Non-stationary vibration signal time-frequency analysis method and system for RSW pump of CANDU6 nuclear power station

Abstract

The invention belongs to the technical field of RSW pumps of CANDU6 nuclear power stations, aims to solve the problem that modal aliasing and false components exist in EMD decomposition in traditional HHT, and discloses a time-frequency analysis method and system for non-stationary vibration signals of an RSW pump of a CANDU6 nuclear power station, and the method comprises the steps: obtaining a rotor vibration signal, carrying out VMD decomposition on the rotor vibration signal, obtaining K modal components, and carrying out VMD decomposition on the K modal components; performing HT transformation on the K modal components, obtaining a Hilbert spectrum of an original signal, finally obtaining the original signal, and performing diagnosis on a rotor fault according to the change of a characteristic frequency in the Hilbert spectrum; the system comprises a vibration signal acquisition module, a signal decomposition and center frequency evaluation module, a modal component and center frequency solving module, a constraint problem conversion module, a modal component calculation module, a Hilbert spectrum acquisition module, an analysis signal construction module and an original signal restoration module. According to the method, the VMD method with excellent decomposition performance is combined with the HT, and the fault feature recognition capability of a traditional HHT method in processing rotor non-stationary vibration signals is optimized.

Description

Technical Field

[0001] The present application belongs to the technical field of RSW pumps of CANDU6 nuclear power plants, and in particular, relates to a time-frequency analysis method and system for non-stationary vibration signals of RSW pumps of CANDU6 nuclear power plants. Background Art

[0002] The important seawater cooling water pump (RSW pump) in the CANDU6 nuclear power plant is a large rotating machine driven by an electric motor. The function of the RSW pump is to pump seawater and cool the recirculating cooling water through the RCW heat exchanger, providing cooling for most of the equipment in the nuclear power plant. It is an important heat sink for the unit. The operating status of the RSW pump directly affects the safety of the nuclear power plant.

[0003] Due to the importance of RSW pumps, monitoring and evaluation of their health status is particularly important. At present, the sensors installed on RSW pumps in CANDU6 nuclear power plants include temperature probes, pressure probes, and low-frequency vibration signal acquisition probes. The acquisition signals of these probes cannot fully reflect the operating conditions of the pumps and motors, nor can they give early warnings. For example, there was an incident in which an operator found that the noise of the bearing at the drive end of the RSW pump increased abnormally during an inspection. After disassembly and inspection, it was found that a large area of ​​metal layer had fallen off and obvious scratches appeared on the inner ring of the bearing, and visible wear marks were found at the contact position between the inner ring of the bearing and the large end of the tapered roller.

[0004] In view of the above situation, the traditional monitoring based on time domain signals cannot meet the needs of large rotating machinery parameter monitoring in nuclear power plants. Traditional frequency domain analysis methods, such as fast Fourier transform (FFT) and spectrum analysis, can reveal the spectral characteristics of signals, but they assume that the signals are stationary within the entire analysis window, which limits their ability to process non-stationary signals, especially for those frequency components that vary with time.

[0005] Existing time-frequency analysis techniques include short-time Fourier transform (STFT), wavelet transform (WT) and Hilbert-Huang transform (HHT). Because they can provide spectral information of signals at different time points, they have become powerful tools for studying rotor fault diagnosis.

[0006] STFT realizes local analysis of signals by introducing the concept of window, but the size and shape of the window cannot be adjusted according to time and frequency, so STFT can only be applied in the analysis of stationary signals and slowly varying non-stationary signals. Although the window shape of WT can be adaptively changed according to the local characteristics of the signal, it cannot obtain high time resolution and frequency resolution at the same time. HHT is not subject to this limitation and can adaptively decompose the signal according to its local characteristics, which is a more effective time-frequency localization analysis method.

[0007] HHT consists of two parts: empirical mode decomposition (EMD) and Hilbert transform (HT). EMD first adaptively decomposes the signal into a series of intrinsic mode functions (IMFs), and then performs HT analysis on each IMF to calculate the instantaneous frequency and amplitude of each IMF, and finally obtains the Hilbert spectrum of the original signal. However, problems such as modal aliasing and false components in EMD decomposition often result in unsatisfactory HHT analysis results.

[0008] Variational mode decomposition (VMD) is a new signal decomposition algorithm that performs significantly better than EMD in speech detection, speech separation and noise robustness, and can effectively suppress mode aliasing in the signal decomposition process. Summary of the invention

[0009] The main purpose of this application is to provide a time-frequency analysis method and system for the non-stationary vibration signal of the RSW pump of a CANDU6 nuclear power plant, to solve the problems of modal aliasing and false components in the EMD decomposition in the traditional HHT, to combine the VMD method with superior decomposition performance with HT, and to propose a new time-frequency analysis strategy of VMD-HT, aiming to optimize the fault feature recognition capability of the traditional HHT method in processing the non-stationary vibration signal of the rotor.

[0010] Another object of the present application is to provide a method and system for time-frequency analysis of non-stationary vibration signals of the RSW pump of a CANDU6 nuclear power plant, so as to solve the problem that the monitoring signals in the existing RSW pump monitoring methods are incomplete and the health status of the RSW pump cannot be fully evaluated.

[0011] In order to achieve the above objectives, this application provides the following technical solutions: A time-frequency analysis method for non-stationary vibration signals of a RSW pump of a CANDU6 nuclear power plant, comprising: Step 1: Set several measuring points on the RSW pump to obtain rotor vibration signals; Step 2, decomposing the collected non-stationary vibration signal into a series of modal components with limited bandwidth, and online evaluating the center frequency of each component; Step 3, obtain K modal components and center frequencies of VMD by solving the constrained variational problem; Step 4: Use the augmented Lagrangian method to transform the constrained variational problem into an unconstrained optimization problem; Step 5: Calculate and obtain K modal components with independent center frequencies and finite bandwidths; Step 6: Use HT variation to obtain the instantaneous frequency of each modal component and obtain the Hilbert spectrum of the original signal; Step 7: construct the analytical signal of the modal component; Step 8: Obtain the instantaneous angular frequency of the signal through the instantaneous phase, calculate the instantaneous frequency, and obtain the original signal.

[0012] In step 1, 7 measuring points are arranged on the RSW pump, the first measuring point is arranged at the radial 90° position of the non-driving end of the motor, the second measuring point is arranged at the radial 0° position of the non-driving end of the motor, the third measuring point is arranged at the axial position of the non-driving end of the motor, the fourth measuring point is arranged at the radial 90° position of the driving end of the motor, the fifth measuring point is arranged at the radial 0° position of the driving end of the motor, the sixth measuring point is arranged at the radial 90° position of the intermediate bearing, and the seventh measuring point is arranged at the radial 0° position of the intermediate bearing.

[0013] In step 3, the constrained variational problem is solved as follows:

[0014] In the formula, is the partial derivative operation with respect to time t, δ(t) is the Dirac delta function, is the square of the L2 norm, and f(t) is the original signal.

[0015] The conversion formula in step 4 is:

[0016] Where α is the quadratic penalty factor of the augmented Lagrangian, and λ(t) is the Lagrangian multiplier; The classical alternating direction multiplier method is used to solve μ k (t),ω k and λ(t) are iteratively updated and the saddle point of the augmented Lagrangian is searched, μ k (t) The iterative process in the Fourier domain is:

[0017] ω k The iterative process in the Fourier domain is:

[0018] In the formula, and They are μ k Fourier transform of f(t) and f(t); The Lagrange multiplier λ(t) is updated as follows:

[0019] In the formula, is the Fourier transform of λ(t), and τ is the iteration step size.

[0020] Furthermore, the iteration process ends after the termination condition in the following formula is satisfied, and K modal components with independent center frequencies and limited bandwidths are obtained, as follows:

[0021] Where ε is the convergence error.

[0022] In step 6, the modal component μ k (t) Perform HT transformation as follows:

[0023] After the signal is transformed by HT, the amplitude of each frequency component will remain unchanged, and the phase will shift by 90 degrees.

[0024] In step 7, the constructed modal component μ k The analytical signal of (t) is as follows:

[0025] In the formula, z k (t) is μ k (t), j is the imaginary number symbol, a k (t) and θ k (t) are the instantaneous amplitude and instantaneous phase of the analytical signal respectively.

[0026] In step 8, the instantaneous angular frequency ω of the signal is obtained through the instantaneous phase k (t), as follows:

[0027] Calculate the instantaneous frequency ν k (t), as follows:

[0028] Then the original signal f(t) is expressed as:

[0029] Where Re represents the real part of the analytical signal.

[0030] On the other hand, the present application also provides a non-stationary vibration signal time-frequency analysis system for a CANDU6 nuclear power plant RSW pump, comprising: Vibration signal acquisition module, used to collect non-stationary vibration signals of RSW pumps in real time; Signal decomposition and center frequency evaluation module, used to decompose non-stationary vibration signals into a series of modal components with limited bandwidth and evaluate the center frequency of each component online; The modal component and center frequency solving module is used to obtain K modal components and center frequencies of VMD by solving the constrained variational problem; The constraint problem conversion module is used to convert the constraint problem into an unconstrained optimization problem; A modal component calculation module is used to calculate and obtain K modal components with independent center frequencies and limited bandwidths; The Hilbert spectrum acquisition module is used to obtain the instantaneous frequency of each modal component by using HT variation to obtain the Hilbert spectrum of the original signal; An analytical signal construction module, used to construct analytical signals of modal components; The original signal restoration module is used to obtain the instantaneous angular frequency of the signal through the instantaneous phase and calculate the instantaneous frequency.

[0031] Furthermore, the vibration signal acquisition module includes: Vibration sensor, used to be installed on the RSW pump to collect non-stationary vibration signals; A data acquisition box, used for receiving and storing signals collected by the vibration sensor; The middle junction box is used to connect the vibration sensor and the data acquisition box.

[0032] Compared with the prior art, the non-stationary vibration signal time-frequency analysis method and system of the RSW pump of the CANDU6 nuclear power plant provided by the present application has the following beneficial effects: This application combines the VMD method with superior decomposition performance with HT, and proposes a new time-frequency analysis strategy of VMD-HT to optimize the fault feature recognition ability of the traditional HHT method in processing the non-stationary vibration signals of the rotor.

[0033] The present application combines VMD and HT to identify the fault characteristics of the non-stationary vibration signal of the rotor under different fault modes, thereby improving the performance of the traditional HHT method.

[0034] This application overcomes the shortcomings of the original vibration signal monitoring system, which has a very low acquisition frequency and lacks the basis for time-frequency analysis, by adding a high-frequency vibration monitoring system for the RSW pump. This makes up for the fact that the current monitoring signals are incomplete and cannot fully evaluate the health status of the RSW pump. Through the new VMD-HT time-frequency analysis method, fault warnings are automatically given for high-frequency vibration parameters, and specific fault modes are analyzed based on the fault characteristics of the non-stationary vibration signals of rotating machinery.

[0035] This application adds a high-frequency vibration sensor to the RSW pump to collect high-frequency vibration signals to support time-frequency analysis, rather than using conventional low-frequency vibration sensors, which have too low a collection frequency to support time-frequency analysis. This application uses high-frequency vibration sensors and uses time-frequency analysis technology to identify and analyze fault information hidden in vibration signals. This application uses time-frequency analysis technology to simultaneously carry out signal analysis in both time and frequency dimensions, thereby effectively extracting and analyzing transient components in non-stationary signals and revealing how fault characteristic frequencies change over time. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solution of the present application, the following is a brief introduction to the drawings required for the technical description.

[0037] Figure 1 A flow chart of a method for time-frequency analysis of non-stationary vibration signals of a RSW pump of a CANDU6 nuclear power plant provided in an embodiment of the present application; Figure 2 A schematic diagram of the distribution of newly added measuring points for the RSW pump provided in the embodiment of the present application; Figure 3 A flow chart of fault feature identification of rotor non-stationary vibration signal based on VMD-HT provided in an embodiment of the present application; Figure 4 A schematic diagram of a non-stationary signal under a rotor imbalance fault provided in an embodiment of the present application; Figure 5 A schematic diagram of a time-frequency analysis result of a non-stationary signal under a rotor imbalance fault obtained by using the VMD-HT method provided in an embodiment of the present application; Figure 6 A schematic diagram of a time-frequency analysis result of a non-stationary signal under a rotor imbalance fault obtained by using the HHT method provided in an embodiment of the present application; Figure 7 A schematic diagram of a non-stationary signal under a rotor misalignment fault provided in an embodiment of the present application; Figure 8 A schematic diagram of a time-frequency analysis result of a non-stationary signal under a rotor misalignment fault obtained by using the VMD-HT method provided in an embodiment of the present application; Fig. 9 A schematic diagram of a time-frequency analysis result of a non-stationary signal under a rotor misalignment fault obtained by using the HHT method provided in an embodiment of the present application; Fig.10 A schematic diagram of the structure of the time-frequency analysis system for the non-stationary vibration signal of the RSW pump of the CANDU6 nuclear power plant provided in an embodiment of the present application. DETAILED DESCRIPTION

[0038] The following is further explained in detail through specific implementation methods.

[0039] like Figure 1 As shown, the embodiment of the present application provides a time-frequency analysis method for a non-stationary vibration signal of an RSW pump of a CANDU6 nuclear power plant, comprising the following steps: Step 1: Add vibration sensors, data acquisition boxes, and intermediate junction boxes to the newly added RSW pump high-frequency vibration monitoring system of the CANDU6 nuclear power plant, and add measurement points to the RSW pump; obtain rotor vibration signals through step 1; Step 2: The non-stationary vibration signal collected by the newly added RSW pump high-frequency vibration monitoring system is synchronously decomposed into a series of modal components with limited bandwidth using the VMD method, and the center frequency of each component is evaluated online; the RSW pump high-frequency vibration monitoring system includes a vibration sensor, a data acquisition box, an intermediate junction box, cables, optical fibers, etc., and the data acquisition box also includes an edge gateway, a communication module, a power module, a photoelectric conversion module, etc.; Step 3: Obtain the K modal components μ of VMD by solving the constrained variational problem k (t)(k=1,2,3,…,K)and center frequency ω k ; Step 4: Use the augmented Lagrangian method to transform the above constrained variational problem into an unconstrained optimization problem; Step 5: Calculate and obtain K modal components μ with independent center frequencies and limited bandwidths k (t); Step 6: Use HT variation to obtain the instantaneous frequency of each modal component and obtain the Hilbert spectrum (time-frequency spectrum) of the original signal; Step 7: Construct modal component μ k (t) analytical signal; Step 8: Obtain the instantaneous angular frequency ω of the signal through the instantaneous phase k (t), the instantaneous frequency ν is calculated k (t), and get the original signal f(t).

[0040] In the embodiment of the present application, 7 new measuring points are added to the RSW pump, and each measuring point is arranged with a corresponding vibration sensor, and a total of 7 vibration sensors are arranged. 2 are arranged at the radial position of the non-driving end of the motor (installed at a horizontal angle of 90 degrees), 1 is arranged at the axial position of the non-driving end of the motor, 2 are arranged at the radial position of the driving end of the motor (installed at a horizontal angle of 90 degrees), and 2 are arranged at the radial position of the intermediate bearing (horizontally at an angle of 90 degrees). At the same measuring point, the monitoring system displays two signals, namely acceleration signal and speed signal.

[0041] Drive end bearing (radial position of the motor drive end): The drive end of the motor is the key part for transmitting power. The vibration signal is strong and can reflect the motor's operating status. Installing it at the drive end bearing can effectively monitor the vibration of the motor.

[0042] At the non-drive end bearing (radial position of the motor non-drive end, axial position of the motor non-drive end): Although the vibration intensity of the non-drive end is relatively small, in some cases, the vibration of the non-drive end can also provide important information, especially when the vibration signal of the drive end is disturbed.

[0043] The position of the intermediate bearing of the water pump (radial position of the intermediate bearing): The bearing of the water pump is a key supporting component, and the vibration signal can reflect the operating status of the bearing and the overall vibration of the water pump.

[0044] Installation in the axial position (axial position of the non-drive end of the motor) and installation of two probes in the same horizontal position (two radial positions of the non-drive end of the motor, two radial positions of the drive end of the motor, and two radial positions of the intermediate bearing): By installing the probes in different directions (such as vertical, horizontal, and axial), the vibration of the equipment can be fully monitored and the accuracy of fault diagnosis can be improved. In addition, by installing the probes in the above-mentioned key components, vibration signals can be directly obtained, reducing the attenuation of the signals during transmission.

[0045] In the embodiment of the present application, the RSW pump speed is approximately between 183 rpm and 5000 rpm, and the vibration sensor frequency range of 0.4-12 KHz can fully meet the requirements for equipment vibration measurement. The vibration sensor uses a high-frequency vibration sensor, and its specific parameters are: Sensitivity: 100mv / g; Measuring range: ±50g; Frequency range: 0.4-12kHz; Working temperature: -40~+120℃; The vibration sensor has stable performance and is shock-resistant; it is EMC compatible and suitable for industrial field monitoring; it has two-core MIL-C-5015 two-core socket output and is IP67.

[0046] The embodiment of the present application adopts welding technology. The installation method of the vibration sensor is based on the principle of not changing the original equipment structure. The bottom block of the vibration sensor is welded to the surface of the pump body by cold welding. After the construction is completed, the welding point is stable and will not affect the position and performance of the pump welding point. After the cold welding process is completed, the base welding point is very firm and the probability of falling is extremely low; even if it falls, the sensor is fixed with cables and cable clips, etc., and will not affect the pump itself.

[0047] In step 1, an intermediate junction box is added next to the motor of each RSW pump. A total of 5 vibration sensor cables at the motor drive end and non-drive end are connected to the intermediate junction box next to the motor. The vibration sensor collects the signal and transmits the signal through the vibration sensor cable.

[0048] The equipment in the data acquisition box includes 1 edge gateway, 1 data acquisition module, 1 communication module, 4 acceleration monitoring modules, as well as a power module and a photoelectric conversion module. The data acquisition device is used to receive the vibration signal collected by the vibration sensor, and realizes the synchronous acquisition of digital signals after A / D conversion through the signal conditioning system. Using embedded technology, the data acquisition software is embedded in the data acquisition device to realize the feature extraction function of each signal.

[0049] In step 3, the constrained variational problem is solved as follows: (1) In the formula, represents the partial derivative operation with respect to time t; δ(t) is the Dirac delta function; is the convolution operator; is the square of the L2 norm; f(t) is the original signal.

[0050] In step 4, the conversion formula is: (2) Where α is the quadratic penalty factor of the augmented Lagrangian; λ(t) is the Lagrangian multiplier; Represents the inner product operation.

[0051] The classical alternating direction multiplier method is used to solve μ k (t),ω k Iteratively update λ(t) and search for the saddle point of the augmented Lagrangian, which is the optimal solution to the original problem.

[0052] Formula (3)~Formula (4) is μ k (t) and ω k Iterative process in the Fourier domain.

[0053] (3) (4) In the formula, and They are μ k In addition, the Lagrange multiplier λ(t) is updated according to equation (5): (5) In the formula, is the Fourier transform of λ(t); τ is the iteration step size.

[0054] In step 5, the above iterative process ends after satisfying the termination condition in equation (6), and finally obtains K modal components with independent center frequencies and finite bandwidths, as follows: (6) Where ε is the convergence error.

[0055] In step 6, the modal component μ in equation (1) is k (t) Perform HT transformation: (7) The HT transform of a signal is equivalent to the signal undergoing an impulse response of The output of the linear system reflects the instantaneous characteristics of the signal. After the signal is transformed by HT, the amplitude of each frequency component will remain unchanged, but the phase will shift by 90 degrees.

[0056] In step 7, the constructed modal component μ k The analytical signal of (t) is as follows: (8) In the formula, z k (t) is μ k (t) is the analytical signal; j is the imaginary number symbol; a k (t) and θ k (t) are the instantaneous amplitude and instantaneous phase of the analytical signal, as follows: (9) In step 8, the instantaneous angular frequency ω of the signal can be obtained through the instantaneous phase k (t), as follows: (10) The instantaneous frequency ν can be further calculated k (t), as follows: (11) Therefore, the original signal f(t) can be expressed as: (12) Where Re represents the real part of the analytical signal.

[0057] From formula (12), we can see that the amplitude of the signal can be expressed as a function of time t and frequency ω. Therefore, the spectrum that describes the signal in the time-frequency domain is called the Hilbert spectrum, which is represented by H(ω,t), as follows: (13) like Figure 2 As shown in the figure, the RSW pump consists of a drive motor + RSW pump body, which is installed vertically and includes the RSW pump body 1, bearing box 2, coupling 3 and drive motor 4 arranged from bottom to top. There is a bearing box in the middle, and the motor shaft is connected to the drive shaft of the RSW pump through the coupling and the bearing box. Seven new vibration measurement points are added on each RSW pump, and the measurement points are distributed as follows Figure 2 As shown, the first measuring point 5 is arranged at the radial 90° position of the non-driving end of the motor, the second measuring point 6 is arranged at the radial 0° position of the non-driving end of the motor, the third measuring point 7 is arranged at the axial position of the non-driving end of the motor, the fourth measuring point 8 is arranged at the radial 90° position of the driving end of the motor, the fifth measuring point 9 is arranged at the radial 0° position of the driving end of the motor, the sixth measuring point 10 is arranged at the radial 90° position of the intermediate bearing, and the seventh measuring point 11 is arranged at the radial 0° position of the intermediate bearing. A vibration sensor is arranged at each measuring point.

[0058] The types and quantities of new vibration sensors added to various components of the RSW pump are shown in Table 1: Table 1 New vibration sensor types and quantities

[0059] At the same measuring point, the monitoring system displays two signals, namely acceleration signal and velocity signal.

[0060] The rotor non-stationary signal fault feature recognition method based on VMD-HT has the following technical routes: Figure 3 As shown, the specific process is as follows: (1) Obtain rotor vibration signal; (2) Perform VMD decomposition on the rotor vibration signal and obtain K modal components μ k ; (3) Perform HT transform on the K modal components and obtain the Hilbert spectrum of the original signal; (4) According to the changes in the characteristic frequencies in the Hilbert spectrum, the rotor faults are diagnosed, including rotor imbalance, rotor misalignment, rotor bending, friction failure and other water pump faults.

[0061] The rotor failure modes are diverse, mainly including imbalance, rubbing, misalignment, bending, cracks, etc. In order to verify the performance of the proposed VMD-HT time-frequency analysis algorithm, the following two typical rotor failure modes are considered, namely, imbalance and misalignment. A simulation test bench is used to simulate the typical rotor failures.

[0062] (1) Rotor imbalance failure The fault characteristics of rotor imbalance are shown in the following table. The time domain waveform of the imbalance signal is a sine wave, and the fault characteristic frequency is the base frequency. The fault characteristics of rotor imbalance are shown in Table 2: Table 2 Fault characteristics of rotor imbalance

[0063] The rotor unbalance is increased by installing screws on the turntable. At the same time, in order to simulate the non-steady-state signal under the rotor unbalance state, the speed of the drive motor is set to increase slowly, and the shaft displacement signal within 2s is intercepted, such as Figure 4 As shown in Figure 2, the rotor speed increases from 2400 rpm to 2640 rpm within 2 seconds, and the corresponding characteristic frequency also increases from 40 Hz to 44 Hz.

[0064] VMD-HT and traditional HHT methods were used to Figure 1 The time-frequency analysis of the non-stationary unbalanced fault signal in the Figure 5 and Figure 6 As shown. It can be seen that both VMD-HT and HHT can give the change of characteristic frequency over time. However, in HHT, the frequency fluctuates greatly, which makes it difficult to accurately identify the characteristic frequency. In contrast, the frequency fluctuation amplitude in the VMD-HT method is significantly smaller, and the characteristic frequency is clearer. Therefore, for non-stationary signals under rotor unbalance fault, the VMD-HT method has better time-frequency analysis performance than the traditional HHT.

[0065] (2) Rotor misalignment fault The fault characteristics of rotor misalignment are shown in Table 3. The time domain waveform of the misalignment signal is a superposition waveform of 1st frequency and 2nd frequency. The fault characteristic frequency is 2nd frequency, accompanied by fundamental frequency and high-order harmonics.

[0066] Table 3 Fault characteristics of rotor misalignment

[0067] The misalignment of the coupling can be increased by adjusting the scale of the misalignment code disk. In order to obtain the misalignment signal of the rotor in a non-steady state, the speed of the drive motor is set to increase slowly, and the vibration signal within 2 seconds is intercepted, such as Figure 7 As shown in Figure 2, within 2 seconds, the rotor speed increased from 1200 rpm to about 1440 rpm, and the fundamental frequency of the signal also increased from 20 Hz to 24 Hz.

[0068] VMD-HT and traditional HHT methods were used to Figure 7 The time-frequency analysis of the non-stationary misalignment fault signal in the Figure 8 and Fig. 9 As shown in the figure, it can be seen that the VMD-HT method can accurately identify the change process of the fundamental frequency and the 2nd frequency of the signal over time, and the fluctuation amplitude of each frequency component is small. In the traditional HHT method, each frequency component not only oscillates with a large amplitude, but also has modal aliasing at multiple moments. Therefore, for non-stationary rotor misalignment signals, the VMD-HT method achieves better time-frequency analysis results than the traditional HHT method.

[0069] Therefore, the above results verify the effectiveness of the VMD-HT method in anomaly detection and fault mode identification of RSW pumps.

[0070] In addition, if Fig.10 As shown, the embodiment of the present application also provides a non-stationary vibration signal time-frequency analysis system for a RSW pump of a CANDU6 nuclear power plant, comprising: Vibration signal acquisition module, used to collect non-stationary vibration signals of RSW pumps in real time; Signal decomposition and center frequency evaluation module, which is used to synchronously decompose the non-stationary vibration signal collected by the newly added RSW pump vibration monitoring system into a series of modal components with limited bandwidth using the VMD method, and online evaluate the center frequency of each component; The modal component and center frequency solving module is used to obtain the K modal components μ of VMD by solving the constrained variational problem. k (t)(k=1,2,3,…,K)and center frequency ω k ; The constraint problem conversion module is used to convert the constraint problem into an unconstrained optimization problem using the augmented Lagrangian method; The modal component calculation module is used to calculate K modal components μ with independent center frequencies and limited bandwidths. k (t); The Hilbert spectrum acquisition module is used to obtain the instantaneous frequency of each modal component by using HT variation to obtain the Hilbert spectrum (time-frequency spectrum) of the original signal; Analytical signal construction module for constructing modal components μ k (t) analytical signal; The original signal restoration module is used to obtain the instantaneous angular frequency ω of the signal through the instantaneous phase k (t), the instantaneous frequency ν is calculated k (t), and get the original signal f(t).

[0071] In one embodiment, the vibration signal acquisition module includes: Vibration sensor, used to be installed on the RSW pump to collect non-stationary vibration signals; A data acquisition box, used for receiving and storing signals collected by the vibration sensor; The middle junction box is used to connect the vibration sensor and the data acquisition box.

[0072] In one embodiment, the signal decomposition and center frequency evaluation module uses a VMD algorithm to perform signal decomposition and center frequency evaluation. The algorithm can adaptively decompose a non-stationary vibration signal into multiple modal components and determine the center frequency of each component in real time.

[0073] In one embodiment, the modal component and center frequency solving module solves the constrained variational problem through an iterative algorithm to obtain K modal components μ of VMD. k (t) and center frequency ω k .

[0074] In one embodiment, the constraint problem conversion module uses the augmented Lagrange multiplier method to convert the constrained variational problem into an unconstrained optimization problem, and by introducing Lagrange multipliers and penalty factors, the constraint conditions are integrated into the objective function for solving.

[0075] In one embodiment, the modal component calculation module calculates K modal components μ with independent center frequencies and finite bandwidths based on the solution of the transformed unconstrained optimization problem. k (t).

[0076] In one embodiment, the analytical signal construction module is constructed by dividing the modal components μ k (t) is combined with the imaginary signal to construct the modal component μ k (t) is the analytical signal.

[0077] In one embodiment, the system further includes a storage module for storing data such as the collected non-stationary vibration signal, the decomposed modal components, the calculated center frequency, the Hilbert spectrum, and the restored original signal.

[0078] The non-stationary vibration signal time-frequency analysis system of the RSW pump of the CANDU6 nuclear power plant provided in the above embodiment can implement the technical solution described in the above method embodiment. The specific implementation principles of the above modules can refer to the corresponding contents in the above method embodiment, which will not be repeated here.

[0079] For the RSW pump of the CANDU6 nuclear power plant, the types and number of existing measurement probes for evaluating the operating status of pumps and motors are relatively limited. This application adopts the method of adding vibration probes to collect high-frequency vibration signals, and uses time-frequency analysis technology to simultaneously carry out signal analysis in both time and frequency dimensions, thereby effectively extracting and analyzing the transient components in non-stationary signals, revealing the law of change of fault characteristic frequency over time, realizing parameter monitoring and early warning of large rotating machinery, and locating the specific cause of the fault according to the fault characteristics.

[0080] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed in the present application should be covered within the protection scope of the present application.

Claims

1. A time-frequency analysis method for non-stationary vibration signals of RSW pumps in CANDU6 nuclear power plants, characterized in that: include: Step 1: Set several measuring points on the RSW pump to obtain rotor vibration signals; Step 2, decomposing the collected non-stationary vibration signal into a series of modal components with limited bandwidth, and online evaluating the center frequency of each component; Step 3, obtain K modal components and center frequencies of VMD by solving the constrained variational problem; Step 4: Use the augmented Lagrangian method to transform the constrained variational problem into an unconstrained optimization problem; Step 5: Calculate and obtain K modal components with independent center frequencies and finite bandwidths; Step 6: Use HT variation to obtain the instantaneous frequency of each modal component and obtain the Hilbert spectrum of the original signal; Step 7: construct the analytical signal of the modal component; Step 8: Obtain the instantaneous angular frequency of the signal through the instantaneous phase, calculate the instantaneous frequency, and obtain the original signal.

2. The time-frequency analysis method for non-stationary vibration signals of the RSW pump of the CANDU6 nuclear power plant according to claim 1 is characterized in that: In step 1, 7 measuring points are arranged on the RSW pump, the first measuring point is arranged at the radial 90° position of the non-driving end of the motor, the second measuring point is arranged at the radial 0° position of the non-driving end of the motor, the third measuring point is arranged at the axial position of the non-driving end of the motor, the fourth measuring point is arranged at the radial 90° position of the driving end of the motor, the fifth measuring point is arranged at the radial 0° position of the driving end of the motor, the sixth measuring point is arranged at the radial 90° position of the intermediate bearing, and the seventh measuring point is arranged at the radial 0° position of the intermediate bearing.

3. The time-frequency analysis method for non-stationary vibration signals of the RSW pump of the CANDU6 nuclear power plant according to claim 1 is characterized in that: In step 3, the constrained variational problem is solved as follows: ； In the formula, is the partial derivative operation with respect to time t, δ(t) is the Dirac delta function, is the square of the L2 norm, and f(t) is the original signal.

4. The method for time-frequency analysis of non-stationary vibration signals of the RSW pump of the CANDU6 nuclear power plant according to claim 1 is characterized in that: The conversion formula in step 4 is: ； Where α is the quadratic penalty factor of the augmented Lagrangian, and λ(t) is the Lagrangian multiplier; The classical alternating direction multiplier method is used to solve μ k (t),ω k and λ(t) are iteratively updated and the saddle point of the augmented Lagrangian is searched, μ k (t) The iterative process in the Fourier domain is: ； ω k The iterative process in the Fourier domain is: ； In the formula, and They are μ k Fourier transform of f(t) and f(t); The Lagrange multiplier λ(t) is updated as follows: ； In the formula, is the Fourier transform of λ(t), and τ is the iteration step size.

5. The method for time-frequency analysis of non-stationary vibration signals of the RSW pump of the CANDU6 nuclear power plant according to claim 4 is characterized in that: The iterative process ends after the termination condition in the following formula is met, and K modal components with independent center frequencies and limited bandwidths are obtained, as follows: ； Where ε is the convergence error.

6. The method for time-frequency analysis of non-stationary vibration signals of the RSW pump of the CANDU6 nuclear power plant according to claim 1 is characterized in that: In step 6, the modal component μ k (t) Perform HT transformation as follows: ； After the signal is transformed by HT, the amplitude of each frequency component will remain unchanged, and the phase will shift by 90 degrees.

7. The method for time-frequency analysis of non-stationary vibration signals of the RSW pump of the CANDU6 nuclear power plant according to claim 1 is characterized in that: In step 7, the constructed modal component μ k The analytical signal of (t) is as follows: ； In the formula, z k (t) is μ k The analytical signal of (t), j is the imaginary number symbol, a k (t) and θ k (t) are the instantaneous amplitude and instantaneous phase of the analytical signal respectively.

8. The method for time-frequency analysis of non-stationary vibration signals of the RSW pump of the CANDU6 nuclear power plant according to claim 1 is characterized in that: In step 8, the instantaneous angular frequency ω of the signal is obtained through the instantaneous phase k (t), as follows: ； Calculate the instantaneous frequency ν k (t), as follows: ； Then the original signal f(t) is expressed as: ； Where Re represents the real part of the analytical signal.

9. A non-stationary vibration signal time-frequency analysis system for the RSW pump of a CANDU6 nuclear power plant, characterized in that: include: Vibration signal acquisition module, used to collect non-stationary vibration signals of RSW pumps in real time; Signal decomposition and center frequency evaluation module, used to decompose non-stationary vibration signals into a series of modal components with limited bandwidth and evaluate the center frequency of each component online; The modal component and center frequency solving module is used to obtain K modal components and center frequencies of VMD by solving the constrained variational problem; The constraint problem conversion module is used to convert the constraint problem into an unconstrained optimization problem; A modal component calculation module is used to calculate and obtain K modal components with independent center frequencies and limited bandwidths; The Hilbert spectrum acquisition module is used to obtain the instantaneous frequency of each modal component by using HT variation to obtain the Hilbert spectrum of the original signal; An analytical signal construction module, used to construct analytical signals of modal components; The original signal restoration module is used to obtain the instantaneous angular frequency of the signal through the instantaneous phase and calculate the instantaneous frequency.

10. The non-stationary vibration signal time-frequency analysis system of the RSW pump of the CANDU6 nuclear power plant according to claim 9 is characterized in that: The vibration signal acquisition module includes: Vibration sensor, used to be installed on the RSW pump to collect non-stationary vibration signals; A data acquisition box, used for receiving and storing signals collected by the vibration sensor; The middle junction box is used to connect the vibration sensor and the data acquisition box.

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