CN116877351A - State monitoring method for wind power generation system - Google Patents
State monitoring method for wind power generation system Download PDFInfo
- Publication number
- CN116877351A CN116877351A CN202310824812.7A CN202310824812A CN116877351A CN 116877351 A CN116877351 A CN 116877351A CN 202310824812 A CN202310824812 A CN 202310824812A CN 116877351 A CN116877351 A CN 116877351A
- Authority
- CN
- China
- Prior art keywords
- data
- component
- unit
- wind power
- power generation
- 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.)
- Pending
Links
- 238000010248 power generation Methods 0.000 title claims abstract description 38
- 238000000034 method Methods 0.000 title claims abstract description 33
- 238000012544 monitoring process Methods 0.000 title claims abstract description 33
- 238000001514 detection method Methods 0.000 claims abstract description 58
- 238000010586 diagram Methods 0.000 claims abstract description 23
- 230000005540 biological transmission Effects 0.000 claims description 14
- 238000005070 sampling Methods 0.000 claims description 9
- 230000009466 transformation Effects 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 claims description 2
- 230000002159 abnormal effect Effects 0.000 abstract description 7
- 239000011159 matrix material Substances 0.000 description 6
- 238000012986 modification Methods 0.000 description 6
- 230000004048 modification Effects 0.000 description 6
- 230000009286 beneficial effect Effects 0.000 description 4
- 238000012163 sequencing technique Methods 0.000 description 3
- 230000000007 visual effect Effects 0.000 description 3
- 238000013473 artificial intelligence Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 239000000779 smoke Substances 0.000 description 2
- 230000000087 stabilizing effect Effects 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 230000005856 abnormality Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
Classifications
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
- F03D—WIND MOTORS
- F03D17/00—Monitoring or testing of wind motors, e.g. diagnostics
-
- 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
- Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Sustainable Development (AREA)
- Sustainable Energy (AREA)
- Chemical & Material Sciences (AREA)
- Combustion & Propulsion (AREA)
- Mechanical Engineering (AREA)
- General Engineering & Computer Science (AREA)
- Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
Abstract
The application discloses a state monitoring method for a wind power generation system, which comprises the following steps: the first detection device is installed on the hardware equipment, and the second detection device is installed on the electrical equipment; collecting and transmitting detection results of the first detection device and the second detection device to an analysis module; comparing the detection result with each parameter threshold preset by the analysis module to obtain an analysis result; classifying the detection results to obtain a function chart, and predicting the trend of the detection results according to the function chart; three-dimensional modeling is carried out on hardware equipment and software equipment through a modeling module, and an analysis result and a function diagram are inserted into a model; the application can monitor the states of hardware equipment and electrical equipment in the wind power generation system in real time, predict the vibration amplitude and the rotation speed of the hardware equipment and the voltage, the current and the load of the electrical equipment, display the detected data more intuitively, improve the monitoring speed and reduce the loss of abnormal states through prediction.
Description
Technical Field
The application relates to the technical field of wind power generation, in particular to a state monitoring method for a wind power generation system.
Background
In general, the wind power generation system has a severe working environment and does not have the condition of using a large amount of human resources to carry out on-site value detection device conservation; therefore, a highly-automatic and intelligent monitoring system and a communication means are required to be adopted to ensure the safe and stable operation of the wind power generation system detection device; specifically, data transmission to a control center and intelligent control are required in real time, so that an intelligent monitoring system with higher reliability of the detection device is required;
the existing monitoring method of the wind power generation system is too simple in displaying the detected data and lacks visual observation of the detected data; moreover, as time goes by, each component in the wind power generation system is prone to a cascade of fault reactions, so that a method capable of predicting states and expressing visual monitoring is needed.
Disclosure of Invention
In order to solve the problems, the application provides the following technical scheme:
a condition monitoring method for a wind power generation system, comprising:
step one, installing a detection device I on hardware equipment of a wind power generation system, and installing a detection device II on electrical equipment of the wind power generation system;
step two, collecting and sending detection results of the detection device I and the detection device II to an analysis module;
step three, comparing the detection result with each parameter threshold preset by the analysis module to obtain an analysis result; classifying the detection results to obtain a function chart, and predicting the trend of the detection results according to the function chart;
and step four, carrying out three-dimensional modeling on the hardware equipment and the software equipment through a modeling module, and inserting the analysis result and the function diagram into a model.
Preferably, in the above method for monitoring a state of a wind power generation system, the hardware device includes:
the engine room is arranged at the top end of the tower barrel;
a generator fixedly mounted inside the nacelle for converting mechanical energy into electrical energy;
the output end of the gear box is connected with the input end of the generator through a transmission part and is used for increasing the rotating speed;
the bearing is fixedly connected in the cabin and is arranged at the input end position of the gear box;
the inner end of the main shaft is fixedly connected with the input end of the gear box, and the outer end of the main shaft penetrates through the bearing and extends to the outside of the engine room; the main shaft is fixedly connected with the bearing;
the blades are provided with a plurality of blades which are fixedly connected with the outer end of the main shaft respectively; the inside of the blade is of a hollow structure.
Preferably, in the above-mentioned condition monitoring method for a wind power generation system, the electrical device includes:
a braking member connected to the bearing for braking the spindle;
a variable current component connected with the generator for keeping the output current frequency consistent with the power grid;
the variable-voltage component is connected with the variable-current component and is used for changing output voltage data;
and the storage component is connected with the transformation component and is used for receiving and storing the converted electric energy.
Preferably, in the above method for monitoring a state of a wind power generation system, the first detecting device includes:
a plurality of vibration sensing members provided on the cabin wall, the main shaft, the bearing, and the gear case, respectively, for detecting vibration amplitude data;
the rotating speed sensing parts are provided with a plurality of rotating speed sensing parts which are respectively arranged on the main shaft and the transmission part and are used for detecting rotating speed data;
the blade breakage sensing parts are arranged in the blades corresponding to the number of the blades and are respectively used for detecting the breakage degree of the blades;
and the temperature sensing component is fixedly arranged in the cabin and is used for detecting temperature data in the cabin.
Preferably, in the above-mentioned condition monitoring method for a wind power generation system, the second detection device includes:
the voltage sensing components are provided with a plurality of voltage sensing components, are respectively and electrically connected with the braking component, the variable-current component, the variable-voltage component and the storage component and are used for detecting voltage data of the voltage sensing components;
a plurality of current sensing parts electrically connected with the braking part, the variable current part, the variable voltage part and the storage part respectively for detecting current data thereof;
and the load sensing components are provided with a plurality of load sensing components, are respectively and electrically connected with the braking component, the variable-current component, the variable-voltage component and the storage component, and are used for detecting load state data of the load sensing components.
Preferably, in the above method for monitoring a state of a wind power generation system, the modeling module includes:
the scanning unit is arranged in the engine room and is used for scanning the hardware equipment and the software equipment and obtaining sampling point data of the hardware equipment and the software equipment;
the transmission unit is in signal connection with the scanning unit and is used for transmitting the acquired sampling point data;
the modeling unit is connected with the transmission unit and is used for modeling according to the sampling point data;
and the storage unit is connected with the modeling unit and is used for storing the three-dimensional model.
Preferably, in the above method for monitoring a state of a wind power generation system, the analysis module includes:
a data receiving unit, which is in signal connection with the first detecting component and the second detecting component, and is used for receiving and storing detection data;
a comparison unit connected with the data receiving unit; the comparison unit is internally provided with corresponding preset range thresholds, and the detection data are compared with the preset range thresholds one by one to obtain the analysis result;
and the result sending unit is in signal connection with the storage display module and is used for correspondingly inserting the analysis result and the detection data into the storage unit.
Preferably, in the above method for monitoring a state of a wind power generation system, the analysis module further includes:
the computing unit is used for computing the received amplitude data and the rotating speed data of each component, classifying the amplitude data and the rotating speed data according to the passing time, and integrating the amplitude data and the rotating speed data of the corresponding component with the corresponding time value into a set; integrating the received load state data and time values of all the components into a set; integrating the received voltage data and current data of each component with the time value into a set;
a drawing unit connected to the calculation unit, the drawing unit setting three-dimensional function diagrams for different components, respectively; respectively bringing the moment value, the amplitude data and the rotating speed data into a horizontal axis, a vertical axis and a vertical axis of the three-dimensional function chart, and obtaining the vibration amplitude trend and the rotating speed trend of each component in the three-dimensional function chart; carrying the load state data and the moment value into the horizontal axis and the vertical axis of the three-dimensional function graph to obtain the load trend of each component; respectively bringing the voltage data, the current data and the time value into a horizontal axis, a vertical axis and a vertical axis of the three-dimensional function diagram to obtain a voltage trend and a current trend of each component;
and the prediction unit is connected with the drawing unit, analyzes the three-dimensional function diagram through big data, predicts the vibration amplitude trend, the rotating speed trend, the load trend, the voltage trend and the current trend of each component, and correspondingly inserts the predicted coordinates into the three-dimensional function diagram.
Preferably, in the above method for monitoring a state of a wind power generation system, the storage unit further includes:
and the display is connected with the drawing unit, the prediction unit, the modeling unit and the result sending unit and is used for displaying a three-dimensional model, detection data, an analysis result and a three-dimensional function diagram.
Compared with the prior art, the application has the beneficial effects that:
1. monitoring states of hardware equipment and electrical equipment in the wind power generation system in real time;
2. the vibration amplitude and the rotation speed of the hardware equipment and the voltage, the current and the load of the electrical equipment can be predicted;
3. the detected data is displayed more intuitively;
4. the speed of monitoring is increased, and the loss of abnormal state is reduced by prediction.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present application, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of the present application;
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application. The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In the present application, the terms "first," "second," "third," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance; the term "plurality" means two or more, unless expressly defined otherwise. The terms "mounted," "connected," "secured," and the like are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; "coupled" may be directly coupled or indirectly coupled through intermediaries. The specific meaning of the above terms in the present application can be understood by those of ordinary skill in the art according to the specific circumstances.
In the description of the present application, it should be understood that the directions or positional relationships indicated by the terms "upper", "lower", "left", "right", "front", "rear", etc. are based on the directions or positional relationships shown in the drawings, are merely for convenience of describing the present application and simplifying the description, and do not indicate or imply that the devices or units referred to must have a specific direction, be constructed and operated in a specific direction, and thus should not be construed as limiting the present application.
In the description of the present specification, the terms "one embodiment," "some embodiments," "particular embodiments," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
In one embodiment, referring to FIG. 1, a condition monitoring method for a wind power generation system includes:
step one, installing a detection device I on hardware equipment of a wind power generation system, and installing a detection device II on electrical equipment of the wind power generation system;
step two, collecting and sending detection results of the detection device I and the detection device II to an analysis module;
step three, comparing the detection result with each parameter threshold preset by the analysis module to obtain an analysis result; classifying the detection results to obtain a function chart, and predicting the trend of the detection results according to the function chart;
and fourthly, carrying out three-dimensional modeling on the hardware equipment and the software equipment through a modeling module, and inserting the analysis result and the function diagram into the model.
The principle of the above embodiment is: dividing a wind power system into hardware types and electrical types, and detecting different parameters aiming at different types of equipment; and counting and drawing by using the detection result and the analysis result, and predicting the state of the equipment according to the image trend.
The beneficial effects of the embodiment are as follows: the wind power system state prediction method and device can be used for predicting the wind power system state, and further reminding a manager to react in advance, so that risks and losses are reduced.
In one embodiment, referring to FIG. 1, a condition monitoring method for a wind power generation system, the hardware devices including a nacelle, a generator, a gearbox, bearings, a main shaft, and blades; the engine room is arranged at the top end of the tower barrel; the generator is fixedly arranged in the engine room and used for converting mechanical energy into electric energy; the output end of the gear box is connected with the input end of the generator through a transmission part and is used for improving the rotating speed; the bearing is fixedly connected in the engine room and is arranged at the input end position of the gear box; the inner end of the main shaft is fixedly connected with the input end of the gear box, and the outer end of the main shaft penetrates through the bearing and extends to the outside of the engine room; the main shaft is fixedly connected with the bearing; the blades are provided with a plurality of blades which are fixedly connected with the outer end of the main shaft respectively; the inside of the blade is of a hollow structure;
the electrical device includes: a braking part, a variable flow part and a variable pressure part; the braking component is connected with the bearing and used for braking the main shaft; the variable-current component is connected with the generator and used for keeping the output current frequency consistent with the power grid; the variable-voltage component is connected with the variable-current component and is used for changing output voltage data; a storage part connected with the transformation part for receiving and storing the converted electric energy;
the first detection device comprises: vibration sensing means, rotation speed sensing means, blade breakage sensing means, and temperature sensing means;
the vibration sensing components are arranged on the cabin wall, the main shaft, the bearing and the gear box respectively and used for detecting vibration amplitude data; the vibration sensing component comprises a laser emission end fixed on the component to be tested and a photosensitive receiving end at the extending direction of the laser emission end, the photosensitive receiving end can be fixedly connected to the inner wall of the engine room, the area of the photosensitive receiving end is related to the maximum limit of vibration, and the larger the limited vibration amplitude range is, the larger the area of the photosensitive receiving end is; the smaller the vibration amplitude range which can be limited, the smaller the area of the photosensitive receiving end;
the rotating speed sensing parts are respectively arranged on the main shaft and the transmission part and used for detecting rotating speed data; the rotating speed sensing component comprises a transmitting detection end and a sensing gear, a central opening of the sensing gear is sleeved and fixed on the component to be detected, a transmitting head of the transmitting detection end is aligned with the edge of the sensing gear, and the transmitting detection end can be fixedly connected to the inner wall of the engine room; the transmitting detection end transmits infrared rays to the edge of the sensing gear, and the number of teeth of the detecting end, through which the infrared rays pass in unit time, is detected, so that rotational speed data are obtained.
The blade breakage sensing parts are arranged in the blades corresponding to the number of the blades and are used for detecting the breakage degree of the blades; the blade breakage sensing component comprises an air pressure sensor and an air pressure stabilizing component; a plurality of air pressure sensors are fixedly arranged in the blades, the air pressure in the blades is larger than the external air pressure through an air pressure stabilizing component, and the stability of the internal air pressure is ensured; when the surface of the blade is damaged, air passes through the outer wall of the blade and enters the hollow part, and the air pressure value is reduced due to the large flow speed and the small pressure, so that the damaged state of the blade is obtained;
a temperature sensing member fixedly installed in the cabin for detecting temperature data of the cabin interior; the temperature sensing means is preferably implemented with a temperature sensor in combination with a smoke sensor;
the second detection device comprises: a voltage sensing part, a current sensing part, and a load sensing part; the voltage sensing components are respectively and electrically connected with the braking component, the variable-current component, the variable-voltage component and the storage component and are used for detecting voltage data of the variable-voltage component; the current sensing components are respectively and electrically connected with the braking component, the variable-current component, the variable-voltage component and the storage component and are used for detecting current data of the current sensing components; the load sensing components are respectively and electrically connected with the braking component, the variable-current component, the variable-voltage component and the storage component and are used for detecting load state data of the load sensing components;
wherein the voltage sensing component is preferably a voltage sensor, the current sensing component is preferably a current sensor, and the load sensing component is preferably a load sensor; the voltage sensor, the current sensor, the load sensor, the temperature sensor, the smoke sensor and the air pressure sensor are all in the prior art.
The beneficial effects of the embodiment are as follows: detecting vibration amplitude, rotation speed and blade damage degree of each piece of hardware in the cabin, and detecting voltage, current and load of electric equipment including equipment such as wires; the monitoring result is more accurate and comprehensive.
In one embodiment, referring to FIG. 1, a condition monitoring method for a wind power generation system, a modeling module includes: the device comprises a scanning unit, a transmission unit, a modeling unit and a storage unit; the scanning unit is arranged in the cabin and is used for scanning the hardware equipment and the software equipment and acquiring sampling point data of the hardware equipment and the software equipment; the transmission unit is in signal connection with the scanning unit and is used for transmitting the acquired sampling point data; the modeling unit is connected with the transmission unit and is used for modeling according to the sampling point data; the storage unit is connected with the modeling unit and is used for storing the three-dimensional model.
The analysis module comprises: the device comprises a data receiving unit, a comparison unit and a result sending unit; the data receiving unit is in signal connection with the first detection component and the second detection component and is used for receiving and storing detection data; the comparison unit is connected with the data receiving unit; the comparison unit is internally provided with corresponding preset range thresholds, and the detection data are compared with the preset range thresholds one by one to obtain an analysis result; the result sending unit is in signal connection with the storage display module and is used for correspondingly inserting the analysis result and the detection data into the storage unit;
the analysis module further includes: the device comprises a computing unit, a drawing unit and a prediction unit; the computing unit is used for computing the received amplitude data and the rotating speed data of each component, classifying the amplitude data and the rotating speed data according to the passing time, and integrating the amplitude data and the rotating speed data of the corresponding component with the corresponding time value into a set; integrating the received load state data and time values of all the components into a set; integrating the received voltage data and current data of each component with the time value into a set; the drawing unit is connected with the computing unit and is used for respectively setting three-dimensional function diagrams aiming at different parts; respectively bringing the moment value, the amplitude data and the rotating speed data into a horizontal axis, a vertical axis and a vertical axis of a three-dimensional function chart, and obtaining the vibration amplitude trend and the rotating speed trend of each component in the three-dimensional function chart; the load state data and the time value are brought into the horizontal axis and the vertical axis of the three-dimensional function diagram, and the load trend of each component is obtained; respectively bringing the voltage data, the current data and the time value into a horizontal axis, a vertical axis and a vertical axis of the three-dimensional function diagram to obtain a voltage trend and a current trend of each component; the prediction unit is connected with the drawing unit, analyzes the three-dimensional function diagram through big data, predicts the vibration amplitude trend, the rotating speed trend, the load trend, the voltage trend and the current trend of each component, and correspondingly inserts the predicted coordinates into the three-dimensional function diagram;
the storage unit further comprises a display, which is connected with the drawing unit, the prediction unit, the modeling unit and the result sending unit and is used for displaying the three-dimensional model, the detection data, the analysis result and the three-dimensional function diagram;
wherein, the contrast process of the contrast unit includes: setting the detected amplitude data as A, and presetting an amplitude range threshold matrix A0 (A1 and A2), wherein A1 is a first amplitude range, A2 is a second amplitude range, and the amplitude values are ordered to be A1< A2;
when A is less than or equal to A1, the component is in a normal vibration state;
when A1< A2, the component is indicated to be in a slight abnormal vibration state;
when A > A2, the component is shown to be in a severely abnormal vibration state;
setting the detected rotation speed data as B, and presetting a threshold value matrix B0 (B1 and B2) of the rotation speed range, wherein B1 is a first rotation speed range, B2 is a second rotation speed range, and the rotation speed values are ranked as B1< B2;
when B is less than or equal to B1, the part is in an excessively low rotation state;
when B1< B.ltoreq.B2, indicating that the component is in a normal rotation state;
when B > B2, the component is shown in an excessively fast rotation state;
setting the detected temperature data as C, presetting a temperature range threshold matrix C0 (C1, C2), wherein C1 is a first temperature range, C2 is a second temperature range, and sequencing the temperature values as C1< C2;
when C is less than or equal to C1, the component is in a normal temperature state;
when C1< C.ltoreq.C2, indicating that the component is in a high temperature state;
when C > C2, the part is shown to be in a severely elevated temperature state;
setting the detected voltage data as D, and presetting a voltage range threshold matrix D0 (D1, D2), wherein D1 is a first voltage range, D2 is a second voltage range, and the voltage values are ordered as D1< D2;
when D is less than or equal to D1, indicating that the component is in a voltage abnormal state;
when D1 is less than or equal to D2, indicating that the voltage of the component is normal;
when D > D2, indicating that the component is in a voltage anomaly state;
setting the detected current data as F, and presetting a current range threshold matrix F0 (F1, F2), wherein F1 is a first current range, F2 is a second current range, and sequencing according to the current value to obtain F1< F2;
when F is less than or equal to F1, indicating that the component is in a current abnormal state;
when F1 is less than or equal to F2, indicating that the current of the component is in a normal state;
when F > F2, indicating that the component is in a current anomaly state;
setting the detected load data as G, presetting a load range threshold matrix G0 (G1, G2), wherein G1 is a first load range, G2 is a second load range, and sequencing according to the size of the load state data as G1< G2;
when G is less than or equal to G1, indicating that the component is in a load abnormal state;
when G1 is less than or equal to G2, indicating that the load of the component is normal;
when G > G2, indicating that the component is in a load abnormality;
the big data mode or artificial intelligence mode adopted for predicting the trend is the prior art.
The beneficial effects of the embodiment are as follows: the accuracy of the analysis result can be improved through comparison by setting a preset threshold range; by constructing a three-dimensional function diagram through rotating speed, vibration and time, constructing a three-dimensional function diagram through voltage, current and trim, and constructing a function diagram through load and time, the observation is more visual, the slope is calculated in a coordinate mode more easily through big data or an artificial intelligence mode, and the trend of the states of all parts is conveniently predicted.
It should be noted that, in the system provided in the foregoing embodiment, only the division of the foregoing functional modules is illustrated, in practical application, the foregoing functional allocation may be performed by different functional modules, that is, the modules or steps in the embodiment of the present application are further decomposed or combined, for example, the modules in the foregoing embodiment may be combined into one module, or may be further split into multiple sub-modules, so as to complete all or part of the functions described above. The names of the modules and steps related to the embodiments of the present application are merely for distinguishing the respective modules or steps, and are not to be construed as unduly limiting the present application.
The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus/apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus/apparatus.
Thus far, the technical solution of the present application has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present application is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present application, and such modifications and substitutions will be within the scope of the present application.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the spirit or scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the appended claims and their equivalents, the present application is intended to include such modifications and variations as would be included in the above description of the disclosed embodiments, enabling those skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (9)
1. A condition monitoring method for a wind power generation system, comprising:
step one, installing a detection device I on hardware equipment of a wind power generation system, and installing a detection device II on electrical equipment of the wind power generation system;
step two, collecting and sending detection results of the detection device I and the detection device II to an analysis module;
step three, comparing the detection result with each parameter threshold preset by the analysis module to obtain an analysis result; classifying the detection results to obtain a function chart, and predicting the trend of the detection results according to the function chart;
and step four, carrying out three-dimensional modeling on the hardware equipment and the software equipment through a modeling module, and inserting the analysis result and the function diagram into a model.
2. A condition monitoring method for a wind power generation system according to claim 1, wherein the hardware device comprises:
the engine room is arranged at the top end of the tower barrel;
a generator fixedly mounted inside the nacelle for converting mechanical energy into electrical energy;
the output end of the gear box is connected with the input end of the generator through a transmission part and is used for increasing the rotating speed;
the bearing is fixedly connected in the cabin and is arranged at the input end position of the gear box;
the inner end of the main shaft is fixedly connected with the input end of the gear box, and the outer end of the main shaft penetrates through the bearing and extends to the outside of the engine room; the main shaft is fixedly connected with the bearing;
the blades are provided with a plurality of blades which are fixedly connected with the outer end of the main shaft respectively; the inside of the blade is of a hollow structure.
3. A condition monitoring method for a wind power generation system according to claim 2, wherein the electrical device comprises:
a braking member connected to the bearing for braking the spindle;
a variable current component connected with the generator for keeping the output current frequency consistent with the power grid;
the variable-voltage component is connected with the variable-current component and is used for changing output voltage data;
and the storage component is connected with the transformation component and is used for receiving and storing the converted electric energy.
4. A condition monitoring method for a wind power generation system according to claim 3, wherein the first detection means comprises:
a plurality of vibration sensing members provided on the cabin wall, the main shaft, the bearing, and the gear case, respectively, for detecting vibration amplitude data;
the rotating speed sensing parts are provided with a plurality of rotating speed sensing parts which are respectively arranged on the main shaft and the transmission part and are used for detecting rotating speed data;
the blade breakage sensing parts are arranged in the blades corresponding to the number of the blades and are respectively used for detecting the breakage degree of the blades;
and the temperature sensing component is fixedly arranged in the cabin and is used for detecting temperature data in the cabin.
5. The method for monitoring the state of a wind power generation system according to claim 4, wherein the second detecting means includes:
the voltage sensing components are provided with a plurality of voltage sensing components, are respectively and electrically connected with the braking component, the variable-current component, the variable-voltage component and the storage component and are used for detecting voltage data of the voltage sensing components;
a plurality of current sensing parts electrically connected with the braking part, the variable current part, the variable voltage part and the storage part respectively for detecting current data thereof;
and the load sensing components are provided with a plurality of load sensing components, are respectively and electrically connected with the braking component, the variable-current component, the variable-voltage component and the storage component, and are used for detecting load state data of the load sensing components.
6. The condition monitoring method for a wind power generation system of claim 5, wherein the modeling module comprises:
the scanning unit is arranged in the engine room and is used for scanning the hardware equipment and the software equipment and obtaining sampling point data of the hardware equipment and the software equipment;
the transmission unit is in signal connection with the scanning unit and is used for transmitting the acquired sampling point data;
the modeling unit is connected with the transmission unit and is used for modeling according to the sampling point data;
and the storage unit is connected with the modeling unit and is used for storing the three-dimensional model.
7. The condition monitoring method for a wind power generation system of claim 6, wherein the analysis module comprises:
a data receiving unit, which is in signal connection with the first detecting component and the second detecting component, and is used for receiving and storing detection data;
a comparison unit connected with the data receiving unit; the comparison unit is internally provided with corresponding preset range thresholds, and the detection data are compared with the preset range thresholds one by one to obtain the analysis result;
and the result sending unit is in signal connection with the storage display module and is used for correspondingly inserting the analysis result and the detection data into the storage unit.
8. The condition monitoring method for a wind power generation system of claim 7, wherein the analysis module further comprises:
the computing unit is used for computing the received amplitude data and the rotating speed data of each component, classifying the amplitude data and the rotating speed data according to the passing time, and integrating the amplitude data and the rotating speed data of the corresponding component with the corresponding time value into a set; integrating the received load state data and time values of all the components into a set; integrating the received voltage data and current data of each component with the time value into a set;
a drawing unit connected to the calculation unit, the drawing unit setting three-dimensional function diagrams for different components, respectively; respectively bringing the moment value, the amplitude data and the rotating speed data into a horizontal axis, a vertical axis and a vertical axis of the three-dimensional function chart, and obtaining the vibration amplitude trend and the rotating speed trend of each component in the three-dimensional function chart; carrying the load state data and the moment value into the horizontal axis and the vertical axis of the three-dimensional function graph to obtain the load trend of each component; respectively bringing the voltage data, the current data and the time value into a horizontal axis, a vertical axis and a vertical axis of the three-dimensional function diagram to obtain a voltage trend and a current trend of each component;
and the prediction unit is connected with the drawing unit, analyzes the three-dimensional function diagram through big data, predicts the vibration amplitude trend, the rotating speed trend, the load trend, the voltage trend and the current trend of each component, and correspondingly inserts the predicted coordinates into the three-dimensional function diagram.
9. The condition monitoring method for a wind power generation system according to claim 7, wherein the storage unit further comprises:
and the display is connected with the drawing unit, the prediction unit, the modeling unit and the result sending unit and is used for displaying a three-dimensional model, detection data, an analysis result and a three-dimensional function diagram.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310824812.7A CN116877351A (en) | 2023-07-04 | 2023-07-04 | State monitoring method for wind power generation system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310824812.7A CN116877351A (en) | 2023-07-04 | 2023-07-04 | State monitoring method for wind power generation system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116877351A true CN116877351A (en) | 2023-10-13 |
Family
ID=88262806
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310824812.7A Pending CN116877351A (en) | 2023-07-04 | 2023-07-04 | State monitoring method for wind power generation system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116877351A (en) |
-
2023
- 2023-07-04 CN CN202310824812.7A patent/CN116877351A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20160333854A1 (en) | Digital Twin Interface for Operating Wind Farms | |
| KR101942806B1 (en) | Moving type defect diagnosis system for photovoltaic power generation equipment | |
| CN104747367B (en) | Power curves of wind-driven generator sets Characteristics Detection system | |
| CN202710100U (en) | Wind generating set remote on-line health state monitoring and fault diagnosing system | |
| EP3043066B1 (en) | System and method of diagnosing wind turbine power generation facility | |
| CN108168682A (en) | A kind of GIL On-line Faults monitoring system based on vibration signal support vector machines | |
| CN103343728A (en) | Wind generating set remote on-line multi-mode health state monitoring and fault diagnosis system | |
| CN112803592A (en) | Intelligent fault early warning method and system suitable for distributed power station | |
| CN112324629A (en) | Wind power blade early damage monitoring system and method based on vibration and sound | |
| US20120029843A1 (en) | Method, system, and computer program product for sensor data collection in a wind turbine | |
| DK2667023T3 (en) | Control of a wind energy system | |
| CN110187233A (en) | Holographic sensor, transmission line malfunction method of disposal and terminal device | |
| CN111878324A (en) | Wind power plant tower drum vortex-induced vibration early warning method and early warning system | |
| CN115238933A (en) | Wind turbine generator inertia response detection method, device and system based on multipoint measurement | |
| CN116877351A (en) | State monitoring method for wind power generation system | |
| CN208076016U (en) | A kind of GIL On-line Faults monitoring system based on vibration signal support vector machines | |
| CN113654587A (en) | Wind-powered electricity generation field environmental data monitoring devices | |
| CN115263683A (en) | Wind turbine generator monitoring control method and system based on optical fiber sensing | |
| CN115111115A (en) | System and method for operating power generation assets | |
| CN114719958A (en) | Vibration monitoring system and method based on WIA-PA and 4G double wireless technology | |
| CN220979768U (en) | Marine wind turbine generator system blade fault diagnosis system | |
| KR101573832B1 (en) | Computer network system for diagnosing and mornitoring remotely of hybrid generating system using wind power and solar energy, and processing method of the same | |
| CN208506574U (en) | Wind turbine equipment safety information automatic propelling device | |
| KR101314716B1 (en) | Wind turbine check system based app. | |
| CN220434942U (en) | Panoramic fault diagnosis system for wind turbine generator |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication |