CN115728057A - Vibration monitoring and fault diagnosis method for gearbox of wind generating set - Google Patents
Vibration monitoring and fault diagnosis method for gearbox of wind generating set Download PDFInfo
- Publication number
- CN115728057A CN115728057A CN202211374051.1A CN202211374051A CN115728057A CN 115728057 A CN115728057 A CN 115728057A CN 202211374051 A CN202211374051 A CN 202211374051A CN 115728057 A CN115728057 A CN 115728057A
- Authority
- CN
- China
- Prior art keywords
- gearbox
- generating
- fault
- data
- time
- 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.)
- Granted
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 123
- 238000003745 diagnosis Methods 0.000 title claims abstract description 37
- 238000000034 method Methods 0.000 title claims abstract description 34
- 238000012423 maintenance Methods 0.000 claims abstract description 30
- 238000004519 manufacturing process Methods 0.000 claims description 9
- 239000011159 matrix material Substances 0.000 claims description 9
- 230000002159 abnormal effect Effects 0.000 claims description 6
- 230000007613 environmental effect Effects 0.000 claims description 4
- 238000010248 power generation Methods 0.000 abstract description 4
- 230000007547 defect Effects 0.000 description 8
- 238000004458 analytical method Methods 0.000 description 6
- 238000001514 detection method Methods 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 230000003111 delayed effect Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 230000007488 abnormal function Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000010835 comparative analysis Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000005461 lubrication Methods 0.000 description 1
- 230000002265 prevention Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
Images
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/70—Wind energy
- Y02E10/72—Wind turbines with rotation axis in wind direction
Landscapes
- Wind Motors (AREA)
- Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
Abstract
The application relates to the technical field of wind power generation, in particular to a vibration monitoring and fault diagnosis method for a gearbox of a wind generating set. The method comprises the following steps: acquiring historical operating data of a plurality of groups of wind turbine generator gearbox, and generating a wind turbine generator gearbox vibration standard value according to the historical operating data; acquiring real-time vibration data of a gearbox of the wind turbine generator, and generating a real-time gearbox vibration monitoring curve according to the real-time vibration data; generating a diagnosis result according to the difference value between the real-time gearbox vibration monitoring curve and the wind turbine generator gearbox vibration standard value, generating an early warning instruction according to the difference value, and sending a maintenance instruction to a monitoring terminal according to the early warning instruction; and generating fault record data according to the diagnosis result, generating a fault database according to the fault record data, and judging whether the fault is a familial fault according to the fault record data. Therefore, serious faults of the wind generating set are prevented, safe and stable operation of the wind generating set is guaranteed, and operation quality of the wind generating set is improved.
Description
Technical Field
The application relates to the technical field of wind power generation, in particular to a vibration monitoring and fault diagnosis method for a gearbox of a wind generating set.
Background
As a renewable new energy technology, wind power generation is rapidly developed in China in recent years. By the end of 2012, the wind generation sets 53764 are installed cumulatively in China, the installed capacity reaches 75324.2MW, and the wind generation set is in the leading position in the world. The wind generating set is a key device for wind power generation, is mostly arranged on a remote field or a rack which is dozens of meters high on the sea, has severe working conditions and very difficult maintenance, and often causes very large accidents and huge loss if the wind generating set fails to be timely treated. Therefore, in order to improve the operational safety, reliability and availability of the wind generating set and reduce the maintenance cost, the development of a monitoring system and a fault diagnosis system capable of realizing the remote online monitoring of the operational state of the wind generating set is urgently needed.
The gear box of the wind generating set comprises a transmission shaft, a bearing, gear teeth and other parts. The faults of the components are caused by inherent defects, poor lubrication or overload, and can be reflected by the operating parameters of the wind generating set and working condition parameters such as vibration, temperature and the like of the corresponding components. However, the traditional monitoring system for the wind generating set can only monitor, but lacks an automatic fault diagnosis system, cannot early warn in time, cannot predict maintenance, and cannot realize remote observation of the running state of the set.
Disclosure of Invention
The purpose of this application is: in order to solve the technical problem, the application provides a vibration monitoring and fault diagnosis method for a gearbox of a wind generating set, and aims to realize remote monitoring and fault diagnosis for the wind generating set.
In some embodiments of the application, vibration data of a gearbox of the wind generating set are obtained in real time according to detection requirements, a standard vibration value under the same running time and the same temperature and other factors is determined according to historical data, the running state of the wind generating set is monitored, and the fault defect frequency is found through characteristic analysis and comparison of faults, so that the type and the position of the faults are determined quickly.
In some embodiments of the application, the fault database is continuously updated according to the fault record data through preset time, the fault types are continuously refined, and different fault defect frequencies are collected more, so that the faults are accurately identified, and the fault processing efficiency is improved.
In some embodiments of this application, through the vibration that detects aerogenerator gear box, the emergence of timely early warning unit trouble realizes unmanned on duty, the maintenance of foreknowledge to the serious trouble appears in the prevention aerogenerator group, guarantee aerogenerator group's safe and steady operation improves aerogenerator group's operational quality.
In some embodiments of the present application, a method for vibration monitoring and fault diagnosis of a gearbox of a wind turbine generator system is provided, comprising:
the method comprises the following steps: acquiring historical operating data of a plurality of groups of wind turbine generator gearbox, and generating a wind turbine generator gearbox vibration standard value according to the historical operating data; acquiring real-time vibration data of a gearbox of a wind turbine generator, and generating a real-time gearbox vibration monitoring curve according to the real-time vibration data;
step two: generating a diagnosis result according to the difference value between the real-time gearbox vibration monitoring curve and the wind turbine generator gearbox vibration standard value, generating an early warning instruction according to the difference value, and sending a maintenance instruction to a monitoring terminal according to the early warning instruction;
step three: and generating fault record data according to the diagnosis result, generating a fault database according to the fault record data, and judging whether the fault record data is a familial fault or not according to the fault record data.
In some embodiments of this application, when generating wind turbine generator system gear box vibration standard value, include:
acquiring operation vibration data of a newly-built gear box, a fault gear box and a monitoring part of an operation gear box of a wind turbine generator, and acquiring a characteristic value of vibration of the gear box;
acquiring the accumulated operation hours of the unit, the use time of a gear box and historical environmental data to generate historical operation data;
and generating a vibration standard value of the gearbox of the wind turbine generator according to the characteristic value of the vibration of the gearbox and the historical operation data.
In some embodiments of the present application, said generating a real-time gearbox vibration monitoring curve comprises:
acquiring the running time of a gear box, real-time environment data and real-time vibration data;
generating a real-time gearbox vibration monitoring curve according to the real-time vibration data and the real-time gearbox operation duration;
and determining a corresponding wind turbine generator gearbox vibration standard value according to the gearbox operation time and the real-time environment data, and generating a monitoring interval.
In some embodiments of the application, the generating the diagnosis result includes:
presetting a gearbox vibration monitoring curve difference matrix A, and setting A (A1, A2, A3), wherein A1 is a preset first gearbox vibration monitoring curve difference, A2 is a preset second gearbox vibration monitoring curve difference, A3 is a preset third gearbox vibration monitoring curve difference, and A1 is more than A2 and less than A3;
acquiring a real-time difference value a;
when the real-time difference a is smaller than a preset first gearbox vibration monitoring curve difference A1, namely a is smaller than A1, the diagnosis result is that the equipment is normal;
when the monitoring data a is in a preset first gearbox vibration monitoring curve difference value A1 and a preset second gearbox vibration monitoring curve difference value A2, namely A1 is larger than a and smaller than A2, the diagnosis result is that the equipment is abnormal;
when the monitoring data a are in a preset second gearbox vibration monitoring curve difference value A2 and a preset third gearbox vibration monitoring curve difference value A3, namely A2 is larger than a and smaller than A3, the diagnosis result is that the main function of the equipment is abnormal;
and when the monitoring data a is larger than the difference A3 of the vibration monitoring curve of the preset third gearbox, namely a is larger than A3, the diagnosis result is that the equipment is invalid.
In some embodiments of the present application, when the difference value generates the warning instruction, the method includes:
presetting a first time interval T1;
obtaining the duration time t1 of the real-time difference value a in each interval of the difference value matrix A of the preset gearbox vibration monitoring curve;
when T1 is larger than T1, generating a primary early warning instruction;
and when T1 is less than T1, no early warning instruction is generated.
In some embodiments of the present application, when the difference generates the early warning instruction, the method further includes:
when the real-time difference a is smaller than a preset first gearbox vibration monitoring curve difference A1, namely a is smaller than A1, no early warning instruction is generated;
when the monitoring data a is in a preset first gearbox vibration monitoring curve difference value A1 and a preset second gearbox vibration monitoring curve difference value A2, generating a first-stage early warning instruction,
when the monitoring data a are in a preset second gearbox vibration monitoring curve difference value A2 and a preset third gearbox vibration monitoring curve difference value A3, namely A2 is larger than a and smaller than A3, a secondary early warning instruction is generated;
and when the monitoring data a is larger than a preset third gearbox vibration monitoring curve difference value A3, namely a is larger than A3, generating a three-level early warning instruction.
In some embodiments of the present application, when sending the warning instruction to the monitoring terminal, the method further includes:
presetting an early warning instruction generation frequency matrix N, and setting N (N1, N2, N3), wherein N1 is the preset first early warning instruction generation frequency, N2 is the preset second early warning instruction generation frequency, N3 is the preset third early warning instruction generation frequency, and N1 is more than N2 and is more than N3;
if the generation times of the first-stage early warning instruction are larger than the generation times N3 of the third early warning instruction within the preset time interval, sending a maintenance instruction to the monitoring terminal;
if the generation times of the secondary early warning instructions are larger than the generation times N2 of the preset second early warning instructions within the preset time interval, sending a maintenance instruction to the monitoring terminal;
and if the generation times of the three-stage early warning instructions are larger than the preset first early warning instruction generation times N1 within the preset time interval, sending a maintenance instruction to the monitoring terminal.
In some embodiments of the present application, the generating the fault database includes:
acquiring historical fault data and expert knowledge base data of the wind turbine generator, and generating a primary fault database;
acquiring fault type information of the gearbox, corresponding real-time vibration data and real-time environment data, and generating fault record data;
and updating the primary fault database according to the fault record data.
In some embodiments of the present application, the updating the primary failure database includes:
presetting a time node, and updating the primary fault database according to the time node;
and acquiring the occurrence frequency of the faults, and setting a time interval between the time interval and the next time node according to the occurrence frequency of the faults.
In some embodiments of the present application, the determining whether the fault is a familial fault includes:
acquiring production parameters of different gearbox parts and fault recording data of different gearboxes;
generating part labels according to the production parameters of the different gearbox parts;
and generating a judgment result according to the part label and the fault record data.
Compared with the prior art, the method for monitoring the vibration of the gear box of the wind generating set and diagnosing the fault of the gear box of the wind generating set has the advantages that:
according to detection requirements, vibration data of a gearbox of the wind generating set are obtained in real time, standard vibration values under the same operation time, the same temperature and other factors are determined according to historical data, the operation state of the wind generating set is monitored, and the fault frequency is found through characteristic analysis and comparison of faults, so that the type and the position of the faults are determined rapidly.
Through the preset time, the fault database is continuously updated according to the fault record data, the fault types are continuously refined, and different fault defect frequencies are collected more, so that the fault is accurately identified, and the fault processing efficiency is improved.
By detecting the vibration of the gear box of the wind driven generator, the occurrence of the fault of the wind driven generator unit is early warned in time, unattended operation and predicted maintenance are realized, so that the serious fault of the wind driven generator unit is prevented, the safe and stable operation of the wind driven generator unit is ensured, and the operation quality of the wind driven generator unit is improved.
Drawings
FIG. 1 is a schematic flow chart of a vibration monitoring and fault diagnosis method for a gearbox of a wind generating set in a preferred embodiment of the application;
fig. 2 is a schematic flow chart of a method for monitoring vibration and diagnosing failure of a gearbox of a wind generating set according to a preferred embodiment of the present application.
Detailed Description
The following detailed description of embodiments of the present application will be described in conjunction with the accompanying drawings and examples. The following examples are intended to illustrate the present application but are not intended to limit the scope of the present application.
In the description of the present application, it is to be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience in describing the present application and simplifying the description, but do not indicate or imply that the referred device or element must have a particular orientation, be constructed in a particular orientation, and be operated, and thus should not be construed as limiting the present application.
The terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or to implicitly indicate the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present application, "a plurality" means two or more unless otherwise specified.
In the description of the present application, it is to be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present application can be understood in a specific case by those of ordinary skill in the art.
As shown in fig. 1, a method for vibration monitoring and fault diagnosis of a gearbox of a wind turbine generator system according to a preferred embodiment of the present application includes:
the method comprises the following steps: acquiring historical operating data of a plurality of groups of wind turbine generator gearbox, and generating a wind turbine generator gearbox vibration standard value according to the historical operating data; acquiring real-time vibration data of a gearbox of the wind turbine generator, and generating a real-time gearbox vibration monitoring curve according to the real-time vibration data;
step two: generating a diagnosis result according to the difference value between the real-time gearbox vibration monitoring curve and the wind turbine generator gearbox vibration standard value, generating an early warning instruction according to the difference value, and sending a maintenance instruction to a monitoring terminal according to the early warning instruction;
step three: and generating fault record data according to the diagnosis result, generating a fault database according to the fault record data, and judging whether the fault is a familial fault according to the fault record data.
Specifically, when generating wind turbine generator system gear box vibration standard value, include:
acquiring operation vibration data of a newly-built gear box, a fault gear box and a monitoring part of an operation gear box of a wind turbine generator, and acquiring a characteristic value of vibration of the gear box;
acquiring the accumulated operation hours of the unit, the service time of a gear box and historical environmental data to generate historical operation data;
and generating a vibration standard value of the gearbox of the wind turbine generator according to the characteristic value of the vibration of the gearbox and historical operation data.
Specifically, when generating real-time gearbox vibration monitoring curve, include:
acquiring the running time of a gear box, real-time environment data and real-time vibration data;
generating a real-time gearbox vibration monitoring curve according to the real-time vibration data and the real-time gearbox operation duration;
and determining a corresponding wind turbine generator gearbox vibration standard value according to the operation time of the gearbox and the real-time environment data, and generating a monitoring interval.
It can be understood that, in the above embodiment, the vibration data of the gearbox of the wind generating set is obtained in real time, the standard vibration value under the same operation time, the same temperature and other factors is determined according to the historical data, the interference of environmental factors is eliminated, the operation state of the wind generating set is accurately monitored, and the fault frequency is found through characteristic analysis and comparison of the fault, so that the type and the position of the fault are quickly determined.
In a preferred embodiment of the present application, the generating the diagnosis result includes:
presetting a gear box vibration monitoring curve difference matrix A, and setting A (A1, A2, A3), wherein A1 is a preset first gear box vibration monitoring curve difference, A2 is a preset second gear box vibration monitoring curve difference, A3 is a preset third gear box vibration monitoring curve difference, and A1 is more than A2 and is more than A3;
acquiring a real-time difference value a;
when the real-time difference a is smaller than a preset first gearbox vibration monitoring curve difference A1, namely a is smaller than A1, the diagnosis result is that the equipment is normal;
when the monitoring data a are in a preset first gearbox vibration monitoring curve difference value A1 and a preset second gearbox vibration monitoring curve difference value A2, namely A1 is larger than a and smaller than A2, the diagnosis result is that the equipment is abnormal;
when the monitoring data a are in a preset second gearbox vibration monitoring curve difference value A2 and a preset third gearbox vibration monitoring curve difference value A3, namely A2 is larger than a and smaller than A3, the diagnosis result is that the main function of the equipment is abnormal;
and when the monitoring data a is larger than the difference A3 of the preset third gearbox vibration monitoring curve, namely a is larger than A3, the diagnosis result is that the equipment is invalid.
Specifically, the equipment normally indicates that the operation parameters or the states change but normally fluctuate, the equipment abnormity indicates that the operation parameters exceed the normal range, the main functions are not affected, the fault can be timely arranged and eliminated, and the main function abnormity of the equipment indicates that some functions of the equipment cannot be realized and can be processed according to the abnormal function condition; equipment failure indicates that the equipment is inoperable and needs immediate disposal or replacement.
As shown in fig. 2, in a preferred embodiment of the present application, when the difference generates the warning instruction, the method includes:
presetting a first time interval T1;
obtaining the duration time t1 of the real-time difference value a in each interval of a difference value matrix A of a preset gearbox vibration monitoring curve;
when T1 is larger than T1, generating an early warning instruction;
and when T1 is less than T1, no early warning instruction is generated.
Specifically, accidental fluctuation data are eliminated through the preset difference value duration, and the monitoring accuracy is guaranteed.
Specifically, when the difference generates the warning instruction, the method further includes:
when the real-time difference a is smaller than a preset first gearbox vibration monitoring curve difference A1, namely a is smaller than A1, no early warning instruction is generated;
when the monitoring data a are in a preset first gearbox vibration monitoring curve difference value A1 and a preset second gearbox vibration monitoring curve difference value A2, generating a first-stage early warning instruction;
when the monitoring data a are in a preset second gearbox vibration monitoring curve difference value A2 and a preset third gearbox vibration monitoring curve difference value A3, namely A2 is larger than a and smaller than A3, generating a secondary early warning instruction;
and when the monitoring data a is larger than a preset third gearbox vibration monitoring curve difference value A3, namely a is larger than A3, generating a three-level early warning instruction.
Specifically, the primary early warning instruction means that the operation of equipment is not influenced within a certain time, a maintenance space within a certain time is allowed, and the maintenance space is usually listed in a quarterly or annual maintenance plan, so that the maintenance frequency is reduced; the secondary early warning instruction means that the operation cannot be stopped immediately, but if the maintenance is continued to be delayed, the probability of accidents is high, so that the defects are scheduled to be overhauled in the near term to ensure the safe operation; the three-level early warning instruction represents that the whole pipe network, the human body and the equipment system can be seriously threatened, the safety needs to be timely processed, if the maintenance is delayed, the probability of major accidents is very high, and the serious threat can be brought once the major accidents happen, so the defects are immediately repaired once found.
Specifically speaking, when sending the early warning instruction to monitor terminal, still include:
presetting an early warning instruction generation frequency matrix N, and setting N (N1, N2, N3), wherein N1 is the preset first early warning instruction generation frequency, N2 is the preset second early warning instruction generation frequency, N3 is the preset third early warning instruction generation frequency, and N1 is more than N2 and is more than N3;
if the generation times of the first-stage early warning instruction are larger than the generation times N3 of the preset third early warning instruction within the preset time interval, sending a maintenance instruction to the monitoring terminal;
if the generation times of the secondary early warning instructions are larger than the generation times N2 of the preset second early warning instructions within the preset time interval, sending a maintenance instruction to the monitoring terminal;
and if the generation times of the three-stage early warning instructions are larger than the preset first early warning instruction generation times N1 within the preset time interval, sending a maintenance instruction to the monitoring terminal.
Specifically, different maintenance schemes are set according to maintenance instructions generated by the early warning instructions without grades.
In the preferred embodiment of the present application, when generating the fault database, the method includes:
acquiring historical fault data and expert knowledge base data of the wind turbine generator, and generating a primary fault database;
acquiring fault type information of the gearbox, corresponding real-time vibration data and real-time environment data, and generating fault record data;
and updating the primary fault database according to the fault record data.
Specifically, the updating of the primary failure database includes:
presetting a time node, and updating a primary fault database according to the time node;
and acquiring the occurrence frequency of the faults, and setting a time interval between the time interval and the next time node according to the occurrence frequency of the faults.
Specifically, the fault log data includes; the system comprises a district name, an equipment manufacturer, failure occurrence time, failure property, a person on duty, failure elimination date, a failure eliminator, an acceptance checker and the like.
Specifically, the fault database comprises fault characteristic values and a fault processing method, and a maintainer can directly obtain the fault position and the fault type of the wind turbine generator and a maintenance method of the wind turbine generator through a maintenance instruction, so that the maintenance efficiency is improved.
Specifically, the judging whether the fault is a familial fault includes:
acquiring production parameters of different gearbox parts and fault record data of different gearboxes;
generating part labels according to production parameters of different gearbox parts;
and generating a judgment result according to the part label and the fault record data.
Specifically, multi-dimensional comparative analysis is automatically performed on manufacturers, models, versions, production time and the like of the gear boxes, and similarity relation among equipment is established to serve as the basis of family fault analysis. The fault management model examines the fault information record regularly, performs statistical analysis on similar faults of similar equipment, compares the result with a set defined threshold value, obtains and reports whether the similar faults are potential familial faults, and confirms whether the analysis result is the familial fault.
Specifically, the familial fault is a fault easily caused in the operation process of equipment due to the production process, and the familial fault is avoided in the production process, so that the operation stability of the wind generating set is improved.
According to the first concept of the application, vibration data of the gearbox of the wind generating set are obtained in real time according to detection requirements, standard vibration values under the same operation time, the same temperature and other factors are determined according to historical data, the operation state of the wind generating set is monitored, and the fault defect frequency is found through characteristic analysis and comparison of faults, so that the type and the position of the faults are determined rapidly.
According to the second concept of the application, the fault database is continuously updated according to the fault record data through the preset time, the fault types are continuously refined, and different fault defect frequencies are collected more, so that the faults are accurately identified, and the fault processing efficiency is improved.
According to the third concept of the application, through detecting the vibration of the gear box of the wind driven generator, the occurrence of the fault of the wind driven generator unit is early warned in time, unattended operation and predicted maintenance are achieved, so that the serious fault of the wind driven generator unit is prevented, the safe and stable operation of the wind driven generator unit is guaranteed, and the operation quality of the wind driven generator unit is improved.
The foregoing is only a preferred embodiment of the present application, and it should be noted that, for those skilled in the art, several modifications and substitutions can be made without departing from the technical principle of the present application, and these modifications and substitutions should also be regarded as the protection scope of the present application.
Claims (10)
1. A vibration monitoring and fault diagnosis method for a gearbox of a wind generating set is characterized by comprising the following steps:
the method comprises the following steps: acquiring historical operating data of a plurality of groups of wind turbine generator gearbox, and generating a wind turbine generator gearbox vibration standard value according to the historical operating data; acquiring real-time vibration data of a gearbox of a wind turbine generator, and generating a real-time gearbox vibration monitoring curve according to the real-time vibration data;
step two: generating a diagnosis result according to the difference value between the real-time gearbox vibration monitoring curve and the wind turbine generator gearbox vibration standard value, generating an early warning instruction according to the difference value, and sending a maintenance instruction to a monitoring terminal according to the early warning instruction;
step three: and generating fault record data according to the diagnosis result, generating a fault database according to the fault record data, and judging whether the fault record data is a familial fault or not according to the fault record data.
2. The method for vibration monitoring and fault diagnosis of a wind turbine generator system gearbox according to claim 1, wherein when generating the wind turbine generator system gearbox vibration standard value, the method comprises:
acquiring operation vibration data of a newly-built gear box, a fault gear box and a monitoring part of an operation gear box of a wind turbine generator, and acquiring a characteristic value of vibration of the gear box;
acquiring the accumulated operation hours of the unit, the use time of a gear box and historical environmental data to generate historical operation data;
and generating a vibration standard value of the gearbox of the wind turbine generator according to the characteristic value of the vibration of the gearbox and the historical operation data.
3. The method of claim 2, wherein the generating a real-time gearbox vibration monitoring curve comprises:
acquiring the running time of a gearbox, real-time environment data and real-time vibration data;
generating a real-time gearbox vibration monitoring curve according to the real-time vibration data and the real-time gearbox operation duration;
and determining a corresponding wind turbine generator gearbox vibration standard value according to the gearbox operation time and the real-time environment data, and generating a monitoring interval.
4. The method of claim 3, wherein the generating the diagnostic result comprises:
presetting a gear box vibration monitoring curve difference matrix A, and setting A (A1, A2, A3), wherein A1 is a preset first gear box vibration monitoring curve difference, A2 is a preset second gear box vibration monitoring curve difference, A3 is a preset third gear box vibration monitoring curve difference, and A1 is more than A2 and is more than A3;
acquiring a real-time difference value a;
when the real-time difference a is smaller than a preset first gearbox vibration monitoring curve difference A1, namely a is smaller than A1, the diagnosis result is that the equipment is normal;
when the monitoring data a are in a preset first gearbox vibration monitoring curve difference value A1 and a preset second gearbox vibration monitoring curve difference value A2, namely A1 is larger than a and smaller than A2, the diagnosis result is that the equipment is abnormal;
when the monitoring data a are in a preset second gearbox vibration monitoring curve difference value A2 and a preset third gearbox vibration monitoring curve difference value A3, namely A2 is greater than a and less than A3, the diagnosis result is that the main function of the equipment is abnormal;
and when the monitoring data a is larger than the difference A3 of the vibration monitoring curve of the preset third gearbox, namely a is larger than A3, the diagnosis result is that the equipment is invalid.
5. The method of claim 4, wherein the step of generating the warning command comprises:
presetting a first time interval T1;
obtaining the duration time t1 of the real-time difference value a in each interval of the difference value matrix A of the preset gearbox vibration monitoring curve;
when T1 is larger than T1, generating an early warning instruction;
and when T1 is less than T1, no early warning instruction is generated.
6. The method of claim 5, wherein the step of generating the warning command further comprises:
when the real-time difference a is smaller than a preset first gearbox vibration monitoring curve difference A1, namely a is smaller than A1, no early warning instruction is generated;
when the monitoring data a is in a preset first gearbox vibration monitoring curve difference value A1 and a preset second gearbox vibration monitoring curve difference value A2, generating a first-stage early warning instruction,
when the monitoring data a are in a preset second gearbox vibration monitoring curve difference value A2 and a preset third gearbox vibration monitoring curve difference value A3, namely A2 is larger than a and smaller than A3, a secondary early warning instruction is generated;
and when the monitoring data a is larger than a preset third gearbox vibration monitoring curve difference value A3, namely a is larger than A3, generating a three-level early warning instruction.
7. The method for vibration monitoring and fault diagnosis of a gearbox of a wind generating set according to claim 6, wherein when the warning instruction is sent to the monitoring terminal, the method further comprises the following steps:
presetting an early warning instruction generation frequency matrix N, and setting N (N1, N2, N3), wherein N1 is the preset first early warning instruction generation frequency, N2 is the preset second early warning instruction generation frequency, N3 is the preset third early warning instruction generation frequency, and N1 is more than N2 and is more than N3;
if the generation times of the first-stage early warning instruction are larger than the generation times N3 of the preset third early warning instruction within the preset time interval, sending a maintenance instruction to the monitoring terminal;
if the generation times of the secondary early warning instructions are larger than the generation times N2 of the preset second early warning instructions within the preset time interval, sending a maintenance instruction to the monitoring terminal;
and if the generation times of the three-stage early warning instructions are larger than the preset first early warning instruction generation times N1 within the preset time interval, sending a maintenance instruction to the monitoring terminal.
8. The method of claim 1, wherein the generating the fault database comprises:
acquiring historical fault data and expert knowledge base data of the wind turbine generator, and generating a primary fault database;
acquiring fault type information of the gearbox, corresponding real-time vibration data and real-time environment data, and generating fault record data;
and updating the primary fault database according to the fault record data.
9. The wind turbine generator system gearbox vibration monitoring and fault diagnosis method of claim 8, wherein said updating the primary fault database includes:
presetting a time node, and updating the primary fault database according to the time node;
and acquiring the occurrence frequency of the faults, and setting a time interval between the time interval and the next time node according to the occurrence frequency of the faults.
10. The method of claim 9, wherein the determining whether the fault is a familial fault comprises:
acquiring production parameters of different gearbox parts and fault record data of different gearboxes;
generating part labels according to the production parameters of the different gearbox parts;
and generating a judgment result according to the part label and the fault record data.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211374051.1A CN115728057B (en) | 2022-11-03 | 2022-11-03 | Vibration monitoring and fault diagnosis method for gearbox of wind generating set |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211374051.1A CN115728057B (en) | 2022-11-03 | 2022-11-03 | Vibration monitoring and fault diagnosis method for gearbox of wind generating set |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115728057A true CN115728057A (en) | 2023-03-03 |
| CN115728057B CN115728057B (en) | 2024-07-09 |
Family
ID=85294550
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211374051.1A Active CN115728057B (en) | 2022-11-03 | 2022-11-03 | Vibration monitoring and fault diagnosis method for gearbox of wind generating set |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115728057B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116223037A (en) * | 2023-05-09 | 2023-06-06 | 山东金帝精密机械科技股份有限公司 | Operation monitoring method and equipment for wind power bearing retainer |
| CN116381490A (en) * | 2023-06-05 | 2023-07-04 | 江苏铭星智能家居有限公司 | Push rod motor performance detection system and method based on data analysis |
| CN118962444A (en) * | 2024-10-16 | 2024-11-15 | 内蒙古电力(集团)有限责任公司内蒙古电力科学研究院分公司 | A method and system for diagnosing status of a generator set |
Citations (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102353534A (en) * | 2011-06-29 | 2012-02-15 | 西安交通大学 | Fault simulation experiment table for step-up drive system of wind-driven generator set |
| US20120197605A1 (en) * | 2011-01-30 | 2012-08-02 | Sinovel Wind Group Co., Ltd. | Comprehensive assessment system and assessment method for vibration and load of wind generating set |
| WO2015076435A1 (en) * | 2013-11-22 | 2015-05-28 | 이선휘 | Method for diagnosing fault of facilities using vibration characteristic |
| CN106441873A (en) * | 2016-10-31 | 2017-02-22 | 上海电机学院 | Wind-driven generator gearbox fault early-warning system |
| JP2017101954A (en) * | 2015-11-30 | 2017-06-08 | 日本精工株式会社 | Mechanical facility evaluation method |
| KR101764540B1 (en) * | 2016-06-21 | 2017-08-02 | 두산중공업 주식회사 | Vibration Monitoring and Diagnosis System for Wind Turbine |
| CN107291044A (en) * | 2017-06-23 | 2017-10-24 | 深圳市盛路物联通讯技术有限公司 | The intelligent control method and system of a kind of lathe running status |
| CN109682597A (en) * | 2019-02-01 | 2019-04-26 | 朗坤智慧科技股份有限公司 | A kind of gear-box vibration signal processing and analysis method |
| CN110119110A (en) * | 2019-04-23 | 2019-08-13 | 江苏中泽电气自动化有限公司 | A kind of remote alarms guarantee system and method based on cloud platform |
| CN209764419U (en) * | 2019-05-28 | 2019-12-10 | 南京工程学院 | Wind Turbine Gearbox Fault Diagnosis Device |
| CN111412134A (en) * | 2019-01-07 | 2020-07-14 | 青岛海尔特种电冰柜有限公司 | Detection system, detection method and compressor |
| CN111679187A (en) * | 2020-05-26 | 2020-09-18 | 浙江浙能技术研究院有限公司 | Large-scale generator state evaluation method based on comprehensive monitoring platform |
| CN213516341U (en) * | 2020-09-25 | 2021-06-22 | 华能大理风力发电有限公司 | Online vibration data monitoring system for wind turbine generator fault diagnosis |
| CN113027607A (en) * | 2021-03-31 | 2021-06-25 | 潍柴动力股份有限公司 | Fault detection method for oil-gas separator and related device |
| CN113123932A (en) * | 2021-02-23 | 2021-07-16 | 北京华能新锐控制技术有限公司 | Real-time dynamic fault diagnosis method for wind turbine generator |
| CN113757048A (en) * | 2021-07-23 | 2021-12-07 | 国能云南新能源有限公司 | Wind turbine generator system gear box on-line monitoring and intelligent fault diagnosis system |
| CN114060227A (en) * | 2020-07-29 | 2022-02-18 | 新疆金风科技股份有限公司 | Method and device for identifying abnormal vibration working condition of wind turbine generator |
| CN114215705A (en) * | 2021-12-15 | 2022-03-22 | 广东省风力发电有限公司 | Wind turbine generator fault early warning method and system |
| CN115258587A (en) * | 2022-06-28 | 2022-11-01 | 华能伊春热电有限公司 | Belt conveyor fault diagnosis method and equipment |
-
2022
- 2022-11-03 CN CN202211374051.1A patent/CN115728057B/en active Active
Patent Citations (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120197605A1 (en) * | 2011-01-30 | 2012-08-02 | Sinovel Wind Group Co., Ltd. | Comprehensive assessment system and assessment method for vibration and load of wind generating set |
| CN102353534A (en) * | 2011-06-29 | 2012-02-15 | 西安交通大学 | Fault simulation experiment table for step-up drive system of wind-driven generator set |
| WO2015076435A1 (en) * | 2013-11-22 | 2015-05-28 | 이선휘 | Method for diagnosing fault of facilities using vibration characteristic |
| JP2017101954A (en) * | 2015-11-30 | 2017-06-08 | 日本精工株式会社 | Mechanical facility evaluation method |
| KR101764540B1 (en) * | 2016-06-21 | 2017-08-02 | 두산중공업 주식회사 | Vibration Monitoring and Diagnosis System for Wind Turbine |
| CN106441873A (en) * | 2016-10-31 | 2017-02-22 | 上海电机学院 | Wind-driven generator gearbox fault early-warning system |
| CN107291044A (en) * | 2017-06-23 | 2017-10-24 | 深圳市盛路物联通讯技术有限公司 | The intelligent control method and system of a kind of lathe running status |
| CN111412134A (en) * | 2019-01-07 | 2020-07-14 | 青岛海尔特种电冰柜有限公司 | Detection system, detection method and compressor |
| CN109682597A (en) * | 2019-02-01 | 2019-04-26 | 朗坤智慧科技股份有限公司 | A kind of gear-box vibration signal processing and analysis method |
| CN110119110A (en) * | 2019-04-23 | 2019-08-13 | 江苏中泽电气自动化有限公司 | A kind of remote alarms guarantee system and method based on cloud platform |
| CN209764419U (en) * | 2019-05-28 | 2019-12-10 | 南京工程学院 | Wind Turbine Gearbox Fault Diagnosis Device |
| CN111679187A (en) * | 2020-05-26 | 2020-09-18 | 浙江浙能技术研究院有限公司 | Large-scale generator state evaluation method based on comprehensive monitoring platform |
| CN114060227A (en) * | 2020-07-29 | 2022-02-18 | 新疆金风科技股份有限公司 | Method and device for identifying abnormal vibration working condition of wind turbine generator |
| CN213516341U (en) * | 2020-09-25 | 2021-06-22 | 华能大理风力发电有限公司 | Online vibration data monitoring system for wind turbine generator fault diagnosis |
| CN113123932A (en) * | 2021-02-23 | 2021-07-16 | 北京华能新锐控制技术有限公司 | Real-time dynamic fault diagnosis method for wind turbine generator |
| CN113027607A (en) * | 2021-03-31 | 2021-06-25 | 潍柴动力股份有限公司 | Fault detection method for oil-gas separator and related device |
| CN113757048A (en) * | 2021-07-23 | 2021-12-07 | 国能云南新能源有限公司 | Wind turbine generator system gear box on-line monitoring and intelligent fault diagnosis system |
| CN114215705A (en) * | 2021-12-15 | 2022-03-22 | 广东省风力发电有限公司 | Wind turbine generator fault early warning method and system |
| CN115258587A (en) * | 2022-06-28 | 2022-11-01 | 华能伊春热电有限公司 | Belt conveyor fault diagnosis method and equipment |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116223037A (en) * | 2023-05-09 | 2023-06-06 | 山东金帝精密机械科技股份有限公司 | Operation monitoring method and equipment for wind power bearing retainer |
| CN116223037B (en) * | 2023-05-09 | 2023-09-19 | 山东金帝精密机械科技股份有限公司 | Operation monitoring method and equipment for wind power bearing retainer |
| CN116381490A (en) * | 2023-06-05 | 2023-07-04 | 江苏铭星智能家居有限公司 | Push rod motor performance detection system and method based on data analysis |
| CN116381490B (en) * | 2023-06-05 | 2023-08-11 | 江苏铭星智能家居有限公司 | Push rod motor performance detection system and method based on data analysis |
| CN118962444A (en) * | 2024-10-16 | 2024-11-15 | 内蒙古电力(集团)有限责任公司内蒙古电力科学研究院分公司 | A method and system for diagnosing status of a generator set |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115728057B (en) | 2024-07-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN115728057B (en) | Vibration monitoring and fault diagnosis method for gearbox of wind generating set | |
| Leahy et al. | Diagnosing wind turbine faults using machine learning techniques applied to operational data | |
| DE102010026678B4 (en) | Monitoring and diagnostic system for a fluid power machine system as well as fluid power axis system | |
| CN117689214B (en) | Dynamic safety assessment method for energy router of flexible direct-current traction power supply system | |
| CN202326011U (en) | State-monitoring and fault-diagnosis system of wind-power set | |
| US20210182749A1 (en) | Method of predicting component failure in drive train assembly of wind turbines | |
| CN115733865B (en) | Data acquisition, analysis and fault early warning system of photovoltaic tracking bracket system | |
| EP3796016A1 (en) | System and method for detecting battery faults in a pitch system of a wind turbine | |
| CN116245506A (en) | Equipment operation and maintenance management system, fault self-detection method and using method thereof | |
| Han et al. | Implementation strategy of predictive maintenance in nuclear power plant | |
| Carter et al. | Continuous Reliability Enhancement for Wind (CREW). Program Update | |
| CN118778566A (en) | A monitoring management and early warning method and system for an industrial cloud platform | |
| CN118208373A (en) | Quality maintenance method and related device for wind generating set | |
| Bezzaoucha et al. | Failure causes based wind turbine components classification and failure propagation: For proactive maintenance implementatio | |
| CN117804763A (en) | Wind power blade diagnosis method based on automatic peak searching and natural frequency calculation | |
| CN117435619A (en) | Quantitative evaluation system and method for fan fault repair process | |
| CN117151683A (en) | Wind power plant equipment health diagnosis and prediction maintenance method, system, chip and equipment | |
| CN114061934A (en) | Blade fault diagnosis method and system based on wind turbine vibration | |
| Tang et al. | Development of predictive maintenance system for nuclear power turbine unit | |
| CN117991704B (en) | Control cabinet fault early warning system | |
| CN112983750A (en) | Method and device for diagnosing mounting dislocation of blades of wind turbine generator | |
| CN217504976U (en) | Online vibration state monitoring device of wind generating set | |
| KR102778630B1 (en) | IoT and AI-based wind turbine bearing condition monitoring and prediction device | |
| CN119543453A (en) | Remote monitoring and fault diagnosis system for photovoltaic power generation equipment | |
| CN221547196U (en) | Fan variable pitch state monitoring and abnormality identification system |
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 |