An automatic test calibration system and method for a time signal purification system

Abstract

This application provides an automatic test calibration system and method for a time signal cleanup system. The method includes: determining the access mode and initial bandwidth candidate range of a noise unit based on a typical curve of a reference source; switching the noise unit according to the access mode to generate a noise test sequence by superimposing different noises; acquiring test signal parameters output by the device under test in response to the execution of the noise test sequence; determining the prediction deviation between the test signal parameters and the typical curve of the reference source, adjusting the noise test sequence according to the prediction deviation, iteratively testing and determining whether the prediction deviation determined by the test signal parameters meets a preset threshold; if not, optimizing the initial bandwidth candidate range to determine the optimal bandwidth range of the time signal cleanup system. The switching of different noises is achieved through a noise switching unit, thereby selecting the optimal bandwidth based on the noise and crystal oscillator characteristic curves to achieve better performance.

Description

Technical Field

[0001] This application relates to the field of time signal testing, specifically to an automatic test calibration system and method for a time signal purification system. Background Technology

[0002] Fiber optic time synchronization signal regeneration and purification equipment is used to purify noise in time synchronization signals such as 10MHz, 1PPS, and IRIG-B time codes transmitted through optical fibers, and is a core component of high-precision time synchronization systems. However, existing testing methods only focus on the "performance testing" of individual indicators, such as the stability and latency of the purified signal. Due to the complexity of actual usage environments, this type of testing cannot guide parameter optimization of the equipment, thus failing to enable the equipment to achieve better performance. Summary of the Invention

[0003] This application aims to provide an automatic testing and calibration system and method for a time signal purification system, which can monitor changes in equipment performance, improve the long-term stability of the equipment, and achieve better performance.

[0004] The technical solution of this application is implemented as follows: In a first aspect, this embodiment provides an automatic test and calibration method for a time signal cleanup system, including: The access mode and initial bandwidth candidate range of the noise unit are determined based on the typical curve of the reference source. The noise unit is switched according to the access mode to generate a noise test sequence by superimposing different noises. In response to the execution of the noise test sequence, the test signal parameters output by the device under test are acquired; The prediction deviation between the test signal parameters and the typical curve of the reference source is determined, and the noise test sequence is adjusted according to the prediction deviation. The test is iterated and it is determined whether the prediction deviation determined by the test signal parameters meets the preset threshold. If not, the initial bandwidth candidate interval is optimized to determine the optimal bandwidth interval of the time signal cleanup system.

[0005] In one specific embodiment, the output noise of the noise unit includes one or more of phase white noise, phase flicker noise, frequency white noise, frequency flicker noise, and random walk noise.

[0006] In one specific implementation, the access mode of the noise unit is determined based on a typical curve of the reference source, including: Obtain typical curves of the reference source, including phase noise curve, frequency stability curve and time stability curve; Identify the noise-sensitive frequency band, frequency-stabilized time window, and time-stabilized window in the typical curve of the reference source; The access mode of the noise unit is determined based on the noise-sensitive frequency band, the frequency stabilization time window, and the time stabilization window mapping corresponding noise. The access mode includes the noise type, noise addition location, and noise addition intensity.

[0007] In one specific implementation, switching the noise unit according to the access mode to generate a noise test sequence by superimposing different noises includes: An identifier is added to each noise segment according to the access mode, wherein the identifier is used to determine the execution time of each noise segment; The identified noise segments are superimposed in a preset order to generate a noise test sequence.

[0008] In one specific implementation, in response to the execution of a noise test sequence, test signal parameters output by the device under test are acquired, including: Determine the parameter type of the device under test, which includes one or more of 10MHz signal, 1PPS signal, and IRIG-B time code; The sampling frequency is determined based on the parameter type; Data of the corresponding parameter types were collected according to the time stamp of the noise test sequence.

[0009] In one specific implementation, the prediction deviation between the test signal parameters and the typical curve of the reference source is determined, and the noise test sequence is adjusted according to the prediction deviation. Iterative testing is performed until the prediction deviation of the test signal parameters is less than a preset threshold. Then, the optimal bandwidth range of the time signal cleanup system is determined, including: Extract the corresponding reference parameters from the typical curve of the reference source, and extract the actual parameters from the actual crystal oscillator curve, and calculate the drop rate based on the reference parameters and the actual parameters; If an initial bandwidth candidate interval is selected, and the drop rate is greater than a preset first threshold under a certain candidate interval, the original interval is shrunk to both sides based on the midpoint of the candidate interval to obtain a shrunk interval; or, if the drop rate is less than a preset second threshold, the original interval is expanded to both sides based on the midpoint of the candidate interval to obtain an expanded interval. If the expanded interval covers an adjacent candidate interval, the two intervals are merged to form a new bandwidth candidate interval. When the new bandwidth candidate interval is iteratively tested and the drop rate determined by the test signal parameters is less than a preset first threshold and greater than a preset second threshold, the bandwidth candidate interval is determined as the optimal bandwidth interval of the time signal purification system.

[0010] Secondly, this embodiment provides an automatic test and calibration system for a time signal purification system, comprising: An initialization module is used to determine the access mode and initial bandwidth candidate range of the noise unit based on the typical curve of the reference source; The sequence generation module is used to switch noise units according to the access mode to generate a noise test sequence by superimposing different noises. The parameter test acquisition module is used to acquire the test signal parameters output by the device under test in response to the execution of the noise test sequence. The bandwidth determination module is used to determine the prediction deviation between the test signal parameters and the typical curve of the reference source, so as to adjust the noise test sequence according to the prediction deviation, iterate the test and determine whether the prediction deviation determined by the test signal parameters meets the preset threshold. If not, the initial bandwidth candidate interval is optimized to determine the optimal bandwidth interval of the time signal purification system.

[0011] In one specific implementation, the initialization module includes: The curve acquisition unit is used to acquire typical curves of the reference source, including phase noise curve, frequency stability curve and time stability curve. The identification unit is used to identify the noise-sensitive frequency band, frequency stability time window, and time stability window in the typical curve of the reference source. The access mode determination unit is used to determine the access mode of the noise unit based on the noise-sensitive frequency band, the frequency stability time window, and the time stability window mapping corresponding noise. The access mode includes the noise type, the noise addition location, and the noise addition intensity.

[0012] In one specific embodiment, the sequence generation module includes: An identifier adding unit is used to add an identifier to each noise segment according to the access mode, wherein the identifier is used to determine the execution time of each noise segment; The sequence generation unit is used to superimpose identified noise segments in a preset order to generate a noise test sequence.

[0013] In one specific implementation, the bandwidth determination module includes: A reference parameter extraction unit is used to extract corresponding reference parameters from the typical curve of the reference source, and to extract actual parameters from the actual crystal oscillator curve, and to calculate the drop rate based on the reference parameters and the actual parameters. The bandwidth selection unit is used to select an initial bandwidth candidate interval. If the drop rate is greater than a preset first threshold under a certain candidate interval, the original interval is shrunk to both sides based on the midpoint of the candidate interval to obtain a shrunk interval. Alternatively, if the drop rate is less than a preset second threshold, the original interval is expanded to both sides based on the midpoint of the candidate interval to obtain an expanded interval. If the expanded interval covers an adjacent candidate interval, the two intervals are merged to form a new bandwidth candidate interval. The bandwidth determination unit is used to determine the bandwidth candidate interval as the optimal bandwidth interval of the time signal purification system when iteratively testing the new bandwidth candidate interval and ensuring that the drop rate determined by the test signal parameters is less than a preset first threshold and greater than a preset second threshold.

[0014] This application provides an automatic test calibration system and method for a time signal cleanup system. The method includes: determining the access mode and initial bandwidth candidate interval of a noise unit based on a typical curve of a reference source; switching the noise unit according to the access mode to generate a noise test sequence by superimposing different noises; acquiring test signal parameters output by the device under test in response to the execution of the noise test sequence; determining the prediction deviation between the test signal parameters and the typical curve of the reference source, adjusting the noise test sequence according to the prediction deviation, iteratively testing and determining whether the prediction deviation determined by the test signal parameters meets a preset threshold; if not, optimizing the initial bandwidth candidate interval to determine the optimal bandwidth interval of the time signal cleanup system. Thus, by switching between different noises through a noise switching unit, it can comprehensively cover interference scenarios in real engineering environments, and further select the optimal bandwidth based on noise and crystal oscillator characteristic curves, thereby enabling real-time monitoring of device performance changes, improving the long-term stability characteristics of the device, and achieving better performance. Attached Figure Description

[0015] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the specification, serve to explain the technical solutions of this application. Obviously, the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0016] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0017] Figure 1 A schematic flowchart of an automatic test calibration method for a time signal cleanup system provided in this application embodiment; Figure 2 This is a block diagram of an automatic test and calibration system module for a time signal purification system provided in an embodiment of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the specific technical solutions of this application will be further described in detail below with reference to the accompanying drawings of the embodiments of this application. The following embodiments are used to illustrate this application, but are not intended to limit the scope of this application.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0020] In the following description, references to "some embodiments," "this embodiment," "this application embodiment," and examples, etc., describe a subset of all possible embodiments. However, it is understood that "some embodiments" may be the same subset or different subset of all possible embodiments and may be combined with each other without conflict.

[0021] If the application documents contain similar descriptions such as "first / second", the following explanation shall be added: In the following description, the terms "first / second / third" are used only to distinguish similar objects and do not represent a specific order of objects. It is understood that "first / second / third" may be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0022] This application provides an automatic testing and calibration method for a time signal cleanup system. Figure 1 An optional flowchart illustrating an automatic test and calibration method for a time signal cleanup system provided in this application embodiment. Figure 1 , will combine Figure 1 The steps shown are explained, including: S1. Determine the access mode and initial bandwidth candidate range of the noise unit based on the typical curve of the reference source; Specifically, typical curves of the reference source can be extracted from the factory calibration documentation of the high-stability signal source or the calibration data pre-acquired by the test system. For example, the following information can be extracted from the phase noise curve: the frequency offset range covers 1Hz to 100kHz, and the key nodes include the phase noise values ​​at 1Hz, 10Hz, 100Hz, 1kHz, 10kHz, and 100kHz (reference specification: -160dBc@1kHz). The following information can be extracted from the frequency stability curve: the time interval covers 1s to 1000s, and the key nodes include the phase noise values ​​at time intervals covering 1s / 10s / 100s / 1000s (reference specification: 3E-13@1s). The following information can be extracted from the time stability curve: the time interval covers 1s to 1000s, and the key nodes include the time stability at time intervals covering 1s / 10s / 100s / 1000s (reference specification: 5ps@1s).

[0023] Furthermore, it is necessary to identify phase noise-sensitive frequency bands and frequency stability abrupt change windows, i.e., selecting frequency ranges where phase noise is greater than a preset value (e.g., frequency ranges > -140dBc@1kHz) to obtain initial bandwidth candidate ranges. Then, noise access modes can be mapped according to specific circumstances. For example, different frequency flicker noise and random walk noise can be selected for different frequency ranges to match the frequency domain weaknesses of the crystal oscillator; different phase white noise and phase flicker noise can be selected for different frequency stability abrupt change windows to match the time domain weaknesses of the crystal oscillator. In addition, noise can be added for mixed interference scenarios, setting different noise intensities for different ranges. Specific adjustments are made according to actual needs.

[0024] It should be noted that both the access mode and the initial bandwidth candidate range are achieved by switching the noise unit. Switching the noise unit allows for adjustments to the noise type, noise location, noise intensity, and noise duration.

[0025] S2. Switch the noise unit according to the access mode to generate a noise test sequence by superimposing different noises. In this step, the noise test sequence refers to controlling the noise unit to perform corresponding switching based on a time series, thereby superimposing the corresponding noise onto the current signal at the corresponding moment. That is, at a certain moment, there may be only one type of noise interference, or multiple types of noise interference may exist simultaneously. Even in a scenario with only one type of noise interference, there may be noise superposition of different intensities, thus simulating interference in complex fiber optic transmission. To avoid the influence of residual noise between different noises on the test results, preferably, each segment in the noise test sequence includes a noise-free interval. This noise-free interval allows the purification system to return to a stable state, avoiding the residual influence of preceding noise. The duration of this noise-free interval is determined based on the intensity and duration of the preceding noise. If the intensity and duration of the preceding noise are strong, the noise-free interval can be appropriately expanded; if the intensity and duration of the preceding noise are weak, the noise-free interval can be appropriately narrowed. It should be noted that each noise segment has a unique identifier to facilitate subsequent data correlation analysis.

[0026] To improve test accuracy, a noise feedback unit is also included. This unit reads the noise parameters output by the noise unit and determines whether parameters such as power spectral density and frequency shift meet requirements. If not, it indicates a defect in the noise superimposed on the signal, insufficient to reflect actual needs, leading to inaccurate test results. In this case, the test must be stopped and the noise parameters adjusted until the requirements are met. In practical scenarios, for tests with lower real-time requirements, post-test verification can be performed using logs. For example, an industrial control computer synchronously records the execution time, noise type, intensity parameters, and noise addition location of the noise test sequence, forming a "Noise Test Sequence Execution Log." The noise feedback unit periodically collects and stores noise parameters, allowing for subsequent deviation analysis based on the time series to trace the test scenario.

[0027] S3. In response to the execution of the noise test sequence, acquire the test signal parameters output by the device under test, which refers to the time signal purification system to be tested. The parameters acquired vary depending on the signal. For a 10MHz signal, parameters such as frequency stability and phase noise at a 1kHz offset point can be acquired. For a 1PPS signal, parameters such as time stability, delay deviation, and phase adjustment resolution can be acquired. For IRIG-B timecode, the time difference with the local timecode can be acquired. All parameters are marked according to the time corresponding to the test sequence. Similarly, in scenarios with high real-time requirements, the accuracy of the parameters needs to be judged in real time. If the acquired parameters clearly do not meet the requirements, acquisition needs to be stopped and a detailed inspection needs to be conducted to determine whether there is a hardware or software fault in the device under test. For tests with lower real-time requirements, post-test analysis is performed using logs.

[0028] S4. Determine the prediction deviation between the test signal parameters and the typical curve of the reference source, adjust the noise test sequence according to the prediction deviation, iterate the test and determine whether the prediction deviation determined by the test signal parameters meets the preset threshold. If not, optimize the initial bandwidth candidate interval to determine the optimal bandwidth interval of the time signal purification system.

[0029] Prediction bias can be calculated using the signal drop rate, with the basic formula: Signal drop rate (%) = (Noise-added parameter value - Noise-free reference value) / Noise-free reference value × 100%. When performing the calculation, the measurement uncertainty of the test system itself must also be considered. If the drop rate is less than the measurement uncertainty range, it is considered that there is no significant drop.

[0030] For the 10MHz frequency signal drop rate, the accuracy of the test results is determined by comparing the 10MHz frequency stability (test) output by the device under test with the 10MHz frequency stability (reference) under noise-free reference conditions, while also considering the uncertainty.

[0031] That is, it can be .

[0032] It should be noted that in actual testing, the drop rate generally varies slightly due to environmental changes such as temperature and humidity, as well as measurement uncertainty. For example, the uncertainty of the drop rate can be set to 5%, meaning that a fluctuation range of 5% is considered a valid measurement. A specific scenario is illustrated below: If the baseline value at a 1-second interval is 2.0E-13 / s, with an uncertainty of 5%, and the output Sy(1s) test value of the device under test after adding white noise at the same 1-second interval is 2.7E-13 / s, and the baseline value is 2.0E-13 / s, then the drop rate is (|2.7-2.0| / 2.0)×100% = 35%. With an uncertainty of 5%, a drop rate between 30% and 40% can be considered a valid measurement.

[0033] The fading rate of a 1PPS time signal is determined by the 1PPS time stability (στ(T) test) and time delay deviation (Δτ test) output by the device under test. The specific calculation method is similar to that for a 10MHz frequency signal fading rate, and will not be elaborated further here.

[0034] Once the optimal bandwidth range is determined, it can be used for factory verification of the device.

[0035] In one specific embodiment, the output noise of the noise unit includes one or more of phase white noise, phase flicker noise, frequency white noise, frequency flicker noise, and random walk noise.

[0036] Generally, the system provides basic parameters for the above noise types. During specific testing, these basic parameters can be adjusted to meet actual needs. For example, for phase white noise, adjusting the parameters degrades the stability from 2E-13 / 1s to 1E-11 / 1s, and the phase noise from -120dBc / Hz@1Hz to -90dBc / Hz@1Hz, primarily affecting 10MHz and 1PPS signals. For frequency flicker noise, adjusting the parameters degrades the frequency stability from 2E-13 / 1s to 5E-12 / 1s, primarily affecting 10MHz signals. For the superposition of random walk noise and phase noise, adjusting the parameters degrades the time stability from 2ps / 1s to 15ps / 1s, primarily affecting 1PPS signals.

[0037] The method in this embodiment achieves switching between different noises through a noise switching unit, which can fully cover interference scenarios in real engineering environments. Furthermore, it selects the optimal bandwidth based on the noise and crystal oscillator characteristic curves, thereby enabling real-time monitoring of equipment performance changes, improving the long-term stability of the equipment, and achieving better performance.

[0038] In one specific implementation, the access mode of the noise unit is determined based on a typical curve of the reference source, including: Obtain typical curves of the reference source, including phase noise curve, frequency stability curve and time stability curve; Identify the noise-sensitive frequency band, frequency-stabilized time window, and time-stabilized window in the typical curve of the reference source; The access mode of the noise unit is determined based on the noise-sensitive frequency band, the frequency stabilization time window, and the time stabilization window mapping corresponding noise. The access mode includes the noise type, noise addition location, and noise addition intensity.

[0039] The identification of typical curves of the reference source specifically involves analyzing the phase noise curve, extracting frequency offset points, and focusing on analyzing the phase noise values ​​at key frequency points such as 1Hz, 10Hz, 100Hz, 1kHz, 10kHz, and 100kHz. For the frequency stability curve, the focus is on analyzing the frequency stability values ​​at key time intervals such as 1s, 10s, 100s, and 1000s. For the time stability curve, the focus is on analyzing the time stability values ​​at key time intervals such as 1s, 10s, 100s, and 1000s.

[0040] The interval where the phase noise is greater than or equal to a preset threshold is defined as the noise-sensitive frequency band (in this embodiment, for example, the frequency interval >-140dBc / Hz is defined as the noise-sensitive frequency band), specifically by traversing the entire frequency interval to select the noise-sensitive frequency interval.

[0041] Similarly, the time interval between the frequency change rate being less than or equal to a preset threshold is defined as the frequency stable time window (in this embodiment, for example, the time interval between ≤3E-15 is defined as the frequency stable time window). Likewise, the frequency stable time window is selected by traversing the inflection points of the curve.

[0042] Similarly, the time interval range where the time stability value is less than or equal to a preset threshold is defined as the time stability window (in this embodiment, for example, the time interval range ≤10ps is defined as the time stability window). Likewise, the time stability window is selected by traversing the inflection points of the curve.

[0043] The specific mapping can be performed through instructions. For example, the mapping instruction format is [noise type encoding, noise location encoding, noise intensity value, test duration].

[0044] In one specific implementation, switching the noise unit according to the access mode to generate a noise test sequence by superimposing different noises includes: An identifier is added to each noise segment according to the access mode, wherein the identifier is used to determine the execution time of each noise segment; The identified noise segments are superimposed in a preset order to generate a noise test sequence.

[0045] It should be noted that this identifier can be combined with mapping instructions, that is, additional timestamps and associated bandwidth encoding can be added to distinguish them.

[0046] In an embodiment, for example, it may include: generating a unique structured identifier for each noise scenario based on the noise access mode and the bandwidth candidate interval output by the crystal oscillator curve analysis module; matching the corresponding execution duration code and associated bandwidth code based on the test scenario to complete the definition of a single noise segment; splicing all noise segments in sequence according to a preset sorting logic, inserting a steady-state recovery interval, and converting the spliced ​​segment sequence into an instruction format recognizable by the noise switching unit to obtain a noise test sequence.

[0047] In one specific implementation, in response to the execution of a noise test sequence, test signal parameters output by the device under test are acquired, including: Determine the parameter type of the device under test, which includes one or more of 10MHz signal, 1PPS signal, and IRIG-B time code; The sampling frequency is determined based on the parameter type; Data of the corresponding parameter types were collected according to the time stamp of the noise test sequence.

[0048] It should be noted that before the test sequence is executed (i.e., before each segment is executed), the noise output parameters are detected and compared with the noise intensity code in the identifier. If the deviation is within an acceptable range, the segment is executed; otherwise, it needs to be re-executed. Similarly, for the acquired test signal parameters, if an abnormal drop in signal is found under a certain noise segment, the segment also needs to be re-executed.

[0049] In one specific implementation, the prediction deviation between the test signal parameters and the typical curve of the reference source is determined, and the noise test sequence is adjusted according to the prediction deviation. Iterative testing is performed until the prediction deviation of the test signal parameters is less than a preset threshold. Then, the optimal bandwidth range of the time signal cleanup system is determined, including: Extract the corresponding reference parameters from the typical curve of the reference source, and extract the actual parameters from the actual crystal oscillator curve, and calculate the drop rate based on the reference parameters and the actual parameters; If an initial bandwidth candidate interval is selected, and the drop rate is greater than a preset first threshold under a certain candidate interval, the original interval is shrunk to both sides based on the midpoint of the candidate interval to obtain a shrunk interval; or, if the drop rate is less than a preset second threshold, the original interval is expanded to both sides based on the midpoint of the candidate interval to obtain an expanded interval. If the expanded interval covers an adjacent candidate interval, the two intervals are merged to form a new bandwidth candidate interval. When the new bandwidth candidate interval is iteratively tested and the drop rate determined by the test signal parameters is less than a preset first threshold and greater than a preset second threshold, the bandwidth candidate interval is determined as the optimal bandwidth interval of the time signal purification system.

[0050] It should be noted that the aforementioned drop rate can be the drop rate of a single indicator, or it can be represented by a weighted average to form a comprehensive drop rate. For example, by using weighting coefficients, the 10MHz, 1PPS, and IRIG-B timecodes can be calculated together, such as: Comprehensive Drop Rate = 10MHz Drop Rate × 40% + 1PPS Drop Rate × 50% + IRIG-B Drop Rate × 10%. Of course, the specific weights can be adjusted according to the actual situation. If a weighted approach is not used, the calculation can be performed on only a single parameter. Regarding the settings of the preset first threshold and the preset second threshold, the preset first threshold is the upper limit of the drop rate. If it exceeds the upper limit, it indicates insufficient noise suppression, and the range needs to be narrowed. The preset second threshold is the lower limit of the drop rate. If it is below the lower limit, it indicates that redundant noise may be introduced, and the range needs to be expanded. After expansion, the expanded interval may cover adjacent candidate intervals, meaning that two originally independent intervals may overlap. In this case, it is necessary to determine whether to merge based on the degree of overlap (e.g., overlap greater than 50%). Specifically, during merging, it is also necessary to determine whether the merged region is too large; if it is too large, merging is not performed. This process continues until convergence is finally achieved.

[0051] Please see Figure 2 , Figure 2 An automatic test calibration system module block diagram of a time signal cleanup system provided in this application embodiment includes: An initialization module is used to determine the access mode and initial bandwidth candidate range of the noise unit based on the typical curve of the reference source; The sequence generation module is used to switch noise units according to the access mode to generate a noise test sequence by superimposing different noises. The parameter test acquisition module is used to acquire the test signal parameters output by the device under test in response to the execution of the noise test sequence. The bandwidth determination module is used to determine the prediction deviation between the test signal parameters and the typical curve of the reference source, adjust the noise test sequence according to the prediction deviation, iterate the test, and determine whether the prediction deviation determined by the test signal parameters meets a preset threshold. If not, the initial bandwidth candidate interval is optimized to determine the optimal bandwidth interval of the time signal cleanup system. It should be noted that the bandwidth candidate interval in this embodiment is, for example, the default bandwidth interval of the loop under different noise types or noise amplitudes, such as a default loop bandwidth interval of 0.1Hz to 10Hz.

[0052] In one specific implementation, the initialization module includes: The curve acquisition unit is used to acquire typical curves of the reference source, including phase noise curves and frequency stability curves. The identification unit is used to identify the noise-sensitive frequency band and frequency stability time window in the typical curve of the reference source; The access mode determination unit is used to determine the access mode of the noise unit based on the noise-sensitive frequency band and the corresponding noise mapped by the frequency stabilization time window, wherein the access mode includes noise type, noise addition location, and noise addition intensity.

[0053] In one specific embodiment, the sequence generation module includes: An identifier adding unit is used to add an identifier to each noise segment according to the access mode, wherein the identifier is used to determine the execution time of each noise segment; The sequence generation unit is used to superimpose identified noise segments in a preset order to generate a noise test sequence.

[0054] In one specific implementation, the bandwidth determination module includes: A reference parameter extraction unit is used to extract corresponding reference parameters from the typical curve of the reference source, and to extract actual parameters from the actual crystal oscillator curve, and to calculate the drop rate based on the reference parameters and the actual parameters. The bandwidth selection unit is used to select an initial bandwidth candidate interval. If the drop rate is greater than a preset first threshold under a certain candidate interval, the original interval is shrunk to both sides based on the midpoint of the candidate interval to obtain a shrunk interval. Alternatively, if the drop rate is less than a preset second threshold, the original interval is expanded to both sides based on the midpoint of the candidate interval to obtain an expanded interval. If the expanded interval covers an adjacent candidate interval, the two intervals are merged to form a new bandwidth candidate interval. The bandwidth determination unit is used to determine the bandwidth candidate interval as the optimal bandwidth interval of the time signal purification system when iteratively testing the new bandwidth candidate interval and ensuring that the drop rate determined by the test signal parameters is less than a preset first threshold and greater than a preset second threshold.

[0055] It should be understood that the phrases "one embodiment," "an embodiment," or "some embodiments" mentioned throughout the specification mean that a specific feature, structure, or characteristic related to an embodiment is included in at least one embodiment of this application. Therefore, "in one embodiment," "in one embodiment," or "in some embodiments" appearing throughout the specification do not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. It should be understood that in the various embodiments of this application, the sequence numbers of the above-described processes do not imply a sequential order of execution; the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application. The sequence numbers of the above-described embodiments are merely for descriptive purposes and do not represent the superiority or inferiority of the embodiments. The descriptions of the various embodiments above tend to emphasize the differences between the various embodiments; their similarities or commonalities can be referred to mutually, and for the sake of brevity, they will not be repeated here.

[0056] The modules described above as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules. They may be located in one place or distributed across multiple network units. Some or all of the modules may be selected to achieve the purpose of this embodiment according to actual needs.

[0057] In addition, each functional module in the various embodiments of this application can be integrated into one processing unit, or each module can be a separate unit, or two or more modules can be integrated into one unit; the integrated modules can be implemented in hardware or in the form of hardware plus software functional units.

[0058] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, read-only memory (ROM), magnetic disks, or optical disks.

[0059] The methods disclosed in the several method embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments.

[0060] The features disclosed in the several product embodiments provided in this application can be arbitrarily combined without conflict to obtain new product embodiments.

[0061] The features disclosed in the several method or device embodiments provided in this application can be arbitrarily combined without conflict to obtain new method or device embodiments.

[0062] The above description is merely an embodiment of this application, but the protection scope of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the protection scope of this application. Therefore, the protection scope of this application should be determined by the protection scope of the claims.

Claims

1. An automatic testing and calibration method for a time signal cleanup system, characterized in that, include: The access mode and initial bandwidth candidate range of the noise unit are determined based on the typical curve of the reference source. The noise unit is switched according to the access mode to generate a noise test sequence by superimposing different noises. In response to the execution of the noise test sequence, the test signal parameters output by the device under test are acquired; The prediction deviation between the test signal parameters and the typical curve of the reference source is determined, and the noise test sequence is adjusted according to the prediction deviation. The test is iterated and it is determined whether the prediction deviation determined by the test signal parameters meets the preset threshold. If not, the initial bandwidth candidate interval is optimized to determine the optimal bandwidth interval of the time signal cleanup system.

2. The automatic test and calibration method for the time signal purification system according to claim 1, characterized in that, The output noise of the noise unit includes one or more of phase white noise, phase flicker noise, frequency white noise, frequency flicker noise, and random walk noise.

3. The automatic test and calibration method for the time signal purification system according to claim 1, characterized in that, The noise unit's access mode is determined based on typical curves from a reference source, including: Obtain typical curves of the reference source, including phase noise curve, frequency stability curve and time stability curve; Identify the noise-sensitive frequency band, frequency-stabilized time window, and time-stabilized window in the typical curve of the reference source; The access mode of the noise unit is determined based on the noise-sensitive frequency band, the frequency stabilization time window, and the time stabilization window mapping corresponding noise. The access mode includes the noise type, noise addition location, and noise addition intensity.

4. The automatic test and calibration method for the time signal purification system according to claim 1, characterized in that, The noise unit is switched according to the access mode to generate a noise test sequence by superimposing different noises, including: An identifier is added to each noise segment according to the access mode, wherein the identifier is used to determine the execution time of each noise segment; The identified noise segments are superimposed in a preset order to generate a noise test sequence.

5. The automatic test and calibration method for the time signal purification system according to claim 1, characterized in that, In response to the execution of the noise test sequence, the test signal parameters output by the device under test are acquired, including: Determine the parameter type of the device under test, which includes one or more of 10MHz signal, 1PPS signal, and IRIG-B time code; The sampling frequency is determined based on the parameter type; Data of the corresponding parameter types were collected according to the time stamp of the noise test sequence.

6. The automatic test and calibration method for the time signal purification system according to claim 1, characterized in that, Determine the prediction deviation between the test signal parameters and the typical curve of the reference source, adjust the noise test sequence according to the prediction deviation, iterate the test, and determine the optimal bandwidth range of the time signal cleanup system when the prediction deviation of the test signal parameters is less than a preset threshold, including: Extract the corresponding reference parameters from the typical curve of the reference source, and extract the actual parameters from the actual crystal oscillator curve, and calculate the drop rate based on the reference parameters and the actual parameters; If an initial bandwidth candidate interval is selected, and the drop rate is greater than a preset first threshold under a certain candidate interval, the original interval is shrunk to both sides based on the midpoint of the candidate interval to obtain a shrunk interval; or, if the drop rate is less than a preset second threshold, the original interval is expanded to both sides based on the midpoint of the candidate interval to obtain an expanded interval. If the expanded interval covers an adjacent candidate interval, the two intervals are merged to form a new bandwidth candidate interval. When the new bandwidth candidate interval is iteratively tested and the drop rate determined by the test signal parameters is less than a preset first threshold and greater than a preset second threshold, the bandwidth candidate interval is determined as the optimal bandwidth interval of the time signal purification system.

7. An automatic test and calibration system for a time signal purification system, characterized in that, include: An initialization module is used to determine the access mode and initial bandwidth candidate range of the noise unit based on the typical curve of the reference source; The sequence generation module is used to switch noise units according to the access mode to generate a noise test sequence by superimposing different noises. The parameter test acquisition module is used to acquire the test signal parameters output by the device under test in response to the execution of the noise test sequence. The bandwidth determination module is used to determine the prediction deviation between the test signal parameters and the typical curve of the reference source, so as to adjust the noise test sequence according to the prediction deviation, iterate the test and determine whether the prediction deviation determined by the test signal parameters meets the preset threshold. If not, the initial bandwidth candidate interval is optimized to determine the optimal bandwidth interval of the time signal purification system.

8. The automatic test and calibration system for the time signal purification system according to claim 7, characterized in that, The initialization module includes: The curve acquisition unit acquires typical curves of the reference source, including phase noise curve, frequency stability curve, and time stability curve. The identification unit is used to identify the noise-sensitive frequency band, frequency stability time window, and time stability window in the typical curve of the reference source. The access mode determination unit determines the access mode of the noise unit based on the noise-sensitive frequency band, the frequency stability time window, and the time stability window mapping corresponding noise. The access mode includes the noise type, noise addition location, and noise addition intensity.

9. The automatic test and calibration system for the time signal purification system according to claim 7, characterized in that, The sequence generation module includes: An identifier adding unit is used to add an identifier to each noise segment according to the access mode, wherein the identifier is used to determine the execution time of each noise segment; The sequence generation unit is used to superimpose identified noise segments in a preset order to generate a noise test sequence.

10. The automatic test and calibration system for the time signal purification system according to claim 7, characterized in that, The bandwidth determination module includes: A reference parameter extraction unit is used to extract corresponding reference parameters from the typical curve of the reference source, and to extract actual parameters from the actual crystal oscillator curve, and to calculate the drop rate based on the reference parameters and the actual parameters. The bandwidth selection unit is used to select an initial bandwidth candidate interval. If the drop rate is greater than a preset first threshold under a certain candidate interval, the original interval is shrunk to both sides based on the midpoint of the candidate interval to obtain a shrunk interval. Alternatively, if the drop rate is less than a preset second threshold, the original interval is expanded to both sides based on the midpoint of the candidate interval to obtain an expanded interval. If the expanded interval covers an adjacent candidate interval, the two intervals are merged to form a new bandwidth candidate interval. The bandwidth determination unit is used to determine the bandwidth candidate interval as the optimal bandwidth interval of the time signal purification system when iteratively testing the new bandwidth candidate interval and ensuring that the drop rate determined by the test signal parameters is less than a preset first threshold and greater than a preset second threshold.

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