Rubidium atomic clock intelligent detection method and detection card

Abstract

The invention discloses a rubidium atomic clock intelligent detection method and a detection card, and relates to the technical field of rubidium atomic clocks, and the method comprises the following steps: monitoring the working state of a rubidium atomic clock in real time, and collecting the data of the rubidium atomic clock and the environmental parameters around the rubidium atomic clock in real time; performing real-time analysis and processing on the acquired data according to an Allan variance analysis algorithm and a linear fitting algorithm so as to evaluate the performance of the rubidium atomic clock; a data processing result is fed back to a monitoring system for adjusting the working state of the rubidium atomic clock so as to optimize the performance of the rubidium atomic clock; the rubidium atomic clock has the advantages of being miniaturized, convenient to carry, low in cost, high in real-time performance and capable of achieving multi-parameter monitoring, real-time monitoring and fault early warning of the state of the rubidium atomic clock can be achieved, and a solid foundation is laid for high-precision navigation.

Description

Technical Field

[0001] The present application relates to the technical field of rubidium atomic clocks, and in particular to an intelligent detection method and detection card for rubidium atomic clocks. Background Art

[0002] The rubidium atomic clock is a high-precision time standard device based on the precise oscillation behavior of rubidium atoms. It provides a high-precision time standard by exciting and measuring the transition frequency of rubidium atoms. The application of rubidium atomic clocks in satellite navigation systems is particularly critical. Satellite navigation systems rely on the high-precision time reference provided by rubidium atomic clocks to ensure the accuracy and stability of navigation signals, thereby achieving accurate positioning and timing services. Although rubidium atomic clocks have high precision and stability, in actual operation, rubidium atomic clocks may be affected by a variety of factors, such as temperature changes, electromagnetic interference, mechanical vibration, etc. These factors may cause the frequency drift or deviation of rubidium atomic clocks, affecting the accuracy of their time measurement. Traditional monitoring methods usually rely on manual regular inspections and manual data recording, which is not only inefficient, but also difficult to achieve real-time monitoring and rapid fault diagnosis. In addition, traditional monitoring methods often lack comprehensive monitoring of environmental parameters and cannot fully understand the impact of environmental changes on the performance of rubidium atomic clocks.

[0003] Although the existing rubidium atomic clock monitoring technology can achieve a certain degree of data collection and analysis, it still has the following shortcomings:

[0004] 1. Poor real-time performance: Traditional monitoring methods cannot achieve real-time data collection and analysis, the monitoring results are delayed, and it is difficult to detect and handle faults in time.

[0005] 2. Insufficient monitoring of environmental parameters: Existing technologies often only focus on the frequency data of rubidium atomic clocks, lack comprehensive monitoring of environmental parameters (such as temperature, humidity, pressure, etc.), and cannot comprehensively evaluate the impact of environmental changes on the performance of rubidium atomic clocks.

[0006] 3. Limited fault diagnosis capability: The existing technology has weak fault diagnosis capability and cannot accurately determine the specific fault type and cause of the rubidium atomic clock, making it difficult to provide effective fault solutions.

[0007] 4. Poor portability: Existing monitoring equipment is large in size, inconvenient to carry and install, which limits its use in various application scenarios.

[0008] 5. Poor cost and reliability: The manufacturing and deployment costs of rubidium atomic clocks are high, and their reliability and stability are crucial to the normal operation of the navigation system.

[0009] Therefore, the present application provides a rubidium atomic clock intelligent detection method and detection card, aiming to solve the above-mentioned defects of the prior art. Summary of the invention

[0010] In order to solve the above problems, the present application provides a rubidium atomic clock intelligent detection method and detection card, which has the advantages of miniaturization, portability, low cost, high real-time performance and multi-parameter monitoring, and can realize real-time monitoring of the state of the rubidium atomic clock and fault warning, laying a solid foundation for high-precision navigation. The technical solution is as follows:

[0011] The first aspect of the present application provides an intelligent detection method for a rubidium atomic clock, comprising the following steps: real-time monitoring of the working state of the rubidium atomic clock, and real-time collection of data of the rubidium atomic clock and environmental parameters around the rubidium atomic clock; real-time analysis and processing of the collected data according to an Allan variance analysis algorithm and a linear fitting algorithm to evaluate the performance of the rubidium atomic clock; and feeding back the data processing results to a monitoring system for adjusting the working state of the rubidium atomic clock to optimize its performance.

[0012] For example, in the intelligent detection method of the rubidium atomic clock provided in one embodiment, the frequency data of the rubidium atomic clock is processed by the Allan variance analysis algorithm to calculate the performance parameters of the rubidium atomic clock, which specifically includes the following steps: first, the collected frequency data is preliminarily processed, including filtering, denoising and normalization; for a series of frequency measurement values, the Allan variance at different time intervals τ is calculated to evaluate the frequency stability; and different types of noise are identified through the Allan variance diagram.

[0013] For example, in the intelligent detection method for the rubidium atomic clock provided in one embodiment, the time scale corresponding to the minimum point of the Allan variance diagram is used as the basis for evaluating the frequency stability of the rubidium atomic clock.

[0014] For example, in the rubidium atomic clock intelligent detection method provided in one embodiment, the clock error model of the rubidium atomic clock satisfies the following formula:

[0015] x(t)=a+bt+0.5Dt*t+C(t) Formula (1);

[0016] Where a is the initial time deviation or initial phase deviation, b is the initial frequency deviation, D is the frequency drift rate, C(t) is the random change component, and t is time;

[0017] The instantaneous relative frequency deviation of the rubidium atomic clock satisfies the following formula:

[0018] y(t)=b+D*t+E(t) Formula (2);

[0019] Among them, E(t) is the random variation component;

[0020] The linear fitting algorithm uses formula (2) to fit the frequency data.

[0021] For example, in the intelligent detection method of the rubidium atomic clock provided in one embodiment, the frequency drift rate of the rubidium atomic clock is calculated by a linear fitting algorithm to compensate for the frequency output of the frequency standard, which specifically includes the following steps: linear fitting is performed on the collected frequency data of the rubidium atomic clock, and the frequency drift rate of the rubidium atomic clock is calculated through long-term data monitoring; then the frequency accuracy of the rubidium atomic clock is evaluated by comparing with the standard frequency source; the short-term and long-term frequency stability of the rubidium atomic clock is calculated, and a linear fitting mathematical model is established; the model is used to predict the frequency drift behavior of the rubidium atomic clock, and the data processing algorithm and parameters are continuously adjusted and optimized according to the actual data and the prediction results.

[0022] For example, in the intelligent detection method of the rubidium atomic clock provided in one embodiment, during the data processing process, 0 and 1 are used to classify data labels, wherein data in the normal range is marked as 1 and abnormal data is marked as 0. By comparing the calculated performance parameters of the rubidium atomic clock with the preset threshold, it is determined whether the rubidium atomic clock is in a normal working state. If a performance parameter exceeds the preset threshold, it is considered that the rubidium atomic clock is faulty. According to different performance parameter abnormalities, the specific fault type is identified, and corresponding solutions and suggestions are provided according to the identified fault type.

[0023] The second aspect of the present application provides a rubidium atomic clock intelligent detection card, including: a data acquisition module, used to collect data from the rubidium atomic clock and its surrounding environment, and convert analog signals into digital signals; a data processing module, used to perform Allan variance analysis and linear fitting algorithm; a display module, used to realize human-computer interaction and view the performance parameters and environmental physical parameters of the rubidium atomic clock; a communication module, including a communication protocol processor responsible for encapsulation and decapsulation of the rubidium atomic clock data and an antenna module for sending and receiving wireless signals to communicate and synchronize data with the outside world; a data interface module, used to connect to the rubidium atomic clock and control the rubidium atomic clock by sending commands and parameters.

[0024] For example, in the rubidium atomic clock intelligent detection card provided in one embodiment, the data acquisition module includes a frequency analyzer, a temperature sensor, a humidity sensor, a pressure sensor and corresponding interface circuits and signal conditioning circuits to collect the frequency stability, accuracy, drift rate and ambient temperature and humidity of the rubidium atomic clock, and convert the analog signal into a digital signal through an analog-to-digital converter for subsequent processing.

[0025] For example, in the rubidium atomic clock intelligent detection card provided in one embodiment, the data processing module integrates an embedded processor and a digital signal processor for executing Allan variance analysis and linear fitting algorithms. The data processing module also includes a memory for storing firmware, models and temporary data, and a power management circuit to provide a stable power supply for the data processing module.

[0026] For example, in the rubidium atomic clock smart detection card provided in one embodiment, when it is detected that the performance parameter of the rubidium atomic clock exceeds a preset threshold, a warning message is displayed through the display module, and an alarm signal is sent to an external monitoring system through the communication module.

[0027] The beneficial effects brought about by a rubidium atomic clock intelligent detection method and detection card provided in some embodiments of the present application are as follows: the present application can collect data of the rubidium atomic clock in real time through high-precision sensors to ensure the timeliness and accuracy of monitoring; it can collect and display environmental parameters around the rubidium atomic clock to help users understand the impact of the environment on the performance of the rubidium atomic clock, and has strong environmental adaptability; through the built-in machine learning algorithm, it can quickly and accurately diagnose the fault of the rubidium atomic clock, and provide solutions to improve maintenance efficiency; the rubidium atomic clock intelligent detection card is small in size, easy to carry and install, and suitable for various application scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the embodiments of this specification or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0029] Figure 1 This is the result diagram of Allan variance analysis algorithm calculation;

[0030] Figure 2 It is a linear fitting model diagram established by the linear fitting algorithm. DETAILED DESCRIPTION

[0031] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0032] Unless otherwise defined, the technical terms or scientific terms used in the present disclosure should be understood by people with ordinary skills in the field to which the present disclosure belongs. The "first", "second" and similar words used in the present disclosure do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0033] The present application provides a rubidium atomic clock intelligent detection method and detection card. The detection card has the advantages of miniaturization, portability, low cost, high real-time performance and multi-parameter monitoring. It can realize real-time monitoring of the state of the rubidium atomic clock and fault warning, laying a solid foundation for high-precision navigation.

[0034] The rubidium atomic clock intelligent detection card of the present application includes:

[0035] A data acquisition module is used to collect data from the rubidium atomic clock and its surrounding environment; the data acquisition module includes a frequency analyzer, a temperature sensor, a humidity sensor, a pressure sensor and corresponding interface circuits and signal conditioning circuits to collect the frequency stability, accuracy, drift rate and environmental temperature and humidity of the rubidium atomic clock, and convert the analog signal into a digital signal through an analog-to-digital converter for subsequent processing;

[0036] A data processing module, wherein the data processing module integrates an embedded processor and a digital signal processor for executing Allan variance analysis and linear fitting algorithms, and the data processing module also includes a memory for storing firmware, models and temporary data and a power management circuit to provide a stable power supply for the data processing module;

[0037] Display module, used to realize human-computer interaction and view the performance parameters of the rubidium atomic clock and environmental physical parameters;

[0038] A communication module, including a communication protocol processor responsible for encapsulation and decapsulation of rubidium atomic clock data and an antenna module for sending and receiving wireless signals to communicate and synchronize data with the outside world;

[0039] The data interface module is used to connect to the rubidium atomic clock and control the rubidium atomic clock by sending commands and parameters.

[0040] Specifically, the data acquisition module includes Pendulum's CNT-90 / 91 / 91R high-performance frequency analyzer, DS18B20 temperature sensor, HDC1080 humidity sensor, MBS3050 pressure sensor, and corresponding interface circuits and signal conditioning circuits to ensure that the data collected from the rubidium atomic clock and the surrounding environment are accurate. The above sensors and measuring devices convert analog signals into digital signals through analog-to-digital converters (ADCs) for subsequent processing;

[0041] The data processing module is based on the STM32F103zet6 Battleship development board, which integrates an embedded processor and a digital signal processor (DSP) to perform complex data processing algorithms such as Allan variance analysis and linear regression analysis.

[0042] The display module includes an OLED display and buttons. Users can interact with the rubidium atomic clock smart detection card through the OLED screen and buttons to view the performance parameters of the rubidium atomic clock and environmental physical parameters, such as frequency stability, accuracy, drift rate, temperature and humidity. When the rubidium atomic clock smart detection card detects a fault in the rubidium atomic clock, the fault information will be displayed on the OLED display to remind the user to take timely measures.

[0043] The communication module includes a communication protocol processor, an antenna and other modules. Through Bluetooth, Wi-Fi, 4G modules and USB or Ethernet interfaces, the rubidium atomic clock smart detection card can communicate and synchronize data with external computers, servers and other monitoring devices. Among them, the communication protocol processor is responsible for the encapsulation and decapsulation of the rubidium atomic clock data to ensure the reliability and security of data transmission, and the antenna is used to send and receive wireless signals.

[0044] The rubidium atomic clock intelligent detection card is connected to the rubidium atomic clock through the UART or SPI interface of the STM32F103ZET6 in the data interface module, and the rubidium atomic clock is controlled by sending commands and parameters, such as setting the working mode and adjusting the frequency. Use the GPIO interface of the STM32F103ZET6 to connect to the clock output pin of the rubidium atomic clock, and obtain the frequency data of the atomic clock through the GPIO interrupt or timer capture function. If the rubidium atomic clock provides digital output, directly connect it to the external interrupt or timer input pin of the STM32F103ZET6 to capture and process the frequency data.

[0045] The rubidium atomic clock intelligent detection card of the present application can quickly and accurately diagnose the fault of the rubidium atomic clock through the built-in machine learning algorithm, and provide solutions to improve maintenance efficiency.

[0046] Specifically, the method for performing intelligent detection on a rubidium atomic clock using the rubidium atomic clock intelligent detection card of the present application comprises the following steps:

[0047] Monitor the working status of the rubidium atomic clock in real time, and collect the data of the rubidium atomic clock and the environmental parameters around the rubidium atomic clock in real time;

[0048] The collected data are analyzed and processed in real time according to the Allan variance analysis algorithm and linear fitting algorithm to evaluate the performance of the rubidium atomic clock;

[0049] The data processing results are fed back to the monitoring system to adjust the working state of the rubidium atomic clock to optimize its performance.

[0050] Among them, the Allan variance analysis algorithm is a technique commonly used to evaluate frequency stability and noise characteristics, especially in fields such as clocks and inertial navigation systems. The Allan variance measures the stability of the average frequency of the frequency measurement data sequence over time. It works by calculating the variance between consecutive averages of frequency data samples, which can reveal the performance of the device under different observation time lengths. The Allan variance calculation formula is:

[0051]

[0052] in, is the Allan variance, y i is the i-th average of the M fractional frequency values ​​over the sampling interval τ.

[0053] The Allan variance analysis algorithm is used to process the frequency data of the rubidium atomic clock and calculate the performance parameters of the rubidium atomic clock, such as frequency stability and frequency drift rate. The specific steps include:

[0054] First, the collected frequency data is preliminarily processed, including filtering, denoising and normalization, to ensure the purity and consistency of the data;

[0055] For a series of frequency measurements, the Allan variance at different time intervals τ is calculated to evaluate the frequency stability;

[0056] Different types of noise can be identified through the Allan variance diagram (σ(τ)-τ diagram), such as white frequency noise, flicker noise, random walk noise, etc. The time scale corresponding to the minimum point of the Allan variance diagram can be used as a basis for evaluating frequency stability.

[0057] For example, based on the obtained rubidium atomic clock data numbered Z03-B-04, in order to ensure the calculation speed and reduce some workload, the first 150,000 data of all the data were intercepted to perform Allan variance calculation, and the change trend of Allan variance with time interval (Tau) was calculated and plotted. Figure 1 shown.

[0058] from Figure 1 It can be seen that: with the increase of time interval Tau, the Allan variance decreases significantly in the initial stage. This shows that on a shorter time scale, the frequency stability of the rubidium atomic clock is higher and the random noise is relatively less. At the same time, as the time interval Tau increases further, the Allan variance gradually tends to be stable, and even increases at some points. This indicates that there is a systematic frequency drift or periodic frequency change on a longer time scale, such as the influence of environmental factors (such as temperature changes). At about Tau = 100 seconds, the Allan variance reaches a lower point and then rises slightly. This minimum point shows that on this time scale, the frequency drift of the rubidium atomic clock is effectively controlled, achieving a higher frequency stability.

[0059] The physical structure of the frequency standard is always in the aging process during use, which will impose a unidirectional slow offset on the frequency output, which is particularly obvious in rubidium atomic clocks. If the frequency output of the frequency standard is to be compensated, it is necessary to accurately estimate the frequency offset and drift rate of the frequency standard at the correction time. The frequency drift rate of the rubidium atomic clock can be calculated based on the linear fitting algorithm.

[0060] The clock error model of the rubidium atomic clock satisfies the following formula:

[0061] x(t)=a+bt+0.5Dt*t+C(t) Formula (1);

[0062] Where a is the initial time deviation or initial phase deviation, b is the initial frequency deviation, D is the frequency drift rate, C(t) is the random change component, and t is time;

[0063] The instantaneous relative frequency deviation of the rubidium atomic clock satisfies the following formula:

[0064] y(t)=b+D*t+E(t) Formula (2);

[0065] Among them, E(t) is the random variation component;

[0066] The linear fitting algorithm uses formula (2) to fit the frequency data, and the frequency drift rate of the rubidium atomic clock is calculated by the linear fitting algorithm to compensate the frequency output of the frequency standard, which specifically includes the following steps:

[0067] Perform linear fitting on the collected rubidium atomic clock frequency data, and calculate the frequency drift rate of the rubidium atomic clock through long-term data monitoring;

[0068] Then compare it with the standard frequency source to evaluate the frequency accuracy of the rubidium atomic clock;

[0069] Calculate the short-term and long-term frequency stability of the rubidium atomic clock and establish a linear fitting mathematical model, such as Figure 2 As shown;

[0070] The model is used to predict the frequency drift behavior of the rubidium atomic clock, and the data processing algorithms and parameters are continuously adjusted and optimized based on the actual data and prediction results.

[0071] Among them, the short-term frequency output of the rubidium atomic clock has good linearity after being powered on for a long enough time. Using a linear model to make predictions within a shorter time scale (about 15 days) can achieve better results.

[0072] Real-time monitoring of the working status of the rubidium atomic clock, including frequency output and environmental parameters. The monitoring data is analyzed in real time by the DSP of the data processing module to evaluate the performance of the rubidium atomic clock. The data processing results are fed back to the monitoring system to adjust the working status of the rubidium atomic clock to optimize its performance.

[0073] During data processing, data labels are classified using 0 and 1, where data in the normal range is marked as 1 and abnormal data is marked as 0, which is helpful for subsequent fault diagnosis and data visualization. By comparing the calculated performance parameters (such as frequency stability and frequency drift rate) with the preset thresholds, it is determined whether the rubidium atomic clock is in normal working condition. If a performance parameter exceeds the preset threshold, it is considered that the rubidium atomic clock may be faulty. According to different performance parameter abnormalities, the specific fault type is identified. For example, if the frequency stability exceeds the normal range, it may be due to temperature fluctuations or electromagnetic interference; if the frequency drift rate is abnormal, it may be due to power supply fluctuations or mechanical vibrations. According to the identified fault type, corresponding solutions and suggestions are provided. For example, if the fault is caused by temperature fluctuations, it is recommended to strengthen temperature control or adjust environmental conditions; if the fault is caused by electromagnetic interference, it is recommended to take shielding measures or adjust the equipment layout.

[0074] When it is detected that the performance parameters of the rubidium atomic clock exceed the preset threshold, a warning message is displayed through the display module, and an alarm signal is sent to the external monitoring system through the communication module.

[0075] The rubidium atomic clock intelligent detection method and detection card of the present application can collect data of the rubidium atomic clock in real time through high-precision sensors, ensuring the timeliness and accuracy of monitoring; it can collect and display environmental parameters around the rubidium atomic clock, helping users understand the impact of the environment on the performance of the rubidium atomic clock, and has strong environmental adaptability; through the built-in machine learning algorithm, it can quickly and accurately diagnose the fault of the rubidium atomic clock, and provide solutions to improve maintenance efficiency; the rubidium atomic clock intelligent detection card is small in size, easy to carry and install, and suitable for various application scenarios.

[0076] Although the implementation scheme of the present application has been disclosed as above, it is not limited to the applications listed in the specification and implementation modes, and it can be fully applicable to various fields suitable for the present application. For those familiar with the art, additional modifications can be easily implemented. Therefore, without departing from the general concept defined by the claims and the scope of equivalents, the present application is not limited to the specific details and the illustrations shown and described herein.

Claims

1. A rubidium atomic clock intelligent detection method, characterized in that: The following steps are involved: Monitor the working status of the rubidium atomic clock in real time, and collect the data of the rubidium atomic clock and the environmental parameters around the rubidium atomic clock in real time; The collected data are analyzed and processed in real time according to the Allan variance analysis algorithm and linear fitting algorithm to evaluate the performance of the rubidium atomic clock; The data processing results are fed back to the monitoring system to adjust the working state of the rubidium atomic clock to optimize its performance.

2. The rubidium atomic clock intelligent detection method according to claim 1, characterized in that: The Allan variance analysis algorithm is used to process the frequency data of the rubidium atomic clock and calculate the performance parameters of the rubidium atomic clock, which specifically includes the following steps: First, the collected frequency data is preliminarily processed, including filtering, denoising and normalization; For a series of frequency measurements, the Allan variance at different time intervals τ is calculated to evaluate the frequency stability; Identify different types of noise using Allan variance plots.

3. The rubidium atomic clock intelligent detection method according to claim 2, characterized in that: The time scale corresponding to the minimum point of the Allan variance diagram is used as the basis for evaluating the frequency stability of the rubidium atomic clock.

4. The rubidium atomic clock intelligent detection method according to claim 1, characterized in that: The clock error model of the rubidium atomic clock satisfies the following formula: x(t)=a+bt+0.5Dt*t+C(t) Formula (1); Where a is the initial time deviation or initial phase deviation, b is the initial frequency deviation, D is the frequency drift rate, C(t) is the random change component, and t is time; The instantaneous relative frequency deviation of the rubidium atomic clock satisfies the following formula: y(t)=b+D*t+E(t) Formula (2); Among them, E(t) is the random variation component; The linear fitting algorithm uses formula (2) to fit the frequency data.

5. The rubidium atomic clock intelligent detection method according to claim 4, characterized in that: The frequency drift rate of the rubidium atomic clock is calculated by a linear fitting algorithm to compensate the frequency output of the frequency standard, which specifically includes the following steps: Perform linear fitting on the collected rubidium atomic clock frequency data, and calculate the frequency drift rate of the rubidium atomic clock through long-term data monitoring; Then compare it with the standard frequency source to evaluate the frequency accuracy of the rubidium atomic clock; Calculate the short-term and long-term frequency stability of the rubidium atomic clock and establish a linear fitting mathematical model, as shown in Figure 2; The model is used to predict the frequency drift behavior of the rubidium atomic clock. Based on the actual data and prediction results, the data processing algorithm and parameters are continuously adjusted and optimized to improve the accuracy of the prediction.

6. The rubidium atomic clock intelligent detection method according to claim 1, characterized in that: During the data processing process, 0 and 1 are used to classify data labels, where data in the normal range is marked as 1 and abnormal data is marked as 0. By comparing the calculated performance parameters of the rubidium atomic clock with the preset threshold, it is determined whether the rubidium atomic clock is in normal working condition. If a performance parameter exceeds the preset threshold, it is considered that the rubidium atomic clock is faulty. According to different performance parameter abnormalities, the specific fault type is identified, and corresponding solutions and suggestions are provided based on the identified fault type.

7. A rubidium atomic clock intelligent detection card, characterized in that: include: A data acquisition module is used to collect data from the rubidium atomic clock and its surrounding environment, and convert analog signals into digital signals; Data processing module, used to perform Allan variance analysis and linear fitting algorithm; Display module, used to realize human-computer interaction and view the performance parameters of the rubidium atomic clock and environmental physical parameters; A communication module, including a communication protocol processor responsible for encapsulation and decapsulation of rubidium atomic clock data and an antenna module for sending and receiving wireless signals to communicate and synchronize data with the outside world; The data interface module is used to connect to the rubidium atomic clock and control the rubidium atomic clock by sending commands and parameters.

8. The rubidium atomic clock intelligent detection card according to claim 7, characterized in that: The data acquisition module includes a frequency analyzer, a temperature sensor, a humidity sensor, a pressure sensor and corresponding interface circuits and signal conditioning circuits to collect the frequency stability, accuracy, drift rate and ambient temperature and humidity of the rubidium atomic clock, and convert the analog signal into a digital signal through an analog-to-digital converter for subsequent processing.

9. The rubidium atomic clock intelligent detection card according to claim 7, characterized in that: The data processing module integrates an embedded processor and a digital signal processor for executing Allan variance analysis and linear fitting algorithms. The data processing module also includes a memory for storing firmware, models and temporary data and a power management circuit to provide a stable power supply for the data processing module.

10. The rubidium atomic clock intelligent detection card according to claim 7, characterized in that: When it is detected that the performance parameters of the rubidium atomic clock exceed the preset threshold, a warning message is displayed through the display module, and an alarm signal is sent to the external monitoring system through the communication module.

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