CN115808236A - Marine turbocharger fault online monitoring and diagnosis method, device and storage medium - Google Patents

Abstract

The present application discloses a marine turbocharger fault online monitoring and diagnosis method, device and storage medium. The method includes: obtaining the vibration signal of the marine turbocharger; frequency analysis to obtain a time-frequency transformed signal; synchronously compressing the time-frequency transformed signal to obtain a compressed time-frequency signal; obtain a reconstructed time-domain vibration signal according to the compressed time-frequency signal, and obtain a reconstructed time-domain vibration signal according to the reconstructed time-domain vibration The signal extracts the fault characteristic parameters of the turbocharger; and performs fault diagnosis on the marine turbocharger according to the fault characteristic parameters. The invention can perform accurate time-frequency analysis on the strong time-varying vibration signal of the marine turbocharger, and perform fault monitoring and diagnosis on the marine turbocharger according to the time-frequency analysis results, and can effectively excavate the faults of the marine turbocharger essential features.

Description

Marine turbocharger fault online monitoring and diagnosis method, device and storage medium

technical field

The invention relates to the technical field of large material management, in particular to a marine turbocharger fault online monitoring and diagnosis method, device, electronic equipment and computer-readable storage medium.

Background technique

The turbocharger is an important part of the marine diesel engine, and once it fails, it will have a significant impact on the performance of the diesel engine. The harsh working environment and complex system composition make marine turbochargers prone to failure during operation, which affects the safe operation of the ship's main engine and even the entire ship. Fault early warning and diagnosis can effectively prevent and avoid serious equipment accidents, and vibration analysis is a common method for state monitoring and fault diagnosis of rotating machinery, and can be used for fault diagnosis of turbochargers.

The variable operating conditions of the marine turbocharger cause the instantaneous frequency and amplitude of the vibration component to change rapidly, and the stiffness of the rotor support of the turbocharger is unstable, resulting in strong amplitude and frequency modulation characteristics of the vibration signal and non-stationarity. For non-stationary signals, the time domain signal is usually extended to Time-Frequency Representation (TFR) by Time-Frequency Analysis (TFA) to analyze the time-varying characteristics of the signal. The classic time-frequency analysis methods include short-time Fourier transform and wavelet transform. Due to the limitation of Heisenberg’s uncertainty principle, the time-frequency results generated by these methods are not aggregated, and the energy ambiguity is serious. Only the approximate signal components can be seen. The amplitude of the signal component has a large gap compared with the real value, and it cannot provide an accurate time-frequency feature description for the time-varying signal. As a result, the existing technology cannot use the time-frequency analysis results of the vibration signal to evaluate the marine turbocharger. device for online fault monitoring and diagnosis.

Therefore, it is necessary to propose an on-line monitoring and diagnosis method for marine turbocharger faults, which can perform accurate time-frequency analysis on the strong time-varying vibration signal of marine turbocharger, and analyze the marine turbocharger according to the time-frequency analysis results. Fault monitoring and diagnosis.

Contents of the invention

In view of this, it is necessary to provide a marine turbocharger fault online monitoring and diagnosis method, device, electronic equipment and computer-readable storage medium to solve the time-frequency results generated by existing vibration signal analysis methods. Seriously, it is impossible to conduct accurate time-frequency analysis on the strong time-varying vibration signal of the marine turbocharger, which leads to inaccurate online fault monitoring and diagnosis of the marine turbocharger.

In order to solve the above problems, the present invention provides a marine turbocharger fault online monitoring and diagnosis method, including:

Obtain vibration signals of marine turbochargers;

Perform time-frequency analysis on the vibration signal by using an improved linear frequency modulation transformation method to obtain a time-frequency transformation signal;

performing synchronous compression on the time-frequency transformed signal to obtain a compressed time-frequency signal;

obtaining a reconstructed time-domain vibration signal according to the compressed time-frequency signal, and extracting fault characteristic parameters of the turbocharger according to the reconstructed time-domain vibration signal;

Fault diagnosis is performed on the marine turbocharger according to the fault characteristic parameters.

Further, the improved chirp conversion method includes:

The optimal demodulation rate corresponding to the minimum value of the sum of Rayleigh entropy and SNR is taken as the demodulation rate of chirp conversion.

Further, performing synchronous compression on the time-frequency transformed signal to obtain a compressed time-frequency signal, including:

determining the frequency bandwidth and center frequency of the time-frequency transformed signal;

Compressing the time-frequency transformed signal according to the frequency bandwidth and the center frequency point to obtain a compressed time-frequency signal.

Further, the reconstructed time-domain vibration signal is obtained according to the compressed time-frequency signal, including:

From the compressed time-frequency signal, a component time-domain signal with a preset frequency multiplication number is reconstructed to obtain a reconstructed time-domain vibration signal.

Further, extracting the fault characteristic parameters of the turbocharger according to the reconstructed time-domain vibration signal, including:

According to the reconstructed time-domain vibration signal, extract the vibration effective value and the vibration phase;

The vibration fault characteristic parameters are obtained according to the vibration effective value and the vibration phase.

Further, the method also includes:

Obtain the axis track signal and speed signal of the marine turbocharger;

According to the shaft center trajectory signal and the rotational speed signal, extracting the variable fault characteristic parameters of the marine turbocharger;

The variation fault characteristic parameter is used to characterize the difference between the operating state and the normal state of the turbocharger.

Further, performing fault diagnosis on the marine turbocharger according to the fault characteristic parameters, including:

Determining the type of fault and the degree of parameter deviation according to the characteristic parameters of the fault;

The fault severity of the turbocharger is determined according to the fault type and the degree of parameter deviation.

The present invention also provides a marine turbocharger fault online monitoring and diagnosis device, comprising:

The signal acquisition module is used to acquire the vibration signal of the marine turbocharger;

A time-frequency analysis module, configured to perform time-frequency analysis on the vibration signal using an improved chirp conversion method to obtain a time-frequency conversion signal;

A synchronous compression module, configured to perform synchronous compression on the time-frequency transformed signal to obtain a compressed time-frequency signal;

A feature extraction module, configured to obtain a reconstructed time-domain vibration signal according to the compressed time-frequency signal, and extract fault characteristic parameters of the turbocharger according to the reconstructed time-domain vibration signal;

A diagnostic module, configured to perform fault diagnosis on the marine turbocharger according to the fault characteristic parameters.

The present invention also provides an electronic device, including a processor and a memory, and a computer program is stored in the memory. When the computer program is executed by the processor, the marine turbocharger described in any one of the above technical solutions can be realized. On-line monitoring and diagnosis method of compressor fault.

The present 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 marine turbocharging described in any one of the above technical solutions is realized. On-line monitoring and diagnosis method for device failure.

Compared with the prior art, the beneficial effects of the present invention include: first, obtain the vibration signal of the marine turbocharger, and use the improved chirp transformation method to perform time-frequency analysis to obtain the time-frequency transformation signal; secondly, the time-frequency Transform the signal and perform synchronous compression to obtain the compressed time-frequency signal, and obtain the reconstructed time-domain vibration signal according to the compressed time-frequency signal; finally, extract the fault characteristic parameters according to the reconstructed time-frequency vibration signal and use the fault characteristic parameters to analyze the marine turbocharger. Carry out troubleshooting. The method of the present invention optimizes the demodulation rate on the basis of the existing linear frequency modulation transformation method, and based on the optimal demodulation rate and synchronous compression transformation, compared with the existing time-frequency analysis method, the time of the generated vibration signal The frequency map is clearer, the time-frequency energy is better concentrated, and the frequency trajectory of the signal can be estimated more accurately. Through the signal reconstruction of the signal after optimal demodulation, synchronous compression and frequency modulation transformation, the strong time-varying signal can be effectively analyzed, and the fault characteristic parameters can be extracted from the reconstructed time-domain vibration signal, which can be compared with the general fault characteristic parameters to characterize the fault characteristics The capability is stronger, and the essential characteristics of the faults of marine turbochargers can be effectively excavated.

Description of drawings

Fig. 1 is a schematic flow chart of an embodiment of a marine turbocharger fault online monitoring and diagnosis method provided by the present invention;

Fig. 2 is that the sensor provided by the present invention collects relevant data of a marine turbocharger one is a connection structure schematic diagram of an embodiment;

Fig. 3 (a) is a schematic diagram of time-frequency results of an embodiment of time-frequency analysis of signals through short-time Fourier transform;

Figure 3(b) is a schematic diagram of time-frequency results of an embodiment of time-frequency analysis of signals through continuous wavelet transform;

Fig. 3 (c) is a schematic diagram of time-frequency results of an embodiment of time-frequency analysis of signals through wavelet synchronous compression transform;

Figure 3(d) is a schematic diagram of the time-frequency results of an embodiment of time-frequency analysis of signals through the optimal demodulation synchronous compression FM transformation provided by the present invention;

Fig. 4 (a) is a schematic diagram of results of an embodiment of principal component analysis of common general characteristic parameters of turbocharger fault diagnosis;

Fig. 4(b) is a schematic diagram of the results of an embodiment of principal component analysis of fault characteristic parameters provided by the present invention;

Fig. 5 is a structural schematic diagram of an embodiment of a marine turbocharger fault online monitoring and diagnosis device provided by the present invention;

FIG. 6 is a schematic structural diagram of an embodiment of an electronic device provided by the present invention.

Detailed ways

Preferred embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of the application and together with the embodiments of the present invention are used to explain the principle of the present invention and are not intended to limit the scope of the present invention.

Before the description of the embodiments, the inventive concept of the present application will be described first.

The turbocharger is an important part of the marine diesel engine, and once it fails, it will have a significant impact on the performance of the diesel engine. Marine turbocharger is a kind of rotating machinery, and vibration analysis is usually used to monitor its operating status during fault warning and diagnosis.

The commonly used vibration analysis method in the prior art is Fourier transform, expressed as:

为傅里叶变换结果，

为时间，

为频率，

为时域信号（即振动信号），

为窗函数，

为自然常数。in,

is the Fourier transform result,

for time,

is the frequency,

is a time domain signal (ie vibration signal),

is the window function,

is a natural constant.

But the Fourier transform can only deal with the smooth signal whose frequency does not change with time, and the variable working conditions of the marine turbocharger make the instantaneous frequency and amplitude of the vibration component change rapidly, and the stiffness of the turbocharger rotor support has different characteristics. Stability, so the vibration signal presents strong amplitude, frequency modulation characteristics and non-stationarity, which is difficult to be processed by Fourier transform.

，并从中选取合适的解调参数c进行计算，振动信号s通过变换得到时频结果G，用公式表示为：For non-stationary signals, classic chirp transform methods such as short-time Fourier transform and wavelet transform can be used for time-frequency analysis of vibration signals. The signal processing process of chirp transform is to add a solution to the Fourier transform. Adjustment operator

, and select the appropriate demodulation parameter c for calculation, the vibration signal s is transformed to obtain the time-frequency result G, which is expressed as:

为线性调频变换结果，

为时间，

为频率，

为振动信号，

为窗函数，

为解调率，

为自然常数，

为时频面旋转角度，

为采样率，

为采样时间，

为解调率的个数。in,

is the chirp transform result,

for time,

is the frequency,

is the vibration signal,

is the window function,

is the demodulation rate,

is a natural constant,

is the rotation angle of the time-frequency plane,

is the sampling rate,

is the sampling time,

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 synchronous compression transformation is usually used to post-process the chirp transformation results, so that the time-frequency energy is concentrated in the frequency direction The instantaneous frequency is estimated around the trajectory, making the time-frequency analysis results more intuitive.

The expression of the synchronous compression transform is as follows:

为瞬时频率估计，

为狄利克雷函数，

为频率。in,

For the instantaneous frequency estimate,

is the Dirichlet function,

for the frequency.

附近的频率能量集中到

处。The function of synchronous compression transformation is to put

Nearby frequency energy is concentrated into

place.

However, when synchronous compression frequency modulation transform is used to analyze the high-frequency signal such as the vibration signal of the marine turbocharger, the energy in the time-frequency representation is still relatively scattered, and the time-frequency aggregation is seriously reduced. Only the rough outline of the signal component can be seen, and the amplitude of the signal component has a large gap compared with the real value, which cannot be used for fault monitoring and diagnosis of the supercharger.

In order to solve the problem of severe energy ambiguity after linear transformation and synchronous compression of the vibration analysis of non-stationary signals in the prior art, and the large gap between the amplitude of the signal component and the real value, the present invention is based on the existing chirp transformation method In the above, focusing on the solution of the optimal demodulation rate, an optimal demodulation synchronous compression frequency modulation transformation is proposed to analyze the time-frequency analysis of the strong time-varying signal of the marine turbocharger, so that the time-frequency diagram of the signal is clearer and the energy aggregation is better. Even better, it is capable of online fault monitoring and diagnosis of marine turbochargers.

An embodiment of the present invention provides a marine turbocharger fault online monitoring and diagnosis method, as shown in Figure 1, Figure 1 is a schematic flow chart of the marine turbocharger fault online monitoring and diagnosis method, including:

Step S101: Obtain the vibration signal of the marine turbocharger;

Step S102: Perform time-frequency analysis on the vibration signal by using an improved chirp transformation method to obtain a time-frequency transformation signal;

Step S103: performing synchronous compression on the time-frequency transformed signal to obtain a compressed time-frequency signal;

Step S104: Obtain a reconstructed time-domain vibration signal according to the compressed time-frequency signal, and extract fault characteristic parameters of the turbocharger according to the reconstructed time-domain vibration signal;

Step S105: Perform fault diagnosis on the marine turbocharger according to the fault characteristic parameters.

The marine turbocharger fault online monitoring and diagnosis method provided in this embodiment, first, obtain the vibration signal of the marine turbocharger, and use the improved chirp conversion method to perform time-frequency analysis to obtain the time-frequency conversion signal; secondly, the The time-frequency transformation signal is compressed synchronously to obtain the compressed time-frequency signal, and the reconstructed time-domain vibration signal is obtained according to the compressed time-frequency signal; finally, the fault characteristic parameters are extracted according to the reconstructed time-frequency vibration signal, and the marine turbocharger is analyzed by the fault characteristic parameters. Compressor fault diagnosis. The method of this embodiment optimizes the demodulation rate on the basis of the existing linear frequency modulation transformation method, based on the optimal demodulation rate and synchronous compression transformation, the time-frequency diagram of the vibration signal is clearer, and the accumulation of time-frequency energy Good sex. By reconstructing the signal after the optimal demodulation, synchronous compression and frequency modulation transformation, the strong time-varying signal can be effectively analyzed, and the fault characteristic parameters can be extracted from the reconstructed time-domain vibration signal. The characterization ability is stronger, which can effectively excavate the essential characteristics of marine turbocharger failures.

As a specific embodiment, in step S101, a vibration signal of a marine turbocharger is acquired through a vibration sensor. In order to comprehensively monitor the faults of the turbocharger, this embodiment also arranges displacement and rotational speed sensors to acquire the axis track signal and rotational speed signal of the marine turbocharger. The layout of each sensor is as follows:

Multiple vibration sensors are arranged on the base of the marine turbocharger; a displacement sensor is arranged on the rotor shaft to measure the shaft center trajectory signal; the speed sensor of the turbocharger is used to measure the speed signal. Each sensor signal is collected by the LMS (Link Management System) collection device and sent to the computer for signal analysis. As shown in Figure 2, Figure 2 shows a schematic diagram of the connection structure for collecting relevant data of a marine turbocharger through sensors.

In practical applications, the sensor should be installed in an accessible place and a location where the energy attenuation of the rotor vibration signal is small and the signal-to-noise ratio is high. The vibration of the turbocharger rotor is transmitted to the base and housing through the oil film and bearings, and the vibration sensor is arranged at the base close to the bolt. The signal transmission 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 synchronous compression are aimed at the vibration signal acquired by the vibration sensor, and the features represented by the axis track signal and the rotational speed signal are directly extracted.

Due to the strong time-varying signal of the vibration signal of the marine turbocharger by the traditional linear frequency modulation conversion and synchronous compression, the energy in the time-frequency representation still appears relatively scattered, and the time-frequency aggregation is seriously reduced. Therefore, in step S102, The time-frequency analysis of the vibration signal is carried out by using the improved chirp transform method.

As a preferred embodiment, in step S102, the improved chirp conversion method includes:

The optimal demodulation rate corresponding to the minimum value of the sum of Rayleigh entropy and SNR is taken as the demodulation rate of chirp conversion.

As a specific embodiment, based on the chirp transform theory, the two parameters of Rayleigh entropy (RayleighEntropy, RE) and signal-to-noise ratio (Signal to Noise Ratio, SNR) are taken as targets to optimize the chirp transform. demodulation rate. specific:

The linear frequency modulation transformation expression is:

，in,

,

；

;

为线性调频变换结果，

为时间，

为频率，

为振动信号，

为窗函数，

为解调率，

为自然常数，

为时频面旋转角度，

为采样率，

为采样时间，

为解调率的个数。

is the chirp transform result,

for time,

is the frequency,

is the vibration signal,

is the window function,

is the demodulation rate,

is a natural constant,

is the rotation angle of the time-frequency plane,

is the sampling rate,

is the sampling time,

is the number of demodulation rates.

有

个取值，解调率c也有

个取值，把

个c值带入同步压缩调频变换的公式：therefore,

have

value, the demodulation rate c also has

a value, put

A c value is brought into the formula of synchronous compression FM transformation:

，

,

Find the sum of Rayleigh entropy and signal-to-noise ratio, that is, RE+SNR; when RE+SNR is the smallest value c is the best demodulation rate c of the signal. Right now:

为最优估计解调率，

为瞬时频率估计（同步压缩将时频能量沿频率方向集中在瞬时频率估计轨迹的周围），m为采样点数，x为有效信号。in,

For the best estimated demodulation rate,

is the instantaneous frequency estimation (synchronous compression concentrates the time-frequency energy along the frequency direction around the instantaneous frequency estimation track), m is the number of sampling points, and x is the effective signal.

The optimal match between the demodulation rate and the vibration signal component modulation rate in the synchronous compressed chirp conversion is achieved through the optimal demodulation rate c.

As a preferred embodiment, in step S103, the time-frequency transform signal is synchronously compressed to obtain a compressed time-frequency signal, including:

determining the frequency bandwidth and center frequency of the time-frequency transformed signal;

Compressing the time-frequency transformed signal according to the frequency bandwidth and the center frequency point to obtain a compressed time-frequency signal.

As a specific embodiment, the frequency bandwidth of the optimal demodulation rate chirp conversion is calculated by the following formula:

为估计频带宽，

为信号第k个分量的幅值，

为信号第k个分量的瞬时相位。in,

To estimate the frequency bandwidth,

is the amplitude of the kth component of the signal,

is the instantaneous phase of the kth component of the signal.

Simultaneously compress the result of the chirp transform to form a new time-frequency representation:

由下式计算得到：Instantaneous Frequency Estimation

It is calculated by the following formula:

为狄利克雷函数，Δ为频带宽。in,

is the Dirichlet function, and Δ is the frequency bandwidth.

As a preferred embodiment, in step S104, the reconstructed time-domain vibration signal is obtained according to the compressed time-frequency signal, including:

From the compressed time-frequency signal, a component time-domain signal with a preset frequency multiplication number is reconstructed to obtain a reconstructed time-domain vibration signal.

As a specific embodiment, the preset frequency multiplication numbers are one frequency multiplication, two frequency multiplication, and nine multiplication. The original vibration signal is decomposed into three component signals of 1, 2, and 9 times frequency. The formula for reconstructing the time domain vibration signal is as follows:

为窗函数的傅里叶变换。in,

is the Fourier transform of the window function.

It should be noted that the component signals of one-octave frequency and two-octave frequency are highly correlated with the fault of the turbocharger, and the component signal of nine-octave frequency is selected in this embodiment assuming that the number of vanes at the compressor end of the turbocharger is Nine masters and nine slave blades, if the number of blades at the compressor end of the turbocharger changes, the double frequency component signal corresponding to the number of blades should be selected.

In order to prove the superiority of the method of the present invention, the time-frequency analysis effect of the optimal demodulation synchronous compression FM transformation proposed by the present invention is demonstrated by simulating a group of strong time-varying signals.

Assume that the simulated signal consists of two components, as follows:

Among them, the sampling frequency is 1000Hz, and the sampling time is 4s.

Fig. 3(a)-Fig. 3(d) respectively show the time obtained by processing the simulated signal by short-time Fourier transform, continuous wavelet transform, wavelet synchronous compression transform and the optimal demodulation synchronous compression FM transform proposed by the present invention. frequency map.

As shown in Figure 3(a), due to the limitation of the Heisenberg uncertainty principle and the strong time-varying characteristics of the signal, the time-frequency results of the short-time Fourier transform (STFT) are not aggregated, and the energy ambiguity is very serious. Also due to the strong time-varying characteristics of the signal, the energy of the time-frequency results of continuous wavelet transform is still very scattered, and only the rough outline of the signal components can be seen, as shown in Figure 3(b). Compared with continuous wavelet transform, the time-frequency result of wavelet synchronous compression transform has further improved time-frequency energy aggregation, as shown in Fig. 3(c).

The energy in the time-frequency diagram of the optimal demodulation synchronous compression FM transformation proposed by the present invention is highly concentrated and not diffused, and the frequency trajectory of the signal component is relatively clear, which can effectively analyze strongly time-varying signals, as shown in Figure 3(d) .

As a preferred embodiment, extracting the fault characteristic parameters of the turbocharger according to the reconstructed time-domain vibration signal includes:

According to the reconstructed time-domain vibration signal, extract the vibration effective value and the vibration phase;

The vibration fault characteristic parameters are obtained according to the vibration effective value and the vibration phase.

As a specific embodiment, the characteristic parameters of the vibration fault include: effective value of vibration, vibration energy ratio, effective ratio of healthy state, coefficient of variation of rotor power frequency phase, coefficient of variation of effective value of vibration, coefficient of variation of instantaneous frequency of vibration, and power frequency vibration RMS standard deviation.

、倍频分量之间的比值

、振动有效值与健康状态的比值

、转子工频相位变异系数、工频振动有效值变异系数、工频振动瞬时频率变异系数、工频振动有效值标准差、转子不平衡因子和轴承磨损因子等15个振动故障特征参数。其中，振动有效值与健康状态的比值为：实际获取的振动有效值与涡轮增压器在健康状态时测量的数据的比值。According to the reconstructed one-, two-, and nine-octave frequency component signals, the effective value of vibration can be extracted

, The ratio between the octave components

, the ratio of vibration effective value to health state

15 vibration fault characteristic parameters, including rotor power frequency phase variation coefficient, power frequency vibration effective value variation coefficient, power frequency vibration instantaneous frequency variation coefficient, power frequency vibration effective value standard deviation, rotor unbalance factor and bearing wear factor. Wherein, the ratio of the vibration effective value to the healthy state is: the ratio of the actually obtained vibration effective value to the data measured when the turbocharger is in a healthy state.

The specific expression of each vibration fault characteristic parameter is as follows:

，单位

。1. The effective value of rotor power frequency (double frequency) vibration

,unit

.

，k=1,2,…,K，K为信号点数，

中转子n倍频振动分量波形记为

。Among them, the vibration signal waveform of the measuring point is recorded as

, k=1,2,...,K, K is the number of signal points,

The waveform of the n-fold frequency vibration component of the middle rotor is denoted as

.

，单位

。2. The effective value of the double frequency vibration of the rotor

,unit

.

，单位

。3. The effective value of the nine times frequency vibration of the rotor

,unit

.

，无量纲。4. The vibration energy ratio of rotor double frequency and power frequency

, dimensionless.

，无量纲。5. The vibration energy ratio of rotor nine times frequency and double frequency

, dimensionless.

，无量纲。6. Ratio of rotor nine times frequency and power frequency vibration energy

, dimensionless.

，无量纲。7. The ratio of the effective value of power frequency vibration to the healthy state

, dimensionless.

为健康状态下信号的转子工频振动分量波形。in,

It is the rotor power frequency vibration component waveform of the signal in the healthy state.

，无量纲。8. The ratio of the effective value of double-frequency vibration to the healthy state

, dimensionless.

为健康状态信号中的转子二倍频振动分量波形。in,

It is the rotor double frequency vibration component waveform in the health state signal.

，无量纲。9. The ratio of the effective value of the nine-fold frequency vibration to the healthy state

, dimensionless.

为健康状态信号中的转子九倍频振动分量波形。in,

It is the rotor nine times frequency vibration component waveform in the health state signal.

，无量纲。10. Coefficient of variation of rotor power frequency phase

, dimensionless.

，单位是度，m=1,2,…,M，M为相位点数。Among them, the power frequency phase of the rotor in the i and j measuring point signals are respectively

, the unit is degree, m=1,2,…,M, M is the number of phase points.

，无量纲。11. Coefficient of variation of effective value of power frequency vibration

, dimensionless.

，无量纲。12. Coefficient of variation of instantaneous frequency of power frequency vibration

, dimensionless.

，单位Hz。Among them, the instantaneous frequency of rotor power frequency vibration is recorded as

, unit Hz.

，单位

。13. Standard deviation of effective value of power frequency vibration

,unit

.

表示把测量信号分为多段，第k段信号n倍频振动有效值。in,

Indicates that the measurement signal is divided into multiple segments, and the effective value of n-fold frequency vibration of the k-th segment signal.

，单位m。14. Rotor unbalance factor

, unit m.

为转子工频，单位Hz。涡轮增压器转速越高，其

值越大，因此把

除以转子工频

，这个值

就剔除了转速的影响，只跟故障程度有关；in,

is the power frequency of the rotor, in Hz. The higher the speed of the turbocharger, the

The larger the value, so the

Divided by the rotor power frequency

, the value

The influence of the speed is eliminated, and it is only related to the degree of failure;

，无量纲。15. Bearing wear factor

, dimensionless.

As a preferred embodiment, the method also includes:

Obtain the axis track signal and speed signal of the marine turbocharger;

According to the shaft center trajectory signal and the rotational speed signal, extracting the variable fault characteristic parameters of the marine turbocharger;

The variation fault characteristic parameter is used to characterize the difference between the operating state and the normal state of the turbocharger.

As a specific embodiment, the variable fault characteristic parameters include:

，无量纲。1. Turbocharger speed fluctuation coefficient

, dimensionless.

，其中k=1,2,…,K，K为信号点数，单位是r/min。Among them, the supercharger rotor speed is recorded as

, where k=1,2,…,K, K is the number of signal points, and the unit is r/min.

，无量纲。2. The coefficient of variation of the abscissa of the rotor axis trajectory

, dimensionless.

、

，其中k=1,2,…,K，K为信号点数，单位是µm。Among them, the transverse and longitudinal displacements of the supercharger rotor axis trajectory are recorded as

,

, where k=1,2,…,K, K is the number of signal points, and the unit is µm.

，无量纲。3. The coefficient of variation of the ordinate of the rotor axis trajectory

, dimensionless.

Calculate the above 3 variable fault characteristic parameters and the above 15 vibration fault characteristic parameters, compare with the criterion benchmarks of each characteristic parameter, and judge the working state of the turbocharger from the mechanism.

It should be noted that the method of obtaining the criterion benchmark of each characteristic parameter is as follows:

In the normal state of the turbocharger, record the characteristic parameters of the multi-working cycle vibration, shaft center trajectory and speed signal under the common working conditions, and carry out cycle averaging on the characteristic parameters of the same characteristic parameter and the same working condition and multi-working cycle. The parameters are used as the criteria for fault diagnosis.

As a preferred embodiment, performing fault diagnosis on the marine turbocharger according to the fault characteristic parameters includes:

Determining the type of fault and the degree of parameter deviation according to the characteristic parameters of the fault;

The fault severity of the turbocharger is determined according to the fault type and the degree of parameter deviation.

……等18个特征参数，综合各故障特征参数的判断结果，识别和判断涡轮增压器的故障种类，并根据特征参数偏离判据的程度来诊断故障严重程度。各特征参数与不同故障及不同故障程度的关系从预先的相关研究结果中获取，这些监测诊断知识在不同机型涡轮增压器上经验证后可直接应用。As a specific embodiment, during the operation of the turbocharger, the optimal demodulation synchronous compression frequency modulation transformation is performed on the signal online, and the online calculation

... and other 18 characteristic parameters, and the judgment results of each fault characteristic parameter are integrated to identify and judge the fault type of the turbocharger, and diagnose the severity of the fault according to the degree of deviation of the characteristic parameters from the criterion. The relationship between each characteristic parameter and different faults and different fault degrees is obtained from the relevant research results in advance. These monitoring and diagnosis knowledge can be directly applied after being verified on different types of turbochargers.

It should be noted that when the supercharger vibration signal is used for fault diagnosis, Principal Component Analysis (PCA) is generally used to test the ability of the extracted characteristic parameters to represent the fault. After the commonly used general feature parameters are extracted by PCA, the samples of the same fault type are not highly aggregated, and some faults will overlap, making it difficult to effectively classify typical faults of turbochargers. However, after the PCA extraction of the fault characteristic parameters constructed by the present invention, the same fault types are aggregated, and the samples of different types of faults are clearly distinguished, indicating that the extracted characteristic parameters can effectively excavate the essential characteristics of turbocharger faults.

In the following, the feature parameters extracted in this embodiment are used to describe the fault characterization capability of the turbocharger through the method of principal component analysis. The principal component analysis method is based on the idea of linear transformation, which reduces the dimensionality of the data through orthogonal transformation, and uses a small amount of information to characterize the characteristics of the data, so as to realize the dimensionality reduction of the data and retain its main information characteristics. Here, the data is reduced by the PCA analysis method. Map from raw space to 2D space for visualization.

The data used for verification adopts the fault simulation test data. Specifically, the fault simulation test was carried out on the turbocharger test bench. The specific test conditions are: simulated turbocharger 35000r/min, 37500r/min, 40000r/min,… ..., under the working condition of 60000r/min, normal, slight dynamic unbalance, severe dynamic unbalance and dynamic unbalance superimposed bearing wear occurred simultaneously.

Principal component analysis was performed on the above experimental data. The common general characteristic parameters of turbocharger fault diagnosis are shown in Table 1.

Table 1 Common general characteristic parameters of turbocharger fault diagnosis

The visualization results of PCA extraction for the feature parameters in Table 1 are shown in Figure 4(a). The distribution of normal state samples in the two-dimensional space is not clustered, and the split is more serious, which shows that after the data set is extracted by general feature PCA, the degree of clustering of samples of the same fault type is not high. In Fig. 4(a), severe rotor unbalance and double faults are very close to each other, and even some data overlap, and the discrimination of the sample features is low. The results show that the general characteristics of turbochargers shown in Table 1 are difficult to effectively classify typical faults of turbochargers.

The collected turbocharger data is processed through the optimal demodulation synchronous compression frequency modulation transformation proposed by the present invention and the signal is reconstructed, and the fault characteristic parameters are extracted according to the reconstructed signal. The visualization result of the characteristic parameters is shown in Figure 4(b) , in Figure 4(b), the intervals between different types of fault samples are large, and the distinction is obvious. The same fault type is aggregated, and there is no crossover of different fault types. This shows that the extracted characteristic parameters can effectively excavate the essential characteristics of turbocharger faults, and can effectively classify the states of turbochargers.

In addition, it can be seen from Figure 4(b) that the extracted characteristic parameters are basically not affected by the change of working conditions, that is, under different working conditions of the supercharger, the characteristic matrix with excellent performance can be obtained by using the proposed characteristic parameter construction method , which effectively solves the problem of the performance degradation of the classification characteristics of the turbocharger due to the change of the working condition.

This embodiment also provides a marine turbocharger fault online monitoring and diagnosing device, as shown in Figure 5, the marine turbocharger fault online monitoring and diagnosing device 500 includes:

A signal acquisition module 501, configured to acquire a vibration signal of a marine turbocharger;

A time-frequency analysis module 502, configured to perform a time-frequency analysis on the vibration signal using an improved chirp transformation method to obtain a time-frequency transformation signal;

A synchronous compression module 503, configured to perform synchronous compression on the time-frequency transformed signal to obtain a compressed time-frequency signal;

A feature extraction module 504, configured to obtain a reconstructed time-domain vibration signal according to the compressed time-frequency signal, and extract fault characteristic parameters of the turbocharger according to the reconstructed time-domain vibration signal;

Diagnosis module 505, configured to perform fault diagnosis on the marine turbocharger according to the fault characteristic parameters.

As shown in Figure 6, the present invention also provides an electronic device 600 corresponding to the above-mentioned method for on-line monitoring and diagnosis of a marine turbocharger fault, which can be a mobile terminal, a desktop computer, a notebook, a palmtop computer and computing devices such as servers. The electronic device includes a processor 601 , a memory 602 and a display 603 .

The memory 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. In other embodiments, the memory 602 may also be an external storage device of the computer device, such as a plug-in hard disk equipped on the computer device, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash memory Card (Flash Card), etc. Further, the memory 602 may also include both an internal storage unit of the computer device and an external storage device. The memory 602 is used to store application software and various data installed in the computer equipment, such as program codes installed in the computer equipment, and the like. The memory 602 can also be used to temporarily store data that has been output or will be output. In one embodiment, a marine turbocharger fault online monitoring and diagnosis method program 604 is stored in the memory 602, and the marine turbocharger fault online monitoring and diagnosis method program 604 can be executed by the processor 601, thereby realizing A marine turbocharger fault online monitoring and diagnosis method according to various embodiments of the present invention.

In some embodiments, the processor 601 may be a central processing unit (Central Processing Unit, CPU), a microprocessor or other data processing chips, which are used to run program codes or process data stored in the memory 602, for example, to execute a marine Turbocharger fault online monitoring and diagnosis method program, etc.

In some embodiments, the display 603 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode, Organic Light-Emitting Diode) touch panel, and the like. The display 603 is used for displaying information on the computer device and for displaying a visual user interface. The components 601-603 of the computer device communicate with each other via a system bus.

This embodiment also provides a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the marine turbocharger described in any one of the above technical solutions is realized. Fault online monitoring and diagnosis method.

The computer-readable storage medium and the computing device provided according to the above-mentioned embodiments of the present invention can be implemented with reference to the specific description of the online monitoring and diagnosis method for a marine turbocharger fault as described above according to the present invention, and have the same characteristics as above The beneficial effect is similar to the online monitoring and diagnosis method for a marine turbocharger fault described above, and will not be repeated here.

The marine turbocharger fault online monitoring and diagnosis method, device, electronic equipment and computer-readable storage medium disclosed by the present invention, first, obtain the vibration signal of the marine turbocharger, and use the improved chirp conversion method to perform time-frequency analysis , to obtain the time-frequency transformation signal; secondly, synchronously compress the time-frequency transformation signal to obtain the compressed time-frequency signal, and obtain the reconstructed time-domain vibration signal according to the compressed time-frequency signal; finally, extract the fault features according to the reconstructed time-frequency vibration signal Parameters and fault diagnosis of marine turbocharger through fault characteristic parameters.

The present invention optimizes the demodulation rate on the basis of the existing linear frequency modulation transformation method, and based on the optimal demodulation rate and synchronous compression transformation, compared with the existing time-frequency analysis method, the generated time-frequency diagram of the vibration signal It is clearer, the aggregation of time-frequency energy is better, and the frequency trajectory of the signal can be estimated more accurately. Through the signal reconstruction of the signal after optimal demodulation, synchronous compression and frequency modulation transformation, the strong time-varying signal can be effectively analyzed, and the fault characteristic parameters can be extracted from the reconstructed time-domain vibration signal, which can be compared with the general fault characteristic parameters to characterize the fault characteristics The capability is stronger, and the essential characteristics of the faults of marine turbochargers can be effectively excavated.

The above is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed in the present invention can easily think of changes or Replacement should be covered within the protection scope of the present invention.

Claims (10)

1. A marine turbocharger fault online monitoring and diagnosis method, characterized in that, comprising; Obtain vibration signals of marine turbochargers; Perform time-frequency analysis on the vibration signal by using an improved linear frequency modulation transformation method to obtain a time-frequency transformation signal; performing synchronous compression on the time-frequency transformed signal to obtain a compressed time-frequency signal; obtaining a reconstructed time-domain vibration signal according to the compressed time-frequency signal, and extracting fault characteristic parameters of the turbocharger according to the reconstructed time-domain vibration signal; Fault diagnosis is performed on the marine turbocharger according to the fault characteristic parameters. 2. marine turbocharger fault online monitoring and diagnosis method according to claim 1, is characterized in that, described improved chirp conversion method comprises: The optimal demodulation rate corresponding to the minimum value of the sum of Rayleigh entropy and SNR is taken as the demodulation rate of chirp conversion. 3. marine turbocharger fault online monitoring and diagnosis method according to claim 1, is characterized in that, described time-frequency conversion signal is carried out synchronous compression, obtains compressed time-frequency signal, comprises: determining the frequency bandwidth and center frequency of the time-frequency transformed signal; Compressing the time-frequency transformed signal according to the frequency bandwidth and the center frequency point to obtain a compressed time-frequency signal. 4. marine turbocharger fault online monitoring and diagnosis method according to claim 1, is characterized in that, obtains reconstruction time-domain vibration signal according to described compression time-frequency signal, comprises: From the compressed time-frequency signal, a component time-domain signal with a preset frequency multiplication number is reconstructed to obtain a reconstructed time-domain vibration signal. 5. marine turbocharger fault online monitoring and diagnosis method according to claim 1, is characterized in that, extracts the fault characteristic parameter of turbocharger according to described reconstruction time-domain vibration signal, comprises: According to the reconstructed time-domain vibration signal, extract the vibration effective value and the vibration phase; The vibration fault characteristic parameters are obtained according to the vibration effective value and the vibration phase. 6. marine turbocharger fault online monitoring and diagnosis method according to claim 5, is characterized in that, also comprises: Obtain the axis track signal and speed signal of the marine turbocharger; According to the shaft center trajectory signal and the rotational speed signal, extracting the variable fault characteristic parameters of the marine turbocharger; The variation fault characteristic parameter is used to characterize the difference between the operating state and the normal state of the turbocharger. 7. The marine turbocharger fault online monitoring and diagnosis method according to claim 1, characterized in that, carrying out fault diagnosis to the marine turbocharger according to the fault characteristic parameters, comprising: Determining the type of fault and the degree of parameter deviation according to the characteristic parameters of the fault; The fault severity of the turbocharger is determined according to the fault type and the degree of parameter deviation. 8. A marine turbocharger fault online monitoring and diagnosis device, characterized in that it comprises: The signal acquisition module is used to acquire the vibration signal of the marine turbocharger; A time-frequency analysis module, configured to perform time-frequency analysis on the vibration signal using an improved chirp conversion method to obtain a time-frequency conversion signal; A synchronous compression module, configured to perform synchronous compression on the time-frequency transformed signal to obtain a compressed time-frequency signal; A feature extraction module, configured to obtain a reconstructed time-domain vibration signal according to the compressed time-frequency signal, and extract fault characteristic parameters of the turbocharger according to the reconstructed time-domain vibration signal; A diagnostic module, configured to perform fault diagnosis on the marine turbocharger according to the fault characteristic parameters. 9. An electronic device, characterized in that it comprises a processor and a memory, and a computer program is stored on the memory, and when the computer program is executed by the processor, the method according to any one of claims 1-7 is realized. A marine turbocharger fault online monitoring and diagnosis method. 10. A computer-readable storage medium, characterized in that, a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, a computer program according to any one of claims 1-7 is realized. A marine turbocharger fault online monitoring and diagnosis method.

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