Quartz crystal oscillator electric vehicle control method based on intelligent application

Abstract

The invention discloses a quartz crystal oscillator electric vehicle control method based on intelligent application, particularly relates to the field of data processing, and comprises the steps of time region division, data acquisition, data analysis, comprehensive analysis and intelligent control. According to the method, the continuity and integrity of data are ensured through time region division and data acquisition, a basis is provided for subsequent analysis, data analysis and the establishment of a comprehensive analysis model enable the performance evaluation of the quartz crystal oscillation electric vehicle to be more accurate and scientific, and the application of an intelligent control method has good application prospects. Real-time monitoring and abnormity early warning of the performance of the quartz crystal oscillator electric car are achieved, normal operation and safety of the quartz crystal oscillator electric car are ensured, on the whole, the operation efficiency and reliability of the quartz crystal oscillator electric car are improved, the maintenance cost is reduced, and the quartz crystal oscillator electric car performance early warning system has remarkable technical and economic values.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and more specifically, to a quartz crystal oscillator tram control method based on intelligent applications. Background Technology

[0002] Existing quartz crystal oscillator-based tram control technology typically follows a fixed operating procedure. First, the system performs initial measurements of various parameters of the quartz crystal oscillator, and then adjusts the tram's operating status based on the measurement results. This process includes multiple stages such as data acquisition, parameter analysis, and status adjustment, aiming to ensure the tram operates in optimal condition.

[0003] However, existing technologies still reveal some shortcomings in practical applications. For example, the accuracy and real-time performance of data acquisition need improvement; the parameter analysis methods are relatively simple and cannot fully reflect the actual performance of the quartz crystal oscillator; and the flexibility of state adjustment is insufficient, making it unable to adapt to complex and changing operating environments. These problems limit further improvements in the performance of quartz crystal oscillator trams. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present invention provide a quartz crystal oscillator tram control method based on intelligent applications, which solves the problems mentioned in the background art through the following solutions.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a quartz crystal oscillator tram control method based on intelligent applications, comprising:

[0006] Step 1: Time Zone Division: This step is used to determine the data acquisition time of the target quartz crystal oscillator tram as the target time zone. The target time zone is divided into sub-time zones by equal time division and labeled as 1, 2...n in sequence.

[0007] Step 2: Data Acquisition: This step involves collecting data on the oscillation characteristics, environmental adaptability, electrical characteristics, and performance stability of the target quartz crystal oscillator tram, and preprocessing the collected data.

[0008] Step 3: Data Analysis: Used to establish oscillation characteristic data analysis models, environmental adaptability data analysis models, electrical characteristic data analysis models, and performance stability data analysis models;

[0009] Step 4: Comprehensive Analysis: This step is used to establish a comprehensive analysis model. The data analysis results are imported into the comprehensive analysis model to calculate the comprehensive optimization index of the target quartz crystal oscillator tram.

[0010] Step 5: Intelligent Control: This step is used to establish a comprehensive anomaly index standard value, to make anomaly judgments on the target quartz crystal oscillator tram based on the comprehensive anomaly index standard value, and to issue intelligent control commands based on the judgment results.

[0011] Preferably, the oscillation characteristic data includes crystal frequency stability offset, start-up timing rise time, amplitude attenuation coefficient, and load capacitance deviation, labeled as FS, FR, FA, and FL, respectively; environmental adaptability data includes frequency drift rate under high and low temperature cycling, mechanical shock response curve, humidity sensitivity coefficient, and frequency response to air pressure change, labeled as TF, TM, TH, and TB, respectively; electrical characteristic data includes equivalent series resistance, drive level dependence, resonant impedance phase angle, and frequency aging rate, labeled as ES, ED, ER, and EF, respectively; and performance stability data includes short-term frequency stability, phase noise, harmonic distortion, and frequency temperature compensation coefficient, labeled as ST, SP, SH, and SF, respectively.

[0012] Preferably, the crystal oscillator frequency stability offset is recorded every 10°C using a frequency counter within a temperature range of -40°C to +85°C, and temperature data is synchronously acquired using a digital temperature sensor. The start-up timing rise time is captured by a high-speed oscilloscope from the moment the crystal oscillator is powered on to the time of stable oscillation, with the sampling rate set to 1GS / s. The amplitude attenuation coefficient is measured by using a spectrum analyzer to measure the amplitude change of the oscillation signal over time, recording data points per minute within one hour. The load capacitance deviation is measured using a precision LCR bridge at the nominal operating frequency, with a measurement accuracy of 0.01pF.

[0013] Preferably, the frequency drift rate under high and low temperature cycling is tested by cycling from -40°C to +85°C in a temperature test chamber, with data recorded every 1°C using a precision frequency meter. The mechanical shock response curve is obtained by applying a half-sine impact with a duration of 0.5ms and an acceleration range of 1500g using an impact test platform, and acquiring the complete response waveform. The humidity sensitivity coefficient is obtained by recording the frequency value every 5%RH during the change from 20%RH to 95%RH in a humidity chamber. The air pressure change frequency response is obtained by recording a set of data every 5kPa during the change from standard atmospheric pressure to 70kPa in a pressure chamber.

[0014] Preferably, the equivalent series resistance value is measured at the resonant frequency using a vector network analyzer, which requires removing the influence of the test fixture. The drive level dependence is achieved by changing the drive power within the range of 100μW to 1mW using an adjustable power source, and recording the frequency changes. The resonant impedance phase angle is measured by scanning within ±100Hz of the resonant frequency using an impedance analyzer, and the phase angle changes are recorded. The frequency aging rate is monitored continuously for 30 days under constant temperature and humidity conditions, with the frequency value recorded at the same time each day.

[0015] Preferably, the short-term frequency stability is calculated by continuously collecting 1000 data points at a sampling interval of τ = 1s using a high-precision frequency counter to calculate the Allan variance; the phase noise is measured by scanning within the carrier offset range of 1Hz to 100kHz using a phase noise analyzer; the harmonic distortion is measured by measuring the amplitude of the fundamental frequency and at least 5 harmonic components using a spectrum analyzer; and the frequency temperature compensation coefficient is obtained by simultaneously recording frequency and temperature data during temperature cycling and fitting the β value using the least squares method.

[0016] Preferably, the oscillation characteristic data analysis model is used to analyze oscillation characteristic data. The oscillation characteristic data is imported into the oscillation characteristic data analysis model to calculate the oscillation characteristic evaluation value for each sub-time region, specifically expressed as follows: F i FS represents the oscillation characteristic evaluation value of the i-th sub-time region. i FR represents the frequency stability offset of the crystal oscillator in the i-th sub-time region. i FA represents the start-up timing rise time of the i-th sub-time region. i FL represents the amplitude attenuation coefficient for the i-th sub-time region. i This represents the load capacitance deviation value of the i-th sub-time region, and n represents the number of sub-time regions.

[0017] Preferably, the environmental adaptability data analysis model is used to analyze environmental adaptability data. The environmental adaptability data is imported into the model to calculate the environmental adaptability assessment value for each sub-time region, specifically expressed as follows: T i TF represents the environmental adaptability assessment value for the i-th sub-time region. i TM represents the frequency drift rate under high and low temperature cycling in the i-th sub-time region. i TH represents the mechanical shock response curve for the i-th sub-time region. i Represents the humidity sensitivity coefficient for the i-th sub-time region, TB i Let n represent the frequency response of air pressure change in the i-th sub-time region, and n represent the number of sub-time regions.

[0018] Preferably, the electrical characteristic data analysis model is used to analyze electrical characteristic data. The electrical characteristic data is imported into the electrical characteristic data analysis model to calculate the electrical characteristic evaluation value for each sub-time region, specifically expressed as follows: E i ES represents the electrical characteristic evaluation value for the i-th sub-time region. i ED represents the equivalent series resistance value of the i-th sub-time region. iER represents the drive level dependence of the i-th sub-time region. i EF represents the resonant impedance phase angle of the i-th sub-time region. i denoted as the frequency aging rate of the i-th sub-time region, and n represents the number of sub-time regions.

[0019] Preferably, the performance stability data analysis model is used to analyze performance stability data. The performance stability data is imported into the performance stability data analysis model to calculate the performance stability evaluation value for each sub-time region, specifically expressed as follows: S i ST represents the performance stability evaluation value for the i-th sub-time region. i SP represents the short-term frequency stability of the i-th sub-time region. i SH represents the phase noise of the i-th sub-time region. i SF represents the harmonic distortion of the i-th sub-time region. i represents the frequency-temperature compensation coefficient for the i-th sub-time region, and n represents the number of sub-time regions.

[0020] Preferably, the comprehensive analysis model is specifically represented as follows: η represents the comprehensive optimization index of the target quartz crystal oscillator electric vehicle, F i T represents the oscillation characteristic evaluation value of the i-th sub-time region. i E represents the environmental adaptability assessment value for the i-th sub-time region. i S represents the electrical characteristic evaluation value for the i-th sub-time region. i λ represents the performance stability assessment value of the i-th sub-time region, and λ represents other influencing factors of the comprehensive anomaly index.

[0021] Preferably, the standard value of the comprehensive anomaly index is marked as η0. When η0≥η, it means that no abnormality has occurred in the target quartz crystal oscillator tram, and the detection of the target quartz crystal oscillator tram is maintained. When η0<η, it means that the target quartz crystal oscillator tram is abnormal, and an early warning signal is sent to the user control terminal.

[0022] The technical effects and advantages of this invention are as follows:

[0023] This invention defines the data acquisition time of the target quartz crystal oscillator tram as the target time zone by dividing the time into equal sub-time zones. This ensures the continuity and integrity of the data. This time zone division facilitates independent analysis of data from different time periods, leading to a better understanding of the tram's performance variations and time-related characteristics. By acquiring various data from the target quartz crystal oscillator tram, including oscillation characteristic data, environmental adaptability data, electrical characteristic data, and performance stability data, a comprehensive evaluation is achieved. This data covers the tram's core performance indicators and the impact of the external environment, providing data support for subsequent precise analysis and intelligent control. Preprocessing this data further improves the accuracy and efficiency of the analysis. By establishing oscillation characteristic data analysis models, environmental adaptability data analysis models, electrical characteristic data analysis models, and performance stability data analysis models through data analysis, in-depth analysis and evaluation of the acquired data are possible. These models can... Transforming complex raw data into intuitive evaluation values ​​helps to better understand and judge the performance status of the quartz crystal oscillator tram. This data analysis method provides a scientific basis for subsequent intelligent control. By establishing a comprehensive analysis model through integrated analysis, the evaluation values ​​of oscillation characteristics, environmental adaptability, electrical characteristics, and performance stability in various time zones are combined to calculate the comprehensive optimization index of the target quartz crystal oscillator tram. This comprehensive analysis method can comprehensively reflect the overall performance status of the quartz crystal oscillator tram, providing more comprehensive and accurate information for intelligent control. Through intelligent control, the target quartz crystal oscillator tram is judged for anomalies based on the comprehensive anomaly index standard value, and intelligent control commands are issued according to the judgment results. This intelligent control method can monitor the performance status of the quartz crystal oscillator tram in real time. Once an anomaly is detected, an early warning signal is immediately issued to the user control terminal, thereby ensuring the normal operation and safety of the quartz crystal oscillator tram. At the same time, the intelligent control method can also adjust the control strategy according to specific situations to achieve more efficient and intelligent management. Attached Figure Description

[0024] Figure 1 This is a schematic diagram of the overall structure of the present invention. Detailed Implementation

[0025] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] refer to Figure 1The method for controlling a quartz crystal oscillator tram based on intelligent applications, as shown, includes the following steps:

[0027] Step 1: Time Zone Division: This step is used to determine the data acquisition time of the target quartz crystal oscillator tram as the target time zone. The target time zone is divided into sub-time zones by equal time division, and they are sequentially marked as 1, 2...n.

[0028] Step 2: Data Acquisition: This step involves collecting data on the oscillation characteristics, environmental adaptability, electrical characteristics, and performance stability of the target quartz crystal oscillator tram, and preprocessing the collected data.

[0029] The oscillation characteristic data includes crystal frequency stability offset, start-up timing rise time, amplitude attenuation coefficient, and load capacitance deviation, labeled as FS, FR, FA, and FL, respectively. The environmental adaptability data includes frequency drift rate under high and low temperature cycling, mechanical shock response curve, humidity sensitivity coefficient, and frequency response to air pressure change, labeled as TF, TM, TH, and TB, respectively. The electrical characteristic data includes equivalent series resistance, drive level dependence, resonant impedance phase angle, and frequency aging rate, labeled as ES, ED, ER, and EF, respectively. The performance stability data includes short-term frequency stability, phase noise, harmonic distortion, and frequency temperature compensation coefficient, labeled as ST, SP, SH, and SF, respectively.

[0030] The crystal oscillator frequency stability offset is measured by recording the frequency value every 10°C within a temperature range of -40°C to +85°C using a frequency counter. Temperature data is collected synchronously using a digital temperature sensor. The start-up timing rise time is captured by a high-speed oscilloscope from the moment the crystal is powered on to the moment it stabilizes. The sampling rate is set to 1GS / s. The amplitude attenuation coefficient is measured by measuring the amplitude change of the oscillation signal over time using a spectrum analyzer. Data points are recorded every minute within one hour. The load capacitance deviation is measured using a precision LCR bridge at the nominal operating frequency. The measurement accuracy must reach 0.01pF.

[0031] The frequency drift rate under high and low temperature cycling was tested in a temperature test chamber from -40℃ to +85℃, with data recorded every 1℃ using a precision frequency meter. The mechanical shock response curve was obtained by applying a half-sine impact with a duration of 0.5ms and an acceleration range of 1500g using an impact test platform, and acquiring the complete response waveform. The humidity sensitivity coefficient was obtained by recording the frequency value every 5%RH during the change from 20%RH to 95%RH in a humidity chamber. The air pressure change frequency response was obtained by recording a set of data every 5kPa during the change from standard atmospheric pressure to 70kPa in a pressure chamber.

[0032] The equivalent series resistance value is measured at the resonant frequency using a vector network analyzer, which requires removing the influence of the test fixture. The drive level dependence is determined by changing the drive power within the range of 100μW to 1mW using an adjustable power source, and the frequency change is recorded. The resonant impedance phase angle is determined by scanning within ±100Hz of the resonant frequency using an impedance analyzer, and the phase angle change is recorded. The frequency aging rate is determined by monitoring continuously for 30 days under constant temperature and humidity conditions, with the frequency value recorded at the same time each day.

[0033] The short-term frequency stability is calculated by continuously collecting 1000 data points at a sampling interval of τ=1s using a high-precision frequency counter to calculate the Allan variance. The phase noise is measured by scanning within the carrier offset range of 1Hz to 100kHz using a phase noise analyzer. The harmonic distortion is measured by measuring the amplitude of the fundamental frequency and at least 5 harmonic components using a spectrum analyzer. The frequency temperature compensation coefficient is obtained by simultaneously recording frequency and temperature data during temperature cycling and fitting the β value using the least squares method.

[0034] Step 3: Data Analysis: Used to establish oscillation characteristic data analysis models, environmental adaptability data analysis models, electrical characteristic data analysis models, and performance stability data analysis models.

[0035] The oscillation characteristic data analysis model is used to analyze oscillation characteristic data. The oscillation characteristic data is imported into the model to calculate the oscillation characteristic evaluation value for each sub-time region, specifically expressed as follows: F i FS represents the oscillation characteristic evaluation value of the i-th sub-time region. i FR represents the frequency stability offset of the crystal oscillator in the i-th sub-time region. i FA represents the start-up timing rise time of the i-th sub-time region. i FL represents the amplitude attenuation coefficient for the i-th sub-time region. i This represents the load capacitance deviation value of the i-th sub-time region, and n represents the number of sub-time regions.

[0036] The environmental adaptability data analysis model is used to analyze environmental adaptability data. By importing the environmental adaptability data into the model, the environmental adaptability assessment value for each sub-time region is calculated, specifically as follows: T i TF represents the environmental adaptability assessment value for the i-th sub-time region. i TM represents the frequency drift rate under high and low temperature cycling in the i-th sub-time region. i TH represents the mechanical shock response curve for the i-th sub-time region. i Represents the humidity sensitivity coefficient for the i-th sub-time region, TB iLet n represent the frequency response of air pressure change in the i-th sub-time region, and n represent the number of sub-time regions.

[0037] The electrical characteristic data analysis model is used to analyze electrical characteristic data. The electrical characteristic data is imported into the model to calculate the electrical characteristic evaluation value for each sub-time region, specifically as follows: E i ES represents the electrical characteristic evaluation value for the i-th sub-time region. i ED represents the equivalent series resistance value of the i-th sub-time region. i ER represents the drive level dependence of the i-th sub-time region. i EF represents the resonant impedance phase angle of the i-th sub-time region. i denoted as the frequency aging rate of the i-th sub-time region, and n represents the number of sub-time regions.

[0038] The performance stability data analysis model is used to analyze performance stability data. By importing the performance stability data into the model, the performance stability evaluation value for each sub-time region is calculated, specifically as follows: S i ST represents the performance stability evaluation value for the i-th sub-time region. i SP represents the short-term frequency stability of the i-th sub-time region. i SH represents the phase noise of the i-th sub-time region. i SF represents the harmonic distortion of the i-th sub-time region. i represents the frequency-temperature compensation coefficient for the i-th sub-time region, and n represents the number of sub-time regions.

[0039] Step 4: Comprehensive Analysis: This step is used to establish a comprehensive analysis model. The data analysis results are imported into the comprehensive analysis model to calculate the comprehensive optimization index of the target quartz crystal oscillator tram.

[0040] The comprehensive analysis model is specifically represented as follows: η represents the comprehensive optimization index of the target quartz crystal oscillator electric vehicle, F i T represents the oscillation characteristic evaluation value of the i-th sub-time region. i E represents the environmental adaptability assessment value for the i-th sub-time region. i S represents the electrical characteristic evaluation value for the i-th sub-time region. i λ represents the performance stability assessment value of the i-th sub-time region, and λ represents other influencing factors of the comprehensive anomaly index.

[0041] Step 5: Intelligent Control: This step is used to establish a comprehensive anomaly index standard value, to make anomaly judgments on the target quartz crystal oscillator tram based on the comprehensive anomaly index standard value, and to issue intelligent control commands based on the judgment results.

[0042] The standard value of the comprehensive anomaly index is marked as η0. When η0≥η, it means that there is no abnormality in the target quartz crystal oscillator tram, and the detection of the target quartz crystal oscillator tram is maintained. When η0<η, it means that the target quartz crystal oscillator tram is abnormal, and an early warning signal is sent to the user control terminal.

[0043] This invention defines the data acquisition time of the target quartz crystal oscillator tram as the target time zone by dividing the time into equal sub-time zones. This ensures the continuity and integrity of the data. This time zone division facilitates independent analysis of data from different time periods, leading to a better understanding of the tram's performance variations and time-related characteristics. By acquiring various data from the target quartz crystal oscillator tram, including oscillation characteristic data, environmental adaptability data, electrical characteristic data, and performance stability data, a comprehensive evaluation is achieved. This data covers the tram's core performance indicators and the impact of the external environment, providing data support for subsequent precise analysis and intelligent control. Preprocessing this data further improves the accuracy and efficiency of the analysis. By establishing oscillation characteristic data analysis models, environmental adaptability data analysis models, electrical characteristic data analysis models, and performance stability data analysis models through data analysis, in-depth analysis and evaluation of the acquired data are possible. These models can... Transforming complex raw data into intuitive evaluation values ​​helps to better understand and judge the performance status of the quartz crystal oscillator tram. This data analysis method provides a scientific basis for subsequent intelligent control. By establishing a comprehensive analysis model through integrated analysis, the evaluation values ​​of oscillation characteristics, environmental adaptability, electrical characteristics, and performance stability in various time zones are combined to calculate the comprehensive optimization index of the target quartz crystal oscillator tram. This comprehensive analysis method can comprehensively reflect the overall performance status of the quartz crystal oscillator tram, providing more comprehensive and accurate information for intelligent control. Through intelligent control, the target quartz crystal oscillator tram is judged for anomalies based on the comprehensive anomaly index standard value, and intelligent control commands are issued according to the judgment results. This intelligent control method can monitor the performance status of the quartz crystal oscillator tram in real time. Once an anomaly is detected, an early warning signal is immediately issued to the user control terminal, thereby ensuring the normal operation and safety of the quartz crystal oscillator tram. At the same time, the intelligent control method can also adjust the control strategy according to specific situations to achieve more efficient and intelligent management.

[0044] Secondly: The accompanying drawings of the embodiments disclosed in this invention only involve the structures involved in the embodiments disclosed in this invention. Other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of this invention can be combined with each other.

[0045] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A quartz crystal oscillator tram control method based on intelligent applications, characterized in that, include: Step 1: Time Zone Division: This step is used to determine the data acquisition time of the target quartz crystal oscillator tram as the target time zone. The target time zone is divided into sub-time zones by equal time division and labeled as 1, 2...n in sequence. Step 2: Data Acquisition: This step involves collecting data on the oscillation characteristics, environmental adaptability, electrical characteristics, and performance stability of the target quartz crystal oscillator tram, and preprocessing the collected data. Step 3: Data Analysis: Used to establish oscillation characteristic data analysis models, environmental adaptability data analysis models, electrical characteristic data analysis models, and performance stability data analysis models; Step 4: Comprehensive Analysis: This step is used to establish a comprehensive analysis model. The data analysis results are imported into the comprehensive analysis model to calculate the comprehensive optimization index of the target quartz crystal oscillator tram. Step 5: Intelligent Control: This step is used to establish a comprehensive anomaly index standard value, to make anomaly judgments on the target quartz crystal oscillator tram based on the comprehensive anomaly index standard value, and to issue intelligent control commands based on the judgment results.

2. The quartz crystal oscillator tram control method based on intelligent applications according to claim 1, characterized in that: The oscillation characteristic data includes crystal frequency stability offset, start-up timing rise time, amplitude attenuation coefficient, and load capacitance deviation, labeled as FS, FR, FA, and FL, respectively. The environmental adaptability data includes frequency drift rate under high and low temperature cycling, mechanical shock response curve, humidity sensitivity coefficient, and frequency response to air pressure change, labeled as TF, TM, TH, and TB, respectively. The electrical characteristic data includes equivalent series resistance, drive level dependence, resonant impedance phase angle, and frequency aging rate, labeled as ES, ED, ER, and EF, respectively. The performance stability data includes short-term frequency stability, phase noise, harmonic distortion, and frequency temperature compensation coefficient, labeled as ST, SP, SH, and SF, respectively.

3. The quartz crystal oscillator tram control method based on intelligent applications according to claim 1, characterized in that: The oscillation characteristic data analysis model is used to analyze oscillation characteristic data. The oscillation characteristic data is imported into the model to calculate the oscillation characteristic evaluation value for each sub-time region, specifically expressed as follows: F i FS represents the oscillation characteristic evaluation value of the i-th sub-time region. i FR represents the frequency stability offset of the crystal oscillator in the i-th sub-time region. i FA represents the start-up timing rise time of the i-th sub-time region. i FL represents the amplitude attenuation coefficient for the i-th sub-time region. i This represents the load capacitance deviation value of the i-th sub-time region, and n represents the number of sub-time regions.

4. The quartz crystal oscillator tram control method based on intelligent applications according to claim 1, characterized in that: The environmental adaptability data analysis model is used to analyze environmental adaptability data. By importing the environmental adaptability data into the model, the environmental adaptability assessment value for each sub-time region is calculated, specifically as follows: T i TF represents the environmental adaptability assessment value for the i-th sub-time region. i TM represents the frequency drift rate under high and low temperature cycling in the i-th sub-time region. i TH represents the mechanical shock response curve for the i-th sub-time region. i Represents the humidity sensitivity coefficient for the i-th sub-time region, TB i Let n represent the frequency response of air pressure change in the i-th sub-time region, and n represent the number of sub-time regions.

5. The quartz crystal oscillator tram control method based on intelligent applications according to claim 1, characterized in that: The electrical characteristic data analysis model is used to analyze electrical characteristic data. The electrical characteristic data is imported into the model to calculate the electrical characteristic evaluation value for each sub-time region, specifically as follows: E i ES represents the electrical characteristic evaluation value for the i-th sub-time region. i ED represents the equivalent series resistance value of the i-th sub-time region. i ER represents the drive level dependence of the i-th sub-time region. i EF represents the resonant impedance phase angle of the i-th sub-time region. i denoted as the frequency aging rate of the i-th sub-time region, and n represents the number of sub-time regions.

6. The quartz crystal oscillator tram control method based on intelligent applications according to claim 1, characterized in that: The performance stability data analysis model is used to analyze performance stability data. By importing the performance stability data into the model, the performance stability evaluation value for each sub-time region is calculated, specifically as follows: S i ST represents the performance stability evaluation value for the i-th sub-time region. i SP represents the short-term frequency stability of the i-th sub-time region. i SH represents the phase noise of the i-th sub-time region. i SF represents the harmonic distortion of the i-th sub-time region. i represents the frequency-temperature compensation coefficient for the i-th sub-time region, and n represents the number of sub-time regions.

7. The quartz crystal oscillator tram control method based on intelligent applications according to claim 1, characterized in that: The comprehensive analysis model is specifically represented as follows: η represents the comprehensive optimization index of the target quartz crystal oscillator electric vehicle, F i T represents the oscillation characteristic evaluation value of the i-th sub-time region. i E represents the environmental adaptability assessment value for the i-th sub-time region. i S represents the electrical characteristic evaluation value for the i-th sub-time region. i λ represents the performance stability assessment value of the i-th sub-time region, and λ represents other influencing factors of the comprehensive anomaly index.

8. The quartz crystal oscillator tram control method based on intelligent applications according to claim 1, characterized in that: The standard value of the comprehensive anomaly index is marked as η0. When η0≥η, it means that there is no abnormality in the target quartz crystal oscillator tram, and the detection of the target quartz crystal oscillator tram is maintained. When η0<η, it means that the target quartz crystal oscillator tram is abnormal, and an early warning signal is sent to the user control terminal.

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