Nuclear reactor control rod driving mechanism life prediction method, device, equipment and medium

Abstract

The invention discloses a nuclear reactor control rod driving mechanism life prediction method, device and equipment and a medium, and the method comprises the steps: obtaining the full life cycle data of a target driving mechanism, and obtaining a plurality of intrinsic mode components according to the full life cycle data; determining an optimal intrinsic mode component according to the spectrum characteristic of the intrinsic mode component and the low-frequency spectrum characteristic of the vibration signal; performing feature extraction on the optimal intrinsic mode component to obtain a time domain feature and a frequency domain feature corresponding to the optimal intrinsic mode component; constructing a health index curve according to the time domain features and the frequency domain features corresponding to the plurality of optimal intrinsic mode components; and fitting the health index curve to construct a polynomial life prediction model which is used for predicting the life of the driving mechanism. The invention belongs to the field of control rod driving mechanisms. According to the invention, online life prediction of the driving mechanism can be realized.

Description

Technical Field

[0001] The present invention relates to the field of control rod drive mechanisms, and in particular to a method, device, equipment and medium for predicting the life of a control rod drive mechanism of a nuclear reactor. Background Art

[0002] The control rod drive (CRD) of a nuclear reactor is a servo mechanism within the reactor's control and safety systems. It is a crucial operating component and a key element influencing the reactor's normal operation, safety, and reliability. The CRD operates in a complex environment. As the only mechanical component in a nuclear reactor that undergoes relative motion, it directly controls the position of the neutron absorber within the core, requiring high reliability and a long service life. Failure can have serious consequences.

[0003] With the informatization of modern industry, the health assessment and life prediction of industrial equipment have attracted significant attention worldwide. Control rod drive (CRD) health assessment and life prediction facilitate precise control of nuclear reactors, improving the reliability and safety of CRDs in both military and civilian reactors. Predicting CRD failures in advance can prevent accidents. Therefore, online research on the remaining life prediction of CRDs in nuclear reactors has become a pressing task. Summary of the Invention

[0004] The present invention solves the technical problem of difficulty in online prediction of the remaining life of a nuclear reactor control rod drive mechanism in the prior art by providing a method, device, equipment and medium for predicting the life of a nuclear reactor control rod drive mechanism, and achieves the technical effect of online prediction of the remaining life of a nuclear reactor control rod drive mechanism.

[0005] In a first aspect, the present invention provides a method for predicting the life of a control rod drive mechanism of a nuclear reactor, the method comprising:

[0006] Acquire full life cycle data of the target drive mechanism, and obtain a plurality of intrinsic modal components based on the full life cycle data, wherein the full life cycle data includes a plurality of vibration signals of the target drive mechanism;

[0007] Determine the optimal intrinsic modal component based on the spectral characteristics of the intrinsic modal component and the low-frequency spectral characteristics of the vibration signal;

[0008] Perform feature extraction on the best intrinsic modal component to obtain the time domain features and frequency domain features corresponding to the best intrinsic modal component;

[0009] Construct a health index curve based on the time domain characteristics and frequency domain characteristics corresponding to several optimal intrinsic modal components;

[0010] The health index curve is fitted to construct a polynomial life prediction model, wherein the polynomial life prediction model is used to predict the life of the drive mechanism.

[0011] Furthermore, the method further comprises:

[0012] Obtaining real-time vibration signals of the driving mechanism to be predicted;

[0013] Determining an optimal intrinsic modal component of the real-time vibration signal of the drive mechanism to be predicted based on the real-time vibration signal of the drive mechanism to be predicted;

[0014] The optimal intrinsic modal component of the real-time vibration signal of the drive mechanism to be predicted is input into the polynomial life prediction model to obtain the life prediction result of the drive mechanism to be predicted.

[0015] Furthermore, several intrinsic modal components are obtained based on the full life cycle data, including:

[0016] Based on the CEEMDAN method, each vibration signal of the target drive mechanism is denoised to obtain multiple intrinsic modal components corresponding to the vibration signal.

[0017] Furthermore, the optimal intrinsic modal component is determined based on the spectral characteristics of the intrinsic modal component and the low-frequency spectral characteristics of the vibration signal, including:

[0018] For each vibration signal, perform Fourier transform on each intrinsic modal component in the vibration signal to obtain the spectral characteristics corresponding to each intrinsic modal component;

[0019] Performing Fourier transform on the vibration signal to obtain low-frequency spectrum characteristics corresponding to the vibration signal;

[0020] An optimal intrinsic modal component of the vibration signal is determined based on low-frequency spectrum characteristics corresponding to the vibration signal and spectrum characteristics of a plurality of intrinsic modal components of the vibration signal.

[0021] Furthermore, determining the optimal intrinsic modal component of the vibration signal based on the low-frequency spectrum characteristics corresponding to the vibration signal and the spectrum characteristics of several intrinsic modal components of the vibration signal includes:

[0022] The intrinsic modal component corresponding to the spectrum feature most similar to the low-frequency spectrum feature of the vibration signal is used as the optimal intrinsic modal component of the vibration signal.

[0023] Furthermore, the best intrinsic modal component is subjected to feature extraction to obtain the frequency domain features corresponding to the best intrinsic modal component, including:

[0024] Based on Fourier transform, the best intrinsic modal component is feature extracted to obtain the frequency domain features corresponding to the best intrinsic modal component.

[0025] Furthermore, obtaining a real-time vibration signal of the drive mechanism to be predicted includes:

[0026] Based on the high-temperature accelerometer, the real-time vibration signal of the drive mechanism to be predicted is obtained.

[0027] In a second aspect, the present invention provides a device for predicting the life of a control rod drive mechanism of a nuclear reactor, the device comprising:

[0028] an acquisition module, configured to acquire full life cycle data of a target drive mechanism and obtain a plurality of intrinsic modal components based on the full life cycle data, wherein the full life cycle data includes a plurality of vibration signals of the target drive mechanism;

[0029] The modal component module is used to determine the optimal intrinsic modal component based on the spectral characteristics of the intrinsic modal component and the low-frequency spectral characteristics of the vibration signal;

[0030] An extraction module is used to extract features of the best intrinsic modal component and obtain time domain features and frequency domain features corresponding to the best intrinsic modal component;

[0031] A curve construction module is used to construct a health index curve based on the time domain characteristics and frequency domain characteristics corresponding to several optimal intrinsic modal components;

[0032] The model building module is used to fit the health index curve to build a polynomial life prediction model, wherein the polynomial life prediction model is used to predict the life of the drive mechanism.

[0033] In a third aspect, the present invention provides an electronic device, comprising:

[0034] processor;

[0035] a memory for storing processor-executable instructions;

[0036] The processor is configured to execute to implement a method for predicting the life of a control rod drive mechanism of a nuclear reactor as provided in the first aspect.

[0037] In a fourth aspect, the present invention provides a non-temporary computer-readable storage medium, which, when the instructions in the storage medium are executed by a processor of an electronic device, enables the electronic device to execute a method for predicting the life of a nuclear reactor control rod drive mechanism as provided in the first aspect.

[0038] One or more technical solutions provided in the present invention have at least the following technical effects or advantages:

[0039] The proposed life prediction method for nuclear reactor control rod drive mechanisms uses CEEMDAN decomposition to extract intrinsic modal components. This method, combined with spectral characteristics, selects the optimal component for feature extraction. A health index curve is constructed and fitted to a polynomial model, enabling quantitative assessment of the drive mechanism's operating status and life prediction. This method enables online analysis based on real-time vibration signals, demonstrating excellent timeliness and promising engineering applications.

[0040] The CEEMDAN method employed in this paper exhibits strong noise immunity, effectively improving the accuracy of feature extraction and enhancing the reliability of lifespan prediction. Furthermore, the polynomial model's simple structure and efficient computation facilitate its deployment and implementation in practical systems, demonstrating its high practicality. The overall method has a clear workflow, adapts to monitoring requirements under complex operating conditions, and provides a strong guarantee for the safe operation of nuclear reactors. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0042] Figure 1 A schematic flow chart of a method for predicting the life of a control rod drive mechanism of a nuclear reactor provided by the present invention;

[0043] Figure 2 A schematic diagram of a process for determining the optimal intrinsic modal component provided by the present invention;

[0044] Figure 3 This is a structural schematic diagram of a life prediction device for a nuclear reactor control rod drive mechanism provided by the present invention. DETAILED DESCRIPTION

[0045] The embodiment of the present invention solves the technical problem of difficulty in online prediction of the remaining service life of a control rod drive mechanism of a nuclear reactor in the prior art by providing a method for predicting the service life of the control rod drive mechanism of a nuclear reactor.

[0046] The technical solution of the present invention is to solve the above technical problems, and the overall idea is as follows:

[0047] A method for predicting the life of a control rod drive mechanism of a nuclear reactor comprises: acquiring full life cycle data of a target drive mechanism, and obtaining a plurality of intrinsic modal components based on the full life cycle data, wherein the full life cycle data includes a plurality of vibration signals of the target drive mechanism; determining an optimal intrinsic modal component based on the spectral characteristics of the intrinsic modal component and the low-frequency spectral characteristics of the vibration signal; performing feature extraction on the optimal intrinsic modal component to obtain time domain features and frequency domain features corresponding to the optimal intrinsic modal component; constructing a health index curve based on the time domain features and frequency domain features corresponding to the plurality of optimal intrinsic modal components; and fitting the health index curve to construct a polynomial life prediction model, wherein the polynomial life prediction model is used to predict the life of the drive mechanism.

[0048] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0049] First, the term "and / or" as used herein simply describes a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A alone, A and B together, or B alone. Furthermore, the character " / " in this document generally indicates an "or" relationship between the associated objects.

[0050] The present invention provides Figure 1 A method for predicting the life of a control rod drive mechanism of a nuclear reactor is shown, comprising steps S11-S15:

[0051] In step S11 , full life cycle data of the target drive mechanism is acquired, and a plurality of intrinsic modal components are obtained based on the full life cycle data, wherein the full life cycle data includes a plurality of vibration signals of the target drive mechanism.

[0052] Several intrinsic modal components are derived from the full lifecycle data. This involves performing noise reduction processing on the vibration signals of the target drive mechanism using the CEEMDAN method to obtain multiple intrinsic modal components corresponding to these vibration signals. It is important to emphasize that the full lifecycle data includes vibration signals at several moments, each of which corresponds to several intrinsic modal components.

[0053] CEEMDAN (Complete Ensemble Empirical Mode Decomposition with Adaptive Noise) is a signal processing method primarily used for analyzing nonlinear and nonstationary signals. CEEMDAN is an evolution of EMD (Empirical Mode Decomposition) and EEMD (Ensemble Empirical Mode Decomposition). By adding adaptive noise to the original signal and repeating the decomposition process multiple times, CEEMDAN overcomes the mode aliasing problem inherent in EMD and improves the consistency and accuracy of the decomposition results.

[0054] When performing noise reduction on the vibration signal of a target drive mechanism, the CEEMDAN method can decompose the complex vibration signal into several intrinsic mode functions (IMFs). Each IMF component represents the oscillation mode of different frequency components in the original signal, and the oscillation mode reflects the intrinsic time scale characteristics of the signal.

[0055] Acquiring a real-time vibration signal of the drive mechanism to be predicted includes: acquiring the real-time vibration signal of the drive mechanism to be predicted based on a high-temperature accelerometer.

[0056] High-temperature accelerometers are typically used to measure vibration or acceleration. They are widely used in aerospace, automotive, energy, and other applications where vibration monitoring and analysis are required in high-temperature environments.

[0057] Step S12: determining the optimal intrinsic modal component according to the spectral characteristics of the intrinsic modal component and the low-frequency spectral characteristics of the vibration signal.

[0058] Figure 2 A flow chart for determining optimal intrinsic modal components is provided. Determining the optimal intrinsic modal components specifically includes: for each vibration signal, performing a Fourier transform on each intrinsic modal component in the vibration signal to obtain spectral characteristics corresponding to each intrinsic modal component; performing a Fourier transform on the vibration signal to obtain low-frequency spectral characteristics corresponding to the vibration signal; and determining the optimal intrinsic modal component of the vibration signal based on the low-frequency spectral characteristics corresponding to the vibration signal and the spectral characteristics of several intrinsic modal components of the vibration signal.

[0059] The Fourier transform is a mathematical tool that can convert a function in the time domain (or space domain) into a function in the frequency domain. Through the Fourier transform, a signal that changes with time can be converted into a frequency component.

[0060] Each intrinsic modal component in the vibration signal can be Fourier transformed to obtain the frequency spectrum characteristics corresponding to each intrinsic modal component; and the vibration signal can be Fourier transformed to obtain the corresponding low-frequency frequency spectrum characteristics.

[0061] Determining the optimal intrinsic modal component of the vibration signal based on the low-frequency spectrum characteristics corresponding to the vibration signal and the spectrum characteristics of multiple intrinsic modal components of the vibration signal includes: selecting the intrinsic modal component corresponding to the spectrum characteristics most similar to the low-frequency spectrum characteristics of the vibration signal as the optimal intrinsic modal component of the vibration signal.

[0062] A vibration signal corresponds to an optimal intrinsic modal component, and the frequency corresponding to the maximum value in the spectrum of the intrinsic modal component corresponding to the vibration signal is closest to (ie, most similar to) the frequency corresponding to the maximum value in the low-frequency spectrum of the vibration signal.

[0063] Step S13 , performing feature extraction on the best intrinsic modal component to obtain time domain features and frequency domain features corresponding to the best intrinsic modal component.

[0064] The method comprises: extracting features of the best intrinsic modal component based on Fourier transform, and obtaining frequency domain features corresponding to the best intrinsic modal component.

[0065] Step S14: constructing a health index curve based on the time domain characteristics and frequency domain characteristics corresponding to the optimal intrinsic modal components.

[0066] Time-domain features are extracted directly from the best intrinsic mode components. These features reflect the temporal variation of the signal. For the best intrinsic mode components, the calculated time-domain features include mean, standard deviation, peak, root mean square (RMS), and skewness or kurtosis.

[0067] Frequency domain features may include: spectral peak, frequency center of gravity, bandwidth, power spectral density (PSD), or harmonic ratio.

[0068] Based on weighted summation, principal component analysis (PCA) or machine learning models, the time domain features and frequency domain features corresponding to the optimal intrinsic modal components can be fused, and then a health indicator curve based on time sequence can be constructed.

[0069] Step S15 , fitting the health index curve to construct a polynomial life prediction model, wherein the polynomial life prediction model is used to predict the life of the driving mechanism.

[0070] The curve fitting method can be polynomial regression. The order of the polynomial (i.e., the highest power) can be adjusted according to the actual situation. Usually, by trying different orders and selecting the one with the best fitting effect, the coefficients of the polynomial can be determined using statistical methods such as the least squares method.

[0071] The method also includes: obtaining a real-time vibration signal of the drive mechanism to be predicted; determining an optimal intrinsic modal component of the real-time vibration signal of the drive mechanism to be predicted based on the real-time vibration signal of the drive mechanism to be predicted; and inputting the optimal intrinsic modal component of the real-time vibration signal of the drive mechanism to be predicted into a polynomial life prediction model to obtain a life prediction result of the drive mechanism to be predicted.

[0072] In summary, the present invention provides a method for predicting the life of a nuclear reactor control rod drive mechanism. The method comprises: obtaining full life cycle data of a target drive mechanism and obtaining several intrinsic modal components based on the full life cycle data, wherein the full life cycle data includes several vibration signals of the target drive mechanism; determining the optimal intrinsic modal component based on the spectral characteristics of the intrinsic modal component and the low-frequency spectral characteristics of the vibration signal; performing feature extraction on the optimal intrinsic modal component to obtain time domain and frequency domain features corresponding to the optimal intrinsic modal component; constructing a health index curve based on the time domain and frequency domain features corresponding to the optimal intrinsic modal components; and fitting the health index curve to construct a polynomial life prediction model, wherein the polynomial life prediction model is used to predict the life of the drive mechanism. The method for predicting the life of a nuclear reactor control rod drive mechanism of the present invention obtains intrinsic modal components through CEEMDAN decomposition, selects the optimal component based on the spectral characteristics for feature extraction, constructs a health index curve, and fits it to a polynomial model, thereby achieving quantitative assessment of the drive mechanism's operating status and life prediction. The method can perform online analysis based on real-time collected vibration signals, and has good timeliness and engineering application prospects. The CEEMDAN method employed exhibits strong noise immunity, effectively improving the accuracy of feature extraction and enhancing the reliability of lifetime prediction. Furthermore, the polynomial model's simple structure and efficient computation facilitate its deployment and implementation in practical systems, making it highly practical. The overall method has a clear workflow and adapts to monitoring requirements under complex operating conditions, providing a strong guarantee for the safe operation of nuclear reactors.

[0073] Based on the same inventive concept, the present invention provides Figure 3 A device for predicting the life of a control rod drive mechanism of a nuclear reactor is shown, the device comprising:

[0074] an acquisition module 31 for acquiring full life cycle data of a target drive mechanism and obtaining a plurality of intrinsic modal components based on the full life cycle data, wherein the full life cycle data includes a plurality of vibration signals of the target drive mechanism;

[0075] The modal component module 32 is used to determine the optimal intrinsic modal component based on the spectral characteristics of the intrinsic modal component and the low-frequency spectral characteristics of the vibration signal;

[0076] An extraction module 33 is used to extract features of the best intrinsic modal component to obtain time domain features and frequency domain features corresponding to the best intrinsic modal component;

[0077] A curve construction module 34 is used to construct a health index curve based on the time domain characteristics and frequency domain characteristics corresponding to a number of optimal intrinsic modal components;

[0078] The model building module 35 is used to fit the health index curve to build a polynomial life prediction model, wherein the polynomial life prediction model is used to predict the life of the driving mechanism.

[0079] Based on the same inventive concept, the present invention further provides an electronic device, comprising:

[0080] processor;

[0081] a memory for storing processor-executable instructions;

[0082] The processor is configured to execute to implement a method for predicting the life of a control rod drive mechanism of a nuclear reactor as provided above.

[0083] Based on the same inventive concept, the present invention also provides a non-temporary computer-readable storage medium. When the instructions in the storage medium are executed by the processor of an electronic device, the electronic device can execute a method for predicting the life of a nuclear reactor control rod drive mechanism as provided above.

[0084] Since the electronic device described in this embodiment is an electronic device used to implement the information processing method in the embodiment of the present invention, based on the information processing method described in the embodiment of the present invention, those skilled in the art will be able to understand the specific implementation of the electronic device of this embodiment and its various variations. Therefore, how the electronic device implements the method in the embodiment of the present invention will not be described in detail here. As long as the electronic device used by those skilled in the art to implement the information processing method in the embodiment of the present invention falls within the scope of protection of the present invention.

[0085] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0086] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0087] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0088] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0089] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0090] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A method for predicting the life of a control rod drive mechanism of a nuclear reactor, characterized in that: The method comprises: Acquiring full life cycle data of a target drive mechanism, and obtaining a plurality of intrinsic modal components based on the full life cycle data, wherein the full life cycle data includes a plurality of vibration signals of the target drive mechanism; Determine the optimal intrinsic modal component based on the spectral characteristics of the intrinsic modal component and the low-frequency spectral characteristics of the vibration signal; Performing feature extraction on the optimal intrinsic modal component to obtain time domain features and frequency domain features corresponding to the optimal intrinsic modal component; Construct a health index curve based on the time domain characteristics and frequency domain characteristics corresponding to several optimal intrinsic modal components; The health index curve is fitted to construct a polynomial life prediction model, wherein the polynomial life prediction model is used to predict the life of the driving mechanism.

2. A method for predicting the life of a nuclear reactor control rod drive mechanism according to claim 1, characterized in that: The method also includes: Obtaining real-time vibration signals of the driving mechanism to be predicted; Determining an optimal intrinsic modal component of the real-time vibration signal of the drive mechanism to be predicted based on the real-time vibration signal of the drive mechanism to be predicted; The optimal intrinsic modal component of the real-time vibration signal of the drive mechanism to be predicted is input into the polynomial life prediction model to obtain a life prediction result of the drive mechanism to be predicted.

3. The method for predicting the life of a control rod drive mechanism of a nuclear reactor according to claim 1, wherein: Several intrinsic modal components are obtained based on the full life cycle data, including: Based on the CEEMDAN method, each vibration signal of the target drive mechanism is denoised to obtain multiple intrinsic modal components corresponding to the vibration signal.

4. A method for predicting the life of a control rod drive mechanism of a nuclear reactor according to claim 3, characterized in that: According to the spectrum characteristics of the intrinsic modal components and the low-frequency spectrum characteristics of the vibration signal, the optimal intrinsic modal components are determined, including: For each vibration signal, perform Fourier transform on each intrinsic modal component in the vibration signal to obtain the spectral characteristics corresponding to each intrinsic modal component; Performing Fourier transform on the vibration signal to obtain low-frequency spectrum characteristics corresponding to the vibration signal; An optimal intrinsic modal component of the vibration signal is determined based on low-frequency spectrum characteristics corresponding to the vibration signal and spectrum characteristics of a plurality of intrinsic modal components of the vibration signal.

5. A method for predicting the life of a control rod drive mechanism of a nuclear reactor according to claim 4, characterized in that: Determining the optimal intrinsic modal component of the vibration signal based on low-frequency spectrum characteristics corresponding to the vibration signal and spectrum characteristics of several intrinsic modal components of the vibration signal includes: The intrinsic modal component corresponding to the spectrum feature most similar to the low-frequency spectrum feature of the vibration signal is used as the optimal intrinsic modal component of the vibration signal.

6. The method for predicting the life of a control rod drive mechanism of a nuclear reactor according to claim 1, wherein: Performing feature extraction on the optimal intrinsic modal component to obtain frequency domain features corresponding to the optimal intrinsic modal component includes: Based on Fourier transform, feature extraction is performed on the optimal intrinsic modal component to obtain frequency domain features corresponding to the optimal intrinsic modal component.

7. A method for predicting the life of a control rod drive mechanism of a nuclear reactor according to claim 2, characterized in that: Obtain the real-time vibration signal of the drive mechanism to be predicted, including: Based on the high-temperature accelerometer, a real-time vibration signal of the drive mechanism to be predicted is obtained.

8. A life prediction device for a control rod drive mechanism of a nuclear reactor, characterized in that: The device comprises: an acquisition module, configured to acquire full life cycle data of a target drive mechanism and obtain a plurality of intrinsic modal components based on the full life cycle data, wherein the full life cycle data includes a plurality of vibration signals of the target drive mechanism; The modal component module is used to determine the optimal intrinsic modal component based on the spectral characteristics of the intrinsic modal component and the low-frequency spectral characteristics of the vibration signal; An extraction module, configured to perform feature extraction on the optimal intrinsic modal component to obtain time domain features and frequency domain features corresponding to the optimal intrinsic modal component; A curve construction module is used to construct a health index curve based on the time domain characteristics and frequency domain characteristics corresponding to several optimal intrinsic modal components; The model building module is used to fit the health index curve to build a polynomial life prediction model, wherein the polynomial life prediction model is used to predict the life of the driving mechanism.

9. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute and implement a method for predicting the life of a control rod drive mechanism of a nuclear reactor according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to implement a method for predicting the life of a control rod drive mechanism of a nuclear reactor according to any one of claims 1 to 7.

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