CN110736926A - Method and device for extracting characteristic parameters of motor running state - Google Patents
Method and device for extracting characteristic parameters of motor running state Download PDFInfo
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- CN110736926A CN110736926A CN201910975007.8A CN201910975007A CN110736926A CN 110736926 A CN110736926 A CN 110736926A CN 201910975007 A CN201910975007 A CN 201910975007A CN 110736926 A CN110736926 A CN 110736926A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/34—Testing dynamo-electric machines
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
- G01H17/00—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves, not provided for in the preceding groups
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Abstract
The method comprises the steps of obtaining vibration acceleration signals obtained by sampling from all positions of a motor and rotating speed discrete signals of a rotating shaft, obtaining acceleration frequency spectrums of the vibration acceleration signals through Fourier transformation on the vibration acceleration signals, fitting the rotating speed discrete signals to obtain rotating speed curves of the rotating speed discrete signals, extracting acceleration envelope curves of the acceleration frequency spectrums, conducting equal angle difference value resampling on the acceleration envelope curves by utilizing the rotating speed curves to obtain acceleration envelope spectrums through Fourier transformation, and extracting characteristic parameters of all positions of the motor according to bearing parameters and the acceleration envelope spectrums of the motor.
Description
Technical Field
The application relates to the technical field of motors, in particular to a characteristic parameter extraction method and device for motor running states.
Background
The motor is widely applied to various industries, how to ensure the safe and stable operation of the motor, and timely and effectively identify and diagnose faults, find the early fault characteristics and fault severity of the motor, and has high practical value for guiding maintenance, saving maintenance cost and shortening maintenance time.
In the characteristic parameters of the prior art, the rotation speed signal is a discrete signal, the continuity is poor, and the stability of parameter conversion is poor under the working condition of changing the rotation speed, so that great deviation exists in the characteristic parameter extraction.
Disclosure of Invention
In view of the above, it is necessary to provide methods and apparatuses for characteristic parameters, which can solve the problem of motor operating conditions with large deviation of characteristic parameter extraction.
method for extracting characteristic parameters of motor running state, the method comprises:
acquiring vibration acceleration signals sampled from all positions of a motor and rotating speed discrete signals of a rotating shaft;
obtaining an acceleration frequency spectrum of the vibration acceleration signal through Fourier transform on the vibration acceleration signal;
fitting the rotating speed discrete signal to obtain a rotating speed curve of the rotating speed discrete signal;
extracting an acceleration envelope curve of the acceleration frequency spectrum, performing equal-angle difference value resampling on the acceleration envelope curve by using the rotating speed curve, and performing Fourier transform to obtain an acceleration envelope spectrum;
and extracting characteristic parameters of each position of the motor according to the bearing parameters of the motor and the acceleration envelope spectrum.
In embodiments, the method further comprises the steps of obtaining threshold values corresponding to characteristic parameters of all positions of the motor, comparing the characteristic parameters with the threshold values, and determining the fault position of the motor according to the comparison result.
In embodiments, the method further comprises the steps of acquiring vibration acceleration signals measured by vibration sensors arranged on the horizontal plane and the vertical plane of the bearing end of the motor and the horizontal plane and the vertical plane of the non-bearing end of the motor, and acquiring a sensor arranged near the rotating shaft of the motor to detect a convex key or a concave groove on the rotating shaft, generating pulse signals and acquiring rotating speed discrete signals.
In embodiments, the method further comprises fitting the rotation speed according to the change rate between any two points in the rotation speed discrete signal to obtain a rotation speed curve corresponding to the rotation speed discrete signal.
In embodiments, the method further comprises performing Hilbert transform on the acceleration frequency spectrum to obtain an acceleration envelope curve.
According to embodiments, the method further comprises the steps of inquiring energy values of frequency points corresponding to all bearing parameters from the acceleration envelope spectrum according to the bearing parameters of the motor, obtaining a total energy value by carrying out square solving and post-evolution operation on the energy values of all frequency points of the acceleration envelope spectrum, and determining the energy values as characteristic parameters of the motor at the position.
A device for extracting characteristic parameters of motor running states, the device comprises:
the signal acquisition module is used for acquiring vibration acceleration signals sampled from all positions of the motor and rotating speed discrete signals of the rotating shaft;
the signal analysis module is used for carrying out Fourier transform on the vibration acceleration signal to obtain an acceleration frequency spectrum of the vibration acceleration signal; fitting the rotating speed discrete signal to obtain a rotating speed curve of the rotating speed discrete signal; extracting an acceleration envelope curve of the acceleration frequency spectrum, performing equal-angle difference value resampling on the acceleration envelope curve by using the rotating speed curve, and performing Fourier transform to obtain an acceleration envelope spectrum;
and the characteristic parameter extraction module is used for extracting the characteristic parameters of each position of the motor according to the bearing parameters of the motor and the acceleration envelope spectrum.
In embodiments, the device further comprises a fault judgment module for acquiring threshold values corresponding to characteristic parameters of each position of the motor, comparing the characteristic parameters with the threshold values, and determining a fault position of the motor according to a comparison result.
computer device comprising a memory and a processor, the memory storing a computer program that when executed by the processor performs the steps of:
acquiring vibration acceleration signals sampled from various positions of a motor and rotating speed discrete signals of a rotating shaft acquired by a sensor;
obtaining an acceleration frequency spectrum of the vibration acceleration signal through Fourier transform on the vibration acceleration signal;
fitting the rotating speed discrete signal to obtain a rotating speed curve of the rotating speed discrete signal;
extracting an acceleration envelope curve of the acceleration frequency spectrum, performing equal-angle difference value resampling on the acceleration envelope curve by using the rotating speed curve, and performing Fourier transform to obtain an acceleration envelope spectrum;
and extracting characteristic parameters of each position of the motor according to the bearing parameters of the motor and the acceleration envelope spectrum.
According to the method, the device, the computer equipment and the storage medium for extracting the characteristic parameters of the motor running state, the vibration acceleration signals and the discrete signals of the rotating speed are obtained from all parts of the motor, then the rotating speed discrete signals are fitted to obtain continuous rotating speed signals, so that the error of the rotating speed signals is reduced under various working conditions, then the equal angle difference value is adopted for resampling to obtain an acceleration envelope spectrum, in the aspect of , the equal angle sampling truly reflects the current running state of the motor, in the aspect of changing the working conditions, the requirement of Fourier transform on signal stability is met through the equal angle resampling, in addition, in the aspect of , the high frequency interference signals in the acceleration can be effectively filtered through resampling, the signal-to-noise ratio is improved, the characteristic parameters of the motor can be more truly reflected, and the complex working condition environment is met.
Drawings
FIG. 1 is a flow chart of a characteristic parameter extraction method for motor operating states in embodiments;
FIG. 2 is a block diagram of a characteristic parameter extraction device for motor operation status in embodiments;
fig. 3 is an internal structural view of a computer device in embodiments.
Detailed Description
For purposes of making the present application, its objects, aspects and advantages more apparent, the present application is described in further detail with reference to the drawings and the examples.
In embodiments, as shown in fig. 1, a characteristic parameter extraction method for motor operating states is provided, which includes the following steps:
and 102, acquiring vibration acceleration signals sampled from all positions of the motor and rotating speed discrete signals of the rotating shaft.
The vibration acceleration signal can be obtained by a vibration sensor arranged on the motor, or more vibration sensors can be arranged at each position of the motor to obtain the vibration sensors at multiple positions, or multiple vibration acceleration signals at the same position of are obtained to determine an accurate vibration acceleration signal, the rotating speed discrete signal can be obtained by a photoelectric sensor, 1 or more pulse signals are collected when the rotating shaft is circles, and the number of the pulses is determined by the number of specific bulges or grooves on the rotating shaft, so that a discrete rotating speed signal is formed.
And 104, performing Fourier transform on the vibration acceleration signal to obtain an acceleration frequency spectrum of the vibration acceleration signal.
In the step, the vibration acceleration signal in the time domain is converted into the frequency domain through Fourier transform, so that the vibration acceleration signal is further analyzed in step .
And step 106, fitting the rotating speed discrete signal to obtain a rotating speed curve of the rotating speed discrete signal.
Fitting the discrete speed signals means that points in the discrete speed signals are connected in a fitting manner, so that continuous curves are formed.
And step 108, extracting an acceleration envelope curve of the acceleration frequency spectrum, performing equal-angle difference value resampling on the acceleration envelope curve by using a rotating speed curve, and performing Fourier transform to obtain the acceleration envelope spectrum.
The resampling is carried out at equal angles, the running state of the current motor can be truly reflected, so that accurate characteristic parameters are extracted, in addition, high-frequency interference signals in acceleration signals can be effectively filtered through resampling, the signal-to-noise ratio is improved, and the accuracy of the characteristic parameters is improved.
In addition, , the sampling angle is fixed at equal angles, the vibration energy value at a fixed angle is extracted, and the requirement of Fourier transform on signal stability is met.
And 110, extracting characteristic parameters of each position of the motor according to the bearing parameters and the acceleration envelope spectrum of the motor.
According to the characteristic parameter extraction method for the motor running state, vibration acceleration signals and discrete signals of the rotating speed are obtained from all parts of the motor, then the rotating speed discrete signals are fitted to obtain continuous rotating speed signals, errors of the rotating speed signals are reduced under various working conditions, then equal-angle difference value resampling is adopted to obtain an acceleration envelope spectrum, in the aspect of , equal-angle sampling truly reflects the current running state of the motor, in the aspect of changing the working conditions, the requirement of Fourier transform on signal stability is met through equal-angle resampling, in the aspect of , high-frequency interference signals in acceleration can be effectively filtered through resampling, the signal-to-noise ratio is improved, the characteristic parameters of the motor are more truly reflected, and a complex working condition environment is met.
In embodiments, after obtaining the characteristic parameters, threshold values corresponding to the characteristic parameters of the various positions of the back-trip motor are needed, so that the characteristic parameters are compared with the threshold values, and the fault position of the motor is determined according to the comparison result.
The comparison of the characteristic parameter with the threshold value further determines the level of the fault, so that the warning measure for the motor is obtained further .
Specifically, a simulation mode can be adopted to set fault samples, and the threshold of the characteristic parameter under each fault sample condition is obtained by setting a motor vibration signal contrast test.
In embodiments, vibration acceleration signals are obtained by using vibration sensors, the vibration sensors are arranged on the horizontal plane and the vertical plane of the bearing end of the motor, the horizontal plane and the vertical plane of the non-bearing end of the motor can be provided with or more vibration sensors at the same position of , in addition, a convex key or a concave groove is arranged on the rotating shaft, when the bearing rotates, the convex key or the concave groove passes through the effective detection distance range of the rotating speed sensor, and the rotating speed sensor can generate corresponding pulse signals, so that discrete signals are obtained.
Specifically, vibration acceleration signals measured by vibration sensors mounted on a horizontal plane and a vertical plane of a bearing end of a motor and a horizontal plane and a vertical plane of a non-bearing end are acquired, a rotating speed sensor mounted near the bearing is acquired, and a rotating speed discrete signal is acquired.
In embodiments, when fitting the discrete rotational speed signal, the discrete rotational speed signal can be fitted according to the change rate between any two points in the discrete rotational speed signal to obtain a rotational speed curve corresponding to the discrete rotational speed signal, so that the rotational speed curve is a smooth and continuous curve, and when resampling is performed by using the rotational speed curve, the actual working conditions can be reflected.
In embodiments, the step of extracting the acceleration envelope of the acceleration spectrum may be to perform hilbert transform on the acceleration spectrum to obtain the acceleration envelope.
In embodiments, when extracting the characteristic parameters of the motor operating state, the energy values of the frequency points corresponding to all the bearing parameters may be queried from the acceleration envelope spectrum according to the bearing parameters of the motor, and the total energy value obtained by performing the operation of squaring and post-evolution on the energy values of the full frequency points of the acceleration envelope spectrum, and each energy value is determined as the characteristic parameter of the motor at the position.
In another embodiment, the vibration acceleration signal is further integrated to obtain the vibration velocity, and then fourier transform is performed to obtain the vibration velocity spectrum, and the velocity curve obtained by fitting may be fourier transformed to extract the velocity spectrum, so as to facilitate equal-angle sampling of the vibration velocity signal.
It should be understood that although the various steps in the flowchart of fig. 1 are shown in sequence as indicated by the arrows, the steps are not necessarily performed in the sequence indicated by the arrows, unless explicitly stated herein, the steps may be performed in other sequences without strict order limitations, and further, at least part of the steps of fig. 1, , may include multiple sub-steps or stages that are not necessarily performed at the same time , but may be performed at different times, the order of performance of the sub-steps or stages may not necessarily be performed in sequence, but may be rotated or alternated with at least part of the other steps or sub-steps or stages of the other steps, as indicated by the arrows at .
In embodiments, as shown in fig. 2, a characteristic parameter extraction device for motor operating states is provided, which includes a signal acquisition module 202, a signal analysis module 204 and a characteristic parameter extraction module 206, wherein:
and the signal acquisition module 202 is used for acquiring vibration acceleration signals sampled from various positions of the motor and rotating speed discrete signals generated by the rotating shaft.
The signal analysis module 204 is configured to perform fourier transform on the vibration acceleration signal to obtain an acceleration frequency spectrum of the vibration acceleration signal; fitting the rotating speed discrete signal to obtain a rotating speed curve of the rotating speed discrete signal; and extracting an acceleration envelope curve of the acceleration frequency spectrum, performing equal-angle difference value resampling on the acceleration envelope curve by using the rotating speed curve, and performing Fourier transform to obtain the acceleration envelope spectrum.
And the characteristic parameter extraction module 206 is configured to extract characteristic parameters of each position of the motor according to the bearing parameters of the motor and the acceleration envelope spectrum.
In embodiments, the system further includes a fault determination module, configured to obtain a threshold corresponding to a characteristic parameter of each position of the motor, compare the characteristic parameter with the threshold, and determine a fault position of the motor according to a comparison result.
In embodiments, the signal obtaining module 202 is further configured to obtain vibration acceleration signals measured by vibration sensors installed on a horizontal plane and a vertical plane of a bearing end of the motor and a horizontal plane and a vertical plane of a non-bearing end of the motor, and obtain a pulse signal generated by the sensors installed near a rotating shaft of the motor detecting a key or a groove on the rotating shaft to obtain a discrete signal of the rotating speed.
In embodiments, the signal analysis module 204 is further configured to fit the rotation speed according to a change rate between any two points in the rotation speed discrete signal to obtain a rotation speed curve corresponding to the rotation speed discrete signal.
In embodiments, the signal analysis module 204 is further configured to perform hilbert transform on the acceleration spectrum to obtain an acceleration envelope.
In embodiments, the characteristic parameter extraction module 206 is further configured to query, according to the bearing parameters of the motor, energy values of frequency points corresponding to all the bearing parameters from the acceleration envelope spectrum, and a total energy value obtained by performing a squaring and post-evolution operation on energy values of all frequency points of the acceleration envelope spectrum, and determine each energy value as a characteristic parameter of the motor at the position.
For the specific limitation of the feature parameter extraction device regarding the motor operation state, reference may be made to the above limitation on the feature parameter extraction method of the motor operation state, and details are not described herein again. All or part of the modules in the characteristic parameter extraction device of the motor running state can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In embodiments, computer devices are provided, wherein the computer devices may be terminals, the internal structure of which may be as shown in fig. 3, the computer devices include a processor, a memory, a network interface, a display screen and an input device connected through a system bus, wherein the processor of the computer devices is used for providing computing and control capabilities, the memory of the computer devices includes a non-volatile storage medium, an internal memory, the non-volatile storage medium stores an operating system and a computer program, the internal memory provides an environment for the operating system and the computer program to run in the non-volatile storage medium, the network interface of the computer devices is used for communicating with external terminals through a network connection, the computer program is executed by the processor to implement a characteristic parameter extraction method for motor running states, the display screen of the computer devices may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer devices may be a touch layer overlaid on the display screen, may be a key, a trackball or a touch pad provided on a housing of the computer devices, may be a keyboard, a mouse, an external mouse, or the like.
Those skilled in the art will appreciate that the architecture shown in fig. 3 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In embodiments, computer devices are provided, comprising a memory storing a computer program and a processor implementing the steps of the above method embodiments when the computer program is executed by the processor.
It will be understood by those of ordinary skill in the art that all or a portion of the processes of the methods of the embodiments described above may be implemented by a computer program that may be stored in a non-volatile computer-readable storage medium, which when executed, may include the processes of the embodiments of the methods described above, wherein any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (9)
1, method for extracting characteristic parameters of motor running state, the method includes:
acquiring vibration acceleration signals sampled from all positions of a motor and rotating speed discrete signals of a rotating shaft;
obtaining an acceleration frequency spectrum of the vibration acceleration signal through Fourier transform on the vibration acceleration signal;
fitting the rotating speed discrete signal to obtain a rotating speed curve of the rotating speed discrete signal;
extracting an acceleration envelope curve of the acceleration frequency spectrum, performing equal-angle difference value resampling on the acceleration envelope curve by using the rotating speed curve, and performing Fourier transform to obtain an acceleration envelope spectrum;
and extracting characteristic parameters of each position of the motor according to the bearing parameters of the motor and the acceleration envelope spectrum.
2. The method according to claim 1, characterized in that it comprises:
acquiring a threshold corresponding to the characteristic parameters of each position of the motor;
and comparing the characteristic parameters with the threshold value, and determining the fault position of the motor according to the comparison result.
3. The method of claim 1, wherein obtaining vibration acceleration signals sampled from various positions of the motor and a rotational speed discrete signal of the rotating shaft comprises:
acquiring vibration acceleration signals measured by vibration sensors arranged on a horizontal plane and a vertical plane of a motor bearing end and a horizontal plane and a vertical plane of a non-bearing end;
and acquiring a sensor arranged near the motor rotating shaft to detect a convex key or a concave groove on the rotating shaft, generating a pulse signal and acquiring a rotating speed discrete signal.
4. The method of any , wherein fitting the discrete speed signal to obtain a speed curve of the discrete speed signal comprises:
and fitting the rotating speed according to the change rate between any two points in the rotating speed discrete signal to obtain a rotating speed curve corresponding to the rotating speed discrete signal.
5. The method according to any of claims 1-4, wherein the extracting the acceleration envelope of the acceleration spectrum comprises:
and performing Hilbert transform on the acceleration frequency spectrum to obtain an acceleration envelope curve.
6. The method according to any of claims 1-4, wherein the extracting the characteristic parameters of each position of the motor according to the bearing parameters of the motor and the acceleration envelope spectrum comprises:
according to the bearing parameters of the motor, inquiring energy values of frequency points corresponding to all bearing parameters from an acceleration envelope spectrum, and carrying out square-solving and back-opening operation on the full-frequency point energy values of the acceleration envelope spectrum to obtain a total energy value;
and determining the energy values as characteristic parameters of the motor at the position.
7, A device for extracting characteristic parameters of motor operation state, characterized in that the device comprises:
the signal acquisition module is used for acquiring vibration acceleration signals sampled from all positions of the motor and rotating speed discrete signals of the rotating shaft;
the signal analysis module is used for carrying out Fourier transform on the vibration acceleration signal to obtain an acceleration frequency spectrum of the vibration acceleration signal; fitting the rotating speed discrete signal to obtain a rotating speed curve of the rotating speed discrete signal; extracting an acceleration envelope curve of the acceleration frequency spectrum, performing equal-angle difference value resampling on the acceleration envelope curve by using the rotating speed curve, and performing Fourier transform to obtain an acceleration envelope spectrum;
and the characteristic parameter extraction module is used for extracting the characteristic parameters of each position of the motor according to the bearing parameters of the motor and the acceleration envelope spectrum.
8. The apparatus of claim 7, further comprising:
the fault judgment module is used for acquiring threshold values corresponding to characteristic parameters of all positions of the motor;
and comparing the characteristic parameters with the threshold value, and determining the fault position of the motor according to the comparison result.
Computer device of , comprising a memory and a processor, the memory storing a computer program, wherein the processor when executing the computer program is configured to carry out the steps of the method of any of claims 1 to 6 as claimed in .
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111521866A (en) * | 2020-05-15 | 2020-08-11 | 湖南银河电气有限公司 | Gyro motor output power stability monitoring method and device |
| CN111896279A (en) * | 2020-07-17 | 2020-11-06 | 南京理工大学 | Linear motor train running gear fault diagnosis method based on envelope analysis |
| CN112100569A (en) * | 2020-08-24 | 2020-12-18 | 瑞声新能源发展(常州)有限公司科教城分公司 | Motor parameter tracking method, device, equipment and medium based on frequency domain analysis |
| CN113064073A (en) * | 2021-03-12 | 2021-07-02 | 合肥恒大江海泵业股份有限公司 | Permanent magnet synchronous motor turn-to-turn short circuit fault diagnosis method based on residual current |
| CN114297569A (en) * | 2021-11-22 | 2022-04-08 | 国网安徽省电力有限公司马鞍山供电公司 | Switch fault detection algorithm of vibration sensor |
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102768115A (en) * | 2012-06-27 | 2012-11-07 | 华北电力大学 | Method for dynamically monitoring health status of wind turbine gearbox in real time |
| CN103529386A (en) * | 2013-10-12 | 2014-01-22 | 山西大学工程学院 | System and method for remote real-time state monitoring and intelligent failure diagnosis of wind turbine generators |
| CN103884502A (en) * | 2014-04-02 | 2014-06-25 | 清华大学 | Method for diagnosing faults of planetary gear system of wind driven generator under variable rotating speed |
| CN104535323A (en) * | 2015-01-12 | 2015-04-22 | 石家庄铁道大学 | Locomotive wheelset bearing fault diagnosis method based on angular domain-time domain-frequency domain |
| CN106525415A (en) * | 2016-10-25 | 2017-03-22 | 华北电力科学研究院有限责任公司 | Health state evaluation system and method for transmission chain of wind turbine generator |
| CN108490304A (en) * | 2018-03-22 | 2018-09-04 | 华能集团技术创新中心有限公司 | Method for positioning single-phase earth fault position of generator stator winding |
| CN110160791A (en) * | 2019-06-27 | 2019-08-23 | 郑州轻工业学院 | Based on small echo-spectrum kurtosis induction machine bearing failure diagnosis system and diagnostic method |
| CN110274764A (en) * | 2019-06-06 | 2019-09-24 | 西安交通大学 | A kind of locomotive engine bearing automatic diagnosis method based on vibration acceleration signal |
-
2019
- 2019-10-14 CN CN201910975007.8A patent/CN110736926A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102768115A (en) * | 2012-06-27 | 2012-11-07 | 华北电力大学 | Method for dynamically monitoring health status of wind turbine gearbox in real time |
| CN103529386A (en) * | 2013-10-12 | 2014-01-22 | 山西大学工程学院 | System and method for remote real-time state monitoring and intelligent failure diagnosis of wind turbine generators |
| CN103884502A (en) * | 2014-04-02 | 2014-06-25 | 清华大学 | Method for diagnosing faults of planetary gear system of wind driven generator under variable rotating speed |
| CN104535323A (en) * | 2015-01-12 | 2015-04-22 | 石家庄铁道大学 | Locomotive wheelset bearing fault diagnosis method based on angular domain-time domain-frequency domain |
| CN106525415A (en) * | 2016-10-25 | 2017-03-22 | 华北电力科学研究院有限责任公司 | Health state evaluation system and method for transmission chain of wind turbine generator |
| CN108490304A (en) * | 2018-03-22 | 2018-09-04 | 华能集团技术创新中心有限公司 | Method for positioning single-phase earth fault position of generator stator winding |
| CN110274764A (en) * | 2019-06-06 | 2019-09-24 | 西安交通大学 | A kind of locomotive engine bearing automatic diagnosis method based on vibration acceleration signal |
| CN110160791A (en) * | 2019-06-27 | 2019-08-23 | 郑州轻工业学院 | Based on small echo-spectrum kurtosis induction machine bearing failure diagnosis system and diagnostic method |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111521866A (en) * | 2020-05-15 | 2020-08-11 | 湖南银河电气有限公司 | Gyro motor output power stability monitoring method and device |
| CN111896279A (en) * | 2020-07-17 | 2020-11-06 | 南京理工大学 | Linear motor train running gear fault diagnosis method based on envelope analysis |
| CN112100569A (en) * | 2020-08-24 | 2020-12-18 | 瑞声新能源发展(常州)有限公司科教城分公司 | Motor parameter tracking method, device, equipment and medium based on frequency domain analysis |
| CN112100569B (en) * | 2020-08-24 | 2024-04-02 | 瑞声新能源发展(常州)有限公司科教城分公司 | Motor parameter tracking method, device, equipment and medium based on frequency domain analysis |
| CN113064073A (en) * | 2021-03-12 | 2021-07-02 | 合肥恒大江海泵业股份有限公司 | Permanent magnet synchronous motor turn-to-turn short circuit fault diagnosis method based on residual current |
| CN114297569A (en) * | 2021-11-22 | 2022-04-08 | 国网安徽省电力有限公司马鞍山供电公司 | Switch fault detection algorithm of vibration sensor |
| WO2024104489A1 (en) * | 2022-11-18 | 2024-05-23 | 中国科学院深圳先进技术研究院 | Product test method, terminal and computer-readable storage medium |
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Application publication date: 20200131 |