SMA connector model signal integrity simulation method
By collecting measured data to establish a baseline model and performing connection degradation index grading and model self-calibration, the problem of unstable signal integrity assessment caused by state changes of SMA connectors was solved, achieving stability and consistency of signal integrity simulation and reducing misjudgment and retesting costs.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SHENZHEN HUARUIDE PRECISION TECH CO LTD
- Filing Date
- 2026-01-16
- Publication Date
- 2026-04-28
AI Technical Summary
Existing technologies cannot effectively address changes in the contact state of SMA connectors caused by factors such as frequent tightening and unplugging, differences in tightening torque, lateral cable pulling, interface contamination, and plating wear when assessing signal integrity. This makes it difficult for simulation curves to remain consistent with measured curves, increasing the uncertainty of retesting and maintenance decisions.
By collecting measured scattering parameter data, a nominal simulation baseline model is established, a comprehensive connectivity degradation index is constructed, the model is self-calibrated, an instantiated connectivity state model is formed, and signal integrity simulation is performed in a closed-loop process. The results are then output as judgment conclusions and handling suggestions to reduce the incomparability between simulation and actual measurements caused by state drift.
This achieves stability and consistency in signal integrity assessment of SMA connectors under long-term use scenarios, reduces the time cost of misjudgment and retesting, and improves the repeatability and reliability of signal integrity simulation.
Smart Images
Figure CN121936151A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of signal simulation technology, and more specifically, to a method for simulating the signal integrity of an SMA connector model. Background Technology
[0002] Signal integrity simulation is mainly used for continuity modeling of reflection, loss and impedance on high-speed or high-frequency interconnect links. It is used to predict risks in advance during R&D integration and production line testing, and to quickly find mismatch locations during testing. It is commonly used in high-speed interconnects, RF measurement fixtures, automated test fixtures, etc. SMA connectors have a standard interface and are easy to assemble. They are generally used for high-frequency connections between fixture ports and coaxial cables, and are also used in conjunction with vector network analyzers for scattering parameter evaluation.
[0003] The existing technology has the following shortcomings: Previous signal integrity assessments of SMA connectors often employed simulation models based on nominal geometry and ideal contact assumptions, using single or limited measured curves as a reference. However, in actual tooling use, frequent tightening and untightening, differences in tightening torque, lateral cable pulling, interface contamination, and plating wear can alter the contact state of the connection interface. Furthermore, changes in the reference surface, adapter, and cable assembly during measurement can introduce additional variations. The combined effect of these factors causes S-parameters at the same port location to drift at different times, making it difficult to maintain comparability and consistency between simulated and measured curves. This leads to unstable judgments regarding reflection spikes, return loss margins, and mismatch attribution, increasing the uncertainty of retesting and maintenance decisions.
[0004] To address the above problems, this invention proposes a solution. Summary of the Invention
[0005] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide a signal integrity simulation method for SMA connector models to address the problems raised in the background art.
[0006] To achieve the above objectives, the present invention provides the following technical solution: The SMA connector model signal integrity simulation method includes the following steps: Step 1, establish baseline by connecting sampling: For the fixture port position configured with SMA connector, collect the measured scattering parameter data and assembly status data of the corresponding connection link at the current sampling time to form a port connection status sample package; and establish a nominal simulation baseline model of SMA connector to obtain the simulation scattering parameters corresponding to the preset interest frequency band under the nominal state. Step 2, Degradation Index Classification: Based on the measured scattering parameters and cumulative insertion / removal times in the port connection status sample packet, a comprehensive connection degradation index characterizing the degree of connection interface degradation is constructed, and the connection status is classified according to a preset threshold. Step 3, Reliable Calibration Feedback: Determine whether to enter the model calibration process based on the comprehensive index and grading results of the connection degradation; when entering the model calibration process, obtain the equivalent contact parameters characterizing the contact interface state of the SMA connector through parameter inversion, and integrate and construct the model self-calibration reliability; when the model self-calibration reliability is not lower than the preset reliability threshold, feedback the equivalent contact parameters into the simulation model to form an instantiated connection state model, and generate a model version identifier; Step 4, Integrity Judgment Closed Loop: Combining the comprehensive index of connection degradation and the model self-calibration reliability, a choice is made between the nominal simulation baseline model and the instantiated connection state model to perform signal integrity simulation. The simulation results are compared with the preset signal integrity judgment threshold, and the signal integrity judgment conclusion and corresponding handling suggestions for the current fixture port position are output. The judgment conclusion, handling action and handling result are recorded in the port position file to complete the closed loop process from state quantification, model update to handling verification.
[0007] In a preferred embodiment, in step one, the port connection status sample packet includes at least the port number, cable number, cumulative number of plugging and unplugging, and the measured amplitude of the reflection parameter and the measured amplitude of the transmission parameter of the preset focus frequency band.
[0008] In a preferred embodiment, the baseline value used to calculate the degradation amount in step two is the baseline return loss and baseline insertion loss obtained by collecting measured data in a stable state after establishing or maintaining the baseline at the fixture port position, and then binding and solidifying them with the port position number as baseline data.
[0009] In a preferred embodiment, step two, constructing the comprehensive connectivity degradation index, includes: calculating the current return loss and current insertion loss based on the measured amplitude of the reflection parameter and the measured amplitude of the transmission parameter; calculating the degradation of the current return loss and current insertion loss relative to the baseline return loss and baseline insertion loss; normalizing and weighting the degradation amount and the cumulative number of insertions / removals to obtain the comprehensive connectivity degradation index.
[0010] In a preferred embodiment, step two classifies the connection state according to a first threshold and a second threshold, including: when the comprehensive connection degradation index is not greater than the first threshold, it is determined to be a stable state; when the comprehensive connection degradation index is greater than the first threshold but not greater than the second threshold, it is determined to be a reversible degradation state; when the comprehensive connection degradation index is greater than the second threshold, it is determined to be a significant degradation state.
[0011] In a preferred embodiment, in step three, when the connection state is determined to be a stable state or a reversible degradation state, the model calibration process is initiated; the equivalent contact parameters include at least contact resistance and micro-gap capacitance.
[0012] In a preferred embodiment, the model self-calibration reliability is constructed by fusing the fitting residual, repeatability consistency, and physical feasibility factor; wherein the fitting residual is used to characterize the consistency deviation between the measured scattering parameters and the simulated scattering parameters, the repeatability consistency is used to characterize the reproducibility of the measured scattering parameters, and the physical feasibility factor is used to characterize whether the equivalent contact parameters are within the engineering feasible range.
[0013] In a preferred embodiment, the equivalent contact parameters obtained by inversion are fed back into the simulation model only when the model self-calibration confidence level is not lower than the confidence level threshold, forming an instantiated connection state model, and generating a model version identifier associated with the port number and cable number and writing it into the port file.
[0014] In a preferred embodiment, in step four, when the degradation is determined to be recoverable, a reinstallation or cleaning suggestion is output, and steps one to three are re-executed after the treatment to verify the restoration of the state; when the degradation is determined to be significant, a suggestion to replace the port or the connector is output, and the baseline is rebuilt after the replacement.
[0015] In a preferred embodiment, the data updated to the port file is used to support subsequent signal integrity simulations of the same fixture port, including recalling historical baseline data and reusable instantiated connection state models.
[0016] The technical effects and advantages of this invention are as follows: This invention focuses on the long-term use scenarios of fixture port positions, integrating measured scattering parameter data, simulation models, and handling verification into a traceable closed-loop process: by uniformly encapsulating the measured scattering parameter data and assembly status data of the fixture port positions at the sampling time to form a port position connection status sample package, and establishing a nominal simulation baseline model aligned with the preset focus frequency band, the evaluation of the same port position at different times has a stable reference, reducing the incomparability between simulation and actual measurement caused by port position status drift, and improving the repeatability and consistency of signal integrity simulation from the source.
[0017] Based on this, the present invention quantifies the reflection and transmission performance within the focus frequency band and the cumulative number of plug-in / plug-out cycles into a comprehensive connection degradation index, and classifies the connection status according to the first threshold and the second threshold, so that the degree of connection interface degradation is transformed from empirical judgment by curves to index-based judgment, thereby enabling more stable identification of stable state, recoverable degradation state and significant degradation state in engineering, reducing misjudgment and retesting caused by fluctuations in a single measurement.
[0018] Furthermore, this invention employs a trusted calibration refeed mode. Under gated conditions, the equivalent contact parameters of the SMA connector contact interface state are obtained through parameter inversion. The equivalent contact parameters should at least include contact resistance and micro-gap capacitance. Then, the two are combined to construct the model self-calibration credibility. Only after the model self-calibration credibility reaches the credibility threshold is the equivalent contact parameters fed back to the simulation model to generate an instantiated connection state model. At the same time, the model version identifier associated with the port number and cable number is written into the port file. The model update is set to have a trusted gate, which avoids unstable measurement or abnormal assembly state from being solidified into an erroneous model, reduces the risk of calibration drift and erroneous refeedback, and enhances the model's reusability and traceability.
[0019] Finally, this invention integrates the comprehensive connectivity degradation index and the model self-calibration reliability in the integrity determination closed loop. It selects between the nominal simulation baseline model and the instantiated connectivity state model to perform signal integrity simulation, compares the simulation results with a preset signal integrity determination threshold, and outputs a signal integrity determination conclusion and handling suggestions for the current fixture port. When the degradation is determined to be recoverable, it provides a reinstallation or cleaning suggestion and re-executes steps one through three after the action to verify the state recovery. When the degradation is determined to be significant, it provides a suggestion to replace the port or connector, rebuilds the baseline after the replacement, and records the determination conclusion, handling action, and handling result in the port file. This forms a closed loop of state quantification, model updating, handling verification, and file storage, improving the stability of signal integrity determination and the consistency of maintenance decisions, and reducing the time cost and uncertainty caused by repeated retesting and maintenance trial and error. Attached Figure Description
[0020] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings; Figure 1 This is a flowchart illustrating the signal integrity simulation method for the SMA connector model of the present invention. Figure 2 This is a schematic diagram of the reliable calibration and recharge process of the present invention. Detailed Implementation
[0021] The technical solutions of 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 some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0022] Example 1: The signal integrity simulation method for the SMA connector model of the present invention, as follows... Figure 1 As shown, it includes the following steps: Step 1: Connect samples and establish baselines; In this embodiment, the application scenario is an automated production line test fixture or laboratory debugging. The fixture port is equipped with an SMA connector to establish a repeatable high-frequency connection between the coaxial cable and the port of the object under test. In this scenario, during long-term repeated tightening and unplugging, the SMA connector is prone to changes in the contact state of the connection interface due to factors such as differences in operator tightening methods, lateral pulling of the cable, interface surface contamination, and plating wear. This causes a gradual drift in return loss and insertion loss, resulting in inconsistent measurement results for the same link at different times. To ensure that the subsequent simulation model can reflect this type of change with usage conditions, this step first defines the SMA connector at the fixture port, the coaxial cable, and the port under test as the evaluation objects of the connection link. The measurement data and assembly status data of this connection link at time t are then uniformly collected and packaged to form a traceable port connection status sample package.
[0023] Specifically, the input for this step should include at least the port number, cable number, model information of the SMA connector used, and the cumulative number of mating / unmating cycles since the port was documented or the last cleaning or replacement event. The cumulative number of insertions and removals characterizes the service life stage of the port and can be recorded by a fixture management system, workstation barcode scanning process, or manual confirmation, and automatically accumulated with each insertion and removal. In addition to service life information, this step also collects frequency domain scattering parameter data of the connection link. Preferably, a vector network analyzer is used to perform frequency sweep measurements on the two-port network within a preset frequency band of interest to obtain the reflection parameter amplitude of the connection link at time t. With transmission parameter amplitude Where f represents the sweep frequency point, and t represents the sampling time. Used to characterize the reflection properties of the aperture at time t. This is used to characterize the transmission characteristics of the port at time t. To ensure comparability between different batches of measurements, this embodiment imposes consistency constraints on the measurement configuration in step one: that is, fixing the reference plane definition, fixing the start and end frequencies and frequency density of the sweep, fixing the port impedance setting, and keeping the adapter and cable combination unchanged as much as possible; when the cable or adapter must be replaced in the field, the replacement event is bound and recorded with the port number to avoid misinterpreting the configuration change as a change in connection status. Through the above constraints, the measurement obtained in this step... and It can be regarded as comparable data under the same reference plane and the same test conditions, providing a stable input for the calculation of subsequent comprehensive analysis points.
[0024] While completing the measured data acquisition, this step establishes a nominal simulation baseline model on the simulation side to provide a starting reference for subsequent model self-calibration. The nominal simulation baseline model can be implemented using a three-dimensional electromagnetic model or an equivalent network model. Its modeling objects include the nominal geometry and material properties of the SMA connector and a coaxial termination structure connected to it. The model port is set to 50Ω according to the system characteristic impedance, and the connection interface is assumed to be an ideal continuous contact under the nominal state to obtain the simulated scattering parameters output under this nominal state. and .in, , The simulation results of the nominal simulation baseline model at frequency f are shown. By obtaining the measured S-parameter curves and the nominal simulation curves in parallel within the same frequency band of interest, this step provides a benchmark and alignment basis for the calculation of the connectivity degradation comprehensive index in step two and the calculation of the model self-calibration credibility in step three.
[0025] The output of this step is a port connection status sample packet and a nominal simulation baseline model. The port connection status sample packet should at least include the port, cable, and cumulative insertion / removal count. within the frequency band of concern and With nominal simulation baseline model and output , This step's output, under conditions of data traceability and comparable test conditions, transforms the connection interface assembly and lifespan variations into calculable comprehensive information, thereby driving the simulation model's self-calibration and closed-loop processing.
[0026] Step 2: Degradation index classification; In this embodiment, step two is used to quantify the measured S-parameters and cumulative insertion / removal counts in the port connection status sample packet collected in step one into a comprehensive quantity that can directly reflect the degree of degradation of the connection interface. This allows for the identification of the degradation trend of the SMA connector at the fixture port during repeated tightening and loosening without relying on human experience, and provides a basis for subsequent model self-calibration and for determining whether to perform reassembly, cleaning, or replacement. The processing object of this step is the port connection status sample packet output from step one, and the input includes the frequency band of interest. Internal reflection parameter amplitude Transmission parameter amplitude and cumulative number of plug-in / plug-out times Where B is the preset frequency band of interest. and These are the start and end frequencies of the frequency band of interest. This represents the cumulative number of insertions and removals at cutoff time t. To ensure the engineering comparability of the calculation results, this embodiment preferably requires that the input data come from measurement results under the same reference plane definition and the same frequency sweep setting.
[0027] To transform frequency-domain scattering parameters into a loss characterization that can be directly understood in engineering, this step first is based on Calculate return loss and based on Calculate insertion loss Return loss reflects the severity of reflections at the connection interface, while insertion loss reflects the degree of signal attenuation caused by the connection link. The return loss is characterized using the worst-case scenario within the frequency band of interest to ensure sensitivity to local reflection spikes; insertion loss The average insertion loss within the frequency band of interest is used to characterize the signal, thereby improving robustness to noise and single-point fluctuations. Return loss and insertion loss can be calculated as follows: , ; In the above formula, Logarithmic operations to base 10; This means taking the minimum value for all frequency points within the frequency band of interest B; This indicates that the average value is taken for all frequency points within the band of interest B; The return loss (in dB) is calculated from the amplitude of the reflection coefficient. Insertion loss (in dB) is calculated from the amplitude of the transmission coefficient.
[0028] To characterize the degree of degradation relative to the baseline, this embodiment, at the initial stage of port location documentation or after a confirmed stable reassembly or cleaning and successful retesting, solidifies the corresponding measured return loss and insertion loss as the baseline return loss. Compared with baseline insertion loss At any subsequent time t, the system is based on the current... , Degradation amount calculated with baseline amount and : , ; in, This indicates the reduction in return loss relative to the baseline (dB) as reflection increases. Decrease, thus Increase; This indicates the magnitude (dB) of the increase in insertion loss relative to the baseline, as the loss increases. Rise, and thus Increase.
[0029] Considering the different dimensions and scales of the three input quantities, this embodiment... , and Normalize them separately to obtain , , ,in This is a normalization function that maps the input to the interval [0,1]. Preferably, the normalization function adopts a linear clipping form based on an engineering threshold: ; Where x is the input quantity to be normalized, which can correspond to , or ; and These are the empirical lower and upper bounds for the quantity under negligible and significant degradation states, respectively. Specifically, for SMA connectors in a 50Ω system, the following can be set: of , ; of , ; of 0 times, These boundary values can be calibrated during system deployment based on the specific connector specifications and manufacturing capabilities.
[0030] After completing the value calculation and normalization, this embodiment constructs and calculates the comprehensive connectivity degradation index. This is used to fuse three types of information—return loss degradation, insertion loss degradation, and aperture lifetime stage—into a single value: ; in, This is a weighting coefficient used to balance the contributions of the three types of information. When historical data is unavailable, initial values can be set based on engineering experience. For example, in high-frequency testing scenarios that emphasize reflection performance, a weighting coefficient can be set. , , And update it in the subsequent closed loop.
[0031] based on The system is based on the first threshold. With the second threshold Output degradation grading results: when The connection is determined to be stable at a certain time; when When the degradation is determined to be reversible, reinstallation or cleaning is preferred, followed by retesting; when If significant degradation is detected, it is preferable to trigger a port replacement or connector replacement and baseline reconstruction. The output of this step includes... The composition and degradation grading results provide a preliminary basis for the model self-calibration gating in step three.
[0032] Step 3: Reliable calibration re-feedback; In this embodiment, step three, based on the degradation quantification and degradation classification completed in step two, introduces the influence of the port connection state changing with tightening state and service life evolution into the simulation model. This upgrades the simulation model from a nominal state to an instantiated connection state model that can reflect the current connection state, thereby reducing the risk of long-term inconsistency between simulation and actual measurement. Figure 2 As shown, the processing objects in this step include the nominal simulation baseline model established in step one and the port connection status sample packets collected in step one. The input includes at least the frequency band of interest. Actual measurement inside , With nominal simulation output , And combined with the output of step two The degradation grading results determine whether to proceed with the calibration process. Preferably, when... Exceeding the threshold The system does not enter model self-calibration but directly enters the processing procedure; when The system then enters the model self-calibration process.
[0033] After entering the model calibration process, the changes in the SMA connector contact interface are abstracted into a small set of variable equivalent contact parameters. These parameters represent the high-frequency discontinuous changes caused by tightening differences, contamination, and wear, without affecting the nominal geometric model. The optimal set of equivalent contact parameters includes at least the contact resistance. and micro-gap capacitance Contact resistance Micro-gap capacitance is used to characterize the weakening of the conductivity at the contact interface. Used to characterize equivalent coupling caused by minute gaps or insufficient contact at the contact interface, searching within the feasible range. and The value is chosen to make the fitting residual Minimum. The search process can be implemented using optimization algorithms, such as in a two-dimensional parameter space. Perform a grid search, traverse the discrete parameter combinations, and select the one that makes the parameter combination the most suitable. smallest and The value is used as the inversion result.
[0034] To express the degree of consistency as a single scalar, this embodiment constructs the fitting residuals. And the differences in return loss and insertion loss are fused within the frequency band: ; in, Indicates by actual measurement The calculated return loss (dB) Indicates by actual measurement The calculated insertion loss (dB); and They represent the given and Return loss and insertion loss calculated by the model under parameter conditions; This means averaging all frequency points within the band of interest (B). This is a tradeoff coefficient used to balance the contributions of the return loss difference term and the insertion loss difference term. The system minimizes this coefficient. Inversion yields the value corresponding to the current time t. and The model is then fed back into the simulation model to form an instantiated connection state model. During the feedback, the three-dimensional electromagnetic model can be implemented through equivalent boundary conditions at the contact interface or equivalent thin / gap layers, and the equivalent network model can be implemented through a combination network of series resistance and parallel capacitance at the port transition, so that the model output can reflect the impact of the current port assembly and lifetime state on reflection and loss.
[0035] To prevent erroneous backfeedback due to measurement instability or the inversion results lacking physical feasibility, this embodiment calculates the model self-calibration reliability in step three. And this confidence level is used as the model refeeding gating value. From the fitting residual Repeatability consistency With physical feasibility factor Together they constitute the whole. Repeatability consistency describes the reproducibility of measurement curves under the same measurement configuration, and is preferably obtained through the correlation coefficient of the return loss curves of two consecutive measurements:
[0036] in, The curve representing the return loss as a function of frequency obtained from the k-th measurement is shown. This represents the curve that was immediately preceding the previous measurement. and These are the arithmetic mean of the two curves within the band of interest B. The closer the Pearson correlation coefficient is to 1, the better the measurement repeatability.
[0037] Physical feasibility factors are used to constrain inversion. and Within the scope of feasible engineering projects, it can be defined by gating method: ; in, For the engineering-feasible range of contact resistance, This represents the engineering-feasible range for micro-gap capacitance. As an example, for a typical gold-plated SMA connector, the feasible range for preset contact resistance can be determined based on its material properties and assembly physical constraints. The feasible range for micro-gap capacitors is: These ranges can be adjusted based on specific connector models, historical calibration sample statistics, or more stringent process constraints.
[0038] Based on the above three quantities, the model self-calibration confidence is calculated and retained according to the following formula: ; in, It is an exponential function. The scaling factor is used to scale the fit residuals. This is mapped to the degree of confidence decay; as an example, it can be set according to the typical magnitude of the fitted residuals. ;when Smaller Close to 1 and hour, The closer the result is to 1, the more reliable the model's self-calibration results are.
[0039] This step is based on the calculation. Then, by threshold Gating the model refeedback. When At that time, the system allows the inverted results to be used for... and The parameters are solidified into instantiated connection state model parameters, and a model version identifier is generated. This model version identifier is associated with the port number, cable number, sampling time t, and calibration error statistics and archived for subsequent traceability and reuse. When the system determines that the current data is insufficient to drive a model update, it preferentially outputs a suggestion for reassembly or cleaning followed by retesting, and keeps the simulation model from being updated to avoid solidifying unstable measurements or abnormal assembly states into an erroneous model. The output of this step is... It also includes the support quantity, the instantiated connection state model and model version identifier formed when the credibility meets the standard, or the output of the gated conclusion of rejecting backfeeding and the retesting requirements when the credibility does not meet the standard, thereby providing a reliable model basis for the signal integrity judgment and handling closed loop in step four.
[0040] Step 4: Integrity assessment and closure; In this embodiment, step four is used to connect the degradation composite index. and model self-calibration credibility As the result of engineering judgment and handling execution, this ensures the quantification of port connection status degradation, reliable updates to the simulation model, and on-site handling cycles, maintaining consistent signal integrity assessment and reducing misjudgments and retesting under real assembly and life evolution environments. This step processes the current port judgment status, model status, and handling execution results, and inputs... , First threshold Second threshold , Frequency bands to watch And the signal integrity requirements within this frequency band. Among them, the threshold value... , , Pre-settings are required based on the system's stability, sensitivity, and risk control requirements. As an initial setting, a degradation grading threshold is connected. , Model self-calibration confidence threshold It can be iteratively optimized based on statistical analysis of a large number of historical judgment results during system operation; at the same time, the model state output in step three is input, that is, the instantiated connection state model ( And when recharge is allowed) or nominal simulation baseline model ( (or when no recharge is applied).
[0041] This step prioritizes... Determine whether the mouth position requires intervention to avoid using its measurement results in decision-making or further calibration when the mouth position has significantly degraded. When the system determines that the port is in a stable connection state, if at this time... Furthermore, since step three has generated an instantiated connection state model, the system preferentially uses this model as the simulation basis to calculate the simulated return loss and simulated insertion loss of the port in the frequency band of interest, and compares them with the index threshold to form a margin conclusion, thereby outputting a judgment report on whether the port meets or does not meet the signal integrity requirements; if If the instantiated model is not solidified, the system will maintain the nominal simulation baseline model unchanged and mark the port position as requiring retesting and confirmation. This requires re-acquiring a sample packet of port position connection status under the same reference plane and measurement configuration to improve measurement repeatability and... This achieves a calibrable threshold, thus avoiding misinterpreting random measurement fluctuations as position degradation or model bias.
[0042] when If the connection fails to meet the requirements, it indicates a risk of reversible degradation at the port. This risk typically includes port conditions achievable through on-site operations, such as insufficient tightening, minor contamination, or short-term unstable contact. The preferred implementation example outputs on-site recommendations for reassembly or cleaning. The subsequent retest serves as a closed-loop verification condition. After the reassembly is completed, step one needs to be repeated to collect a new port connection status sample package, and step two needs to be repeated to calculate the new connection status. To determine whether the price has fallen back; when Falling back to In the following case, re-execute step three to calculate the new... And only Only when the instantiated connection state model and the final simulation results are solidified are the recoverable degradation transformed into a stable and usable port state through a closed-loop process. This mechanism avoids misjudgments caused by short-term fluctuations due to assembly differences, reducing the cost of repeated testing and disputes.
[0043] when When the system determines that a port position is at risk of degradation, typically due to plating wear, irreversible damage to the contact surface, or long-term contamination accumulation, further reassembly or cleaning to restore the port position has a low success rate and introduces significant testing uncertainty. This embodiment directly outputs a suggestion to replace the port position or connector, and triggers baseline reconstruction and reuse after replacement to ensure availability corresponds to the reference. After replacement, the replacement event is bound to the port position number and written into the port position file. Under the first stable measurement conditions after replacement, the new baseline return loss is solidified. Compared with baseline insertion loss At the same time, the cumulative number of plug-in / plug-out times will be recorded. Recount or mark a new lifespan starting point so that subsequent... The calculation has a correct reference, avoiding interference from the degradation history of the old mouth position on the determination of the new mouth position.
[0044] While completing the judgment and handling, this step will perform a closed-loop update of the simulation model, handling actions, and retest results, updating the data used for each judgment. , The threshold judgment result, the type and time of the handling action, the retest result after handling, and the final pass / fail conclusion are stored in the port file. When the instantiated connection state model can be solidified, the model version identifier is stored in the port file. When sampling the same port later, this model can be called as the initial value for simulation, reducing calibration iterations and consistency. When the retest after handling shows that the port has reached stability, the recovered measurement result can be stored in the new baseline quantity, that is, the baseline is always the reference value of the current usable state. Through the above recording and updating operations, this embodiment transforms the random fluctuations caused by assembly differences and life degradation into an engineering closed-loop process driven by comprehensive index and reliable gating quantity, thereby realizing the synchronization and consistency between the SMA connector signal integrity simulation results and the actual usage state, further improving the reliability of test judgment and reducing rework and retesting costs.
[0045] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.
[0046] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.
[0047] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.
[0048] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.
[0049] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.
Claims
1. A signal integrity simulation method for SMA connector models, characterized in that, Includes the following steps: Step 1, establish baseline by connecting sampling: For the fixture port position configured with SMA connector, collect the measured scattering parameter data and assembly status data of the corresponding connection link at the current sampling time to form a port connection status sample package; and establish a nominal simulation baseline model of SMA connector to obtain the simulation scattering parameters corresponding to the preset interest frequency band under the nominal state. Step 2, Degradation Index Classification: Based on the measured scattering parameters and cumulative insertion / removal times in the port connection status sample packet, a comprehensive connection degradation index characterizing the degree of connection interface degradation is constructed, and the connection status is classified according to a preset threshold. Step 3, Reliable Calibration Feedback: Determine whether to enter the model calibration process based on the comprehensive index and grading results of the connection degradation; when entering the model calibration process, obtain the equivalent contact parameters characterizing the contact interface state of the SMA connector through parameter inversion, and integrate and construct the model self-calibration reliability; when the model self-calibration reliability is not lower than the preset reliability threshold, feedback the equivalent contact parameters into the simulation model to form an instantiated connection state model, and generate a model version identifier; Step 4, Integrity Judgment Closed Loop: Combining the comprehensive index of connection degradation and the model self-calibration reliability, a choice is made between the nominal simulation baseline model and the instantiated connection state model to perform signal integrity simulation. The simulation results are compared with the preset signal integrity judgment threshold, and the signal integrity judgment conclusion and corresponding handling suggestions for the current fixture port position are output. The judgment conclusion, handling action and handling result are recorded in the port position file to complete the closed loop process from state quantification, model update to handling verification.
2. The SMA connector model signal integrity simulation method according to claim 1, characterized in that: In step one, the port connection status sample packet includes at least the port number, cable number, cumulative number of plugging and unplugging, and the measured amplitude of the reflection parameter and the measured amplitude of the transmission parameter of the preset focus frequency band.
3. The SMA connector model signal integrity simulation method according to claim 1, characterized in that: The baseline values used in step two to calculate the degradation amount are the baseline return loss and baseline insertion loss obtained by collecting measured data in a stable state after establishing or maintaining the baseline at the fixture port, and then binding them with the port number to solidify them as baseline data.
4. The SMA connector model signal integrity simulation method according to claim 1, characterized in that: In step two, constructing the comprehensive connectivity degradation index includes: calculating the current return loss and current insertion loss based on the measured amplitude of the reflection parameter and the measured amplitude of the transmission parameter; calculating the degradation of the current return loss and current insertion loss relative to the baseline return loss and baseline insertion loss; normalizing the degradation amount and the cumulative number of insertions and removals, and then weighting and fusing them to obtain the comprehensive connectivity degradation index.
5. The SMA connector model signal integrity simulation method according to claim 1, characterized in that: In step two, the connection status is classified according to the first threshold and the second threshold, including: when the comprehensive index of connection degradation is not greater than the first threshold, it is determined to be a stable state; when the comprehensive index of connection degradation is greater than the first threshold but not greater than the second threshold, it is determined to be a reversible degradation state; when the comprehensive index of connection degradation is greater than the second threshold, it is determined to be a significantly degraded state.
6. The SMA connector model signal integrity simulation method according to claim 5, characterized in that: In step three, when the connection state is determined to be a stable state or a reversible degradation state, the model calibration process begins; the equivalent contact parameters include at least contact resistance and micro-gap capacitance.
7. The SMA connector model signal integrity simulation method according to claim 6, characterized in that: The model self-calibration reliability is constructed by fusing the fitting residual, repeatability consistency, and physical feasibility factor. The fitting residual is used to characterize the consistency deviation between the measured scattering parameters and the simulated scattering parameters, the repeatability consistency is used to characterize the reproducibility of the measured scattering parameters, and the physical feasibility factor is used to characterize whether the equivalent contact parameters are within the engineering feasible range.
8. The SMA connector model signal integrity simulation method according to claim 7, characterized in that: Only when the model self-calibration confidence level is not lower than the confidence level threshold will the equivalent contact parameters obtained by inversion be fed back into the simulation model to form an instantiated connection state model, and a model version identifier associated with the port number and cable number will be generated and written to the port file.
9. The SMA connector model signal integrity simulation method according to claim 5, characterized in that: In step four, if the degradation is determined to be recoverable, a reinstallation or cleaning suggestion is output, and steps one to three are re-executed after the treatment to verify the restoration of the state; if the degradation is determined to be significant, a suggestion to replace the port or connector is output, and the baseline is rebuilt after the replacement.
10. The SMA connector model signal integrity simulation method according to claim 1, characterized in that: The data updated to the port file is used to support subsequent signal integrity simulations of the same fixture port, including calling historical baseline data and reusable instantiated connection state models.