Frequency calibration method, device and equipment of crystal oscillator and storage medium

Abstract

The invention relates to the technical field of crystal oscillator calibration, and discloses a frequency calibration method, device and equipment of a crystal oscillator and a storage medium. Clock signals are continuously output, the signals and environment data are recorded, the signals and the environment data are fused, deviation analysis characteristics are generated, and the deviation characteristics are transmitted to a network platform. According to the method, through real-time monitoring, intelligent analysis and prediction, the precision and efficiency of frequency calibration are improved, the system stability is enhanced, and the system reliability is improved. The method is suitable for crystal oscillator frequency adjustment in a complex environment, and solves the problem that a crystal oscillator depends on manual regular calibration in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field of crystal oscillator calibration, and particularly to a frequency calibration method, device, equipment and storage medium for a crystal oscillator. Background Art

[0002] As a core component for precise time and frequency control, crystal oscillators play a crucial role in modern electronic devices and communication systems. They are widely used in wireless communication, computers, navigation systems, aerospace, and other application fields with high-precision requirements. To ensure that the signals output by crystal oscillators have high precision and high stability, effective frequency calibration is essential. Traditional frequency calibration methods mostly rely on manual intervention, by manually adjusting the calibrator, measuring the deviation, and regularly calibrating the crystal oscillator according to environmental changes or aging factors. These methods are often limited by the experience of operators and the state of equipment, and it is difficult to meet the requirements of high efficiency, precision, and real-time. In addition, the selection and execution of frequency calibration schemes are usually based on fixed standards, lacking comprehensive consideration of the real-time state of equipment, environmental changes, and future requirements. Summary of the Invention

[0003] The purpose of the present invention is to provide a frequency calibration method, device, equipment and storage medium for a crystal oscillator, aiming to solve the problem that crystal oscillators in the prior art rely on manual periodic calibration.

[0004] The present invention is implemented as follows. In a first aspect, the present invention provides a frequency calibration method for a crystal oscillator, including: Let the crystal oscillator continuously output clock signals as a frequency source, and continuously record the timing of each clock signal to obtain a sequence of signals to be measured. At the same time, continuously record the working environment conditions of the crystal oscillator at each time node through a pre-deployed sensor group to obtain a working environment sequence of the crystal oscillator; Perform sequence fusion processing on the sequence of signals to be measured and the working environment sequence to obtain a deviation analysis reference feature of the crystal oscillator, and transmit the deviation analysis reference feature to a specified network data platform through wireless data at predetermined intervals; According to the reference signal sequence stored on the network data platform and the historical calibration records of the crystal oscillator, perform multi-dimensional calibration requirement analysis on the deviation analysis reference feature to obtain a calibration requirement feature of the crystal oscillator within the current calibration cycle; Obtain the module performance information of the environment-level calibration module and the signal-level calibration module configured by the crystal oscillator, and perform a demand implementation plan analysis on the calibration requirement feature according to the module performance information to obtain several frequency calibration schemes for the crystal oscillator; Collect auxiliary prediction data for the crystal oscillator based on an enhanced prediction model, and assign execution priorities to various frequency calibration schemes according to the collected auxiliary prediction data, so as to calibrate the environmental level calibration module and the signal level calibration module according to the frequency calibration scheme with the highest execution priority.

[0005] In a second aspect, the present invention provides a frequency calibration device for a crystal oscillator, which is used to implement the frequency calibration method for a crystal oscillator described in any one of the first aspects, and includes: A data recording module, which is used to make the crystal oscillator continuously output a clock signal as a frequency source, and continuously record the timing of each clock signal to obtain a signal sequence to be measured. At the same time, it continuously records the working environment status of the crystal oscillator at each time node through a pre-deployed sensor group to obtain a working environment sequence of the crystal oscillator; A data transmission module, which is used to perform sequence fusion processing on the signal sequence to be measured and the working environment sequence to obtain a deviation analysis reference feature of the crystal oscillator, and transmit the deviation analysis reference feature to a specified network data platform through wireless data at a predetermined time interval; A requirement analysis module, which is used to perform multi-dimensional calibration requirement analysis on the deviation analysis reference feature according to the reference signal sequence stored on the network data platform and the historical calibration records of the crystal oscillator, so as to obtain the calibration requirement feature of the crystal oscillator within the current calibration period; A scheme analysis module, which is used to obtain the module performance information of the environmental level calibration module and the signal level calibration module configured by the crystal oscillator, and perform requirement implementation scheme analysis on the calibration requirement feature according to the module performance information to obtain several frequency calibration schemes for the crystal oscillator; A calibration operation module, which is used to collect auxiliary prediction data for the crystal oscillator based on an enhanced prediction model, and assign execution priorities to various frequency calibration schemes according to the collected auxiliary prediction data, so as to calibrate the environmental level calibration module and the signal level calibration module according to the frequency calibration scheme with the highest execution priority.

[0006] In a third aspect, the present invention provides a computer device, including a memory and a processor. The memory stores a computer program that can run on the processor. When the processor executes the computer program, it implements the frequency calibration method for a crystal oscillator described in any one of the first aspects.

[0007] In a fourth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored. When the computer program is run by the processor, the processor is caused to execute the frequency calibration method for a crystal oscillator described in any one of the first aspects.

[0008] The present invention provides a frequency calibration method for a crystal oscillator, which has the following beneficial effects: The present invention continuously outputs a clock signal and records the signal and environmental data, fuses the signal and environmental data, generates deviation analysis features, transmits the deviation features to a network platform, analyzes the calibration requirements based on historical data, obtains and analyzes the performance of the calibration module, formulates a calibration plan, optimizes the priority of the plan using an enhanced prediction model, and performs the calibration operation. This method improves the accuracy and efficiency of frequency calibration through real-time monitoring, intelligent analysis, and prediction, enhances the system stability, is applicable to the frequency adjustment of crystal oscillators in complex environments, and solves the problem that crystal oscillators in the prior art rely on manual periodic calibration. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 is a schematic diagram of the steps of a frequency calibration method for a crystal oscillator provided by an embodiment of the present invention; Figure 2 is a schematic diagram of the structure of a frequency calibration device for a crystal oscillator provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0010] In order to make the objectives, technical solutions, and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0011] The implementation of the present invention will be described in detail below with reference to specific embodiments.

[0012] Referring to Figure 1 、 Figure 2 shown, a preferred embodiment is provided by the present invention.

[0013] In a first aspect, the present invention provides a frequency calibration method for a crystal oscillator, including: S1: Let the crystal oscillator continuously output a clock signal as a frequency source, and continuously record the timing of each clock signal to obtain a signal sequence to be measured. At the same time, continuously record the working environment conditions of the crystal oscillator at each time node through a pre-deployed sensor group to obtain a working environment sequence of the crystal oscillator; S2: Perform sequence fusion processing on the signal sequence to be measured and the working environment sequence to obtain a deviation analysis reference feature of the crystal oscillator, and transmit the deviation analysis reference feature to a specified network data platform through wireless data at predetermined intervals. S3: Based on the reference signal sequence stored on the network data platform and the historical calibration records of the crystal oscillator, perform multi-dimensional calibration requirement analysis on the deviation analysis reference features to obtain the calibration requirement features of the crystal oscillator within the current calibration cycle. S4: Obtain the module performance information of the environment-level calibration module and the signal-level calibration module configured for the crystal oscillator, and perform requirement implementation plan analysis on the calibration requirement features according to the module performance information to obtain several frequency calibration schemes for the crystal oscillator. S5: Collect auxiliary prediction data for the crystal oscillator based on the enhanced prediction model, and assign execution priorities to various frequency calibration schemes according to the collected auxiliary prediction data, so as to calibrate the environment-level calibration module and the signal-level calibration module according to the frequency calibration scheme with the highest execution priority.

[0014] Specifically, in step S1 of the embodiment provided by the present invention, the crystal oscillator, as a frequency source, continuously outputs clock signals. These clock signals will serve as the basic data for subsequent analysis. During this process, the crystal oscillator is continuously operating and outputting stable clock signals, usually continuously generated at a certain specific frequency (such as 10 MHz or 100 MHz). Through a high-precision timing device or sampler, continuously record the time series of the clock signals output by the crystal oscillator. The purpose of this process is to obtain the detailed timing information of each clock signal, including key parameters such as the frequency, phase, and period of the signal. It is necessary to use high-precision time measurement tools or data acquisition systems to ensure the accurate recording of the output of each clock signal in time. The recorded signal data will become the basis for subsequent frequency analysis and calibration.

[0015] More specifically, record the working environment conditions of the crystal oscillator. In the working environment of the crystal oscillator, deploy multiple sensor groups to continuously monitor and record the environmental factors affecting the oscillator performance. Common environmental parameters include temperature, humidity, air pressure, vibration, etc. The sensor groups will record these environmental data at multiple time nodes to form the working environment sequence of the crystal oscillator. Deploy appropriate sensors, such as temperature sensors, humidity sensors, pressure sensors, etc. These sensors should have high precision and high stability and be able to continuously and stably work under different working conditions and output accurate data.

[0016] More specifically, the above-mentioned clock signal data and environmental data will be stored and backed up in real time through a data acquisition system. Cloud storage, databases, or local servers may be used to save this raw data for subsequent analysis and processing. The data storage system needs to have a large capacity and high-speed read and write capabilities to ensure that data accumulation over a long period of time will not be lost or delayed. In the recorded clock signal sequence and environmental condition sequence, data synchronization operations may be required to ensure that the changes in each clock signal match the corresponding environmental data. Through timestamps or synchronization mechanisms, the impact of clock signals and environmental changes can be associated. The data synchronization system needs to accurately process timing data to ensure that the clock signals and environmental data are correctly corresponding within the same time frame.

[0017] More specifically, ultimately, through the analysis of this timing data, a set of analysis data sets containing clock signal characteristics and the impact of environmental parameters can be obtained. These data sets will provide a basis for further frequency calibration, performance optimization, or fault prediction. Data analysis and processing tools are required to process the data sets using appropriate algorithms (such as time series analysis, spectrum analysis, regression analysis, etc.) to extract valuable information.

[0018] It can be understood that by continuously recording the timing of clock signals, the working state of the crystal oscillator at different time points can be accurately understood. Especially during long-term operation or environmental changes, any minor changes in the clock signals can be recorded, facilitating subsequent frequency analysis and performance optimization. The deployment of the environmental sensor group ensures comprehensive monitoring of all environmental factors affecting the performance of the crystal oscillator, which enables timely adjustment or optimization of the operating mode of the crystal oscillator according to environmental changes, improving its stability and accuracy.

[0019] More specifically, synchronously recording and analyzing the clock signals and environmental data can reveal the impact of environmental changes (such as temperature, humidity, etc.) on the performance of the crystal oscillator. For example, temperature changes may cause frequency drift of the crystal oscillator, and humidity changes may affect the stability of the oscillator, etc. Such data analysis helps to understand and predict the behavior of the oscillator. Based on the comprehensive analysis of the clock signal sequence and the working environment sequence, more accurate data support for frequency calibration can be provided. By comparing the environmental conditions with the changes in the clock signals, the system can identify which environmental factors have the greatest impact on frequency drift, and thus take targeted calibration measures.

[0020] Specifically, in step S2 of the embodiment provided by the present invention, the system first obtains the signal sequence to be measured and the working environment sequence from the output clock signal of the crystal oscillator and the environmental sensor. The signal sequence to be measured contains the clock signal data of the crystal oscillator at different time points, while the working environment sequence records the environmental factors at these moments, such as temperature, humidity, air pressure, etc. It is necessary to ensure the real-time collection of data and guarantee the accuracy and timing consistency of the signals for subsequent fusion and analysis. Usually, precise sampling devices are used for data recording.

[0021] More specifically, sequence fusion processing is performed on the signal sequence to be measured and the working environment sequence. The data of the signal sequence to be measured and the working environment sequence are fused. mainly through methods such as time alignment and feature matching to merge the two sets of data to form a composite data set containing clock signal features and environmental impacts. The goal of this process is to analyze the relationship between the deviation of the clock signal and the working environment factors, so as to obtain more accurate reference features for deviation analysis. It is necessary to ensure the synchronization of the signal to be measured and the working environment data in time. Timestamp alignment may be required, and data fusion algorithms (such as Kalman filtering, weighted average, regression analysis, etc.) are used for sequence fusion to extract the relationship between the signal and the environmental factors. Deviation analysis features, such as the amount of frequency drift and the impact of environmental changes on frequency, are extracted from the fused data.

[0022] More specifically, after the sequence fusion processing, the obtained composite data set will be used to generate reference features for deviation analysis of the crystal oscillator. These features may include: frequency deviation: the frequency difference between the output signal of the crystal oscillator and the predetermined standard; environmental impact: the degree of impact of environmental changes on the frequency; trend analysis: analyzing the trend of deviation changes based on historical data to predict possible future performance deviations; The feature extraction process requires the use of appropriate algorithms, such as time series analysis, statistical regression, spectrum analysis, etc., to ensure that the key features affecting the performance of the crystal oscillator can be accurately extracted.

[0023] More specifically, the reference features for deviation analysis are transmitted wirelessly at a predetermined time interval. Once the generation of the reference features for deviation analysis is completed, the system will transmit these reference features to the designated network data platform at a predetermined time interval (such as every hour, every day, etc.) through wireless data transmission. Wireless communication technologies (such as Wi-Fi, Bluetooth, Zigbee, LTE, etc.) are used to transmit the data to the designated remote data platform or server for centralized management. The received data will be stored in the cloud platform or local server for subsequent analysis and visualization. It is necessary to have a stable and high-speed wireless communication module to ensure that the data can be transmitted in real time and accurately, and to ensure the security of the data during the transmission process to avoid data leakage or tampering. The cloud platform or local data center needs to have sufficient storage capacity to store a large amount of time series data.

[0024] More specifically, after receiving the data, the specified network data platform performs further processing, storage, and visualization of the deviation analysis reference features. The platform can perform the following based on these data: Real-time monitoring: Continuously monitor the performance and health status of the crystal oscillator; Predictive analysis: Predict the future state of the crystal oscillator (such as frequency change trend, possible faults, etc.) based on historical data and current deviation analysis features; Alarm mechanism: If an abnormal deviation is detected, the platform can automatically generate an alarm to notify relevant personnel for handling.

[0025] It can be understood that by fusing the signal sequence to be measured and the working environment sequence, the relationship between the frequency deviation of the crystal oscillator and environmental factors can be accurately analyzed, providing detailed reference data for frequency calibration. This can significantly improve the accuracy and effectiveness of frequency calibration. Wireless data transmission enables the deviation analysis reference features to be transmitted to the remote platform in real time, avoiding manual intervention and the difficulties of on-site data collection, and providing a more convenient monitoring and management method. Through the data platform, relevant personnel can monitor the operating conditions of the crystal oscillator at any time.

[0026] More specifically, through the accumulation of historical data and continuous monitoring of the deviation analysis reference features, the data platform can predict the operating trend of the crystal oscillator, thereby discovering potential problems in advance and realizing predictive maintenance of the equipment. This helps to reduce equipment downtime and extend the equipment life. Through the real-time collection and transmission of the deviation analysis reference features, the platform can provide effective decision-making support. Relevant personnel can optimize the usage and maintenance strategies of the equipment, rationally allocate resources, and improve work efficiency according to the data analysis results. By combining the working environment factors with the deviation data of the clock signal, the most suitable frequency calibration strategy can be selected under different environmental conditions. With the accumulation of more data, the system can gradually optimize the calibration scheme and improve the stability and reliability of the crystal oscillator in various environments.

[0027] Specifically, in step S3 of the embodiment provided by the present invention, the reference signal sequence and historical calibration records of the crystal oscillator are extracted from the network data platform. The reference signal sequence usually contains the output signal that the crystal oscillator should have under ideal conditions, while the historical calibration records provide detailed data on all past calibrations (such as environmental factors, deviation conditions, adjustment amplitudes, etc.) during calibration. The data platform needs to be able to accurately store and manage a large amount of historical data while ensuring the timing and integrity of the data for subsequent analysis.

[0028] More specifically, a multi-dimensional analysis is performed on the deviation analysis reference features. The purpose of this multi-dimensional analysis of the deviation analysis reference features is to interpret the calibration requirements of the current crystal oscillator from multiple perspectives (such as time, frequency, environmental factors, etc.). This step generally includes the following aspects: Comparing the current deviation analysis reference features with the frequency deviations in the historical calibration records to analyze whether the current deviation exceeds a predetermined threshold and whether there is a trend deviation; Environmental factor comparison: Comparing the changes in the current working environment with the deviation performance under historical environmental conditions to analyze the impact of environmental factors (such as temperature, humidity, etc.) on the frequency deviation and determine whether targeted adjustments are required; Timing analysis: Analyzing the change trend of deviations within the historical calibration period, predicting the deviation performance in the current period, and adjusting the calibration strategy according to the trend; Calibration requirement assessment: Based on the results of the multi-dimensional analysis, assessing whether calibration is required in the current period, as well as the magnitude and direction of the adjustment required.

[0029] More specifically, the current deviation analysis reference features need to be matched and compared with historical data, and multi-dimensional analysis is performed using techniques such as time series analysis and regression analysis. Machine learning algorithms (such as predictive modeling, clustering analysis, etc.) may need to be combined to more precisely extract patterns from historical data and automatically identify calibration requirements based on the current deviation situation.

[0030] More specifically, calibration requirement features for the crystal oscillator are generated. Through the multi-dimensional analysis of the deviation analysis reference features, calibration requirement features for the current calibration cycle are generated. The specific features include: Calibration amplitude: Determining the amplitude of calibration required based on the comparison between the current deviation and the historical deviation; Calibration timing: Determining when to perform calibration (for example, whether a predetermined deviation threshold has been reached or whether calibration is performed in advance based on trend prediction); Adjustment direction and strategy: Determining the adjustment direction (such as increasing frequency, decreasing frequency, etc.) and the specific calibration strategy (such as increasing or decreasing the temperature compensation parameters of the crystal oscillator) based on the performance of environmental factors and frequency deviations. Generating calibration requirement features requires combining physical modeling and data analysis to ensure that the calibration requirements are accurate and in line with the actual situation. Flexible adjustment strategies need to be supported to cope with different environmental and deviation situations.

[0031] More specifically, based on the generated calibration requirement features, specific calibration plans and strategies are formulated. This includes selecting appropriate calibration methods (such as manual calibration, automatic calibration, online calibration, etc.) and determining the technical parameters required during the calibration process (such as the amplitude of adjustment, accuracy requirements, etc.). The formulation of the calibration plan needs to rely on precise control models and automated calibration technologies, and comprehensive consideration needs to be given to each possible influencing factor of the crystal oscillator to ensure the feasibility and efficiency of the calibration plan.

[0032] More specifically, according to the established calibration scheme, the calibration of the crystal oscillator is implemented, and the effect after calibration is monitored in real time. If the calibration result does not meet the expectation, secondary calibration or further adjustment may be required. The calibration process needs to be monitored in real time to ensure the accuracy of the calibration process, and the calibration result is fed back through the data platform in real time for evaluation.

[0033] It can be understood that through multi-dimensional deviation analysis and calibration requirement analysis, the calibration requirements of the crystal oscillator can be accurately identified, human errors can be reduced, and the best effect can be ensured for each calibration. This helps to improve the stability of the crystal oscillator and the reliability of long-term operation. By combining historical data with current deviation characteristics and using intelligent algorithms to generate accurate calibration requirements, the limitations of traditional empirical calibration methods can be avoided. The data-driven decision-making process can make the calibration more scientific and automated.

[0034] More specifically, based on the multi-dimensional analysis of historical calibration records and current deviation analysis results, the potential calibration requirements of the crystal oscillator can be predicted in advance, and preventive adjustments can be made, thereby reducing equipment failures and downtime. This helps to improve the availability and maintenance efficiency of the equipment. The automated calibration requirement analysis and scheme generation reduce manual intervention and improve the efficiency of the calibration process. The application of machine learning and data analysis makes the calibration decision more scientific and efficient, reducing operation risks and human errors.

[0035] Specifically, in step S4 of the embodiment provided by the present invention, this module is usually responsible for adjusting the influence of environmental variables (such as temperature, humidity, electromagnetic interference, etc.) on the crystal oscillator. When obtaining the performance information of this module, key attention is paid to its calibration ability under different environmental conditions, and how to maintain frequency stability through external compensation or adjustment algorithms. This module is responsible for directly adjusting the frequency output of the crystal oscillator, and eliminating or reducing frequency deviation through direct processing of the signal. When obtaining the performance information of this module, key attention is paid to indicators such as its frequency adjustment range, accuracy, and response time. When obtaining the performance information of these modules, it is necessary to clarify the working range, limitations, response characteristics, and control accuracy of the modules, and the performance indicators such as the working temperature range, stability requirements, adjustment ability, and accuracy need to be obtained from each module. Module information may come from equipment manuals, test reports, historical calibration data, etc. The performance of each module is evaluated, including the difference between the performance under actual operating conditions and the theoretical performance.

[0036] More specifically, conduct an analysis of the implementation plan for calibration requirement features. Based on the previous deviation analysis and combined with the performance information of the environmental-level calibration module and the signal-level calibration module, perform an implementation analysis of the calibration requirement features. Specifically, it is necessary to analyze the impact of the current environment on the frequency of the crystal oscillator and the adjustment ability of the signal-level module. If environmental factors (such as temperature changes) may cause significant frequency deviations, it is necessary to analyze the adjustment range and response time of the environmental-level calibration module to ensure that it can adapt to environmental changes and perform effective compensation.

[0037] More specifically, through the performance information of the signal-level calibration module, analyze whether it can achieve precise adjustment under the current deviation situation and whether it can reach the required frequency accuracy. Based on the above analysis, establish the implementation plan for calibration requirements, considering whether it is necessary to use both the environmental calibration and signal calibration modules simultaneously or use a certain module alone to solve the problem. When conducting the analysis of the implementation plan for requirements, consider the synergy effect between different calibration modules, how to achieve the best frequency adjustment effect through the combination of each module, and use mathematical models or simulation tools to quantitatively analyze different calibration schemes, evaluate their effects, and select the best scheme.

[0038] More specifically, generate several frequency calibration schemes for the crystal oscillator. According to the implementation plan for requirements, generate multiple different frequency calibration schemes. Each calibration scheme may adopt different module combinations, adjustment strategies, and calibration periods. Scheme 1: It may use the environmental-level calibration module to compensate for environmental changes and combine the signal-level calibration module to finely adjust the frequency. This scheme is applicable to situations where environmental changes are large but the signal-level calibration module can provide high accuracy. Scheme 2: If environmental changes are small and the signal-level calibration module is accurate enough, the frequency may be adjusted only through the signal-level module. Scheme 3: It may include periodic joint calibration, that is, alternately use the signal-level and environmental-level calibration modules regularly according to historical data. The generated calibration schemes need to be flexibly selected according to different actual application situations to ensure that they can handle different frequency deviation scenarios. Automated algorithms (such as machine learning, optimization algorithms) can be used to intelligently recommend the optimal calibration scheme.

[0039] More specifically, conduct verification based on the generated frequency calibration schemes to ensure that each scheme can meet the performance requirements of the crystal oscillator and achieve an ideal calibration effect in a specific application scenario. Calibration verification includes laboratory environment testing and actual operation testing. Verify whether the calibrated frequency is stable and accurate. Further optimize and adjust the calibration scheme according to the test results to improve calibration efficiency and reduce errors. Optimize the calibration scheme by combining experimental data and simulation results to ensure its effectiveness in actual applications. During actual use, continuously optimize the calibration scheme through a feedback mechanism to enhance the overall stability of the system.

[0040] It is understandable that by obtaining detailed module performance information, the performance boundaries of the environmental and signal calibration modules can be accurately understood, thereby ensuring that the frequency of the crystal oscillator can be precisely adjusted within the specified range. According to different calibration requirements and module performance information, multiple calibration schemes can be generated to provide the optimal calibration strategy for different usage environments and deviation situations. This improves the adaptability and stability of the crystal oscillator in various environments. Through the analysis and optimization of the demand implementation plan, unnecessary calibration operations are reduced, ensuring that frequency adjustment is only performed when necessary. This helps to improve the overall efficiency of the system and reduce maintenance costs. According to the actual situation of environmental changes and frequency deviations, the calibration strategy is dynamically adjusted to ensure the stability and accuracy of the frequency under various changing conditions. This is particularly important for devices operating in complex or extreme environments.

[0041] Specifically, in step S5 of the embodiment provided by the present invention, first, an enhanced prediction model is established or optimized. This model can predict future frequency deviations based on historical data, real-time environmental variables (such as temperature, humidity, voltage, etc.) and the state of the oscillator. These models are usually trained based on machine learning algorithms (such as regression analysis, neural networks or deep learning) in order to accurately predict the performance of the crystal oscillator under different environmental conditions. Auxiliary data related to the oscillator, such as temperature, pressure, electromagnetic interference, power fluctuations, etc., is collected through sensors, data recording devices or real-time monitoring systems. This data will be used to enhance the prediction model to predict future frequency deviations.

[0042] More specifically, based on the prediction results of the model, the frequency deviations of the crystal oscillator are estimated under different conditions, providing a basis for the priority allocation of subsequent calibration schemes. An accurate acquisition system is required to monitor the environmental parameters and the state of the oscillator in real time to ensure the timeliness and accuracy of the data. The enhanced prediction model must be able to handle non-linear and highly complex data and accurately predict the frequency deviations of the crystal oscillator.

[0043] More specifically, according to the functions and performance characteristics of the environmental layer calibration module and the signal layer calibration module, different frequency calibration schemes are designed. Each calibration scheme may involve different calibration means. For example, environmental layer calibration may focus on temperature compensation, while signal layer calibration may focus on frequency adjustment. Based on the collected auxiliary prediction data and combined with the output of the enhanced prediction model, the execution priority of each frequency calibration scheme is determined. For example, if the prediction model shows that a certain environmental change (such as a sudden increase in temperature) may cause frequency deviation of the oscillator, the system may give priority to executing the environmental layer calibration scheme.

[0044] More specifically, based on the predicted frequency deviation magnitude, the response speed of the calibration module, and the expected calibration effect, evaluate the priority of each scheme. The scheme with a higher priority is usually the one that can correct the deviation fastest and provide the most accurate calibration effect. Establish a multi-factor priority evaluation system that can comprehensively evaluate the priority of each calibration scheme from multiple dimensions such as predicted data, module performance, and response speed. The system needs to have an automated decision-making mechanism to dynamically adjust the priority allocation according to real-time data to ensure the selection of the most appropriate calibration scheme under different circumstances.

[0045] More specifically, according to the result of the priority allocation, select and execute the frequency calibration scheme with the highest priority. This may mean performing environmental-level calibration first and then signal-level calibration as needed. Which scheme to choose depends on the type of deviation predicted currently (whether it is affected by environmental factors or signal processing needs adjustment). Start the selected calibration module for operation through the control system. For example, the environmental-level calibration module can start the heater or cooling system to adjust the temperature, while the signal-level calibration module can make precise adjustments by fine-tuning the settings of the frequency generator. During the calibration operation, monitor the frequency change of the oscillator in real time and adjust the calibration process through the feedback mechanism to ensure that the final frequency adjustment achieves the expected effect, ensure that the executed calibration operation has high precision and high response speed, and avoid further frequency deviation caused by errors. During the calibration process, implement a real-time feedback mechanism to adjust the calibration strategy based on the actual change of the frequency to ensure that the accuracy of the target frequency meets the requirements.

[0046] More specifically, after the calibration operation is executed, use a frequency measurement instrument to evaluate the frequency of the crystal oscillator to ensure that it reaches the target frequency. Based on the calibration effect, if there is still a deviation in the frequency, further optimize the calibration scheme by combining real-time data and the prediction model, and execute subsequent calibration steps. The system automatically optimizes and enhances the prediction model according to the feedback result, enabling more accurate prediction and priority allocation in future calibration operations. Through continuous feedback of the calibration results, the system can gradually optimize the prediction model and the priority allocation strategy, improving the overall calibration effect and efficiency.

[0047] It can be understood that through the auxiliary data collection and analysis of the enhanced prediction model, the frequency deviation of the crystal oscillator can be accurately predicted, and the most appropriate calibration scheme can be selected accordingly. This method can greatly improve the calibration accuracy and reduce the frequency deviation. Through the data-driven priority allocation mechanism, the system can automatically select the calibration scheme with the highest priority according to the real-time prediction result, ensuring that the calibration operation is always in the most effective state. By performing calibration operations according to actual needs, unnecessary operations are avoided, and the resource utilization efficiency of the calibration system is improved. For example, the collaborative work of the environmental-level calibration module and the signal-level calibration module makes the calibration process more streamlined and efficient.

[0048] The present invention provides a frequency calibration method for a crystal oscillator, which has the following beneficial effects: The present invention continuously outputs a clock signal and records the signal and environmental data, fuses the signal and environmental data to generate deviation analysis features, transmits the deviation features to a network platform, analyzes the calibration requirements based on historical data, obtains and analyzes the performance of a calibration module, formulates a calibration plan, optimizes the priority of the plan using an enhanced prediction model, and executes the calibration operation. This method improves the accuracy and efficiency of frequency calibration through real-time monitoring, intelligent analysis, and prediction, enhances the system stability, is applicable to the frequency adjustment of crystal oscillators in complex environments, and solves the problem in the prior art that crystal oscillators rely on manual periodic calibration.

[0049] Preferably, the steps of making the crystal oscillator continuously output a clock signal as a frequency source, continuously recording the time sequence of each clock signal to obtain a signal sequence to be measured, and simultaneously continuously recording the working environment conditions of the crystal oscillator at each time node through a pre-deployed sensor group to obtain a working environment sequence of the crystal oscillator include: S11: Configure the working parameters of the clock frequency source for the crystal oscillator so that the crystal oscillator continuously outputs a clock signal as a frequency source; S12: Synchronously receive the clock signal of the crystal oscillator and generate time stamps through a plurality of synchronous clock function units, and perform weighted fusion on the time stamps generated by each synchronous clock function unit to obtain the recorded time stamp of the clock signal generated by the crystal oscillator; S13: Record the signal at the corresponding coordinate position of the clock signal with the recorded time stamp through a pre-constructed time coordinate axis to obtain a signal sequence to be measured; S14: Continuously collect the working environment conditions of the crystal oscillator through a sensor group pre-deployed in the adjacent environment of the crystal oscillator to obtain sensor network data for feedback on the working environment conditions of the crystal oscillator; wherein, the sensor network data includes temperature level data, humidity level data, air pressure level data, vibration level data, and electromagnetic interference level data; S15: Record the sensor network data collected at each time node at the corresponding coordinate position through a pre-constructed time coordinate axis to obtain a working environment sequence.

[0050] Specifically, the crystal oscillator needs to be initialized and configured to continuously output a clock signal as a frequency source. By setting appropriate parameters such as the frequency range, output mode, and stability, ensure that the crystal oscillator operates continuously and stably. The frequency of the oscillator needs to be stably output under appropriate conditions, avoiding being affected by external interference or system instability. The configuration process requires the use of high-precision equipment or systems to ensure that the output signal of the oscillator meets the design requirements and has good stability.

[0051] More specifically, for the clock signal synchronization and timestamp generation of the synchronous clock function unit, several synchronous clock function units are deployed. These units are responsible for receiving the clock signal generated by the crystal oscillator and generating timestamps. Each synchronous clock function unit generates a timestamp based on the signal received by its own system clock. The timestamps collected from different synchronous clock function units are weighted and fused to ensure that the timestamps have high precision and consistency. This weighted fusion can be performed through algorithms, such as processing the timestamps of different units based on weighted average or least squares method, etc., to reduce errors and deviations. The precision of the synchronous clock function unit is very important. It is necessary to ensure that the clock synchronization error between units is minimized. The weighted fusion algorithm needs to ensure the high precision of the timestamps and reduce the inconsistency of timestamps caused by equipment differences.

[0052] More specifically, a time axis is pre-constructed to correspond the recorded timestamps of all clock signals to specific time positions. The design of the time axis needs to consider the actual working cycle and time resolution of the system to ensure that each signal can be accurately recorded at the corresponding time position. According to the matching relationship between the timestamps generated by the synchronous clock unit and the time axis, the clock signal generated by the crystal oscillator is recorded as a signal sequence to be measured, forming a signal data stream with time tags. The time axis needs to have high resolution to ensure that the timestamps of each clock signal can be accurately recorded. The storage and processing of the signal sequence to be measured require an efficient storage system and algorithm for quick reading and analysis.

[0053] More specifically, a sensor group is deployed in the vicinity of the crystal oscillator to continuously monitor various parameters related to the working environment of the crystal oscillator. These sensors usually include types such as temperature, humidity, air pressure, vibration, and electromagnetic interference. The sensor group records the data of the working environment in real time and collects these data in a time series manner. The data of each sensor will include a timestamp indicating the specific time point when the data is collected. The sensor group needs to have high precision to accurately record environmental changes and ensure the consistency and reliability of the data. A processing system is required during the real-time data collection process to quickly analyze and transmit the environmental data.

[0054] More specifically, the matching and recording of environmental data with the time axis is achieved by synchronously recording the environmental data collected by each sensor through a pre-constructed time axis, ensuring that each data point is matched with its corresponding timestamp. The time axis will record the environmental data and clock signal at each time node. By matching the timestamps of the environmental data and the clock signal, a complete working environment sequence is obtained. This sequence includes the clock signal of the oscillator and the related environmental information, ensuring the precise alignment of the clock signal and the environmental data, and avoiding errors caused by clock synchronization or sensor data delay. The multi-dimensional fusion of environmental data requires precise algorithms and system support to ensure that different types of data (such as temperature, humidity, etc.) can be synchronously recorded and matched with the clock signal.

[0055] It can be understood that through the cooperation of the synchronous clock functional unit and the time axis, the clock signal generated by the crystal oscillator is accurately recorded in time, providing reliable data support for subsequent timing analysis. The environmental data (such as temperature, humidity, air pressure, etc.) collected by the sensor group can reflect the working environment of the crystal oscillator in real time, which helps to analyze the performance of the oscillator under different environmental conditions and conduct targeted calibration and optimization. Through the timestamp weighted fusion of the multi-synchronous clock functional unit and the construction of the time axis, the error caused by the time deviation of different devices can be effectively reduced, ensuring the precise alignment of the clock signal and the environmental data.

[0056] More specifically, the continuously collected environmental data can provide real-time feedback on the health status of the crystal oscillator. When an abnormal environmental change is detected, a quick response can be made to adjust the working state of the oscillator, thus ensuring the stability of the oscillator under different environmental conditions. By combining the clock signal of the crystal oscillator and the environmental data, in-depth analysis can be carried out to evaluate the influence of different environmental factors on the frequency stability of the oscillator, providing data support for product optimization and maintenance. The system can automatically monitor and adjust the working state of the oscillator to keep it working stably under various environmental conditions, reducing frequency deviation and improving the long-term reliability of the device.

[0057] Preferably, the steps of performing sequence fusion processing on the to-be-tested signal sequence and the working environment sequence to obtain the deviation analysis reference feature of the crystal oscillator and transmitting the deviation analysis reference feature to a specified network data platform through wireless data at a predetermined interval include: S21: According to the time axes possessed by the to-be-tested signal sequence and the working environment sequence, perform alignment processing on the time coordinate systems of the to-be-tested signal sequence and the working environment sequence so that the to-be-tested signal sequence and the working environment sequence are in a time coordinate alignment state; S22: Based on the time coordinate alignment state between the signal sequence to be measured and the working environment sequence, perform spatio-temporal correlation connection on the sequence data of the signal sequence to be measured and the working environment sequence, so as to construct an information connection vector between each signal to be measured in the signal sequence to be measured and each sensor network data in the working environment sequence; S23: Perform temporal correlation analysis between vectors on the information connection vectors between each signal to be measured in the signal sequence to be measured and each sensor network data in the working environment sequence, so as to generate a connection deviation vector for describing the temporal correlation between each information connection vector; S24: Perform permutation and combination of a predetermined specification on the information connection vector and the connection deviation vector to obtain a sequence fusion feature matrix; S25: Perform supervised evaluation of the corresponding time of the signal sequence to be measured and the working environment sequence according to a predetermined time standard. When the supervised evaluation result shows that the signal sequence to be measured and the working environment sequence meet the predetermined time standard, perform sequence information compression and decompression method annotation on the signal sequence to be measured and the working environment sequence according to the sequence fusion feature matrix, so as to obtain a deviation analysis reference feature; S26: Obtain the registration information of the crystal oscillator on the specified network data platform, obtain the generation time information corresponding to the deviation analysis reference feature, perform encapsulation processing on the deviation analysis reference feature according to the registration information and the generation time information, and transmit the encapsulated deviation analysis reference feature to the specified network data platform through wireless data.

[0058] Specifically, according to the respective time coordinate axes of the signal sequence to be measured and the working environment sequence, align the two sequences in the time coordinate system to ensure that the signal sequence to be measured and the working environment sequence correspond in time and can be matched. Even if they come from different sources or devices respectively, the corresponding time nodes can be aligned. This step needs to ensure the accuracy of time coordinate alignment to avoid deviations between signals and environmental data, ensure the time alignment of the signal to be measured and the working environment data, avoid data inconsistency caused by time differences, and construct an efficient time coordinate system that can accommodate multiple data sources and achieve precise alignment.

[0059] More specifically, in the state of time coordinate alignment, the signal sequence to be measured is connected with the working environment sequence in terms of spatio-temporal correlation. This means that the signal to be measured is associated with the corresponding working environment data both in time and space to construct an information connection vector. Each signal to be measured (such as the frequency signal of a crystal oscillator) will be associated with specific environmental data (such as temperature, humidity, etc.), and these associations are represented by vectors. A suitable algorithm is used to connect the signal and the environmental data to ensure precise docking in time and space, construct a vector representing the connection relationship, and ensure that this vector can truly reflect the internal connection between the signal to be measured and the environmental data.

[0060] More specifically, perform a temporal correlation analysis on all the information connection vectors. This means that it is necessary to analyze the temporal correlation between each signal to be measured and its corresponding environmental data, and generate a connection deviation vector describing the temporal correlation. The connection deviation vector reflects the time variation characteristics between the signal to be measured and the environmental data and can be used for subsequent deviation analysis. Using suitable temporal analysis methods (such as autoregressive analysis, cross-correlation analysis, etc.), identify the temporal dependence relationship between the signal and the environmental data. The connection deviation vector should be able to describe the time deviation characteristics between different signals and environmental factors and have analytical value.

[0061] More specifically, arrange and combine the information connection vectors and the connection deviation vectors according to a predetermined specification to generate a sequence fusion feature matrix. This matrix contains all the information between the signal to be measured and the working environment sequence and can reflect the temporal correlation and deviation characteristics between the two, constructing a feature matrix that can integrate different signals, environmental data, and their temporal relationships. This matrix needs to have the ability of efficient storage and processing, set clear matrix construction rules, and ensure that the signal to be measured and the environmental data can be correctly fused.

[0062] More specifically, conduct a supervised evaluation on the signal sequence to be measured and the working environment sequence according to a predetermined time standard to check whether they meet the time alignment standard. When the supervised evaluation result shows that the signal sequence and the environmental sequence meet the standard, use the sequence fusion feature matrix to perform information compression and decompression annotation on the signal sequence to obtain a deviation analysis reference feature. The goal of this process is to simplify the signal and environmental data and extract the most valuable features for analysis, define and verify the time standard, ensure that the signal and environmental data meet the specified accuracy in time, and design efficient compression and decompression methods so that the sequence can reduce the data volume while maintaining the integrity of the information.

[0063] More specifically, obtain the registration information of the crystal oscillator on the specified network data platform, extract the generation time information corresponding to the deviation analysis reference features, and perform encapsulation processing on the deviation analysis reference features according to the registration information and the generation time information to ensure standardization of the data format and easy transmission. Transmit the encapsulated deviation analysis reference features to the specified network data platform through wireless data for remote monitoring and analysis. It is necessary to ensure that the deviation analysis reference features can be correctly parsed and used on the network platform, and use an efficient and reliable wireless transmission protocol to ensure that the data can be stably and quickly transmitted to the specified platform.

[0064] It can be understood that through the alignment of the time coordinate system and the connection of spatio-temporal correlation, it is ensured that the signal to be measured and the working environment data can be accurately matched in time and space, thus providing a reliable data basis for subsequent deviation analysis. The connection deviation vector generated through sequential correlation analysis enables the system to accurately describe the sequential dependence relationship between the signal and the environmental data, which provides an important basis for subsequent performance optimization and fault diagnosis.

[0065] More specifically, the construction of the sequence fusion feature matrix can effectively integrate the information of the signal to be measured and the working environment sequence, and through information compression and decompression annotation, reduce the complexity of data storage and transmission, improve data processing efficiency. Transmitting the deviation analysis reference features to the network data platform through wireless data realizes remote monitoring and analysis, facilitates real-time acquisition of the operating status of the oscillator and environmental influencing factors, enhances the intelligent management ability of the system, and the generated deviation analysis reference features provide a basis for the performance analysis of the crystal oscillator, which can help to timely discover potential problems of the oscillator and the impact brought by environmental changes, and further optimize the stability and accuracy of the system.

[0066] Preferably, the step of parsing the calibration requirements of the deviation analysis reference features in multiple dimensions according to the reference signal sequence stored on the network data platform and the historical calibration records of the crystal oscillator to obtain the calibration requirement features of the crystal oscillator in the current calibration cycle includes: S31: Perform preliminary information parsing on the deviation analysis reference features to obtain the encapsulation information of the deviation analysis reference features; wherein, the encapsulation information includes the registration information of the crystal oscillator corresponding to the deviation analysis reference features and the generation time information of the deviation analysis reference features; S32: Retrieve the reference signal sequence and the historical calibration records of the crystal oscillator on the network data platform according to the encapsulation information to obtain the reference signal sequence and the historical calibration records of the crystal oscillator corresponding to the deviation analysis reference features; S33: Decompress the deviation analysis reference feature to obtain a signal sequence to be measured, a working environment sequence, and a sequence fusion feature matrix; S34: Perform time alignment matching on the signal sequence to be measured according to the reference signal sequence to obtain the signal deviation feature distribution of the signal sequence to be measured relative to the reference signal sequence; S35: Analyze the environmental impact factors of the working environment sequence relative to the signal deviation feature distribution according to the sequence fusion feature matrix to obtain an environmental impact factor sequence corresponding to the signal deviation feature distribution; S36: Perform time unit deviation analysis on the signal deviation feature distribution in the signal deviation time series accumulation mode according to the environmental impact factor sequence to obtain a set of unit time deviation features of the environmental impact factor sequence; wherein, the set of unit time deviation features includes several unit time deviation features arranged in time sequence, and the unit time deviation features are used to predict various possibilities of the oscillation deviation of the crystal oscillator caused by environmental impact factors in the unit time; S38: Allocate the deviation weights of environmental factors to the crystal oscillator according to the unit time deviation analysis results corresponding to each unit time deviation feature to obtain the deviation factor weights of each environmental factor in the working environment where the crystal oscillator is located; S39: Convert the deviation factor weights of each environmental factor in the working environment where the crystal oscillator is located into the form of calibration requirements, and perform historical reference correction processing on the conversion of calibration requirements based on the historical calibration record of the crystal oscillator to obtain the calibration requirement characteristics of the crystal oscillator in the current calibration cycle. S39: Convert the deviation factor weights of each environmental factor in the working environment where the crystal oscillator is located into the form of calibration requirements, and perform historical reference correction processing on the conversion of calibration requirements based on the historical calibration record of the crystal oscillator to obtain the calibration requirement characteristics of the crystal oscillator in the current calibration cycle.

[0067] Specifically, perform preliminary analysis on the deviation analysis reference feature, extract the packaging information therein, and the packaging information includes: crystal oscillator registration information: including identification information related to the crystal oscillator (such as model, specification, serial number, etc.), generation time information: indicating the specific time when the deviation analysis reference feature is generated. By analyzing the packaging information of the deviation analysis reference feature, it is possible to further track the specific crystal oscillator and time point related to this feature, efficiently extract and store the packaging information, and ensure that all subsequent steps can accurately obtain the required historical data through this information.

[0068] More specifically, retrieve the reference signal sequence and historical calibration records. According to the crystal oscillator registration information and generation time information in the encapsulation information, retrieve the corresponding reference signal sequence and historical calibration records from the network data platform. The reference signal sequence is used to compare with the signal sequence to be measured, while the historical calibration records provide a reference for subsequent calibration requirement analysis. It is necessary to ensure efficient access to the data platform to accurately retrieve the reference signal sequence and historical calibration records. The retrieved historical calibration records must be strictly matched with the crystal oscillator information and generation time corresponding to the deviation analysis reference features.

[0069] More specifically, perform decompression processing on the deviation analysis reference features to restore its original signal sequence to be measured, working environment sequence, and sequence fusion feature matrix. The decompressed data will be used for subsequent analysis and matching work. Use an efficient decompression algorithm to ensure that no information is lost during the restoration process and the speed is fast. The decompressed sequence needs to ensure data integrity to ensure accurate subsequent analysis.

[0070] More specifically, perform time alignment matching on the signal sequence to be measured based on the reference signal sequence. In this way, the signal deviation feature distribution of the signal sequence to be measured relative to the reference signal sequence can be obtained. This process helps to quantify the deviation between the signal to be measured and the reference signal, and then analyze the operating state of the oscillator to ensure that the signal sequence to be measured and the reference signal sequence can be accurately aligned. Extract the signal deviation features from the aligned data to construct a deviation feature distribution map.

[0071] More specifically, according to the sequence fusion feature matrix, analyze the environmental impact factors of the working environment sequence relative to the signal deviation feature distribution. The goal of this step is to analyze the impact of various factors in the working environment on the signal deviation. Through this process, an environmental impact factor sequence related to the signal deviation feature distribution can be obtained, and a suitable correlation model between the environmental factors and the signal deviation can be constructed to ensure that the analysis results truly reflect the environmental impact.

[0072] More specifically, use the environmental impact factor sequence to perform time unit deviation analysis on the signal deviation feature distribution in the time series cumulative mode of signal deviation. The goal of this step is to perform time series accumulation of signal deviation through the environmental impact factor sequence, and then generate a set of unit time deviation features. The set of unit time deviation features includes multiple unit time deviation features arranged in chronological order. These features are used to predict the oscillation deviation of the crystal oscillator caused by environmental factors within the unit time. Perform time series cumulative analysis on the signal deviation features to ensure that the correct time unit deviation can be extracted from the environmental impact and accurately construct the set of unit time deviation features to ensure that the oscillation deviation under environmental impact can be effectively predicted.

[0073] More specifically, temporal interaction verification is performed among the individual unit time deviation features in the set of unit time deviation features, and historical reference verification is carried out in combination with historical calibration records. Through these two verification methods, weighted certainty analysis can be performed on the set of unit time deviation features, so as to obtain the unit time deviation analysis results of each unit time deviation feature, improve the reliability of deviation analysis by using the methods of temporal interaction and historical verification, and perform weighted processing on the analysis results to ensure the high credibility of the final result.

[0074] More specifically, according to the unit time deviation analysis results, environmental factor deviation weight allocation is carried out. According to the influence degree of different environmental factors on the crystal oscillator, corresponding deviation weights are assigned to each environmental factor, and these deviation weights will be used for subsequent calibration requirement analysis. A scientific environmental factor deviation weight allocation algorithm is designed to ensure that the weight allocation can reflect the actual influence of the environment on the oscillator.

[0075] More specifically, the deviation weights are converted into the form of calibration requirements, and the converted form of calibration requirements is corrected based on the historical calibration records of the crystal oscillator. This process ensures the accuracy of the calibration requirements, which conforms to the current state and environmental requirements of the oscillator. The conversion of the calibration requirement form ensures that the deviation weights can be converted into a suitable form of calibration requirements, and the historical calibration correction combines the historical calibration records to correct the requirements, ensuring that the calibration scheme is consistent with the historical operating conditions of the oscillator.

[0076] More specifically, based on the above steps, the calibration requirement characteristics of the crystal oscillator during the current calibration cycle are finally obtained, providing an accurate reference for the next calibration, outputting the calibration requirement characteristics that meet the requirements, and providing a basis for the subsequent calibration of the crystal oscillator.

[0077] It can be understood that through multi-dimensional analysis, the influence of environmental factors on the performance of the crystal oscillator can be accurately identified, and then accurate input data can be provided for the calibration of the oscillator. Through temporal interaction verification and historical reference verification, calibration requirements can be intelligently identified and corrected to ensure the accuracy and efficiency of the calibration process. This method can significantly improve the accuracy and efficiency of the calibration process through environmental factor deviation weight allocation and accurate conversion of calibration requirements, and reduces the need for manual intervention.

[0078] More specifically, a dynamic calibration requirement feedback mechanism is established by combining historical data and real-time data to provide support for real-time adjustment of the system. The multi-dimensional calibration requirement analysis can consider the influence of different time periods and different environmental factors on the crystal oscillator, thereby improving the comprehensive performance of the calibration process. The accurate calibration requirement characteristics can ensure that the crystal oscillator maintains the best performance under different environments, improving the long-term stability and reliability of the system.

[0079] Preferably, the steps of obtaining the module performance information of the environmental level calibration module and the signal level calibration module configured in the crystal oscillator, and analyzing the requirement implementation plan for the calibration requirement characteristics according to the module performance information to obtain several frequency calibration schemes for the crystal oscillator include: S41: Obtain the module performance information of the environmental level calibration module and the signal level calibration module configured in the crystal oscillator; wherein, the environmental level calibration module is a functional module pre-deployed in the working environment of the crystal oscillator for controlling the environmental conditions of the working environment, and the signal level calibration module is pre-connected to the crystal oscillator in a signal connection manner for calibrating the clock signal output by the crystal oscillator; S42: Perform digital simulation on the environmental level calibration module and the signal level calibration module according to the module performance information of the environmental level calibration module and the signal level calibration module to obtain an environmental level calibration digital model corresponding to the environmental level calibration module and a signal level calibration digital model corresponding to the signal level calibration module; S43: Perform requirement implementation analysis on the calibration requirement characteristics in terms of the resource requirement dimension of the plan execution, the prediction dimension of the plan execution effect, and the adaptability dimension of the plan execution task according to the environmental level calibration digital model and the signal level calibration model to obtain an environmental level calibration parameter multi-dimensional evaluation map corresponding to the calibration requirement characteristics of the environmental level calibration digital model and the signal level calibration model and a signal level calibration parameter multi-dimensional evaluation map; S44: Select the feasible nodes for collaborative calibration of the environmental level calibration parameter multi-dimensional evaluation map and the signal level calibration parameter multi-dimensional evaluation map to obtain a node combination of the environmental level calibration parameter node and the signal level calibration parameter node; S45: Evaluate the calibration modes of each of the node combinations, perform representative analysis of the calibration modes on each of the node combinations based on the evaluation results, and select several node combinations with the most representative calibration modes for calibration execution mode conversion to obtain several frequency calibration schemes for the crystal oscillator.

[0080] Specifically, collect the module performance information of the environmental level calibration module and the signal level calibration module configured in the crystal oscillator, which is used to control the conditions of the oscillator working environment, such as influencing factors like temperature and humidity. By monitoring and adjusting the environmental factors, ensure the stability of the oscillator, and perform precise calibration on the clock signal output by the crystal oscillator to ensure the frequency stability of the output signal. Accurately obtain and store the module performance data, such as key indicators like accuracy, response time, and adjustment range, and provide a complete description of the environmental and signal calibration modules to ensure that the functions, roles, and performance indicators of the two types of modules can be clearly distinguished and described.

[0081] More specifically, the digital simulation environment level and signal level calibration module digitally simulates the environment level calibration module and the signal level calibration module based on the obtained module performance information. Through simulation, the corresponding environment level calibration digital model and signal level calibration digital model can be obtained for further calibration analysis. Use advanced simulation tools to model the environment and signal level calibration modules to ensure the accuracy of the simulation. The simulation results should include the dynamic response of environmental factors to the oscillator and the precision of signal adjustment.

[0082] More specifically, according to the environment level calibration digital model and the signal level calibration digital model, perform a multi-dimensional requirement implementation analysis on the calibration requirement characteristics. The analysis dimensions include: Pre-plan execution resource requirement dimension: Analyze the required hardware, software resources, and technical support. Pre-plan execution effect prediction dimension: Evaluate the possible effects brought by the calibration plan, such as frequency stability, error range, etc. Pre-plan execution task adaptability dimension: Analyze the adaptability of the calibration plan in different environments or conditions, and evaluate potential problems and challenges during the execution process. Construct a multi-dimensional analysis model to ensure a comprehensive and accurate analysis of the calibration requirements, accurately predict the effects after implementing the calibration, and ensure that the calibration process meets expectations.

[0083] More specifically, according to the results of the requirement implementation analysis, generate a multi-dimensional evaluation atlas of environment level calibration parameters and a multi-dimensional evaluation atlas of signal level calibration parameters. These atlases provide a basis for analyzing the multi-dimensional performance of the calibration plan, can intuitively display the distribution and influence of environment level and signal level calibration parameters, and display the evaluation results of each dimension in a graphical way to ensure the clarity and easy understanding of the information, and ensure that the multi-dimensional evaluation atlas can accurately reflect the actual performance of the calibration parameters.

[0084] More specifically, select the feasible nodes for collaborative calibration of the multi-dimensional evaluation atlas of environment level calibration parameters and the multi-dimensional evaluation atlas of signal level calibration parameters. Through the analysis of each node, determine which nodes can be effectively combined to achieve the best calibration effect. Design an accurate node selection algorithm to ensure that the selected nodes can maximize the calibration effect, and evaluate each feasible node combination to ensure that its synergistic effect can optimize the calibration result.

[0085] More specifically, evaluate the calibration mode of the selected node combination and evaluate its improvement effect on the oscillator performance. Based on the evaluation results, perform a representative analysis of the calibration mode for each node combination, select the most representative node combination, and finally transform it into an actual calibration execution method. Design a calibration mode evaluation model that can quantitatively evaluate the effect of each node combination to ensure that the evaluation results can be accurately transformed into an operable calibration execution strategy.

[0086] More specifically, based on the previous representative analysis of the calibration mode, several node combinations most representative of the calibration mode are selected, and corresponding frequency calibration schemes are formulated. These schemes can provide multiple calibration schemes for the crystal oscillator according to different environmental conditions and signal characteristics to achieve the best frequency stability. Through multi-dimensional evaluation, the most effective and cost-optimal frequency calibration scheme is selected to ensure that the selected frequency calibration scheme can be verified in practice and continuously optimized. It can be understood that through comprehensive module performance analysis and multi-dimensional requirement implementation analysis, several optimal frequency calibration schemes can be provided for the crystal oscillator. These schemes not only meet the current environmental and signal conditions but also can adapt to possible future changes. The selection of nodes for collaborative calibration and mode evaluation can ensure the best coordination between the environmental-level and signal-level calibration modules, maximize the calibration effect, and ensure the long-term stability of the crystal oscillator. By analyzing the resources, effects, and adaptability required for the implementation of the contingency plan, it is ensured that the resources required for the calibration process are reasonably allocated and the calibration task can be smoothly executed under different environmental conditions. After comprehensive evaluation of the node combinations and their representative analysis, they are finally transformed into an operable frequency calibration execution method, making the calibration process more accurate and efficient, and ensuring that the clock signal output by the oscillator meets the predetermined frequency standard.

[0087] Preferably, the steps of collecting auxiliary prediction data for the crystal oscillator based on the enhanced prediction model and assigning execution priorities to various frequency calibration schemes according to the collected auxiliary prediction data, and then calibrating the environmental-level calibration module and the signal-level calibration module according to the frequency calibration scheme with the highest execution priority include: S51: Query the feasibility of extracting enhanced prediction elements for the crystal oscillator based on several enhanced prediction elements analyzable by the enhanced prediction model, and generate an enhanced prediction mode of the crystal oscillator relative to the enhanced prediction model according to the extractable enhanced prediction elements; wherein, the enhanced prediction elements include equipment aging prediction elements, future task prediction elements, and calibration mode adaptability prediction elements; S52: Collect auxiliary prediction data for the corresponding enhanced prediction elements of the crystal oscillator according to the enhanced prediction mode, and substitute the collected auxiliary prediction data into the enhanced prediction model that has completed model training to perform element prediction for each corresponding enhanced prediction element of the crystal oscillator, and obtain the prediction feature distribution of the crystal oscillator for each corresponding enhanced prediction element; S53: Perform adaptability analysis on various frequency calibration schemes based on the prediction feature distribution, and assign execution priorities to various frequency calibration schemes according to the adaptability analysis results to obtain the execution priorities of various frequency calibration schemes; S54: Perform a calibration operation in response to the environmental layer calibration module and the signal layer calibration module according to the frequency calibration scheme with the highest execution priority.

[0088] Specifically, according to the performance and application requirements of the crystal oscillator, based on the enhanced prediction model, first query the feasibility of extracting enhanced prediction elements. These enhanced prediction elements include: device aging prediction elements: analyze the aging trend of the crystal oscillator, evaluate its frequency stability and possible deviation after long-term use; future task prediction elements: predict the requirements of future tasks for the oscillator performance, including performance requirements under different workloads; calibration mode adaptability prediction elements: evaluate the adaptability of different calibration modes to the crystal oscillator, especially the impact of signal calibration and environmental calibration on the oscillator. Build an enhanced prediction model that can integrate multiple factors to support the extraction and analysis of different prediction elements, ensuring that effective prediction elements can be extracted from the operating data of the oscillator and laying a foundation for subsequent prediction data collection.

[0089] More specifically, generate an enhanced prediction mode of the crystal oscillator relative to the enhanced prediction model. According to the query results of the feasibility of extracting enhanced prediction elements, determine the prediction elements that can be extracted, and generate an enhanced prediction mode of the crystal oscillator relative to the enhanced prediction model. This mode comprehensively considers device aging, the requirements of future tasks, and the adaptability of the calibration mode to form a dynamic prediction mode for the crystal oscillator. Based on the extracted enhanced prediction elements, generate a comprehensive and dynamically adjusted prediction mode. The enhanced prediction mode can be adjusted according to real-time data changes to adapt to different working conditions.

[0090] More specifically, based on the generated enhanced prediction mode, perform corresponding auxiliary prediction data collection for the crystal oscillator. Substitute the collected data into the pre-trained enhanced prediction model to obtain the prediction feature distributions of each enhanced prediction element, such as: the trend change of the device aging prediction element, the impact of future task requirements on performance, the adaptability and stability of the calibration mode. Ensure that the collected data is comprehensive and accurate, and can truly reflect the working state of the crystal oscillator and possible future changes. The enhanced prediction model needs to be fully trained to ensure that it can efficiently process data from different elements and give accurate predictions.

[0091] More specifically, the auxiliary prediction data is substituted into the enhanced prediction model for element prediction. The collected auxiliary prediction data is substituted into the enhanced prediction model that has been pre-trained to perform element prediction for each enhanced prediction element, obtaining the prediction feature distribution of each enhanced prediction element of the crystal oscillator for analyzing its future performance. For example: the prediction features of device aging, the prediction of the impact of future tasks, the prediction of the adaptability of various calibration modes to performance. The enhanced prediction model should be able to quickly process the collected auxiliary data and output accurate prediction results to ensure that the prediction results can reflect the actual distribution of each enhanced prediction element and support subsequent analysis.

[0092] More specifically, based on the prediction feature distribution of each enhanced prediction element, an adaptability analysis of different frequency calibration schemes is carried out to evaluate the adaptability of each calibration scheme in the current and future environments. Combining the results of the adaptability analysis, an execution priority is assigned to various frequency calibration schemes. The priority assignment is based on the following factors: the improvement effect of the frequency calibration scheme on the oscillator performance, the adaptability of each scheme to the prediction of future tasks, the stability and adaptability of the calibration mode. Design and implement a multi-dimensional adaptability analysis model that can comprehensively evaluate the advantages and disadvantages of each scheme considering multiple factors. Based on the analysis results, a scientific and reasonable priority assignment is made to different schemes to ensure the optimization of resource and task execution.

[0093] More specifically, according to the frequency calibration scheme with the highest execution priority, the calibration operation to be performed is determined. This operation will include: the operation of the environmental level calibration module: adjusting environmental conditions (such as temperature, humidity, etc.) to adapt to the working requirements of the oscillator; the operation of the signal level calibration module: precisely adjusting the output signal to ensure the accuracy of the clock signal frequency. Ensure that during the execution of the calibration operation, the adjustments of the environmental level and signal level calibration modules reach the required accuracy to ensure the stability of the oscillator frequency. Real-time monitoring and feedback are required during the calibration process to ensure that the calibration effect meets the expectations and make timely adjustments.

[0094] It can be understood that by enhancing the prediction model, the performance of the crystal oscillator under different conditions can be accurately predicted, supporting a more efficient decision-making process. Especially in terms of device aging, task changes, and calibration adaptability, countermeasures can be taken in advance. Through the adaptive analysis and priority allocation of various frequency calibration schemes, the most effective and adaptable calibration scheme can be ensured in actual operation, thereby improving the working stability and accuracy of the oscillator. Based on the prediction data and priority allocation, the calibration operation can be automatically executed and fine-tuned according to real-time feedback, avoiding manual intervention and improving work efficiency and accuracy. According to the prediction feature distribution and task requirements, the calibration scheme can be adapted according to resources and requirements to achieve the optimization of the calibration scheme, thereby reducing costs and improving the overall system performance. By enhancing the dynamic adjustment ability of the prediction model, the calibration strategy can be continuously optimized according to device aging, task demand changes, and environmental changes to maintain the long-term stability and accuracy of the oscillator.

[0095] Referring to Figure 2 As shown, in a second aspect, the present invention provides a frequency calibration device for a crystal oscillator, which is used to implement the frequency calibration method for a crystal oscillator described in any one of the first aspects, including: A data recording module, which is used to make the crystal oscillator continuously output a clock signal as a frequency source, and continuously record the timing of each clock signal to obtain a signal sequence to be measured. At the same time, the working environment status of the crystal oscillator at each time node is continuously recorded through a pre-deployed sensor group to obtain the working environment sequence of the crystal oscillator; A data transmission module, which is used to perform sequence fusion processing on the signal sequence to be measured and the working environment sequence to obtain the deviation analysis reference features of the crystal oscillator, and transmit the deviation analysis reference features to a specified network data platform through wireless data at regular intervals; A requirement analysis module, which is used to perform multi-dimensional calibration requirement analysis on the deviation analysis reference features according to the reference signal sequence stored on the network data platform and the historical calibration records of the crystal oscillator to obtain the calibration requirement features of the crystal oscillator in the current calibration cycle; A scheme analysis module, which is used to obtain the module performance information of the environment-level calibration module and the signal-level calibration module configured by the crystal oscillator, and perform requirement implementation scheme analysis on the calibration requirement features according to the module performance information to obtain several frequency calibration schemes for the crystal oscillator; A calibration operation module, which is used to collect auxiliary prediction data for the crystal oscillator based on the enhanced prediction model, and perform execution priority allocation on various frequency calibration schemes according to the collected auxiliary prediction data, so as to perform calibration operations on the environment-level calibration module and the signal-level calibration module according to the frequency calibration scheme with the highest execution priority.

[0096] In this embodiment, for the specific implementation of each module in the above device embodiment, please refer to the description in the above method embodiment, and details are not described herein again.

[0097] In a third aspect, the present invention provides a computer device, including a memory and a processor, where the memory stores a computer program that can run on the processor, and when the processor executes the computer program, it implements a frequency calibration method for a crystal oscillator according to any one of the first aspect.

[0098] In a fourth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is run by a processor, the processor is caused to execute a frequency calibration method for a crystal oscillator according to any one of the first aspect.

[0099] The above are only the preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A frequency calibration method for a crystal oscillator, characterized in that: include: The crystal oscillator is used as a frequency source to continuously generate clock signals, and each clock signal is continuously recorded in time sequence to obtain a signal sequence to be tested. At the same time, the working environment conditions of the crystal oscillator at each time node are continuously recorded through a pre-deployed sensor group to obtain a working environment sequence of the crystal oscillator; Performing sequence fusion processing on the signal sequence to be tested and the working environment sequence to obtain a deviation analysis reference feature of the crystal oscillator, and transmitting the deviation analysis reference feature to a designated network data platform via wireless data at predetermined intervals; According to the reference signal sequence and the historical calibration record of the crystal oscillator stored on the network data platform, a multi-dimensional calibration requirement analysis is performed on the deviation analysis reference feature to obtain the calibration requirement feature of the crystal oscillator in the current round of calibration cycle; Acquire module performance information of an environment level calibration module and a signal level calibration module configured by the crystal oscillator, and perform demand implementation solution analysis on the calibration demand characteristics according to the module performance information to obtain several frequency calibration solutions for the crystal oscillator; Auxiliary prediction data of the crystal oscillator is collected based on the enhanced prediction model, and execution priorities are assigned to various frequency calibration schemes according to the collected auxiliary prediction data, so that the environmental level calibration module and the signal level calibration module are calibrated according to the frequency calibration scheme with the highest execution priority.

2. The frequency calibration method of a crystal oscillator according to claim 1, characterized in that: The steps of making a crystal oscillator as a frequency source continuously output a clock signal, and continuously recording each clock signal in time sequence to obtain a signal sequence to be tested, and continuously recording the working environment conditions of the crystal oscillator at each time node through a pre-deployed sensor group to obtain the working environment sequence of the crystal oscillator include: Performing clock frequency source operating parameter configuration on the crystal oscillator so that the crystal oscillator continuously generates a clock signal as a frequency source; The crystal oscillator is synchronously received and timestamped by a plurality of synchronous clock function units, and the timestamps generated by the synchronous clock function units are weighted and merged to obtain a recording timestamp of the clock signal generated by the crystal oscillator; Recording the clock signal with the recording timestamp at the corresponding coordinate position through the pre-constructed time coordinate axis to obtain a signal sequence to be measured; The working environment conditions of the crystal oscillator are continuously collected by a sensor group pre-deployed in the vicinity of the crystal oscillator to obtain sensor network data for feedback of the working environment conditions of the crystal oscillator; wherein the sensor network data includes temperature level data, humidity level data, air pressure level data, vibration level data, and electromagnetic interference level data; The sensor network data collected at each time node is recorded at the corresponding coordinate position through the pre-constructed time coordinate axis to obtain the working environment sequence.

3. The frequency calibration method of a crystal oscillator according to claim 2, characterized in that: The steps of performing sequence fusion processing on the signal sequence to be tested and the working environment sequence to obtain a deviation analysis reference feature of the crystal oscillator, and transmitting the deviation analysis reference feature to a designated network data platform via wireless data at predetermined intervals include: According to the time coordinate axes of the signal sequence to be tested and the working environment sequence, aligning the time coordinate systems of the signal sequence to be tested and the working environment sequence, so that the signal sequence to be tested and the working environment sequence are in a state of time coordinate alignment; Based on the time coordinate alignment state of the signal sequence to be tested and the working environment sequence, the time-space correlation connection of the sequence data of the signal sequence to be tested and the working environment sequence is performed to construct an information connection vector between each signal to be tested of the signal sequence to be tested and each sensor network data of the working environment sequence; Performing a time series correlation analysis between information connection vectors between each test signal of the test signal sequence and each sensor network data of the working environment sequence, so as to generate a connection deviation vector for describing the time series correlation between each information connection vector; The information connection vector and the connection deviation vector are arranged and combined according to a predetermined specification to obtain a sequence fusion feature matrix; Performing a supervision and evaluation of the sequence corresponding time of the signal sequence to be tested and the working environment sequence according to a predetermined time standard, when the supervision and evaluation result shows that the signal sequence to be tested and the working environment sequence meet the predetermined time standard, annotating the sequence information compression and decompression mode of the signal sequence to be tested and the working environment sequence according to the sequence fusion feature matrix to obtain a deviation analysis reference feature; Acquire the registration information of the crystal oscillator on the designated network data platform, acquire the generation time information corresponding to the deviation analysis reference feature, package the deviation analysis reference feature according to the registration information and the generation time information, and transmit the packaged deviation analysis reference feature to the designated network data platform via wireless data.

4. The frequency calibration method of a crystal oscillator according to claim 1, characterized in that: The steps of performing multi-dimensional calibration requirement analysis on the deviation analysis reference features according to the reference signal sequence and the historical calibration record of the crystal oscillator stored on the network data platform to obtain the calibration requirement features of the crystal oscillator in the current round of calibration cycle include: Performing preliminary information analysis on the deviation analysis reference feature to obtain packaging information of the deviation analysis reference feature; wherein the packaging information includes crystal oscillator registration information corresponding to the deviation analysis reference feature and generation time information of the deviation analysis reference feature; Retrieving the reference signal sequence and the historical calibration record of the crystal oscillator from the network data platform according to the packaging information to obtain the reference signal sequence and the historical calibration record of the crystal oscillator corresponding to the deviation analysis reference feature; Decompressing the deviation analysis reference features to obtain a signal sequence to be tested, a working environment sequence, and a sequence fusion feature matrix; Performing time alignment matching on the signal sequence to be tested according to the reference signal sequence to obtain a signal deviation characteristic distribution of the signal sequence to be tested relative to the reference signal sequence; Performing environmental impact factor analysis on the working environment sequence relative to the signal deviation feature distribution according to the sequence fusion feature matrix to obtain an environmental impact factor sequence corresponding to the signal deviation feature distribution; Performing a time unit deviation analysis on the signal deviation feature distribution in a signal deviation time series accumulation mode according to the environmental influencing factor sequence to obtain a unit time deviation feature set of the environmental influencing factor sequence; wherein the unit time deviation feature set includes a plurality of unit time deviation features arranged in time sequence, and the unit time deviation feature is used to predict multiple possibilities of the oscillation deviation of the crystal oscillator caused by the environmental influencing factors in a unit time; Performing a timing interaction verification between each unit time deviation feature within the unit time deviation feature set, and performing a historical reference verification on the unit time deviation feature set based on the historical calibration record of the crystal oscillator, and performing a weighted confidence analysis on the unit time deviation feature set through the timing interaction verification and the historical reference verification to obtain a unit time deviation analysis result corresponding to each unit time deviation feature in the unit time deviation feature set; Performing environmental factor deviation weight allocation on the crystal oscillator according to the unit time deviation analysis results corresponding to each of the unit time deviation characteristics, so as to obtain deviation factor weights of various environmental factors of the working environment of the crystal oscillator; The deviation factor weights of various environmental factors in the working environment of the crystal oscillator are converted into a calibration requirement form, and the calibration requirement form conversion is corrected with historical reference based on the historical calibration record of the crystal oscillator to obtain the calibration requirement characteristics of the crystal oscillator in the current round of calibration cycle.

5. The frequency calibration method of a crystal oscillator according to claim 1, characterized in that: The steps of obtaining module performance information of an environment level calibration module and a signal level calibration module configured by a crystal oscillator, and performing a demand implementation solution analysis on the calibration demand characteristics according to the module performance information to obtain several frequency calibration solutions of the crystal oscillator include: Acquire module performance information of an environmental level calibration module and a signal level calibration module configured by the crystal oscillator; wherein the environmental level calibration module is a functional module pre-deployed in the working environment of the crystal oscillator and used to control the environmental conditions of the working environment, and the signal level calibration module is pre-signally connected to the crystal oscillator and used to perform signal calibration on the clock signal output by the crystal oscillator; Digitally simulating the environmental level calibration module and the signal level calibration module according to the module performance information of the environmental level calibration module and the signal level calibration module to obtain an environmental level calibration digital model corresponding to the environmental level calibration module and a signal level calibration digital model corresponding to the signal level calibration module; According to the environmental level calibration digital model and the signal level calibration model, the calibration requirement characteristics are analyzed for the requirements of plan execution resource requirements, plan execution effect prediction, and plan execution task adaptability, so as to obtain a multi-dimensional evaluation map of environmental level calibration parameters and a multi-dimensional evaluation map of signal level calibration parameters of the environmental level calibration digital model and the signal level calibration model corresponding to the calibration requirement characteristics; Selecting feasible nodes for collaborative calibration of the multidimensional evaluation graph of the environment level calibration parameters and the multidimensional evaluation graph of the signal level calibration parameters to obtain a node combination of the environment level calibration parameter nodes and the signal level calibration parameter nodes; The calibration mode of each node combination is evaluated, and based on the evaluation results, the representativeness analysis of the calibration mode of each node combination is performed to select several node combinations that are most representative of the calibration mode for conversion of the calibration execution mode, so as to obtain several frequency calibration schemes of the crystal oscillator.

6. The frequency calibration method of a crystal oscillator according to claim 1, characterized in that: The steps of collecting auxiliary prediction data of the crystal oscillator based on the enhanced prediction model, and assigning execution priorities to various frequency calibration schemes according to the collected auxiliary prediction data, so as to calibrate the environment level calibration module and the signal level calibration module according to the frequency calibration scheme with the highest execution priority include: Based on a number of enhanced prediction elements that can be analyzed by the enhanced prediction model, the feasibility of extracting enhanced prediction elements is queried for the crystal oscillator, so as to generate an enhanced prediction mode of the crystal oscillator relative to the enhanced prediction model according to the extractable enhanced prediction elements; wherein the enhanced prediction elements include equipment aging prediction elements, future task prediction elements, and calibration mode adaptability prediction elements; According to the enhanced prediction mode, the auxiliary prediction data of the enhanced prediction elements corresponding to the crystal oscillator are collected, and the collected auxiliary prediction data are substituted into the enhanced prediction model that has completed model training in advance, so as to perform element prediction of each enhanced prediction element corresponding to the crystal oscillator, and obtain the prediction feature distribution of each enhanced prediction element of the crystal oscillator; Performing adaptability analysis on various frequency calibration schemes based on the predicted characteristic distribution, and assigning execution priorities to the various frequency calibration schemes according to the adaptability analysis results to obtain execution priorities of the various frequency calibration schemes; The environment level calibration module and the signal level calibration module are responsive to the calibration operation according to the frequency calibration scheme having the highest execution priority.

7. A frequency calibration device for a crystal oscillator, characterized in that: A method for calibrating a frequency of a crystal oscillator according to any one of claims 1 to 6, comprising: A data recording module is used to make the crystal oscillator as a frequency source continuously generate clock signals, and continuously record the timing of each clock signal to obtain a signal sequence to be tested, and at the same time, continuously record the working environment conditions of the crystal oscillator at each time node through a pre-deployed sensor group to obtain a working environment sequence of the crystal oscillator; A data transmission module, used for performing sequence fusion processing on the signal sequence to be tested and the working environment sequence to obtain a deviation analysis reference feature of the crystal oscillator, and transmitting the deviation analysis reference feature to a designated network data platform via wireless data at predetermined intervals; A demand analysis module, for performing multi-dimensional calibration demand analysis on the deviation analysis reference features according to the reference signal sequence and the historical calibration records of the crystal oscillator stored on the network data platform, so as to obtain the calibration demand features of the crystal oscillator in the current round of calibration cycle; A scheme analysis module is used to obtain module performance information of an environment level calibration module and a signal level calibration module configured by the crystal oscillator, and perform a demand implementation scheme analysis on the calibration demand characteristics according to the module performance information to obtain several frequency calibration schemes of the crystal oscillator; The calibration operation module is used to collect auxiliary prediction data for the crystal oscillator based on the enhanced prediction model, and to assign execution priorities to various frequency calibration schemes according to the collected auxiliary prediction data, so as to perform calibration operations on the environmental level calibration module and the signal level calibration module according to the frequency calibration scheme with the highest execution priority.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program executable on the processor, wherein: When the processor executes the computer program, the frequency calibration method of a crystal oscillator according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the processor is enabled to execute a frequency calibration method for a crystal oscillator according to any one of claims 1 to 6.

Images