Method and equipment for testing punctuality precision of time synchronization device

Abstract

The invention provides a method and equipment for testing the punctuality precision of a time synchronization device, belongs to the technical field of time frequency, and aims to solve the problems of low test automation, difficulty in quantification of environmental influence, inaccurate evaluation and high result subjectivity in the prior art. The method comprises the following steps: simulating an external signal interruption punctuality scene through a dual-channel radio frequency switch, and synchronously acquiring an output signal (time deviation data compared with a high-precision reference clock) of a time synchronization device and temperature, humidity and air pressure environment data; and analyzing the stability of the crystal oscillator through a TIE algorithm and Arron variance, and correlating modeling to quantify the environmental influence to generate a multi-dimensional evaluation report. The objective performance portrait containing parameters such as frequency drift and stability is provided, the defects of a traditional method are overcome, and a scientific basis is provided for equipment research and development optimization and model selection design.

Description

Technical Field

[0001] This invention belongs to the field of time and frequency technology, and specifically relates to a method and equipment for testing the timekeeping accuracy of a time synchronization device. Background Technology

[0002] Although the self-timekeeping capability of time synchronization devices is crucial, existing technologies for evaluating this performance metric generally suffer from numerous problems, making it difficult to meet the stringent requirements of modern critical infrastructure for testing efficiency, accuracy, and objectivity.

[0003] First, existing testing methods heavily rely on manual operation, resulting in low testing efficiency and poor consistency. Traditional testing procedures typically require technicians to manually disconnect the external synchronization signal source and then, over a lengthy testing period (potentially several days or weeks), periodically record and compare the time output of the device under test with that of a high-precision reference source. This process is not only time-consuming and labor-intensive but also highly susceptible to errors introduced by human negligence or improper operation, leading to a lack of comparability between test results from different batches or from different personnel.

[0004] Secondly, existing technologies struggle to effectively simulate and quantify the impact of complex environmental factors on timekeeping accuracy. The internal crystal oscillator of a time synchronization device is crucial to its self-timekeeping capability, but its frequency stability is highly susceptible to environmental variables such as temperature, humidity, and air pressure. However, traditional laboratory tests are often conducted in ideal environments with constant temperature and humidity, which differs significantly from actual deployment environments. This testing method cannot reveal how environmental changes systematically cause drift in timekeeping accuracy under real-world operating conditions, thus providing limited reference value for equipment selection, deployment, and maintenance.

[0005] Furthermore, the lack of standardized and precise quantitative evaluation algorithms leads to highly subjective and difficult-to-reproduce evaluation results. Existing tests often use simple mean or maximum time deviations to describe timekeeping performance, which fails to comprehensively and deeply characterize the intrinsic stability features of crystal oscillators. For example, it cannot distinguish between short-term random fluctuations and long-term systematic drift, nor can it assess the performance of equipment at different time scales. This evaluation method is not only crude but also lacks unified industry standards, making it difficult to objectively compare the performance of equipment from different manufacturers on the same dimension, introducing significant uncertainty into system integration and maintenance. Summary of the Invention

[0006] In view of this, the present invention provides a method and device for testing the timekeeping accuracy of a time synchronization device, in order to solve the problems of low automation of the testing process, difficulty in quantifying the influence of environmental factors, inaccurate evaluation algorithms, and strong subjectivity of results in the prior art when evaluating the self-timekeeping capability of a time synchronization device.

[0007] The technical solution adopted in this invention is as follows: A method for testing the timekeeping accuracy of a time synchronization device includes: Step 1: Dynamically control the signal connection and disconnection between the external signal source and the time synchronization device through a dual-channel RF switch to simulate a timekeeping scenario where the external signal is interrupted; In step 1, a dual-channel RF switch is used to control the time synchronization device to maintain cleanliness with external signals in order to simulate normal operating conditions.

[0008] Step 2: In the timekeeping scenario stage of simulated signal interruption, continuously collect and record the time signal output by the time synchronization device, and compare the collected time signal with the high-precision reference clock inside the system to form time deviation data; During the timed scenario phase of simulating signal interruption, environmental data in the test environment, including temperature, humidity, and air pressure data, are collected synchronously. The environmental data acquisition methods described in step 2 include passive correlation acquisition and active environmental stress acquisition; The active environmental stress acquisition is achieved through a controllable environmental stress chamber, simulating temperature changes and corresponding humidity and air pressure gradient changes.

[0009] Step 3: Based on the collected time deviation data sequence, the instantaneous time deviation is calculated using the time interval error algorithm, and the Allan variance algorithm is used to analyze the frequency stability of the internal crystal oscillator at different time scales; Step 3, specifically the calculation of the instantaneous time deviation using the time interval error algorithm, includes: Determine the output timestamp of the time synchronization device under test at time t, denoted as . ; Determine the ideal timestamp of the system's internal high-precision reference clock at time t, denoted as . ; Will and Substitute into the formula The instantaneous time deviation at time t is calculated.

[0010] Step 3, which involves using the Allan variance algorithm to analyze the frequency stability of the internal crystal oscillator at different time scales, specifically includes: The time deviation data sequence is continuously divided into blocks according to a fixed time length τ; Calculate the average of all time deviation samples within each data block to obtain the mean sequence. ; Calculate the mean of two adjacent sequences and The sum of squared differences is calculated and normalized to obtain the Allen variance for the corresponding time scale τ. ; Through the obtained multiple Allen variance values This generates Allan variance curves with multiple time scales τ, which helps identify the noise type of the internal crystal oscillator.

[0011] Following step 3, there is also a crystal oscillator error compensation step, which specifically includes: Linear regression analysis was performed on the acquired instantaneous time deviation (TIE) data to establish a crystal oscillator aging rate model, which characterizes the natural drift trend of the crystal oscillator frequency over time. By correlating the collected temperature data with TIE data, a crystal oscillator frequency-temperature characteristic model was established to reveal the frequency drift characteristics of the crystal oscillator at different temperatures. The crystal oscillator aging rate model, frequency-temperature characteristic model, crystal oscillator noise type parameters, real-time acquired time deviation data and temperature data are input into the Kalman filter. The Kalman filter uses the system dynamic model and measurement data to make the optimal estimate and prediction of the instantaneous frequency error of the crystal oscillator and outputs the error estimate and prediction results.

[0012] Step 4: Correlate the time deviation data with the environmental data to quantify the impact of environmental factors on timekeeping accuracy and generate an evaluation report containing multi-dimensional performance indicators.

[0013] Step 4, specifically the correlation modeling of time deviation data and environmental data, includes: Step A1: Preprocess the time deviation data output from Step 3 and the synchronously acquired environmental data, calculate the instantaneous frequency error using the finite difference method, and extract the environmental data set containing nonlinear characteristics; Step A1 specifically includes: Step A11: Based on the instantaneous time deviation data sequence (k=1, 2…n, where n is the number of samples), the first-order central difference method is used to calculate the time. instantaneous frequency error The first and last samples are supplemented by forward difference (k=1) and backward difference (k=n) respectively to ensure that the frequency error sequence is consistent with the length of the original data sequence; Step A12: Extract the raw environmental data at time tk, including temperature. ,humidity air pressure And added a secondary temperature term Characterize the nonlinear effects of temperature and form a complete set of environmental features. ; Step A13: Accurately align the time deviation data with the environmental data using timestamps, and remove outliers using the Grubbs criterion to ensure the consistency and validity of the dataset.

[0014] Step A2: Construct a multivariate multinomial regression model containing linear terms, quadratic terms, and optional interaction terms; fit the model coefficients based on the preprocessed data and verify the fitting effect. Step A2 specifically includes: Step A21: Construct a multivariate multinomial regression model, the expression of which is:

[0015] in , , , , The coefficients are those of the model to be fitted. To satisfy the normal distribution The random error term; Step A22: Based on the preprocessed frequency error data Using the environmental feature set, the least squares method is used to fit the model coefficients, and the coefficients of determination are used to determine the model. To verify the fitting effect, the requirements are as follows: To ensure the explanatory power of the model; Step A23: If Supplement temperature and humidity interaction items Or the second term of air pressure Optimize the model structure and re-execute the fitting process until the goodness-of-fit requirement is met, ensuring that the model can accurately represent the influence of environmental factors on timekeeping accuracy.

[0016] Step A3: Through standardized analysis of model coefficients, quantify the individual influence weights and nonlinear contributions of temperature, humidity, and air pressure on timekeeping accuracy, and output the quantification results for performance evaluation.

[0017] A time synchronization device timing accuracy testing device, comprising: Dual-channel RF switch module: Used to dynamically control the signal connection and disconnection between an external signal source and a time synchronization device to simulate a time-keeping scenario where the external signal is interrupted; this module is the key execution unit for simulating an external synchronization source interruption. By dynamically controlling the connection and disconnection of two independent high-precision satellite navigation signals (such as GPS / BeiDou), the system can accurately switch the device under test to a "time-keeping" state within milliseconds, providing stable and reproducible initial conditions for testing.

[0018] Environmental monitoring unit: Used to synchronously collect environmental data in the test environment, including temperature, humidity, and air pressure, during the timed scenario phase of the simulated signal interruption. This unit has built-in high-precision sensors for temperature, humidity, air pressure, and other parameters, and can synchronously collect data with time deviations, recording the environmental profile of the entire test process. This provides raw data support for subsequent analysis of how environmental factors affect crystal oscillator performance.

[0019] Signal analysis interface: used to continuously acquire and record the time signal output by the time synchronization device during the timekeeping scenario phase of analog signal interruption, and compare the acquired time signal with the high-precision reference clock inside the system to form time deviation data; this interface is responsible for receiving and parsing the time synchronization signal (such as PTP, IRIG-B, etc.) output by the device under test, and comparing it with the high-precision atomic clock or rubidium clock inside the system to generate the original time deviation data stream.

[0020] Software control system: The instantaneous time deviation is calculated using a time interval error algorithm, and the frequency stability of the internal crystal oscillator is analyzed at different time scales using the Allan variance algorithm; By linking time deviation data with environmental data and modeling, the impact of environmental factors on timekeeping accuracy is quantified, and an evaluation report containing multi-dimensional performance indicators is generated.

[0021] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: 1. This invention, through deep integration of software and hardware, transforms the originally cumbersome and error-prone manual testing process into a standardized automated procedure. This not only greatly improves testing efficiency, but more importantly, it ensures that every test is conducted under exactly the same conditions, thereby obtaining highly consistent and reproducible test results, providing a solid foundation for performance comparison and reliability verification; 2. This invention, by integrating an environmental monitoring unit, enables testing in dynamic, real-world environments and utilizes advanced data analysis algorithms to accurately quantify the impact of environmental factors on timekeeping accuracy. This capability makes the test results more valuable and provides forward-looking guidance for the deployment of equipment in different geographical regions and climatic conditions.

[0022] 3. By employing methods such as Time Interval Error (TIE) and Allan variance, this invention provides an objective, multi-dimensional performance profile that includes multiple key parameters such as frequency drift, stability, and aging rate. This not only solves the problems of strong subjectivity and limited information in traditional evaluation methods, but also provides scientific and authoritative decision-making basis for equipment manufacturers in product development and optimization, as well as system integrators in equipment selection and system design. Attached Figure Description

[0023] The present invention will be described by way of example and with reference to the accompanying drawings, wherein: Figure 1 This is a schematic diagram of the process structure of the present invention; Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0025] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0026] It should be noted that, unless otherwise specified, the embodiments and features described in this invention can be combined with each other.

[0027] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0028] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can include direct contact between the first and second features, or contact between the first and second features through another feature between them. Furthermore, "above," "over," and "on top" of the second feature includes the first feature directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature includes the first feature directly below or diagonally below the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.

[0029] It should be noted that, unless otherwise specified, the embodiments and features described in this invention can be combined with each other.

[0030] Example 1

[0031] like Figure 1 As shown in the figure, an embodiment of the present invention discloses a method for testing the timekeeping accuracy of a time synchronization device, including: Step 1: A dual-channel RF switch is used to control the time synchronization device to maintain confidentiality with external signals, simulating normal operating conditions. Specifically: After system initialization and calibration, the test enters the baseline testing phase under normal operating conditions. At this stage, the software control system connects two stable and continuous satellite navigation signals to the device under test (DUT) via an RF switch module. Upon receiving the external high-precision timing signal, the DUT's internal clock is tamed and locked to an extremely high level of accuracy. During this period, the test system continuously acquires and records the deviation between the DUT's output signal and its internal reference clock using a signal analysis interface. This data serves as the performance baseline of the DUT under "ideal" external synchronization source support, used for subsequent performance comparison and analysis under "time-keeping" conditions.

[0032] By using a dual-channel RF switch, the signal connection and disconnection between the external signal source and the time synchronization device are dynamically controlled to simulate a timekeeping scenario where the external signal is interrupted. Specifically: After the baseline test is completed, the system will automatically enter the core timekeeping capability test phase—the simulated signal interruption test. According to the preset test protocol, the software sends commands to the RF switch module to precisely disconnect one or all external satellite navigation signals. This operation instantly pushes the device under test into a state where it relies entirely on its internal crystal oscillator for autonomous timekeeping.

[0033] From the moment the signal is interrupted, the signal analysis interface will continuously monitor and record the time deviation between the output signal of the device under test (DUT) and the high-precision reference clock inside the system at an extremely high sampling frequency (e.g., once per second or higher). This deviation will gradually increase over time, and its rate and shape of change (e.g., linear drift, random walk, etc.) directly reflect the stability of the crystal oscillator inside the DUT. The test system will continuously and uninterruptedly acquire this massive amount of time deviation data over several days or even weeks, providing a complete dataset for evaluating its long-term timekeeping performance.

[0034] Step 2: In the timekeeping scenario stage of simulated signal interruption, continuously collect and record the time signal output by the time synchronization device, and compare the collected time signal with the high-precision reference clock inside the system to form time deviation data; During the timed scenario phase of simulating signal interruption, environmental data in the test environment, including temperature, humidity, and air pressure data, are collected synchronously. The environmental data acquisition methods described in step 2 include passive correlation acquisition and active environmental stress acquisition; Passive correlation analysis: Throughout the signal interruption test, the environmental monitoring unit and the signal analysis interface work synchronously, recording environmental data such as temperature and humidity in real time. After the test, the data analysis module will perform correlation analysis on these two parallel data streams to establish a mathematical model between time deviation and environmental variables.

[0035] The active environmental stress acquisition method places the device under test (DUT) in a controlled environmental stress chamber (such as a high / low temperature chamber or a humidity chamber), and actively applies different environmental stresses by changing environmental conditions (such as temperature variations from -40°C to +85°C). The test system repeatedly performs signal interruption tests under different environmental conditions to obtain timekeeping performance data under specific environmental profiles. This active testing method can more clearly reveal how environmental factors systematically affect the frequency stability of crystal oscillators, providing a more convincing basis for equipment reliability design and deployment strategies.

[0036] Step 3: Based on the collected time deviation data sequence, the instantaneous time deviation is calculated using the time interval error algorithm, and the Allan variance algorithm is used to analyze the frequency stability of the internal crystal oscillator at different time scales; Step 3, specifically the calculation of the instantaneous time deviation using the time interval error algorithm, includes: Determine the output timestamp of the time synchronization device under test at time t, denoted as . ; Determine the ideal timestamp of the system's internal high-precision reference clock at time t, denoted as . ; Will and Substitute into the formula The instantaneous time deviation at time t is calculated.

[0037] Step 3, which involves using the Allan variance algorithm to analyze the frequency stability of the internal crystal oscillator at different time scales, specifically includes: The time deviation data sequence is continuously divided into blocks according to a fixed time length τ; Calculate the average of all time deviation samples within each data block to obtain the mean sequence. ; Calculate the mean of two adjacent sequences and The sum of squared differences is calculated and normalized to obtain the Allen variance for the corresponding time scale τ. ; Through the obtained multiple Allen variance values This process generates Allan variance curves across multiple time scales τ to identify the noise types within the crystal oscillator. By obtaining multiple Allan variance values ​​σ_y²(τ), a multi-time-scale Allan variance curve is formed. This curve clearly reveals five typical noise types present in the crystal oscillator: white noise, flicker noise, random walk noise, white frequency noise, and white phase noise. For example, at short time scales, the magnitude of the Allan variance value primarily reflects the level of white noise; while at longer time scales, it more significantly reflects the influence of random walk noise (i.e., frequency drift). This multi-dimensional analytical capability is unmatched by traditional, simple mean or maximum value evaluation methods.

[0038] Following step 3, there is also a crystal oscillator error compensation step, which specifically includes: Linear regression analysis was performed on the acquired instantaneous time deviation (TIE) data to establish a crystal oscillator aging rate model, which characterizes the natural drift trend of the crystal oscillator frequency over time. By correlating the collected temperature data with TIE data, a crystal oscillator frequency-temperature characteristic model was established to reveal the frequency drift characteristics of the crystal oscillator at different temperatures. The crystal oscillator aging rate model, frequency-temperature characteristic model, crystal oscillator noise type parameters, real-time acquired time deviation data and temperature data are input into the Kalman filter. The Kalman filter uses the system dynamic model and measurement data to make the optimal estimate and prediction of the instantaneous frequency error of the crystal oscillator and outputs the error estimate and prediction results.

[0039] Step 4: Correlate the time deviation data with the environmental data to quantify the impact of environmental factors on timekeeping accuracy and generate an evaluation report containing multi-dimensional performance indicators.

[0040] Step 4, specifically the correlation modeling of time deviation data and environmental data, includes: Step A1: Preprocess the time deviation data output from Step 3 and the synchronously acquired environmental data, calculate the instantaneous frequency error using the finite difference method, and extract the environmental data set containing nonlinear characteristics; Step A1 specifically includes: Step A11: Based on the instantaneous time deviation data sequence (k=1, 2…n, where n is the number of samples), the first-order central difference method is used to calculate the time. instantaneous frequency error The first and last samples are supplemented by forward difference (k=1) and backward difference (k=n) respectively to ensure that the frequency error sequence is consistent with the length of the original data sequence; Step A12: Extract the raw environmental data at time tk, including temperature. ,humidity air pressure And added a secondary temperature term Characterize the nonlinear effects of temperature and form a complete set of environmental features. ; Step A13: Accurately align the time deviation data with the environmental data using timestamps, and remove outliers using the Grubbs criterion to ensure the consistency and validity of the dataset.

[0041] Step A2: Construct a multivariate multinomial regression model containing linear terms, quadratic terms, and optional interaction terms; fit the model coefficients based on the preprocessed data and verify the fitting effect. Step A2 specifically includes: Step A21: Construct a multivariate multinomial regression model, the expression of which is:

[0042] in , , , , The coefficients are those of the model to be fitted. To satisfy the normal distribution The random error term; Step A22: Based on the preprocessed frequency error data Using the environmental feature set, the least squares method is used to fit the model coefficients, and the coefficients of determination are used to determine the model. To verify the fitting effect, the requirements are as follows: To ensure the explanatory power of the model; Step A23: If Supplement temperature and humidity interaction items Or the second term of air pressure Optimize the model structure and re-execute the fitting process until the goodness-of-fit requirement is met, ensuring that the model can accurately represent the influence of environmental factors on timekeeping accuracy.

[0043] Step A3: Through standardized analysis of model coefficients, quantify the individual influence weights and nonlinear contributions of temperature, humidity, and air pressure on timekeeping accuracy, and output the quantification results for performance evaluation.

[0044] Example 2

[0045] A time synchronization device timing accuracy testing device, comprising: Dual-channel RF switch module: Used to dynamically control the signal connection and disconnection between an external signal source and a time synchronization device to simulate a time-keeping scenario where the external signal is interrupted; this module is the key execution unit for simulating an external synchronization source interruption. By dynamically controlling the connection and disconnection of two independent high-precision satellite navigation signals (such as GPS / BeiDou), the system can accurately switch the device under test to a "time-keeping" state within milliseconds, providing stable and reproducible initial conditions for testing.

[0046] The performance of this module is crucial, as its key parameters directly affect the accuracy of test results. For example, isolation measures the degree of signal attenuation between the input and output terminals of a switch in the "off" state. A switch with high isolation (typically ≥70dB) ensures that unselected signal sources do not cause perceptible interference to the device under test when switching signal paths, thus guaranteeing a clean test environment and adhering to the principle of single variable. Insertion loss refers to the signal power loss introduced by the switch in the "on" state, and its typical value should be controlled within ≤0.35dB. Lower insertion loss means less energy loss after the signal passes through the switch, more accurately reflecting the original signal quality and avoiding test deviations caused by signal attenuation. Switching speed is usually measured by pull-in and release times, with typical requirements of pull-in time ≤10ms and release time ≤5ms. This parameter determines the response speed of the test system to changes in the state of the external signal source, and is crucial for evaluating the dynamic performance of the device under test (e.g., the response time of a phase-locked loop) during rapid signal interruption or recovery. See Table 1 for details.

[0047] Table 1 Key performance parameters of the dual-channel RF switch module and their impact on test results

[0048] Environmental monitoring unit: Used to synchronously collect environmental data in the test environment, including temperature, humidity, and air pressure, during the timed scenario phase of the simulated signal interruption. This unit has built-in high-precision sensors for temperature, humidity, air pressure, and other parameters, and can synchronously collect data with time deviations, recording the environmental profile of the entire test process. This provides raw data support for subsequent analysis of how environmental factors affect crystal oscillator performance.

[0049] In critical sectors such as power systems, relevant testing procedures (such as DL / T1507-2016) explicitly require verification of equipment performance under different environmental stresses. This unit is designed to meet this need, enabling the capture of realistic and dynamic environmental profiles through deployment at test sites (such as laboratories or substations). This not only helps reveal the frequency drift characteristics of the crystal oscillator inside the device under test under different temperature and humidity conditions but also provides a forward-looking assessment basis for the reliability of the equipment in extreme or dynamically changing real-world application scenarios.

[0050] Signal analysis interface: used to continuously acquire and record the time signal output by the time synchronization device during the timekeeping scenario phase of analog signal interruption, and compare the acquired time signal with the high-precision reference clock inside the system to form time deviation data; this interface is responsible for receiving and parsing the time synchronization signal (such as PTP, IRIG-B, etc.) output by the device under test, and comparing it with the high-precision atomic clock or rubidium clock inside the system to generate the original time deviation data stream.

[0051] At the heart of this interface is a high-precision time interval analyzer capable of measuring the time difference between two events at nanosecond or even higher resolution. The system's internal reference clock source, typically an atomic clock or a rubidium clock disciplined by an external high-precision time source (such as GPS), boasts extremely high long-term stability, ensuring the accuracy of the test benchmark. By continuously comparing the signal from the device under test with this stable benchmark, the system obtains a high-sampling-rate time error sequence, which forms the basis for the effective operation of all subsequent advanced data analysis algorithms (such as Allan ANOVA).

[0052] Software control system: The instantaneous time deviation is calculated using a time interval error algorithm, and the frequency stability of the internal crystal oscillator is analyzed at different time scales using the Allan variance algorithm; By linking time deviation data with environmental data and modeling, the impact of environmental factors on timekeeping accuracy is quantified, and an evaluation report containing multi-dimensional performance indicators is generated.

[0053] The circuits, electronic components, and modules involved are all existing technologies, which can be fully implemented by those skilled in the art, and need not be elaborated upon. The scope of protection of this invention does not involve any improvement to the software and methods.

[0054] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0055] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for testing the timekeeping accuracy of a time synchronization device, characterized in that, include: Step 1: Dynamically control the signal connection and disconnection between the external signal source and the time synchronization device through a dual-channel RF switch to simulate a timekeeping scenario where the external signal is interrupted; Step 2: In the timekeeping scenario stage of simulated signal interruption, continuously collect and record the time signal output by the time synchronization device, and compare the collected time signal with the high-precision reference clock inside the system to form time deviation data; During the timed scenario phase of simulating signal interruption, environmental data in the test environment, including temperature, humidity, and air pressure data, are collected synchronously. Step 3: Based on the collected time deviation data sequence, the instantaneous time deviation is calculated using the time interval error algorithm, and the Allan variance algorithm is used to analyze the frequency stability of the internal crystal oscillator at different time scales; Step 4: Correlate the time deviation data sequence with environmental data to quantify the impact of environmental factors on timekeeping accuracy and generate an evaluation report containing multi-dimensional performance indicators.

2. The time synchronization device timing accuracy testing method according to claim 1, characterized in that, Step 3, specifically the calculation of the instantaneous time deviation using the time interval error algorithm, includes: Determine the output timestamp of the time synchronization device under test at time t, denoted as . ; Determine the ideal timestamp of the system's internal high-precision reference clock at time t, denoted as . ; Will and Substitute into the formula The instantaneous time deviation at time t is calculated.

3. The time synchronization device timing accuracy testing method according to claim 1, characterized in that, Step 3, which involves using the Allan variance algorithm to analyze the frequency stability of the internal crystal oscillator at different time scales, specifically includes: The time deviation data sequence is continuously divided into blocks according to a fixed time length τ; Calculate the average of all time deviation samples within each data block to obtain the mean sequence. ; Calculate the mean of two adjacent sequences and The sum of squared differences is calculated and normalized to obtain the Allen variance for the corresponding time scale τ. ; Through the obtained multiple Allen variance values This generates Allan variance curves with multiple time scales τ, which helps identify the noise type of the internal crystal oscillator.

4. The time synchronization device timing accuracy testing method according to claim 3, characterized in that, Between steps 3 and 4, there is also a crystal oscillator error compensation step, which specifically includes: Linear regression analysis was performed on the acquired instantaneous time deviation (TIE) data to establish a crystal oscillator aging rate model, which characterizes the natural drift trend of the crystal oscillator frequency over time. By correlating the collected temperature data with TIE data, a crystal oscillator frequency-temperature characteristic model was established to reveal the frequency drift characteristics of the crystal oscillator at different temperatures. The crystal oscillator aging rate model, frequency-temperature characteristic model, crystal oscillator noise type parameters, real-time acquired time deviation data and temperature data are input into the Kalman filter. The Kalman filter uses the system dynamic model and measurement data to make the optimal estimate and prediction of the instantaneous frequency error of the crystal oscillator and outputs the error estimate and prediction results.

5. The time synchronization device timing accuracy test method according to claim 1, characterized in that, Step 4, specifically the association modeling of the time deviation data sequence with environmental data, includes: Step A1: Preprocess the time deviation data output from Step 3 and the synchronously acquired environmental data, calculate the instantaneous frequency error using the finite difference method, and extract the environmental data set containing nonlinear characteristics; Step A2: Construct a multivariate multinomial regression model that includes linear terms, quadratic terms, and optional interaction terms; fit the model coefficients based on the preprocessed data and verify the fitting effect. Step A3: Through standardized analysis of model coefficients, quantify the individual influence weights and nonlinear contributions of temperature, humidity, and air pressure on timekeeping accuracy, and output the quantification results for performance evaluation.

6. The time synchronization device timing accuracy test method according to claim 5, characterized in that, Step A1 specifically includes: Step A11: Based on the instantaneous time deviation data sequence (k=1, 2…n, where n is the number of samples), the first-order central difference method is used to calculate the time. instantaneous frequency error The first and last samples are supplemented by forward difference (k=1) and backward difference (k=n) respectively to ensure that the frequency error sequence is consistent with the length of the original data sequence; Step A12: Extract the raw environmental data at time tk, including temperature. ,humidity air pressure And added a secondary temperature term Characterize the nonlinear effects of temperature and form a complete set of environmental features. ; Step A13: Accurately align the time deviation data with the environmental data using timestamps, and remove outliers using the Grubbs criterion to ensure the consistency and validity of the dataset.

7. The time synchronization device timing accuracy testing method according to claim 5, characterized in that, Step A2 specifically includes: Step A21: Construct a multivariate multinomial regression model, the expression of which is: in , , , , The coefficients are those of the model to be fitted. To satisfy the normal distribution The random error term; Step A22: Based on the preprocessed frequency error data Using the environmental feature set, the least squares method is used to fit the model coefficients, and the coefficients of determination are used to determine the model. To verify the fitting effect, the requirements are as follows: To ensure the explanatory power of the model; Step A23: If Supplement temperature and humidity interaction items Or the second term of air pressure Optimize the model structure and re-execute the fitting process until the goodness-of-fit requirement is met, ensuring that the model can accurately represent the influence of environmental factors on timekeeping accuracy.

8. The time synchronization device timing accuracy testing method according to claim 1, characterized in that, The environmental data acquisition methods described in step 2 include passive correlation acquisition and active environmental stress acquisition; The active environmental stress acquisition is achieved through a controllable environmental stress chamber, simulating temperature changes and corresponding humidity and air pressure gradient changes.

9. The time synchronization device timing accuracy test method according to claim 1, characterized in that, In step 1, a dual-channel RF switch is used to control the time synchronization device to maintain cleanliness with external signals in order to simulate normal operating conditions.

10. A time synchronization device timing accuracy testing equipment, characterized in that, A method for testing the timekeeping accuracy of a time synchronization device as described in claims 1-7 includes: Dual-channel RF switch module: used to dynamically control the signal connection and disconnection between an external signal source and a time synchronization device to simulate a timekeeping scenario where the external signal is interrupted; Environmental monitoring unit: used to synchronously collect environmental data in the test environment, including temperature, humidity and air pressure data, during the time-keeping scenario phase of simulated signal interruption; Signal analysis interface: used to continuously acquire and record the time signal output by the time synchronization device during the timekeeping scenario phase of analog signal interruption, and compare the acquired time signal with the high-precision reference clock inside the system to form time deviation data; Software control system: The instantaneous time deviation is calculated using a time interval error algorithm, and the frequency stability of the internal crystal oscillator is analyzed at different time scales using the Allan variance algorithm; By linking time deviation data with environmental data and modeling, the impact of environmental factors on timekeeping accuracy is quantified, and an evaluation report containing multi-dimensional performance indicators is generated.

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