A High-Speed I / O Connector High-Frequency Simulation Test Data Analysis Method and System

Abstract

The present invention relates to the field of I / O connector simulation testing, and is used to solve the problems of insufficient data processing during the simulation testing process, resulting in insufficient reliability of test results, and the lack of fuzzy processing ability, resulting in insufficient determination of the landing range of test results. Specifically, it is a method and system for high-speed I / O connector high-frequency simulation test data analysis. The present invention simultaneously conducts simulation testing through a dual-data-group comparison architecture of a test group and a constant group, quantifies the reference error based on the constant group according to the dual results of the test group and the constant group to obtain the data floating situation, and corrects the data of the test group according to the floating situation. When evaluating signal integrity, electromagnetic coupling, and time-domain characteristics, it can not only output accurate simulation test results, but also predict data drift based on the data after floating correction to predict the possible landing range of the simulation test results, improving the diversity and reliability of the output results.

Description

Technical Field

[0001] The present invention relates to the field of I / O connector simulation testing, and specifically to a data analysis method and system for high-frequency simulation testing of high-speed I / O connectors. Background Art

[0002] The performance of I / O connectors in high-frequency environments is crucial, especially in applications involving high-speed data transmission, such as servers, communication devices, or high-performance computing. High-frequency simulation testing of I / O connectors is a process of modeling, analyzing, and validating the performance of input / output (I / O) connectors in high-frequency signal transmission scenarios using electromagnetic field simulation tools. The core objective is to evaluate the signal integrity (SI), electromagnetic compatibility (EMC), and high-frequency characteristics of the connectors, such as impedance matching, crosstalk, and loss, to ensure their reliable operation in high-speed digital or radio frequency systems. Currently, commonly used electromagnetic simulation software includes ANSYS HFSS, CST Studio Suite, etc., all of which can analyze the transmission performance of I / O connectors.

[0003] Currently, the connector simulation testing in the prior art can model and analyze the performance of I / O connectors with the help of simulation testing software to obtain the connector performance. However, during the testing process, due to the variety of parameters, some special parameters will interfere with the simulation test results, causing the simulation test results to deviate from the actual situation. Moreover, the simulation testing in the prior art only outputs a fixed result, resulting in insufficient reliability of the simulation test results. At the same time, there is a lack of fuzzy processing ability for the test results, and it is impossible to locate the range of the test results under interference.

[0004] In view of the above technical problems, the present application proposes a solution. Summary of the Invention

[0005] The present invention independently performs parameter configuration and simultaneously conducts simulation testing through a dual-data group comparison architecture of a test group and a constant group. Based on the dual results of the test group and the constant group, benchmark error quantification is performed based on the constant group to obtain the data floating situation, and the data of the test group is corrected according to the floating situation. When evaluating signal integrity, electromagnetic coupling, and time-domain characteristics, not only can accurate simulation test results be output, but also data drift prediction can be performed based on the data after floating correction to predict the possible landing range of the simulation test results, improving the diversity and reliability of the output results, and solving the problems of insufficient data processing during the simulation testing process, resulting in insufficient reliability of the test results and lack of fuzzy processing ability, resulting in insufficient determination of the landing range of the test results. Thus, a data analysis method and system for high-frequency simulation testing of high-speed I / O connectors are proposed.

[0006] The object of the present invention can be achieved by the following technical solutions: A method for analyzing high-frequency simulation test data of a high-speed I / O connector, comprising the following steps:

[0007] Step 1: Select a simulation test tool, set the input parameters in the simulation test tool, generate a test group and a constant group, perform a simulation test through the simulation test tool, and obtain test group simulation test data and constant group simulation test data;

[0008] Step 2: Filter the noise of the test group simulation test data, judge the credibility of the filtered data, perform corresponding processing according to the credibility judgment result, and obtain applicable data;

[0009] Step 3: Compare the constant group simulation test data with the set numerical standard to obtain the constant group numerical difference, and generate a test deviation according to the constant group numerical difference;

[0010] Step 4: Compare the test deviation with the set deviation upper limit to obtain a data anomaly signal or a data floating signal, combine and analyze the applicable data and the test deviation, and generate post-floating data;

[0011] Step 5: Analyze the applicable data, and analyze the signal integrity, time-domain characteristics, and electromagnetic compatibility;

[0012] Step 6: Correct the available data according to the post-floating data to obtain the corrected signal integrity, electromagnetic compatibility, and time-domain characteristics.

[0013] As a preferred embodiment of the present invention, when filtering the noise in Step 2, the input signal frequency is obtained through the input parameters set in Step 1, the signal frequency range is obtained by expanding according to the set range based on the input signal frequency. After obtaining the simulation test data in Step 1, the signal frequency in the simulation test data is compared with the signal frequency range, the signal frequency outside the signal frequency range is recorded as the noise frequency and filtered, and the signal frequency within the signal frequency range is retained.

[0014] As a preferred embodiment of the present invention, the method for judging the credibility of the filtered data in Step 2 is:

[0015] Each type of data in the filtered data is used as a set to obtain multiple data sets, and the data in each data set is graphically processed to obtain a data distribution curve, where the vertical axis of the coordinates where the curve is located is the numerical size of the data, and the horizontal axis is the data acquisition time;

[0016] After obtaining the data distribution curve, analyze the oscillation degree of the data distribution curve to obtain the curve oscillation value, and limit the curve range through the curve oscillation value, and record the curve data within the limited range as applicable data.

[0017] As a preferred embodiment of the present invention, the method for analyzing the oscillation degree of the data distribution curve is as follows:

[0018] Obtain the highest point and the lowest point of the data distribution curve, and record the difference between the highest point and the lowest point as the curve amplitude ZF. Select points on the data distribution curve, calculate the differences between the selected points and the highest point and the lowest point respectively, and record them as the upper margin SF and the lower margin XF. Calculate the fluctuation degree B through the formula, and perform arithmetic averaging on the fluctuation degrees of all points to obtain the curve oscillation value.

[0019] As a preferred embodiment of the present invention, the method for limiting the curve range through the curve oscillation value is as follows:

[0020] Take the midpoint between the highest point and the lowest point of the distribution curve as the data midpoint, and extend 0.5 times the product of the curve amplitude and the fluctuation degree from the data midpoint to both the upper and lower sides, and record the extended width as the limited range.

[0021] As a preferred embodiment of the present invention, the method for obtaining the constant group numerical difference in step three is as follows:

[0022] Calculate the ratio of each data in the constant group simulation test data to the corresponding item in the set numerical standard, and record the average value of the ratios as the constant group numerical difference;

[0023] The comparison method in step four is as follows: If the constant group numerical difference is greater than the set deviation upper limit, generate a data anomaly signal and record the simulation test data this time as unavailable; if the constant group numerical difference is not greater than the set deviation upper limit, generate a data floating signal.

[0024] As a preferred embodiment of the present invention, the method for generating the data floating degree in step four is as follows: Record the constant group numerical difference as A, record the applicable data as Y, and obtain the floating data through Y×(1 + A) and Y×(1 - A);

[0025] In step six, calculate the signal integrity, electromagnetic compatibility, and time domain characteristics respectively through the two sets of floating data, and take the results between the two sets of signal integrity, electromagnetic compatibility, and time domain characteristics as the possible true result range, and take the signal integrity, time domain characteristics, and electromagnetic compatibility in step five as the expected true results.

[0026] The present invention also provides a high-speed I / O connector high-frequency simulation test data analysis system, including a test generation unit, a data acquisition unit, a data correction unit, a deviation comparison unit, a data floating unit, and a result output unit. The test generation unit is used to perform the simulation test in Step 1;

[0027] The data acquisition unit is used to collect data from the simulation test in Step 1 to obtain test group simulation test data and constant group simulation test data;

[0028] The data correction unit is used to perform noise filtering, credibility judgment, and generation of applicable data in Step 2;

[0029] The deviation comparison unit is used to generate the test deviation in Step 3 and generate a data anomaly signal or a data floating signal for the test deviation;

[0030] The data floating unit is used to generate the post-floating data in Step 4;

[0031] The result output unit is used to analyze and generate the signal integrity, time-domain characteristics, and electromagnetic compatibility in Steps 5 and 6 and output the analysis results.

[0032] Compared with the prior art, the beneficial effects of the present invention are:

[0033] 1. In the present invention, during the high-frequency simulation evaluation of the I / O connector, through independent parameterization configuration and the dual-data-group comparison architecture of the test group and the constant group to simultaneously perform the simulation test, dual results of the test group and the constant group are output. Based on the output results, the reference error quantization based on the constant group is performed to obtain the data floating situation, and the dynamic threshold trigger is performed through the floating situation to correct the data of the test group. Therefore, when evaluating the signal integrity, electromagnetic coupling, and time-domain characteristics, not only accurate simulation test results can be output, but also the data drift prediction can be performed based on the data after floating correction, so as to predict the possible landing range of the simulation test results, improving the diversity and reliability of the output results.

[0034] 2. In the present invention, the dual processing mechanism of noise filtering and credibility verification for the data collected during the simulation test realizes the automatic interception of abnormal data and the secondary processing of data, thereby deeply cleaning the data and improving the data authenticity. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] For the convenience of those skilled in the art to understand, the present invention will be further described below with reference to the accompanying drawings.

[0036] Figure 1 It is the system block diagram of the present invention;

[0037] Figure 2 is the system flow chart of the present invention;

[0038] Figure 3 is the schematic diagram of the data distribution curve of the present invention. Specific embodiments

[0039] The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0040] Embodiment 1: Please refer to Figure 1 - Figure 3 shown, a method for analyzing high-speed I / O connector high-frequency simulation test data includes the following steps:

[0041] Step 1: The tester selects a simulation test tool through the test generation unit, such as electromagnetic simulation software, and sets the input parameters in the simulation test tool. At the same time, the test generation unit automatically generates a test group and a constant group, conducts a simulation test through the simulation test tool, and acquires the simulation test data of the test group and the simulation test data of the constant group through the data acquisition unit during the simulation test;

[0042] Step 2: The data correction unit obtains the set input parameters through the test generation unit to obtain the input signal frequency, expands the input signal frequency according to the set range to obtain the frequency range where the signal is located. At the same time, after acquiring the simulation test data through the data acquisition unit, the signal frequency in the simulation test data is compared with the frequency range where the signal is located, and the signal frequency outside the frequency range where the signal is located is recorded as the noise frequency and filtered, and the signal frequency within the frequency range where the signal is located is retained to achieve noise filtering of the simulation test data of the test group. Each type of data in the filtered data is used as a set to obtain multiple data sets, and the data in each data set is graphically processed to obtain a data distribution curve, where the vertical axis of the coordinates where the curve is located is the numerical size of the data, and the horizontal axis is the acquisition time of the data;

[0043] After the data correction unit obtains the data distribution curve, it analyzes the oscillation degree of the data distribution curve:

[0044] The data correction unit obtains the highest point and the lowest point of the data distribution curve, records the difference between the highest point and the lowest point as the curve amplitude ZF, selects points on the data distribution curve, calculates the differences between the selected points and the highest point and the lowest point respectively, and records them as the upper margin SF and the lower margin XF. The fluctuation degree B is calculated by a formula. The arithmetic mean of the fluctuation degrees of all points is calculated to obtain the curve oscillation value. The data credibility is reflected according to the curve oscillation value, and the curve range is limited according to the curve oscillation value. The midpoint of the highest point and the lowest point of the distribution curve is used as the data midpoint, and X distance is extended from the data midpoint to both the upper and lower sides. The width after extending X distance is recorded as the limited range, and the curve data within the limited range is recorded as the applicable data. Thus, the applicable data is optimized according to the credibility of the initial data.

[0045] Step 3: The deviation comparison unit obtains the constant group simulation test data through the data acquisition unit, compares the constant group simulation test data with the set numerical standard, calculates the ratio of each data in the constant group simulation test data to the corresponding item in the set numerical standard, and records the average value of the ratios as the constant group numerical difference. Thus, the constant group numerical difference is obtained, and the test deviation is generated according to the constant group numerical difference.

[0046] Step 4: The data floating unit obtains the test deviation through the deviation comparison unit, and compares the test deviation with the set deviation upper limit. If the constant group numerical difference is greater than the set deviation upper limit, a data anomaly signal is generated, and the simulation test data this time is recorded as unavailable. If the constant group numerical difference is not greater than the set deviation upper limit, a data floating signal is generated, and the applicable data and the test deviation are combined and analyzed. Specifically, first record the constant group numerical difference as A, then record the applicable data as Y, and obtain the floating data on both sides of the original data through Y×(1 + A) and Y×(1 - A).

[0047] Step 5: The result output unit obtains the application data through the data correction unit, analyzes the applicable data, and analyzes the signal integrity, time domain characteristics, and electromagnetic compatibility, so as to output a set of determined signal integrity, time domain characteristics, and electromagnetic compatibility, and regard the accurate result as the expected true result. The output method of the signal integrity includes the S-parameter matrix, return loss, and eye diagram. The output method of the electromagnetic compatibility is the near-field radiation value and crosstalk parameters. The output method of the time domain characteristics is the time domain reflection waveform (TDR).

[0048] Step 6: The result output unit obtains the floating data through the data floating unit, corrects the available data according to the floating data Y×(1 + A) and Y×(1 - A), and generates two sets of signal integrity, electromagnetic compatibility, and time-domain characteristics based on the corrected data. The ranges between the two sets of signal integrity, the ranges between the two sets of electromagnetic compatibility, and the two sets of time-domain characteristics are used as the possible ranges where the true simulation test results after interference removal may fall, that is, the true result landing range. According to the output of the true result landing range, the result after fuzzy processing can be presented to the user, facilitating the user to fully understand the deviation degree and deviation consequences of the simulation test results and improving the comprehensiveness of the simulation test results.

[0049] Embodiment 2: Please refer to Figure 1 - Figure 3 As shown in the figure, a high-speed I / O connector high-frequency simulation test data analysis system includes a test generation unit, a data acquisition unit, a data correction unit, a deviation comparison unit, a data floating unit, and a result output unit;

[0050] Among them, the test generation unit is used to select a simulation test tool and perform simulation tests on the test group and the constant group through the simulation test tool;

[0051] The data acquisition unit is used to collect data for the simulation test to obtain test group simulation test data and constant group simulation test data;

[0052] The data correction unit performs noise filtering, credibility judgment, and generation of applicable data on the test group simulation test data and the constant group simulation test data collected by the data acquisition unit;

[0053] The deviation comparison unit is used to compare the constant group simulation test data with the set numerical standard to obtain the test deviation included in the current simulation test system, and generate a data anomaly signal or a data floating signal for the test deviation;

[0054] The data floating unit generates floating data according to the data floating signal;

[0055] The result output unit is used to analyze and generate the signal integrity, time-domain characteristics, and electromagnetic compatibility obtained from the final analysis, and output the analysis results, where the output results include the expected true results and the possible landing ranges of the true results.

[0056] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific embodiments only. Obviously, many modifications and variations can be made according to the content of this specification. These embodiments are selected and specifically described in this specification in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can well understand and utilize the present invention. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A high-speed I / O connector high-frequency simulation test data analysis method, characterized in that: The following steps are involved: Step 1: Select a simulation test tool, set input parameters in the simulation test tool, generate a test group and a constant group, perform simulation testing through the simulation test tool, and obtain simulation test data of the test group and simulation test data of the constant group; Step 2: Filter the noise of the simulation test data of the test group, and make a credibility judgment on the filtered data, and perform corresponding processing according to the credibility judgment result to obtain applicable data; Step 3: Compare the constant group simulation test data with the set numerical standard to obtain the constant group numerical difference, and generate the test deviation according to the constant group numerical difference; Step 4: Compare the test deviation with the set upper limit of the deviation to obtain data anomaly signals or data floating signals, and combine the applicable data and the test deviation for analysis to generate floating data; Step 5: Analyze applicable data, including signal integrity, time domain characteristics, and electromagnetic compatibility; Step 6: Correct the applicable data according to the floating data to obtain the corrected signal integrity, electromagnetic compatibility and time domain characteristics; The method for obtaining the constant group value difference in step 3 is: Calculate the ratio of each item in the constant group simulation test data to the corresponding item in the set numerical standard, and record the average value of the ratio as the constant group numerical difference; The comparison method in step 4 is: if the difference of the constant group values ​​is greater than the set upper limit of the deviation, a data abnormality signal is generated, and the simulation test data is recorded as unavailable; if the difference of the constant group values ​​is not greater than the set upper limit of the deviation, a data floating signal is generated; The method for generating the data floating degree in step 4 is: record the constant group value difference as A, record the applicable data as Y, and obtain the floating data through Y×(1+A) and Y×(1-A); In the step six, the signal integrity, electromagnetic compatibility and time domain characteristics are calculated respectively by two sets of floating data, and the results between the two sets of signal integrity, electromagnetic compatibility and time domain characteristics are taken as the possible real result range, and the signal integrity, time domain characteristics and electromagnetic compatibility in step five are taken as the expected real results.

2. A high-speed I / O connector high-frequency simulation test data analysis method according to claim 1, characterized in that: When filtering the noise in the step 2, the input signal frequency is obtained through the input parameters set in the step 1, and the frequency range of the signal is obtained by expanding the frequency of the input signal through the set range. After obtaining the simulation test data in the step 1, the signal frequency in the simulation test data is compared with the frequency range of the signal, and the signal frequency outside the frequency range of the signal is recorded as the noise frequency and filtered, and the signal frequency within the frequency range of the signal is retained.

3. A high-speed I / O connector high-frequency simulation test data analysis method according to claim 1, characterized in that: The method for judging the credibility of the filtered data in step 2 is: Each type of data in the filtered data is taken as a set to obtain multiple data sets, and the data in each data set is graphically processed to obtain a data distribution curve, wherein the vertical axis of the coordinates of the curve is the numerical value of the data, and the horizontal axis is the acquisition time of the data; After obtaining the data distribution curve, the oscillation degree of the data distribution curve is analyzed to obtain the curve oscillation value, and the curve range is limited by the curve oscillation value, and the curve data within the limited range is recorded as applicable data.

4. A high-speed I / O connector high-frequency simulation test data analysis method according to claim 3, characterized in that: The analysis method for the oscillation degree of the data distribution curve is: Get the highest point and the lowest point of the data distribution curve, and record the difference between the highest point and the lowest point as the curve amplitude ZF; select a point in the data distribution curve, calculate the difference between the selected point and the highest point and the lowest point, and record them as the upper margin SF and the lower margin XF respectively; calculate the fluctuation degree B by the formula; take the arithmetic average of the fluctuation degrees of all points to get the curve oscillation value.

5. A high-speed I / O connector high-frequency simulation test data analysis method according to claim 3, characterized in that: The method of limiting the curve range by the curve oscillation value is: The midpoint between the highest and lowest points of the distribution curve is taken as the data midpoint, and the distance extending upward and downward from the data midpoint is 0.5 times the product of the curve amplitude and the degree of fluctuation, and the extended width is recorded as the limited range.

6. A high-speed I / O connector high-frequency simulation test data analysis system, used for a high-speed I / O connector high-frequency simulation test data analysis method as claimed in any one of claims 1 to 5, characterized in that: It includes a test generation unit, a data acquisition unit, a data correction unit, a deviation control unit, a data floating unit and a result output unit, wherein the test generation unit is used to perform the simulation test in step 1; The data acquisition unit is used to collect data for the simulation test in step 1 to obtain the test group simulation test data and the constant group simulation test data; The data correction unit is used to perform noise filtering, credibility judgment and generation of applicable data in step 2; The deviation control unit is used to generate the test deviation in step 3, and generate a data abnormality signal or a data floating signal for the test deviation; The data floating unit is used to generate the floating data in step 4; The result output unit is used to analyze and generate the signal integrity, time domain characteristics and electromagnetic compatibility in step five and step six, and output the analysis results.

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