CN115031959A - Gear fault diagnosis method and system and computer readable storage medium - Google Patents
Gear fault diagnosis method and system and computer readable storage medium Download PDFInfo
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- CN115031959A CN115031959A CN202210590574.3A CN202210590574A CN115031959A CN 115031959 A CN115031959 A CN 115031959A CN 202210590574 A CN202210590574 A CN 202210590574A CN 115031959 A CN115031959 A CN 115031959A
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- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M13/00—Testing of machine parts
- G01M13/02—Gearings; Transmission mechanisms
- G01M13/021—Gearings
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- G—PHYSICS
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- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
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Abstract
The embodiment of the application provides a gear fault diagnosis method, a gear fault diagnosis system and a computer readable storage medium, wherein the gear fault diagnosis method comprises the following steps: acquiring a vibration signal of the gear; processing the vibration signal of the gear by using a time domain synchronous average algorithm to obtain a time domain synchronous average signal of the gear; determining a conventional vibration signal of the gear according to the time domain synchronous average signal; and determining a health signal of the gear according to the time domain synchronous average signal and the conventional vibration signal, wherein the health signal comprises a differential signal and a residual signal. The gear fault diagnosis method is simple, convenient and quick to calculate and has high reliability.
Description
Technical Field
The embodiment of the application relates to the field of mechanical transmission, in particular to a gear fault diagnosis method and system and a computer readable storage medium.
Background
With the gradual depletion of energy sources such as coal and petroleum, human beings increasingly pay more attention to the utilization of renewable energy sources. Wind energy is increasingly gaining attention as a clean renewable energy source in all countries of the world. With the continuous development of wind power technology, the application of wind generating sets in power systems is increasing day by day. Wind generating sets are large-scale devices that convert wind energy into electrical energy, and are usually installed in areas with abundant wind energy resources.
The existing wind generating set is installed at wind gaps of mountains, wildlands, beaches, islands and the like, is impacted by irregular wind power changing direction and load and strong gusts, is influenced by severe summer and cold and extreme temperature difference all the year round, and each part of the wind generating set is easy to break down. The gear boxes are important components of the wind driven generator, a plurality of gear boxes are applied to the wind driven generator, the main function of the gear boxes is to transmit power generated by a wind wheel under the action of wind power to the generator and enable the generator to obtain corresponding rotating speed, and when a gear in the gear boxes breaks down, the gear in the gear boxes is often difficult to find when the fault occurs due to the fact that the gear is installed in a main machine, and serious consequences are easy to cause.
Disclosure of Invention
The embodiment of the application aims to provide a gear fault diagnosis method, a gear fault diagnosis system and a computer readable storage medium, which are simple, convenient and quick to calculate and have high reliability.
One aspect of an embodiment of the present application provides a gear fault diagnosis method, including:
acquiring a vibration signal of the gear;
processing the vibration signal of the gear by using a time domain synchronous average algorithm to obtain a time domain synchronous average signal of the gear;
determining a conventional vibration signal of the gear according to the time domain synchronous average signal;
determining a health signal of the gear according to the time domain synchronous average signal and the conventional vibration signal, wherein the health signal comprises at least one of a differential signal and a residual signal;
and carrying out fault diagnosis on the gear according to the health condition signal.
Optionally, the processing the vibration signal of the gear by using a time domain synchronous averaging algorithm to obtain a time domain synchronous averaged signal of the gear includes:
determining a cutting period according to the rotating speed of the gear;
segmenting the vibration signal according to the segmentation period to obtain a plurality of segments of sub-vibration signals;
and processing the multi-segment sub-vibration signals by utilizing a time domain synchronous average algorithm to obtain time domain synchronous average signals of the gear.
Optionally, the processing the vibration signal of the gear by using a time domain synchronous averaging algorithm to obtain a time domain synchronous averaged signal of the gear includes:
carrying out cubic spline fitting interpolation processing on the vibration signal of the gear to obtain a smooth vibration signal;
based on an order tracking theory, performing time domain to angle domain conversion on the smooth vibration signal to obtain an order tracking signal;
and processing the order tracking signal by utilizing the time domain synchronous averaging algorithm to obtain a time domain synchronous averaging signal of the gear.
Optionally, performing fourier transform on the time domain synchronous average signal to obtain a time domain synchronous average signal frequency spectrum;
determining a gear meshing vibration signal and a gear shaft rotating vibration signal of the gear according to the time domain synchronous average signal frequency spectrum;
and determining a conventional vibration signal of the gear according to the gear meshing vibration signal and the gear shaft rotation vibration signal.
Optionally, the determining the gear meshing vibration signal and the gear shaft rotating vibration signal of the gear according to the time domain synchronous average signal frequency spectrum includes:
determining the gear meshing frequency, the gear meshing amplitude and the gear meshing phase of the gear, and the gear shaft rotation frequency, the gear shaft rotation amplitude and the gear shaft rotation phase of the gear according to the time domain synchronous average signal frequency spectrum;
carrying out inverse Fourier transform on the gear meshing frequency, the gear meshing amplitude and the gear meshing phase to obtain a gear meshing vibration signal of the gear;
and carrying out Fourier inverse transformation on the gear shaft rotation frequency, the gear shaft rotation amplitude and the gear shaft rotation phase to obtain a gear shaft rotation vibration signal of the gear.
Optionally, the determining the gear meshing frequency, the gear meshing amplitude and the gear meshing phase of the gear and the gear shaft rotation frequency, the gear shaft rotation amplitude and the gear shaft rotation phase of the gear according to the time domain synchronous average signal frequency spectrum includes:
and determining the gear meshing frequency of the gear and the gear shaft rotation frequency of the gear by using a maximum amplitude method according to the time domain synchronous average signal frequency spectrum.
Optionally, the determining a conventional vibration signal of the gear according to the gear meshing vibration signal and the gear shaft rotation vibration signal includes:
performing trigonometric function transformation according to the gear meshing vibration signal and the time domain synchronous average signal frequency spectrum to obtain a gear meshing modulation vibration signal of the gear;
and determining a conventional vibration signal of the gear according to the gear meshing vibration signal, the gear shaft rotation vibration signal and the gear meshing modulation vibration signal.
Optionally, the diagnosing the fault of the gear according to the health status signal includes:
obtaining a signal characteristic value according to the health condition signal, wherein the signal characteristic value comprises a root mean square value, an energy ratio and a kurtosis; and if the signal characteristic value is larger than a fault threshold value, determining that the gear is in fault, and giving an alarm.
Another aspect of the embodiments of the present application provides a gear fault diagnosis system: one or more processors are included for implementing the above-described gear failure diagnostic method.
Yet another aspect of embodiments of the present application also provides a computer-readable storage medium. The computer-readable storage medium has stored thereon a program which, when executed by a processor, implements the gear failure diagnosis method as described above.
According to the gear fault monitoring method, the gear fault is monitored by monitoring the health condition signal of the gear, the health condition signal comprises at least one of a residual signal and a differential signal, the fault degree of a transmission gear is reflected, and the accuracy is high; when the health condition signal is determined, the gear fault monitoring method uses a time domain synchronous averaging technology, obtains the conventional vibration signal capable of accurately expressing the normal vibration condition of the gear according to the time domain synchronous averaging signal, and determines the health condition signal of the gear according to the time domain synchronous averaging signal and the conventional vibration signal, so that the health condition signal in the vibration signal of the gear is rapidly extracted, the method is simple, convenient and rapid, has high reliability, and the fault monitoring is more accurate.
Drawings
FIG. 1 is a flow chart of a gear fault diagnostic method according to an embodiment of the present application;
FIG. 2 is a time domain waveform diagram of a vibration signal of a gear of one embodiment of the gear fault diagnostic method of FIG. 1;
FIG. 3 is a time domain waveform diagram of a time domain synchronous average signal of the gear fault diagnostic method of FIG. 2;
FIG. 4 is a detailed flowchart of step S2 of the gear fault diagnosis method of FIG. 1;
FIG. 5 is a detailed flowchart of step S23 of the gear fault diagnosis method of FIG. 1;
FIG. 6 is a detailed flowchart of step S3 of the gear fault diagnosis method of FIG. 1;
FIG. 7 is a time domain synchronous average signal spectrum diagram of the embodiment shown in FIG. 2;
FIG. 8 is a detailed flowchart of step S32 of the gear fault diagnosis method of FIG. 6;
FIG. 9 is a time domain waveform diagram and a frequency spectrum diagram of the conventional vibration signal of the embodiment shown in FIG. 2;
FIG. 10 is a time domain waveform diagram and a spectrum diagram of a residual signal of the embodiment shown in FIG. 2;
FIG. 11 is a time domain diagram of residual signal feature values for the embodiment shown in FIG. 2;
FIG. 12 is a time domain waveform diagram and a frequency spectrum diagram of a time domain synchronous averaged signal of another embodiment of the gear fault diagnostic method of FIG. 1;
FIG. 13 is a detailed flowchart of step S32 of the gear fault diagnostic method of FIG. 12;
FIG. 14 is a time domain waveform diagram and a frequency spectrum diagram of the conventional vibration signal of the embodiment shown in FIG. 12;
FIG. 15 is a time domain waveform diagram and a spectrum diagram of the differential signal of the embodiment shown in FIG. 12;
FIG. 16 is a time domain plot of the differential signal characteristic values of the embodiment shown in FIG. 12;
FIG. 17 is a schematic block diagram of a gear fault diagnostic system of one embodiment of the present application.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus consistent with certain aspects of the present application, as detailed in the appended claims.
The terminology used in the embodiments of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. Unless otherwise defined, technical or scientific terms used in the embodiments of the present application should have the ordinary meaning as understood by those having ordinary skill in the art to which the present application belongs. The terms "first," "second," and the like, as used in the description and in the claims, do not denote any order, quantity, or importance, but rather are used to distinguish one element from another. Also, the use of the terms "a" or "an" and the like do not denote a limitation of quantity, but rather denote the presence of at least one. "plurality" or "a number" means two or more. Unless otherwise indicated, "front", "rear", "lower" and/or "upper" and the like are for convenience of description and are not limited to one position or one spatial orientation. The word "comprising" or "comprises", and the like, means that the element or item listed as preceding "comprising" or "includes" covers the element or item listed as following "comprising" or "includes" and its equivalents, and does not exclude other elements or items. The terms "connected" or "coupled" and the like are not restricted to physical or mechanical connections, but may include electrical connections, whether direct or indirect. As used in this specification and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
Fig. 1 is a flowchart of a gear fault diagnosis method according to an embodiment of the present application. Referring to fig. 1, the present application provides a gear fault diagnosis method, including: steps S1-S5.
In step S1, a vibration signal of the gear is acquired. In some embodiments, the vibration signal of the gear includes vibration acceleration and rotation speed. An acceleration sensor can be arranged on the outer surface of the gear box to monitor the vibration acceleration of the gear, and vibration acceleration data of a time period is collected at fixed time intervals, for example, data is collected once every 0.5 hour, the collection time is 4 seconds, and the vibration acceleration data within 4 seconds is collected. In some embodiments, a corresponding speed sensor may be provided to sense the magnitude of the rotational speed of the gear, typically mounted on the generator shaft.
In step S2, the vibration signal of the gear is processed by using a time domain synchronous averaging algorithm to obtain a time domain synchronous averaged signal of the gear. FIG. 2 is a time domain waveform diagram of a vibration signal of a gear of one embodiment of the gear fault diagnostic method of FIG. 1. Referring to fig. 2, the vibration signals of the gear acquired by the sensor include synchronous incoherent signals and noise signals, and if the vibration signals are not processed for denoising, the gear fault is easily misjudged. Fig. 3 is a time domain waveform diagram of a time domain synchronous average signal of the gear fault diagnosis method of fig. 2. Referring to fig. 3, the time domain synchronous averaging algorithm is used in the present application, and the time domain synchronous averaging signal of the gear is obtained after the time domain synchronous averaging algorithm is processed, so that the gear fault diagnosis method of the present application has high accuracy.
Fig. 4 is a detailed flowchart of step S2 of the gear fault diagnosis method of fig. 1. In some embodiments, in order to further improve the accuracy of the time domain synchronous average signal obtained in step S2 so as to improve the accuracy of the gear fault diagnosis method of the present application, step S2 may include steps S21 to S23.
In step S21, a cubic spline fitting interpolation process is performed on the vibration signal of the gear to obtain a smooth vibration signal. In this way, the data size of the vibration signal of the gear can be increased, and the resolution of the vibration signal of the gear obtained through interpolation processing in the time dimension is increased, so as to achieve the purpose of improving the accuracy of the vibration signal of the gear obtained in step S1.
In step S22, the smooth vibration signal is subjected to time domain to angle domain conversion based on order tracking theory, resulting in an order tracking signal. The order tracking is based on the constant angular data to synchronously resample, so that an angular domain graph and an order spectrum can be directly obtained, and meanwhile, the angular data value can be preset, so that the order resolution and the maximum measurable order can be controlled, a more accurate order spectrum can be obtained, and a foundation is provided for the subsequent gear fault diagnosis. In some embodiments, before the smooth vibration signal of the gear is processed by the order tracking, whether the rotation speed data is a rotation speed value or a rotation speed time sequence needs to be judged, and if the rotation speed data is the rotation speed value, the rotation speed data is converted into the rotation speed time sequence. In some embodiments, the rotation speed unit is circle/minute, the rotation speed value is S, and the rotation speed time sequence is 0, 60/S, 120/S and 180/S … ….
In step S23, the order tracking signal is processed by using a time domain synchronous averaging algorithm to obtain a time domain synchronous averaged signal of the gear. In some embodiments, the order tracking signal obtained through the order tracking processing can ensure that the signal keeps the same sampling point number in each segmentation period, so that the characteristic signal related to the rotation speed of the gear can be analyzed more conveniently and effectively, and a powerful basis is provided for the subsequent gear fault diagnosis.
In some embodiments, the time domain synchronous averaging algorithm of the present application is to divide the vibration signal of the gear according to the number of shaft rotation turns of the gear, and then average, thereby removing synchronous incoherent signals generated by other vibration sources (such as other gears) and simultaneously removing noise signals. Fig. 5 is a detailed flowchart of step S23 of the gear fault diagnosis method of fig. 1, referring to fig. 5, in some embodiments, step S23 further includes steps S231-S233.
In step S231, a cutting cycle is determined according to the rotation speed of the gear. For better time domain synchronous averaging, the cutting period is determined according to the rotating speed of the gear and is increased along with the increase of the rotating speed of the gear. In some embodiments, step S231 includes: and calculating the rotation speed ratio speration of the shaft of the gear to be researched and the rotation speed test shaft according to the rotation speed of the gear, and determining that the cutting period is 2 pi spattio. The obtained segmentation period is reasonable, and the accuracy of the finally obtained time domain synchronous average signal is high.
In step S232, the vibration signal is sliced according to the slicing period to obtain a multi-segment sub-vibration signal. In step S233, the multiple segments of sub-vibration signals are processed by using a time domain synchronous averaging algorithm to obtain a time domain synchronous average signal of the gear. In some embodiments, the "processing the multiple sub-vibration signals" in step S233 specifically includes adding the multiple sub-vibrations obtained in step S232 and then averaging the multiple sub-vibrations, so as to remove the influence of the synchronous incoherent signal and the noise signal on the vibration signal of the gear.
Therefore, the vibration signal of the gear processed by the time domain synchronous averaging algorithm accurately keeps the synchronous coherent signal of the gear, the vibration condition of the gear can be more accurately shown, and the reliability of the gear fault diagnosis method is improved. In some embodiments, the order tracking signals obtained in steps S21 and S22 may be subjected to the slicing and time-domain synchronous average calculation according to the slicing period in steps S231 to S233, so as to obtain a time-domain synchronous average signal.
Returning to fig. 1, in step S3, a normal vibration signal of the gear is determined based on the time domain synchronous average signal. In some embodiments, the synchronous coherent signal obtained by removing the synchronous incoherent signal and the noise signal in step S2 includes a normal vibration signal. The conventional vibration signal of the gear represents a theoretical vibration signal when the gear operates without faults, and can be used as a reference for diagnosing whether the gear is in faults or not.
Fig. 6 is a detailed flowchart of step S3 of the gear failure diagnosis method of fig. 1. Referring to fig. 6, in order to determine the normal vibration signal of the gear, the time-domain synchronous average signal is processed, and the step S3 includes steps S31-S33. In step S31, the time-domain synchronous average signal is fourier-transformed to obtain a time-domain synchronous average signal spectrum. FIG. 7 is a diagram of the spectrum of the time-domain synchronous average signal of the embodiment shown in FIG. 2. Referring to fig. 7, after fourier transform, the time domain synchronous average signal is converted into a frequency spectrum, and the frequency spectrum of the time domain synchronous average signal contains abundant gear vibration information including gear meshing frequency, gear meshing amplitude, and gear meshing phase of a gear, gear shaft rotation frequency, gear shaft rotation amplitude, and gear shaft rotation phase of the gear, etc., and the abscissa of the time domain synchronous average signal is frequency and the ordinate of the time domain synchronous average signal is amplitude.
In some embodiments, the conventional vibration signals of the gears include gear shaft rotation vibration signals and gear mesh vibration signals. In step S32, the gear meshing vibration signal and the gear shaft rotating vibration signal of the gear are determined based on the time domain synchronous averaged signal spectrum. The gear meshing vibration signal and the gear shaft rotating vibration signal of the gear can be obtained by performing inverse Fourier transform on the frequency, amplitude and phase of the gear meshing vibration signal and the gear shaft rotating vibration signal respectively.
Fig. 8 is a detailed flowchart of step S32 of the gear failure diagnosis method of fig. 6. Referring to fig. 8, in some embodiments, the step S32 includes steps S321 to S323 in order to determine the gear meshing vibration signal and the gear shaft rotation vibration signal of the gear.
In step S321, the gear mesh frequency, the gear mesh amplitude, and the gear mesh phase of the gear, and the gear shaft rotational frequency, the gear shaft rotational amplitude, and the gear shaft rotational phase of the gear are determined from the time domain synchronous average signal spectrum. Referring to fig. 7, the gear meshing frequency, the gear meshing amplitude, and the gear meshing phase, and the gear shaft rotation frequency, the gear shaft rotation amplitude, and the gear shaft rotation phase of the gear can be directly or indirectly obtained according to the time domain synchronous average signal frequency spectrum. In some embodiments, the gear mesh frequency of the gear and the gear shaft rotation frequency of the gear may be determined using a maximum magnitude method based on the time domain synchronous averaged signal spectrum. In some embodiments, the maximum amplitude method is embodied by taking the frequency corresponding to the maximum amplitude as the gear shaft rotation frequency of the gear and calculating the gear mesh frequency. In other embodiments, other methods, such as amplitude comparison, spectral energy, etc., may be utilized to determine the meshing frequency of the gears and the gear shaft rotational frequency of the gears.
In the illustrated embodiment, in order to more accurately obtain the gear meshing vibration signal and the gear shaft rotation vibration signal of the gear, the step S321 further includes: determining gear meshing frequency and harmonic mf thereof of the gear according to the time domain synchronous average signal frequency spectrum i Gear mesh amplitude and its harmonic amplitude mfa i Gear mesh phase and its harmonic phase mfp i And gear shaft rotation frequency of gearRate and its harmonics sf i Gear shaft rotation amplitude and harmonic amplitude sfa thereof i And gear shaft rotational phase and its harmonic phase sfp i . In some embodiments, the harmonic and its harmonic amplitude and phase within the fifth multiple may be selected, where i is 1,2,3,4,5, so that the gear meshing vibration signal and the gear shaft rotation vibration signal obtained after the inverse transformation are more accurate.
In step S322, performing inverse fourier transform on the gear engagement frequency, the gear engagement amplitude, and the gear engagement phase to obtain a gear engagement vibration signal of the gear; and carrying out inverse Fourier transform on the rotation frequency of the gear shaft, the rotation amplitude of the gear shaft and the rotation phase of the gear shaft to obtain a gear shaft rotation vibration signal of the gear. The inverse fourier transform may restore a time-domain waveform map of a signal based on its frequency, amplitude, and phase. In the illustrated embodiment, the gear mesh vibration signal is formulated as
The rotary vibration signal formula of the gear shaft is
Where the start of t is 0 and the interval is the sampling period of the time domain synchronous averaged signal.
With continued reference to fig. 6, in step S33, a normal vibration signal of the gear is determined based on the gear mesh vibration signal and the gear shaft rotation vibration signal. Fig. 9 is a time domain waveform diagram and a frequency spectrum diagram of the conventional vibration signal of the embodiment shown in fig. 2. Referring to fig. 9, in the illustrated embodiment, the conventional vibration signal yrt is the sum of the gear shaft rotation vibration signal and the gear mesh vibration signal, and the specific formula of the conventional vibration signal yrt for the gear is as follows:
in some embodiments, when the gear does not have a fault in normal operation, only a slight error exists between the time domain synchronous average signal and the conventional vibration signal, once the gear has a fault, a difference value between the time domain synchronous average signal and the conventional vibration signal becomes large, the difference value mainly comprises a residual signal and a differential signal, wherein the conventional vibration signal for obtaining the differential signal also needs to comprise a gear mesh modulation vibration signal on the basis of formula 1, and the gear fault diagnosis method monitors the operation state of the gear by recording the difference value.
In some embodiments, the differential signal and the residual signal contain abundant transmission gear fault information, the characteristic values obtained by the differential signal and the residual signal can well reflect the fault degree of the transmission gear, and can also perform well when the traditional time domain characteristic and the traditional frequency domain characteristic are not well performed, and the running state of the transmission gear is monitored together with the traditional time domain characteristic and the traditional frequency domain characteristic and can be used as a health condition signal of the gear. Returning to fig. 1, in step S4, a health signal of the gear is determined according to the time domain synchronous average signal and the normal vibration signal, wherein the health signal includes at least one of a differential signal and a residual signal. Fig. 10 is a time domain waveform diagram and a frequency spectrum diagram of the residual signal of the embodiment shown in fig. 2. Referring to fig. 10, in the illustrated embodiment, the health condition signal is a residual signal, which is the sum of the time domain synchronous average signal minus the gear shaft rotation vibration signal and the gear meshing vibration signal.
The gear fault diagnosis method can be suitable for monitoring the gear for a long time. In step S5, a failure diagnosis is performed on the gear based on the health status signal. In some embodiments, since there is a certain rule in the change of the health status signal when the fault occurs, the characteristic value may be determined according to the health status signal, and step S5 further includes: obtaining a signal characteristic value according to the health condition signal, wherein the signal characteristic value comprises a root mean square value, an energy ratio and a kurtosis; and if the signal characteristic value is larger than the fault threshold value, determining that the gear is in fault, and giving an alarm. In the illustrated embodiment, the signal is a residual signal due to the health condition, wherein the residual signal characteristic value comprises a residual root mean square value, RS _ RMS, of the formula
Residual energy ratio RS _ ER of the formula
And a residual kurtosis RS _ NS4, formulated as
Fig. 11 is a time domain diagram of the residual signal characteristic values of the embodiment shown in fig. 2, and referring to fig. 11, the three residual signal characteristic values can well reflect the failure degree of the transmission gear. And if the signal characteristic value is larger than the fault threshold value, determining that the gear is in fault, and giving an alarm. In the illustrated embodiment, at times 2017-09-14 and thereafter, the three residual signal feature values all increase significantly, and it can be determined whether the residual signal feature values are greater than the fault threshold value. If yes, the gear can be determined to be in fault, an alarm is given, and maintenance personnel are reminded to replace the gear in time.
Fig. 12 is a time-domain waveform diagram and a frequency spectrum diagram of a time-domain synchronous average signal of another embodiment of the gear fault diagnosis method of fig. 1. Referring to fig. 12, in other embodiments, the gear mesh vibration signal is amplitude modulated, and in order to obtain a more accurate conventional vibration signal, the gear mesh modulated vibration signal needs to be calculated, and fig. 13 is a detailed flowchart of step S32 of the gear fault diagnosis method of fig. 12. In addition to the above-described steps S321 to S322, the step S32 may further include steps S323 to S324. In step S323, a trigonometric function transformation is performed based on the gear mesh vibration signal and the time domain synchronous average signal spectrum, and a gear mesh modulation vibration signal of the gear is obtained. In some embodiments, the modulation formula for the gear mesh vibration signal may be derived from a modulation formula for the gear mesh vibration signal, whether amplitude modulated or frequency modulated.
In some embodiments, the modulation method is amplitude modulation, and the trigonometric function transformation process is as follows: when the signal is subjected to amplitude modulation, the formula is
Where Am is the amplitude of the modulation formula, fm is the frequency of the modulation equation,
for the phase of the modulation formula, after trigonometric function transformation
In some embodiments, when the gear mesh vibration signal is modulated by the rotation of the gear shaft, the function parameter can be calculated by using a left-right average method, and the left and right sidebands of the gear mesh vibration signal are generated by using the modulation formula, and the amplitude modulation formula of the gear mesh modulation vibration signal is Aa ═ lsbfa i +rsbfa i 、2f m ＝rsbf i -lsbf i 、
Yield a ═ lsbfa (lsbfa) i +rsbfa i )/A、f m ＝(rsbf i -lsbf i )/2、
Wherein, lsbf i Left hand band frequency, rsbf i For the right band frequency, lsbfa i To the left band amplitude, rsbfa i Is the right band amplitude, lsbfp i Left band phase and rsbfpi right band phase. Therefore, the gear mesh modulation vibration signal of the gear can be accurately restored, and a more accurate gear conventional vibration signal can be obtained.
In step S324, a normal vibration signal of the gear is determined based on the gear mesh vibration signal, the gear shaft rotation vibration signal, and the gear mesh modulation vibration signal. At this time, the conventional vibration signal ydt of the gear is the sum of the gear shaft rotation vibration signal, the gear mesh vibration signal and the gear mesh modulation vibration signal, and the specific formula is as follows:
the conventional vibration signal ydt including the differential signal obtained in equation 2 is obtained by adding the gear mesh modulation vibration signal obtained in step S323 to equation 1, and the obtained conventional vibration signal reflects the vibration of the gear in this embodiment.
Fig. 14 is a time domain waveform diagram and a frequency spectrum diagram of the conventional vibration signal of the embodiment shown in fig. 12, and fig. 15 is a time domain waveform diagram and a frequency spectrum diagram of the differential signal of the embodiment shown in fig. 12. Referring to fig. 14-15, in the embodiment shown in fig. 12, the health status signal in step S4 is a differential signal, which is the sum of the time domain synchronous average signal minus the gear shaft rotation vibration signal, the gear mesh vibration signal and the gear mesh modulation vibration signal.
Fig. 16 is a time domain diagram of the differential signal characteristic values of the embodiment shown in fig. 12. In the embodiment shown in fig. 12, the signal characteristic values of step S4 include a differential root mean square value, a differential energy ratio and a differential kurtosis, and these three differential signal characteristic values can also well reflect the fault degree of the amplitude-modulated gear.
According to the gear fault monitoring method, the gear fault is monitored by monitoring the health condition signal of the gear, the health condition signal comprises at least one of a residual signal and a differential signal, the fault degree of a transmission gear is reflected, and the accuracy is high; when the health condition signal is determined, the gear fault monitoring method uses a time domain synchronous averaging technology, obtains the conventional vibration signal capable of accurately expressing the normal vibration condition of the gear according to the time domain synchronous averaging signal, and determines the health condition signal of the gear according to the time domain synchronous averaging signal and the conventional vibration signal, so that the health condition signal in the vibration signal of the gear is rapidly extracted, the method is simple, convenient and rapid, has high reliability, and the fault monitoring is more accurate.
The embodiment of the application further provides a gear fault diagnosis design system 200 which can be applied to a wind driven generator. FIG. 17 is a schematic block diagram of a gear failure diagnostic design system 200 according to an embodiment of the present application. As shown in fig. 17, the gear failure diagnosis design system 200 may include one or more processors 201 for implementing the gear failure diagnosis design method described in any of the above embodiments. In some embodiments, the gear failure diagnostic design system 200 may include a computer-readable storage medium 202, and the computer-readable storage medium 202 may store a program that may be invoked by the processor 201, and may include a non-volatile storage medium. In some embodiments, the gear failure diagnostic design system 200 may include a memory 203 and an interface 204. In some embodiments, the gear failure diagnosis design system 200 of the present application embodiment may also include other hardware depending on the actual application.
The gear failure diagnosis design system 200 of the embodiment of the present application has similar beneficial technical effects to the above-described gear failure diagnosis design method, and therefore, details are not repeated herein.
The embodiment of the application also provides a computer readable storage medium. The computer-readable storage medium has a program stored thereon, and the program, when executed by a processor, implements the gear failure diagnosis design method described in any of the above embodiments.
Embodiments of the present application may take the form of a computer program product embodied on one or more storage media including, but not limited to, disk storage, CD-ROM, optical storage, and the like, in which program code is embodied. Computer-readable storage media include permanent and non-permanent, removable and non-removable media and may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer readable storage media include, but are not limited to: phase change memory/resistive random access memory/magnetic memory/ferroelectric memory (PRAM/RRAM/MRAM/FeRAM) and like new memories, Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technologies, compact disc read only memory (CD-ROM), Digital Versatile Disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, may be used to store information that may be accessed by a computing device.
The gear fault diagnosis design method, the gear fault diagnosis system and the computer readable storage medium provided by the embodiments of the present application are described in detail above. The gear fault diagnosis design method, the gear fault diagnosis system and the computer-readable storage medium according to the embodiments of the present application are described herein by using specific examples, and the above description of the embodiments is only used to help understand the core idea of the present application and is not intended to limit the present application. It should be noted that, for those skilled in the art, without departing from the spirit and principle of the present application, several improvements and modifications can be made to the present application, and these improvements and modifications should also fall into the protection scope of the appended claims of the present application.
Claims (10)
1. A gear fault diagnosis method, comprising:
acquiring a vibration signal of the gear;
processing the vibration signal of the gear by using a time domain synchronous average algorithm to obtain a time domain synchronous average signal of the gear;
determining a conventional vibration signal of the gear according to the time domain synchronous average signal;
determining a health signal of the gear according to the time domain synchronous average signal and the conventional vibration signal, wherein the health signal comprises at least one of a differential signal and a residual signal;
and carrying out fault diagnosis on the gear according to the health condition signal.
2. The gear fault diagnosis method according to claim 1, wherein the processing the vibration signal of the gear by using the time domain synchronous averaging algorithm to obtain the time domain synchronous averaged signal of the gear comprises:
determining a cutting period according to the rotating speed of the gear;
segmenting the vibration signal according to the segmentation period to obtain a plurality of segments of sub-vibration signals;
and processing the multi-segment sub-vibration signals by utilizing a time domain synchronous average algorithm to obtain time domain synchronous average signals of the gear.
3. The gear fault diagnosis method according to claim 1, wherein the processing the vibration signal of the gear by using the time-domain synchronous averaging algorithm to obtain the time-domain synchronous averaged signal of the gear comprises:
carrying out cubic spline fitting interpolation processing on the vibration signal of the gear to obtain a smooth vibration signal;
based on an order tracking theory, performing time domain to angle domain conversion on the smooth vibration signal to obtain an order tracking signal;
and processing the order tracking signal by utilizing the time domain synchronous averaging algorithm to obtain a time domain synchronous averaging signal of the gear.
4. The gear fault diagnosis method according to claim 1, wherein the determining a regular vibration signal of the gear based on the time domain synchronous averaged signal comprises:
performing Fourier transform on the time domain synchronous average signal to obtain a time domain synchronous average signal frequency spectrum;
determining a gear meshing vibration signal and a gear shaft rotating vibration signal of the gear according to the time domain synchronous average signal frequency spectrum;
and determining a conventional vibration signal of the gear according to the gear meshing vibration signal and the gear shaft rotation vibration signal.
5. The gear fault diagnosis method according to claim 4, wherein the determining the gear meshing vibration signal and the gear shaft rotation vibration signal of the gear based on the time domain synchronous averaged signal spectrum includes:
determining the gear meshing frequency, the gear meshing amplitude and the gear meshing phase of the gear, and the gear shaft rotation frequency, the gear shaft rotation amplitude and the gear shaft rotation phase of the gear according to the time domain synchronous average signal frequency spectrum;
carrying out inverse Fourier transform on the gear meshing frequency, the gear meshing amplitude and the gear meshing phase to obtain a gear meshing vibration signal of the gear;
and carrying out Fourier inverse transformation on the gear shaft rotation frequency, the gear shaft rotation amplitude and the gear shaft rotation phase to obtain a gear shaft rotation vibration signal of the gear.
6. The gear fault diagnosis method according to claim 5, wherein the determining of the gear mesh frequency, the gear mesh amplitude, and the gear mesh phase of the gear and the gear shaft rotation frequency, the gear shaft rotation amplitude, and the gear shaft rotation phase of the gear based on the time domain synchronous averaged signal spectrum comprises:
and determining the gear meshing frequency of the gear and the gear shaft rotation frequency of the gear by using a maximum amplitude method according to the time domain synchronous average signal frequency spectrum.
7. The gear fault diagnosis method according to claim 4, wherein the determining a regular vibration signal of the gear based on the gear mesh vibration signal and the gear shaft rotation vibration signal includes:
performing trigonometric function transformation according to the gear meshing vibration signal and the time domain synchronous average signal frequency spectrum to obtain a gear meshing modulation vibration signal of the gear;
and determining a conventional vibration signal of the gear according to the gear meshing vibration signal, the gear shaft rotating vibration signal and the gear meshing modulation vibration signal.
8. The gear fault diagnosis method according to claim 1, wherein the fault diagnosing the gear according to the health signal includes:
obtaining signal characteristic values according to the health condition signals, wherein the signal characteristic values comprise root mean square values, energy ratios and kurtosis;
and if the signal characteristic value is larger than a fault threshold value, determining that the gear is in fault, and giving an alarm.
9. A gear fault diagnostic system characterized by: comprising one or more processors for implementing the gear fault diagnosis method according to any one of claims 1-8.
10. A computer-readable storage medium, characterized in that a program is stored thereon, which when executed by a processor, implements the gear failure diagnosis method according to any one of claims 1 to 8.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115795292A (en) * | 2022-10-20 | 2023-03-14 | 南京工大数控科技有限公司 | Gear milling machine spindle box fault diagnosis system and method based on LabVIEW |
| WO2024074084A1 (en) * | 2022-10-08 | 2024-04-11 | 中国航发商用航空发动机有限责任公司 | Fault diagnosis method and system for gearbox, device, and medium |
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2022
- 2022-05-26 CN CN202210590574.3A patent/CN115031959A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2024074084A1 (en) * | 2022-10-08 | 2024-04-11 | 中国航发商用航空发动机有限责任公司 | Fault diagnosis method and system for gearbox, device, and medium |
| CN115795292A (en) * | 2022-10-20 | 2023-03-14 | 南京工大数控科技有限公司 | Gear milling machine spindle box fault diagnosis system and method based on LabVIEW |
| CN115795292B (en) * | 2022-10-20 | 2023-10-17 | 南京工大数控科技有限公司 | Gear milling machine spindle box fault diagnosis system and method based on LabVIEW |
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