A rotor misalignment vibration fault identification method and system and a storage medium
By analyzing vibration measurement data, calculating the total vibration and extracting peak frequency values, the algorithm is simplified to identify rotor misalignment faults, solving the problem of complex calculations and large amounts of computation in existing technologies, and achieving efficient identification of rotor misalignment.
Patent Information
- Application Number
- CN202211023504.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2022-08-25
- Publication Date
- 2026-01-27
- Estimated Expiration
- 2042-08-25
AI Technical Summary
Existing technologies for rotor misalignment fault identification involve complex algorithms, high computational load, and low efficiency, making it difficult to effectively identify the misalignment state of the rotor system.
By analyzing the measured vibration data, calculating the total vibration, performing spectral transformation, extracting the peak frequency values of axial and radial vibration, and judging rotor misalignment faults based on the set threshold, the algorithm is simplified and the amount of calculation is reduced.
It enables simple and efficient identification of rotor misalignment vibration faults, reduces computational complexity and workload, and improves identification efficiency.
Smart Images
Figure CN115493840B_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of rotor misalignment fault identification technology. This invention relates to a rotor misalignment vibration fault identification method, system and storage medium. Background Technology
[0002] The rotor system is a core component of equipment such as aero engines, steam turbines, and wind turbines. Due to manufacturing and installation errors, wear of support bearings, rotor deflection, and thermal deformation, the rotor can be misaligned in various ways. This can range from causing excessive vibration of the entire machine to causing damage to the entire rotor system, threatening the safe and stable operation of the equipment. Misalignment failures are unavoidable, but if the misalignment status (type, location, and degree) of the rotor system can be identified in a timely manner, maintenance measures can be taken promptly to reduce the accident rate caused by misalignment failures.
[0003] Rotor misalignment can be caused by poor assembly, deformation or malfunction of parts during operation. Deformation of components such as supports, casings, and bearings during operation due to heat, stress, or uneven temperature can lead to rotor misalignment. Rotor misalignment occurs when the rotor and its support, or between supports themselves, are not concentric, and can be angular or vertical. Angular misalignment refers to the relative tilt of the shaft and support. Vertical misalignment refers to bearings or bearings that are parallel to the shaft centerline but at different heights. Both types of misalignment cause axial and radial forces to interact between the shaft and bearings. As the rotor rotates, these forces alternate, causing vibration in both the rotor and its support.
[0004] Application No. 2021101406953 discloses a rotor misalignment state identification method based on improved DS evidence fusion. This method uses mutual information to measure the similarity between evidence bodies, corrects the initial evidence source based on the similarity level, and obtains fault state identification based on DS evidence theory. However, this method, which uses DS evidence theory to identify fault states, is computationally complex, computationally intensive, and inefficient. Summary of the Invention
[0005] The purpose of this invention is to provide a method, system, and storage medium for identifying rotor misalignment vibration faults. By analyzing measured vibration data and obtaining rotor misalignment vibration faults based on rotor misalignment vibration characteristics, rotor misalignment vibration faults can be effectively identified.
[0006] The technical solution to achieve the purpose of this invention is as follows:
[0007] A method for identifying rotor misalignment vibration faults includes the following steps:
[0008] S01: Obtain N radial vibration values to form a radial vibration signal array Vr[]; Obtain N axial vibration values to form an axial vibration signal array Vz[];
[0009] S02: Calculate the total vibration A based on Vr[] and Vz[];
[0010] S03: When the total vibration A is greater than or equal to the vibration limit value Vmax, perform spectral transformation on Vr[] and Vz[] to obtain the vibration spectrum data Fr[i] and Fz[i];
[0011] S04: Based on the vibration spectrum data Fr[i] and Fz[i], obtain the frequency values Pr[j] and Pz[j] of Np peak points;
[0012] S05: Extract the axial 1x vibration value Pz1x = Pz[0] from Pz[j], and extract the radial 2x vibration value Pr2x = Pr[1] from Pr[j];
[0013] S06: If Pz1x≥Kz and Pr2x≥Kr, where Kz and Kr are set thresholds, determine the rotor misalignment fault.
[0014] In a preferred embodiment, the method for calculating the total vibration in step S02 includes:
[0015] S21: Combine Vr[] and Vz[] to form vibration data V[i]:
[0016]
[0017] S22: Calculate the total vibration A:
[0018]
[0019] Where N is the length of the calculated sequence of vibration data.
[0020] In a preferred embodiment, the method for statistically obtaining the peak frequency value in step S04 includes:
[0021] S41: Traverse all spectrum data;
[0022] S42: When F[i+1]≤F[i] and F[i]>F[i-1], determine that F[i] is a peak point;
[0023] S43: Obtain Np maximum peak values Pmax = F[i], where the index of the maximum peak is ip = i, and ip corresponds to the vibration frequency;
[0024] S44: Peak frequency value P[k] = Frip, frequency Frip = ip * Fp / (2M), where M is the length of F[] and Fp is the sampling frequency of the vibration signal.
[0025] In a preferred embodiment, the method further includes the following step before step S05:
[0026] S51: Obtain rotor speed
[0027] S52: If the 1x peak frequency is not equal to the current speed, it is determined that it is not a rotor misalignment fault, and the process ends; if the 2x peak frequency is not equal to the current 2x, it is determined that it is not a rotor misalignment fault, and the process ends.
[0028] S54: Conversely, proceed to step S05.
[0029] In the preferred technical solution, Kz and Kr are determined based on experience.
[0030] In the preferred technical solution, Kz and Kr are determined based on the magnitude of the peak values of the spectrum measured under normal operating conditions. Kz is determined by the ratio of the axial 1x peak vibration value to the radial 1x peak vibration value; Kr is determined by the ratio of the radial 2x peak vibration value to the radial 1x peak vibration value.
[0031] The present invention also discloses a computer storage medium storing a computer program thereon, wherein the computer program, when executed, implements the rotor misalignment vibration fault identification method according to any one of claims 1-6.
[0032] This invention also discloses a rotor misalignment vibration fault identification system, comprising:
[0033] The vibration signal acquisition module acquires N radial vibration values to form a radial vibration signal array Vr[]; and acquires N axial vibration values to form an axial vibration signal array Vz[].
[0034] The vibration total calculation module calculates the total vibration A based on Vr[] and Vz[].
[0035] The vibration spectrum transformation module performs spectrum transformation on Vr[] and Vz[] when the total vibration A is greater than or equal to the vibration limit value Vmax, to obtain vibration spectrum data Fr[i] and Fz[i].
[0036] The peak frequency value acquisition module obtains Np peak frequency values Pr[j] and Pz[j] based on the vibration spectrum data Fr[i] and Fz[i].
[0037] The extraction module extracts the axial 1x vibration value Pz1x = Pz[0] from Pz[j] and the radial 2x vibration value Pr2x = Pr[1] from Pr[j].
[0038] The rotor misalignment fault detection module determines a rotor misalignment fault if Pz1x≥Kz and Pr2x≥Kr, where Kz and Kr are set thresholds.
[0039] In a preferred embodiment, the method for calculating the total vibration in the total vibration calculation module includes:
[0040] S21: Combine Vr[] and Vz[] to form vibration data V[i]:
[0041]
[0042] S22: Calculate the total vibration A:
[0043]
[0044] Where N is the length of the calculated sequence of vibration data.
[0045] In a preferred embodiment, the method for statistically obtaining peak frequency values in the peak frequency value acquisition module includes:
[0046] S41: Traverse all spectrum data;
[0047] S42: When F[i+1]≤F[i] and F[i]>F[i-1], determine that F[i] is a peak point;
[0048] S43: Obtain Np maximum peak values Pmax = F[i], where the index of the maximum peak is ip = i, and ip corresponds to the vibration frequency;
[0049] S44: Peak frequency value P[k] = Frip, frequency Frip = ip * Fp / (2M), where M is the length of F[] and Fp is the sampling frequency of the vibration signal.
[0050] Compared with the prior art, the significant advantages of this invention are:
[0051] By analyzing the measured vibration data and identifying rotor misalignment vibration faults based on the characteristics of rotor misalignment vibration, the algorithm is simple, computationally inexpensive, and can effectively identify rotor misalignment vibration faults. Attached Figure Description
[0052] Figure 1 A flowchart of the rotor misalignment vibration fault identification method in this embodiment;
[0053] Figure 2 This is a schematic diagram of the rotor misalignment vibration fault identification system in the embodiment.
[0054] Figure 3 Vibration time-domain diagram of a preferred embodiment;
[0055] Figure 4 Vibration spectrum diagram of a preferred embodiment;
[0056] Figure 5 This is a schematic diagram illustrating the peak point determination in an embodiment. Detailed Implementation
[0057] The principle of this invention is: by analyzing the measured vibration data and obtaining the rotor misalignment vibration fault based on the rotor misalignment vibration characteristics, rotor misalignment vibration faults can be effectively identified.
[0058] Example 1:
[0059] like Figure 1 As shown, a method for identifying rotor misalignment vibration faults includes the following steps:
[0060] S01: Obtain N radial vibration values to form a radial vibration signal array Vr[]; Obtain N axial vibration values to form an axial vibration signal array Vz[];
[0061] S02: Calculate the total vibration A based on Vr[] and Vz[];
[0062] S03: When the total vibration A is greater than or equal to the vibration limit value Vmax, perform spectral transformation on Vr[] and Vz[] to obtain the vibration spectrum data Fr[i] and Fz[i];
[0063] S04: Based on the vibration spectrum data Fr[i] and Fz[i], obtain the frequency values Pr[j] and Pz[j] of Np peak points;
[0064] S05: Extract the axial 1x vibration value Pz1x = Pz[0] from Pz[j], and extract the radial 2x vibration value Pr2x = Pr[1] from Pr[j];
[0065] S06: If Pz1x≥Kz and Pr2x≥Kr, where Kz and Kr are set thresholds, determine the rotor misalignment fault.
[0066] In a preferred implementation, the method for calculating the total vibration in step S02 includes:
[0067] S21: Combine Vr[] and Vz[] to form vibration data V[i]:
[0068]
[0069] S22: Calculate the total vibration A:
[0070]
[0071] Where N is the length of the calculated sequence of vibration data.
[0072] In a preferred implementation, the methods for statistically obtaining peak frequency values in S04 include:
[0073] S41: Traverse all spectrum data;
[0074] S42: When F[i+1]≤F[i] and F[i]>F[i-1], determine that F[i] is a peak point;
[0075] S43: Obtain Np maximum peak values Pmax = F[i], where the index of the maximum peak is ip = i, and ip corresponds to the vibration frequency;
[0076] S44: Peak frequency value P[k] = Frip, frequency Frip = ip * Fp / (2M), where M is the length of F[] and Fp is the sampling frequency of the vibration signal.
[0077] In a preferred implementation, step S05 is preceded by:
[0078] S51: Obtain rotor speed
[0079] S52: If the 1x peak frequency is not equal to the current speed, it is determined that it is not a rotor misalignment fault, and the process ends; if the 2x peak frequency is not equal to the current 2x, it is determined that it is not a rotor misalignment fault, and the process ends.
[0080] S54: Conversely, proceed to step S05.
[0081] In a better implementation, Kz and Kr are determined based on experience. For newly developed engines, where historical experimental data is completely lacking, Kz can be tentatively set to 0.5, and Kr can be set to 0.55, which will be adjusted as experimental data increases.
[0082] In a preferred implementation, for engines that are not newly developed, Kz and Kr are determined based on the magnitude of the peak values of the spectrum measured under normal operating conditions. Kz is determined by the ratio of the axial 1x peak vibration value to the radial 1x peak vibration value; Kr is determined by the ratio of the radial 2x peak vibration value to the radial 1x peak vibration value.
[0083] In another embodiment, the present invention also discloses a computer storage medium storing a computer program thereon, which, when executed, implements the above-described rotor misalignment vibration fault identification method.
[0084] In another embodiment, such as Figure 2 As shown, this invention also discloses a rotor misalignment vibration fault identification system, comprising:
[0085] The vibration signal acquisition module 10 acquires N radial vibration values to form a radial vibration signal array Vr[]; and acquires N axial vibration values to form an axial vibration signal array Vz[].
[0086] Vibration total calculation module 20 calculates the total vibration A based on Vr[] and Vz[].
[0087] The vibration spectrum transformation module 30 performs spectrum transformation on Vr[] and Vz[] when the total vibration A is greater than or equal to the vibration limit value Vmax, to obtain vibration spectrum data Fr[i] and Fz[i].
[0088] The peak frequency value acquisition module 40 obtains Np peak frequency values Pr[j] and Pz[j] based on the vibration spectrum data Fr[i] and Fz[i].
[0089] Extraction module 50 extracts the axial 1x vibration value Pz1x=Pz[0] from Pz[j] and the radial 2x vibration value Pr2x=Pr[1] from Pr[j];
[0090] The rotor misalignment fault detection module 60 determines a rotor misalignment fault if Pz1x≥Kz and Pr2x≥Kr, where Kz and Kr are set thresholds.
[0091] The following description uses a preferred embodiment as an example:
[0092] The unit of rotor critical speed is revolutions per minute (r / min). The unit of rotor vibration frequency is generally Hz, but (r / min) can also be used; (r / min) is used here. The vibration frequency that is the same as the rotational speed is called the fundamental frequency (or 1st harmonic, or 1x), and the vibration frequency that is the same as n times the rotational speed is called the nth harmonic (nx).
[0093] The most prominent characteristic of rotor misalignment vibration is:
[0094] 1) The rotor has large axial vibration (e.g., 1x);
[0095] 2) There is a large 2x vibration in the radial direction.
[0096] Other mechanical faults may also exhibit 2x vibration, but they will not simultaneously cause large axial vibrations. Therefore, the two characteristics mentioned above can be used to determine whether a rotor misalignment fault has occurred. If a rotor misalignment fault is confirmed, the relative magnitudes of 2x and 1x can be used to determine the degree of rotor misalignment. The larger the 2x relative to 1x, the more severe the rotor misalignment.
[0097] The amplitude-time curve plotted from the vibration data is shown below. Figure 3 Its horizontal axis is time, hence it is called a vibration time-domain plot.
[0098] After Fourier spectrum analysis, a vibration frequency domain diagram, or spectrum diagram, can be plotted, such as... Figure 4 As shown in the figure. The vertical axis represents amplitude, and the horizontal axis represents frequency in Hz or r / min (revolutions per minute). In the figure, the frequencies of the 1st, 2nd, and 3rd peaks correspond to the rotor's 1st, 2nd, and 3rd critical speeds, respectively.
[0099] (1) The main algorithm steps are as follows:
[0100] 1) Start
[0101] 2) Set the rotor misalignment fault flag JD=0
[0102] Set a misalignment fault indicator JD. When JD=0, it means there is no fault. When JD=1, it means that a rotor misalignment fault has occurred.
[0103] 3) Set the axial vibration 1x threshold value Kz to indicate excessive axial vibration.
[0104] Kz is one of two criteria used to determine whether a rotor misalignment fault has occurred.
[0105] 4) Set the threshold value Kr for excessive radial 2x vibration.
[0106] Kr is another criterion used to determine whether a rotor misalignment fault has occurred.
[0107] Kz and Kr need to be determined based on experience. For engines that are not newly developed, they can be determined based on the magnitude of the spectral peak values measured under normal operating conditions in the early stages of engine development.
[0108] Kz is determined by the ratio of the axial 1x peak vibration value to the radial 1x peak vibration value;
[0109] Kr is determined by the ratio of the radial 2x peak vibration value to the radial 1x peak vibration value.
[0110] For the newly developed engine, there is a complete lack of historical experimental data. Kz can be tentatively set at 0.5, and Kr can be set at 0.55, which will be adjusted in a timely manner as more experimental data is collected.
[0111] 5) Set the vibration limit value Vmax
[0112] Vmax is used to determine whether the current vibration exceeds the limit. If the total vibration exceeds this value, it indicates a vibration fault, requiring further fault identification. The Vmax value is given in the engine development general requirements; if it is not available, Vmax = 40g can be used, where g is the acceleration due to gravity.
[0113] 6) Input the acquisition frequency Fp and the upper limit of the frequency for spectrum transformation Frmax;
[0114] Fp is measured in Hz, which stands for times per second, indicating the number of data points collected per second. Fp and Frmax = Fp / 2 are required in spectrum conversion.
[0115] 7) Input N radial vibration signals Vr[]
[0116] "[]" represents an array. Input N radial vibration values (such as acceleration values) are stored in the array Vr[i], where i corresponds to time:
[0117] Time = 1 / Fp.
[0118] 8) Input N axial vibration signals Vz
[0119] Input N axial vibration values are stored in the array Vz.
[0120] 9) Input the rotor speed NG
[0121] The input rotor speed is stored in the array NG, and the number of data is also N, the same as that of Vr and Vz.
[0122] 10) Calculate the total vibration amount A
[0123] Calculate the total vibration amount according to Vr and Vz.
[0124] 11) If A < Vmax, go to step 21)
[0125] If the calculated total vibration amount A is less than the vibration limit value Vmax, it indicates that the engine rotor vibration is normal. Then, the rotor vibration normal flag JD = 0 can be output, and the calculation is stopped.
[0126] 12) Perform fast Fourier spectrum transformation (FFT) to obtain M radial and axial vibration spectrum data Fr[i], Fz[i]
[0127] Apply the mature technology FFT to perform spectrum transformation on Vr and Vz to obtain M radial and axial vibration spectrum data Fr[i], Fz[i], where i corresponds to the vibration frequency:
[0128] Vibration frequency = i * Frmax / M, where Frmax = Fp / 2 is the frequency upper limit set for the FFT calculation formula.
[0129] 13) Statistically obtain Np peak point frequency values Pr[j], Pz[j] from the vibration spectrum data Fr[i], Fz[i]
[0130] The arrays Pr[j] and Pz[j] store the frequency values (unit: r / min) from large to small, and a total of Np frequency values are stored;
[0131] 14) If the frequencies Pr[0], Pz[0] of the main peak points (1x) do not correspond to the current speed, go to step 21)
[0132] If the frequencies of the main peak points (1x) do not correspond to the current speed, it indicates that it is not a rotor misalignment fault, but may be other faults (such as casing resonance).
[0133] 15) If the frequencies of the secondary peak points Pr[1] and Pz[1] do not correspond to the current 2x, go to 21). The vibration characteristics of rotor misalignment are not satisfied, so it can be determined that the rotor misalignment fault has not occurred.
[0134] 16) Extract the axial 1x vibration value Pz1x = Pz[0] from Pz, and extract the radial 1x vibration value Pr1x = Pr[0] from Pr.
[0135] A large axial 1x vibration is a fault characteristic of rotor misalignment, so it is extracted and compared for judgment.
[0136] 17) If: (Pz1x / Pr1x < Kz), go to 21).
[0137] The vibration characteristics of rotor misalignment are not satisfied, so it can be determined that the rotor misalignment fault has not occurred.
[0138] 18) Extract the radial 2x vibration value Pr2x = Pr[1] from Pr.
[0139] A large radial 2x vibration value is a fault characteristic of rotor misalignment, so it is extracted and compared for judgment.
[0140] 19) If: (Pr2x / Pr1x < Kr), go to 21).
[0141] The vibration characteristics of rotor misalignment are not satisfied, so it can be determined that the rotor misalignment fault has not occurred.
[0142] 20) Set the rotor fault flag JD = 1.
[0143] The possibilities of no rotor misalignment fault have been excluded, so it can be determined that a rotor misalignment fault has occurred, and set the rotor misalignment fault determination index JD = 1.
[0144] 21) Output the fault flag JD.
[0145] 22) Stop.
[0146] Specifically, the vibration total amount algorithm:
[0147] Calculate the vibration total amount according to the root mean square value formula of the vibration signal. The formula is as follows:
[0148]
[0149] Among them, N is the calculation sequence length of the vibration data, and V[i] (i = 1...N) is the vibration data (such as vibration acceleration).
[0150] The steps of the vibration total amount extraction algorithm are as follows:
[0151] 1) Start
[0152] 2) Input the synthetic vibration test data V[]
[0153] "Synthesis" refers to the process of synthesizing components V beforehand if V has multiple components, such as Vx, Vy, and Vz.
[0154]
[0155] 3) Set A = 0
[0156] Set the initial value of the total vibration to 0.
[0157] 4) for(i=0; i <N;i++)
[0158] All vibration test data are cycled.
[0159] 5) Calculation: A=A+V[i]*V[i]
[0160] That is, calculate A = A + (V[i]). 2 See equation (1).
[0161] 6) Continue loop 4) until the end.
[0162] 7) Calculate: A = sqrt(B / N)
[0163] Immediate calculation See equation (1).
[0164] 8) Output the calculation result: A;
[0165] Output total vibration value A.
[0166] 9) Stop.
[0167] Specifically, peak frequency value extraction algorithm
[0168] like Figure 4 As shown in the spectrum, there are three peaks. The peak frequency extraction algorithm is to extract the frequency values of these three peaks and save them.
[0169] The peak frequency value extraction algorithm steps are as follows:
[0170] 1) Start
[0171] 2) Set the peak point array P[]
[0172] This array is used to store peak frequency values.
[0173] 3) Set Np = 3
[0174] Np is the number of peaks selected.
[0175] 4) Input M vibration spectrum data F[]
[0176] Vibration spectrum data is obtained by performing FFT transformation on vibration time-domain data.
[0177] 5) j = 1
[0178] Set the initial value of the subscript for the first iteration of loop 9).
[0179] 6) for(k=0;k <Np;k++)
[0180] Perform Np loops to find the first Np largest peaks.
[0181] 7) Pmax=0
[0182] Set the initial value of the peak value.
[0183] 8) ip=0
[0184] Set the initial value of the peak value index.
[0185] 9) for(i = j; i <M-1;i++)
[0186] Loop through all M spectral data F[i].
[0187] 10) If (F[i+1]>F[i] and F[i]>F[i-1]), go to 9)
[0188] If F[i+1]>F[i] and F[i]>F[i-1], it means that it is not the peak value, so proceed to the next loop.
[0189] Peak point (peak point) identification method:
[0190] like Figure 5 As shown, the values at points 1, 2, 3, and 4 gradually increase, indicating that they are not peak points.
[0191] If the price rises between 3 and 4 o'clock and falls between 4 and 5 o'clock, then the peak point can be identified. The characteristic is that the price rises first and then falls between these three points.
[0192] The values at points 4, 5, and 6 gradually decrease, indicating that they are not peak points.
[0193] 11) Pmax = F[i], ip = i
[0194] Select the current largest peak value and save it; IP corresponds to the vibration frequency.
[0195] The vibration frequency Frip = ip * Frmax / M, that is, Frip = ip * Fp / (2M), and Frmax = Fp / 2 is the upper limit of the frequency set by the FFT calculation formula.
[0196] 12)j=ip+1
[0197] Set the initial subscript value for the next iteration of loop 9).
[0198] 13) Continue looping 9) until the end.
[0199] 14) P[k] = Frip
[0200] Save the peak frequency at P.
[0201] 15) Continue the loop 6) until the end.
[0202] 16) Output the calculation result P[]
[0203] 17) Stop
[0204] The above embodiments are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments. Any changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention shall be considered equivalent substitutions and shall be included within the protection scope of the present invention.
Claims
1. A method for identifying rotor misalignment vibration faults, characterized in that, Includes the following steps: S01: Obtain N radial vibration values to form a radial vibration signal array Vr[]; Obtain N axial vibration values to form an axial vibration signal array Vz[]; S02: Calculate the total vibration A based on Vr[] and Vz[]; S03: When the total vibration A is greater than or equal to the vibration limit value Vmax, perform spectral transformation on Vr[] and Vz[] to obtain the vibration spectrum data Fr[i] and Fz[i]; S04: Based on the vibration spectrum data Fr[i] and Fz[i], obtain Np peak frequency values Pr[j] and Pz[j]; The method for obtaining peak frequency values through statistics includes: S41: Traverse all spectrum data; S42: When F[i+1]≤F[i] and F[i]> F[i-1], determine that F[i] is a peak point; S43: Obtain Np maximum peak values Pmax=F[i], where the index of the maximum peak is ip=i and ip corresponds to the vibration frequency; S44: Peak frequency value P[k] = Frip, frequency Frip = ip Fp / (2M), where M is the length of F[] and Fp is the sampling frequency of the vibration signal; S05: Extract the axial 1x vibration value Pz1x= Pz[0] from Pz[j], and extract the radial 2x vibration value Pr2x=Pr[1] from Pr[j]; S06: If Pz1x≥Kz and Pr2x≥Kr, where Kz and Kr are set thresholds, determine the rotor misalignment fault.
2. The rotor misalignment vibration fault identification method according to claim 1, characterized in that, The method for calculating the total vibration in step S02 includes: S21: Combine Vr[] and Vz[] to form vibration data V[i]: S22: Calculate the total vibration A: (1) Where N is the length of the calculated sequence of vibration data.
3. The rotor misalignment vibration fault identification method according to claim 1, characterized in that, Before step S05, the following is also included: S51: Obtain rotor speed; S52: If the 1x peak frequency is not equal to the current speed, it is determined that it is not a rotor misalignment fault, and the process ends; if the 2x peak frequency is not equal to the current 2x, it is determined that it is not a rotor misalignment fault, and the process ends. S54: Conversely, proceed to step S05.
4. The rotor misalignment vibration fault identification method according to claim 1, characterized in that, Kz and Kr are determined based on experience.
5. The rotor misalignment vibration fault identification method according to claim 1, characterized in that, Kz and Kr are determined based on the magnitude of the peak values of the spectrum measured under normal operating conditions. Kz is determined by the ratio of the axial 1x peak vibration value to the radial 1x peak vibration value; Kr is determined by the ratio of the radial 2x peak vibration value to the radial 1x peak vibration value.
6. A computer storage medium having a computer program stored thereon, characterized in that, When the computer program is executed, it implements the rotor misalignment vibration fault identification method according to any one of claims 1-5.
7. A rotor misalignment vibration fault identification system, characterized in that, include: The vibration signal acquisition module acquires N radial vibration values to form a radial vibration signal array Vr[]; and acquires N axial vibration values to form an axial vibration signal array Vz[]. The vibration total calculation module calculates the total vibration A based on Vr[] and Vz[]. The vibration spectrum transformation module performs spectrum transformation on Vr[] and Vz[] when the total vibration A is greater than or equal to the vibration limit value Vmax, to obtain vibration spectrum data Fr[i] and Fz[i]. The peak frequency value acquisition module obtains Np peak frequency values Pr[j] and Pz[j] based on the vibration spectrum data Fr[i] and Fz[i]. The method for obtaining peak frequency values through statistics includes: S41: Traverse all spectrum data; S42: When F[i+1]≤F[i] and F[i]> F[i-1], determine that F[i] is a peak point; S43: Obtain Np maximum peak values Pmax=F[i], where the index of the maximum peak is ip=i and ip corresponds to the vibration frequency; S44: Peak frequency value P[k] = Frip, frequency Frip = ip Fp / (2M), where M is the length of F[] and Fp is the sampling frequency of the vibration signal; The extraction module extracts the axial 1x vibration value Pz1x= Pz[0] from Pz[j] and the radial 2x vibration value Pr2x=Pr[1] from Pr[j]. The rotor misalignment fault detection module determines a rotor misalignment fault if Pz1x≥Kz and Pr2x≥Kr, where Kz and Kr are set thresholds.
8. The rotor misalignment vibration fault identification system according to claim 7, characterized in that, The method for calculating the total vibration in the vibration total calculation module includes: S21: Combine Vr[] and Vz[] to form vibration data V[i]: S22: Calculate the total vibration A: (1) Where N is the length of the calculated sequence of vibration data.
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