CN116358864A - Method and system for diagnosing fault type of rotary mechanical equipment - Google Patents
Method and system for diagnosing fault type of rotary mechanical equipment Download PDFInfo
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Abstract
The invention discloses a fault type diagnosis method and system for rotary mechanical equipment, and relates to the technical field of fault type diagnosis of rotary mechanical equipment. The method comprises the steps of collecting vibration signals of rotary mechanical equipment to be diagnosed at different moments; acquiring frequency spectrum data of a vibration signal, wherein the frequency spectrum data comprises frequency data and amplitude data; dispersing the frequency spectrum data to obtain discrete frequency data and discrete amplitude data; determining change frequency data and change amplitude data of the vibration signal based on the discrete frequency data and the discrete amplitude data; drawing a frequency stability chart according to the change frequency data and the change amplitude data; the type of fault of the rotating machine to be diagnosed is determined based on the frequency stability diagram. The frequency stability diagram provided by the invention is a scatter diagram, the change frequency data is clear at a glance, an effective visualization tool is provided for fault diagnosis of rotary mechanical equipment, the change frequency data and the change amplitude data are not required to be manually analyzed, and the efficiency and the accuracy of manual diagnosis and analysis are improved.
Description
Technical Field
The invention relates to the technical field of fault type diagnosis of rotary mechanical equipment, in particular to a fault type diagnosis method and system of rotary mechanical equipment.
Background
In the field of predictive maintenance of mechanical equipment, acquisition of vibration signals of the mechanical equipment is one of the main modes for analyzing equipment abnormality and faults, and monitoring of the vibration signals can discover most faults of the mechanical equipment, such as bearing faults, gear faults, rotor imbalance, misalignment of a coupling, abrasion of the coupling, looseness of a foundation and the like.
In the prior art, the fault diagnosis method for the vibration signal mainly relies on a diagnosis expert to check the characteristic trend of vibration, analyze the vibration waveform and the frequency spectrum of abnormal vibration time, and identify whether the frequency spectrum has fault frequency, whether the amplitude of specific frequency is increased or not, and the like, so as to complete the fault diagnosis of mechanical equipment. Aiming at the problem of automatic identification of fault diagnosis, a plurality of documents and patents disclose corresponding methods, fault diagnosis automation mainly establishes a fault diagnosis identification model through fault case numerical drive algorithm modeling, at present, as the reliability of most mechanical equipment is continuously improved, the fault rate of the mechanical equipment is continuously reduced, the mode of establishing the fault diagnosis model based on fault case numerical values is limited by case numerical values lack, and if the modeling based on small sample case numerical values cannot guarantee higher fault diagnosis accuracy. The automatic or intelligent fault diagnosis mode for algorithm modeling will be limited by the number of fault cases, so the fault diagnosis mode through manual analysis will still play an important role.
In some existing multi-spectrum analysis methods, such as a 'waterfall diagram' of a vibration spectrum, although the frequency change condition can be visually checked through the waterfall diagram, the frequency change data can be extracted only by manually and severely participating in the analysis process. Therefore, it is necessary to provide a method and a system for diagnosing the fault type of the rotating machinery equipment, which can directly provide a frequency stability chart corresponding to the change frequency data, so that manual analysis of the change frequency data and corresponding change amplitude data are not needed.
Disclosure of Invention
The invention aims to provide a fault type diagnosis method and system for rotary mechanical equipment, which are used for solving the problem that in the prior art, manual heavy participation analysis is needed in fault diagnosis of the rotary mechanical equipment.
In order to achieve the above object, the present invention provides the following solutions:
a fault type diagnosis method of a rotary machine, comprising:
collecting vibration signals of rotary mechanical equipment to be diagnosed at different moments;
acquiring spectrum data of the vibration signal by adopting a spectrum analysis method; the frequency spectrum data comprises frequency data and amplitude data;
dispersing the spectrum data to obtain discrete frequency data and discrete amplitude data;
determining change frequency data and change amplitude data of the vibration signal based on the discrete frequency data and the discrete amplitude data;
drawing a frequency stability diagram by taking the change frequency data as an abscissa and the change amplitude data as an ordinate;
and determining the fault type of the rotary mechanical equipment to be diagnosed based on the frequency stability diagram.
Optionally, the spectrum data is discretized to obtain discrete frequency data and discrete amplitude data, which specifically includes:
dividing each frequency data into a plurality of groups of frequency values at intervals of N frequency resolution, taking a first frequency value of each group of frequency values as a discrete frequency value of the current group of frequency values, wherein the discrete frequency values of each group of frequency values form the discrete frequency data;
dividing the amplitude data into a plurality of groups of amplitude values at intervals of N times of amplitude values, taking the amplitude statistical value of each group of amplitude values as the discrete amplitude value of the current group of amplitude values, and forming the discrete amplitude data by the discrete amplitude values of each group of amplitude values.
Optionally, determining the change frequency data and the change amplitude data of the vibration signal based on the discrete frequency data and the discrete amplitude data specifically includes:
taking the discrete amplitude data corresponding to the vibration signal acquired at the earliest moment as a reference discrete amplitude;
subtracting the discrete amplitude data corresponding to the vibration signals acquired at other moments from the reference discrete amplitude in sequence to obtain a difference amplitude array;
the first K difference amplitude data which are arranged from large to small in each group of difference amplitude arrays are selected as change amplitude data;
and taking the discrete frequency data corresponding to the first K difference amplitude values as the change frequency data.
Optionally, the determining, based on the frequency stability diagram, a fault type of the rotating machinery to be diagnosed specifically includes:
judging whether the frequency stability diagram has a stable frequency value or not;
if yes, determining that the fault type of the rotary mechanical equipment to be diagnosed is rotor fault or bearing fault;
if not, determining that the fault type of the rotary mechanical equipment to be diagnosed is irrelevant to the vibration signal, and that the rotor faults and the bearing faults do not exist.
Optionally, when the frequency stability chart has a stable frequency value, determining that the fault type of the rotating machinery to be diagnosed is a rotor type fault or a bearing fault, including:
when the frequency stability diagram has a stable frequency value, judging whether the stable frequency value is an integer multiple of the rotating frequency;
if yes, determining that the fault type of the rotary mechanical equipment to be diagnosed is a rotor fault;
if not, determining the fault type of the rotary mechanical equipment to be diagnosed as bearing fault.
The invention also provides a fault diagnosis system of the rotary mechanical equipment, which comprises the following steps:
the vibration signal acquisition module is used for acquiring vibration signals of the rotary mechanical equipment to be diagnosed at different moments;
the frequency spectrum data acquisition module is used for acquiring frequency spectrum data of the vibration signal by adopting a frequency spectrum analysis method; the frequency spectrum data comprises frequency data and amplitude data;
the frequency spectrum data dispersing module is used for dispersing the frequency spectrum data to obtain discrete frequency data and discrete amplitude data;
the change frequency data and change amplitude data determining module is used for determining change frequency data and change amplitude data of the vibration signal based on the discrete frequency data and the discrete amplitude data;
the frequency stability diagram drawing module is used for drawing a frequency stability diagram by taking the change frequency data as an abscissa and the change amplitude data as an ordinate;
and the fault type determining module is used for determining the fault type of the rotary mechanical equipment to be diagnosed based on the frequency stability diagram.
Optionally, the spectrum data discrete module includes:
a discrete frequency data acquisition unit, configured to divide each frequency data into a plurality of groups of frequency values at intervals of N-frequency resolution, and take a first frequency value of each group of frequency values as a discrete frequency value of a current group of frequency values, where the discrete frequency values of each frequency data form the discrete frequency data;
the discrete amplitude data acquisition unit is used for dividing each amplitude data into a plurality of groups of amplitude values at intervals of N times of amplitude values, taking the amplitude statistical value of each group of amplitude values as the discrete amplitude value of the current group of amplitude values, and forming the discrete amplitude data by the discrete amplitude values of each amplitude data.
Optionally, the change frequency data and change amplitude data determining module includes:
the reference discrete amplitude determining unit is used for taking the discrete amplitude data corresponding to the vibration signal acquired at the earliest moment as a reference discrete amplitude;
the difference amplitude array determining unit is used for sequentially subtracting the discrete amplitude data corresponding to the vibration signals acquired at other moments from the reference discrete amplitude to obtain a difference amplitude array;
the change amplitude data determining unit is used for selecting the first K difference amplitude data which are arranged from large to small in each group of difference amplitude arrays as change amplitude data;
and the change frequency data determining unit is used for taking the discrete frequency data corresponding to the first K difference amplitude values as change frequency data.
Optionally, the fault type determining module includes:
the judging unit is used for judging whether the frequency stability diagram has a stable frequency value or not;
the fault type determining unit is used for determining that the fault type of the rotary mechanical equipment to be diagnosed is a rotor fault or a bearing fault when the frequency stability diagram has a stable frequency value;
and the result determining unit is used for determining that the fault type of the rotary mechanical equipment to be diagnosed is irrelevant to the vibration signal when the frequency stability diagram does not have a stable frequency value, and rotor faults and bearing faults do not exist.
Optionally, the fault type determining unit includes:
a judging subunit, configured to judge whether the stable frequency value is an integer multiple of the frequency conversion;
a rotor type fault determining subunit, configured to determine that a fault type of the rotating mechanical device to be diagnosed is a rotor type fault when the stable frequency value is an integer multiple of a rotation frequency;
and the bearing fault determining subunit is used for determining that the fault type of the rotary mechanical equipment to be diagnosed is a bearing fault when the stable frequency value is not an integral multiple of the rotating frequency.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the fault type diagnosis method and system for the rotary mechanical equipment provided by the invention collect vibration signals of the rotary mechanical equipment to be diagnosed at different moments; acquiring frequency spectrum data of the vibration signal by adopting a frequency spectrum analysis method, wherein the frequency spectrum data comprises frequency data and amplitude data; dispersing the frequency spectrum data to obtain discrete frequency data and discrete amplitude data; determining change frequency data and change amplitude data of the vibration signal based on the discrete frequency data and the discrete amplitude data; drawing a frequency stability diagram by taking the variable frequency data as an abscissa and the variable amplitude data as an ordinate; the type of fault of the rotating machine to be diagnosed is determined based on the frequency stability diagram. The frequency stability diagram provided by the invention is a scatter diagram, the change frequency data in the diagram is clear at a glance, the frequency stability diagram provides effective visualization tools for fault diagnosis of the rotary mechanical equipment, and the change frequency data and the change amplitude data are not needed to be manually analyzed, so that the efficiency and the accuracy of manual diagnosis and analysis are improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a fault type diagnosis method for rotary mechanical equipment according to a first embodiment of the present invention;
FIG. 2 is a frequency stabilization diagram corresponding to the development of a bearing failure of a device;
FIG. 3 is a frequency stabilization chart corresponding to the development of an impeller imbalance fault of a device;
fig. 4 is a block diagram of a fault type diagnosis system for rotary machine according to a second embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention aims to provide a fault type diagnosis method and system for rotary mechanical equipment, which are characterized in that a frequency stability diagram is drawn through change frequency data and change amplitude data, the fault type of the rotary mechanical equipment to be diagnosed is determined based on the frequency stability diagram, and the efficiency and the accuracy of manual diagnosis and analysis are improved.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
Example 1
As shown in fig. 1, a fault type diagnosis method for a rotary mechanical device according to an embodiment of the present invention includes the following steps:
step 101: vibration signals of rotary mechanical equipment to be diagnosed at different moments are collected.
In this embodiment, according to the requirement of fault diagnosis and analysis of the mechanical device, vibration signals collected at different moments of monitoring and measuring of the mechanical device are selected as the vibration signals to be analyzed, and vibration signals selected sequentially in time are named as d1, d2, d 3. The vibration signal satisfies the same sampling frequency and the same sampling time length, and the selection principle of the vibration signal can be determined according to the vibration characteristic trend, for example: the important basis for selecting the vibration signal can be taken as the important basis according to the vibration characteristic growth stage. Wherein the vibration signal types include an acceleration signal, a velocity signal, and a displacement signal.
Step 102: acquiring frequency spectrum data of the vibration signal by adopting a frequency spectrum analysis method; the spectral data includes frequency data and amplitude data.
In this embodiment, spectral data obtained by sequentially performing spectral analysis on the vibration signals d1, d2, d3, dn includes frequency data f1, f2, f3,) fn with corresponding magnitude data m1, m2, m3,/mn. The spectrum analysis method comprises a fast Fourier transform analysis method, an envelope demodulation analysis method for acquiring an acceleration signal, a wavelet analysis method or other time-frequency domain analysis methods. The frequency data and the amplitude data are equal-length arrays, and the array length of the frequency data and the amplitude data accords with the fast Fourier transform; and when the equal-length arrays are limited to directly meet the requirement of the subsequent calculation of the difference amplitude arrays, the arrays are ensured to be subtracted in one-to-one correspondence.
Step 103: and dispersing the frequency spectrum data to obtain discrete frequency data and discrete amplitude data. Because the acquisition process of multiple times of different moments can be influenced by the outside, and meanwhile, partial mechanical equipment has the condition of fluctuation of rotating speed, the dispersion can ensure that signals acquired at multiple moments have stronger comparability; while the discrete can be located to an effective fault frequency band instead of some precise fault frequency during the fault diagnosis stage.
Further, step 103 specifically includes:
dividing each frequency data into a plurality of groups of frequency values at intervals of N frequency resolution, taking the first frequency value of each group of frequency values as the discrete frequency value of the current group of frequency values, and forming the discrete frequency data by the discrete frequency values of each group of frequency values. The frequency resolution is the difference between two adjacent frequency values in each set of frequency values. N is equal to or more than 1 and equal to or less than L, and the recommended value of N is 5,L which is the array length of each frequency data or each amplitude data. The frequency resolution dfi=f2-fi 1, fi2 represents the 2 nd frequency value of the frequency data fi corresponding to the vibration signal di, fi1 represents the 1 st frequency value of the frequency data fi corresponding to the vibration signal di, and i represents the i-th group of vibration signals.
Dividing each amplitude value into a plurality of groups of amplitude value at intervals of N times of amplitude values, taking the amplitude value statistical value of each group of amplitude value as the discrete amplitude value of the current group of amplitude value, and forming the discrete amplitude value data by the discrete amplitude value of each group of amplitude value. The amplitude statistic value comprises a minimum value, a maximum value, an average value, a median, a primary difference maximum value, a standard deviation and a variance; different statistics can analyze different characteristics of spectrum data, and finally diagnosis and positioning of different fault types of different equipment are facilitated, and the maximum value is generally used for general analysis.
Step 104: and determining the change frequency data and the change amplitude data of the vibration signal based on the discrete frequency data and the discrete amplitude data.
Further, step 104 specifically includes:
and taking the discrete amplitude data corresponding to the vibration signal acquired at the earliest moment as a reference discrete amplitude.
Subtracting the discrete amplitude data corresponding to the vibration signals acquired at other moments from the reference discrete amplitude in sequence to obtain a difference amplitude array; the array length of the difference amplitude array is equal to the array length of the discrete amplitude array.
The first K difference amplitude data which are arranged from large to small in each group of difference amplitude arrays are selected as change amplitude data; k is more than or equal to 1 and less than or equal to L/N.
And taking the discrete frequency data corresponding to the first K difference amplitude values as the change frequency data.
In this embodiment, a set of discrete amplitude data corresponding to the vibration signal d1 with the earliest acquisition time is selected as a reference discrete amplitude; subtracting the discrete amplitude data of d2, d3 and dn from the reference discrete amplitude in sequence to obtain a difference amplitude array c2, c3. and cn; and sequentially detecting the first K difference amplitude data which are arranged from large to small in cn as change amplitude data, taking discrete frequency data corresponding to the first K difference amplitude data as change frequency data, storing all the change amplitude data into an array cm, and storing all the change frequency data into an array cf.
Step 105: and drawing a frequency stability chart by taking the change frequency data as an abscissa and the change amplitude data as an ordinate.
Step 106: the type of fault of the rotating machine to be diagnosed is determined based on the frequency stability diagram. According to the scattered point distribution of the frequency stability diagram, whether a certain discrete frequency has variation in multiple acquisition time can be intuitively determined.
Further, step 106 specifically includes:
and judging whether the frequency stability diagram has a stable frequency value or not. The quantitative determination method of the frequency stability value is that the same discrete frequency occurrence number is greater than or equal to n multiplied by 0.5, and n is the total quantity of the acquired vibration signals.
If yes, determining that the fault type of the rotary mechanical equipment to be diagnosed is rotor fault or bearing fault; judging whether the stable frequency value is an integer multiple of the frequency conversion; if yes, determining that the fault type of the rotary mechanical equipment to be diagnosed is a rotor fault; if not, determining the fault type of the rotary mechanical equipment to be diagnosed as bearing fault.
If not, determining that the fault type of the rotary mechanical equipment to be diagnosed is irrelevant to the vibration signal, and no rotor faults and bearing faults exist.
Fig. 2 is a frequency stabilization diagram corresponding to the development of a bearing failure of a certain device. As shown in fig. 2, the main stable frequency value is 144HZ directly observed from the current frequency stability chart, and the vibration signals acquired at a plurality of moments are analyzed to obtain the vibration signals, namely the vibration signals indicate that the frequency of 144HZ appears for a long time at a plurality of moments and the amplitude of the vibration signals is most obvious relative to the standard increase, so that the frequency of 144HZ is used as the key analysis frequency and can be used for fault diagnosis and positioning. Analysis determines that the frequency is not a multiple of 25Hz of the rotational frequency, and can basically determine that the fault is related to the bearing fault, and the frequency is determined to be the bearing fault frequency through verification of the bearing model. Therefore, the fault complex change information can be intuitively embodied through a single graph of the frequency stability graph, the diagnosis efficiency and accuracy are effectively improved, and compared with the traditional spectrogram and related analysis spectrogram, the specificity is obviously reduced.
Fig. 3 is a frequency stability diagram corresponding to the development of an impeller imbalance fault of a certain device. As shown in fig. 3, the main stable frequency value of 12.5HZ can be directly observed from the current frequency stability diagram. Analysis determined that the frequency corresponds to 1 times the 12.5HZ of the transition frequency. The fault can be basically determined to be related to the rotor type fault, and the fault can be determined to be unbalanced by considering that the frequency stability diagram only comprises one-time frequency stability values and one-time frequency change.
Example two
Aiming at the fault type diagnosis method of the rotary mechanical equipment provided by the first embodiment, the second embodiment of the invention provides a fault type diagnosis system of the rotary mechanical equipment.
As shown in fig. 4, the system includes:
the vibration signal acquisition module 201 is used for acquiring vibration signals of the rotary mechanical equipment to be diagnosed at different moments.
A spectrum data acquisition module 202, configured to acquire spectrum data of the vibration signal by using a spectrum analysis method; the spectral data includes frequency data and amplitude data.
The spectrum data dispersing module 203 is configured to disperse spectrum data to obtain discrete frequency data and discrete amplitude data.
The change frequency data and change amplitude data determining module 204 is configured to determine change frequency data and change amplitude data of the vibration signal based on the discrete frequency data and the discrete amplitude data.
The frequency stability diagram drawing module 205 is configured to draw a frequency stability diagram with the change frequency data as an abscissa and the change amplitude data as an ordinate.
A fault type determination module 206 for determining a fault type of the rotating machine to be diagnosed based on the frequency stability diagram.
Further, the spectrum data discrete module 203 includes:
the discrete frequency data acquisition unit is used for dividing each frequency data into a plurality of groups of frequency values at intervals of N frequency resolution, taking the first frequency value of each group of frequency values as the discrete frequency value of the current group of frequency values, and forming the discrete frequency data by the discrete frequency values of each frequency data.
The discrete amplitude data acquisition unit is used for dividing each amplitude data into a plurality of groups of amplitude values at intervals of N times of amplitude values, taking the amplitude statistical value of each group of amplitude values as the discrete amplitude value of the current group of amplitude values, and forming the discrete amplitude data by the discrete amplitude values of each amplitude data. The value range of N is 1-N-L, L is the array length of each frequency data or each amplitude data.
Further, the change frequency data and change amplitude data determining module 204 includes:
the reference discrete amplitude determining unit is used for taking the discrete amplitude data corresponding to the vibration signal acquired at the earliest moment as the reference discrete amplitude.
The difference amplitude array determining unit is used for subtracting the discrete amplitude data corresponding to the vibration signals acquired at other moments from the reference discrete amplitude in sequence to obtain a difference amplitude array.
The change amplitude data determining unit is used for selecting the first K difference amplitude data which are arranged from large to small in each group of difference amplitude arrays as change amplitude data; k is more than or equal to 1 and less than or equal to L/N.
And the change frequency data determining unit is used for taking discrete frequency data corresponding to the first K difference amplitude values as change frequency data.
Further, the fault type determination module 206 includes:
and the judging unit is used for judging whether the frequency stability diagram has a stable frequency value.
And the fault type determining unit is used for determining that the fault type of the rotary mechanical equipment to be diagnosed is a rotor type fault or a bearing fault when the stable frequency value exists in the frequency stability diagram.
And the result determining unit is used for determining that the fault type of the rotary mechanical equipment to be diagnosed is irrelevant to the vibration signal when the stable frequency value does not exist in the frequency stability diagram, and rotor faults and bearing faults do not exist.
Further, the failure type determining unit includes:
and the judging subunit is used for judging whether the stable frequency value is an integral multiple of the frequency conversion.
And the rotor type fault determining subunit is used for determining that the fault type of the rotary mechanical equipment to be diagnosed is a rotor type fault when the stable frequency value is an integral multiple of the rotating frequency.
And the bearing fault determining subunit is used for determining that the fault type of the rotary mechanical equipment to be diagnosed is bearing fault when the stable frequency value is not an integral multiple of the rotating frequency.
According to the fault type diagnosis method and system for the rotary mechanical equipment, provided by the invention, the efficiency and accuracy of fault type diagnosis of the mechanical equipment are improved, effective and convenient visualization tools are provided for the fault type diagnosis of the rotary mechanical equipment, the equipment fault can be positioned quickly, an effective basis is provided for predictive maintenance of the equipment, the potential safety hazard of the equipment is further effectively reduced, and the abnormal shutdown and the great economic loss of the equipment are avoided.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to facilitate an understanding of the methods and systems of the present invention and the core ideas thereof; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.
Claims (10)
1. A fault type diagnosis method for a rotary machine, comprising:
collecting vibration signals of rotary mechanical equipment to be diagnosed at different moments;
acquiring spectrum data of the vibration signal by adopting a spectrum analysis method; the frequency spectrum data comprises frequency data and amplitude data;
dispersing the spectrum data to obtain discrete frequency data and discrete amplitude data;
determining change frequency data and change amplitude data of the vibration signal based on the discrete frequency data and the discrete amplitude data;
drawing a frequency stability diagram by taking the change frequency data as an abscissa and the change amplitude data as an ordinate;
and determining the fault type of the rotary mechanical equipment to be diagnosed based on the frequency stability diagram.
2. The method for diagnosing a fault type of a rotary machine according to claim 1, wherein the dispersing of the spectrum data to obtain discrete frequency data and discrete amplitude data comprises:
dividing each frequency data into a plurality of groups of frequency values at intervals of N frequency resolution, taking a first frequency value of each group of frequency values as a discrete frequency value of the current group of frequency values, wherein the discrete frequency values of each group of frequency values form the discrete frequency data;
dividing the amplitude data into a plurality of groups of amplitude values at intervals of N times of amplitude values, taking the amplitude statistical value of each group of amplitude values as the discrete amplitude value of the current group of amplitude values, and forming the discrete amplitude data by the discrete amplitude values of each group of amplitude values.
3. The rotary machine fault type diagnosis method according to claim 1, wherein determining the change frequency data and the change amplitude data of the vibration signal based on the discrete frequency data and the discrete amplitude data, specifically comprises:
taking the discrete amplitude data corresponding to the vibration signal acquired at the earliest moment as a reference discrete amplitude;
subtracting the discrete amplitude data corresponding to the vibration signals acquired at other moments from the reference discrete amplitude in sequence to obtain a difference amplitude array;
the first K difference amplitude data which are arranged from large to small in each group of difference amplitude arrays are selected as change amplitude data;
and taking the discrete frequency data corresponding to the first K difference amplitude values as the change frequency data.
4. The fault type diagnosis method of a rotary machine according to claim 1, wherein the determining the fault type of the rotary machine to be diagnosed based on the frequency stability diagram specifically includes:
judging whether the frequency stability diagram has a stable frequency value or not;
if yes, determining that the fault type of the rotary mechanical equipment to be diagnosed is rotor fault or bearing fault;
if not, determining that the fault type of the rotary mechanical equipment to be diagnosed is irrelevant to the vibration signal, and that the rotor faults and the bearing faults do not exist.
5. The method according to claim 4, wherein when the frequency stability map has a stable frequency value, determining that the fault type of the rotating machine to be diagnosed is a rotor-type fault or a bearing fault, specifically comprising:
when the frequency stability diagram has a stable frequency value, judging whether the stable frequency value is an integer multiple of the rotating frequency;
if yes, determining that the fault type of the rotary mechanical equipment to be diagnosed is a rotor fault;
if not, determining the fault type of the rotary mechanical equipment to be diagnosed as bearing fault.
6. A rotary machine fault type diagnosis system, comprising:
the vibration signal acquisition module is used for acquiring vibration signals of the rotary mechanical equipment to be diagnosed at different moments;
the frequency spectrum data acquisition module is used for acquiring frequency spectrum data of the vibration signal by adopting a frequency spectrum analysis method; the frequency spectrum data comprises frequency data and amplitude data;
the frequency spectrum data dispersing module is used for dispersing the frequency spectrum data to obtain discrete frequency data and discrete amplitude data;
the change frequency data and change amplitude data determining module is used for determining change frequency data and change amplitude data of the vibration signal based on the discrete frequency data and the discrete amplitude data;
the frequency stability diagram drawing module is used for drawing a frequency stability diagram by taking the change frequency data as an abscissa and the change amplitude data as an ordinate;
and the fault type determining module is used for determining the fault type of the rotary mechanical equipment to be diagnosed based on the frequency stability diagram.
7. The rotating machine fault type diagnostic system of claim 6, wherein the spectrum data discretization module comprises:
a discrete frequency data acquisition unit, configured to divide each frequency data into a plurality of groups of frequency values at intervals of N-frequency resolution, and take a first frequency value of each group of frequency values as a discrete frequency value of a current group of frequency values, where the discrete frequency values of each frequency data form the discrete frequency data;
the discrete amplitude data acquisition unit is used for dividing each amplitude data into a plurality of groups of amplitude values at intervals of N times of amplitude values, taking the amplitude statistical value of each group of amplitude values as the discrete amplitude value of the current group of amplitude values, and forming the discrete amplitude data by the discrete amplitude values of each amplitude data.
8. The rotating machine fault type diagnostic system of claim 6, wherein the change frequency data and change amplitude data determination module comprises:
the reference discrete amplitude determining unit is used for taking the discrete amplitude data corresponding to the vibration signal acquired at the earliest moment as a reference discrete amplitude;
the difference amplitude array determining unit is used for sequentially subtracting the discrete amplitude data corresponding to the vibration signals acquired at other moments from the reference discrete amplitude to obtain a difference amplitude array;
the change amplitude data determining unit is used for selecting the first K difference amplitude data which are arranged from large to small in each group of difference amplitude arrays as change amplitude data;
and the change frequency data determining unit is used for taking the discrete frequency data corresponding to the first K difference amplitude values as change frequency data.
9. The rotating machine fault type diagnostic system of claim 6, wherein the fault type determination module comprises:
the judging unit is used for judging whether the frequency stability diagram has a stable frequency value or not;
the fault type determining unit is used for determining that the fault type of the rotary mechanical equipment to be diagnosed is a rotor fault or a bearing fault when the frequency stability diagram has a stable frequency value;
and the result determining unit is used for determining that the fault type of the rotary mechanical equipment to be diagnosed is irrelevant to the vibration signal when the frequency stability diagram does not have a stable frequency value, and rotor faults and bearing faults do not exist.
10. The rotary machine fault type diagnosis system according to claim 9, wherein the fault type determination unit includes:
a judging subunit, configured to judge whether the stable frequency value is an integer multiple of the frequency conversion;
a rotor type fault determining subunit, configured to determine that a fault type of the rotating mechanical device to be diagnosed is a rotor type fault when the stable frequency value is an integer multiple of a rotation frequency;
and the bearing fault determining subunit is used for determining that the fault type of the rotary mechanical equipment to be diagnosed is a bearing fault when the stable frequency value is not an integral multiple of the rotating frequency.
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