as signal energy level and frequency granularity, and determines according to the direction of the matching gradient, loads the current settings of the corresponding inductor and capacitor tuning modules, reads the set values of the inductor and capacitor modules, detects whether the tuning module needs to be adjusted, and obtains the inductor-capacitor tuning settings; The response recording and adjustment sub-module loads the inductor-capacitor tuning settings, selects the adjustment method by judging the direction of the matching gradient. If the direction of the matching gradient is positive, it performs the micro-step value increment operation of the series inductor. If the direction of the matching gradient is negative, it performs the micro-step value decrement operation of the parallel capacitor, and records the reflection coefficient, amplitude response, and phase response data corresponding to the frequency points after each adjustment to obtain a frequency point response matching data group.

[0013] As a further solution of the present invention, it further includes a calibration path switching module. The calibration path switching module obtains the frequency point response matching data group, selects a configuration better than the current path as the new path, and generates a frequency point path optimization adjustment list.

[0014] As a further solution of the present invention, the frequency point path optimization adjustment list includes fluctuation boundary point indexes, path preference parameter groups, and set tags of the replaced paths.

[0015] As a further solution of the present invention, the calibration path switching module includes: The fluctuation detection and marking sub-module calculates the change slope of the phase values of three consecutive frequency points in the frequency point response matching data group, and takes the difference between adjacent two slopes as the fluctuation rate, determines whether the fluctuation rate exceeds the phase slope mutation threshold. If satisfied, it marks the frequency point as a fluctuation boundary point, retrieves the test path information and the available path alternative group to which the fluctuation boundary point belongs, and obtains the fluctuation boundary point path distribution information set; The path switching and optimization sub-module compares the frequency granularity and response resolution parameters of the paths in the available path alternative group according to the fluctuation boundary point path distribution information set, screens the configuration paths with finer granularity or higher resolution as the alternative options for the current path, establishes the corresponding substitution relationship, and generates a frequency point path optimization adjustment list.

[0016] A microwave component automatic testing method, which is executed based on the above microwave component automatic testing system, includes the following steps: S1: Obtain the data of the microwave component on the test platform, construct a coordinate map and divide it into equally spaced blocks, calculate the distribution density of the state nodes in the blocks, and obtain the frequency band state distribution coordinate set; S2: According to the distribution density of the state nodes in the frequency band state distribution coordinate set, screen the signal parameter combinations that meet the discrimination conditions, and generate a partition signal excitation configuration group; S3: According to the frequency step value and excitation energy level set for each block in the partition signal excitation configuration group, perform signal injection on each frequency band of the microwave component, mark the frequency points that meet the conditions, and generate a frequency point tuning response annotation table; S4: Based on the frequency points marked in the frequency point tuning response annotation table, perform micro-step value adjustment of series inductors or parallel capacitors to generate a frequency point response matching data group; S5: Obtain the frequency point response matching data group, select the configuration that is better than the current path as the new path, and generate a frequency point path optimization adjustment list.

[0017] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In the present invention, a three-dimensional state coordinate is constructed through frequency injection response, and density classification labels are established with frequency block division as the unit, enabling the frequency domain state evolution to have a visual recognition basis. Subsequently, signal combination screening is performed through the minimum difference and maximum change rate of the response fluctuation amplitude and phase shift dynamically, completing the adaptation to different frequency band excitation granularity and energy levels, solving the problem of insufficient resolution in previous frequency domain response adjustments. After signal parameter matching, combined with the judgment of the path frequency step direction and response gradient direction, the step-by-step tuning of the micro-structure device is performed to ensure continuous acquisition of response parameters, avoiding path deviation caused by misjudgment of the tuning direction. After completely collecting the three types of response results of reflection coefficient, amplitude, and phase, for the slope fluctuation trend of the response curve, the phase slope difference between multiple frequency points is extracted as the fluctuation rate index, the fluctuation boundary points in the frequency domain are located and mapped to the path structure, and combined with the frequency granularity and response resolution data of the alternative paths for comparison and screening of alternative paths, constructing a path optimization adjustment mechanism based on real-time fluctuation recognition to complete the construction of the path alternative scheme, having the dynamic switching ability when the multi-frequency point joint response state changes violently. This processing chain constructs an overall closed loop with state point density, fluctuation speed, direction gradient, and tuning structure as a continuous process, enabling parameter tuning and path reconstruction to have a response adjustment mechanism relying on data driving, improving the tuning accuracy and path replaceability in frequency domain testing. Description of the Drawings

[0018] Figure 1 is the system flow chart of the present invention; Figure 2 is the flow chart of the node density recognition module of the present invention; Figure 3 is the flow chart of the energy level regulation module of the present invention; Figure 4 is the flow chart of the matching gradient extraction module of the present invention; Figure 5 is the flow chart of the dynamic test execution module of the present invention; Figure 6This is a flow chart of the calibration path switching module of the present invention. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0020] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0021] See also Figure 1 The present invention provides a technical solution: a microwave component automatic testing system includes: The node density identification module obtains the response amplitude, phase shift, and temperature rise of the microwave component under each frequency injection in the test platform, constructs a three-dimensional state coordinate map, divides it into equally spaced blocks according to the set frequency span, calculates the state node distribution density in the block, compares the node distribution density with the density boundary value group, performs block classification operations and records the coordinate points of the corresponding state distribution, and obtains the frequency band state distribution coordinate set; The energy level control module extracts the minimum response amplitude difference and the maximum adjacent phase offset change value between the state points in the corresponding frequency range according to the frequency range and coordinate point distribution of the frequency band state distribution coordinate concentration density block, calls the signal energy level and frequency granularity combination items in the signal library, and selects the signal parameter combination that meets the distinction conditions according to the standard that the frequency granularity is less than the minimum amplitude spacing and the energy level is higher than the maximum phase difference required for excitation, and generates a partition signal excitation configuration group; The matching gradient extraction module implements signal injection for each frequency band of the microwave component according to the frequency step value and excitation energy level set for each block in the partition signal excitation configuration group, records the input and output impedance values ​​in real time during the frequency point scanning process, calculates the matching coefficient according to the frequency sequence, extracts the difference between the matching coefficients of adjacent frequency points as the matching gradient value, collects the matching gradient sequence according to the frequency partition, compares the matching gradient change amplitude with the set tuning trigger threshold, marks the frequency points that meet the conditions, and associates the corresponding signal configuration with the state distribution coordinates to generate a frequency point tuning response annotation table; The dynamic test execution module extracts the associated signal excitation configuration parameters based on the frequency points marked in the frequency point tuning response annotation table, loads the current settings of the corresponding inductor and capacitor tuning modules, matches the corresponding direction of the gradient, performs micro-step value adjustment of the series inductor or parallel capacitor according to the matching direction, records the reflection coefficient, amplitude response and phase response values ​​at the corresponding frequency points, and generates a frequency point response matching data group; The calibration path switching module obtains the phase values ​​of three consecutive frequency points in the frequency point response matching data group to calculate the change slope, and the difference between two adjacent slopes as the fluctuation rate, and determines whether the fluctuation rate exceeds the phase slope mutation threshold. If it meets the threshold, the frequency point is marked as a fluctuation boundary point, and the test path information and the available path candidate group to which the fluctuation boundary point belongs are retrieved. The frequency granularity and response resolution parameters of the alternative paths are compared, and the configuration that is better than the current path is selected as the new path, and a frequency point path optimization adjustment list is generated; The frequency band state distribution coordinate set includes the frequency interval identifier, the corresponding block density level label, and the state point three-dimensional coordinate set. The partitioned signal excitation configuration group specifically includes the signal frequency granularity, the signal energy level, and the block corresponding excitation parameter index. The frequency point tuning response annotation table includes the frequency point position label, the matching gradient direction identifier, and the signal parameter association index. The frequency point response matching data group specifically refers to the reflection coefficient record value, the amplitude response data column, and the phase response data column. The frequency point path optimization adjustment list includes the fluctuation boundary point index, the path optimization parameter group, and the replaced path setting label.

[0022] See also Figure 2 , the node density identification module includes: The state parameter construction submodule obtains the three types of parameter data of the response amplitude, phase offset, and temperature rise of the microwave component under each frequency injection in the test platform, divides it into multiple continuous frequency blocks according to the frequency step, and uses the three types of response parameters corresponding to each frequency block as the input variables of the amplitude axis, phase axis, and temperature rise axis respectively, constructs the coordinate representation of the state point in the three-dimensional response space, and marks each state point in the frequency block to which it belongs, and generates a state response coordinate set; Obtain three types of response data, namely the response amplitude, phase shift, and temperature rise of the microwave component under each frequency injection in the test platform. Specifically, within the specified frequency range, the injection frequency points are sequentially set in steps of 2 MHz. The frequency control unit is called to increase the microwave frequency from 8.0 GHz to 12.0 GHz in sequence. Record the amplitude response (unit: dBm), phase response (unit: degree), and temperature rise response (unit: °C) of the microwave component at each frequency point. Real-time sampling of the amplitude and phase is performed based on the frequency point. 100 samples are collected at each frequency point to improve data accuracy, and the mean method is used to eliminate random perturbations. For example, when the injection frequency is 9.0 GHz, the recorded amplitude samples are [-22.3, -22.5, -22.4, …, -22.6] dBm, and the average value is -22.45 dBm. The phase samples are [35.2, 35.4, 35.3, …, 35.6] degrees, and the average value is 35.4°. The temperature rise samples are [2.8, 2.9, 2.9, …, 3.0] °C, and the mean value is 2.9 °C. The acquisition of the three types of response quantities at the frequency point 9.0 GHz is completed. On this basis, the complete frequency range is divided into frequency blocks in units of 100 MHz, and a total of 40 blocks are divided. For all frequency points within each frequency block, lists are established and numbered respectively according to the corresponding relationship of injection frequency, amplitude response, phase response, and temperature rise response. For example, if there are 50 frequency points in the frequency block [9.0 GHz, 9.1 GHz), the three-dimensional response coordinate information of 50 groups of frequency points in this block is correspondingly recorded. A three-dimensional state space coordinate system is constructed with frequency as the horizontal axis. The frequency is the x-axis, the amplitude response is the y-axis, the phase response is the z-axis, and the temperature rise is used as the annotation attribute and bound to each three-dimensional coordinate point. The state point belonging is marked for all three-dimensional coordinate points in the frequency block, and the state response coordinate set is formed by binding labels through the frequency block range to which the state point frequency belongs.

[0023] Based on the number of state points included in each frequency block in the state response coordinate set, the density calculation sub-module extracts the amplitude response sequence and phase shift sequence of all state points within the block, and uses the formula: ; Calculate the normalized node density value of the frequency block , and organize the density values according to the frequency block to obtain the normalized density sequence of the frequency band nodes; Among them, is the number of state nodes within the frequency block , which is a dimensionless positive integer, is the standard deviation of the amplitude response sequence within the frequency block , reflecting the amplitude dispersion degree, and the unit is the same as the response amplitude, is the maximum value of the standard deviation of the amplitude response among all frequency blocks, used as the normalization reference benchmark, ​ is the phase response value of the th state point in the frequency block, with the unit of degree or radian. is the phase response value of the th state point in the frequency block, adjacent to . is the absolute value of the phase difference between the th and is the total number of state nodes within the frequency block . is the sum of the phase differences of the frequency block from the th to the th state point. is the maximum value in the set of average phase changes in all frequency blocks, serving as the reference benchmark for phase change normalization. is the index of the state point in the sequence.

[0024] First, extract the amplitude response sequence from each frequency block, calculate its standard deviation to measure the response fluctuation, and use the formula , where represents the amplitude response (in dBm) of the th state point in the frequency block is the mean value of the amplitude response within this block. is the number of state points. For example, if the amplitude responses of 5 state points in the block [9.000 GHz, 9.100 GHz) are -22.3, -22.6, -22.1, -22.2, -22.5 dBm respectively, then its mean value is : ; where the unit of the standard deviation is still dBm, used to measure the dispersion degree of the amplitude response; at the same time, take the absolute value of the difference between the phase response values of adjacent state points within this frequency block and calculate the average value to represent the phase response change degree. For example, if the phase responses of 5 state points in this block are 35.1, 35.4, 35.2, 35.3, 35.5 degrees, then the phase difference sequence is 0.3, 0.2, 0.1, 0.2, and the average value is degrees. Repeat this process for all blocks to calculate that the maximum value of the amplitude response standard deviation in all frequency blocks is 0.315 dBm, and the maximum value of the average phase change is 0.45 degrees, which are used as the normalization reference values respectively. Normalize the current block values accordingly. The amplitude normalization value is , and the phase normalization value is , combined state point quantity , substitute into the formula: , thus calculate the normalized node density index of this frequency block, and repeat this process to complete the normalized density calculation of all blocks.

[0025] The density classification sub-module extracts the density values at multiple positions in the sequence as the demarcation criteria to divide the corresponding density regions according to the normalized density values of each frequency block in the frequency band node normalized density sequence, summarizes the frequency range, attribution level, and three-dimensional coordinates of state points of each type of block, and generates a frequency band state distribution coordinate set; First, arrange the density values of all blocks in ascending order, and extract the density values corresponding to the 25%, 50%, and 75% positions in the arranged sequence as the three-level density division thresholds. In the example, the 8 density values are [0.842, 1.213, 1.458, 2.017, 2.784, 3.092, 3.923, 4.110]. The 25th percentile is the 2nd item: 1.213, the 50th percentile is the 4th item: 2.017, and the 75th percentile is the 6th item: 3.092. They are respectively set as the low-density, medium-density, and high-density division thresholds, and judge the normalized density value of each frequency block in turn. If the density value is less than 1.213, it is classified as a low-density block. For example, the [8.2–8.3) block, its density value is 0.842, which is less than the low-density threshold 1.213. If the density value is between 1.213 and 3.092, it is classified as a medium-density block. For example, the density of the [8.0–8.1) block is 1.458. If the density is greater than 3.092, it is classified as a high-density block. For example, the density of the [8.1–8.2) block is 3.923. This result shows that after density classification, the state distribution differences under different frequency bands can be clarified, and a frequency band state distribution coordinate set can be formed.

[0026] Please refer to Figure 3 , the energy level regulation module includes: The amplitude difference calculation sub-module extracts the amplitude response values of all state points within the frequency range covered by each density block based on the frequency range and coordinate point distribution of the density blocks in the frequency band state distribution coordinate set, obtains the amplitude differences of each pair of state points, and identifies the minimum amplitude response difference in the amplitude difference set; According to the frequency range and coordinate point distribution of the density block in the frequency band state distribution coordinates, obtain the amplitude response values of all state points in each frequency block, sort them in ascending order of frequency, and perform a pairwise difference operation on the amplitude response values of each pair of adjacent state points. During the detailed execution, if the frequency point sequence in the block [9.0 GHz, 9.1 GHz) is [9.000, 9.002, 9.004, 9.006, 9.008] GHz, and the corresponding amplitude responses are [-22.3, -22.5, -22.4, -22.1, -22.6] dBm, after sorting, the adjacent differences are 0.2, 0.1, 0.3, 0.5 in sequence. The minimum difference of 0.1 dBm is obtained by using the minimum value judgment operation. The judgment operation is completed by traversing the above difference array and calling the numerical comparison instruction. To ensure the repeatability of this operation, a mapping index table corresponding to the amplitude difference vector and the frequency sequence is constructed to identify the frequency combination of the difference source point. For example, the difference of 0.1 comes from the combination of the frequency points 9.002 GHz and 9.004 GHz. During the implementation process, the influence of thermal drift on the amplitude change needs to be considered. In actual tests, the temperature rise difference threshold is set to 0.2 °C as the point pair screening condition. This setting is based on the temperature rise perturbation statistical results of 100 repeated injections of the same frequency point on the platform. The temperature rise difference samples are as follows: the temperature rises of the point pair 9.002 and 9.004 are 2.91 °C and 2.93 °C respectively, and the difference is 0.02 °C; the point pair 9.004 and 9.006 are 2.93 °C and 2.92 °C respectively, and the difference is 0.01 °C; the point pair 9.006 and 9.008 are 2.92 °C and 2.94 °C respectively, and the difference is 0.02 °C, all within 0.2 °C. Therefore, in actual screening, only the point pairs with a temperature rise difference not exceeding this threshold are subjected to the amplitude difference operation and the minimum value extraction operation, and finally the minimum response amplitude difference is obtained.

[0027] The phase difference extraction sub-module reads the phase response values of the state points in each frequency block from the state coordinate points, and after arranging them in ascending order of frequency, compares the phase values of adjacent state points in sequence to determine the maximum value among them, and obtains the maximum adjacent phase offset change value; Call the phase response values of the recorded state points in the density block, extract adjacent state point pairs point by point after sorting them in ascending order of frequency, and perform an absolute difference operation on the phase values of each pair of state points. For example, if the state point frequency sequence is [9.000, 9.002, 9.004, 9.006] GHz and the corresponding phase values are [35.2, 35.4, 35.1, 35.3] degrees, the adjacent differences are |35.4 - 35.2| = 0.2, |35.1 - 35.4| = 0.3, |35.3 - 35.1| = 0.2. After obtaining all the phase differences, use the maximum value identification operation to select the maximum phase offset difference of 0.3 degrees from them. During the implementation, the phase response values are collected in angular units, and the average value is taken after 100 consecutive measurements at each frequency point by relying on the fast sampling device of the platform. The data participating in the difference calculation are all average values. In addition, to exclude the influence of outliers caused by faults or spike jumps, a phase jump upper limit threshold of 3.0 degrees is set. If the difference is greater than this threshold, it is regarded as an invalid point pair and does not participate in the maximum value judgment. This threshold refers to the maximum phase response change amplitude observed in continuous tests of the same component at different frequency points. The sample data shows that for the frequency point pair 9.002 and 9.004, the phase values are 35.4 and 35.1, and the difference of 0.3 degrees is valid; for the point pair 9.004 and 9.006, the phase values are 35.1 and 35.3, and the difference of 0.2 degrees is valid; for the point pair 9.006 and 9.008, the phase values are 35.3 and 38.6, and the difference of 3.3 degrees is invalid. Finally, only the valid point pairs are retained to perform the maximum value operation to obtain the maximum adjacent phase offset change value.

[0028] The signal excitation screening sub-module calls all the signal energy level and frequency granularity combination items set in the signal library, compares the frequency granularity with the minimum amplitude response difference, and screens out the combination items with granularity values greater than the minimum amplitude difference. It performs an excitation threshold judgment on the signal energy level and phase difference with the maximum adjacent phase offset change value, and screens out the combination items with excitation capabilities lower than the current maximum phase offset. For the remaining combination items, a normalization matching operation is performed in the frequency and energy dimensions, using the formula: ; Calculate the excitation adaptation score of the th signal combination, sort the excitation adaptation scores, and establish a partitioned signal excitation configuration group; Among them, represents the difference between the th frequency granularity item and the median frequency of the excitation frequency interval in the th signal combination, represents the energy level value of the th signal in the th signal combination, represents the The amplitude response difference of a state point, represents the phase difference of the th state point, and

[0029] represents the number of signal parameter items in the combination to be screened. First, obtain the minimum response amplitude difference in the amplitude difference calculation sub-module, which is 0.1 dBm here, and then call the maximum adjacent phase shift change value in the phase difference extraction sub-module, which is 0.3 degrees here. Take 0.1 dBm as the frequency granularity judgment threshold, and compare whether the granularity item ΔF in the signal combination is less than this threshold one by one. For example, the frequency granularity array is [0.05, 0.15, 0.1, 0.2] MHz, and only the combination item with ΔF of 0.05 is retained; then take 0.3 degrees as the excitation threshold, set the energy level array as [0.2, 0.4, 0.5, 0.8] mW, and through the energy and phase excitation matching relationship, the excitation energy required for the current maximum phase shift of 0.3 degrees is 0.35 mW. Accordingly, retain the combination items with E≥0.35, that is, the combinations corresponding to 0.4, 0.5, and 0.8. Finally, call the scoring function to calculate the fitness of the remaining combination items, using the following formula: ; wherein, = [0.05, 0.08, 0.09, 0.07] MHz, = [0.4, 0.5, 0.5, 0.8] mW, = [0.1, 0.2, 0.3, 0.15] dBm, = [0.3, 0.25, 0.2, 0.28] degrees, and substitute into the formula for itemized calculation as follows: The first item is ; The second item is ; The third item is ; The fourth item is .

[0030] The sum is 3.736, and the average value is: .

[0031] Finally, obtain the excitation fitness score of this combination item as 0.934. After sorting the scoring results of the remaining combination items in ascending order, select the combination item with a lower scoring value to establish a partition signal excitation configuration group. The advantage of the formula is that by incorporating the signal frequency granularity and energy level at the same time, a denominator ratio relationship is established with the actual response offset amplitude and angle of the state point, taking into account the signal ability and response difficulty in the normalization dimension and enhancing the combination discrimination accuracy.

[0032] Please refer to Figure 4, the matching gradient extraction module includes: The injection scanning submodule performs signal injection operation on each frequency band of the microwave component according to the frequency step value and excitation energy level set for each block in the partition signal excitation configuration group. During the frequency point scanning process, the input impedance value and output impedance value of the corresponding frequency point are collected in real time at the set time interval to obtain the impedance monitoring data set; Signal injection is implemented for each frequency band of the microwave component. During the execution process, the step value and energy level corresponding to each frequency block in the signal configuration group need to be mapped to the scanning control module one by one. The frequency starting value is set to 8.000GHz, the step value is 2MHz, and a total of 50 frequency points are injected. Each injection lasts for 0.2 seconds. At the same time, the power module is controlled to output the corresponding amplitude according to the excitation level in the signal configuration. For example, the output at 9.000GHz is 0.5mW, and at 9.002GHz is 0.6mW. During the scanning process, the impedance sampling unit is synchronously connected to collect the input impedance and output impedance corresponding to each frequency point. The bridge measurement principle is used. The voltage and current components are extracted after signal injection. If the input voltage is 2.5 volts and the input current is 0.025 amperes at a certain frequency point, the input impedance is 100 ohms. The output impedance is obtained by measuring the value at the output terminal at the same frequency point. For example, the voltage measured at the output terminal is 1.8 volts and the current is 0.018 amperes, then the output impedance is 100 ohms. The input and output impedance values ​​of all frequency points in the full frequency band are collected to form a frequency-impedance matching matrix array. Each set of data uses the frequency point as the index, and the impedance value pair is stored as the content in a two-dimensional array structure for subsequent calculation of the matching coefficient to finally obtain the impedance monitoring data set.

[0033] The matching coefficient calculation submodule is based on the impedance monitoring data set, and calls the input impedance value and output impedance value of each frequency point in sequence according to the frequency point, using the formula: ; Calculate frequency points The corresponding matching coefficient , integration obtains the matching coefficient sequence; in, Indicates frequency point The input impedance value is Indicates frequency point The output impedance value is Indicates the input properties. Indicates output terminal properties.

[0034] Set frequency point GHz, its input impedance Ohms, output impedance Ohms, the matching coefficient at this frequency point is calculated as follows: ; All frequency points during the frequency scanning process are calculated one by one in this way to obtain a matching coefficient sequence , where each term represents the mismatch ratio of the input and output impedances at that frequency point, and the value range is between 0 and 1. The closer to 0, the closer the impedance is to matching. If the matching coefficient exceeds 0.3, it means there is an impedance deviation at that point, which needs to be marked for subsequent attention. This sequence will be passed to the next module for calculating the difference between frequency points, and finally a matching coefficient sequence is obtained.

[0035] Based on the matching coefficient sequence, the tuning annotation generation sub-module extracts the difference between the matching coefficients of adjacent frequency points in the order of frequency points as the matching gradient value, classifies and organizes the matching gradient values by block to form a gradient sequence set, compares the matching gradient value corresponding to each frequency point with the set tuning trigger threshold, marks the frequency points that meet the tuning trigger threshold condition, and generates a frequency point tuning response annotation table; Extract the difference between the matching coefficients of adjacent frequency points in the order of frequency as the matching gradient value, and construct a matching gradient sequence array. For example, if the frequency point sequence is [9.000, 9.002, 9.004, 9.006] GHz and its matching coefficients are [0.085, 0.111, 0.134, 0.102], then the corresponding gradients are |0.111 - 0.085| = 0.026, |0.134 - 0.111| = 0.023, |0.102 - 0.134| = 0.032, and the matching gradient sequence is [0.026, 0.023, 0.032]. The gradient values of all frequency points are sorted and archived in units of frequency blocks to form a gradient distribution set. A numerical comparison and judgment operation is performed on the gradient value of each frequency point and the set tuning trigger threshold. The tuning trigger threshold is set to 0.03, and the average matching fluctuation obtained from the historical component during stable state scanning is 0.028. To distinguish the boundary value, it is rounded up to 0.03. If the matching gradient value of a frequency point is greater than this threshold, it is marked as a tunable point. For example, in the previous example, the gradient value corresponding to 9.006 GHz is 0.032, which is greater than 0.03, and it is determined as a tuning frequency point. All frequency points that meet the conditions are marked in this way, and they are indexed and matched with the signal configuration group number used and the state distribution coordinates corresponding to the frequency points to form a three-dimensional annotation structure, the content of which is frequency point, matching gradient value, signal excitation number, and state coordinate point set identifier. Finally, a frequency point tuning response annotation table is established.

[0036] Please refer to Figure 5 , the dynamic test execution module includes: The signal excitation configuration extraction sub-module extracts the signal excitation configuration parameters corresponding to the marked frequency points based on the frequency point tuning response annotation table, loads the signal source configuration, including information such as signal energy level and frequency granularity, and determines according to the direction of the matching gradient, loads the current settings of the corresponding inductor and capacitor tuning modules, reads the set values of the inductor and capacitor modules, detects whether the tuning module needs to be adjusted, and obtains the inductor-capacitor tuning settings; First, extract the corresponding signal excitation configuration parameters item by item according to the target frequency points marked in the frequency annotation table. This parameter group usually includes the frequency granularity, excitation signal level, and adapted power range applicable to the corresponding frequency points. In an actual test scenario, assume the frequency point is 9.012 GHz, and its excitation parameter configuration is a granularity of 0.002 GHz and a signal energy of 15 dBm. After reading this parameter, enter the tuning device calling process, call the tuning unit module configured in the current system and load its current setting value. The tuning unit is distributed according to two physical structures of series inductors and parallel capacitors. The current tuning step value of each type of device is output by the memory or register. For example, the inductor is currently set to 8.5 nH, and the capacitor is currently set to 1.4 pF. Detect the required matching direction at the current frequency point, that is, judge the gradient change direction of the corresponding parameters of the current response curve. If the reflection parameter curve at the target frequency shows an upward trend, it is judged as a positive gradient, and an adjustment in the series inductor direction needs to be performed. If the curve drops, it is judged as a negative gradient, and a response adjustment in the parallel capacitor direction needs to be performed. The gradient matching judgment is based on comparing the change direction of the reflection coefficients corresponding to the two test frequency points before and after the current frequency point. For example, the reflection coefficient at frequency point 9.010 GHz is 0.31, and at frequency point 9.012 GHz is 0.34, then the calculated gradient is positive, and the direction is judged as positive, and the inductor tuning configuration is prepared to be loaded to continue the adjustment operation, and the inductor-capacitor tuning settings are obtained.

[0037] The response recording and adjustment sub-module loads the inductor-capacitor tuning settings, selects the adjustment method by judging the direction of the matching gradient. If the direction of the matching gradient is positive, perform a micro-step value increment operation on the series inductor. If the direction of the matching gradient is negative, perform a micro-step value decrement operation on the parallel capacitor. Record the reflection coefficient, amplitude response, and phase response data corresponding to the frequency points after each adjustment to obtain a frequency point response matching data group; Extract the inductance-capacitance tuning settings loaded by the sub-module according to the signal excitation configuration, and perform the actual tuning adjustment operation. If the determined direction is positive, perform a micro-step value increment adjustment for the series inductance module. For example, if the current inductance value is 8.5 nH and the fine-tuning step size is 0.1 nH each time, after updating to 8.6 nH, reload the excitation signal, and record the reflection coefficient, amplitude response, and phase response values in the new state. Conversely, if the direction is negative, perform a micro-step value decrement operation for the parallel capacitance module. For example, if the current capacitance value is 1.4 pF, adjust it step by step by 0.1 pF to 1.3 pF, then inject the excitation signal and collect the results. During the above fine-tuning process, use a reflection coefficient meter to collect the S11 parameter, and the example record is 0.29. The amplitude response is obtained by a power meter, with a value of -22.1 dBm, and the phase response is synchronously measured by a phase sensor, with a result of 34.2°. All the collected parameters are bound and saved corresponding to the adjusted frequency point, and a response data group structure is constructed with the frequency as the index, and arranged in sequence according to the test frequency to form a complete set. This set contains four data columns: frequency point, reflection coefficient, amplitude response, and phase response, forming a two-dimensional extended result record matrix corresponding to the frequency response, and obtain the frequency point response matching data group.

[0038] Please refer to Figure 6 , the calibration path switching module includes: The fluctuation detection and marking sub-module obtains the phase values of three consecutive frequency points in the frequency point response matching data group to calculate the change slope, and the difference between two adjacent slopes as the fluctuation rate, and determines whether the fluctuation rate exceeds the phase slope mutation threshold. If it is satisfied, mark this frequency point as the fluctuation boundary point, and retrieve the test path information and the available path alternative group to which the fluctuation boundary point belongs to obtain the fluctuation boundary point path distribution information set; Obtain the phase values of three consecutive frequency points in the frequency point response matching data group, and extract the phase values corresponding to each group of three adjacent frequency points in the order of frequency. Let the frequency point be , and the phase values of the three points are , then calculate the front and back slopes respectively with an equal frequency interval as the reference, that is: , .

[0039] Calculate the difference between two adjacent slopes: .

[0040] As the current frequency point The fluctuation rate at [specific location] is traversed through the entire frequency response matching data set in this way to generate a complete frequency point fluctuation rate sequence. Based on this, it is judged whether the fluctuation rate of each frequency point exceeds the set phase slope mutation threshold. The threshold is set to 400° / GHz. This value is derived from the statistical results of the peak distribution of the fluctuation rate changes during the continuous scanning of the microwave component in the experiment. The value corresponding to the 90th percentile is rounded up to 400° / GHz as the defining benchmark. If the current frequency point fluctuation rate is greater than this threshold, it is marked as a fluctuation boundary point, and the test path number corresponding to this fluctuation boundary point is retrieved backward. The mapping relationship from the frequency point to the test path can be obtained from the frequency block index table, and then all the configured information under the current path is called through the path scheduling index table. At the same time, the available path alternative group is read, where the alternative paths are the set of paths not occupied by the current frequency point in the same block. Finally, the fluctuation boundary point path distribution information set is obtained.

[0041] According to the fluctuation boundary point path distribution information set, the path switching optimization sub-module compares the frequency granularity and response resolution parameters of each path in the available path alternative group, filters the configured paths with finer granularity or higher resolution as the alternative options for the current path, establishes the corresponding alternative relationship, and generates a frequency point path optimization adjustment list; According to the fluctuation boundary point path distribution information set obtained in the fluctuation detection marking sub-module, the frequency granularity and response resolution parameters of the original test path corresponding to the current fluctuation boundary point and all available alternative paths are extracted. The frequency granularity refers to the spacing value between frequency points in the current path, and the response resolution parameter refers to the minimum measurable change value of the amplitude and phase responses of this path in the current block. Suppose the current path frequency granularity is 2MHz, and the alternative path granularities are 1MHz, 3MHz, 2MHz respectively, and the response resolution ability is 0.1dBm for amplitude and 0.2° for phase. The alternative paths are Path 1: 0.08dBm / 0.15°, Path 2: 0.15dBm / 0.25°, Path 3: 0.1dBm / 0.18°. Then, two comparisons need to be made for the frequency granularity and response resolution parameters of each path. The first step is to judge whether the alternative path granularity is less than the current path, and the second step is to judge whether its minimum measurable range in the amplitude and phase dimensions is better than the current path setting, that is, at least one of the two indicators is better than the current configuration. The priority is set using the weighting method: if the amplitude resolution is better than the current set value of 0.1dBm, 1 point is counted, and if the phase resolution is better than the current set value of 0.2°, another 1 point is counted, and if the frequency granularity is better than the current path's 2MHz, another 1 point is counted.

[0042] According to this logic, the score of the first alternative path is , and the score of the second alternative path is , and the score of the third alternative path is , so the first path is selected as an alternative, a one-to-one association relationship between the frequency points and the alternative path is constructed, and the path number, frequency point position, alternative path granularity, and resolution parameter are recorded. Finally, a frequency point path optimization and adjustment list is generated.

[0043] The microwave component automatic test method is based on the above-mentioned microwave component automatic test system and includes the following steps: S1: Obtain the data of the microwave component on the test platform, construct a coordinate map and divide it into equally spaced blocks, calculate the distribution density of the state nodes within the blocks, and obtain the frequency band state distribution coordinate set; S2: According to the distribution density of the state nodes in the frequency band state distribution coordinate set, screen the signal parameter combinations that meet the discrimination conditions, and generate a partitioned signal excitation configuration group; S3: According to the frequency step value and excitation energy level set for each block in the partitioned signal excitation configuration group, inject signals into each frequency band of the microwave component, mark the frequency points that meet the conditions, and generate a frequency point tuning response annotation table; S4: Based on the frequency points marked in the frequency point tuning response annotation table, perform micro-step value adjustment of the series inductor or parallel capacitor to generate a frequency point response matching data group; S5: Obtain the frequency point response matching data group, select the configuration that is better than the current path as the new path, and generate a frequency point path optimization and adjustment list.

[0044] The above is only a preferred embodiment of the present invention and does not limit the present invention in other forms. Any person skilled in the art may use the technical content disclosed above to make changes or modifications into equivalent embodiments with equivalent changes and apply them to other fields. However, as long as it does not depart from the technical solution content of the present invention, any simple modification, equivalent change, and modification made to the above embodiments based on the technical essence of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. Microwave component automated testing system, characterized in that: The system comprises: The node density identification module obtains the data of microwave components on the test platform, constructs a coordinate map and divides it into equally spaced blocks, calculates the state node distribution density in the block, and obtains the frequency band state distribution coordinate set; The energy level control module selects a signal parameter combination that meets the differentiation condition according to the state node distribution density of the frequency band state distribution coordinate set, and generates a partition signal excitation configuration group; The matching gradient extraction module implements signal injection for each frequency band of the microwave component according to the frequency step value and excitation energy level set for each block in the partition signal excitation configuration group, marks the frequency points that meet the conditions, and generates a frequency point tuning response annotation table; The dynamic test execution module performs micro-step value adjustment of the series inductor or the parallel capacitor based on the frequency points marked in the frequency point tuning response annotation table to generate a frequency point response matching data group.

2. The microwave component automatic testing system according to claim 1, characterized in that: The frequency band state distribution coordinate set includes a frequency interval identifier, a corresponding block density level label, and a state point three-dimensional coordinate set; the partitioned signal excitation configuration group specifically includes a signal frequency granularity, a signal energy level, and a block corresponding excitation parameter index; the frequency point tuning response annotation table includes a frequency point position label, a matching gradient direction identifier, and a signal parameter association index; the frequency point response matching data group specifically refers to a reflection coefficient record value, an amplitude response data column, and a phase response data column.

3. The microwave component automatic testing system according to claim 1, characterized in that: The node density identification module comprises: The state parameter construction submodule obtains the three types of parameter data of the response amplitude, phase offset, and temperature rise of the microwave component under each frequency injection in the test platform, divides it into multiple continuous frequency blocks according to the frequency step, and uses the three types of response parameters corresponding to each frequency block as the input variables of the amplitude axis, phase axis, and temperature rise axis respectively, constructs the coordinate representation of the state point in the three-dimensional response space, and marks each state point in the frequency block to which it belongs, and generates a state response coordinate set; The density calculation submodule extracts the amplitude response sequence and phase offset sequence of all state points in the block based on the number of state points in each frequency block in the state response coordinate set, using the formula: ； Calculation frequency block The normalized node density value of , sort the density values ​​by frequency blocks to obtain the normalized density sequence of frequency band nodes; in, It is a frequency block The number of state nodes in It is a frequency block The standard deviation of the internal amplitude response series, is the maximum value of the standard deviation of the amplitude response in all frequency blocks, It is a frequency block Middle The phase response value of the state point is It is a frequency block Middle The phase response value of the state point is It is a frequency block The total number of state nodes in is the maximum value among the phase change average values ​​in all frequency blocks, is the index of the state point in the sequence, is the total number of state nodes in the frequency block; The density classification submodule extracts the density values ​​of various positions in the sequence as the demarcation criteria to divide the corresponding density areas according to the normalized density value of each frequency block in the normalized density sequence of the frequency band node, summarizes the frequency range, attribution level, and three-dimensional coordinates of the state point of each type of block, and generates a frequency band state distribution coordinate set.

4. The microwave component automatic testing system according to claim 1, characterized in that: The energy level control module comprises: The amplitude difference calculation submodule extracts the amplitude response values ​​of all state points within the frequency range covered by each density block based on the frequency range and coordinate point distribution of the density block in the frequency band state distribution coordinate set, obtains the amplitude difference of each pair of state points, and identifies the minimum amplitude response difference in the amplitude difference set; The phase difference extraction submodule reads the phase response value of the state point in each frequency block from the state coordinate point, arranges them in ascending order of frequency, and then compares the phase values ​​of adjacent state points in turn to determine the maximum value, thereby obtaining the maximum adjacent phase offset change value; The signal excitation screening submodule calls all signal energy level and frequency granularity combination items set in the signal library, compares the frequency granularity with the minimum amplitude response difference, screens out the combination items with granularity values ​​greater than the minimum amplitude difference, and performs excitation threshold judgment on the signal energy level and phase difference and the maximum adjacent phase offset change value, screens out the combination items with excitation capabilities lower than the current maximum phase offset, and performs normalized matching operations on the remaining combination items through frequency and energy dimensions, using the formula: ； Calculate the Stimulus adaptation score for signal combinations , sort the incentive adaptation scores and establish a partition signal incentive configuration group; in, Indicates The signal combination The difference between the frequency granularity item and the median frequency of the excitation frequency interval, Indicates The signal combination The energy level value of the signal, Indicates The amplitude response difference of the state points, Indicates The phase difference of each state point is Indicates the number of signal parameter items in the combination to be filtered.

5. The microwave component automatic testing system according to claim 1, characterized in that: The matching gradient extraction module comprises: The injection scanning submodule performs a signal injection operation on the frequency band of the microwave component according to the frequency step value and the excitation energy level set for each block in the partition signal excitation configuration group, collects the input impedance value and the output impedance value of the corresponding frequency point in real time at a set time interval during the frequency point scanning process, and obtains an impedance monitoring data set; The matching coefficient calculation submodule is based on the impedance monitoring data set, and calls the input impedance value and output impedance value of each frequency point in order of frequency points, using the formula: ； Calculate frequency points The corresponding matching coefficient , integration obtains the matching coefficient sequence; in, Indicates frequency point The input impedance value is Indicates frequency point The output impedance value is Indicates the input properties. Indicates output terminal attributes; The tuning annotation generation submodule is based on the matching coefficient sequence, extracts the matching coefficient differences between adjacent frequency points in frequency point order as matching gradient values, classifies the matching gradient values ​​by block to form a gradient sequence set, compares the matching gradient value corresponding to each frequency point with the set tuning trigger threshold, marks the frequency points that meet the tuning trigger threshold conditions, and generates a frequency point tuning response annotation table.

6. The microwave component automatic testing system according to claim 1, characterized in that: The dynamic test execution module includes: The signal excitation configuration extraction submodule extracts the signal excitation configuration parameters of the corresponding frequency points based on the frequency points marked in the frequency point tuning response annotation table, loads the signal source configuration, including information such as signal energy level and frequency granularity, and loads the corresponding current settings of the inductance and capacitance tuning modules according to the direction of the matching gradient, reads the set values ​​of the inductance and capacitance modules, detects whether the tuning modules need to be adjusted, and obtains the inductance and capacitance tuning settings; The response recording and adjustment submodule loads the inductor and capacitor tuning settings, selects the adjustment mode by judging the direction of the matching gradient, and executes the microstep value increment operation of the series inductor if the matching gradient direction is positive; and executes the microstep value decrement operation of the parallel capacitor if the matching gradient direction is negative. The reflection coefficient, amplitude response and phase response data of the corresponding frequency point after each adjustment are recorded to obtain a frequency point response matching data group.

7. The microwave component automatic testing system according to claim 1, characterized in that: It also includes a calibration path switching module, which obtains the frequency point response matching data group, selects a configuration that is better than the current path as a new path, and generates a frequency point path optimization adjustment list.

8. The microwave component automatic testing system according to claim 7, characterized in that: The frequency point path optimization adjustment list includes a fluctuation boundary point index, a path optimization parameter group, and a post-replacement path setting label.

9. The microwave component automatic testing system according to claim 7, characterized in that: The calibration path switching module comprises: The fluctuation detection marking submodule obtains the phase value calculation change slope of three consecutive frequency points in the frequency point response matching data group, and the difference between two adjacent slopes as the fluctuation rate, and determines whether the fluctuation rate exceeds the phase slope mutation threshold. If it meets the threshold, the frequency point is marked as a fluctuation boundary point, and the test path information and the available path candidate group to which the fluctuation boundary point belongs are retrieved to obtain the fluctuation boundary point path distribution information set; The path switching optimization submodule compares the frequency granularity and response resolution parameters of the paths in the available path alternative group according to the fluctuation boundary point path distribution information set, selects the configuration path with finer granularity or higher resolution as an alternative option for the current path, establishes a corresponding alternative relationship, and generates a frequency point path optimization adjustment list.

10. A microwave component automated testing method, characterized in that: The microwave component automated testing system according to any one of claims 1 to 9 comprises the following steps: S1: Obtain the data of the microwave component on the test platform, construct a coordinate map and divide it into equally spaced blocks, calculate the distribution density of the state nodes in the blocks, and obtain the frequency band state distribution coordinate set; S2: According to the state node distribution density of the frequency band state distribution coordinate set, a signal parameter combination that meets the differentiation condition is screened to generate a partition signal excitation configuration group; S3: According to the frequency step value and excitation energy level set for each block in the partition signal excitation configuration group, signal injection is performed on each frequency band of the microwave component, frequency points that meet the conditions are marked, and a frequency point tuning response annotation table is generated; S4: Based on the frequency points marked in the frequency point tuning response annotation table, perform micro-step value adjustment of the series inductor or the parallel capacitor to generate a frequency point response matching data group; S5: Acquire the frequency point response matching data group, select a configuration that is better than the current path as a new path, and generate a frequency point path optimization adjustment list.

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