Resonant cavity high-precision deviation diagnosis method based on multimode analysis

Abstract

The invention discloses a resonant cavity high-precision deviation diagnosis method based on multimode analysis, and relates to the technical field of high-frequency resonant cavities. The method comprises the following steps: S1, constructing a physical deviation-resonance characteristic data set; s2, obtaining resonance characteristics of the to-be-tested piece; s3, carrying out feature matching; and S4, deviation attribution is completed. According to the method, non-intrusive high-precision diagnosis is realized through multimode features, the efficiency and accuracy of deviation positioning are improved, the property, position and severity of deviation can be effectively judged, and targeted correction suggestions are provided.

Description

Technical Field

[0001] This invention relates to the field of high-frequency resonant cavity technology, and more specifically to a high-precision deviation diagnosis method for resonant cavities based on multimode analysis. Background Technology

[0002] With the development of high-frequency microwave and millimeter-wave technologies, the size of resonant cavities is becoming increasingly miniaturized, making the precision requirements for manufacturing and assembly extremely stringent. However, due to the tiny size of the resonant cavity, even minor errors in its manufacturing and assembly can lead to significant performance variations, such as frequency shifts, deterioration of return loss, and mode changes. Furthermore, after the multiple components of the resonant cavity are welded together, it is difficult to accurately measure the dimensional changes within the cavity and welding deviations. These changes are conventionally diagnosed through measurement and empirical analysis, which is inefficient and has limited accuracy. Currently, there is a lack of a method to quickly locate manufacturing and assembly problems by analyzing changes in the resonant cavity's mode frequencies.

[0003] Although there have been some studies on resonant cavity frequency adjustment, most of the methods focus on adjusting structural parameters to change the frequency of the operating mode, and lack non-invasive and precise analysis methods for the internal conditions of the resonant cavity.

[0004] While research on production control exists in other fields, the following problems remain: 1. Insufficient adaptability to different scenarios: High-frequency resonant cavities are far more sensitive to dimensional changes and assembly errors than general devices, requiring precise location of specific dimensional variations to improve processing control. 2. Limited analytical methods: Existing analytical methods mainly rely on the cavity's S-parameters and dimensional analysis, making it difficult to comprehensively capture multi-dimensional information such as frequency variations and mode distribution, especially unable to diagnose specific mode changes caused by processing or assembly. 3. Difficulty in quickly and accurately detecting changes in the internal structure of the resonant cavity without damaging it. Summary of the Invention

[0005] To overcome the shortcomings of existing technologies, this invention provides a high-precision deviation diagnosis method for resonant cavities based on multi-mode data analysis, aiming to solve the problems of low diagnostic efficiency, insufficient accuracy, and difficulty in non-destructive testing of the internal structure during the fabrication and assembly of resonant cavities.

[0006] Considering that vector network analyzers (VNAs) typically have a wide frequency scanning bandwidth in actual testing, they can not only capture the resonant peak of the target operating mode but also include the frequency response of several higher-order or adjacent modes. Furthermore, the frequency distribution of these non-operating modes is also sensitive to local changes in the resonant cavity structure and has different response characteristics to different types of dimensional deviations. Compared to focusing only on a single operating mode, this multi-mode response can provide richer structural information, which helps to improve the resolution of deviation diagnosis. Based on this, this method uses joint analysis of multi-mode resonant frequencies to quickly locate the regions of specific problems such as processing dimensions, assembly deviations, and deformation, and realizes the identification and attribution of minor structural errors, providing a more efficient and reliable quality control means for the processing and assembly of high-frequency resonant cavities.

[0007] Compared with traditional methods, this invention, as a non-invasive detection method, can achieve high-precision detection without damaging the resonant cavity, while significantly optimizing detection efficiency.

[0008] To achieve the above objectives, the present invention provides the following technical solution:

[0009] A high-precision deviation diagnosis method for resonant cavities based on multi-mode data analysis, characterized by the following steps:

[0010] S1. Construct a physical deviation-resonance feature dataset;

[0011] An ideal simulation model of the resonant cavity is established through software simulation. The geometric dimensions and assembly parameters of the ideal simulation model are changed multiple times to obtain the S-parameters corresponding to error models with different structural parameters, and the simulation dataset is obtained.

[0012] The S-parameters of the ideal simulation model are used to perform feature optimization on each simulation data in the simulation dataset, and a database is constructed based on the optimized simulation data.

[0013] The feature optimization method is as follows: The S-parameters contain multiple resonant modes; the frequency and return loss corresponding to each resonant mode in the S-parameters of the ideal simulation model are used as reference data, the frequency and return loss corresponding to each resonant mode in the simulation data S-parameters are extracted, and normalization is performed based on the reference data to obtain frequency feature data and return loss feature data.

[0014] S2. Obtain the resonance characteristics of the device under test;

[0015] The S-parameters of the resonant cavity under test are measured, and the frequencies and return losses corresponding to each resonant mode are extracted from the S-parameters. Based on the reference data, the normalization process is performed to obtain the frequency characteristic data and return loss characteristic data of the resonant cavity under test, thereby forming the resonant characteristics that can characterize the state of the device under test.

[0016] S3. Perform feature matching;

[0017] The resonance characteristics of the device under test (DUT) are pattern matched with the database established in S1 to obtain a set of simulation data that best matches the resonance characteristics of the DUT; the geometric dimensions and assembly parameters in the simulation data are used as the geometric dimensions and assembly parameters of the DUT.

[0018] S4. Complete the deviation attribution;

[0019] Based on the geometric dimensions and assembly parameters of the test part obtained in step S3, the nature, location, and severity of existing machining or assembly problems are determined, and a deviation diagnosis report is output to provide guidance and suggestions for subsequent process correction or assembly adjustment.

[0020] Furthermore, in step S3, the pattern matching method is as follows:

[0021] First, the primary and secondary modes are determined based on the operating mode of the resonant cavity, and different weights are assigned to each mode. Then, the frequency deviation and return loss deviation between the resonant cavity under test and each mode in the database are extracted, and the weighted deviation results are used as the matching index.

[0022] Furthermore, during the mode matching process, in order to avoid changes in the order of resonance modes caused by changes in structural parameters, the electromagnetic field distribution characteristics and quality factors recorded in the database are combined to perform mode recognition on each resonance peak to ensure that different modes correspond, so as to ensure that a set of simulation data that best matches the resonance characteristics of the device under test is obtained.

[0023] Furthermore, several resonant cavities were fabricated based on an ideal simulation model, their geometric dimensions and assembly parameters were measured, and the S-parameters were detected. The data of each resonant cavity were entered into a database to supplement the actual fabrication deviation data.

[0024] Compared with the prior art, the present invention has at least the following beneficial effects:

[0025] This invention utilizes multi-mode correlation mapping analysis between the frequency distribution characteristics of resonant cavity modes and structural problems to achieve precise localization of processing and assembly issues, significantly improving the efficiency and accuracy of fault diagnosis, shortening manual processing time, and enhancing the overall evaluation efficiency of the manufacturing and assembly process. Furthermore, this invention can not only predict the specific impact of problems on the performance of resonant cavity operating modes but also provide targeted repair suggestions (such as adjusting assembly tilt angles or repairing gaps), improving the performance consistency of resonant cavity products, reducing product deviations caused by assembly and processing errors, and providing strong support for high-precision resonant cavity manufacturing. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the high-precision deviation diagnosis method for resonant cavities based on multi-mode data analysis according to the present invention.

[0027] Figure 2 This is a schematic diagram of the resonant cavity structure in the embodiment.

[0028] Figure 3 This is a dimensioned diagram of the resonant cavity in the embodiment.

[0029] Figure 4 The simulation S-parameters are for the ideal model of the resonant cavity.

[0030] Figure 5 The images shown are actual photos of the tilted assembly in typical test example 3, and the corrected actual photos.

[0031] Figure 6 The measured S-parameters of typical test example 3 and the S-parameters of the matched error model are shown.

[0032] Explanation of reference numerals in the attached drawings: 1. Outer shell, 2. Cable groove, 3. Rectangular coupling cavity, 4. Electron injection channel, 5. Output port. Detailed Implementation

[0033] To more clearly demonstrate the technical solutions and advantages, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0034] This embodiment provides a high-precision deviation diagnosis method for resonant cavities based on multi-mode data analysis, such as... Figure 1 As shown, it includes the following steps:

[0035] S1. Construct a physical deviation-resonance feature dataset;

[0036] For example Figures 2-3 Taking the resonant cavity model operating in the W band (75-110GHz) as an example, the resonant cavity is assembled from two symmetrical components, including: a shell, an electron beam channel inside the shell, several parallel grooves perpendicular to the electron beam channel on the upper and lower sides of the shell, rectangular coupling cavities at both ends of the grooves, and an output port outside the rectangular coupling cavities.

[0037] In actual manufacturing and assembly, the resonant cavity is composed of multiple components. Due to manufacturing and assembly errors, the structural parameters may deviate from the ideal simulation model. Therefore, manufacturing and assembly errors, such as gap tolerance, dislocation deviation, and rotation angle, must be considered during data acquisition.

[0038] In this embodiment, the important geometric dimensions and assembly parameters are shown in the table below:

[0039] Table 1. Important geometric dimensions and assembly parameters

[0040] symbol Symbol meaning Specific value / mm TX width of the electron channel 7.5 TY height of electronic channel 0.64 P Cycle of cable tray 1.19 LG Length of the cable tray 0.46 HG Height of cable tray 1.8 WC Width of coupling cavity 0.83 HC Height of the coupling cavity 2.15 LC Length of coupling cavity 4.8 DY Assembly gap deviation 0 (ideal value) DX, DZ dislocation deviation in assembly 0 (ideal value) THETA Assembly rotation angle 0 (ideal value)

[0041] An ideal simulation model of the resonant cavity was built in the commercial electromagnetic simulation software CST Studio Suite, and S-parameters were extracted. Based on the S-parameters, the frequency and return loss data of each resonant mode were calculated, denoted as F. 0 , Where the superscript 0 indicates an ideal model, f j Let A represent the ideal frequency of the j-th mode. j This represents the return loss of the j-th mode.

[0042] Several error models were obtained by gradually changing a certain parameter (geometric dimensions and assembly parameters) using the controlled variable method, and the corresponding S-parameters of the error models were extracted. Then, based on the S-parameters of the error models, the frequency and return loss data of each resonant mode were calculated, denoted as F. s , The superscript 's' represents the sequence number of the error model; thus, the simulation dataset is obtained.

[0043] In this embodiment, the height error range of the resonant cavity is 0.001-0.01 mm, with a step size of 0.001 mm. The error ranges of the gap width, cavity spacing, and side cavity width are 0.002–0.02 mm, with a step size of 0.002 mm. The tilt angle error range between the two half cavities is 0–2°, with a step size of 0.2°. Other errors are similar and set based on engineering experience, and will not be elaborated here. Furthermore, preliminary controlled variable method simulation screening revealed that the cavity height of this embodiment has the greatest impact on the modal frequency, with a sensitivity of 52 GHz / mm for the operating mode. The influence of the cavity lateral dimensions is relatively small, with a sensitivity of only 2 GHz / mm for the operating mode. Therefore, a smaller error step size is used for the former when establishing the error model.

[0044] The cavity was machined using high-precision computer numerical control (CNC) technology. Through precision control, the maximum machining deviation was ±0.002 mm, and the assembly accuracy between cavities reached 0.01 mm. 1° represents the maximum permissible deviation that may occur during the actual assembly of the cavity. The error model constructed using the above method covers the vast majority of actual process variations.

[0045] The S-parameters of the ideal simulation model are used to perform feature optimization on each simulation data in the simulation dataset, and a database is constructed based on the optimized simulation data.

[0046] The feature optimization method is as follows: within the testable range of 75 GHz to 110 GHz, the S-parameters contain a total of 7 resonant modes; for matched mode pairs (e.g., f1... s f1 0 The frequency corresponding to the resonant mode of the ideal simulation model. Return loss As reference data, the frequencies corresponding to each resonant mode are extracted from the S-parameters of the simulation data. Return loss And normalization is performed based on the reference data: , ,in It is the deviation of the frequency from the ideal frequency. The deviation between return loss and ideal return loss.

[0047] The formula for return loss is: Among them, among them, Indicates the first Return loss values ​​(in dB) for each resonant mode. This represents the scattering parameter value at that frequency point.

[0048] To eliminate the influence of single-mode random errors, this invention further extracts the statistical characteristics of mode deviation across the entire frequency band, using the mean and variance of frequency deviation as frequency feature data and the mean and variance of return loss deviation as return loss feature data, and uses these as data to construct the database.

[0049] The formulas for calculating the mean and standard deviation of the resonant mode frequency deviation are as follows:

[0050]

[0051]

[0052] Mean frequency deviation The standard deviation StdDev reflects the impact of the uniformity deviation of the cavity size on the resonant frequency, and reflects the difference in the sensitivity of different resonant modes to errors.

[0053] The mean and variance of the return loss deviation are calculated in the same way as for the frequency, so they will not be repeated here.

[0054] S2. Obtain the resonance characteristics of the device under test;

[0055] The S-parameters of the resonant cavity under test are measured, and the frequencies and return losses corresponding to each resonant mode are extracted from the S-parameters. The data are then normalized based on reference data, and the frequency characteristic data and return loss characteristic data of the resonant cavity under test are extracted, thereby forming the resonant characteristics that can characterize the state of the device under test.

[0056] S3. Perform feature matching;

[0057] The resonance characteristics of the device under test (DUT) are pattern matched with the database established in S1 to obtain a set of simulation data that best matches the resonance characteristics of the DUT; the geometric dimensions and assembly parameters in the simulation data are used as the geometric dimensions and assembly parameters of the DUT.

[0058] To reflect the importance of each resonant mode in the overall performance and to balance the contributions of different physical quantities, different weights are assigned to each mode, with weighting coefficients... The middle working mode has the highest weight, while the secondary working mode has a lower weight than the working mode.

[0059] The feature matching score D is then defined using the following formula:

[0060]

[0061] in, The deviation of the resonant frequency between the device under test and the database sample in the i-th mode is given. The ideal frequency for the i-th mode; Let i be the return loss deviation in each mode. This represents the ideal value for return loss; and The weighting coefficients for the frequency and return loss of the i modes.

[0062] The smaller the frequency feature matching score D, the higher the degree of fit between the device under test (DUT) and the samples in the database. Through this matching process, the error model that best matches the features of the DUT is identified.

[0063] S4. Complete the deviation attribution;

[0064] Based on the best-matching error model obtained in step S3, the nature, location, and severity of existing processing or assembly problems are determined, and a deviation diagnosis report is output. This allows the observed resonance characteristics to be attributed to one or more specific physical deviations (such as assembly gaps, cavity size changes, assembly tilt, etc.), providing guidance for subsequent process corrections or assembly adjustments.

[0065] Optionally, defects in the device under test can be predicted based on the resonance characteristics of the device under test.

[0066] 1. An abnormal increase in the number of modes: This indicates that the mode was not activated and there is a missing modeling defect. This is likely due to assembly tilt or rotational asymmetry.

[0067] 2. Only a few modes show irregular upward shift and a sharp deterioration in return loss: This is judged to be due to a localized reduction in size;

[0068] 3. Consistent downward shift across the entire frequency range with a small standard deviation: This indicates an increase in the height of the resonant cavity or gaps in the assembly.

[0069] 4. Significant frequency shift in high-order modes, slight shift in operating modes: This is judged to be due to assembly tilt or rotational asymmetry;

[0070] 5. If the frequency variation of all modes is less than the given value, and there are no abnormally increasing resonant modes, the manufacturing and assembly are considered to be within the allowable range. In this implementation case, 100 MHz is set as the standard.

[0071] In this implementation case, the provided attribution results are mainly used to identify possible types and locations of deviations, enabling rapid localization.

[0072] The following are three representative diagnostic cases, corresponding to three common problems: assembly gaps, local dimensional deviations, and assembly tilt. In each case, the system outputs the possible deviation types through multi-modal feature matching.

[0073] Typical example 1: There are gaps between the cavities.

[0074] Measurements were taken of component 1 under test, and the results showed that the frequencies of all designed resonant modes shifted downwards compared to the ideal model, with a small standard deviation of the deviation, and the number of mode excitations remained unchanged. Feature matching was performed on the component under test using the aforementioned method, and the corresponding error model was the case of an increase in the overall cavity height or an assembly gap between the upper and lower cavities. Further experimental verification revealed a small gap at the junction of the upper and lower cavities. After adjustment and re-measurement, all frequency deviations were reduced to within the design values.

[0075] Typical Example 2: The size of the side cavity is reduced.

[0076] Measurement results showed that only a specific high-order mode experienced a significant frequency shift, while other master modes remained stable, indicating that the structural deviation had regional characteristics. According to error model matching in the database, this phenomenon was consistent with the geometric shrinkage of the side cavities. Inspection revealed that solder infiltration into the side cavities during the welding process caused a reduction in effective size. This mode existed only in the side cavities, hence the most significant frequency change. After changing the welding process, the frequency of this mode recovered, while other modes showed no significant changes, making the attribution and repair logic clear.

[0077] Typical Example 3: Assembly tilt leads to the triggering of error modes.

[0078] In one measurement sample, due to adjustments in the mounting method, in addition to an overall frequency drift in all design modes, several non-design modes were observed to be excited, resulting in new troughs in the return loss curve. Based on comparative analysis of error models, it was inferred that this abnormal response originated from structural tilting during cavity assembly, and the closest error model was identified. Further disassembly and verification revealed uneven contact between the upper and lower cavity surfaces, with a noticeable gap visible on one side of the port, while the other side was free of gaps. After correcting the mounting method, reassembling, and measuring, the gap disappeared, the corresponding S-parameter curve returned to normal, and the erroneously excited modes were effectively suppressed.

Claims

1. A high-precision deviation diagnosis method for resonant cavities based on multi-mode data analysis, characterized in that, Includes the following steps: S1. Construct a physical deviation-resonance feature dataset; An ideal simulation model of the resonant cavity is established through software simulation; the geometric dimensions and assembly parameters of the ideal simulation model are changed multiple times to obtain the S-parameters corresponding to error models with different structural parameters, and the simulation dataset is obtained. The S-parameters of the ideal simulation model are used to perform feature optimization on each piece of simulation data in the simulation dataset, and a database is constructed based on the optimized simulation data. S2. Obtain the resonance characteristics of the device under test; S-parameters are measured on the resonant cavity under test. The frequencies and return losses corresponding to each resonant mode in the S-parameters are extracted and normalized based on the reference data to obtain the frequency characteristic data and return loss characteristic data of the resonant cavity under test, thereby forming the resonant characteristics that can characterize the state of the device under test. S3. Perform feature matching; The resonance characteristics of the device under test are matched with the database established in S1 to obtain a set of simulation data that best matches the resonance characteristics of the device under test. The geometric dimensions and assembly parameters in the simulation data are used as the geometric dimensions and assembly parameters of the part under test. S4. Complete the deviation attribution; Based on the geometric dimensions and assembly parameters of the test part obtained in step S3, the nature, location, and severity of existing machining or assembly problems are determined, and a deviation diagnosis report is output.

2. The high-precision deviation diagnosis method for resonant cavities based on multi-mode data analysis as described in claim 1, characterized in that, In step S1, the feature optimization method is as follows: the S-parameters contain multiple resonant modes; the frequency and return loss corresponding to each resonant mode in the S-parameters of the ideal simulation model are used as reference data, the frequency and return loss corresponding to each resonant mode in the simulation data S-parameters are extracted, and normalization is performed based on the reference data to obtain frequency feature data and return loss feature data.

3. The high-precision deviation diagnosis method for resonant cavities based on multi-mode data analysis as described in claim 2, characterized in that, In step S3, the pattern matching method is as follows: First, the primary and secondary modes are determined based on the operating mode of the resonant cavity, and different weights are assigned to each mode. Then, the frequency deviation and return loss deviation between the resonant cavity under test and each mode in the database are extracted, and the weighted deviation results are used as the matching index.

4. The high-precision deviation diagnosis method for resonant cavities based on multi-mode data analysis as described in claim 3, characterized in that, During the pattern matching process, the electromagnetic field distribution characteristics and quality factors recorded in the database are combined to perform pattern recognition on each resonance peak to ensure that different modes correspond, so as to obtain a set of simulation data that best matches the resonance characteristics of the device under test.

5. The high-precision deviation diagnosis method for resonant cavities based on multi-mode data analysis as described in claim 4, characterized in that, Several resonant cavities were fabricated based on an ideal simulation model. Their geometric dimensions and assembly parameters were measured, and the S-parameters were obtained. The data of each resonant cavity were entered into the database to supplement the actual fabrication deviation data.

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