KR-20260067567-A - SIGNAL PROCESSING METHOD AND SYSTEM CAPABLE OF DETERMINING ABNORMAL OPERATION STATUS OF SENSORS FOR MONITORING THE STATUS OF A NUCLEAR POWER PLANT SYSTEM

KR20260067567AKR 20260067567 AKR20260067567 AKR 20260067567AKR-20260067567-A

Abstract

The present invention provides a signal processing method comprising receiving vibration signals from each of a plurality of sensors provided in a nuclear power generation system, analyzing the correlation between the plurality of vibration signals, extracting information indicating a relationship regarding phase from the correlation based on the analysis result, deriving a phase-based correlation according to the unit time of receiving the vibration signals using the extracted information, and determining an abnormal operating state for at least one of the plurality of sensors based on the pattern of the phase-based correlation.

Inventors

윤두병
이정한
장대식

Assignees

한국원자력연구원

Dates

Publication Date: 20260513
Application Date: 20241106

Claims (15)

A step of receiving vibration signals from each of a plurality of sensors equipped in a nuclear power generation system; A step of analyzing the correlation between multiple vibration signals; A step of extracting information representing a relationship regarding phase from the correlation based on the analysis result above, and using the extracted information to derive a phase-based correlation according to the unit time of receiving the vibration signal; and A signal processing method comprising the step of determining an abnormal operating state for at least one of the plurality of sensors based on the pattern of the phase-based correlation above.
In claim 1, the step of receiving the vibration signal is, A signal processing method for receiving vibration signals observed during a predetermined time interval from each of the plurality of sensors at every predetermined time period.
In claim 1, the step of analyzing the correlation is, A signal processing method for analyzing the correlation according to the frequency components of multiple vibration signals observed in a time series in the same time period.
In claim 3, the step of analyzing the correlation above is, A step of performing a Fourier transform on each of the plurality of vibration signals to generate a plurality of frequency components corresponding to each of the plurality of vibration signals; and A signal processing method comprising the step of calculating the mutual spectrum between the plurality of frequency components and verifying the correlation between the plurality of vibration signals.
In claim 4, the step of confirming the above correlation is, Select any two vibration signals among the plurality of vibration signals above, and calculate the mutual spectrum for the two selected vibration signals, A signal processing method for calculating the mutual spectrum for all possible combinations of vibration signal pairs based on the plurality of vibration signals.
In claim 1, the step of deriving the phase-based correlation is, A step of normalizing the above correlation corresponding to a predetermined normalization range; and A signal processing method comprising the step of extracting a phase value, which is information representing the relationship to the phase in the normalized correlation above.
In claim 6, the step of normalizing the correlation is, Based on the correlation analyzed at a first point in time based on a predetermined time period, the correlation analyzed according to the time period after the first point in time is normalized, A signal processing method that performs normalization on multiple correlations based on the number of iterations of the time period corresponding to a predetermined normalization range.
In claim 6, the step of deriving the phase-based correlation is, A signal processing method further comprising the step of converting the phase value extracted from the normalized correlation into a time series to derive the phase-based correlation according to the unit time.
In claim 8, the step of deriving a phase-based correlation according to the unit time is, A signal processing method for deriving a phase-based correlation over unit time by performing a Fourier transform on the phase value extracted from the normalized correlation.
In claim 1, the step of determining the abnormal operating state is, A step of confirming the phase-based correlation pattern derived at predetermined time intervals so as to receive a plurality of vibration signals from the plurality of sensors; and A signal processing method comprising the step of determining the abnormal operating state of at least one of the plurality of sensors based on the above verification result.
In claim 1, the step of determining the abnormal operating state is, A step of generating a graph representing a phase-based correlation pattern according to the above unit time; and A signal processing method comprising the step of inputting the generated graph into a pre-trained learning model to determine whether there is an abnormal operating state for at least one of the plurality of sensors.
In claim 11, the learning model is, A signal processing method that is learned to output the abnormal operating state of an image of a specific graph when the image of the graph is input, by utilizing the graph representing a phase-based correlation pattern according to the above unit time and the abnormal operating state of a plurality of sensors corresponding to the graph.
In claim 1, the step of determining the abnormal operating state is, A step of calculating the change amount of a plurality of the above-mentioned phase-based correlations derived according to a predetermined normalization range; and A signal processing method comprising the step of determining that at least one of the plurality of sensors is in an abnormal operating state when the calculated change amount deviates from a predetermined threshold range.
An input unit that receives vibration signals from each of a plurality of sensors provided in a nuclear power generation system; and It includes a control unit that determines an abnormal operating state for at least one of the plurality of sensors based on the vibration signal, and The above control unit is, A signal processing system that analyzes the correlation between multiple vibration signals, extracts information indicating a relationship regarding phase from the correlation based on the analysis result, derives a phase-based correlation based on the unit time of receiving the vibration signal using the extracted information, and determines an abnormal operating state for at least one of the multiple sensors based on the pattern of the phase-based correlation.
A program that is executed by one or more processes in an electronic device and stored on a computer-readable recording medium, The above program is, A step of receiving vibration signals from each of a plurality of sensors equipped in a nuclear power generation system; A step of analyzing the correlation between multiple vibration signals; A step of extracting information representing a relationship regarding phase from the correlation based on the analysis result above, and using the extracted information to derive a phase-based correlation according to the unit time of receiving the vibration signal; and A program stored on a computer-readable recording medium characterized by including instructions for performing a step of determining an abnormal operating state for at least one of the plurality of sensors based on the pattern of the phase-based correlation above.

Description

Signal processing method and system capable of determining abnormal operation status of sensors for monitoring the status of a nuclear power plant system The present invention relates to a signal processing method and system capable of determining an abnormal operating state of a sensor for monitoring the condition of a nuclear power generation system. Nuclear power plants play a major role in meeting the energy demands of modern society. However, because nuclear power plants operate in high-temperature and high-pressure environments and pose a risk of radiation leakage if abnormalities occur during the operation of nuclear fuel, research to ensure the safety of nuclear power plants is continuously underway. In this regard, conventional methods utilize installing multiple vibration sensors in nuclear power generation systems to monitor shock phenomena or abnormal vibration phenomena occurring in the nuclear power generation system. Therefore, if the vibration sensors installed in the nuclear power generation system do not operate normally, it becomes impossible to detect structural abnormalities in the nuclear power generation system, so periodic preventive maintenance is required. As an example of such preventive maintenance, a test is conducted in which artificial shock vibrations are generated on the surface of the reactor system using a steel ball while the nuclear power generation system is shut down, and the waveform of the vibration signal observed by the vibration sensors due to the shock vibrations is observed normally. FIG. 1 illustrates a signal processing system according to the present invention. FIG. 2 is a flowchart illustrating a signal processing method according to the present invention. FIG. 3 is a flowchart illustrating an embodiment of analyzing the correlation between multiple vibration signals. FIG. 4 illustrates an embodiment for calculating the mutual spectrum between multiple vibration signals. FIG. 5 is a flowchart illustrating an example of deriving a phase-based correlation. Figure 6 is a flowchart illustrating an example of normalizing correlations. FIGS. 7 and FIGS. 8 illustrate an example of normalizing correlations according to a normalization range. FIG. 9 is a flowchart illustrating an embodiment for determining an abnormal operating state of at least one of a plurality of sensors. FIG. 10 illustrates an example of determining an abnormal operating state using a learning model. FIG. 11 illustrates a graph showing an example of a phase-based correlation pattern according to the operating state of a plurality of sensors. Hereinafter, embodiments disclosed in this specification will be described in detail with reference to the attached drawings. Identical or similar components are assigned the same reference number regardless of the drawing symbols, and redundant descriptions thereof will be omitted. The suffixes "module" and "part" used for components in the following description are assigned or used interchangeably solely for the ease of drafting the specification and do not have distinct meanings or roles in themselves. Furthermore, in describing the embodiments disclosed in this specification, if it is determined that a detailed description of related prior art could obscure the essence of the embodiments disclosed in this specification, such detailed description will be omitted. Additionally, the attached drawings are intended only to facilitate understanding of the embodiments disclosed in this specification; the technical concept disclosed in this specification is not limited by the attached drawings, and it should be understood that they include all modifications, equivalents, and substitutions that fall within the spirit and technical scope of the present invention. Terms including ordinal numbers, such as first, second, etc., may be used to describe various components, but said components are not limited by said terms. These terms are used solely for the purpose of distinguishing one component from another. When it is stated that one component is "connected" or "connected" to another component, it should be understood that while it may be directly connected or connected to that other component, there may also be other components in between. On the other hand, when it is stated that one component is "directly connected" or "directly connected" to another component, it should be understood that there are no other components in between. A singular expression includes a plural expression unless the context clearly indicates otherwise. In this application, terms such as “comprising” or “having” are intended to specify the existence of the features, numbers, steps, actions, components, parts, or combinations thereof described in the specification, and should be understood as not precluding the existence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof. FIG. 1 illustrates a signal processing system according to