CN112798044A - Remote intelligent monitoring system for transmission chain of wind turbine generator - Google Patents
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Abstract
The invention relates to a remote intelligent monitoring system for a transmission chain of a wind turbine generator, which comprises: the data acquisition module is used for acquiring monitoring signals of the wind turbine generator component in real time; the data processing module is used for calculating time domain characteristics and frequency domain characteristics of the monitoring signals to obtain characteristic data; the analysis and diagnosis module is used for carrying out analysis and diagnosis on the characteristic data according to a preset alarm threshold value to obtain diagnosis information and generating alarm information according to the diagnosis information; the communication module is used for realizing data interaction with the remote management module; and the remote management module is used for storing and displaying the transmission data of the data processing module and the analysis and diagnosis module. The remote intelligent monitoring system for the transmission chain of the wind turbine generator can evaluate and identify the fault state, position and degree of the wind turbine generator in real time, provide accurate and reliable decision data basis for operation and maintenance personnel, find the fault of the wind turbine generator in time, and avoid secondary damage and cause larger loss.
Description
Technical Field
The invention belongs to the technical field of fan monitoring, and particularly relates to a remote intelligent monitoring system for a transmission chain of a wind turbine generator.
Background
The wind energy is formed by uneven heating of the surface of the earth by solar radiation, is a green energy, can be effectively utilized by wind power generation, and does not damage the natural environment while obtaining energy. The wind generating set is characterized by relatively simple structure, but expensive manufacturing cost and maintenance of each part. In case of major failure, the power supply will be insufficient. With the expansion of the operation scale and the increase of the operation time of the wind generating set, the fault diagnosis and prevention of the wind generating set become more concerned in the industry.
The existing wind generating set is generally arranged to carry out fault diagnosis, an inspection worker is arranged to inspect a wind generating set system according to the ground on time, and the inspection worker can master the running state of the wind generating set by detecting the wind generating set system. However, real-time monitoring cannot be achieved through manual monitoring, uncertain errors exist in monitoring results due to human factors, and the wind generating set is located at a high altitude and is inconvenient to detect.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a remote intelligent monitoring system for a transmission chain of a wind turbine generator. The technical problem to be solved by the invention is realized by the following technical scheme:
the invention provides a remote intelligent monitoring system for a transmission chain of a wind turbine generator, which comprises:
the data acquisition module is used for acquiring monitoring signals of the wind turbine generator component in real time;
the data processing module is used for calculating time domain characteristics and frequency domain characteristics of the monitoring signals to obtain characteristic data;
the analysis and diagnosis module is used for carrying out analysis and diagnosis on the characteristic data according to a preset alarm threshold value to obtain diagnosis information and generating alarm information according to the diagnosis information;
the communication module is used for realizing data interaction with the remote management module;
and the remote management module is used for storing and displaying the transmission data of the data processing module and the analysis and diagnosis module.
In one embodiment of the invention, the data acquisition module comprises a vibration sensor and a rotation speed sensor which are installed on the wind turbine component; the monitoring signals comprise vibration signals and rotating speed signals.
In one embodiment of the invention, the data processing module comprises a signal processing unit and a calculation unit, wherein,
the signal processing unit comprises a vibration signal processing subunit and a rotating speed signal processing subunit, and the vibration signal processing subunit is used for carrying out normalization, filtering and analog-to-digital conversion processing on the vibration signal; the rotating speed signal processing subunit is used for performing optical coupling isolation and signal shaping processing on the waveform of the rotating speed signal;
the calculating unit comprises a time domain calculating subunit, a frequency domain calculating subunit and a rotating speed calculating subunit, wherein the time domain calculating subunit is used for performing time domain characteristic calculation on the processed vibration signal to obtain time domain data; the frequency domain calculating subunit is used for performing frequency domain characteristic calculation on the processed vibration signal to obtain frequency domain data; and the rotating speed calculating subunit is used for calculating the processed rotating speed signal to obtain rotating speed data.
In an embodiment of the present invention, the data processing module further includes a data cleaning unit, configured to perform cleaning processing on the processed monitoring signal according to the acquired background noise signal, so as to remove interference data.
In one embodiment of the invention, the time domain data includes peaks, significant values, variances, and kurtosis of the signal, and the frequency domain data includes FFT spectral features, envelope spectra, and wavelet energies of the signal.
In an embodiment of the invention, the analysis and diagnosis module comprises an analysis and diagnosis unit and an alarm unit, wherein the analysis and diagnosis unit is used for performing weighted statistics on the characteristic data and diagnosing the state of the wind turbine generator according to a preset alarm threshold value to obtain diagnosis information; the alarm unit is used for generating alarm information according to the diagnosis information, and the alarm information comprises fault early warning information and fault alarm information.
In an embodiment of the present invention, the communication module uses an ethernet communication method.
In one embodiment of the invention, the wind turbine components comprise a main bearing of a wind turbine, a main shaft, a gearbox and a generator.
Compared with the prior art, the invention has the beneficial effects that:
1. the remote intelligent monitoring system for the transmission chain of the wind turbine generator can evaluate and identify the fault state, position and degree of the wind turbine generator in real time, provide accurate and reliable decision data basis for operation and maintenance personnel, find the fault of the wind turbine generator in time, and avoid secondary damage and cause larger loss;
2. the remote intelligent monitoring system for the transmission chain of the wind turbine generator can effectively and accurately clean edge hardware data, solves the wind field data bandwidth restriction condition, provides more accurate and effective data for big data analysis, and solves the problem of small data quantity of deep diagnosis and analysis;
3. the remote intelligent monitoring system for the transmission chain of the wind turbine generator set can flexibly adapt to different working conditions, and is wider in application and strong in adaptability.
The foregoing description is only an overview of the technical solutions of the present invention, and in order to make the technical means of the present invention more clearly understood, the present invention may be implemented in accordance with the content of the description, and in order to make the above and other objects, features, and advantages of the present invention more clearly understood, the following preferred embodiments are described in detail with reference to the accompanying drawings.
Drawings
Fig. 1 is a schematic structural diagram of a remote intelligent monitoring system for a transmission chain of a wind turbine generator according to an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of another wind turbine generator transmission chain remote intelligent monitoring system provided by the embodiment of the invention;
fig. 3 is a schematic structural diagram of another remote intelligent monitoring system for a transmission chain of a wind turbine generator according to an embodiment of the present invention.
Icon: 1-a data acquisition module; 101-a vibration sensor; 102-a rotational speed sensor; 2-a data processing module; 201-a signal processing unit; 2011-vibration signal processing subunit; 2012-tacho signal processing subunit; 202-a computing unit; 2021-time domain calculation subunit; 2022-frequency domain calculating subunit; 2023-rotation speed calculating subunit; 203-a data washing unit; 3-an analytical diagnostic module; 301-an analytical diagnostic unit; 302-an alarm unit; 4-a communication module; 5-remote management module.
Detailed Description
In order to further explain the technical means and effects of the present invention adopted to achieve the predetermined invention purpose, the following describes in detail a remote intelligent monitoring system for a wind turbine generator transmission chain according to the present invention with reference to the accompanying drawings and the detailed embodiments.
The foregoing and other technical matters, features and effects of the present invention will be apparent from the following detailed description of the embodiments, which is to be read in connection with the accompanying drawings. The technical means and effects of the present invention adopted to achieve the predetermined purpose can be more deeply and specifically understood through the description of the specific embodiments, however, the attached drawings are provided for reference and description only and are not used for limiting the technical scheme of the present invention.
Example one
Referring to fig. 1, fig. 1 is a schematic structural diagram of a remote intelligent monitoring system for a transmission chain of a wind turbine generator according to an embodiment of the present invention. As shown in the figure, the remote intelligent monitoring system for the transmission chain of the wind turbine generator set comprises: the system comprises a data acquisition module 1, a data processing module 2, an analysis and diagnosis module 3, a communication module 4 and a remote management module 5. The data acquisition module 1 is used for acquiring monitoring signals of wind turbine components in real time; the data processing module 2 is used for calculating time domain characteristics and frequency domain characteristics of the monitoring signals to obtain characteristic data; the analysis and diagnosis module 3 is used for carrying out analysis and diagnosis on the characteristic data according to a preset alarm threshold value to obtain diagnosis information and generating alarm information according to the diagnosis information; the communication module 4 is used for realizing data interaction with the remote management module; the remote management module 5 is used for storing and displaying the transmission data of the data processing module and the analysis and diagnosis module.
The wind turbine generator system transmission chain remote intelligent monitoring system can evaluate and identify the fault state, position and degree of the wind turbine generator system components in real time, provides accurate and reliable decision data basis for operation and maintenance personnel, and a user can find out the faults of the wind turbine generator system components in time through data displayed by the remote management module, thereby avoiding secondary damage and causing greater loss.
Specifically, in the present embodiment, the wind turbine components include the main bearing of the wind turbine, the main shaft, the gearbox and the generator.
Referring to fig. 2, fig. 2 is a schematic structural diagram of another remote intelligent monitoring system for a transmission chain of a wind turbine generator according to an embodiment of the present invention. As shown, the data acquisition module 1 includes a vibration sensor 101 and a rotation speed sensor 10 mounted on the wind turbine component, and accordingly, the monitoring signal includes a vibration signal and a rotation speed signal.
It should be noted that in this embodiment, the data acquisition module further includes an excitation circuit, and the excitation circuit is a configurable constant current source of 4 to 20mA, and provides an excitation current required by the operation for the sensor.
Further, the data processing module 2 includes a signal processing unit 201 and a calculation unit 202. The signal processing unit 201 includes a vibration signal processing subunit 2011 and a rotational speed signal processing subunit 2012, where the vibration signal processing subunit 2011 is configured to perform normalization, filtering, and analog-to-digital conversion on the vibration signal; the rotation speed signal processing subunit 2012 is configured to perform optical coupling isolation and signal shaping processing on the waveform of the rotation speed signal.
In this embodiment, the vibration signal is normalized, filtered and analog-to-digital converted by using a signal conditioning circuit, a band-pass filter circuit and an analog-to-digital conversion circuit. And the rotating speed signal isolation and conversion circuit is adopted to carry out optical coupling isolation and signal shaping processing on the waveform of the rotating speed signal.
Further, the calculating unit 202 includes a time domain calculating subunit 2021, a frequency domain calculating subunit 2022, and a rotation speed calculating subunit 2023, where the time domain calculating subunit 2021 is configured to perform time domain feature calculation on the processed vibration signal to obtain time domain data; the frequency domain calculating subunit 2022 is configured to perform frequency domain feature calculation on the processed vibration signal to obtain frequency domain data; the rotation speed calculation subunit 2023 is configured to calculate the processed rotation speed signal to obtain rotation speed data.
Optionally, in this embodiment, the time domain data includes a peak value, a valid value, a variance, and a kurtosis of the vibration signal, and in other embodiments, the time domain data may further include an average value, an average amplitude, a standard deviation, and a margin of the signal. Wherein, the average value can indicate the central trend of the signal, highlight the static information of the vibration signal and represent the fluctuation center of the vibration signal. The effective value, also called root mean square value, can be used to reflect the irregular vibration conditions due to poor manufacturing accuracy and pitting corrosion on the working surface, the lower the manufacturing accuracy or the greater the degree of wear of the bearing, the higher the effective value. Kurtosis is more sensitive to early faults, and if the kurtosis value is too large, it indicates that a fault has occurred. As the fault conditions become more gradual, the kurtosis value also increases slowly.
In this implementation, the frequency domain data includes FFT spectral characteristics, envelope spectrum, and wavelet energy of the vibration signal, and the frequency domain characteristic calculation may be performed through FFT operation and envelope spectrum operation. When the wind turbine generator component is in fault, the amplitude and probability distribution of the time domain data of the vibration signal will change, which can visually reflect partial fault information, and when the amplitude exceeds a certain limit, the amplitude also indicates that the related components are possibly invalid, indicates that the components need to be replaced in time, but cannot indicate the specific information of the components, so that the time domain analysis of the vibration signal can only be used as simple diagnosis. To know the specific position of the wind turbine fault, the type of the fault, and the influence caused by the fault, a frequency domain analysis method is required to be considered for analyzing the vibration signal. The frequency domain analysis is to convert a signal set on a time series into a signal set on a frequency series by using fourier transform. Therefore, the vibration signals are analyzed on the frequency domain, the position change conditions of different signal spectrum peaks are observed, and related frequency domain indexes are calculated to reflect fault information.
Further, in other embodiments, the data processing module 2 further includes a data cleaning unit 203, as shown in fig. 3, the data cleaning unit 203 is configured to perform cleaning processing on the processed monitoring signal according to the acquired background noise signal, so as to remove the interference data. Specifically, by collecting the actual background noise signal and according to the weight of the characteristic data in the fault diagnosis, the monitoring signal is accurately deleted and cleaned, and the pressure of the communication transmission of the monitoring system and the data processing of the subsequent computing unit 202 is reduced.
It should be noted that, in other embodiments, the data processing module 2 further includes an abnormal value removing unit, configured to remove abnormal data in the monitoring signal, for example: and eliminating abnormal data generated by electromagnetic interference in the monitoring signal.
Further, the analysis and diagnosis module 3 includes an analysis and diagnosis unit 301 and an alarm unit 302, wherein the analysis and diagnosis unit 301 is configured to perform weighted statistics on the feature data, and diagnose the state of the wind turbine generator according to a preset alarm threshold value to obtain diagnosis information; the alarm unit 302 is configured to generate alarm information according to the diagnosis information, where the alarm information includes fault early warning information and fault alarm information.
Specifically, in this embodiment, the analysis and diagnosis unit 301 may perform analysis and diagnosis by selecting a specific feature value and performing weighted statistics, and then complete diagnosis and determination of the alarm level of the wind turbine state by combining the set multidimensional alarm threshold. In this embodiment, the initial value of the alarm threshold may be set according to an empirical value, and may also be modified and improved during the operation of the system.
In this embodiment, the data processing module 2 and the analysis and diagnosis module 3 may be implemented by an FPGA and a circuit built around the FPGA.
Further, in this embodiment, the communication module 4 adopts an ethernet communication mode, and can customize a data frame format to communicate with the remote management module 5, so as to implement data uploading, parameter configuration, and command interaction.
Further, the remote management module 5 comprises a human-computer interaction interface, and the human-computer interaction interface is used for retrieving and displaying data of vibration signals and rotation speed signals of the wind turbine generator, and transmitting characteristic data and alarm information by the data processing module 2 and the analysis and diagnosis module 3. In addition, the user can also call and check historical data of the wind turbine generator through the human-computer interaction interface.
Further, in this embodiment, the intelligent monitoring system further includes a configuration scheduling module, where the configuration scheduling module is configured to implement functions of on-line transmission of data, offline storage task scheduling, detector configuration (information such as real-time, deployment information, characteristic threshold parameter, sampling interval, filter parameter, and network parameter), TCP communication module control, protocol package, and parameter memory control.
The remote intelligent monitoring system for the transmission chain of the wind turbine generator set can effectively and accurately clean edge hardware data, solves the wind field data bandwidth restriction condition, provides more accurate and effective data for big data analysis, and solves the problem of small data quantity of deep diagnosis analysis.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that an article or device that comprises a list of elements does not include only those elements but may include other elements not expressly listed. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of additional like elements in the article or device comprising the element. The terms "connected" or "coupled" and the like are not restricted to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The directional or positional relationships indicated by "upper", "lower", "left", "right", etc., are based on the directional or positional relationships shown in the drawings, and are only for convenience of describing the present invention and simplifying the description, but do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention.
The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.
Claims (8)
1. The utility model provides a wind turbine generator system driving chain remote intelligent monitoring system which characterized in that includes:
the data acquisition module is used for acquiring monitoring signals of the wind turbine generator component in real time;
the data processing module is used for calculating time domain characteristics and frequency domain characteristics of the monitoring signals to obtain characteristic data;
the analysis and diagnosis module is used for carrying out analysis and diagnosis on the characteristic data according to a preset alarm threshold value to obtain diagnosis information and generating alarm information according to the diagnosis information;
the communication module is used for realizing data interaction with the remote management module;
and the remote management module is used for storing and displaying the transmission data of the data processing module and the analysis and diagnosis module.
2. The remote intelligent monitoring system for the wind turbine generator transmission chain according to claim 1, wherein the data acquisition module comprises a vibration sensor and a rotation speed sensor mounted on the wind turbine generator component; the monitoring signals comprise vibration signals and rotating speed signals.
3. The wind turbine generator system drive chain remote intelligent monitoring system according to claim 2, wherein the data processing module comprises a signal processing unit and a computing unit, wherein,
the signal processing unit comprises a vibration signal processing subunit and a rotating speed signal processing subunit, and the vibration signal processing subunit is used for carrying out normalization, filtering and analog-to-digital conversion processing on the vibration signal; the rotating speed signal processing subunit is used for performing optical coupling isolation and signal shaping processing on the waveform of the rotating speed signal;
the calculating unit comprises a time domain calculating subunit, a frequency domain calculating subunit and a rotating speed calculating subunit, wherein the time domain calculating subunit is used for performing time domain characteristic calculation on the processed vibration signal to obtain time domain data; the frequency domain calculating subunit is used for performing frequency domain characteristic calculation on the processed vibration signal to obtain frequency domain data; and the rotating speed calculating subunit is used for calculating the processed rotating speed signal to obtain rotating speed data.
4. The wind turbine generator system transmission chain remote intelligent monitoring system according to claim 3, wherein the data processing module further comprises a data cleaning unit for cleaning the processed monitoring signal according to the acquired background noise signal to remove interference data.
5. The remote intelligent monitoring system for the transmission chain of the wind turbine generator set according to claim 3, wherein the time domain data comprises a peak value, a valid value, a variance and a kurtosis of a signal, and the frequency domain data comprises FFT spectral characteristics, an envelope spectrum and wavelet energy of the signal.
6. The system according to claim 1, wherein the analysis and diagnosis module comprises an analysis and diagnosis unit and an alarm unit, wherein the analysis and diagnosis unit is configured to perform weighted statistics on the characteristic data and diagnose the state of the wind turbine according to a preset alarm threshold value to obtain diagnosis information; the alarm unit is used for generating alarm information according to the diagnosis information, and the alarm information comprises fault early warning information and fault alarm information.
7. The wind turbine generator system transmission chain remote intelligent monitoring system according to claim 1, wherein the communication module adopts an ethernet communication mode.
8. The remote intelligent monitoring system for the wind turbine transmission chain according to claim 1, wherein the wind turbine components include a main bearing, a main shaft, a gearbox and a generator of the wind turbine.
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| CN103529386A (en) * | 2013-10-12 | 2014-01-22 | 山西大学工程学院 | System and method for remote real-time state monitoring and intelligent failure diagnosis of wind turbine generators |
| CN107061183A (en) * | 2017-01-17 | 2017-08-18 | 中山大学 | A kind of automation method for diagnosing faults of offshore wind farm unit |
| CN111322206A (en) * | 2020-02-28 | 2020-06-23 | 唐智科技湖南发展有限公司 | Intelligent operation and maintenance system and method for large mechanical part of wind turbine generator |
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- 2020-12-31 CN CN202011635545.1A patent/CN112798044A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201408116Y (en) * | 2009-06-02 | 2010-02-17 | 中能电力科技开发有限公司 | Condition monitoring device of wind power machine set |
| CN103529386A (en) * | 2013-10-12 | 2014-01-22 | 山西大学工程学院 | System and method for remote real-time state monitoring and intelligent failure diagnosis of wind turbine generators |
| CN107061183A (en) * | 2017-01-17 | 2017-08-18 | 中山大学 | A kind of automation method for diagnosing faults of offshore wind farm unit |
| CN111322206A (en) * | 2020-02-28 | 2020-06-23 | 唐智科技湖南发展有限公司 | Intelligent operation and maintenance system and method for large mechanical part of wind turbine generator |
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