CN113340640B - Rotating machinery axis track purification method, device, equipment and storage medium - Google Patents
Rotating machinery axis track purification method, device, equipment and storage medium Download PDFInfo
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- CN113340640B CN113340640B CN202110827859.XA CN202110827859A CN113340640B CN 113340640 B CN113340640 B CN 113340640B CN 202110827859 A CN202110827859 A CN 202110827859A CN 113340640 B CN113340640 B CN 113340640B
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Abstract
The invention discloses a method, a device, equipment and a storage medium for purifying an axis track of a rotary machine, which solve the problem of inaccurate purification of the axis track caused by only signal denoising in the conventional rotor axis track purification method; the technical scheme of the application carries out harmonic wavelet decomposition on the vibration signal obtained in the running process of the rotary machine to obtain the time domain characteristics of the vibration signal and eliminate the noise influence in the axis track signal; and correcting the time domain characteristics of the vibration signal according to the rotation speed information of the rotary machine, extracting the time domain characteristics of the vibration signal corresponding to the rotation speed information of the rotary machine from the time domain characteristics of the vibration signal, further filtering noise in the axis track signal, eliminating the interference of complex noise pollution and non-stationary components caused by the fault, accurately purifying the axis track of the rotating shaft, and simultaneously reducing the influence of frequency band bandwidth and amplitude constancy in harmonic wavelet decomposition on signal reconstruction.
Description
Technical Field
The invention relates to the technical field of rotating machinery, in particular to a rotating machinery axis track purification method, a rotating machinery axis track purification device, rotating machinery axis track purification equipment and a storage medium.
Background
The axis track is used as an important state characteristic parameter of the rotary machine, and can intuitively, simply and vividly reflect the running condition of the equipment. However, in an actual working state, the axial center trajectory of the rotor is inevitably interfered by random noise and electromagnetic signals, and meanwhile, the axial center trajectory is abnormally disordered due to abnormal vibration caused by rotor faults, so that a clear axial center trajectory capable of representing fault characteristics is difficult to obtain. Therefore, eliminating the interference of noise and non-stationary components and obtaining a clear and recognizable axis track after purification is an important premise for identifying the fault type of the rotary machine.
The starting point of the rotor axis track purification of the existing rotary equipment is signal denoising, and methods such as low-pass filtering, wavelet denoising, empirical mode decomposition and the like are widely used for eliminating axis vibration signal noise pollution and extracting a denoised axis track. However, the situation of an industrial field is more complicated, the axis track of the rotor is interfered by the noise of a testing environment, and a non-stationary component is introduced into observation data in a complicated fault state, so that the form of the axis track is blurred, and the judgment of the rotor fault is interfered.
Disclosure of Invention
The embodiment of the invention provides a rotating machinery axis track purification method, a rotating machinery axis track purification device and a storage medium, and solves the problem of inaccurate axis track purification caused by signal denoising only in the existing rotor axis track purification method.
In one aspect, the present application provides a method for purifying a rotating machine axis trajectory, where the method includes:
acquiring a vibration signal of a rotor in the running process of a rotary machine;
carrying out harmonic wavelet decomposition on the vibration signal to obtain the time domain characteristics of the vibration signal;
and correcting the time domain characteristics of the vibration signal according to the rotation speed information of the rotor to obtain the purified axis locus of the rotor.
In some embodiments of the present application, the modifying the time domain characteristic of the vibration signal according to the rotational speed information of the rotor to obtain the purified axis locus of the rotor includes:
acquiring rotating speed information of the rotor in the rotating machine;
correcting the time domain characteristics of the vibration signals according to the rotating speed information to obtain target time domain characteristics matched with the rotating speed information;
and obtaining the purified axis locus of the rotor according to the target time domain characteristics.
In some embodiments of the present application, the modifying the time domain characteristic of the vibration signal according to the rotation speed information to obtain a target time domain characteristic matched with the rotation speed information includes:
inputting the rotating speed information into a preset filter to obtain a predicted time domain characteristic corresponding to the rotating speed information of the rotor;
comparing and analyzing the predicted time domain characteristic and the time domain characteristic of the vibration signal through the filter to obtain an error between the predicted time domain characteristic and the time domain characteristic of the vibration signal;
and minimizing the error through a least square method, and correcting the time domain characteristics of the vibration signal to obtain the target time domain characteristics matched with the rotating speed information.
In some embodiments of the present application, the performing harmonic wavelet decomposition on the vibration signal to obtain a time domain feature of the vibration signal includes:
carrying out Fourier transform on the vibration signal to obtain frequency domain characteristics corresponding to the vibration signal;
calculating frequency domain band values through the frequency domain features;
carrying out harmonic wavelet decomposition according to the frequency domain characteristics and the frequency domain frequency band values;
and carrying out inverse Fourier transform on the frequency domain characteristics subjected to harmonic wavelet decomposition to obtain the time domain characteristics of the vibration signals.
In some embodiments of the present application, said calculating frequency domain bin values from said frequency domain features comprises:
acquiring rotating speed information of the rotor in the rotating machine;
determining a target fundamental frequency from the frequency domain features according to the rotation speed information;
acquiring a target frequency range corresponding to the target fundamental frequency;
acquiring a preset decomposition layer number of harmonic wavelet decomposition;
according to the preset decomposition layer number and the target frequency range, carrying out integer zero-taking operation to obtain the target frequency segment number of the target frequency range;
calculating a target frequency difference of harmonic wavelet decomposition according to the target frequency segment number and the preset decomposition layer number;
and calculating a frequency domain frequency band value corresponding to the target frequency range according to the target frequency difference.
In some embodiments of the present application, after the time-domain characteristic of the vibration signal is modified according to the rotational speed information of the rotating machine to obtain the purified axis center trajectory, the method includes:
obtaining a plurality of purified axis tracks of the vibration signal, and integrating the plurality of purified axis tracks;
synchronously averaging the purified axis locus after the synthesis, and purifying an average axis locus signal;
drawing a purified average axis track according to the average axis track signal;
and acquiring a target fault type of the rotor corresponding to the shape of the purified average axis track according to the incidence relation between the preset axis track shape and the fault type.
In some embodiments of the present application, the modifying the time domain characteristic of the vibration signal according to the rotational speed information of the rotating machine to obtain the purified axis center trajectory further includes:
decomposing the time domain characteristics of the vibration signal into a plurality of mode function components with time characteristic scales arranged from large to small by utilizing ensemble empirical mode decomposition;
selecting a corresponding inherent function component reconstruction signal from the inherent mode components according to the rotating speed information of the rotor;
and combining the inherent mode component reconstruction signals to obtain the purified axis locus of the rotor.
In another aspect, the present application provides a rotating machine axis track purification device, the device includes:
the acquisition module is used for acquiring a vibration signal of the rotor in the running process of the rotary machine;
the decomposition module is used for carrying out harmonic wavelet decomposition on the vibration signal to obtain the time domain characteristics of the vibration signal;
and the correction module is used for correcting the time domain characteristics of the vibration signals according to the rotating speed information of the rotor to obtain the purified axis locus of the rotor.
In another aspect, the present application provides a rotating machine axis track refining apparatus, including a memory and a processor; the memory stores an application program, and the processor is configured to run the application program in the memory to perform the operations of the rotating machine axis track refining method.
In another aspect, the present application provides a storage medium storing a plurality of instructions, where the instructions are suitable for being loaded by a processor to perform the steps of the rotating machine axis track refining method.
The embodiment of the invention carries out harmonic wavelet decomposition on the vibration signal obtained in the running process of the rotary machine to obtain the time domain characteristic of the vibration signal and eliminate the noise influence in the axis track signal; and correcting the time domain characteristics of the vibration signal according to the rotation speed information of the rotary machine, extracting the time domain characteristics of the vibration signal corresponding to the rotation speed information of the rotary machine from the time domain characteristics of the vibration signal, further filtering noise in the axis track signal, eliminating the interference of complex noise pollution and non-stationary components caused by the fault, accurately purifying the axis track of the rotating shaft, and simultaneously reducing the influence of frequency band bandwidth and amplitude constancy in harmonic wavelet decomposition on signal reconstruction.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a diagram illustrating an embodiment of a result of refining an axis trajectory only through harmonic wavelet decomposition according to an embodiment of the present disclosure;
FIG. 2 is a graph illustrating the results of an embodiment of a Vold-Kalman filtered axial trace refinement result provided by an embodiment of the present application;
fig. 3 is a schematic flowchart of an embodiment of a method for controlling an axial center trajectory according to the present application;
FIG. 4 is a schematic diagram of an embodiment of a purified axial trace provided in an embodiment of the present application;
FIG. 5 is a frequency spectrum diagram of a target time domain feature of a modified vibration signal provided by an embodiment of the present application;
fig. 6 is a schematic flowchart of an embodiment of a modified time domain feature in a method for purifying a rotating machine axis trajectory according to the present application;
fig. 7 is a schematic flowchart of another embodiment of a modified time domain feature in a method for purifying a rotating machine axis trajectory according to an embodiment of the present disclosure;
FIG. 8 is a time domain waveform of a vibration signal provided by an embodiment of the present application in the X direction;
FIG. 9 is a time domain waveform of a vibration signal provided by an embodiment of the present application in the Y direction;
FIG. 10 is an embodiment of a graph of the spectrum in the X direction provided by the embodiments of the present application;
fig. 11 is an embodiment of a spectrum graph in the Y direction according to the present invention;
fig. 12 is a schematic view of an application scenario of a rotating machine axis track purification method according to an embodiment of the present application;
FIG. 13 is an initial axial trace provided by an embodiment of the present application;
FIG. 14 is a schematic diagram of another embodiment of a purified axial trace provided in an embodiment of the present application;
FIG. 15 is a schematic diagram of another embodiment of a refined average axial trace provided in an example of the present application;
FIG. 16 is a schematic diagram illustrating the results of one embodiment of a rotating machine axis track refining apparatus according to the present application;
fig. 17 is a schematic flow chart of an embodiment of a rotating mechanical axis track refining apparatus according to an embodiment of the present disclosure.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the application considers that the vibration signal is only subjected to harmonic wavelet decomposition, the amplitude value in the frequency band of the reconstructed signal is constant, the amplitude outside the band is zero, therefore, the decomposed signal is often mixed with irrelevant components in the doped segment, as shown in fig. 1, fig. 1 is a result diagram of an embodiment of the axis locus purification result only subjected to harmonic wavelet decomposition provided by the embodiment of the present application, wherein (a) in FIG. 1 is a frequency-doubled axial trace only subjected to harmonic wavelet decomposition, and (b) in FIG. 1 is a horizontal vibration signal spectrum only subjected to harmonic wavelet decomposition, the graph (c) in figure 1 is a graph of the vertical vibration signal spectrum with only harmonic wavelet decomposition, it can be found that the frequency-doubling axis locus shown in the diagram (a) in fig. 1 is very disordered, which can prove that the wavelet packet is still insufficient for purification of the axis locus alone, and 50Hz interference components still exist in the result of conversion of the harmonic wavelet packet. Considering that the vibration signal is only subjected to Vold-Kalman filtering (chinese: freckman filtering), and is influenced by the bandwidth of the Vold-Kalman filter, so as to affect the removal of noise in the vibration signal, as shown in fig. 2, fig. 2 is a schematic diagram of the result of the purification result of the axial trace only subjected to Vold-Kalman filtering provided by the embodiment of the present application, wherein (a) in fig. 2 is a single axial trace only subjected to Vold-Kalman filtering, fig. 2 (b) is a spectrum diagram of a horizontal direction vibration signal only subjected to Vold-Kalman filtering, fig. 2 (c) is a spectrum diagram of a vertical direction vibration signal only subjected to Vold-Kalman filtering, the effect of the Vold-Kalman filtering directly used for purifying the axial trace is not ideal, the identified axial trace is blurred, and not only 50Hz electromagnetic interference can be found from the (b) diagram in fig. 2 and the (c) diagram in fig. 2, but also weak double frequency components. Therefore, the embodiment of the application combines the harmonic wavelet decomposition and the Vold-Kalman filtering, corrects the time domain characteristics after the harmonic wavelet decomposition by using the Vold-Kalman filtering, eliminates the complex noise pollution and the interference of non-stationary components caused by faults, accurately purifies the axis locus of the rotating shaft, and simultaneously reduces the influence of constant frequency band bandwidth and amplitude in the harmonic wavelet decomposition on signal reconstruction.
The embodiment of the invention provides a rotating machinery axis track purification method, a rotating machinery axis track purification device and a rotating machinery axis track purification storage medium.
In accordance with an embodiment of the present disclosure, there is provided a method for refining a rotating machine axis track, where the steps shown in the flowchart of the drawings are executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in an order different from that shown.
In some embodiments of the present application, the method for purifying a shaft center trajectory of a rotating machine provided in the embodiments of the present application is used for purifying a rotating shaft trajectory in a rotating machine. In some embodiments of the present application, rotary-type machines include, but are not limited to, generators, turbines, aircraft engines, water pumps, and blowers.
As shown in fig. 3, fig. 3 is a schematic flow chart of an embodiment of a method for controlling an axial center trajectory according to an embodiment of the present application. The method for purifying the axial track of the rotary machine provided by the embodiment of the present application takes the axial track purifying device as an execution main body for example, and for simplifying the description, the execution main body is omitted in the embodiment of the present application, and it can be understood that the execution main body of the following technical method is the axial track purifying device. In some embodiments of the present application, the axis track purification device is a cloud axis track purification device including, but not limited to, a computer, a mobile terminal, a network host, a single axis track purification device, multiple axis track purification device sets, or multiple axis track purification devices. Wherein the cloud axis track purification equipment is composed of a large number of computers based on cloud computing or cloud axis track purification equipment. As shown in FIG. 3, the illustrated axis trajectory control method includes steps 301 to 303:
The vibration signals are vibration signals perpendicular to each other on the same cross section of the rotor for a preset time, wherein the preset time may be 2 s. In some embodiments of the present application, the vibration signals perpendicular to each other on the same cross section may be transverse and longitudinal vibration signals perpendicular to each other on the same cross section; in some embodiments of the present application, the mutually perpendicular vibration signals on the same cross section may be mutually perpendicular transverse and axial vibration signals on the same cross section; in some embodiments of the present application, the mutually perpendicular vibration signals of the same cross section may be mutually perpendicular axial and longitudinal vibration signals of the same cross section.
And 302, performing harmonic wavelet decomposition on the vibration signal to obtain the time domain characteristics of the vibration signal.
The time domain feature is a time domain waveform of the vibration signal in the time domain.
In some embodiments of the present application, harmonic wavelet decomposition includes, but is not limited to, harmonic wavelet transforms, modified harmonic wavelet transforms, and windowed harmonic wavelet (packet) transforms.
The axis locus describes displacement changes in two directions perpendicular to each other on the same cross section of the inner rotor at the preset time, and for example, a vibration signal is a transverse vibration signal and a longitudinal vibration signal perpendicular to each other on the same cross section of the inner rotor at the preset time, the purified axis locus corresponding to the vibration signal is shown in fig. 4, fig. 4 is a schematic view of an embodiment of the purified axis locus provided by the embodiment of the present application, and fig. 4 (a) is a schematic view of an embodiment of the purified axis locus provided by the embodiment of the present application.
In some embodiments of the present application, the time domain characteristics of the vibration signal may be modified according to the rotational speed information of the rotor, so as to obtain target time domain characteristics matched with the rotational speed information, and the axis locus of the rotor after purification is obtained according to the target time domain characteristics, specifically, the method includes steps a 1-a 3:
step a1, obtaining information of the rotation speed of the rotor in the rotating machine.
In some embodiments of the present application, there are various manners of obtaining the rotation speed information of the rotor, which includes, for example:
(1) the rotational speed information of the rotor in the rotary machine can be acquired through a centrifugal tachometer.
(2) The rotating speed information of the rotor in the rotating machine can be acquired through the magnetic tachometer.
(3) The rotating speed information of the rotor in the rotating machinery can be acquired through the tachogenerator.
(4) The rotating speed information of the rotor in the rotating machinery can be acquired through the photoelectric tachometer.
(4) The rotating speed information of the rotor in the rotating machine can be acquired through an electronic digital tachometer.
(5) The rotation speed information of the rotor in the rotating machine can be collected through a flash velocimeter.
The above-described method for acquiring the rotational speed information of the rotor is merely an example, and does not limit the method for acquiring the rotational speed information in the method for presenting the axial center trajectory according to the embodiment of the present application.
Step a2, correcting the time domain characteristics of the vibration signal according to the rotation speed information to obtain target time domain characteristics matched with the rotation speed information.
The target time domain characteristic is a time domain waveform of the modified vibration signal indicating a change in amplitude of the modified vibration signal with time. In some embodiments of the present application, the target time-domain feature includes time-domain waveforms in two directions perpendicular to each other, and for example, the vibration signal is a transverse vibration signal and a longitudinal vibration signal perpendicular to each other on the same cross section of the rotor in a preset time, and the target time-domain feature includes a transverse time-domain waveform and a longitudinal time-domain waveform.
In some embodiments of the present application, the target time domain feature matched with the rotation speed information is a target time domain feature corresponding to the rotation speed information.
Step a3, obtaining the purified axis locus of the rotor according to the target time domain characteristics.
In some embodiments of the present application, the axis trajectory of the rotor after purification may be obtained through the amplitude in the target time domain feature, specifically, the amplitudes at the same time in two directions perpendicular to each other are obtained from the target time domain feature, and the displacement change of the rotor in the preset time period is obtained by using the amplitudes in the two directions. Illustratively, the vibration signal is a transverse vibration signal and a longitudinal vibration signal which are perpendicular to each other on the same cross section of the rotor within a preset time, as shown in fig. 5, fig. 5 is a spectrogram of a target time domain feature of a modified vibration signal provided in an embodiment of the present application, where fig. 5 (a) is a spectrogram of a target time domain feature of a modified horizontal direction vibration signal, and fig. 5 (b) is a spectrogram of a target time domain feature of a modified vertical direction vibration signal, and amplitudes at the same time of the transverse direction and the longitudinal direction are obtained from the spectrogram, so as to obtain displacement changes perpendicular to each other on the same cross section of the rotor within a preset time period.
In some embodiments of the present application, after obtaining the purified axial center trajectory of the rotor, the operation fault of the rotary machine may be identified according to the purified axial center trajectory of the rotor, and specifically, the method includes steps b 1-b 5:
step b1, obtaining a plurality of purified axis tracks of the vibration signal, and synthesizing the plurality of purified axis tracks.
In some embodiments of the present application, the vibration signal includes multiple time domain features, the step 103 obtains a plurality of purified axis tracks corresponding to the time domain features, and synthesizes the plurality of purified axis tracks, for example, obtaining 0.5 times of the purified axis tracks, 1 time of the purified axis tracks, 2 times of the purified axis tracks, and 4 times of the purified axis tracks in the vibration signal, and then synthesizing the 0.5 times of the purified axis tracks, 1 time of the purified axis tracks, 2 times of the purified axis tracks, and 4 times of the purified axis tracks.
And b2, synchronously averaging the integrated purified axis locus, and purifying an average axis locus signal.
The refined average axis track signal is the axis track of the refined axis track in the unit phase.
The phase synchronous averaging of the axis locus is synchronous averaging through the axis locus/a preset phase, and a purified average axis locus signal of the axis locus in a unit phase is obtained.
And b3, drawing a purified average axis locus according to the purified average axis locus signal.
Illustratively, as shown in fig. 4 (b), fig. 4 (b) is a schematic diagram of an embodiment of the purified average axial center trajectory provided in the embodiments of the present application.
Step b5, obtaining the target fault type of the rotor corresponding to the shape of the purified average axis track according to the incidence relation between the preset axis track shape and the fault type.
The fault types include, but are not limited to, rotor imbalance, rotor misalignment, oil whirl, and rotor friction.
The association relationship between the preset shaft center track shape and the fault type is used for indicating the corresponding relationship between the preset shaft center track shape and the fault type, illustratively, a vibration signal is a transverse vibration signal and a longitudinal vibration signal which are perpendicular to each other on the same cross section of a rotor in a preset time, the association relationship between the preset shaft center track shape and the fault type is shown in a table I, the table I is an embodiment of the association relationship between the preset shaft center track shape and the fault type provided by the embodiment of the application, and when the shape of the purified average shaft center track is an ellipse, the target fault type of the corresponding rotor is rotor imbalance; when the shape of the purified average axis locus is an external octagon, the corresponding target fault type of the rotor is that the rotor is not centered; when the shape of the purified average axis locus is a star shape, the target failure type of the corresponding rotor is rotor friction.
Association relation between form of axis trace and fault type
| Shape of axial trace | Type of failure |
| Oval shape | Rotor unbalance |
| External eight-shape | Misalignment of rotor |
| Star-shaped | Rotor friction |
| Inner eight shape | Oil film whirl |
It should be noted that the shape of the axial trace and the type of the fault shown in table one are merely exemplary, and in the embodiment of the present application, the type of the axial trace, the type of the fault, and the corresponding relationship between the shape of the axial trace and the type of the fault are not limited, and when the rotor is not centered, the shape of the axial trace may also be a banana shape.
The embodiment of the application removes the noise in the axis track signal.
Carrying out harmonic wavelet decomposition on the obtained vibration signal in the running process of the rotary machine to obtain the time domain characteristics of the vibration signal and eliminate the noise influence in the axis track signal; and correcting the time domain characteristics of the vibration signal according to the rotation speed information of the rotary machine, extracting the time domain characteristics of the vibration signal corresponding to the rotation speed information of the rotary machine from the time domain characteristics of the vibration signal, further filtering noise in the axis track signal, eliminating the interference of complex noise pollution and non-stationary components caused by the fault, accurately purifying the axis track of the rotating shaft, and simultaneously reducing the influence of frequency band bandwidth and amplitude constancy in harmonic wavelet decomposition on signal reconstruction.
In some embodiments of the present application, in order to further filter noise in the vibration signal and improve accuracy of the purified axis locus, in step a2, the time domain feature subjected to harmonic wavelet decomposition is corrected by using a filter to obtain the purified axis locus, specifically, as shown in fig. 6, fig. 6 is a schematic flow chart of an embodiment of correcting the time domain feature in the method for purifying the axis locus of the rotating machine provided in the embodiment of the present application, and the method for correcting the time domain feature includes steps 601 to 603:
The filter is used for filtering noise interference in time domain characteristics of harmonic wavelet decomposition.
In some embodiments of the present application, the filters include, but are not limited to, Vold-Kalman filters and adaptive Vold-Kalman filters. Illustratively, the filter is a Vold-Kalman filter, which includes a prediction signal corresponding to the rotation speed information constructed according to the rotation speed information and performs a comparison analysis with the actually measured vibration signal to minimize a difference between the prediction signal and the actually measured vibration signal, thereby extracting a time-domain feature corresponding to the rotation speed information from the actually measured vibration signal.
In some embodiments of the present application, the angular speed of the rotor may be obtained according to the rotation speed information, and the angular speed is input to the filter to obtain the predicted time domain characteristic corresponding to the rotation speed information of the rotor.
The error is a measurement error caused by non-stationary components contained in the time domain characteristics of the vibration signal.
In some embodiments of the present application, an error between the predicted time-domain feature and the time-domain feature of the vibration signal is analyzed by a filter, for example, the filter is a Vold-Kalman filter, the rotational speed information is input to the Vold-Kalman filter to obtain the predicted time-domain feature corresponding to the rotational speed information of the rotor, and the square sum of the non-coincident terms in the predicted time-domain feature is calculated; and predicting the square sum of the measurement error between the time domain characteristic and the vibration signal through calculation of a Vold-Kalman filter, and taking the sum of the square sum of the non-uniform terms and the square sum of the measurement error as an error.
In some embodiments of the present application, the error is minimized by a least square method, so as to modify the time domain feature of the vibration signal, and obtain a target time domain feature matched with the rotation speed information.
In some embodiments of the present application, in order to further filter noise in the vibration signal and improve the accuracy of the purified axial center trajectory, in step 203, the time domain characteristic of the vibration signal may be modified based on an empirical mode decomposition method to obtain the purified axial center trajectory of the rotor. Specifically, as shown in fig. 7, fig. 7 is a schematic flow chart of another embodiment of correcting a time domain feature in the method for purifying a rotating machine axis track provided in the embodiment of the present application, where the method for correcting the time domain feature includes steps 701 to 703:
In some embodiments of the present application, the time domain features of the transverse and longitudinal vibration signals perpendicular to each other on the same cross section of the rotor are subjected to ensemble empirical mode decomposition, respectively. For example, the transverse vibration signal x (t) is taken as an example for explanation, and the decomposition method specifically comprises the steps c 1-c 5:
step c1, adding white Gaussian noise N with average value of 0 and standard deviation of amplitude constant into the vibration signal x (t) after harmonic wavelet decompositioni(t) obtaining a signal x after adding white Gaussian noisei(t)。
Step c2, by
For xi(t) performing ensemble empirical mode decomposition to obtain M eigen mode function components
And a remainder
。
Step c3, using the principle that the statistical mean of uncorrelated random sequences is 0, by
Component of eigenmode function
Performing a global averaging operation by
Will remain
Performing overall average operation to eliminate the influence of multiple times of Gaussian random white noise on the real vibration signal and obtain the inherent function component c after the ensemble empirical mode decompositionj(t) and remainder rj(t)。
Step c4, by
And obtaining the intrinsic function components of the M characteristic time scales which are orderly arranged from large to small.
Step c5, low pass filtering, high pass filtering and/or band pass filtering the eigenmode function component.
In some embodiments of the present application, the decomposition method of the longitudinal vibration signal y (t) is the same as the decomposition method of the transverse vibration signal x (t), and is not described herein again.
And step 702, selecting a corresponding inherent function component reconstruction signal from the inherent mode components according to the rotation speed information of the rotor.
And 703, combining the inherent mode component reconstruction signals to obtain the purified axis locus of the rotor.
In some embodiments of the present application, in step 302, a fourier transform is performed on the vibration signal to obtain a frequency domain feature corresponding to the vibration signal, and a parameter of harmonic wavelet decomposition is set according to the frequency domain feature to perform a wavelet transform on the frequency domain feature, which specifically includes steps d 1-d 4:
and d1, performing Fourier transform on the vibration signal to obtain frequency domain characteristics corresponding to the vibration signal.
In some embodiments of the present application the fourier transform is a fast fourier transform.
In some embodiments of the present application, the frequency domain features include frequency values and frequency spectra of the vibration signal.
In some embodiments of the present application, mutually perpendicular vibration signals are collected on the same cross section of the rotor
，
(ii) a Wherein L is the length of the acquired data and is an integer greater than 2, and Fourier transform is respectively carried out on the acquired vibration signals X and Y to obtain frequency values
And
wherein
Is the angular arc of the vibration signal; and obtaining a spectrogram of the vibration signal in the X direction and a spectrogram of the vibration signal in the Y direction. Exemplarily, a sampling frequency is 2000Hz, a data length is L =4000, and a rotation speed of a rotor is 3348 rpm/min, as shown in fig. 8 and 9, fig. 8 is a time domain waveform of a vibration signal in an X direction provided by an embodiment of the present application, and fig. 9 is a time domain waveform of a vibration signal provided by an embodiment of the present applicationTime domain waveform of the vibration signal Y direction; as shown in fig. 10 and 11, fig. 10 is an embodiment of a frequency spectrum diagram in the X direction provided in the embodiment of the present application, and fig. 11 is an embodiment of a frequency spectrum diagram in the Y direction provided in the embodiment of the present application.
And d2, calculating frequency domain frequency band values through the frequency domain characteristics.
In some embodiments of the present application, a frequency domain band value may be calculated by combining the rotation speed information of the rotor with the frequency domain characteristics, and specifically, the method for calculating the frequency domain band value includes steps f 1-f 7:
and f1, obtaining the rotation speed information of the rotor in the rotary machine.
And f2, determining the target fundamental frequency from the frequency domain characteristics according to the rotation speed information.
In some embodiments of the present application, the target fundamental frequency includes a 0.5 octave, a first octave, and a second octave.
In some embodiments of the present application, a target fundamental frequency is determined from a spectrogram according to rotation speed information, for example, by taking a sampling frequency of 2000Hz, a data length of L =4000, and a rotation speed of a rotor of 3348 rpm as an example, it can be found through analysis of the spectrogram that a rotor of the rotating machine has poor centering effect, and meanwhile, the rotor of the rotating machine is also interfered by an alternating current of 50Hz, so that a first frequency multiplication and a second frequency multiplication of the target fundamental frequency are determined.
And f3, acquiring a target frequency range corresponding to the target fundamental frequency.
Illustratively, taking the example that the sampling frequency is 2000Hz, the data length is L =4000, and the rotation speed of the rotor is 3348 rpm, the target frequency range includes a frequency range of one frequency multiplication and a frequency range of two frequency multiplication.
And f4, acquiring the preset decomposition layer number of the harmonic wavelet decomposition.
In some embodiments of the present application, the predetermined number of decomposition layers satisfies 5 ≦ 8.
And f5, performing integer-zero-taking operation according to the preset decomposition layer number and the target frequency range to obtain the target frequency segment number of the target frequency range.
In some embodiments of the present application, an integer operation is performed toward zero by presetting the number of decomposition layers and the center frequency of a target frequency range, so as to obtain the number of target frequency segments of the target frequency range. Illustratively, taking the target fundamental frequency as a frequency doubling as an example, when the sampling frequency is 2000Hz, the data length is L =4000, and the rotation speed of the rotor is 3348 rpm, the center frequency f of the target frequency range is 55.8Hz, the nyquist frequency fs of the vibration signal is calculated by using the nyquist frequency = sampling frequency/2, the preset number j of decomposition layers is obtained, and the target fundamental frequency is obtained by multiplying the target fundamental frequency by the nyquist frequency
Performing remainder operation to determine
Whether or not it is equal to 0; if it is not
Equal to 0, then pass
Carrying out zero integer taking operation and calculating the number k of target frequency segments; if it is not
Not equal to 0, pass k = cell ((2)j*f)/fs) And performing an integer-taking-to-zero operation, and calculating the target frequency segment number k, wherein the cell (.) is the integer-taking-to-zero operation. For example, when the sampling frequency is 2000Hz, the number of preset decomposition layers is 6, and the center frequency f of the target frequency range is 55.8Hz, the calculation is performed
Is not equal to 0 by
And calculating to obtain the target frequency segment number k of 3.
And f6, calculating the target frequency difference of the harmonic wavelet decomposition according to the target frequency band number and the preset decomposition layer number.
In some embodiments of the present application, the upper and lower limits of the harmonic wavelet decomposition are calculated by a target number of bands and a preset number of decomposition layers, and the target frequency difference of the harmonic wavelet decomposition is obtained by calculating a difference between the upper and lower limits of the harmonic wavelet decomposition. In particular, by calculating the upper limit m of the harmonic wavelet decompositionkBy passing
Calculating the lower limit n of harmonic wavelet decompositionkBy passing
The target frequency difference of the harmonic wavelet decomposition is obtained. Illustratively, the sample frequency is 2000Hz, the preset number of decomposition layers is 6, the target frequency band number k is 3, and the center frequency f of the target frequency range is 55.8Hz
Calculating the upper limit m of harmonic wavelet decompositionkIs 64.5, by
Calculating the lower limit n of harmonic wavelet decompositionk46.875.
And f7, calculating the frequency domain frequency band value corresponding to the target frequency range according to the target frequency difference.
In some embodiments of the present application, an angular radian of the vibration signal is determined according to the rotational speed information of the rotor, and a frequency domain band value corresponding to the target frequency range is calculated according to a range of the angular radian and the target frequency difference. In particular, the rotational speed information of the rotor determines the angular curvature of the vibration signal
(ii) a Determining the angular arc
A range of (d); if it is not
Satisfy the requirement of
Then pass through
Calculating the frequency domain frequency band value corresponding to the target frequency range
(ii) a If it is not
Satisfy the requirement of
Or
Then, the frequency domain frequency band value corresponding to the target frequency range is calculated
Is set to 0.
And d3, carrying out harmonic wavelet decomposition according to the frequency domain characteristics and the frequency domain frequency band values.
In some embodiments of the present application, harmonic wavelet decomposition is performed based on frequency values in frequency domain features and frequency domain band values, in particular, by
And
are respectively paired
And
and performing harmonic wavelet decomposition to obtain the frequency domain characteristics after the harmonic wavelet decomposition, wherein i =1,2, … and L. Exemplarily, the sampling frequency is 2000Hz, the data length is L =4000, and the rotation speed of the rotor is 3348 rpmTo illustrate, as shown in fig. 1 (b) and fig. 1 (c), fig. 1 (b) is an embodiment of a frequency domain feature spectrogram of an X-direction vibration signal subjected to harmonic wavelet decomposition according to an embodiment of the present application, and fig. 1 (c) is an embodiment of a frequency domain feature spectrogram of a Y-direction vibration signal subjected to harmonic wavelet decomposition according to an embodiment of the present application.
And d4, performing inverse Fourier transform on the frequency domain characteristics after the harmonic wavelet decomposition to obtain the time domain characteristics of the vibration signals.
In the embodiment of the application, the parameters of harmonic wavelet decomposition are set through the frequency domain characteristics, the frequency domain characteristics are subjected to wavelet transformation, noise in a vibration signal is removed, a good data base is corrected for subsequent time domain characteristics, the noise in the vibration signal is removed through the harmonic wavelet decomposition, and the influence of the bandwidth of a filter on a correction result in the subsequent time domain characteristic correction is reduced.
In some embodiments of the present application, to better describe the method for purifying the axial center trajectory of the rotary machine provided in the embodiment of the present application, for example, an application scenario of the axial center trajectory purification is provided by taking the sampling frequency as 2000Hz, the data length as L =4000, and the rotation speed of the rotor as 3348 rpm as an example, as shown in fig. 12, fig. 12 is an application scenario schematic diagram of the method for purifying the axial center trajectory of the rotary machine provided in the embodiment of the present application, and the method for purifying the axial center trajectory of the rotary machine shown in the embodiment of the present application includes steps e1 to e 9:
step e1, inputting vibration signals perpendicular to each other, as shown in fig. 13, where fig. 13 is an initial axial trace provided by the embodiment of the present application.
And e2, obtaining a spectrogram of the vibration signal through fast Fourier transform.
Step e3, determining a target frequency range according to the spectrogram of the vibration signal.
And e4, acquiring the number of the harmonic wavelet decomposition layers and the number of the target frequency bands.
And e5, calculating frequency domain frequency band values.
And e6, performing harmonic wavelet decomposition, and performing inverse Fourier transform on the decomposed frequency domain characteristics to obtain time domain characteristics.
Step e7, performing Vold-Kalman filtering correction on the time-domain features to obtain a purified axis trajectory, as shown in fig. 4 (a) and fig. 14, where fig. 14 is another embodiment of the purified axis trajectory provided in this application.
And e8, performing time synchronization averaging on the purified axis locus to obtain an average axis locus signal.
Step e9, drawing the refined average axial center trajectory according to the average axial center trajectory signal, as shown in fig. 4 (b) and fig. 15, where fig. 15 is a schematic view of another embodiment of the refined average axial center trajectory provided in this embodiment of the present application.
The embodiment of the application considers that the vibration signal is only subjected to harmonic wavelet decomposition, the amplitude in the frequency band of the reconstructed signal is constant, and the outside of the band is zero, so that the decomposed signal is often mixed with irrelevant components in the doped band, the vibration signal is only subjected to Vold-Kalman filtering and is influenced by the bandwidth of a Vold-Kalman filter, the removal of noise in the vibration signal is influenced, the harmonic wavelet decomposition and the Vold-Kalman filtering are combined, the time domain characteristic subjected to the harmonic wavelet decomposition is corrected by the Vold-Kalman filtering, the interference of complex noise pollution and non-stationary components caused by faults is eliminated, the axis locus of a rotating shaft is accurately purified, and the influence of the bandwidth and the amplitude constancy of the frequency band in the harmonic wavelet decomposition on the signal reconstruction is reduced.
In order to better implement the method for purifying a shaft center trajectory of a rotary machine provided in the embodiment of the present application, on the basis of the method for purifying a shaft center trajectory of a rotary machine, an embodiment of the present application further provides a device for purifying a shaft center trajectory of a rotary machine, as shown in fig. 16, where fig. 16 is a schematic diagram of a result of an embodiment of the device for purifying a shaft center trajectory of a rotary machine provided in the embodiment of the present application, and the device for purifying a shaft center trajectory of a rotary machine shown in the embodiment of the present application includes:
the obtaining module 1601 is used for obtaining a vibration signal of a rotor in the operation process of the rotary machine;
a decomposition module 1602, configured to perform harmonic wavelet decomposition on the vibration signal to obtain a time domain characteristic of the vibration signal;
a correcting module 1603, configured to correct the time domain characteristic of the vibration signal according to the rotation speed information of the rotor, so as to obtain an axis track of the rotor after purification.
In some embodiments of the present application, the modification module 1603 includes:
a rotation speed unit for acquiring rotation speed information of the rotor in a rotary machine;
and the correcting unit is used for correcting the time domain characteristics of the vibration signals according to the rotating speed information of the rotor in the rotary machine to obtain target time domain characteristics matched with the rotating speed information of the rotor in the rotary machine.
And the track unit is used for obtaining the purified axis track of the rotor according to the target time domain characteristics.
In some embodiments of the present application, the modifying unit is configured to input the rotational speed information of the rotor in the rotary machine into a preset filter, so as to obtain a predicted time domain characteristic corresponding to the rotational speed information of the rotor in the rotary machine; comparing and analyzing the predicted time domain characteristic and the time domain characteristic of the vibration signal through the filter to obtain an error between the predicted time domain characteristic and the time domain characteristic of the vibration signal; and minimizing the error through a least square method, and correcting the time domain characteristics of the vibration signal to obtain target time domain characteristics matched with the rotating speed information of the rotor in the rotary machine.
In some embodiments of the present application, the decomposition module 1602 includes:
the transformation unit is used for carrying out Fourier transformation on the vibration signal to obtain frequency domain characteristics corresponding to the vibration signal;
a calculating unit, configured to calculate frequency domain band values through the frequency domain features;
the decomposition unit is used for carrying out harmonic wavelet decomposition according to the frequency domain characteristics and the frequency domain frequency band values;
and the transforming unit is used for performing inverse Fourier transform on the frequency domain characteristics subjected to the harmonic wavelet decomposition to obtain the time domain characteristics of the vibration signals.
In some embodiments of the present application, the calculating unit is further configured to obtain information of a rotational speed of the rotor in the rotary machine to obtain information of the rotational speed of the rotor in the rotary machine; determining a target fundamental frequency from the frequency domain characteristics according to the rotation speed information of a rotor in the rotary machine; acquiring a target frequency range corresponding to the target fundamental frequency; acquiring a preset decomposition layer number of harmonic wavelet decomposition; according to the preset decomposition layer number and the target frequency range, carrying out integer zero-taking operation to obtain the target frequency segment number of the target frequency range; calculating a target frequency difference of harmonic wavelet decomposition according to the target frequency segment number and the preset decomposition layer number; and calculating a frequency domain frequency band value corresponding to the target frequency range according to the target frequency difference.
In some embodiments of the present application, the apparatus for purifying axial center trajectory of rotary machine further includes an output module 1604, where the output module is configured to obtain a plurality of purified axial center trajectories of the vibration signal, and synthesize the plurality of purified axial center trajectories; synchronously averaging the purified axis locus after the synthesis, and purifying an average axis locus signal; drawing a purified average axis track according to the average axis track signal; and acquiring a target fault type of the rotor corresponding to the shape of the purified average axis track according to the incidence relation between the preset axis track shape and the fault type.
In some embodiments of the present application, the modifying module 1603 is further configured to decompose the time domain feature of the vibration signal into a plurality of mode function components with time feature scales arranged from large to small by using ensemble empirical mode decomposition; selecting corresponding inherent function component reconstruction signals from the inherent mode components according to the rotating speed information of the rotor; and combining the inherent mode component reconstruction signals to obtain the purified axis locus of the rotor.
The method and the device have the advantages that harmonic wavelet decomposition is carried out on the obtained vibration signals in the running process of the rotary machine, so that the time domain characteristics of the vibration signals are obtained, and the noise influence in the axis track signals is eliminated; and correcting the time domain characteristics of the vibration signal according to the rotation speed information of the rotary machine, extracting the time domain characteristics of the vibration signal corresponding to the rotation speed information of the rotary machine from the time domain characteristics of the vibration signal, further filtering noise in the axis track signal, eliminating the interference of complex noise pollution and non-stationary components caused by the fault, accurately purifying the axis track of the rotating shaft, and simultaneously reducing the influence of frequency band bandwidth and amplitude constancy in harmonic wavelet decomposition on signal reconstruction.
An embodiment of the present application further provides a rotating machine axis track purification apparatus, as shown in fig. 17, fig. 17 is a schematic flow diagram of an embodiment of the rotating machine axis track purification apparatus provided in the embodiment of the present application.
Rotating machinery axle center orbit purification equipment has integrateed any kind of rotating machinery axle center orbit purification device that this application embodiment provided, and shown rotating machinery axle center orbit purification equipment includes:
comprising a memory and a processor; the memory stores an application program, and the processor is configured to run the application program in the memory to perform the steps in any embodiment of the method for purifying a shaft center trajectory of a rotating machine to purify the shaft center trajectory.
The rotating machine axis track refining apparatus may include components such as a processor 1701 with one or more processing cores, memory 1702 with one or more computer-readable storage media, power supply 1703, and input unit 1704. Those skilled in the art will appreciate that the configuration of the rotating machine axis track refining apparatus shown in fig. 17 is not intended to be limiting and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components. Wherein:
the processor 1701 is a control center of the apparatus for refining the axial center trajectory of the rotating machine, and connects various parts of the entire apparatus for refining the axial center trajectory of the rotating machine by using various interfaces and lines, and executes various functions and processing data of the apparatus for refining the axial center trajectory of the rotating machine by operating or executing software programs and/or modules stored in the memory 1702 and calling data stored in the memory 1702, thereby performing overall monitoring of the apparatus for refining the axial center trajectory of the rotating machine. Optionally, the processor 1701 may include one or more processing cores; preferably, the processor 1701 may integrate an application processor, which mainly handles operating systems, user interfaces, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 1701.
The memory 1702 may be used to store software programs and modules, and the processor 1701 executes various functional applications and data processing by executing the software programs and modules stored in the memory 1702. The memory 1702 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data created from use of the rotating machine axis locus refining device, and the like. Additionally, the memory 1702 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device. Accordingly, the memory 1702 may also include a memory controller to provide the processor 1701 access to the memory 1702.
The apparatus for purifying the axial track of the rotating machine further comprises a power supply 1703 for supplying power to each component, preferably, the power supply 1703 may be logically connected to the processor 1701 through a power management system, so as to implement functions of managing charging, discharging, power consumption, and the like through the power management system. The power supply 1703 may also include one or more dc or ac power sources, recharging systems, power failure detection circuitry, power converters or inverters, power status indicators, and any other components.
The apparatus may further comprise an input unit 1704, the input unit 1704 may be configured to receive input numeric or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs associated with user settings and function controls.
Although not shown, the rotating machine axis track purification apparatus may further include a display unit and the like, which are not described herein again. Specifically, in this embodiment, the processor 1701 in the apparatus for refining a shaft center trajectory of a rotating machine loads an executable file corresponding to a process of one or more applications into the memory 1702 according to the following instructions, and the processor 1701 runs the applications stored in the memory 1702, thereby implementing various functions as follows:
acquiring a vibration signal of a rotor in the running process of a rotary machine;
carrying out harmonic wavelet decomposition on the vibration signal to obtain the time domain characteristics of the vibration signal;
and correcting the time domain characteristics of the vibration signal according to the rotation speed information of the rotor to obtain the purified axis locus of the rotor.
It will be understood by those skilled in the art that all or part of the steps of the methods of the above embodiments may be performed by instructions or by associated hardware controlled by the instructions, which may be stored in a computer readable storage medium and loaded and executed by a processor.
To this end, an embodiment of the present application further provides a storage medium, where the storage medium is a computer-readable storage medium, and the storage medium stores a plurality of instructions, where the instructions are suitable for being loaded by a processor to perform steps in any method for refining a shaft center trajectory of a rotating machine provided in an embodiment of the present application. For example, the instructions may perform the steps of:
acquiring a vibration signal of a rotor in the running process of a rotary machine;
carrying out harmonic wavelet decomposition on the vibration signal to obtain the time domain characteristics of the vibration signal;
and correcting the time domain characteristics of the vibration signal according to the rotation speed information of the rotor to obtain the purified axis locus of the rotor.
The above operations can be implemented in the foregoing embodiments, and are not described in detail herein.
Wherein the storage medium may include: a Read Only Memory (ROM, Chinese: Read Only Memory), a Random Access Memory (RAM, Random Access Memory, Chinese: Random Access Memory), a magnetic or optical disk, and the like.
Since the instructions stored in the storage medium may execute the steps in any of the rotating machine axis trajectory purification methods provided in the embodiments of the present invention, beneficial effects that can be achieved by any of the rotating machine axis trajectory purification methods provided in the embodiments of the present invention may be achieved, which are detailed in the foregoing embodiments and will not be described herein again.
The method, the apparatus, the device and the storage medium for purifying the axial locus of the rotating machine provided by the embodiment of the present invention are described in detail above, and a specific example is applied in the present disclosure to explain the principle and the implementation of the present invention, and the description of the above embodiment is only used to help understanding the method and the core idea of the present invention; meanwhile, for those skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. A method for purifying a shaft center track of a rotating machine is characterized by comprising the following steps:
acquiring a vibration signal of a rotor in the running process of a rotary machine;
carrying out harmonic wavelet decomposition on the vibration signal to obtain the time domain characteristics of the vibration signal;
and according to the rotating speed information of the rotor, obtaining a predicted time domain characteristic corresponding to the time domain characteristic of the vibration signal through a preset filter, and correcting the time domain characteristic by minimizing the error between the predicted time domain characteristic and the time domain characteristic through a least square method to obtain the purified axis locus of the rotor.
2. The method for purifying the axial center trajectory of the rotating machine according to claim 1, wherein the step of obtaining the purified axial center trajectory of the rotor by obtaining the predicted time domain characteristic corresponding to the time domain characteristic of the vibration signal through a preset filter according to the rotation speed information of the rotor and minimizing an error between the predicted time domain characteristic and the time domain characteristic by a least square method to correct the time domain characteristic comprises the steps of:
acquiring rotating speed information of the rotor in the rotating machine;
according to the rotating speed information, obtaining a predicted time domain characteristic corresponding to the rotating speed information of the rotor through a preset filter;
acquiring an error between the predicted time domain feature and the time domain feature, and correcting the time domain feature by minimizing the error through a least square method to obtain a target time domain feature matched with the rotating speed information;
and obtaining the purified axis locus of the rotor according to the target time domain characteristics.
3. The method for purifying the axial center trajectory of the rotating machine according to claim 2, wherein the obtaining of the error between the predicted time-domain feature and the time-domain feature, and the correcting of the time-domain feature by minimizing the error through a least square method to obtain the target time-domain feature matched with the rotating speed information comprises:
comparing and analyzing the predicted time domain feature and the time domain feature through the filter to obtain an error between the predicted time domain feature and the time domain feature;
and minimizing the error through a least square method, and correcting the time domain characteristics to obtain target time domain characteristics matched with the rotating speed information.
4. The method for purifying the axial center trajectory of the rotating machine according to claim 1, wherein the performing harmonic wavelet decomposition on the vibration signal to obtain the time domain feature of the vibration signal comprises:
carrying out Fourier transform on the vibration signal to obtain frequency domain characteristics corresponding to the vibration signal;
calculating frequency domain band values through the frequency domain features;
carrying out harmonic wavelet decomposition according to the frequency domain characteristics and the frequency domain frequency band values;
and carrying out inverse Fourier transform on the frequency domain characteristics subjected to harmonic wavelet decomposition to obtain the time domain characteristics of the vibration signals.
5. The method of claim 4, wherein the calculating frequency domain band values from the frequency domain features comprises:
acquiring rotating speed information of the rotor in the rotating machine;
determining a target fundamental frequency from the frequency domain features according to the rotation speed information;
acquiring a target frequency range corresponding to the target fundamental frequency;
acquiring a preset decomposition layer number of harmonic wavelet decomposition;
according to the preset decomposition layer number and the target frequency range, carrying out integer zero-taking operation to obtain the target frequency segment number of the target frequency range;
calculating a target frequency difference of harmonic wavelet decomposition according to the target frequency segment number and the preset decomposition layer number;
and calculating a frequency domain frequency band value corresponding to the target frequency range according to the target frequency difference.
6. The method according to any one of claims 1 to 5, wherein the method comprises, after obtaining the purified axial center trajectory, obtaining a preset time domain feature corresponding to the time domain feature of the vibration signal by a preset filter according to the rotational speed information of the rotary machine, and correcting the time domain feature by minimizing an error between the preset time domain feature and the time domain feature by a least square method, the method comprises:
obtaining a plurality of purified axis tracks of the vibration signal, and integrating the plurality of purified axis tracks;
synchronously averaging the purified axis locus after the synthesis, and purifying an average axis locus signal;
drawing a purified average axis track according to the average axis track signal;
and acquiring a target fault type of the rotor corresponding to the shape of the purified average axis track according to the incidence relation between the preset axis track shape and the fault type.
7. The method for purifying the axial center trajectory of the rotary machine according to claim 1, wherein before the step of obtaining the purified axial center trajectory, the method further comprises the steps of obtaining a predicted time domain characteristic corresponding to the time domain characteristic of the vibration signal through a preset filter according to the rotational speed information of the rotary machine, and correcting the time domain characteristic by minimizing an error between the predicted time domain characteristic and the time domain characteristic through a least square method:
decomposing the time domain characteristics of the vibration signal into a plurality of mode function components with time characteristic scales arranged from large to small by utilizing ensemble empirical mode decomposition;
selecting a corresponding inherent function component reconstruction signal from the inherent mode components according to the rotating speed information of the rotor;
and combining the inherent mode component reconstruction signals to obtain the purified axis locus of the rotor.
8. A rotating machinery axis track purification device is characterized in that the device comprises:
the acquisition module is used for acquiring a vibration signal of the rotor in the running process of the rotary machine;
the decomposition module is used for carrying out harmonic wavelet decomposition on the vibration signal to obtain the time domain characteristics of the vibration signal;
and the correction module is used for obtaining a predicted time domain characteristic corresponding to the time domain characteristic of the vibration signal through a preset filter according to the rotating speed information of the rotor, and correcting the time domain characteristic by minimizing the error between the predicted time domain characteristic and the time domain characteristic through a least square method to obtain the purified axis locus of the rotor.
9. The equipment for purifying the axis track of the rotating machinery is characterized by comprising a memory and a processor; the memory stores an application program, and the processor is configured to execute the application program in the memory to perform the operations of the rotating machine axis track refining method according to any one of claims 1 to 7.
10. A storage medium storing instructions adapted to be loaded by a processor to perform the steps of the method of refining a rotating machine axis trajectory according to any one of claims 1 to 7.
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