CN106017921A - Rotating machine fault diagnosis method based on peak index - Google Patents
Rotating machine fault diagnosis method based on peak index Download PDFInfo
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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
- G01M13/00—Testing of machine parts
- G01M13/02—Gearings; Transmission mechanisms
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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
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Abstract
The invention provides a rotating machine fault diagnosis method based on a peak index. A peak index is constructed based on the idea of signal separation to overcome the shortcomings of the traditional peak index diagnosis technology and improve the accuracy and reliability of diagnosis. Based on a standard vibration signal, vibration signals acquired in real time are divided into trouble-free vibration signals and mixed signals. A peak index is constructed using mixed signals and trouble-free vibration signals, the peak index is more sensitive to fault diagnosis, and weak fault feature signals can be better detected through signal change. There is less overlap between the value range of peak index under normal operation of rotating mechanical equipment and the value range of peak index under failure of the rotating mechanical equipment, and the peak index changes apparently under different conditions. The peak index is sensitive to the fault of an eccentric shaft, and the fault can be well differentiated from other faults. Rotating machine fault diagnosis is highly precise and reliable.
Description
Technical field
The present invention relates to a kind of rotary machinery fault diagnosis method, particularly to a kind of rotary machinery fault diagnosis method based on peak index, belong to fault diagnosis and signal processing analysis technical field.
Background technology
Large rotating machinery equipment (such as steam turbine, swivel bearing, compressor etc.) is the key equipment of the important engineering fields such as oil, chemical industry, machine-building, Aero-Space, rotating machinery is just towards maximization, automatization, the direction development of precise treatment, its the Nomenclature Composition and Structure of Complexes also becomes to become increasingly complex, the probability broken down is the most increasing, and therefore the requirement to the safety and reliability of large rotating machinery equipment is more and more higher.
But, during large rotating machinery device fails, often there is substantial amounts of non-linear, random, the information that can not travel through in vibration monitoring signal, brings the biggest difficulty to the analysis of fault-signal and the diagnosis of rotating machinery fault.
The rotary machinery fault diagnosis of prior art is based primarily upon vibration signal and is analyzed, and typically use temporal analysis, by the probability density function analysis to mechanical oscillation signal, be deduced in amplitude domain has dimension index and dimensionless index, has dimension index such as average, root-mean-square value etc.；Dimensionless index such as peak index, margin index, pulse index etc..
In actual applications, prior art have dimension index sensitive to fault signature, its numerical value can rise along with the development of fault, simultaneously because of working condition, changes such as the change of load, rotating speed etc., and is easily affected by environmental disturbances, and performance is not sufficiently stable.
Peak index in dimensionless index is insensitive for the disturbance in vibration signal, sensitive to soft fault.Especially, peak index is insensitive to the amplitude of vibration signal and the change of frequency, i.e. little with the working condition relation of machine, only depends on the shape of probability density function, and therefore peak index is widely used in rotary machinery fault diagnosis.
But, prior art uses peak index diagnosis to be a kind of technical method that " peak parameters " is used for equipment fault diagnosis, peak index is utilized mainly to have some problem following to the fault diagnosing rotating machinery: one is that the thought not using Signal separator builds peak index, not to standard vibration Signal separator, cannot preferably embody the fault of rotating machinery, the diagnosis to fault is insensitive；Two is that peak index is just reliable when signal has obvious pulsating nature, when the fault of rotating machinery constantly extends, after peak value progressively reaches ultimate value, root-mean-square value starts to increase, and peak index progressively reduces, until size when returning to fault-free, therefore peak index exists breakdown judge inefficacy, particularly some faint fault-signal reactions are insensitive, are easily generated erroneous judgement, and the accuracy and reliability of rotary machinery fault diagnosis is poor；Three be the vibration signal using running-in period as standard vibration signal, do not account for rotating machinery noise in initial operating stage vibration signal serious, be not suitable for the problem as standard vibration signal, tracing trouble is inaccurate.
Summary of the invention
For the deficiencies in the prior art, the present invention provides a kind of rotary machinery fault diagnosis method based on peak index, the shortcoming overcoming conventional peak index diagnostic techniques, improve the accuracy and reliability of diagnosis, building peak index by the thought of Signal separator, due to the separation to standard vibration signal, remaining mixed signal can preferably embody the fault of rotating machinery, diagnosis to fault is more sensitive, and the diagnostic result drawn can diagnose the fault of rotating machinery exactly.
For reaching above technique effect, the technical solution adopted in the present invention is as follows:
A kind of rotary machinery fault diagnosis method based on peak index, comprises the following steps:
(1) gathering rotating machinery normal operational parameters after running running-in period by vibration acceleration sensor, described normal operational parameters is by sampling frequency fsThe fault-free vibration signal s gathered0(t) (t=0,1 ..., T-1)；
(2) to fault-free vibration signal s0T () obtains standard vibration signal s (t) after being normalized；
(3) standard vibration signal s (t) is done fast Fourier transform (FFT) obtain standard vibration frequency-region signal S (k) (k=0,1 ..., K-1)；
(4) needing operational factor during fault diagnosis by vibration acceleration sensor collection rotating machinery, operational factor during described fault diagnosis is by sampling frequency fsOperating Real-time Collection vibration signal z (t) of Real-time Collection rotating machinery (t=0,1 ..., T-1)；
(5) Real-time Collection vibration signal z (t) is done fast Fourier transform (FFT) vibrated in real time frequency-region signal Z (k) (k=0,1 ..., K-1)；
(6) standard vibration frequency-region signal S (k) taking complex conjugate is S (k)*, by Z (k) and S (k)*Be multiplied obtain Y (k) (k=0,1 ..., K-1), then to Y (k) (k=0,1 ..., K-1) do inverse fast Fourier transform (IFFT) and obtain two signals Z (k) and S (k)*Correlation function I (t) (t=0,1 ..., T-1)；
(7) at t=0,1, ..., T-1 takes the mould of correlation function I (t) | I (t) |, time point corresponding to the maximum of | I (t) | is Real-time Collection vibration signal and the delay time T of standard vibration signal, τ=argmax | I (t) |；
(8) the correlation coefficient c, c=E [z (t) s (t-τ)] of the standard vibration signal s (t-τ) after seeking Real-time Collection vibration signal z (t) and postponing；
(9) calculating mixed signal y (t), y (t) is that fault signature extracts signal and the mixed signal of noise, y (t)=z (t)-cs (t-τ)；
(10) peak index is calculated
A kind of rotary machinery fault diagnosis method based on peak index, further, according to peak index CysValue, it is judged that whether rotating machinery breaks down and fault category, and following interval value includes boundary value:
Peak index CysValue between 2.1986 to 3.7719 time, rotating machinery normal operation；
Peak index CysValue between 3.8474 to 6.0233 time, it is considered to rotating machinery there occurs and splits axle fault；
Peak index CysValue between 3.8830 to 6.1981 time, it is considered to rotating machinery there occurs cambered axle fault；
Peak index CysValue between 3.9094 to 7.5683 time, it is considered to rotating machinery there occurs eccentric shaft fault；
Peak index CysValue between 4.1663 to 7.3144 time, it is considered to rotating machinery there occurs and splits axle+cambered axle fault；
Peak index CysValue between 3.9924 to 7.4869 time, it is considered to rotating machinery there occurs and splits axle+eccentric shaft fault；
Peak index CysValue between 4.5938 to 6.2757 time, it is considered to rotating machinery there occurs cambered axle+eccentric shaft fault；
Peak index CysValue between 4.0169 to 6.1841 time, it is considered to rotating machinery there occurs and splits axle+cambered axle+eccentric shaft fault.
A kind of rotary machinery fault diagnosis method based on peak index, further, fast Fourier transform (FFT) uses the fast algorithm of finite sequence discrete Fourier transform (DFT), described fast Fourier transform (FFT) uses decimation in frequency algorithm, according to parity packet and utilizes periodicity and symmetry to calculate sequence in frequency domain.
A kind of rotary machinery fault diagnosis method based on peak index, further, each frequency component, by the frequency spectrum in Y (k) frequency domain, is transformed into time domain sinusoidal wave by inverse fast Fourier transform (IFFT), more all superposition obtains correlation function I (t).
A kind of rotary machinery fault diagnosis method based on peak index, further, step (1) and step (4) are one group by 1024 points and sample, and sample frequency is 1000Hz.
Compared with prior art, it is an advantage of the current invention that:
1. a kind of based on peak index the rotary machinery fault diagnosis method that the present invention provides, by standard vibration signal, the characteristic of rotating machines vibration signal of Real-time Collection being divided into fault-free vibration signal and mixed signal, wherein mixed signal contains fault characteristic signals and Gaussian noise.Peak index is built with mixed signal and fault-free vibration signal, the thought employing Signal separator builds peak index, due to the separation to standard vibration signal, remaining mixed signal can preferably embody the fault of rotating machinery, diagnosis to fault is more sensitive, compared with existing peak index, it is better able to the change-detection Weak fault characteristic signal by signal.
2. a kind of based on peak index the rotary machinery fault diagnosis method that the present invention provides, by a series of mathematical operation, when making rotating machinery properly functioning and break down, the span relative superposition of the peak index obtained is few, under different conditions, peak index change is substantially, localized delamination to bearing in rotating machinery, the faults such as impression are very sensitive, and the abswolute level impact of the most vibrated signal, it is not easy to produce erroneous judgement, more sensitive to eccentric shaft failure ratio especially, well this fault can be come with other fault distinguish, reaction is fast, sensitivity is good, the accuracy and reliability of rotary machinery fault diagnosis is higher.
3. a kind of based on peak index the rotary machinery fault diagnosis method that the present invention provides, use running-in period terminate after vibration signal normalization after as standard vibration signal, consider rotating machinery noise in initial operating stage vibration signal serious, it is not suitable for the problem as standard vibration signal, fault-signal is quick on the draw, tracing trouble more accurate and effective.
Accompanying drawing explanation
Fig. 1 is the flow chart of a kind of based on peak index the rotary machinery fault diagnosis method that the present invention provides.
Detailed description of the invention
Below in conjunction with the accompanying drawings, the technical scheme of a kind of based on peak index the rotary machinery fault diagnosis method that the present invention provides is conducted further description, makes those skilled in the art can be better understood from the present invention and can be practiced.
Seeing Fig. 1 and Biao 1, the present invention provides a kind of rotary machinery fault diagnosis method based on peak index, comprises the following steps:
(1) gathering rotating machinery normal operational parameters after running running-in period by vibration acceleration sensor, normal operational parameters is by sampling frequency fsThe fault-free vibration signal s gathered0(t) (t=0,1 ..., T-1), it is one group by 1024 points and samples, peak index takes 50 groups, takes the minima of peak index 50 groups and the maximum span as this peak index；
(2) to fault-free vibration signal s0T () obtains standard vibration signal s (t) after being normalized, use after the vibration signal normalization after running-in period as standard vibration signal, consider rotating machinery noise in initial operating stage vibration signal serious, it is not suitable for the problem as standard vibration signal, fault-signal is quick on the draw, tracing trouble more accurate and effective；
(3) standard vibration signal s (t) is done fast Fourier transform (FFT) obtain standard vibration frequency-region signal S (k) (k=0,1 ..., K-1)；
(4) needing operational factor during fault diagnosis by vibration acceleration sensor collection rotating machinery, operational factor during described fault diagnosis is by sampling frequency fsOperating Real-time Collection vibration signal z (t) of Real-time Collection rotating machinery (t=0,1 ..., T-1)；
(5) Real-time Collection vibration signal z (t) is done fast Fourier transform (FFT) vibrated in real time frequency-region signal Z (k) (k=0,1 ..., K-1)；
(6) standard vibration frequency-region signal S (k) being asked conjugate complex number is S (k)*, two real parts of conjugate complex number are equal, imaginary part opposite number each other.
When imaginary part is not zero, conjugate complex number is exactly that real part is equal, and imaginary part is contrary, if imaginary part is zero, its conjugate complex number is exactly self.By Z (k) and S (k)*Be multiplied obtain Y (k) (k=0,1 ..., K-1), then to Y (k) (k=0,1 ..., K-1) do inverse fast Fourier transform (IFFT) and obtain two signals Z (k) and S (k)*Correlation function I (t) (t=0,1 ..., T-1)；
(7) at t=0,1, ..., T-1 takes the mould of correlation function I (t) | I (t) |, time point corresponding to the maximum of | I (t) | is Real-time Collection vibration signal and the delay time T of standard vibration signal, τ=argmax | I (t) |；
(8) the correlation coefficient c of the standard vibration signal s (t-τ) after seeking Real-time Collection vibration signal z (t) and postponing, c is the mathematic expectaion of z (t) s (t-τ), c=E [z (t) s (t-τ)]；
(9) calculate z (t)-cs (t-τ) obtaining y (t), y (t) is that fault signature extracts signal and the mixed signal of noise；
Real-time Collection vibration signal z (t)=cs (t-τ)+x (t)+ν (t), time τ is the time delay of real-time vibration signal and standard signal, ν (t) is Gaussian noise, x (t) is fault characteristic signals, c is correlation coefficient, y (t) is that fault signature extracts signal and the mixed signal of noise, y (t)=x (t)+υ (t), Real-time Collection vibration signal z (t)=cs (t-τ)+y (t)；
By standard vibration signal s (t), Real-time Collection vibration signal z (t) is divided into fault-free vibration signal and mixed signal y (t), mixed signal contains fault characteristic signals x (t) and Gaussian noise ν (t), peak index is built with mixed signal y (t) and fault-free vibration signal, have fault diagnosis sensitiveer, compared with existing peak index, it is better able to the change-detection Weak fault characteristic signal by signal；
(10) peak index is calculatedE is mathematic expectaion；
As a kind of preferred version, a kind of based on peak index the rotary machinery fault diagnosis method that the present invention provides, according to peak index CysValue, it is judged that whether rotating machinery breaks down and fault category, and following interval value includes boundary value:
Peak index CysValue between 2.1986 to 3.7719 time, rotating machinery normal operation；
Peak index CysValue between 3.8474 to 6.0233 time, it is considered to rotating machinery there occurs and splits axle fault；
Peak index CysValue between 3.8830 to 6.1981 time, it is considered to rotating machinery there occurs cambered axle fault；
Peak index CysValue between 3.9094 to 7.5683 time, it is considered to rotating machinery there occurs eccentric shaft fault；
Peak index CysValue between 4.1663 to 7.3144 time, it is considered to rotating machinery there occurs and splits axle+cambered axle fault；
Peak index CysValue between 3.9924 to 7.4869 time, it is considered to rotating machinery there occurs and splits axle+eccentric shaft fault；
Peak index CysValue between 4.5938 to 6.2757 time, it is considered to rotating machinery there occurs cambered axle+eccentric shaft fault；
Peak index CysValue between 4.0169 to 6.1841 time, it is considered to rotating machinery there occurs and splits axle+cambered axle+eccentric shaft fault.
Table 1
A kind of based on peak index the rotary machinery fault diagnosis method that the present invention provides, when rotating machinery is properly functioning and breaks down, peak index change is substantially, localized delamination to bearing in rotating machinery, the faults such as impression are very sensitive, and the abswolute level impact of the most vibrated signal, it is not easy to produce erroneous judgement, more sensitive to eccentric shaft failure ratio especially, well this fault can be come with other fault distinguish, reaction is fast, sensitivity is good, and the accuracy and reliability of rotary machinery fault diagnosis is higher.
As a kind of preferred version, a kind of based on peak index the rotary machinery fault diagnosis method that the present invention provides, fast Fourier transform (FFT) uses the fast algorithm of finite sequence discrete Fourier transform (DFT), fast Fourier transform (FFT) uses decimation in frequency algorithm, according to parity packet and utilizes periodicity and symmetry to calculate sequence in frequency domain.
As a kind of preferred version, a kind of based on peak index the rotary machinery fault diagnosis method that the present invention provides, inverse fast Fourier transform (IFFT) is by the frequency spectrum in Y (k) frequency domain, each frequency component is transformed into time domain sinusoidal wave, more all superposition obtains correlation function I (t).Fast Fourier transform is greatly improved the operation efficiency of computer, decreases operation times.Discrete Fourier transform and inverse transformation are as follows:
Wherein 0≤k≤N-1, makes W=e-j2 π /N, then the discrete Fourier transform of N point sequence is:
WknHave periodically: Wkn=Wn (k+N)=Wk(n+N)
WknThere is symmetry: Wkn=-Wkn+N2
By periodically simplifying discrete Fourier transform with symmetry.
As a kind of preferred version, a kind of based on peak index the rotary machinery fault diagnosis method that the present invention provides, step (1) and step (4) be one group by 1024 points and sample, and sample frequency is 1000Hz.
A kind of peak index that the present invention provides sensitivity under different faults is different, more sensitive to eccentric shaft failure ratio, well this fault can be come with other fault distinguish, can well reflect different faults characteristic information, the peak index of structure is to be constituted with ratio, has the advantages that not affected by machine operating mode, localized delamination to bearing in rotating machinery, the faults such as impression are very sensitive, and the abswolute level impact of the most vibrated signal, it is not easy to produce erroneous judgement.
Above-mentioned embodiment is the present invention preferably embodiment; but embodiments of the present invention are not limited by above-mentioned embodiment; the change made under other any spirit without departing from the present invention and principle, modify, substitute, combine, simplify; all should be the substitute mode of equivalence, within being included in protection scope of the present invention.
Claims (5)
1. a rotary machinery fault diagnosis method based on peak index, it is characterised in that comprise the following steps:
(1) rotating machinery normal operational parameters after running running-in period, described normal fortune are gathered by vibration acceleration sensor
Line parameter is by sampling frequency fsThe fault-free vibration signal s gathered0(t) (t=0,1 ..., T-1)；
(2) to fault-free vibration signal s0T () obtains standard vibration signal s (t) after being normalized；
(3) standard vibration signal s (t) is done fast Fourier transform and obtain standard vibration frequency-region signal
S (k) (k=0,1 ..., K-1)；
(4) operational factor during fault diagnosis is needed by vibration acceleration sensor collection rotating machinery, during described fault diagnosis
Operational factor be by sampling frequency fsReal-time Collection rotating machinery operating Real-time Collection vibration signal
Z (t) (t=0,1 ..., T-1)；
(5) Real-time Collection vibration signal z (t) is done fast Fourier transform and vibrated frequency-region signal Z (k) in real time
(k=0,1 ..., K-1)；
(6) standard vibration frequency-region signal S (k) taking complex conjugate is S (k)*, by Z (k) and S (k)*It is multiplied and obtains Y (k)
(k=0,1 ..., K-1), then to Y (k) (k=0,1 ..., K-1) do inverse fast Fourier transform and obtain two signals Z (k) and S (k)*
Correlation function I (t) (t=0,1 ..., T-1)；
(7) at t=0,1 ..., T-1 takes the mould of correlation function I (t) | I (t) |, the time point corresponding to the maximum of | I (t) |
For Real-time Collection vibration signal and the delay time T of standard vibration signal, τ=argmax | I (t) |；
(8) the correlation coefficient c of the standard vibration signal s (t-τ) after seeking Real-time Collection vibration signal z (t) and postponing,
C=E [z (t) s (t-τ)]；
(9) calculating mixed signal y (t), y (t) is that fault signature extracts signal and the mixed signal of noise,
Y (t)=z (t)-cs (t-τ)；
(10) peak index is calculated
A kind of rotary machinery fault diagnosis method based on peak index the most according to claim 1, it is characterised in that root
According to described peak index CysValue, it is judged that whether rotating machinery breaks down and fault category, and following interval value all includes boundary value:
Peak index CysValue between 2.1986 to 3.7719 time, rotating machinery normal operation；
Peak index CysValue between 3.8474 to 6.0233 time, it is considered to rotating machinery there occurs and splits axle fault；
Peak index CysValue between 3.8830 to 6.1981 time, it is considered to rotating machinery there occurs cambered axle fault；
Peak index CysValue between 3.9094 to 7.5683 time, it is considered to rotating machinery there occurs eccentric shaft fault；
Peak index CysValue between 4.1663 to 7.3144 time, it is considered to rotating machinery there occurs and splits axle+cambered axle fault；
Peak index CysValue between 3.9924 to 7.4869 time, it is considered to rotating machinery there occurs and splits axle+eccentric shaft fault；
Peak index CysValue between 4.5938 to 6.2757 time, it is considered to rotating machinery there occurs cambered axle+eccentric shaft fault；
Peak index CysValue between 4.0169 to 6.1841 time, it is considered to rotating machinery there occurs split axle+cambered axle+eccentric shaft therefore
Barrier.
A kind of rotary machinery fault diagnosis method based on peak index the most according to claim 1, it is characterised in that: institute
State the fast Fourier transform in step (3) and step (5) and use the fast algorithm of finite sequence discrete Fourier transform, institute
State fast Fourier transform and use decimation in frequency algorithm, in frequency domain, sequence according to parity packet and is utilized periodicity and symmetry
Calculate.
A kind of rotary machinery fault diagnosis method based on peak index the most according to claim 1, it is characterised in that: institute
State the inverse fast Fourier transform in step (7) and pass through the frequency spectrum in Y (k) frequency domain, each frequency component is transformed into time domain sinusoidal
Ripple, more all superposition obtains correlation function I (t).
5. according to a kind of based on peak index the rotary machinery fault diagnosis method described in claim 1 or 4, it is characterised in that:
Described step (1) and step (4) are one group by 1024 points and sample, and sample frequency is 1000Hz.
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| CN117969050A (en) * | 2023-09-04 | 2024-05-03 | 重庆数智融合创新科技有限公司 | Equipment fault diagnosis method and system based on probability statistics |
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