CN114060291B - Centrifugal pump multi-source signal parallel processing method based on coupling misalignment working condition - Google Patents
Centrifugal pump multi-source signal parallel processing method based on coupling misalignment working condition Download PDFInfo
- Publication number
- CN114060291B CN114060291B CN202111257274.5A CN202111257274A CN114060291B CN 114060291 B CN114060291 B CN 114060291B CN 202111257274 A CN202111257274 A CN 202111257274A CN 114060291 B CN114060291 B CN 114060291B
- Authority
- CN
- China
- Prior art keywords
- centrifugal pump
- signal
- working condition
- vibration
- parallel
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 230000008878 coupling Effects 0.000 title claims abstract description 40
- 238000010168 coupling process Methods 0.000 title claims abstract description 40
- 238000005859 coupling reaction Methods 0.000 title claims abstract description 40
- 238000003672 processing method Methods 0.000 title claims abstract description 11
- 230000010349 pulsation Effects 0.000 claims abstract description 32
- 238000000034 method Methods 0.000 claims abstract description 25
- 238000001914 filtration Methods 0.000 claims abstract description 20
- 238000006073 displacement reaction Methods 0.000 claims abstract description 17
- 238000012545 processing Methods 0.000 claims abstract description 13
- 238000005259 measurement Methods 0.000 claims abstract description 11
- 238000001228 spectrum Methods 0.000 claims abstract description 11
- 230000007787 long-term memory Effects 0.000 claims abstract description 9
- 238000010183 spectrum analysis Methods 0.000 claims abstract description 5
- 230000001360 synchronised effect Effects 0.000 claims abstract description 5
- 238000012360 testing method Methods 0.000 claims abstract description 5
- 230000015654 memory Effects 0.000 claims description 10
- 238000012544 monitoring process Methods 0.000 claims description 6
- 230000001133 acceleration Effects 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 claims description 3
- 239000011159 matrix material Substances 0.000 claims description 3
- 230000002093 peripheral effect Effects 0.000 claims description 3
- 230000003068 static effect Effects 0.000 claims description 3
- 238000012546 transfer Methods 0.000 claims description 3
- 239000006185 dispersion Substances 0.000 claims description 2
- 230000006403 short-term memory Effects 0.000 abstract description 6
- 238000013461 design Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 230000002159 abnormal effect Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000003595 spectral effect Effects 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Classifications
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04D—NON-POSITIVE-DISPLACEMENT PUMPS
- F04D15/00—Control, e.g. regulation, of pumps, pumping installations or systems
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04D—NON-POSITIVE-DISPLACEMENT PUMPS
- F04D15/00—Control, e.g. regulation, of pumps, pumping installations or systems
- F04D15/0088—Testing machines
Landscapes
- Engineering & Computer Science (AREA)
- Mechanical Engineering (AREA)
- General Engineering & Computer Science (AREA)
- Control Of Non-Positive-Displacement Pumps (AREA)
- Structures Of Non-Positive Displacement Pumps (AREA)
- Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)
Abstract
The invention belongs to the technical field of centrifugal pumps, and relates to a centrifugal pump multi-source signal parallel processing method based on a coupling misalignment working condition. The process of the invention is as follows: establishing a centrifugal pump multi-source signal synchronous measurement test bed; establishing a centrifugal pump multi-source signal parallel noise reduction processing algorithm based on a long-term and short-term memory network improved parallel extended Kalman filtering algorithm; adopting an improved Kalman filtering method to perform noise reduction treatment on synchronously acquired multisource signals of the centrifugal pump and X-direction axial displacement of the coupling under normal working conditions and coupling misalignment working conditions; performing spectrum analysis on the multi-source signal after noise reduction by adopting fast Fourier transform and a Hanning window to obtain a frequency domain of the multi-source signal; and analyzing the frequency spectrum characteristics and the 1/3 octave spectrum distribution characteristics of the pressure pulsation, vibration or flow noise of the centrifugal pump under the normal working condition and the non-centering working condition of the coupling.
Description
Technical Field
The invention relates to the technical field of centrifugal pumps, in particular to a centrifugal pump multi-source signal parallel processing method based on a coupling misalignment working condition.
Background
Abnormal vibration and noise of the centrifugal pump are mainly induced by rotor faults, and rotor misalignment accounts for more than 60% of them. Rotor misalignment includes bearing misalignment and shafting misalignment. The misalignment of the bearing can be automatically eliminated according to the structural characteristics of the bearing, and the misalignment of the shaft system, namely the misalignment of the coupling, refers to misalignment of the center lines of two shafts connected in the actual operation process, and is difficult to completely eliminate by changing the structure of the coupling. The misalignment of the centrifugal pump coupling includes three forms of parallel misalignment, angular misalignment, and integrated misalignment. During actual operation, the centrifugal pump inevitably has a phenomenon of misalignment of the coupling.
The centrifugal pump pressure pulsation, vibration and noise signal collection are easy to be influenced by self-excitation loads such as the outside, a pipeline system and the like, so that the collected signals have stable white noise and random noise which causes a plurality of peaks or abrupt changes of waveforms, and analysis of vibration and noise characteristic frequencies is influenced. Therefore, noise reduction processing is required for the acquired signal to improve the signal-to-noise ratio of the signal.
However, the existing centrifugal pump signal noise reduction methods are all filtering noise reduction of a single signal, and no report of a centrifugal pump multi-source signal parallel processing method based on a coupling misalignment working condition is yet seen.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a centrifugal pump multi-source signal parallel processing method based on a coupling misalignment working condition, which aims to provide a certain reference for processing impeller machinery multi-source signals and can reduce noise in parallel.
The invention provides a centrifugal pump multi-source signal parallel processing method based on a coupling misalignment working condition, which comprises the following steps:
Establishing a centrifugal pump multisource signal synchronous measurement test stand, wherein pressure pulsation is collected by a high-frequency dynamic pressure sensor, vibration signals are collected by a vibration acceleration sensor, flow noise is collected by a hydrophone, X-direction axial displacement of a coupler and an axial center track of a Y-direction are collected by an eddy current displacement sensor;
The method is characterized in that a centrifugal pump multi-source signal parallel noise reduction processing algorithm is established based on a long-term and short-term memory network improved parallel extended Kalman filtering algorithm, namely: taking the average value of the centrifugal pump measurement signal at the previous moment of each parallel filter as the input of a long-short-period memory network, obtaining a predicted value of the average value of the centrifugal pump measurement signal at the current moment through the processing of the long-short-period memory network structure, and carrying out least square polynomial fitting on the predicted value to obtain a transfer coefficient matrix of a predicted error, thereby carrying out Kalman filtering on each parallel filter. Wherein, the filter for obtaining the pressure pulsation signal, the vibration signal or the flowing noise signal by adopting an iterative dispersion differential filtering algorithm and an extended Kalman filtering algorithm adopts a random gradient descent algorithm to adjust the learning rate descent factor of the long-term and short-term memory network in real time
By intensity of pressure pulsationAnalyzing the pressure pulsation characteristics of the centrifugal pump under the normal working condition and the non-centering working condition of the coupling; or adopting a vibration speed stage VL to analyze the vibration characteristics of the centrifugal pump under the normal working condition and the non-centering working condition of the coupling; or adopting the sound pressure level SPL to analyze the flow noise characteristics of the centrifugal pump under the normal working condition and the non-centering working condition of the coupling;
Synchronously acquiring multi-source signals of the centrifugal pump under a normal working condition and a non-centering working condition of the coupler respectively, simultaneously measuring axial displacement of the coupler in the X direction and an axial center track of the coupler in the Y direction, and adopting an improved Kalman filtering method to perform noise reduction treatment on the multi-source signals of the centrifugal pump and the axial displacement of the coupler in the X direction;
Performing spectrum analysis on the multi-source signal after noise reduction by adopting fast Fourier transform and a Hanning window to obtain a frequency domain of the multi-source signal;
and analyzing the frequency spectrum characteristics and the 1/3 octave spectrum distribution characteristics of the pressure pulsation, vibration or flow noise of the centrifugal pump under the normal working condition and the non-centering working condition of the coupling.
Optionally, the multi-source signal is: a multi-measuring-point pressure pulsation signal, or a vibration signal, or a flow noise signal; or a combination of a pressure pulsation signal and a vibration signal; or a combination of a pressure pulsation signal and a flow noise signal; or a combination of vibration signal and flow noise signal; or a combination of pressure pulsation signals, vibration signals and flow noise signals.
Optionally, the pressure pulsation intensityThe method comprises the following steps: Wherein the average pressure P i is the static pressure of the monitoring point i, N is the number of pressure pulsation monitoring points, ρ is the working medium density, and u 2 is the peripheral speed of the impeller outlet.
Optionally, the vibration speed stage VL is: wherein v is the effective value of the vibration speed of the measuring point; v 0 is the reference vibration speed level.
Optionally, the sound pressure level SPL is: Wherein p is the effective sound pressure value of the measuring point; p ref is the reference sound pressure in the working medium.
Optionally, the parallel filters automatically adjust weights of the parallel filters through residuals, an initial weight of each parallel filter is 1/(n+1), weights of each subsequent parallel filter are automatically updated through filter solution calculation to obtain residuals and residual covariance obtained from a kth parallel filter, wherein n is the number of the filters.
Optionally, the learning rate reduction factor of the long-term and short-term memory network is 0.01-0.2.
The centrifugal pump multi-source signal parallel processing method based on the coupling misalignment working condition has the following beneficial effects: the parallel extended Kalman filtering algorithm is improved based on the long-term memory network, and noise reduction processing can be carried out on the multi-source signals of the centrifugal pump.
Drawings
FIG. 1 is a flow chart of a centrifugal pump multi-source signal parallel processing method based on a coupling misalignment working condition, which is provided by an embodiment of the invention;
Fig. 2 is a schematic diagram of a centrifugal pump multi-source signal synchronous measurement test stand provided by an embodiment of the invention;
FIG. 3 is a diagram of axial trajectories of a normal condition of a centrifugal pump and a misalignment condition of a coupling at a design flow provided by an embodiment of the present invention;
FIG. 4 is a comparison of axial displacement in the X direction of a noise reduction front and rear coupling provided by an embodiment of the present invention;
FIG. 5 is a graph showing the spectral characteristics of centrifugal pump vibration under normal operating conditions and coupling misalignment conditions provided by an embodiment of the present invention;
FIG. 6 is a graph showing the distribution of 1/3 octave spectrum of vibration of a centrifugal pump under normal operation and coupling misalignment conditions provided by an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Examples:
In the embodiment of the invention, the main design parameters of the vertical centrifugal pump are as follows: the design flow is 100m 3/h, the lift is 80m, and the rotating speed is 2950r/min.
In the following, a specific embodiment of the method for parallel processing of multi-source signals of a centrifugal pump based on a coupling misalignment condition of the present invention is described, and fig. 1 is a schematic flow diagram of the method for parallel processing of multi-source signals of a centrifugal pump based on a coupling misalignment condition provided in the embodiment of the present invention, where the present specification provides method operation steps as an example or a flowchart, but may include more or fewer operation steps based on conventional or non-inventive labor. The order of steps recited in the embodiments is merely one way of performing the order of steps and does not represent a unique order of execution. When implemented in a real system or server product, the methods illustrated in the embodiments or figures may be performed sequentially or in parallel (e.g., in a parallel processor or multithreaded environment). As shown in fig. 1, the method includes:
S101: a centrifugal pump multi-source signal synchronous measurement test bed is established, as shown in fig. 2, wherein pressure pulsation is collected by a high-frequency dynamic pressure sensor, vibration signals are collected by a vibration acceleration sensor, flow noise is collected by a hydrophone, X-direction axial displacement of a coupler and an axial center track of a Y-direction are collected by an eddy current displacement sensor.
S102: the method is characterized in that a centrifugal pump multi-source signal parallel noise reduction processing algorithm is established based on a long-term and short-term memory network improved parallel extended Kalman filtering algorithm, namely: taking the average value of the centrifugal pump measurement signal at the previous moment of each parallel filter as the input of a long-short-period memory network, obtaining a predicted value of the average value of the centrifugal pump measurement signal at the current moment through the processing of the long-short-period memory network structure, and carrying out least square polynomial fitting on the predicted value to obtain a transfer coefficient matrix of a predicted error, thereby carrying out Kalman filtering on each parallel filter.
Optionally, the multi-source signal combination is: a multi-measuring-point pressure pulsation signal, or a vibration signal, or a flow noise signal; or a combination of a pressure pulsation signal and a vibration signal; or a combination of a pressure pulsation signal and a flow noise signal; or a combination of vibration signal and flow noise signal; or a combination of pressure pulsation signals, vibration signals and flow noise signals.
Optionally, the parallel filters automatically adjust weights of the parallel filters through residuals, an initial weight of each parallel filter is 1/(n+1), weights of each subsequent parallel filter are automatically updated through filter solution calculation to obtain residuals and residual covariance obtained from a kth parallel filter, wherein n is the number of the filters.
Optionally, the learning rate reduction factor of the long-term and short-term memory network is 0.01-0.2.
In the embodiment of the invention, the measured flow is 100m 3/h of designed flow; the multi-source signal is a vibration signal of 4 measuring points, wherein M1 is a foundation pin measuring point, M2 is an inlet flange measuring point, M3 is an outlet flange measuring point, and M4 is a pump body measuring point; the learning rate decline factor of the long-short-term memory network is 0.05.
S103: by intensity of pressure pulsationAnalyzing the pressure pulsation characteristics of the centrifugal pump under the normal working condition and the non-centering working condition of the coupling; or adopting a vibration speed stage VL to analyze the vibration characteristics of the centrifugal pump under the normal working condition and the non-centering working condition of the coupling; or adopting the sound pressure level SPL to analyze the flow noise characteristics of the centrifugal pump under the normal working condition and the non-centering working condition of the coupling.
Optionally, the pressure pulsation intensityThe method comprises the following steps: Wherein the average pressure P i is the static pressure of the monitoring point i, N is the number of pressure pulsation monitoring points, ρ is the working medium density, and u 2 is the peripheral speed of the impeller outlet.
Optionally, the vibration speed stage VL is: wherein v is the effective value of the vibration speed of the measuring point; v 0 is the reference vibration speed level.
Optionally, the sound pressure level SPL is: Wherein p is the effective sound pressure value of the measuring point; p ref is the reference sound pressure in the working medium.
In the embodiment of the invention, the vibration speed stage VL is adopted to analyze the vibration characteristics of the centrifugal pump under the normal working condition and the non-centering working condition of the coupling; the working medium is water; the reference vibration velocity level v 0 is 1X 10 -9 m/s.
S104: synchronously acquiring multi-source signals of the centrifugal pump under a normal working condition and a non-centering working condition of the coupler respectively, simultaneously measuring axial displacement of the coupler in the X direction and an axial center track of the coupler in the Y direction, and adopting an improved Kalman filtering method to perform noise reduction treatment on the multi-source signals of the centrifugal pump and the axial displacement of the coupler in the X direction;
In the embodiment of the invention, the misalignment working condition of the coupler is that the coupler is parallel and misaligned by 1mm; and respectively and synchronously acquiring 4 vibration signals of a normal working condition of the centrifugal pump and an misalignment working condition of the coupler under the design flow, simultaneously measuring the axial displacement of the coupler in the X direction and the axis track in the Y direction, and carrying out noise reduction treatment on the 4 vibration signals and the axial displacement of the coupler in the X direction by adopting an improved Kalman filtering method.
In the embodiment of the invention, the axis track of the centrifugal pump coupler in the Y direction is shown in figure 3; the axial displacement of the coupling in the X direction before and after noise reduction under normal working conditions and the coupling misalignment working conditions is shown in figure 4.
S105: and carrying out spectrum analysis on the multi-source signal after noise reduction by adopting fast Fourier transform and a Hanning window to obtain a frequency domain of the multi-source signal.
In the embodiment of the invention, the frequency spectrum analysis is carried out on the vibration signal after noise reduction by adopting the fast Fourier transform and the Hanning window, so that the frequency domain information under the normal working condition and the non-centering working condition of the coupler is obtained.
S106: and analyzing the frequency spectrum characteristics and the 1/3 octave spectrum distribution characteristics of the pressure pulsation, vibration or flow noise of the centrifugal pump under the normal working condition and the non-centering working condition of the coupling.
In the embodiment of the invention, the frequency spectrum characteristic and the 1/3 octave spectrum distribution characteristic of the vibration of the centrifugal pump under the normal working condition and the non-centering working condition of the coupling are analyzed, and are respectively shown in figures 5 and 6.
In summary, the centrifugal pump multi-source signal parallel processing method based on the coupling misalignment working condition provided by the embodiment of the invention comprises the following steps: the multi-source signal of the centrifugal pump can be noise reduced by improving the parallel extended Kalman filtering algorithm based on the long-term memory network.
The above disclosure is only one embodiment of the present invention, and it is not intended to limit the scope of the claims, so that the equivalent changes according to the claims of the present invention still fall within the scope of the present invention.
Claims (7)
1. The centrifugal pump multi-source signal parallel processing method based on the coupling misalignment working condition is characterized by comprising the following steps of:
Establishing a centrifugal pump multisource signal synchronous measurement test stand, wherein pressure pulsation is collected by a high-frequency dynamic pressure sensor, vibration signals are collected by a vibration acceleration sensor, flow noise is collected by a hydrophone, X-direction axial displacement of a coupler and an axial center track of a Y-direction are collected by an eddy current displacement sensor;
Establishing a centrifugal pump multi-source signal parallel noise reduction processing algorithm based on a long-period memory network improved parallel extended Kalman filtering algorithm, wherein an iterative dispersion differential filtering algorithm and an extended Kalman filtering algorithm are adopted to obtain a filter of a pressure pulsation signal, a vibration signal or a flow noise signal, and a random gradient descent algorithm is adopted to adjust a learning rate descent factor of the long-period memory network in real time; the method for establishing the centrifugal pump multi-source signal parallel noise reduction processing algorithm based on the long-term memory network improved parallel extended Kalman filtering algorithm comprises the following steps of: taking the average value of the centrifugal pump measurement signal at the previous moment of each parallel filter as the input of a long-short-period memory network, obtaining a predicted value of the average value of the centrifugal pump measurement signal at the current moment through the processing of the long-short-period memory network structure, and carrying out least square polynomial fitting on the predicted value to obtain a transfer coefficient matrix of a predicted error, so that Kalman filtering is carried out on each parallel filter;
By intensity of pressure pulsation Analyzing the pressure pulsation characteristics of the centrifugal pump under the normal working condition and the non-centering working condition of the coupling; adopting a vibration speed stage VL to analyze the vibration characteristics of the centrifugal pump under the normal working condition and the non-centering working condition of the coupling; analyzing the flow noise characteristics of the centrifugal pump under the normal working condition and the non-centering working condition of the coupling by adopting a sound pressure level SPL;
Synchronously acquiring multi-source signals of the centrifugal pump under a normal working condition and a non-centering working condition of the coupler respectively, simultaneously measuring axial displacement of the coupler in the X direction and an axial center track of the coupler in the Y direction, and adopting an improved Kalman filtering method to perform noise reduction treatment on the multi-source signals of the centrifugal pump and the axial displacement of the coupler in the X direction;
Performing spectrum analysis on the multi-source signal after noise reduction by adopting fast Fourier transform and a Hanning window to obtain a frequency domain of the multi-source signal;
And analyzing the frequency spectrum characteristics and the 1/3 octave spectrum distribution characteristics of pressure pulsation, vibration and flow noise of the centrifugal pump under the normal working condition and the non-centering working condition of the coupling.
2. The method of claim 1, wherein the multi-source signal is: a multi-measuring-point pressure pulsation signal, or a vibration signal, or a flow noise signal; or a combination of a pressure pulsation signal and a vibration signal; or a combination of a pressure pulsation signal and a flow noise signal; or a combination of vibration signal and flow noise signal; or a combination of pressure pulsation signals, vibration signals and flow noise signals.
3. The method of claim 1, wherein the parallel filters automatically adjust weights of the parallel filters by residual errors, wherein an initial weight of each parallel filter is 1/(n+1), and weights of each subsequent parallel filter are automatically updated by filter solution calculation to obtain residual errors and residual covariance obtained from a kth parallel filter, wherein n is the number of the filters.
4. The method of claim 1, wherein the learning rate reduction factor of the long-short term memory network is 0.01-0.2.
5. The method of claim 1, wherein the pressure pulsation intensity isThe method comprises the following steps: Wherein the average pressure P i is the static pressure of the monitoring point i, N is the number of pressure pulsation monitoring points, ρ is the working medium density, and u 2 is the peripheral speed of the impeller outlet.
6. The method of claim 1, wherein the vibration velocity level VL is: wherein v is the effective value of the vibration speed of the measuring point; v 0 is the reference vibration speed level.
7. The method of claim 1, wherein the sound pressure level SPL is: Wherein p is the effective sound pressure value of the measuring point; p ref is the reference sound pressure in the working medium.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111257274.5A CN114060291B (en) | 2021-10-27 | 2021-10-27 | Centrifugal pump multi-source signal parallel processing method based on coupling misalignment working condition |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111257274.5A CN114060291B (en) | 2021-10-27 | 2021-10-27 | Centrifugal pump multi-source signal parallel processing method based on coupling misalignment working condition |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114060291A CN114060291A (en) | 2022-02-18 |
| CN114060291B true CN114060291B (en) | 2024-07-30 |
Family
ID=80235943
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111257274.5A Active CN114060291B (en) | 2021-10-27 | 2021-10-27 | Centrifugal pump multi-source signal parallel processing method based on coupling misalignment working condition |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114060291B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118188530B (en) * | 2024-05-17 | 2024-07-26 | 中建安装集团黄河建设有限公司 | Relay pump operation fatigue degree monitoring method, medium and system |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105545765A (en) * | 2016-01-15 | 2016-05-04 | 江苏大学 | Performance test device under swing condition of marine pump |
| CN107273565A (en) * | 2017-05-04 | 2017-10-20 | 江苏大学 | Flow-induction noise figure computational methods in a kind of centrifugal pump based on LES/LBM |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9624936B2 (en) * | 2012-05-16 | 2017-04-18 | Compressor Controls Corporation | Turbocompressor antisurge control by vibration monitoring |
| CN108708871A (en) * | 2018-04-19 | 2018-10-26 | 浙江大学 | A kind of axial flow blower vibration signal subconstiuent extracting method based on inverse Short Time Fourier Transform |
| CN109682601B (en) * | 2019-03-04 | 2020-11-17 | 北京天泽智云科技有限公司 | Early fault identification method for rolling bearing under variable rotating speed working condition |
| CN110173439B (en) * | 2019-05-29 | 2020-05-08 | 浙江大学 | Pump cavitation primary identification method based on balanced square envelope spectrum |
-
2021
- 2021-10-27 CN CN202111257274.5A patent/CN114060291B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105545765A (en) * | 2016-01-15 | 2016-05-04 | 江苏大学 | Performance test device under swing condition of marine pump |
| CN107273565A (en) * | 2017-05-04 | 2017-10-20 | 江苏大学 | Flow-induction noise figure computational methods in a kind of centrifugal pump based on LES/LBM |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114060291A (en) | 2022-02-18 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109190166B (en) | Cavitation judgment and state evaluation method and system for vane pump | |
| CN109488630B (en) | Centrifugal fan rotor misalignment fault diagnosis method based on harmonic relative index | |
| US5258923A (en) | System and method for detecting the occurrence, location and depth of cracks in turbine-generator rotors | |
| CN102262215B (en) | Method for detecting stator and rotor air gap eccentric faults of large generator | |
| CN110410336B (en) | Automatic pump cavitation state identification method | |
| CN114060291B (en) | Centrifugal pump multi-source signal parallel processing method based on coupling misalignment working condition | |
| CN113239613B (en) | Method for judging swing degree alarm of water turbine unit | |
| Hou et al. | Acoustic feature enhancement in rolling bearing fault diagnosis using sparsity-oriented multipoint optimal minimum entropy deconvolution adjusted method | |
| CN102966526B (en) | Based on the compressor low frequency flow induced vibrations class method for diagnosing faults that axial vibration is analyzed | |
| CN108644130B (en) | Pump set fault detection method | |
| CN112525533A (en) | Online detection method for contact angle of ball bearing of aero-engine | |
| Luo et al. | Fault diagnosis of rolling element bearing using an adaptive multiscale enhanced combination gradient morphological filter | |
| Shan et al. | A novel experimental research on vibration characteristics of the running high-speed motorized spindles | |
| Guo et al. | Fast spectral correlation detector for periodic impulse extraction of rotating machinery | |
| Wan et al. | Adaptive asymmetric real Laplace wavelet filtering and its application on rolling bearing early fault diagnosis | |
| CN112491228A (en) | Method for detecting key magnetic pole causing stator low-frequency vibration based on vibration waveform | |
| CN110207987B (en) | Method for judging performance degradation decline node of rolling bearing | |
| CN112446326A (en) | Canned motor pump fault mode identification method and system based on deep rewinding and accumulating network | |
| CN114048562B (en) | Method for analyzing parameter relevance of steam turbine generator unit | |
| Wu et al. | Fault Diagnosis of Wind Turbine Vibration Based on Wavelet Transform And Neural Network. | |
| CN113049251A (en) | Bearing fault diagnosis method based on noise | |
| CN111739160A (en) | Method for identifying dynamic and static interference vibration frequency of water turbine runner | |
| CN114861118B (en) | Measuring point layout determining method for fault monitoring of double-rotor rotating equipment | |
| RU2322666C1 (en) | Mode of oscillating-acoustic diagnostics of machines | |
| Shelts et al. | Acoustic Testing of the Bell 699 Rotor on the Tiltrotor Test Rig (TTR) in the National Full-Scale Aerodynamics Complex 40-by 80-Foot Wind Tunnel in Conversion and Airplane Configuration |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |