Automated testing system and method for time synchronization accuracy of tsn devices

Abstract

The application provides an automatic test system and method for time synchronization precision of TSN equipment, and belongs to the technical field of industrial communication network testing. The system comprises a central control unit, a reference clock source, a measured TSN equipment, a test slave equipment, a damage simulation unit and a message capture and analysis unit. The method comprises the following steps: the central control unit controls the damage simulation unit to apply multiple groups of network damage according to a preset test scene sequence; high-precision hardware timestamp is used to collect synchronization message time information and test slave equipment clock information; based on the collected information, time synchronization error sequences and residence time sequences under each damage scene are calculated and accumulated; based on all the accumulated data, an overall stability score is calculated through a dynamic weighted evaluation algorithm. The application realizes fully automatic testing by constructing a dynamic damage environment, and solves the problems of idealized test environment, low efficiency and lack of deep performance insight in the prior art.

Description

Technical Field

[0001] This invention relates to the field of industrial communication network testing technology, and in particular to an automated testing system and method for the time synchronization accuracy of TSN devices. Background Technology

[0002] Time-Sensitive Networking (TSN), as an evolution of traditional Ethernet technology, provides deterministic guarantees for data transmission through a series of IEEE standards (such as IEEE 802.1AS-Rev for gPTP). Nanosecond-level high-precision time synchronization is the cornerstone for achieving key functions such as periodic scheduling and traffic shaping. In fields with extremely high real-time requirements, such as industrial automation, automotive networks, and aerospace, the time synchronization accuracy of TSN devices (including switches and end devices) directly determines the performance ceiling and reliability of the entire control system. Therefore, rigorous and reliable testing of time synchronization accuracy is crucial during equipment development, network acceptance, and regular maintenance.

[0003] Currently, the industry mainly uses the following methods to test the time synchronization accuracy of TSN devices:

[0004] (1) Direct measurement method using oscilloscope / time interval analyzer: This method uses a high-precision oscilloscope to directly probe the physical layer signals (such as PPS pulses) of the master and slave ports of the device under test, and calculates the synchronization error by measuring the phase difference between the signals. Although this method is direct, it has significant limitations: First, the testing process is highly dependent on manual operation and interpretation, which is inefficient and makes it difficult to automate and scale up testing; second, the required high-bandwidth oscilloscope equipment is extremely expensive; more importantly, this method can only measure physical layer signals and cannot effectively evaluate the comprehensive impact of the device's internal protocol stack processing, clock servo algorithm, etc. on the synchronization accuracy, resulting in an incomplete testing dimension.

[0005] (2) Hardware timestamp testing method based on general computing platform: This method runs the PTP / gPTP protocol stack on a general computing platform and uses a network card that supports hardware timestamps to record and compare the timestamps of synchronization messages. Although hardware timestamps have higher accuracy than software timestamps, they are still limited by factors such as the clock source quality, system interrupt handling, and driver overhead of the general computing platform. In actual testing, it is difficult to stably achieve the nanosecond-level synchronization accuracy required by TSN devices, and the controllability and repeatability of the test environment are still not ideal. In addition, this method is usually difficult to integrate deeply with complex network impairment simulation environments and cannot fully evaluate the synchronization performance of the device under dynamic and harsh network conditions.

[0006] (3) Testing methods based on commercial network testers: Some high-end professional network testers (such as products from brands like IXIA) integrate PTP / TSN testing functions. These devices provide a relatively integrated solution. However, their core drawback is that they are black-box systems. The quality of the clock source, the damage simulation mechanism, and the precise algorithms inside the tester are not transparent to the user. It is difficult for users to customize complex and dynamically changing damage models according to specific application scenarios (such as simulating sudden jitter under specific operating conditions). In addition, the procurement and maintenance costs of these high-end testers are very high, which limits their widespread application in equipment manufacturers and laboratories.

[0007] In summary, existing technologies either employ overly idealized testing environments that fail to simulate the dynamic and harsh transmission conditions present in real networks, or lack automated testing processes that result in low efficiency and are prone to human error, or have excessively high testing system costs or insufficient flexibility and transparency, making it impossible to systematically and automatically quantitatively evaluate and deeply diagnose the ability of devices to maintain synchronization accuracy under extreme operating conditions.

[0008] Therefore, there is an urgent need in this field for a TSN device time synchronization accuracy testing system and method that can simulate real network dynamic damage, achieve fully automated testing, possess high precision and high reliability, and is cost-controllable and has strong test insight, in order to fill the gap in the existing technology. Summary of the Invention

[0009] The purpose of this invention is to provide an automated testing system and method for the time synchronization accuracy of TSN devices, in order to solve the problems of idealized testing environments, inability to automatically quantify synchronization accuracy under extreme conditions, high testing costs, and lack of in-depth performance insight in the prior art.

[0010] To achieve the above objectives, this invention provides an automated testing method for the time synchronization accuracy of TSN devices, comprising the following steps:

[0011] Step S1: The central control unit controls the damage simulation unit to apply multiple different network damages to the test network in sequence according to a preset sequence.

[0012] Step S2: For each group of network impairments, the central control unit automatically collects the synchronization message time information and the clock information of the test slave device recorded by the message capture and analysis unit.

[0013] Step S3: Based on the information collected in step S2, the central control unit calculates and accumulates time synchronization performance data under each damage scenario;

[0014] Step S4: After traversing all damage scenarios, based on all accumulated time synchronization performance data, the central control unit calculates the overall stability score through a dynamic weighted evaluation algorithm to quantitatively characterize the comprehensive time synchronization performance of the tested TSN device under dynamic damage conditions.

[0015] Preferably, in step S1, applying multiple sets of different network impairments to the test network in a preset sequence specifically involves the central control unit configuring the network impairment parameters defined for each test scenario from a preset test scenario sequence into the impairment simulation unit to apply network impairments defined by at least one of the parameters: latency, latency jitter, and packet loss rate.

[0016] Preferably, in step S2, the central control unit triggers the message capture and analysis unit to perform high-precision hardware timestamps on the TSN synchronization messages at the entry and exit points of the TSN device under test, in order to obtain the entry timestamp. and export timestamp ;

[0017] At the same time, the central control unit reads the synchronized clock information from the test slave device.

[0018] Preferably, in step S3, the central control unit calculates and accumulates time synchronization performance data under each damage scenario, specifically including:

[0019] Step S31: Calculate the end-to-end time synchronization error sequence based on the clock information of the test slave device;

[0020] Step S32, based on the entry timestamp and export timestamp Calculate the dwell time series of the tested TSN device. :

[0021] ;

[0022] Step S33: Store the time synchronization error sequence and dwell time sequence under the current damage scenario.

[0023] Preferably, in step S4, the dynamic weighted evaluation algorithm includes the following steps:

[0024] Step S41: Based on the accumulated time synchronization error sequences and residence time sequences, calculate the basic stability index. Robustness indicators and processing consistency indicators ;

[0025] Step S42: Set the basic stability index Robustness indicators and processing consistency indicators The overall stability score is calculated as a composite performance index.

[0026] Preferably, in step S41, the basic stability index The calculation method is as follows: the standard deviation of the time synchronization error sequence under all test scenarios. According to its corresponding scenario dynamic weight Perform a weighted average, that is:

[0027] ;

[0028] Among them, scene dynamic weights It is positively correlated with the severity of network impairment in this scenario.

[0029] Preferably, in step S41, the robustness index The calculation method is as follows: select the maximum value of the time synchronization error sequence from all test scenarios. The largest front Calculate these scenarios. The arithmetic mean, i.e.:

[0030] ;

[0031] in, Indicates the selected first Index of each scenario Indicates the first The maximum value of the time synchronization error sequence for each scenario.

[0032] Preferably, in step S41, the consistency index is processed. The calculation method is as follows: the standard deviation of the dwell time series under all test scenarios. A weighted average is used to characterize the fluctuation of message processing delay under different damage conditions. The calculation formula is as follows:

[0033] ;

[0034] in, Indicates the test scenario The standard deviation of the residence time series, Indicates the test scenario Dynamic weights.

[0035] Preferably, in step S42, the comprehensive performance index is calculated as follows: the basic stability index is... Robustness indicators and processing consistency indicators After normalization, the components are linearly combined according to dynamically adjusted weighting factors.

[0036] Overall performance index The calculation formula is:

[0037] ;

[0038] in, Represents the normalization function. This represents the basic stability index after normalization. This represents the robustness index after normalization. This represents the consistency index after normalization. , , All represent weighting factors, which are dynamically adjusted based on the performance of the tested TSN device. The adjustment method is as follows:

[0039] Calculate the basic stability index With robustness indicators The ratio of the original values ​​before normalization and basic stability indicators Consistency metrics with processing The ratio of the original values ​​before normalization ,Right now:

[0040] ;

[0041] ;

[0042] Weighting factors , , Calculate using the following formula:

[0043] ;

[0044] ;

[0045] .

[0046] The present invention also provides an automated testing system for the time synchronization accuracy of TSN devices, comprising: a central control unit, a reference clock source, a TSN device under test, a test slave device, a damage simulation unit, and a message capture and analysis unit;

[0047] The reference clock source is connected to the main port of the TSN device under test through the damage simulation unit;

[0048] The slave port of the TSN device under test is connected to the test slave device;

[0049] The timestamp port of the message capture and analysis unit is connected across the synchronization message link between the damage simulation unit and the TSN device under test, and between the TSN device under test and the test slave device.

[0050] The central control unit communicates with the damage simulation unit, message capture and analysis unit, and test slave devices via a control network and is configured to execute a dynamic weighted evaluation algorithm to calculate the overall stability score.

[0051] Therefore, the present invention employs the above-mentioned automated testing system and method for the time synchronization accuracy of TSN devices, and the beneficial technical effects are as follows:

[0052] (1) It realizes fully automated and high-precision testing under simulated real harsh network conditions, and solves the problems of idealized testing environment, low efficiency and insufficient accuracy of existing technologies.

[0053] This invention utilizes a central control unit to achieve closed-loop control of the impairment simulation unit, automatically applying and switching various network impairments, including latency, jitter, and packet loss, thus constructing a dynamic and realistic test environment. Simultaneously, data acquisition is based on the high-precision hardware timestamps of the packet capture and analysis unit, fundamentally avoiding the uncertainty of software timestamps and ensuring nanosecond-level test accuracy. The entire configuration-acquisition-calculation-evaluation process requires no manual intervention, significantly improving testing efficiency and reliability.

[0054] (2) It provides in-depth performance insight and comprehensive evaluation capabilities that exceed conventional indicators, solving the problems of insufficient insight and inability to quantify the comprehensive synchronous stability of existing black box testers.

[0055] This invention does not simply output discrete error data. Instead, it uses a unique multi-dimensional dynamic weighted evaluation algorithm to transform the device's performance under various damage scenarios into sub-indicators such as basic stability and robustness, ultimately merging them into an intuitive overall stability score (CPI). The dynamic weight adjustment mechanism in this algorithm adaptively highlights the device's performance shortcomings, thus providing users with an unprecedented in-depth analytical perspective. It can not only determine whether the device is qualified but also accurately locate its performance weaknesses, guiding optimization directions. Attached Figure Description

[0056] Figure 1 This is a flowchart of the automated testing method for the time synchronization accuracy of TSN devices according to the present invention;

[0057] Figure 2 This is an architecture diagram of the automated testing system for the time synchronization accuracy of TSN devices according to the present invention. Detailed Implementation

[0058] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0059] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.

[0060] Example 1

[0061] This embodiment provides a specific implementation method for automated testing of the time synchronization accuracy of TSN devices. By constructing a complete test environment and executing a detailed test process, it demonstrates the specific application of the present invention.

[0062] 1. Test environment setup.

[0063] The testing system used in this embodiment includes the following components:

[0064] Central control unit: It uses an industrial server equipped with an Intel Xeon E5 processor and 32GB of memory, and runs automated test control software developed based on Python 3.9.

[0065] Reference clock source: Symmetricom xLi quartz clock with time stability better than ±0.1ppm, outputting IEEE1588v2 (PTP) synchronization signal.

[0066] Impairment Simulation Unit: Employs a TSN tester with high-precision network impairment simulation capabilities, such as the network impairment module integrated into the NetSeek6000 TSN analyzer. This module supports programmable control and injection of network impairment parameters such as latency, jitter, and packet loss rate with nanosecond-level precision.

[0067] Message capture and analysis unit: It adopts a timestamp unit based on a highly stable clock source and dedicated hardware processing logic (such as the technology used in the SyncOne series testers). Its single message timestamp accuracy can reach ±4 nanoseconds to meet the extreme accuracy requirements of TSN testing.

[0068] The TSN device under test is an 8-port TSN switch from a certain manufacturer, which supports the IEEE 802.1AS-Rev protocol.

[0069] Test device: An industrial communication module with hardware PTP timestamp capability was used.

[0070] System connection configuration:

[0071] The PTP output port of the reference clock source is connected to input port A of the damage simulation unit, and output port A of the damage simulation unit is connected to port 1 (master port) of the TSN device under test. Port 2 (slave port) of the TSN device under test is connected to the test slave device. The two monitoring ports of the message capture and analysis unit are respectively connected across the links between the damage simulation unit and the TSN device under test, and between the TSN device under test and the test slave device.

[0072] 2. Test parameter settings.

[0073] The preset test scenario sequence contains 5 different sets of network impairment parameters, as shown in Table 1:

[0074] Table 1 Scene Settings

[0075]

[0076] 3. Test execution process, such as Figure 1 As shown.

[0077] Step S1: The central control unit controls the damage simulation unit to apply multiple different network damages to the test network in sequence according to a preset sequence.

[0078] Specifically: The central control unit initiates the test process, first initializing all test devices. Then, following the test scenario sequence described above, it configures the network impairment parameters for each scenario into the impairment simulation unit. For example, when executing scenario 3, the central control unit connects to the impairment simulation unit via a control interface (such as the SSH protocol) and sends configuration commands to it, setting a fixed latency of 100μs, latency jitter of ±10μs (uniformly distributed), and a packet loss rate of 0.5%.

[0079] Step S2: For each group of network impairments, the central control unit automatically collects the synchronization message time information and the clock information of the test slave devices recorded by the message capture and analysis unit.

[0080] Specifically: Trigger the packet capture and analysis unit to start recording: Through the acquisition program developed based on DPDK, gPTP packets (including Announce, Sync, Follow_Up, etc.) are captured synchronously at the entry and exit points of the test network, and the precise hardware timestamps are recorded.

[0081] Clock information is read from the test slave device: The current clock value is read from the test slave device once per second via the Modbus TCP protocol, for a total of 60 samples.

[0082] Specific data collection results for scenario 3:

[0083] Entry timestamp sequence: ,in Indicates the first The entry timestamp of a Sync message. =180 (Number of Sync packets captured during the 3-minute test);

[0084] Export timestamp sequence: ,in Indicates the first The exit timestamp of each Sync message;

[0085] Test the sequence of clock values ​​from the device: ,in This indicates the clock value of the device being tested at the 60th second.

[0086] Step S3: Based on the information collected in step S2, the central control unit calculates and accumulates time synchronization performance data under each damage scenario.

[0087] The central control unit calculates and accumulates time synchronization performance data under various damage scenarios, specifically including:

[0088] Step S31: Calculate the end-to-end time synchronization error sequence based on the clock information of the test slave device;

[0089] ;

[0090] in, This represents the time synchronization error sequence. This represents the master clock value of the reference clock source at the corresponding moment. In the scenario 3 test, 60 time synchronization error values ​​were calculated, in nanoseconds.

[0091] Step S32, based on the entry timestamp and export timestamp Calculate the dwell time series of the tested TSN device. :

[0092] ;

[0093] In the scenario 3 test, 180 dwell time values ​​were calculated, in nanoseconds.

[0094] Step S33: Store the time synchronization error sequence and dwell time sequence under the current damage scenario.

[0095] Step S4: After completing all 5 test scenarios, based on all accumulated time synchronization performance data, the central control unit calculates the overall stability score through a dynamic weighted evaluation algorithm to quantitatively characterize the comprehensive time synchronization performance of the tested TSN device under dynamic damage conditions.

[0096] Step S41: Calculate the sub-indicators: Based on the accumulated time synchronization error series and residence time series, calculate the basic stability index. Robustness indicators and processing consistency indicators ;

[0097] Basic stability index The calculation method is as follows: the standard deviation of the time synchronization error sequence under all test scenarios. According to its corresponding scenario dynamic weight Perform a weighted average, that is:

[0098] ;

[0099] Among them, scene dynamic weights It is positively correlated with the severity of network impairment in this scenario.

[0100] Robustness index The calculation method is as follows: select the maximum value of the time synchronization error sequence from all test scenarios. The largest front Calculate these scenarios. The arithmetic mean, i.e.:

[0101] ;

[0102] in, Indicates the selected first Index of each scenario Indicates the first The maximum value of the time synchronization error sequence for each scenario.

[0103] Processing consistency metrics The calculation method is as follows: the standard deviation of the dwell time series under all test scenarios. A weighted average is used to characterize the fluctuation of message processing delay under different damage conditions. The calculation formula is as follows:

[0104] ;

[0105] in, Indicates the test scenario The standard deviation of the residence time series, Indicates the test scenario Dynamic weights.

[0106] The specific data for each scenario is shown in the table below:

[0107] Table 2 Data Results

[0108]

[0109] Based on all accumulated test data, three sub-indicators are calculated:

[0110] Basic stability metrics:

[0111] The weighted average calculation yielded a basic stability index of 58.4 nanoseconds, reflecting the average fluctuation level of the synchronization error of the equipment under various damage conditions.

[0112] Robustness indicators:

[0113] The three scenarios with the largest time synchronization errors (Scenarios 3, 4, and 5) were selected, and the arithmetic mean of their maximum error values ​​was calculated. The robustness index was 232 nanoseconds, which characterizes the performance of the equipment under extreme damage conditions.

[0114] Handling consistency metrics:

[0115] The weighted average calculation yielded a processing consistency index of 23.1 nanoseconds, reflecting the fluctuation in message processing delay under different damage conditions.

[0116] Step S42, Integrate into a comprehensive index: Combine the basic stability index Robustness indicators and processing consistency indicators The overall stability score is calculated as the composite performance index (CPI).

[0117] Basic stability indicators Robustness indicators and processing consistency indicators After normalization, the components are linearly combined according to dynamically adjusted weighting factors.

[0118] Overall performance index The calculation formula is:

[0119] ;

[0120] in, Represents the normalization function. This represents the basic stability index after normalization. This represents the robustness index after normalization. This represents the consistency index after normalization, with weighting factors. , , It is not a preset fixed value, but is dynamically adjusted according to the performance of the TSN device under test. The adjustment method is as follows:

[0121] Calculate the basic stability index With robustness indicators The ratio of the original values ​​before normalization and basic stability indicators Consistency metrics with processing The ratio of the original values ​​before normalization ,Right now:

[0122] ;

[0123] ;

[0124] Then weighting factor , , Calculate using the following formula:

[0125] ;

[0126] ;

[0127] .

[0128] Specifically, the three sub-indicators were normalized to obtain the normalized basic stability index of 0.62, robustness index of 0.78, and processing consistency index of 0.54.

[0129] The ratio of the basic stability index to the robustness index was calculated to be 0.252, and the ratio of the basic stability index to the treatment consistency index was 2.528.

[0130] Based on the above ratios, the dynamic weighting factors are calculated, resulting in a basic stability weight of 0.875, a robustness weight of 0.119, and a processing consistency weight of 0.006.

[0131] The final calculated comprehensive performance index is 0.634. This value is between 0 and 1. The higher the value, the better the time synchronization performance of the device.

[0132] This step integrates multi-scenario test data into a quantitative comprehensive performance index (CPI=0.634) through a dynamic weighted evaluation algorithm, achieving a comprehensive and automated evaluation of the equipment's synchronization performance. At the same time, based on the analysis of sub-indicators and dynamic weights (such as a basic stability weight of 0.875), it accurately reveals the performance shortcomings of the equipment in maintaining synchronization accuracy under high damage conditions. Thus, while providing objective acceptance criteria, it also provides a clear diagnostic direction for targeted equipment optimization, effectively solving the problems of low efficiency and insufficient insight of traditional testing methods.

[0133] 4. Test result analysis.

[0134] The overall performance index (CPI) obtained in this embodiment is 0.634 (range 0-1, with higher values ​​indicating better performance), indicating that the overall time synchronization performance of the tested TSN device under dynamic damage conditions is at a moderate level. The dynamic weight allocation shows that the device's processing consistency is relatively good. Smaller (The weight is low), but the basic stability and robustness need to be improved, especially the ability to maintain synchronization accuracy under high damage conditions.

[0135] This embodiment successfully achieved fully automated testing under simulated harsh network conditions. The method described above provides in-depth insights into device synchronization performance, offering clear technical directions for device optimization and improvement. The entire testing process is fully automated, achieving nanosecond-level accuracy, effectively overcoming the limitations of traditional testing methods.

[0136] Example 2

[0137] like Figure 2 As shown, the automated test system for the time synchronization accuracy of TSN devices includes: a central control unit, a reference clock source, the TSN device under test, a test slave device, a damage simulation unit, and a message capture and analysis unit.

[0138] The reference clock source is connected to the main port of the TSN device under test through the damage simulation unit;

[0139] The slave port of the TSN device under test is connected to the test slave device;

[0140] The high-precision timestamp port of the message capture and analysis unit is connected across the synchronization message link between the damage simulation unit and the TSN device under test, as well as between the TSN device under test and the test slave device.

[0141] The central control unit communicates with the damage simulation unit, message capture and analysis unit, and test slave devices via a control network and is configured to execute a dynamic weighted evaluation algorithm to calculate the overall stability score.

[0142] The central control unit is specifically configured as follows:

[0143] According to the preset test scenario sequence, the network impairment parameters defined for each scenario are configured into the impairment simulation unit in sequence;

[0144] The message capture and analysis unit is triggered to collect the timestamp information of the synchronization message and read the clock information from the test slave device.

[0145] Based on timestamp information and clock information, calculate and accumulate time synchronization performance data under various damage scenarios;

[0146] Based on all accumulated time synchronization performance data, an overall stability score is calculated using a dynamic weighted evaluation algorithm.

[0147] It is worth noting that all contents not described in detail in this invention are existing technologies and are well known to those skilled in the art.

[0148] Therefore, the present invention adopts the above-mentioned automated testing system and method for the time synchronization accuracy of TSN devices. By constructing a dynamic damage testing environment, it realizes a fully automated and high-precision testing process, providing a comprehensive, accurate, and quantifiable evaluation of the synchronization performance of TSN devices under real network conditions.

[0149] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. An automated testing method for the time synchronization accuracy of TSN devices, characterized in that, Includes the following steps: Step S1: The central control unit controls the damage simulation unit to apply multiple different network damages to the test network in sequence according to a preset sequence. Step S2: For each group of network impairments, the central control unit automatically collects the synchronization message time information and the clock information of the test slave device recorded by the message capture and analysis unit. Step S3: Based on the information collected in step S2, the central control unit calculates and accumulates time synchronization performance data under each damage scenario; Step S4: After traversing all damage scenarios, based on all accumulated time synchronization performance data, the central control unit calculates the overall stability score through a dynamic weighted evaluation algorithm to quantitatively characterize the comprehensive time synchronization performance of the tested TSN device under dynamic damage conditions.

2. The automated testing method for the time synchronization accuracy of TSN devices according to claim 1, characterized in that, In step S1, applying multiple sets of different network impairments to the test network in a preset sequence is specifically as follows: the central control unit configures the network impairment parameters defined for each test scenario into the impairment simulation unit from a preset test scenario sequence.

3. The automated testing method for the time synchronization accuracy of TSN devices according to claim 1, characterized in that, In step S2, the central control unit triggers the message capture and analysis unit to perform high-precision hardware timestamps on the TSN synchronization messages at the ingress and egress points of the TSN device under test, in order to obtain the ingress timestamp. and export timestamp ; At the same time, the central control unit reads the synchronized clock information from the test slave device.

4. The automated testing method for the time synchronization accuracy of TSN devices according to claim 3, characterized in that, In step S3, the central control unit calculates and accumulates time synchronization performance data under various damage scenarios, specifically including: Step S31: Calculate the end-to-end time synchronization error sequence based on the clock information of the test slave device; Step S32, based on the entry timestamp and export timestamp Calculate the dwell time series of the tested TSN device. : ； Step S33: Store the time synchronization error sequence and dwell time sequence under the current damage scenario.

5. The automated testing method for the time synchronization accuracy of TSN devices according to claim 4, characterized in that, In step S4, the dynamic weighted evaluation algorithm includes the following steps: Step S41: Based on the accumulated time synchronization error sequences and residence time sequences, calculate the basic stability index. Robustness indicators and processing consistency indicators ; Step S42: Set the basic stability index Robustness indicators and processing consistency indicators The overall stability score is calculated as a composite performance index.

6. The automated testing method for the time synchronization accuracy of TSN devices according to claim 5, characterized in that, In step S41, the basic stability index The calculation method is as follows: the standard deviation of the time synchronization error sequence under all test scenarios. According to its corresponding scenario dynamic weight Perform a weighted average, that is: ； Among them, scene dynamic weights It is positively correlated with the severity of network impairment in this scenario.

7. The automated testing method for the time synchronization accuracy of TSN devices according to claim 5, characterized in that, In step S41, robustness index The calculation method is as follows: select the maximum value of the time synchronization error sequence from all test scenarios. The largest front Calculate these scenarios. The arithmetic mean, that is: ； in, Indicates the selected first Index of each scenario Indicates the first The maximum value of the time synchronization error sequence for each scenario.

8. The automated testing method for the time synchronization accuracy of TSN devices according to claim 5, characterized in that, In step S41, the consistency index is processed. The calculation method is as follows: the standard deviation of the dwell time series under all test scenarios. A weighted average is used to characterize the fluctuation of message processing delay under different damage conditions. The calculation formula is as follows: ； in, Indicates the test scenario The standard deviation of the residence time series, Indicates the test scenario Dynamic weights.

9. The automated testing method for the time synchronization accuracy of TSN devices according to claim 5, characterized in that, In step S42, the comprehensive performance index is calculated as follows: the basic stability index is... Robustness indicators and processing consistency indicators After normalization, the components are linearly combined according to dynamically adjusted weighting factors. Overall performance index The calculation formula is: ； in, Represents the normalization function. This represents the basic stability index after normalization. This represents the robustness index after normalization. This represents the consistency index after normalization. , , All represent weighting factors, which are dynamically adjusted based on the performance of the tested TSN device. The adjustment method is as follows: Calculate the basic stability index With robustness indicators The ratio of the original values ​​before normalization and basic stability indicators Consistency metrics with processing The ratio of the original values ​​before normalization ,Right now: ； ； Weighting factors , , Calculate using the following formula: ； ； 。 10. An automated testing system for the time synchronization accuracy of TSN devices, characterized in that, include: Central control unit, reference clock source, TSN device under test, test slave device, damage simulation unit, and message capture and analysis unit; The reference clock source is connected to the main port of the TSN device under test through the damage simulation unit; The slave port of the TSN device under test is connected to the test slave device; The timestamp port of the message capture and analysis unit is connected across the synchronization message link between the damage simulation unit and the TSN device under test, and between the TSN device under test and the test slave device. The central control unit communicates with the damage simulation unit, message capture and analysis unit, and test slave devices via a control network and is configured to execute a dynamic weighted evaluation algorithm to calculate the overall stability score.

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