VIBRATION MONITORING AND DIAGNOSING SYSTEM FOR WIND POWER GENERATOR

• US 20170363072A1
• Filed: 06/09/2017
• Published: 12/21/2017
• Est. Priority Date: 06/21/2016
• Status: Active Grant

• Current Assignee: Doosan Heavy Industries and Construction Company Limited
• Original Assignee: Doosan Heavy Industries and Construction Company Limited
• Inventors: SON, Jong Duk, LEE, Jeong Hoon, LEE, Ki Hak, EOM, Seung Man
• Granted Patent: US 10,570,887 B2
• Time in Patent Office: Days
• CPC Class Codes: F03D 17/00 Monitoring or testing of wind motors, e.g. diagnostics testing during commissioning of wind motors F03D13/30
• CPC Class Codes: F05B 2200/211 Square root
• CPC Class Codes: F05B 2200/30 miscellaneous
• CPC Class Codes: F05B 2260/80 Diagnostics
• CPC Class Codes: F05B 2260/96 Preventing, counteracting or reducing vibration or noise
• CPC Class Codes: F05B 2270/334 Vibration measurements
• CPC Class Codes: F05B 2270/807 Accelerometers
• CPC Class Codes: G01H 1/003 of rotating machines G01H1/10 takes precedence
• CPC Class Codes: G01H 1/006 of the rotor of turbo machines
• CPC Class Codes: G01M 13/028 Acoustic or vibration analysis
• CPC Class Codes: G01M 13/045 Acoustic or vibration analysis
• CPC Class Codes: G01M 7/00 Vibration-testing of structures; Shock-testing of structures G01M9/00 takes precedence
• CPC Class Codes: G01P 15/00 Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration
• CPC Class Codes: Y02E 10/72 Wind turbines with rotation axis in wind direction

Abstract

Disclosed herein is a vibration monitoring and diagnosing system for monitoring conditions of a wind power generator and diagnosing a defective portion thereof using vibration characteristics obtained from acceleration sensors mounted to the wind power generator. A vibration-based defect detecting method may include: collecting vibration data of the wind power generator using the plurality of sensors; extracting a first characteristic value of a time domain based on the vibration data; extracting characteristic values in one or more frequency bands for a location of each sensor in a frequency domain or an envelope frequency domain if the first characteristic value is greater than a preset alarm setting value; and determining that a defect is present when at least one characteristic value of the characteristic values is greater than a preset normal value.

Claims

1. A fault detecting method of detecting a fault in of a wind power generator using vibration data, the fault detecting method comprising:

receiving vibration data of the wind power generator from a plurality of sensors;

extracting a first characteristic value in a time domain based on the vibration data;

determining whether the first characteristic value is greater than an alarm setting value; and

determining, when the first characteristic value is determined to be greater than the alarm setting value, whether there is the fault by extracting a characteristic value in a frequency domain obtained by performing a Fourier transform operation on the vibration data,

wherein the determining whether there is the fault comprises;

extracting, based on the vibration data received by the plurality of sensors, second characteristic values in the frequency domain, for one or more preset frequency bands by each of the plurality of sensors;

extracting, based on the vibration data received by the plurality of sensors, third characteristic values in an envelope frequency domain for the one or more preset frequency bands by each of the plurality of sensors in an envelope frequency domain; and

determining that the fault is present when at least one from among a characteristic value of the second characteristic values or a characteristic value of the third characteristic values is equal to or greater than a preset normal value.

2. The fault detecting method according to claim 1, further comprising

determining, when the at least one from among the characteristic value of the second characteristic values or the characteristic value of the third characteristic values is equal to or greater than the preset normal value, a location of the fault and a kind of the fault based on a frequency band of the preset frequency bands and a location of a corresponding sensor of the plurality of sensors.

3. The fault detecting method according to claim 1,

wherein the first characteristic value includes at least one of a root mean square, a kurtosis, and a crest factor,

wherein the root mean square (x_rms) is calculated by

4. The fault detecting method according to claim 1, wherein the extracting of the second characteristic values in the frequency domain for the one or more preset frequency bands by each of the plurality of sensors, based on the vibration data received by the plurality of sensors comprises:

performing a fast Fourier transform (FFT) operation on the vibration data; and

extracting, as a second characteristic value based on a result of the performing of the FFT operation, a peak value in a frequency band which has a corresponding one of the one or more preset center frequencies for each of the plurality of sensors as a center thereof, and opposite ends which are each spaced apart from the preset center frequency by 1 Hz.

5. The fault detecting method according to claim 4, wherein the one or more preset center frequencies comprise frequencies f_r, f_c, f_s, f_o, f_t, and a gear mesh frequency (GMF) calculated by Equations (1) to (6), wherein

6. The fault detecting method according to claim 1, wherein the extracting of the third characteristic values in the envelope frequency domain, for the one or more preset frequency bands by each of the plurality of sensors in the envelope frequency domain based on the vibration data received by the sensors comprises:

extracting an envelope from the vibration data for each of the plurality of sensors;

performing a fast Fourier transform (FFT) operation based on the envelope; and

extracting, as a third characteristic value based on a result of the performing of the FFT operation, a peak value in a frequency band which has a corresponding one of the one or more preset center frequencies for each of the plurality of sensors as a center thereof, and opposite ends which are each spaced apart from the preset center frequency by 1 Hz.

7. The fault detecting method according to claim 6, wherein the extracting of the envelope from the vibration data comprises:

passing the vibration data through a band pass filter;

obtaining an absolute value of an output of the band pass filter; and

passing the obtained absolute value through a low pass filter.

8. The fault detecting method according to claim 6, wherein the one or more preset center frequencies comprise frequencies f_r, f_c, f_s, f_o, f_t, and a gear mesh frequency (GMF) calculated by Equations (1) to (6), wherein

9. The fault detecting method according to claim 1, further comprising:

forming a frequency matrix having respective locations of the plurality of sensors and the one or more preset frequency bands as a row and a column and having the second characteristic values as values of the matrix, and an envelope frequency matrix having respective locations of the plurality of sensors and the preset frequency bands as a row and a column and having the third characteristic values as values of the matrix; and

displaying the frequency matrix and the envelope frequency matrix on a display.

10. The fault detecting method according to claim 1,

wherein the vibration data is classified into a plurality of classes according to operation conditions, and

wherein operations are performed for each of the plurality of classes.

11. A fault detecting system of detecting a fault in a wind power generator including a main bearing, a gearbox, and a generator using vibration data received from a plurality of sensors, the fault detecting system comprising:

a sensor unit comprising a plurality of sensors disposed at the wind power generator, the plurality of sensors being configured to receive the vibration data;

at least one processor configured to implement;

an abnormal state detection unit configured to extract a first characteristic value in a time domain based on the vibration data received by the sensor unit and detect whether the wind power generator is in an abnormal state; and

a precise diagnosis unit configured to determine, when an abnormal state detection signal is received from the abnormal state detection unit, a location and a kind of a fault by extracting a characteristic value in a frequency domain obtained by performing a Fourier transform operation on the vibration data received by the sensor unit.

12. The fault detecting system according to claim 11, wherein the abnormal state detection unit calculates a first characteristic value including at least one of a root mean square, a kurtosis, and a crest factor based on the vibration data, and determines that the wind power generator is in the abnormal state when the first characteristic value is a preset alarm setting value or more,

wherein the root mean square (x_rms) is calculated by

13. The fault detecting system according to claim 11,

wherein the precise diagnosis unit performs a fast Fourier transform (FFT) based on the vibration data,

wherein the precise diagnosis unit calculate, based on a result of performing the FFT, second characteristic values each of which is a peak value in a frequency band which has a corresponding one of the one or more preset center frequencies for each of the plurality of sensors as a center thereof, and opposite ends which are each spaced apart from the preset center frequency by 1 Hz, and

wherein, when at least one of the second characteristic values is greater than a preset normal value, the precise diagnosis unit determines that the fault is present, and determines a location of the fault and a kind of the fault based both on a location of a sensor that has obtained the at least one second characteristic value and on the one or more preset center frequencies.

14. The fault detecting system according to claim 13, wherein the one or more preset center frequencies comprise frequencies f_r, f_c, f_s, f_o, f_t, and a gear mesh frequency (GMF) calculated by Equations (1) to (6), wherein

15. The fault detecting system according to claim 13,

wherein the precise diagnosis unit extracts an envelope of the vibration data for each of the plurality of sensors,

wherein the precise diagnosis unit performs a fast Fourier transform (FFT) operation based on the envelope,

wherein the precise diagnosis unit calculate, based on a result of performing the FFT, third characteristic values each of which is a peak value in a frequency band which has a corresponding one of the one or more preset center frequencies for each of the plurality of sensors as a center thereof, and opposite ends which are each spaced apart from the preset center frequency by 1 Hz, and

wherein, when at least one of the third characteristic values is greater than a preset normal value, the precise diagnosis unit determines that the fault is present, and determines a location of the fault and a kind of the fault based both on a location of a sensor that has obtained the at least one third characteristic value and on the preset center frequency.

16. The fault detecting system according to claim 15, wherein the one or more preset center frequencies comprise frequencies f_r, f_c, f_s, f_o, f_t, and a gear mesh frequency (GMF) calculated by Equations (1) to (6), wherein

17. The fault defect detecting system according to claim 11,

wherein the plurality of sensors comprises a tachometer and fifteen acceleration sensors,

wherein the tachometer is mounted to a driven shaft extending from the gearbox to the generator and is configured to measure an RPM of the driven shaft, and

wherein the fifteen acceleration sensors comprise two acceleration sensors configured to measure vertical and horizontal vibrations on the main bearing, one acceleration sensor provided on each of an left end and a right end of a torque arm of the gearbox coupled with the main shaft, one acceleration sensor configured to measure vibration of a mechanical pump bearing, one acceleration sensor configured to measure vibration of a wheel bearing of a third gear stage of the gearbox, one acceleration sensor configured to measure vibration of a drive shaft of the third gear stage of the gearbox, two acceleration sensors configured to measure vibration of a driven shaft of the third gear stage of the gearbox, two acceleration sensors configured to measure horizontal and vertical vibrations at a side of the generator which is coupled with the gearbox so as to measure vibration of the generator, and two acceleration sensors configured to measure horizontal and vertical vibrations at a side opposite to the side of the generator that is coupled with the gearbox, and two acceleration sensors configured to detect front/rear direction vibration and left/right direction vibration of the wind power generator.

18. The fault detecting system according to claim 15, further comprising:

a display unit configured to display the first characteristic value, the second characteristic values, the third characteristic values, and the vibration data,

wherein the display unit forms a time matrix having locations of the plurality of sensors and the one or more preset center frequencies and having the first characteristic value as a value of the matrix, a frequency matrix having the locations of the plurality of sensors and the one or more preset center frequencies and having the second characteristic values as value of the matrix, an envelope frequency matrix having the locations of the plurality of sensors and the one or more preset center frequencies and having the third characteristic values as values of the matrix, and a vibration data matrix having the locations of the plurality of sensors and the one or more preset center frequencies and having the received vibration data as a value of the matrix, and

wherein the time matrix, the frequency matrix, the envelope frequency matrix, and the vibration data matrix are successively displayed on the display unit from a top thereof to a bottom.

19. The fault detecting system according to claim 15, further comprising:

a display unit configured to display the first characteristic value, the second characteristic values, and the third characteristic values,

wherein the display unit if further configured to display;

a fundamental information unit configured to display summary information including information about a site where the wind power generator is installed and information about a time during which the vibration data is received, operation data and filter information including a wind speed, a speed of the wind power generator, and production power of the wind power generator, and a shock finder configured to indicate, based on a preset filter range, the number of the plurality of sensors which undergo vibration corresponding to the filter range;

a gear unit including a column representing installation locations of vibration sensor installed on gears, a part representing at least one characteristic value of the first characteristic value, the second characteristic value, and the third characteristic value for each of the vibration sensors, and a part setting a filter value; and

a bearing unit including a column representing installation locations of vibration sensor installed on bearings, a part representing at least one characteristic value of the first characteristic value, the second characteristic value, and the third characteristic value for each of the vibration sensors, and a part setting a filter value, and

wherein the display unit displays a characteristic value corresponding to the set filter value with a color that is different from a color of the other characteristic values so as to distinguish the corresponding characteristic value from the other characteristic values so that a user can recognize the location and the kind of the defect.