CN-121980902-A - Crystal oscillator aging prediction method, system, equipment and storage medium

CN121980902ACN 121980902 ACN121980902 ACN 121980902ACN-121980902-A

Abstract

The application provides a crystal oscillator aging prediction method, a system, equipment and a storage medium, wherein the method comprises the steps of obtaining an aging test data set and establishing a comprehensive aging model based on the aging test data set; the method comprises the steps of generating an initial joint model by combining an introduced improved temperature acceleration model with a comprehensive aging model, optimizing joint parameters of the initial joint model according to the aging test data set and a parameter optimization algorithm to generate joint optimization parameters, substituting the joint optimization parameters into the initial joint model to determine the joint model, substituting acquired aging data into the joint model, and predicting aging behaviors of a crystal oscillator under the current condition to obtain a long-term frequency deviation prediction result. According to the method, the accuracy of crystal oscillator aging prediction is remarkably improved.

Inventors

WANG WEIHUA
XIA QI
CUI WEI
ZHENG WENQIANG
DUAN YOUFENG

Assignees

北京无线电计量测试研究所

Dates

Publication Date: 20260505
Application Date: 20251208

Claims (10)

1. A method for predicting aging of a crystal oscillator, comprising: based on the acquired aging test data set, establishing a comprehensive aging model; combining the introduced improved temperature acceleration model with the comprehensive aging model to generate an initial combined model; Optimizing the joint parameters of the initial joint model according to the aging test data set and a parameter optimization algorithm to generate joint optimization parameters; substituting the joint optimization parameters into the initial joint model to determine a joint model; substituting the obtained aging data into a joint mode, and predicting to obtain a long-term frequency deviation prediction result.
2. A method of crystal oscillator aging prediction as recited in claim 1, further comprising: The frequency tolerance limit of the crystal oscillator is preset, and the long-term frequency deviation prediction result is combined, so that the time from the beginning of use of the crystal oscillator to the time when the frequency drift of the crystal oscillator exceeds the frequency tolerance limit is calculated.
3. A method of crystal oscillator aging prediction as recited in claim 1, further comprising: According to the long-term frequency deviation prediction result, combining at least one preset specific time interval, and calculating the average aging rate of the crystal oscillator in each interval; And determining the long-term stability of the crystal oscillator according to the average aging rate.
4. The method for crystal oscillator aging prediction according to claim 1, wherein the establishing a comprehensive aging model based on the acquired aging test data set comprises: and determining a comprehensive aging model according to the first aging mechanism parameter, the first time, the second aging mechanism parameter, the second time, the linear drift coefficient, the aging time, the initial frequency deviation and the random fluctuation term.
5. The method for predicting aging of a crystal oscillator according to claim 4, wherein the obtaining means of the initial frequency deviation comprises: and obtaining the initial temperature of each temperature group sample, establishing a functional relation between the initial frequency deviation and the initial temperature through linear fitting or polynomial fitting, and determining the initial frequency deviation.
6. The method of claim 1, wherein optimizing joint parameters of the initial joint model according to the aging test data set and a parameter optimization algorithm, the generating joint optimization parameters comprises: preliminary estimation is carried out on the joint parameters of the initial joint model by adopting a least square method, so as to obtain initial values of the parameters of the initial joint model; and adopting a simplex optimization algorithm to iteratively adjust the initial value until the numerical value of the constructed objective function is converged to a preset threshold range, and generating a joint optimization parameter.
7. The method for predicting aging of a crystal oscillator according to claim 1, wherein substituting the obtained aging data into a joint pattern, predicting to obtain a long-term frequency deviation prediction result comprises: Obtaining the normal use temperature of the crystal oscillator, substituting the normal use temperature into a combined model of the comprehensive aging model and the temperature acceleration model, and calculating the relative frequency deviation of the crystal oscillator at the normal use temperature within the preset aging time; according to the calculated relative frequency deviation corresponding to different aging time, generating a long-term aging prediction curve of the relative frequency deviation along with the aging time, wherein the prediction curve is the long-term frequency deviation prediction result.
8. A crystal oscillator aging prediction system, the system comprising: the first construction module is used for establishing a comprehensive aging model based on the acquired aging test data set; the second building module is used for generating an initial combined model by combining the introduced improved temperature acceleration model with the comprehensive aging model; The parameter calculation module is used for optimizing the joint parameters of the initial joint model according to the aging test data set and a parameter optimization algorithm to generate joint optimization parameters; the optimization module is used for substituting the joint optimization parameters into the initial joint model to determine a joint model; and the prediction module is used for substituting the acquired aging data into the joint mode and predicting to obtain a long-term frequency deviation prediction result.
9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the method of any of claims 1-7 when executing the computer program.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 7.

Description

Crystal oscillator aging prediction method, system, equipment and storage medium Technical Field The application relates to the field of crystal oscillators, in particular to a crystal oscillator aging prediction method, a crystal oscillator aging prediction system, crystal oscillator aging prediction equipment and a storage medium. Background The frequency stability of a quartz crystal oscillator, which is used as a key frequency control element in electronic equipment, directly affects the performance index of the whole system. Due to the physicochemical changes inside the crystal oscillator, the output frequency thereof may drift systematically with time, a phenomenon called aging. The frequency drift caused by aging is a key parameter for evaluating the long-term reliability of the crystal oscillator, and will directly affect the long-term working performance of a communication system, navigation equipment and precise measurement instruments. At present, research on crystal oscillator aging and an aging model for predicting the crystal oscillator aging are too simplified, and many prior art adopts a simple linear model or a single logarithmic model to describe the aging process, so that the complexity of an aging mechanism is not fully considered, or only the linear relation between aging and time logarithm is considered, and larger deviation can be generated in actual long-term prediction. Therefore, there is a strong need in the art for a crystal oscillator aging prediction and warranty assessment method that can accurately describe the multi-mechanism composite aging process, reliably correlate temperature acceleration effects, and facilitate engineering applications. Disclosure of Invention Aiming at the problem that the aging degree of the crystal oscillator is not accurate enough in actual application in the prior art, the application provides a method, a system, a device and a storage medium for predicting the aging degree of the crystal oscillator. An embodiment of a first aspect of the present application provides a crystal oscillator aging prediction method, including: based on the acquired aging test data set, establishing a comprehensive aging model; combining the introduced improved temperature acceleration model with the comprehensive aging model to generate an initial combined model; Optimizing the joint parameters of the initial joint model according to the aging test data set and a parameter optimization algorithm to generate joint optimization parameters; substituting the joint optimization parameters into the initial joint model to determine a joint model; substituting the obtained aging data into a joint mode, and predicting to obtain a long-term frequency deviation prediction result. In a possible embodiment, the method further comprises: The frequency tolerance limit of the crystal oscillator is preset, and the long-term frequency deviation prediction result is combined, so that the time from the beginning of use of the crystal oscillator to the time when the frequency drift of the crystal oscillator exceeds the frequency tolerance limit is calculated. In a possible embodiment, the method further comprises: According to the long-term frequency deviation prediction result, combining at least one preset specific time interval, and calculating the average aging rate of the crystal oscillator in each interval; And determining the long-term stability of the crystal oscillator according to the average aging rate. In a possible implementation manner, the building the comprehensive aging model based on the acquired aging test data set includes: and determining a comprehensive aging model according to the first aging mechanism parameter, the first time, the second aging mechanism parameter, the second time, the linear drift coefficient, the aging time, the initial frequency deviation and the random fluctuation term. In a possible implementation manner, the obtaining manner of the initial frequency deviation includes: and obtaining the initial temperature of each temperature group sample, establishing a functional relation between the initial frequency deviation and the initial temperature through linear fitting or polynomial fitting, and determining the initial frequency deviation. In a possible implementation manner, the optimizing the joint parameters of the initial joint model according to the aging test data set and a parameter optimization algorithm, and generating the joint optimization parameters includes: preliminary estimation is carried out on the joint parameters of the initial joint model by adopting a least square method, so as to obtain initial values of the parameters of the initial joint model; and adopting a simplex optimization algorithm to iteratively adjust the initial value until the numerical value of the constructed objective function is converged to a preset threshold range, and generating a joint optimization parameter. In a possible implementation manner, substitut