CN115808236A - Fault on-line monitoring and diagnosing method and device for marine turbocharger and storage medium - Google Patents
Fault on-line monitoring and diagnosing method and device for marine turbocharger and storage medium Download PDFInfo
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Abstract
The application discloses a method, a device and a storage medium for online monitoring and diagnosing faults of a marine turbocharger, wherein the method comprises the following steps: acquiring a vibration signal of a marine turbocharger; performing time-frequency analysis on the vibration signal by using an improved linear frequency modulation method to obtain a time-frequency conversion signal; synchronously compressing the time-frequency transformation signal to obtain a compressed time-frequency signal; obtaining a reconstruction time domain vibration signal according to the compressed time frequency signal, and extracting a fault characteristic parameter of the turbocharger according to the reconstruction time domain vibration signal; and carrying out fault diagnosis on the marine turbocharger according to the fault characteristic parameters. The invention can carry out accurate time-frequency analysis on the strong time-varying vibration signal of the marine turbocharger, and carry out fault monitoring and diagnosis on the marine turbocharger according to the time-frequency analysis result, thereby effectively excavating the essential fault characteristics of the marine turbocharger.
Description
Technical Field
The invention relates to the technical field of large-scale material management, in particular to a method and a device for online monitoring and diagnosing faults of a marine turbocharger, electronic equipment and a computer readable storage medium.
Background
Turbochargers are an important component of marine diesel engines and, in the event of a failure, have a significant impact on diesel engine performance. The severe working environment and the complex system composition cause the marine turbocharger to be easy to break down in the operation process, thereby influencing the safe operation of a marine main engine and even the whole ship. The fault early warning and diagnosis can effectively prevent and avoid serious accidents of equipment, and vibration analysis is a common method for monitoring the state of the rotary machine and diagnosing faults and can be used for diagnosing the faults of the turbocharger.
The transient frequency and amplitude of the vibration component of the marine turbocharger are rapidly changed along with the variable operation condition of the marine turbocharger, and the rigidity of the rotor support of the turbocharger is unstable, so that the vibration signal presents strong amplitude, frequency modulation characteristics and non-stationarity. For non-stationary signals, the Time-domain signal is typically extended to a Time-Frequency representation (TFR) by Time-Frequency Analysis (TFA) to analyze the Time-varying characteristics of the signal. The classical time-frequency analysis methods comprise short-time Fourier transform and wavelet transform, and are limited by the Heisenberg inaccurate measurement principle, time-frequency results generated by the methods are not aggregated, energy is fuzzy and serious, only approximate outlines of signal components can be seen, the amplitude values of the signal components have larger difference compared with real values, and accurate time-frequency characteristic description cannot be provided for time-varying signals, so that the prior art cannot perform online fault monitoring and diagnosis on the marine turbocharger through the time-frequency analysis results of vibration signals.
Therefore, it is necessary to provide an online monitoring and diagnosing method for faults of a marine turbocharger, which can perform accurate time-frequency analysis on a strong time-varying vibration signal of the marine turbocharger, and perform fault monitoring and diagnosis on the marine turbocharger according to a time-frequency analysis result.
Disclosure of Invention
In view of the above, it is necessary to provide a method, an apparatus, an electronic device and a computer-readable storage medium for online monitoring and diagnosing a fault of a marine turbocharger, so as to solve the problems that a time-frequency result generated by an existing vibration signal analysis method is not aggregated, energy is blurred seriously, and an accurate time-frequency analysis cannot be performed on a strong time-varying vibration signal of the marine turbocharger, so that online fault monitoring and diagnosing of the marine turbocharger are inaccurate.
In order to solve the above problems, the present invention provides an online fault monitoring and diagnosing method for a marine turbocharger, comprising:
acquiring a vibration signal of a marine turbocharger;
performing time-frequency analysis on the vibration signal by using an improved linear frequency modulation conversion method to obtain a time-frequency conversion signal;
synchronously compressing the time-frequency transformation signal to obtain a compressed time-frequency signal;
obtaining a reconstruction time domain vibration signal according to the compressed time frequency signal, and extracting a fault characteristic parameter of the turbocharger according to the reconstruction time domain vibration signal;
and carrying out fault diagnosis on the marine turbocharger according to the fault characteristic parameters.
Further, the improved chirp conversion method includes:
and taking the optimal demodulation rate corresponding to the minimum value of the Rayleigh entropy and the sum of the signal to noise ratio as the demodulation rate of the linear frequency modulation transformation.
Further, the step of synchronously compressing the time-frequency transformation signal to obtain a compressed time-frequency signal includes:
determining the frequency bandwidth and the central frequency point of the time-frequency conversion signal;
and compressing the time-frequency conversion signal according to the frequency bandwidth and the central frequency point to obtain a compressed time-frequency signal.
Further, obtaining a reconstructed time domain vibration signal according to the compressed time frequency signal includes:
and reconstructing a component time domain signal of a preset frequency multiplication number from the compressed time frequency signal to obtain a reconstructed time domain vibration signal.
Further, extracting a fault characteristic parameter of the turbocharger according to the reconstructed time domain vibration signal includes:
extracting a vibration effective value and a vibration phase according to the reconstructed time domain vibration signal;
and obtaining a vibration fault characteristic parameter according to the vibration effective value and the vibration phase.
Further, the method further comprises:
acquiring an axis track signal and a rotating speed signal of the marine turbocharger;
extracting variation fault characteristic parameters of the marine turbocharger according to the axis track signal and the rotating speed signal;
the variation fault characteristic parameter is used for representing the difference between the running state and the normal state of the turbocharger.
Further, the fault diagnosis of the marine turbocharger according to the fault characteristic parameters comprises:
determining the fault type and the parameter deviation degree according to the fault characteristic parameters;
and determining the fault severity of the turbocharger according to the fault type and the parameter deviation degree.
The invention also provides a device for online monitoring and diagnosing the faults of the marine turbocharger, which comprises:
the signal acquisition module is used for acquiring a vibration signal of the marine turbocharger;
the time-frequency analysis module is used for carrying out time-frequency analysis on the vibration signal by utilizing an improved linear frequency modulation conversion method to obtain a time-frequency conversion signal;
the synchronous compression module is used for synchronously compressing the time-frequency transformation signal to obtain a compressed time-frequency signal;
the characteristic extraction module is used for obtaining a reconstruction time domain vibration signal according to the compressed time-frequency signal and extracting a fault characteristic parameter of the turbocharger according to the reconstruction time domain vibration signal;
and the diagnosis module is used for carrying out fault diagnosis on the marine turbocharger according to the fault characteristic parameters.
The invention also provides an electronic device, which comprises a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the online monitoring and diagnosing method for the fault of the marine turbocharger in any technical scheme is realized.
The invention also provides a computer readable storage medium, wherein a computer program is stored in the computer readable storage medium, and when the computer program is executed by a processor, the online monitoring and diagnosing method for the faults of the marine turbocharger according to any one of the above technical solutions is realized.
Compared with the prior art, the invention has the beneficial effects that: firstly, acquiring a vibration signal of a marine turbocharger, and performing time-frequency analysis by using an improved linear frequency modulation method to obtain a time-frequency conversion signal; secondly, synchronously compressing the time-frequency conversion signal to obtain a compressed time-frequency signal, and obtaining a reconstructed time-domain vibration signal according to the compressed time-frequency signal; and finally, extracting fault characteristic parameters according to the reconstructed time-frequency vibration signals and carrying out fault diagnosis on the marine turbocharger through the fault characteristic parameters. The method optimizes the demodulation rate on the basis of the existing linear frequency modulation conversion method, and based on the optimal demodulation rate and synchronous compression conversion, compared with the existing time-frequency analysis method, the method has the advantages that the generated time-frequency graph of the vibration signal is clearer, the aggregation of time-frequency energy is good, and the frequency track of the signal can be estimated more accurately. The signal reconstruction is carried out on the signal after the optimal demodulation synchronous compression frequency modulation conversion, the strong time-varying class signal is effectively analyzed, the fault characteristic parameter is extracted from the reconstructed time-domain vibration signal, the characterization capability of the fault characteristic parameter on the fault characteristic is stronger than that of the general fault characteristic parameter, and the fault essential characteristic of the marine turbocharger can be effectively excavated.
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FIG. 1 is a schematic flow chart of an embodiment of a method for online monitoring and diagnosing a fault of a turbocharger for a ship provided by the invention;
fig. 2 is a schematic view of a connection structure of an embodiment of a sensor for collecting data related to a marine turbocharger provided by the invention;
FIG. 3 (a) is a schematic diagram of a time-frequency result of an embodiment of performing a time-frequency analysis on a signal by short-time Fourier transform;
FIG. 3 (b) is a schematic diagram of a time-frequency result of an embodiment of performing time-frequency analysis on a signal by continuous wavelet transform;
FIG. 3 (c) is a schematic diagram of a time-frequency result of an embodiment of performing a time-frequency analysis on a signal by wavelet synchronous compression transform;
FIG. 3 (d) is a schematic diagram of a time-frequency result of an embodiment of performing time-frequency analysis on a signal by using the optimal demodulation synchronous compression FM transform provided by the present invention;
FIG. 4 (a) is a diagram illustrating the results of an embodiment of principal component analysis of common characteristic parameters for turbocharger fault diagnosis;
FIG. 4 (b) is a diagram illustrating the result of principal component analysis of fault signature parameters according to an embodiment of the present invention;
FIG. 5 is a schematic structural diagram of an embodiment of an online fault monitoring and diagnosing apparatus for a marine turbocharger according to the present invention;
fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate preferred embodiments of the invention and together with the description, serve to explain the principles of the invention and not to limit the scope of the invention.
Before the description of the embodiments, the inventive concept of the present application is first explained.
Turbochargers are an important component of marine diesel engines and, in the event of a failure, have a significant effect on the performance of the diesel engine. As a rotary machine, a marine turbocharger generally monitors its operation state by vibration analysis in the early warning and diagnosis of a fault.
A commonly used vibration analysis method in the prior art is fourier transform, which is expressed by a formula:
wherein ,
In order to obtain the result of the fourier transform,
as a matter of time, the time is,
is a function of the frequency of the received signal,
is a time domain signal (i.e. a vibration signal),
in order to be a function of the window,
are natural constants.
However, the fourier transform can only process a steady signal with a frequency that does not change with time, while the variable working conditions of the marine turbocharger enable the instantaneous frequency and amplitude of the vibration component to change rapidly, and the rigidity of the rotor support of the turbocharger has instability, so that the vibration signal presents strong amplitude, frequency modulation characteristics and non-stationarity, and the fourier transform is difficult to process the vibration signal.
For non-stationary signals, the time-frequency analysis can be carried out on the vibration signals by adopting classical linear frequency modulation transformation methods such as short-time Fourier transformation, wavelet transformation and the like, and the signal processing process by the linear frequency modulation transformation is to add a demodulation operator on the basis of the Fourier transformation
And selecting proper demodulation parameters c from the signals to calculate, and obtaining a time-frequency result G by converting the vibration signal s, wherein the time-frequency result G is expressed by a formula as follows:
wherein ,
as a result of the chirp-conversion,
as a matter of time, the time is,
in order to be the frequency of the radio,
in order to be a vibration signal, the vibration signal,
in order to be a function of the window,
in order to achieve a demodulation rate,
is a natural constant and is a natural constant,
in order to rotate the angle of the time-frequency plane,
in order to be able to sample the rate,
in order to be the time of sampling,
is the number of demodulation rates.
After the chirp transformation is performed on the signal, in order to make the time-frequency diagram of the signal clearer and the time-frequency energy aggregation better, the chirp transformation result is usually post-processed by using synchronous compression transformation, so that the time-frequency energy is concentrated around the instantaneous frequency estimation track along the frequency direction, and the time-frequency analysis result is more visual.
The expression for the synchronous compression transform is as follows:
wherein ,
in order to be an instantaneous frequency estimate,
in order to be a function of the dirichlet allocation,
is the frequency.
The synchronous compression transform functions as
The nearby frequency energy is concentrated to
To (3).
However, when the synchronous compression frequency modulation transformation is used for analyzing a high-frequency-weighted signal such as a vibration signal of a marine turbocharger, the energy in time-frequency representation is still dispersed, the time-frequency aggregation property is seriously reduced, the finally obtained transformation result is not aggregated, the energy is fuzzy and serious, only the approximate outline of a signal component can be seen, and the amplitude of the signal component has a larger difference from a true value, so that the synchronous compression frequency modulation transformation cannot be used for fault monitoring and diagnosis of the turbocharger.
In order to solve the problems that in the prior art, after linear transformation and synchronous compression are carried out on vibration analysis of non-stationary signals, energy is fuzzy and the difference between the amplitude of a signal component and a true value is large, the invention focuses on solving the optimal demodulation rate on the basis of the existing linear frequency modulation transformation method, and provides the optimal demodulation synchronous compression frequency modulation transformation for carrying out time-frequency analysis on strong time-varying signals of the marine turbocharger, so that a signal time-frequency diagram is clearer, the energy aggregation is better, and online fault monitoring and diagnosis of the marine turbocharger can be carried out.
The embodiment of the invention provides an online fault monitoring and diagnosing method for a marine turbocharger, which is shown in fig. 1, wherein fig. 1 is a schematic flow chart of the online fault monitoring and diagnosing method for the marine turbocharger, and the method comprises the following steps:
step S101: acquiring a vibration signal of a marine turbocharger;
step S102: performing time-frequency analysis on the vibration signal by using an improved linear frequency modulation conversion method to obtain a time-frequency conversion signal;
step S103: synchronously compressing the time-frequency transformation signal to obtain a compressed time-frequency signal;
step S104: obtaining a reconstruction time domain vibration signal according to the compressed time frequency signal, and extracting a fault characteristic parameter of the turbocharger according to the reconstruction time domain vibration signal;
step S105: and carrying out fault diagnosis on the marine turbocharger according to the fault characteristic parameters.
The method for online monitoring and diagnosing the fault of the marine turbocharger provided by the embodiment comprises the steps of firstly, obtaining a vibration signal of the marine turbocharger, and performing time-frequency analysis by using an improved linear frequency modulation (chirp) conversion method to obtain a time-frequency conversion signal; secondly, synchronously compressing the time-frequency conversion signal to obtain a compressed time-frequency signal, and obtaining a reconstructed time-domain vibration signal according to the compressed time-frequency signal; and finally, extracting fault characteristic parameters according to the reconstructed time-frequency vibration signals and carrying out fault diagnosis on the marine turbocharger through the fault characteristic parameters. The method of the embodiment optimizes the demodulation rate on the basis of the existing linear frequency modulation conversion method, and enables the time-frequency diagram of the vibration signal to be clearer and the aggregation of time-frequency energy to be good on the basis of the optimal demodulation rate and synchronous compression conversion. The signal reconstruction is carried out on the signal after the optimal demodulation synchronous compression frequency modulation conversion, the strong time-varying class signal can be effectively analyzed, the fault characteristic parameter is extracted from the reconstructed time-domain vibration signal, the characterization capability of the fault characteristic parameter on the fault characteristic is stronger than that of the general fault characteristic parameter, and the fault essential characteristic of the marine turbocharger can be effectively excavated.
As a specific example, in step S101, a vibration signal of the marine turbocharger is acquired by a vibration sensor. In order to comprehensively monitor the faults of the turbocharger, the embodiment is also provided with a displacement and rotating speed sensor for acquiring an axle center track signal and a rotating speed signal of the marine turbocharger. The arrangement mode of each sensor is as follows:
arranging a plurality of vibration sensors on a base of the marine turbocharger; arranging a displacement sensor on the rotor shaft to measure an axis track signal; and measuring a rotating speed signal by using a rotating speed sensor of the turbocharger. Each path of sensing signal is collected by LMS (Link management System) collection equipment and is sent to a computer end for signal analysis. As shown in fig. 2, fig. 2 shows a schematic diagram of a connection structure for collecting data related to the marine turbocharger through a sensor.
In practical application, the sensor should be installed at a position where the sensor can be close to the sensor and where the energy attenuation of the rotor vibration signal is small and the signal-to-noise ratio of the signal is high. The vibration of the turbocharger rotor is transmitted to the base and the shell through an oil film and a bearing, and the vibration sensor is arranged at the position, close to the bolt, of the base, so that the signal propagation path is short, the structure of the transmission path is simple, the signal energy attenuation is small, and the signal-to-noise ratio is high.
It should be noted that, the improved chirp conversion method and the synchronous compression are directed to the vibration signal acquired by the vibration sensor, and a manner of directly extracting features is adopted for the features represented by the axis track signal and the rotation speed signal.
Because the energy in the time-frequency representation still appears to be relatively dispersed and the time-frequency aggregation property is seriously reduced when the traditional linear frequency modulation conversion and synchronous compression are applied to the vibration signal of the marine turbocharger, namely a strong time-varying signal, in the step S102, the time-frequency analysis is carried out on the vibration signal by adopting an improved linear frequency modulation conversion method.
As a preferred embodiment, in step S102, the improved chirp conversion method includes:
and taking the optimal demodulation rate corresponding to the minimum value of the Rayleigh entropy and the sum of the signal to noise ratio as the demodulation rate of the linear frequency modulation transformation.
As a specific example, based on the chirp transform theory, the demodulation rate in chirp transform is optimized by targeting two parameters, rayleigh Entropy (RE) and Signal-to-Noise Ratio (SNR). Specifically, the method comprises the following steps:
the chirp transform expression is:
wherein ,
，
Therefore, the number of the first and second electrodes is increased,
is provided with
The value of demodulation rate c is also
Value of each is
The c value is substituted into the formula of synchronous compression frequency modulation conversion:
solving the sum of Rayleigh entropy and signal-to-noise ratio, namely RE + SNR; the value of c when the RE + SNR is minimum is the optimal demodulation rate c of the signal. Namely:
wherein ,
in order to optimally estimate the demodulation rate,
for instantaneous frequency estimation (synchronous compression concentrates time-frequency energy around the instantaneous frequency estimation track along the frequency direction), m is the number of sampling points, and x is the effective signal.
The optimal matching of the demodulation rate and the vibration signal component modulation rate in the synchronous compression linear frequency modulation conversion is achieved through the optimal demodulation rate c.
As a preferred embodiment, in step S103, performing synchronous compression on the time-frequency transform signal to obtain a compressed time-frequency signal, including:
determining the frequency bandwidth and the central frequency point of the time-frequency conversion signal;
and compressing the time-frequency conversion signal according to the frequency bandwidth and the central frequency point to obtain a compressed time-frequency signal.
As a specific example, the frequency bandwidth of the optimal demodulation rate chirp conversion is calculated by the following formula:
wherein ,
in order to estimate the frequency bandwidth,
for the amplitude of the k-th component of the signal,
the instantaneous phase of the kth component of the signal.
And synchronously compressing the result of the linear frequency modulation transformation to form a new time-frequency representation:
instantaneous frequency estimation
Calculated from the following formula:
wherein ,
is the dirichlet function, and Δ is the bandwidth.
As a preferred embodiment, in step S104, obtaining a reconstructed time-domain vibration signal according to the compressed time-frequency signal includes:
and reconstructing a component time domain signal of a preset frequency multiplication number from the compressed time frequency signal to obtain a reconstructed time domain vibration signal.
As a specific embodiment, the preset frequency multiplication number is one frequency multiplication, two frequency multiplication, and nine frequency multiplication, and after performing optimal demodulation, synchronous compression, frequency modulation and conversion on the original vibration signal, time domain signal reconstruction is performed, which is equivalent to decomposing the original vibration signal into three component signals of one frequency multiplication, two frequency multiplication, and nine frequency multiplication, and a formula for reconstructing the time domain vibration signal is as follows:
wherein ,
is the fourier transform of a window function.
It should be noted that the component signals of the first frequency multiplication and the second frequency multiplication have a high degree of correlation with the fault of the turbocharger, and the component signal of the ninth frequency multiplication is selected in this embodiment, it is assumed that the number of the compressor-side blades of the turbocharger is nine main blades and nine auxiliary blades, and if the number of the compressor-side blades of the turbocharger changes, the frequency multiplication component signal corresponding to the number of the blades should be selected.
In order to prove the superiority of the method, the time-frequency analysis effect of the optimal demodulation synchronous compression frequency modulation transformation provided by the invention is shown by specifically simulating a group of strong time-varying signals.
Assume that the emulated signal consists of two components, as follows:
wherein, the sampling frequency is 1000Hz, and the sampling time is 4s.
Fig. 3 (a) -fig. 3 (d) respectively show the time-frequency diagrams obtained by processing the simulation signals by using the short-time fourier transform, the continuous wavelet transform, the wavelet synchronous compression transform and the optimal demodulation synchronous compression frequency modulation transform proposed by the present invention.
As shown in fig. 3 (a), due to the limitation of the heisenberg inaccurate measurement principle and the influence of strong time-varying characteristics of signals, time-frequency results of short-time fourier transform (STFT) are not aggregated, and energy blurring is very serious. Also due to the strongly time-varying nature of the signal, the time-frequency result energy of the continuous wavelet transform is still quite dispersive, and only the approximate profile of the signal components can be seen, as shown in fig. 3 (b). The time-frequency result of the wavelet synchronous compression transform is further improved in the aggregation of time-frequency energy compared with the continuous wavelet transform, as shown in fig. 3 (c).
The optimal demodulation synchronous compression frequency modulation transformation time-frequency diagram provided by the invention has the advantages that the energy is highly concentrated and is not diffused, the frequency trace of the signal component is clearer, and the strong time-varying signals can be effectively analyzed, as shown in fig. 3 (d).
As a preferred embodiment, extracting the fault characteristic parameter of the turbocharger according to the reconstructed time-domain vibration signal includes:
extracting a vibration effective value and a vibration phase according to the reconstructed time domain vibration signal;
and obtaining a vibration fault characteristic parameter according to the vibration effective value and the vibration phase.
As a specific embodiment, the vibration fault characteristic parameters include: the vibration effective value, the vibration energy ratio, the health state effective ratio, the rotor power frequency phase variation coefficient, the vibration effective value variation coefficient, the vibration instantaneous frequency variation coefficient and the power frequency vibration effective value standard deviation.
According to the reconstructed first, second and ninth frequency component signals, the effective value of vibration can be extracted
Ratio between the multiplied frequency components
Ratio of vibration effective value to health status
And 15 vibration fault characteristic parameters such as a rotor power frequency phase variation coefficient, a power frequency vibration effective value variation coefficient, a power frequency vibration instantaneous frequency variation coefficient, a power frequency vibration effective value standard deviation, a rotor unbalance factor, a bearing wear factor and the like. Wherein, the ratio of the vibration effective value to the health state is as follows: the ratio of the actual effective value of the acquired vibration to the data measured by the turbocharger in a healthy state.
The characteristic parameters of each vibration fault are specifically expressed as follows:
1. effective value of industrial frequency (frequency doubling) vibration of rotor
Unit of
。
Wherein the waveform of the vibration signal of the measuring point is recorded as
K =1,2, \ 8230, K, K is the number of signal points,
the waveform of the n-times frequency vibration component of the middle rotor is recorded as
。
2. Rotor double frequency vibration effective value
Unit of
。
3. Rotor nine-frequency-multiplication vibration effective value
Unit of
。
4. Rotor frequency doubling to power frequency vibration energy ratio
And is dimensionless.
5. Rotor frequency multiplication and frequency multiplication vibration energy ratio
And is dimensionless.
6. Rotor frequency nona-octave to power frequency vibration energy ratio
And is dimensionless.
7. Ratio of power frequency vibration effective value to healthy state
And is dimensionless.
wherein ,
the rotor power frequency vibration component waveform of the signal under the healthy state.
8. Ratio of the effective value of double frequency vibration of healthy state
And is dimensionless.
wherein ,
the waveform of the rotor frequency doubling vibration component in the health state signal is obtained.
9. Ratio of the effective value of nine times frequency vibration of the healthy state
And is dimensionless.
wherein ,
the waveform of the rotor frequency-nonaddressed vibration component in the health state signal is obtained.
10. Power frequency phase variation coefficient of rotor
And is dimensionless.
Wherein, the power frequency phases of the rotor in the i and j measuring point signals are respectively
The unit is degree, M =1,2, \8230, M and M are phase point numbers.
11. Variation coefficient of power frequency vibration effective value
And is dimensionless.
12. Power frequency vibration instantaneous frequency variation coefficient
And is dimensionless.
Wherein the instantaneous frequency of the rotor power frequency vibration is recorded as
In Hz.
13. Standard deviation of effective value of power frequency vibration
Unit of
。
wherein ,
the method is characterized in that a measurement signal is divided into a plurality of sections, and the kth section of signal has an n-th frequency multiplication vibration effective value.
14. Rotor imbalance factor
The unit m.
wherein ,
is the rotor power frequency in Hz. The higher the turbocharger speed, the higher it
The larger the value is, therefore
Divided by rotor power frequency
This value
The influence of the rotating speed is eliminated and is only related to the fault degree;
15. wear factor of bearing
And is dimensionless.
As a preferred embodiment, the method further comprises:
obtaining an axis track signal and a rotating speed signal of a marine turbocharger;
extracting variation fault characteristic parameters of the marine turbocharger according to the axis track signal and the rotating speed signal;
the variant fault characteristic parameter is used for characterizing the difference between the running state and the normal state of the turbocharger.
As a specific embodiment, the variant fault characteristic parameters include:
1. coefficient of fluctuation of supercharger speed
Dimensionless。
Wherein the supercharger rotor speed is recorded
Wherein K =1,2, \8230, K is the number of signal points in r/min.
2. Coefficient of variation of rotor axis locus abscissa
And is dimensionless.
Wherein, the transverse and longitudinal displacement of the axial center track of the supercharger rotor is recorded as
、
Wherein K =1,2, \ 8230, K and K are signal point numbers and the unit is mum.
3. Coefficient of variation of rotor axis locus ordinate
And is dimensionless.
And calculating the 3 variation fault characteristic parameters and the 15 vibration fault characteristic parameters, comparing the calculation result with the criterion of each characteristic parameter, and judging the working state of the turbocharger from the mechanism.
It should be noted that the criterion of each characteristic parameter is obtained as follows:
recording characteristic parameters of common working condition multi-working cycle vibration, an axis track and a rotating speed signal under the normal state of the turbocharger, circularly averaging the characteristic parameters of the same characteristic parameter and the same working condition multi-working cycle, and taking the characteristic parameters with stable normal state as the criterion of fault diagnosis.
In a preferred embodiment, the fault diagnosis of the marine turbocharger according to the fault characteristic parameter includes:
determining the fault type and the parameter deviation degree according to the fault characteristic parameters;
and determining the fault severity of the turbocharger according to the fault type and the parameter deviation degree.
As a specific embodiment, during the operation of the turbocharger, the optimal demodulation synchronous compression frequency modulation conversion is carried out on the signal on line, and the signal is calculated on line
The method comprises the steps of weighing 18 characteristic parameters, identifying and judging fault types of the turbocharger by integrating judgment results of the fault characteristic parameters, and diagnosing fault severity according to the degree of deviation of the characteristic parameters from criteria. The relation between each characteristic parameter and different faults and different fault degrees is obtained from the relevant research results in advance, and the monitoring and diagnosing knowledge can be directly applied to different types of turbochargers after being verified.
It should be noted that, when diagnosing a fault by using a vibration signal of a supercharger, principal Component Analysis (PCA) is generally used to check the capability of the extracted characteristic parameters to characterize the fault. After the conventional general characteristic parameters are extracted by PCA, the aggregation degree of samples of the same fault type is not high, partial faults can be overlapped, and effective classification of typical faults of the turbocharger is difficult to realize. However, after the fault characteristic parameters constructed by the method are extracted by PCA, the same fault types are gathered, and the different fault samples are distinguished obviously, which shows that the extracted characteristic parameters can effectively excavate the essential fault characteristics of the turbocharger.
The feature parameters extracted in the present embodiment will be described below with respect to the capability of characterizing a failure of a turbocharger by a principal component analysis method. The principal component analysis method is based on the idea of linear transformation, the dimension of data is reduced through orthogonal transformation, the characteristics of the data are represented by a small amount of information so as to realize the dimension reduction of the data and reserve the main information characteristics of the data, and the visualization is realized by mapping the data from an original space to a two-dimensional space through a PCA analysis method.
The data used for verification adopts fault simulation test data, specifically carries out fault simulation test on a turbocharger test bench, and the specific test conditions are as follows: 2 faults of normal, slight dynamic unbalance, serious dynamic unbalance and dynamic unbalance superposition bearing abrasion simultaneously occur under the working condition of 60000r/min, 37500r/min, 40000 r/min, \8230 \ 8230 `.
And performing principal component analysis on the test data. Common characteristic parameters common to turbocharger fault diagnosis are shown in table 1.
TABLE 1 common general characteristic parameters for turbocharger fault diagnosis
The result of performing PCA extraction on the feature parameters in table 1 is shown in fig. 4 (a). The normal state samples are not gathered in the distribution of the two-dimensional space, the splitting is serious, and the gathering degree of the samples of the same fault type is not high after the data set is extracted by the general characteristic PCA. In fig. 4 (a), the rotor imbalance is very close to the double fault, even if part of the data is overlapped, and the sample characteristics are low in discrimination. The results indicate that the general turbocharger characteristics shown in table 1 make it difficult to achieve an effective classification of typical turbocharger faults.
The collected turbocharger data is processed through the optimal demodulation synchronous compression frequency modulation conversion and reconstructed signals, fault characteristic parameters are extracted according to the reconstructed signals, the characteristic parameter visualization result is shown in fig. 4 (b), in the fig. 4 (b), the intervals among different fault samples are large, the distinction is obvious, the same fault types are gathered, and the condition that the different fault types are crossed does not occur. The extracted characteristic parameters can effectively mine the essential fault characteristics of the turbocharger and can effectively classify the states of the turbocharger.
In addition, it can be seen from fig. 4 (b) that the extracted feature parameters are not affected by the change of the working conditions, that is, under different working conditions of the turbocharger, a feature matrix with excellent performance can be obtained by using the proposed feature parameter construction method, and the problem of performance reduction of the classification features of the turbocharger due to the change of the working conditions is effectively solved.
The present embodiment further provides an online fault monitoring and diagnosing apparatus for a marine turbocharger, as shown in fig. 5, the online fault monitoring and diagnosing apparatus 500 for a marine turbocharger includes:
the signal acquisition module 501 is used for acquiring a vibration signal of the marine turbocharger;
a time-frequency analysis module 502, configured to perform time-frequency analysis on the vibration signal by using an improved chirp transform method to obtain a time-frequency transform signal;
a synchronous compression module 503, configured to perform synchronous compression on the time-frequency transform signal to obtain a compressed time-frequency signal;
the feature extraction module 504 is configured to obtain a reconstructed time-domain vibration signal according to the compressed time-frequency signal, and extract a fault feature parameter of the turbocharger according to the reconstructed time-domain vibration signal;
and the diagnosis module 505 is used for carrying out fault diagnosis on the marine turbocharger according to the fault characteristic parameters.
As shown in fig. 6, the present invention further provides an electronic device 600, which may be a computing device such as a mobile terminal, a desktop computer, a notebook, a palm computer, and a server. The electronic device comprises a processor 601, a memory 602 and a display 603.
The storage 602 may be an internal storage unit of the computer device in some embodiments, such as a hard disk or a memory of the computer device. The memory 602 may also be an external storage device of the computer device in other embodiments, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), etc. provided on the computer device. Further, the memory 602 may also include both internal storage units and external storage devices of the computer device. The memory 602 is used for storing application software installed on the computer device and various data, such as program codes for installing the computer device. The memory 602 may also be used to temporarily store data that has been output or is to be output. In an embodiment, the memory 602 stores an online monitoring and diagnosing method for a fault 604 of a marine turbocharger, and the online monitoring and diagnosing method for a fault 604 of a marine turbocharger can be executed by the processor 601, so as to implement an online monitoring and diagnosing method for a fault of a marine turbocharger according to embodiments of the present invention.
The processor 601 may be a Central Processing Unit (CPU), microprocessor or other data Processing chip in some embodiments, and is used for running program codes stored in the memory 602 or Processing data, such as executing a program of online monitoring and diagnosing faults of the marine turbocharger.
The display 603 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-emitting diode) touch panel, or the like in some embodiments. The display 603 is used to display information at the computer device and to display a visual user interface. The components 601-603 of the computer device communicate with each other via a system bus.
The embodiment also provides a computer readable storage medium, in which a computer program is stored, and when the computer program is executed by a processor, the online monitoring and diagnosing method for the fault of the marine turbocharger according to any one of the above technical solutions is implemented.
According to the computer-readable storage medium and the computing device provided by the above embodiments of the present invention, the detailed description of the implementation of the online fault monitoring and diagnosing method for a marine turbocharger according to the present invention can be referred to, and the method has similar beneficial effects to the online fault monitoring and diagnosing method for a marine turbocharger, and therefore, the detailed description is omitted here.
The invention discloses a method, a device, electronic equipment and a computer readable storage medium for online monitoring and diagnosing faults of a marine turbocharger, wherein firstly, a vibration signal of the marine turbocharger is obtained, and an improved linear frequency modulation method is utilized to carry out time-frequency analysis to obtain a time-frequency conversion signal; secondly, synchronously compressing the time-frequency conversion signal to obtain a compressed time-frequency signal, and obtaining a reconstructed time-domain vibration signal according to the compressed time-frequency signal; and finally, extracting fault characteristic parameters according to the reconstructed time-frequency vibration signals and carrying out fault diagnosis on the marine turbocharger through the fault characteristic parameters.
The invention optimizes the demodulation rate on the basis of the existing linear frequency modulation conversion method, and based on the optimal demodulation rate and synchronous compression conversion, compared with the existing time-frequency analysis method, the generated vibration signal has clearer time-frequency diagram, good aggregation of time-frequency energy and more accurate estimation of the frequency track of the signal. The signal reconstruction is carried out on the signal after the optimal demodulation synchronous compression frequency modulation conversion, the strong time-varying signal is effectively analyzed, the fault characteristic parameter is extracted from the reconstructed time domain vibration signal, the characterization capability of the fault characteristic parameter on the fault characteristic is stronger than that of the general fault characteristic parameter, and the fault essential characteristic of the marine turbocharger can be effectively excavated.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention.
Claims (10)
1. An online fault monitoring and diagnosing method for a marine turbocharger is characterized by comprising the following steps of;
acquiring a vibration signal of a marine turbocharger;
performing time-frequency analysis on the vibration signal by using an improved linear frequency modulation method to obtain a time-frequency conversion signal;
synchronously compressing the time-frequency transformation signal to obtain a compressed time-frequency signal;
obtaining a reconstruction time domain vibration signal according to the compressed time frequency signal, and extracting a fault characteristic parameter of the turbocharger according to the reconstruction time domain vibration signal;
and carrying out fault diagnosis on the marine turbocharger according to the fault characteristic parameters.
2. The marine turbocharger fault online monitoring and diagnosing method according to claim 1, wherein the improved chirp method comprises:
and taking the optimal demodulation rate corresponding to the minimum value of the Rayleigh entropy and the sum of the signal to noise ratio as the demodulation rate of the linear frequency modulation transformation.
3. The online monitoring and diagnosing method for the faults of the marine turbocharger according to claim 1, wherein the step of synchronously compressing the time-frequency transformation signal to obtain a compressed time-frequency signal comprises the following steps:
determining the frequency bandwidth and the central frequency point of the time-frequency conversion signal;
and compressing the time-frequency conversion signal according to the frequency bandwidth and the central frequency point to obtain a compressed time-frequency signal.
4. The online monitoring and diagnosing method for the faults of the marine turbocharger according to claim 1, wherein obtaining a reconstructed time-domain vibration signal according to the compressed time-frequency signal comprises:
and reconstructing a component time domain signal with a preset frequency multiplication number from the compressed time frequency signal to obtain a reconstructed time domain vibration signal.
5. The online fault monitoring and diagnosing method for the marine turbocharger according to claim 1, wherein the step of extracting the fault characteristic parameters of the turbocharger according to the reconstructed time-domain vibration signal comprises the following steps:
extracting a vibration effective value and a vibration phase according to the reconstructed time domain vibration signal;
and obtaining a vibration fault characteristic parameter according to the vibration effective value and the vibration phase.
6. The online fault monitoring and diagnosing method for the marine turbocharger according to claim 5, further comprising:
obtaining an axis track signal and a rotating speed signal of a marine turbocharger;
extracting variation fault characteristic parameters of the marine turbocharger according to the axis track signal and the rotating speed signal;
the variant fault characteristic parameter is used for characterizing the difference between the running state and the normal state of the turbocharger.
7. The online fault monitoring and diagnosing method for the marine turbocharger according to claim 1, wherein the fault diagnosing for the marine turbocharger according to the fault characteristic parameters comprises:
determining the fault type and the parameter deviation degree according to the fault characteristic parameters;
and determining the fault severity of the turbocharger according to the fault type and the parameter deviation degree.
8. The utility model provides a marine turbo charger trouble on-line monitoring diagnostic device which characterized in that includes:
the signal acquisition module is used for acquiring a vibration signal of the marine turbocharger;
the time-frequency analysis module is used for carrying out time-frequency analysis on the vibration signal by utilizing an improved linear frequency modulation conversion method to obtain a time-frequency conversion signal;
the synchronous compression module is used for synchronously compressing the time-frequency transformation signal to obtain a compressed time-frequency signal;
the characteristic extraction module is used for obtaining a reconstruction time domain vibration signal according to the compressed time-frequency signal and extracting a fault characteristic parameter of the turbocharger according to the reconstruction time domain vibration signal;
and the diagnosis module is used for carrying out fault diagnosis on the marine turbocharger according to the fault characteristic parameters.
9. An electronic device, comprising a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the online fault monitoring and diagnosing method for a marine turbocharger according to any one of claims 1 to 7 is implemented.
10. A computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the computer program implements a method for online fault monitoring and diagnosing of a marine turbocharger according to any one of claims 1 to 7.
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