CN112162197A - Online diagnosis method for stator and rotor center offset fault of vertical unit - Google Patents

Online diagnosis method for stator and rotor center offset fault of vertical unit Download PDF

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Publication number
CN112162197A
CN112162197A CN202011016603.2A CN202011016603A CN112162197A CN 112162197 A CN112162197 A CN 112162197A CN 202011016603 A CN202011016603 A CN 202011016603A CN 112162197 A CN112162197 A CN 112162197A
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signal
stator
rotor
vertical unit
fault
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谌洪江
卢国林
姚本培
孔祥坤
陈明东
陈国锋
刘军
杨秀江
蒋金宏
王杨琛
杨科帆
周媛
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Guangzhao Branch Of Guizhou Beipanjiang Electric Power Co ltd
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Guangzhao Branch Of Guizhou Beipanjiang Electric Power Co ltd
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/34Testing dynamo-electric machines
    • G01R31/346Testing of armature or field windings
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01HMEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
    • G01H17/00Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves, not provided for in the preceding groups
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/34Testing dynamo-electric machines
    • G01R31/343Testing dynamo-electric machines in operation

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  • General Physics & Mathematics (AREA)
  • Control Of Eletrric Generators (AREA)

Abstract

The invention discloses an online diagnosis method for a stator and rotor center offset fault of a vertical unit, which comprises the following steps: acquiring waveform data of a vibration signal output by a stator and rotor winding of a vertical unit to be diagnosed; denoising the signal by signal conditioning low-pass filtering and converting the signal into a frequency spectrum signal; comparing different frequency components in the frequency spectrum signal with a standard fault map of the stator and the rotor of the vertical unit; and when the comparison result is greater than a preset threshold value, judging that a fault occurs, and sending an alarm signal. The method can accurately, quickly and reliably judge whether the fault exists or not, has high fault diagnosis rate, dynamically eccentric faults of the air gap in the synchronous generator and provides technical support for operation, maintenance and repair of the vertical unit. Furthermore, monitoring data collected by the hydropower station are effectively utilized, and in the aspect of service efficiency enhancement, the condition maintenance, the optimized scheduling and the quality and efficiency enhancement of safe production service are driven through the application of a big data technology.

Description

Online diagnosis method for stator and rotor center offset fault of vertical unit
Technical Field
The invention relates to the technical field of generators, in particular to an online diagnosis method for a stator and rotor center offset fault of a vertical unit.
Background
With the development of economy and the demand on electric power, China establishes a plurality of hydropower stations and hydroelectric generating sets, and in the long-term operation process, most generators have air gap eccentricity in different degrees, which is a condition of uneven air gaps between a stator and a rotor caused by manufacturing and mounting errors, bearing offset, stator core deformation and the like.
The stator and rotor center offset fault of the vertical unit means that in the operation process of the synchronous generator, the center of a stator is the rotation center of a rotor, but the center of the rotor is not coincident with the center of the stator, which is equivalent to that the center of a bearing is offset from the center of the stator to a certain direction, but the rotor rotates by taking the bearing as the center, and the air gap of the stator and the rotor constantly changes.
In the production and operation process of the hydropower station, managers need to make decisions on production plans, operation management, accident handling, daily maintenance and the like of the hydropower station, and the decision making needs to use mass data provided in the production process of the hydropower station as a basis. A large number of sensors are installed in a hydropower station, and a large amount of monitoring data and video monitoring data related to the operation of the hydropower station are generated every second.
However, in practical application, the monitoring data and the video monitoring data cannot be directly used as an effective basis for judging the occurrence of the air gap dynamic eccentric fault of the synchronous generator, and great difficulty is brought to fault diagnosis, later-stage accurate maintenance and repair of the synchronous generator.
Therefore, how to analyze and obtain whether the stator and the rotor of the vertical unit have the air gap dynamic eccentric fault or not based on the monitoring data is a difficult problem to be solved urgently.
Disclosure of Invention
In view of this, the invention provides an online diagnosis method for a vertical unit stator and rotor center offset fault, which can solve the problem of judging whether the vertical unit stator and rotor has an air gap dynamic eccentric fault.
The embodiment of the invention provides an online diagnosis method for a stator and rotor center offset fault of a vertical unit, which comprises the following steps:
acquiring waveform data of a vibration signal output by a stator and rotor winding of a vertical unit to be diagnosed;
denoising the signal by signal conditioning low-pass filtering and converting the signal into a frequency spectrum signal;
comparing different frequency components in the frequency spectrum signal with a standard fault map of the stator and the rotor of the vertical unit;
and when the comparison result is greater than a preset threshold value, judging that a fault occurs, and sending an alarm signal.
In one embodiment, acquiring waveform data of a vibration signal output by a stator and rotor winding of a vertical unit to be diagnosed comprises the following steps:
acquiring two rotor vibration acceleration signals in the axial direction and the diameter direction of a rotor through an acceleration sensor;
and transmitting the two rotor vibration acceleration signals to a signal conditioner through a slip ring current leading device.
In one embodiment, signal conditioning low pass filtering denoising, comprises:
performing N-layer lifting wavelet decomposition on the vibration acceleration signal;
carrying out threshold processing on detail coefficients of each layer;
and (5) carrying out lifting wavelet reconstruction by using the estimated detail coefficient and the approximate coefficient from high to low to obtain a denoised signal.
In one embodiment, the transformation into a spectral signal comprises:
and transforming the denoised vibration acceleration time domain signal into a frequency spectrum signal by utilizing fast Fourier transform.
In one embodiment, when the comparison result is greater than the preset threshold, the method includes:
and when the comparison result shows that the fundamental wave amplitude of the output vibration acceleration of the stator and rotor windings of the vertical unit to be diagnosed is larger than the preset threshold value.
Compared with the prior art, the method for diagnosing the offset fault of the stator and the rotor center of the vertical unit on line provided by the embodiment of the invention can accurately, quickly and reliably judge whether the fault exists or not, has high fault diagnosis rate, dynamically offsets the fault of the air gap in the synchronous generator, and provides technical support for the operation, maintenance and repair of the vertical unit. And also has the following advantages:
1) monitoring data collected by the hydropower station is effectively utilized, and in the aspect of service enhancement, the condition maintenance, the optimized scheduling and the quality and efficiency improvement of safe production service are driven by the application of a big data technology.
2) When the fault is judged to exist, alarming is carried out in time; in the aspect of state maintenance, the hidden trouble of the fault can be found in time, and the unit can be guided to be maintained finely.
3) In the aspect of optimizing and scheduling, the running of a failed generator is stopped, a standby generator set is started, the load distribution of the generator set is optimized, and the efficiency of a power generation enterprise is improved.
4) In the aspect of safety production, safety accidents caused by faults are reduced, and the safety production management level of the power station is improved.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a flowchart of an online diagnosis method for a vertical unit stator and rotor center offset fault according to an embodiment of the present invention;
fig. 2 is a flowchart of step S100 according to an embodiment of the present invention;
fig. 3 is a flowchart of signal conditioning low-pass filtering denoising according to an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
Referring to fig. 1, an embodiment of the present invention provides an online diagnosis method for a vertical unit stator and rotor center offset fault, including:
s100, acquiring waveform data of vibration signals output by stator and rotor windings of the vertical unit to be diagnosed;
s200, denoising through signal conditioning low-pass filtering and converting into a frequency spectrum signal;
s300, comparing different frequency components in the frequency spectrum signal with a standard fault map of the stator and the rotor of the vertical unit;
and S400, when the comparison result is larger than a preset threshold value, judging that a fault occurs, and sending an alarm signal.
The method comprises the steps of collecting waveform data of vibration signals output by a stator and rotor winding of the vertical unit to be diagnosed, filtering and denoising, and transforming the vibration time domain signals into frequency spectrum signals by utilizing fast Fourier transform. After a large amount of historical data are mined, deviation calculation is carried out on the extracted characteristic signal values and the historical values under the same working condition, trend changes of the deviation state of the centers of the stator and the rotor can be revealed, and potential faults can be found in advance. And an early warning signal is sent out to prompt operators to pay attention to monitoring the health state of the central deviation of the stator and the rotor, so that the faults are avoided, and the loss is avoided. The method can accurately, quickly and reliably judge whether the fault exists or not, has high fault diagnosis rate, dynamically eccentric faults of the air gap in the synchronous generator and provides technical support for operation, maintenance and repair of the vertical unit.
The above steps will be described in detail below.
In one embodiment, as described with reference to fig. 2, step S100 includes:
s101, acquiring two rotor vibration acceleration signals in the axial direction and the diameter direction of a rotor through an acceleration sensor;
and S102, transmitting the two rotor vibration acceleration signals to a signal conditioner through a slip ring current leading device.
A certain number of two rotor vibration signals in the rotor axis and diameter directions in a certain sampling period are measured according to a determined time interval or sampling frequency through an eddy current acceleration sensor or a Hall sensor. And is transmitted to the signal conditioner by the slip ring current-leading device. Furthermore, the signal conditioned by the signal conditioner is converted into a digital signal by an A/D converter and is read into a computer, and the computer performs program processing.
In one embodiment, the denoising by signal conditioning lowpass filtering in step S200 includes:
s201, performing N-layer lifting wavelet decomposition on the vibration acceleration signal;
s202, carrying out threshold processing on detail coefficients of each layer;
s203, lifting wavelet reconstruction is carried out by using the estimated detail coefficient and the approximate coefficient from high to low, and a signal after noise reduction is obtained.
In this embodiment, the specific steps are as follows: (1) performing N-layer lifting wavelet decomposition on the vibration acceleration signal; for passing vibration acceleration signal
Figure BDA0002699265370000051
Performing wavelet lifting, and calculating by formula:
se (k) ═ s (2k), k ∈ Z; z is a positive integer;
so(k)=s(2k+1),k∈Z;
subdividing a data sequence { s (k), k ∈ Z } into an odd sample sequence and an even sample sequence;
re-routing type
d(k)=so(k)-P[se(k)],k∈Z
c(k)=se(k)+U[d(k)],k∈Z
Obtaining approximate coefficients c and detail coefficients d of the N groups of lifting wavelets,
wherein, P (-) is a predictor, so (k) is predicted by se (k), the prediction deviation is a detail signal d (k), U (-) is an updater, se (k) is updated by the detail signal d (k), and c (k) is an approximation signal;
(2) carrying out threshold processing on detail coefficients of each layer; is represented by the formula:
Figure BDA0002699265370000052
the soft threshold processing is performed and the soft threshold processing is performed,
wherein sign (x) is a sign function of x;
obtaining an estimated detail coefficient G;
(3) carrying out lifting wavelet reconstruction by using the estimated detail coefficient G and the approximate coefficient c from high to low; is composed of
se(k)=c(k)-U[d(k)],k∈Z;
so(k)=d(k)-P[se(k)],k∈Z;
And performing lifting wavelet reconstruction from high to low to obtain a signal subjected to noise reduction.
The low-frequency components in the signals are decomposed, so that the high-frequency components contained in the low frequency of the next level of resolution are reduced, the essence of the original signals is shown, the signals are gathered, and the characteristic values show the dense characteristic; the method carries out denoising reconstruction on the signal, effectively filters out the interfered noise signal, and enables discrete points of characteristic values to be embodied by the most essential information of the signal, the plane distribution of the characteristic values is quite scattered before the signal is denoised, the distribution conditions of various running states are difficult to distinguish, and after denoising processing, the distribution conditions of the characteristic values are obviously improved, the distribution of the characteristic values is dense, and the obvious interval exists among the running states.
In one embodiment, when the comparison result is greater than the preset threshold, the method includes:
and when the comparison result shows that the fundamental wave amplitude of the output vibration acceleration of the stator and rotor windings of the vertical unit to be diagnosed is larger than the preset threshold value.
In one embodiment, step S400 includes:
and when the fundamental wave amplitude of the output vibration acceleration of the stator and rotor windings of the vertical unit to be diagnosed is larger than a preset threshold value according to the comparison result, judging that a fault occurs, and sending an alarm signal.
In this embodiment, the computer processes the digital signal by the following program to complete the fault diagnosis process and display the result; comparing different frequency components in the frequency spectrum signal with a standard fault map of the stator and the rotor of the vertical unit; judging whether a fault occurs; if a fault occurs, the alarm sends out an alarm signal. Further, the alarm can adopt three levels of alarms, wherein green indicates that the index is in a qualified state currently, yellow indicates that the index is in an alarm state, and red indicates that the index is in a dangerous state.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention and are not limited. Although the present invention has been described in detail with reference to the embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the spirit and scope of the invention as defined in the appended claims.

Claims (5)

1. An online diagnosis method for a stator and rotor center offset fault of a vertical unit is characterized by comprising the following steps:
acquiring waveform data of a vibration signal output by a stator and rotor winding of a vertical unit to be diagnosed;
denoising the signal by signal conditioning low-pass filtering and converting the signal into a frequency spectrum signal;
comparing different frequency components in the frequency spectrum signal with a standard fault map of the stator and the rotor of the vertical unit;
and when the comparison result is greater than a preset threshold value, judging that a fault occurs, and sending an alarm signal.
2. The method for on-line diagnosis of the offset fault of the stator and rotor center of the vertical unit according to claim 1, wherein the step of obtaining waveform data of the vibration signal output by the stator and rotor winding of the vertical unit to be diagnosed comprises the following steps:
acquiring two rotor vibration acceleration signals in the axial direction and the diameter direction of a rotor through an acceleration sensor;
and transmitting the two rotor vibration acceleration signals to a signal conditioner through a slip ring current leading device.
3. The method for on-line diagnosis of the offset fault of the stator and the rotor of the vertical unit as claimed in claim 2, wherein the denoising by signal conditioning low-pass filtering comprises:
performing N-layer lifting wavelet decomposition on the vibration acceleration signal;
carrying out threshold processing on detail coefficients of each layer;
and (5) carrying out lifting wavelet reconstruction by using the estimated detail coefficient and the approximate coefficient from high to low to obtain a denoised signal.
4. The method for on-line diagnosis of the vertical unit stator and rotor center offset fault according to claim 3, wherein the step of converting the signal into a frequency spectrum signal comprises the following steps:
and transforming the denoised vibration acceleration signal into a frequency spectrum signal by utilizing fast Fourier transform.
5. The method for on-line diagnosis of the offset fault of the stator and the rotor of the vertical unit according to claim 3, wherein when the comparison result is greater than a preset threshold, the method comprises the following steps:
and when the comparison result shows that the fundamental wave amplitude of the output vibration acceleration of the stator and rotor windings of the vertical unit to be diagnosed is larger than the preset threshold value.
CN202011016603.2A 2020-09-24 2020-09-24 Online diagnosis method for stator and rotor center offset fault of vertical unit Pending CN112162197A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115638875A (en) * 2022-11-14 2023-01-24 国家电投集团河南电力有限公司技术信息中心 Power plant equipment fault diagnosis method and system based on map analysis
CN116256164A (en) * 2023-05-12 2023-06-13 莫安迪(苏州)电机技术有限公司 Vertical variable frequency rotor testing device

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CN109540447A (en) * 2018-11-12 2019-03-29 中国飞行试验研究院 Aeroengine fan blades foreign object strike test platform
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CN1696630A (en) * 2004-12-27 2005-11-16 西北工业大学 Method and equipment for measuring torsional vibration of rotating mechanical rotor
CN102262215A (en) * 2011-04-29 2011-11-30 华北电力大学(保定) Method for detecting stator and rotor air gap eccentric faults of large generator
WO2014123443A1 (en) * 2013-02-06 2014-08-14 Ivanov Alexandr Vladimirovich Method and device for vibration diagnosis and forecasting sudden engine failure
CN108318815A (en) * 2018-01-17 2018-07-24 河海大学 A kind of doubly-fed wind turbine on-line monitoring and synthetic fault diagnosis method
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CN109540447A (en) * 2018-11-12 2019-03-29 中国飞行试验研究院 Aeroengine fan blades foreign object strike test platform
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Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115638875A (en) * 2022-11-14 2023-01-24 国家电投集团河南电力有限公司技术信息中心 Power plant equipment fault diagnosis method and system based on map analysis
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CN116256164A (en) * 2023-05-12 2023-06-13 莫安迪(苏州)电机技术有限公司 Vertical variable frequency rotor testing device
CN116256164B (en) * 2023-05-12 2023-08-08 莫安迪(苏州)电机技术有限公司 Vertical variable frequency rotor testing device

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