CN106499594B - A kind of driving chain of wind generating set torsional frequency online recognition method and device - Google Patents
A kind of driving chain of wind generating set torsional frequency online recognition method and device Download PDFInfo
- Publication number
- CN106499594B CN106499594B CN201610872961.0A CN201610872961A CN106499594B CN 106499594 B CN106499594 B CN 106499594B CN 201610872961 A CN201610872961 A CN 201610872961A CN 106499594 B CN106499594 B CN 106499594B
- Authority
- CN
- China
- Prior art keywords
- data
- generating set
- acquisition
- continuous
- driving chain
- 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.)
- Expired - Fee Related
Links
- 238000000034 method Methods 0.000 title claims abstract description 27
- 230000001133 acceleration Effects 0.000 claims abstract description 25
- 238000005070 sampling Methods 0.000 claims description 17
- 230000002123 temporal effect Effects 0.000 claims description 11
- 239000000284 extract Substances 0.000 claims description 7
- 241001269238 Data Species 0.000 claims description 6
- 230000005540 biological transmission Effects 0.000 abstract description 30
- 238000000605 extraction Methods 0.000 abstract description 2
- 238000001228 spectrum Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 2
- 230000010355 oscillation Effects 0.000 description 2
- 230000001960 triggered effect Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000006854 communication Effects 0.000 description 1
- 238000004590 computer program Methods 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 230000003595 spectral effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Abstract
The invention discloses a kind of driving chain of wind generating set torsional frequency online recognition method and devices, 50ms, which is uninterruptedly sampled, to be realized to blower main control PLC operating parameter using data acquisition line journey, other data processing threads are under the triggering of data acquisition line journey, it is automatic to calculate blower transmission chain torsion vibration natural frequencies, then main control PLC is uploaded to by MODBUS Transmission Control Protocol, realizes the online tracking of blower transmission chain torsional frequency.The present invention solves the problems, such as that extraction blower transmission chain torsional frequency is more difficult using the angular acceleration data of blower.
Description
Technical field
The invention belongs to intelligent wind power power field, in particular to a kind of driving chain of wind generating set torsional frequency is online
Recognition methods and device.
Background technique
With the continuous improvement that wind energy utilization requires, structure, the control mode of wind power generating set also proposed newly
Requirement.Its essence is the processes for converting wind energy into mechanical energy and being further converted into electric energy for wind-power electricity generation, by wind wheel to hair
Motor constitutes the transmission chain of entire blower, because its structure is complicated, required precision is high, therefore study transmission chain problem have it is very great
Meaning.
The transmission chain of wind power generating set can generate larger vibration in transmission process, stability, reliability to complete machine
There is larger impact with the service life, driving chain of wind generating set twisting vibration not only influences the fluctuation of speed of generator, also increases and passes
The fatigue load of dynamic chain mechanical part, causes very big hidden danger to the safety of wind-driven generator.Driving chain of wind driven generator is influenced to turn round
The dynamic factor of rotational oscillation mainly has, the variation of wind wheel pneumatic torque caused by wind speed changes and generator electromagnetic torque is given changes
Become, when pneumatic torque or electromagnetic torque include the intrinsic frequency of transmission chain twisting vibration, the torsion of transmission chain will be caused total
Vibration.Therefore, in the generator torque signal that master control is sent to current transformer, the intrinsic frequency of torsional oscillation that filters out transmission chain using trapper
Rate to avoid resonance.
In the prior art, the method for obtaining wind energy conversion system transmission chain Torsional Vibration Natural Frequency is acquired using metadata acquisition tool
Rotation speed of fan signal draws frequency spectrum, finds in frequency spectrum the corresponding frequency values of maximum value in 1Hz to 3Hz range, is transmission chain
Intrinsic frequency, but this method the wind-driven generator fluctuation of speed infrequently in the case where, cannot easily extract transmission
Chain torsional frequency.
Summary of the invention
The purpose of the present invention is to provide a kind of driving chain of wind generating set torsional frequency online recognition method and device,
For solving the problems, such as that extraction blower transmission chain torsional frequency is more difficult.
To achieve the above object, the technical scheme is that
A kind of driving chain of wind generating set torsional frequency online recognition method, method includes the following steps:
1) data in continuous acquisition setting time, the data include generator angular acceleration；
2) angular acceleration data are handled, and extract the corresponding frequency of maximum value of 1Hz to the angular acceleration between 3Hz
Value.
The data further include that the data further include data sampling time information, i.e. year, month, day, hour, min, second, millisecond
Temporal information, and according to the temporal information judge acquisition data it is whether continuous.
When the data sampling time interval of two adjacent datas is equal to a data sampling period, illustrate the two data
It is continuous.
If loss of data occurs during acquiring for data, the data acquired before abandoning resurvey new data.
The acquisition data period is 50ms, and the continuous sampling time is 60s.
The present invention also provides a kind of driving chain of wind generating set frequency online recognition device, which includes:
Acquisition unit: for the data in continuous acquisition setting time, the data include generator angular acceleration；
Computing unit: being calculated for angular acceleration data, extracts the maximum of 1Hz to the angular acceleration between 3Hz
It is worth corresponding frequency values.
The device further include the data further include the year, month, day, hour, min of data, the second, millisecond temporal information, and root
The whether continuous unit of data of acquisition is judged according to the temporal information.
When the data sampling time interval of two adjacent datas is equal to a data sampling period, illustrate the two data
It is continuous.
If during including data acquisition loss of data occurs for the device, the data acquired before abandoning are resurveyed
The unit of new data.
The device further includes the acquisition data period for 50ms, and the continuous sampling time is 60s.
The beneficial effects of the present invention are:
Present invention uses generator angular acceleration datas, without the use of revolving speed, because can more dash forward in angular velocity data
Frequency spectrum high frequency components out, especially in the case where the wind-driven generator fluctuation of speed infrequently, the energy in angular acceleration data
Easily extract transmission chain torsional frequency.
By utilizing method of the invention, the online tracking to driving chain of wind generating set torsional frequency is realized automatically
With identification, solves driving chain of wind driven generator torsional frequency and need manpower brought by artificial calculating and write-in fixed value
Increased costs and frequency values drift about caused error problem at any time, the transmission chain frequency caused by component wear or replacement component
When change, system still can automatically track resonant frequency.
By the way of using continuous acquisition to data, it ensure that frequency spectrum can not be interfered by high-frequency signal.
Detailed description of the invention
Fig. 1 is the structural block diagram of driving chain of wind generating set torsional frequency online recognition method；
Fig. 2 is phase generator speed signal and generator angular acceleration signal spectral contrast figure in the same time；
Fig. 3 is the flow chart of driving chain of wind generating set torsional frequency online recognition method.
Specific embodiment
A kind of embodiment of driving chain of wind generating set torsional frequency online recognition method of the invention:
A kind of driving chain of wind generating set torsional frequency online recognition method, the structural block diagram of this method as shown in Figure 1,
Data acquisition program is responsible for acquiring the operation data of wind power generating set as required first, then stores data in database
In, final data processing routine reads latest data from database, calculates transmission chain torsion frequency, then the numerical value is uploaded
To master control system, the process of this method as shown in figure 3, specifically includes the following steps:
1 by standard MODBUS Transmission Control Protocol, with the sample rate of 50ms to main control PLC continuous sampling, the data packet of acquisition
It includes, year, month, day, hour, min, second, millisecond, PLC major state, generator power, generator speed, generator angular acceleration etc..
2 when PLC major state is that 14 generator powers are greater than 25kw, and 14 refer to the normal operating conditions of PLC, generator power
Greater than 25kw, the data at this moment acquired are just significant, and continuous sampling 60 seconds, if do not had in communication process during acquisition data
Loss of data occurs, then data are stored in database, if loss of data occurs for period, has adopted data again before abandoning
Acquisition；When acquiring data, if program judges it is to acquire data to PLC for the first time, remember that this group of data are first group of numbers
According to, and data are saved into the memory of computer, the temporal information of data is saved into floating-point array Temp, when program is judged
When the data of acquisition are not first group of data, then to judge the continuity of two adjacent groups data, specifically be, with floating-point array
The temporal information of the upper one group of data saved in Temp is compared, the time difference dt of procedure judges adjacent data, when
Every minute and second information is converted into millisecond, then is compared, such as 1 minute 60 × 1000 milliseconds of correspondence.Consider the following two kinds situation:
(1) when, minute, second it is identical, millisecond is respectively 180 and 230, then dt=(230-180) ms=50ms, illustrates two groups of numbers
According to time interval be 50 milliseconds, be continuous；
When the time of (2) two groups of data is 6 respectively 30 divide 59 seconds 960 milliseconds and when 6 31 divide 00 second 10 milliseconds, then dt=
[60 × 1000 × (31-30)+1000 × (0-59)+(10-960)] ms=50ms, illustrates that two groups of data are continuous；
(3) if when the time of first group of data is 23 59 divide 59 seconds 960 milliseconds, at this moment above-mentioned dt expression formula is no longer suitable
With needing to be added the data on day or days, but a talent occurs primary under the circumstances, and is just at this moment acquiring data
Even more small probability event, therefore while only determining, is able to satisfy design requirement.
Therefore, we only consider above-mentioned (1) and (2) two kinds of situations, if time difference dt of two groups of data meets: 50ms≤
Dt < 100ms then saves this data into the memory of computer, saves the temporal information of data into floating-point array Temp, with
Judge that next group of data use for computer program.If millisecond time difference dt < 50ms, data are sent to PLC again and are asked
It asks, if millisecond time difference dt >=100ms, empties data and send request of data to PLC again.It is protected using this judgment method
It is continuous for having demonstrate,proved two adjacent groups data, and is not repeated.
1200 datas of acquisition are stored to database by 3 computers, after data are successfully stored in database, data acquisition program
Message is triggered, subsequent data acquisition program enters dormant state, sends request of data to PLC after ten minutes, continues to acquire data.
4 detect after message is triggered, and 1024 newest generator angles accelerate in data processor reading database
Degree evidence because angular acceleration signal can more protrude the radio-frequency component in frequency spectrum, especially when the wind-driven generator fluctuation of speed not
In frequent situation, transmission chain vibration signal can not be extracted in the frequency spectrum of tach signal, but can in angular acceleration signal
The frequency of transmission chain twisting vibration is easily extracted, specifically as shown in Fig. 2, then to wind-driven generator angular acceleration data
It is FFT (Fourier transform), extracts frequency values, the i.e. torsional frequency of transmission chain corresponding to 1Hz to the maximum value between 3Hz.
Torsional frequency Value Data is sent to main control PLC system by standard MODBUS Transmission Control Protocol by 5.
6 data processor inbound message blocked states, after detecting the message of data acquisition program triggering, data
Angular acceleration data in processing routine reading database, angular acceleration data make Fourier transform, calculate the torsion of transmission chain
Turn frequency.
The present invention also provides a kind of driving chain of wind generating set torsional frequency online recognition device, which includes adopting
Collect unit and computing unit；Wherein for acquisition unit for the data in continuous acquisition setting time, the data include generator
Angular acceleration, computing unit are calculated for angular acceleration data, extract the maximum of 1Hz to the angular acceleration between 3Hz
It is worth corresponding frequency values.
The step of above-mentioned identification device, actually a kind of software architecture, each unit therein is with above-mentioned recognition methods
The corresponding process of 1-6 or program.Therefore, no longer the identification device is described in detail.
Above-mentioned identification device is run in generating set transmission chain as a kind of program, using data acquisition line journey to wind
Machine main control PLC operating parameter realize 50ms uninterruptedly sample, data processing threads in addition under the triggering of data acquisition line journey,
It is automatic to calculate blower transmission chain torsion vibration natural frequencies, main control PLC is then uploaded to by MODBUS Transmission Control Protocol, realizes wind
The online tracking of machine transmission chain torsional frequency.The present invention solves previous blower transmission chain torsional frequency and needs manually
The problems such as calculating and be written error caused by the increase of human cost brought by fixed numbers is drifted about at any time with frequency values, separately
Outside, when the transmission chain frequency shift caused by component wear or replacement component, system still can automatically track generating set biography
Dynamic chain torsional frequency.
Above embodiments are only to illustrate technical solution rather than limiting the invention, although referring to above-described embodiment to this hair
It is bright to be described in detail, those skilled in the art should understand that；Still the present invention can be modified or be waited
With replacement, without departing from the spirit or scope of the invention, or any substitutions, should all cover in power of the invention
In sharp claimed range.
Claims (6)
1. a kind of driving chain of wind generating set torsional frequency online recognition method, which is characterized in that this method includes following step
It is rapid:
1) data in continuous acquisition setting time, the data include generator angular acceleration, PLC major state and generator
Power；
2) to meeting the angular acceleration that PLC major state is the data that normal operating conditions and generator power are greater than 25kw condition
Data are handled, and the corresponding frequency values of maximum value of 1Hz to the angular acceleration between 3Hz are extracted；
The data further include data sampling time information, i.e., year, month, day, hour, min, the second, millisecond temporal information, and according to
The temporal information judges whether the data of acquisition are continuous；If loss of data occurs during acquiring for data, adopted before abandoning
The data of collection resurvey new data.
2. driving chain of wind generating set torsional frequency online recognition method according to claim 1, which is characterized in that when
When the data sampling time interval of two adjacent datas is equal to a data sampling period, illustrate that the two data are continuous.
3. driving chain of wind generating set torsional frequency online recognition method according to claim 1 or 2, feature exist
In the acquisition data period is 50ms, and the continuous sampling time is 60s.
4. a kind of driving chain of wind generating set torsional frequency online recognition device, which is characterized in that the device includes:
1) acquisition unit: for the data in continuous acquisition setting time, the data include generator angular acceleration, PLC master
State and generator power；
2) computing unit: for being the number that normal operating conditions and generator power are greater than 25kw condition to PLC major state is met
According to angular acceleration data calculated, extract 1Hz to the angular acceleration between 3Hz the corresponding frequency values of maximum value；
The data further include data sampling time information, i.e., year, month, day, hour, min, the second, millisecond temporal information, device is also
The whether continuous unit of data including judging acquisition according to the temporal information；If device is sent out during further including data acquisition
Raw loss of data, the then data acquired before abandoning, resurveys the unit of new data.
5. driving chain of wind generating set torsional frequency online recognition device according to claim 4, which is characterized in that when
When the data sampling time interval of two adjacent datas is equal to a data sampling period, illustrate that the two data are continuous.
6. driving chain of wind generating set torsional frequency online recognition device according to claim 4 or 5, feature exist
In the acquisition data period is 50ms, and the continuous sampling time is 60s.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610872961.0A CN106499594B (en) | 2016-09-30 | 2016-09-30 | A kind of driving chain of wind generating set torsional frequency online recognition method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610872961.0A CN106499594B (en) | 2016-09-30 | 2016-09-30 | A kind of driving chain of wind generating set torsional frequency online recognition method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106499594A CN106499594A (en) | 2017-03-15 |
| CN106499594B true CN106499594B (en) | 2019-01-08 |
Family
ID=58293462
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610872961.0A Expired - Fee Related CN106499594B (en) | 2016-09-30 | 2016-09-30 | A kind of driving chain of wind generating set torsional frequency online recognition method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106499594B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114151293B (en) * | 2021-11-30 | 2022-11-22 | 甘肃中电瓜州风力发电有限公司 | Fault early warning method, system, equipment and storage medium of fan variable pitch system |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100082276A1 (en) * | 2008-09-29 | 2010-04-01 | Prueftechnik Dieter Busch Ag | Process for monitoring a drive train component of a wind power plant |
| CN103745070A (en) * | 2014-01-28 | 2014-04-23 | 中国科学院电工研究所 | Modeling and simulating method for mechanical transient characteristics of transmission chain of wind generating set |
| CN105227824A (en) * | 2014-06-30 | 2016-01-06 | 深圳市大疆创新科技有限公司 | A kind of The Cloud Terrace parameter regulation means, device and tripod head equipment |
| CN105320794A (en) * | 2014-07-30 | 2016-02-10 | 南车株洲电力机车研究所有限公司 | Method for evaluating dynamic characteristics of transmission chain of wind generating set |
-
2016
- 2016-09-30 CN CN201610872961.0A patent/CN106499594B/en not_active Expired - Fee Related
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100082276A1 (en) * | 2008-09-29 | 2010-04-01 | Prueftechnik Dieter Busch Ag | Process for monitoring a drive train component of a wind power plant |
| CN103745070A (en) * | 2014-01-28 | 2014-04-23 | 中国科学院电工研究所 | Modeling and simulating method for mechanical transient characteristics of transmission chain of wind generating set |
| CN105227824A (en) * | 2014-06-30 | 2016-01-06 | 深圳市大疆创新科技有限公司 | A kind of The Cloud Terrace parameter regulation means, device and tripod head equipment |
| CN105320794A (en) * | 2014-07-30 | 2016-02-10 | 南车株洲电力机车研究所有限公司 | Method for evaluating dynamic characteristics of transmission chain of wind generating set |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106499594A (en) | 2017-03-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108087210B (en) | Wind generating set blade abnormity identification method and device | |
| CN102102629A (en) | On-line data acquisition and analysis device of wind generating set | |
| CN107061183A (en) | A kind of automation method for diagnosing faults of offshore wind farm unit | |
| CN112946471A (en) | Variable frequency motor fault monitoring system | |
| CN101858778A (en) | Vibration monitoring-based wind generator set automatic fault diagnosis method | |
| CN103758696A (en) | SCADA (supervisory control and data acquisition) temperature parameter based wind turbine set security evaluation method | |
| CN103321854A (en) | Vibration control method for wind generator set tower | |
| CN107420269B (en) | method for identifying a wind distribution pattern on a rotor plane and wind turbine implementing the method | |
| CN202676203U (en) | Large-size pumping station state monitoring and diagnosing and energy efficiency management device | |
| CN104564542B (en) | A kind of fault diagnosis system and its diagnostic method based on big data technology | |
| CN110469462A (en) | A kind of Wind turbines intelligent condition monitoring system based on multi-template | |
| CN108896879B (en) | Diagnostic map phase windowing parameter adjusting method based on partial discharge signal characteristics | |
| CN101949774A (en) | Method for monitoring remote real-time state of wind generating multi-set | |
| CN104018988A (en) | Wind generating set monitoring system based on physical component model and real-time data | |
| CN108894932B (en) | Intelligent diagnosis system and method for bearing fault of generator of wind turbine generator | |
| CN105403402A (en) | Method for monitoring torsional vibration state of driving chain system of wind generating set | |
| AU2019478946B2 (en) | Method and system for monitoring health state of blade root fastener | |
| CN202793793U (en) | Large wind generation set bearing fault diagnosis system | |
| CN102706560A (en) | State monitoring method and device of wind turbine generator set | |
| CN106499594B (en) | A kind of driving chain of wind generating set torsional frequency online recognition method and device | |
| CN114061743A (en) | Vibration monitoring method, device, equipment and medium for wind generating set | |
| CN111664061B (en) | Fault diagnosis method and device for yaw system in wind generating set | |
| CN114114006A (en) | Wind driven generator diagnosis device and diagnosis method thereof | |
| CN102117374A (en) | Method for calculating torsional oscillation modal damping of shaft system of generator set based on disturbance signal | |
| CN111693283B (en) | Bearing unsteady state fault feature non-rotating speed extraction method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | 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 | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20190108 Termination date: 20200930 |