CN117905656A - On-line monitoring device for fan blade - Google Patents
On-line monitoring device for fan blade Download PDFInfo
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- CN117905656A CN117905656A CN202410317706.4A CN202410317706A CN117905656A CN 117905656 A CN117905656 A CN 117905656A CN 202410317706 A CN202410317706 A CN 202410317706A CN 117905656 A CN117905656 A CN 117905656A
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- 230000005540 biological transmission Effects 0.000 claims abstract description 22
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- 230000008569 process Effects 0.000 claims description 9
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- 230000002159 abnormal effect Effects 0.000 claims description 4
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- 238000003199 nucleic acid amplification method Methods 0.000 claims description 4
- 239000002243 precursor Substances 0.000 claims description 4
- 230000005236 sound signal Effects 0.000 claims description 2
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- 238000007689 inspection Methods 0.000 description 6
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- 238000011900 installation process Methods 0.000 description 2
- 239000013307 optical fiber Substances 0.000 description 2
- 230000036316 preload Effects 0.000 description 2
- 230000009467 reduction Effects 0.000 description 2
- 230000004044 response Effects 0.000 description 2
- 238000011179 visual inspection Methods 0.000 description 2
- 235000017166 Bambusa arundinacea Nutrition 0.000 description 1
- 235000017491 Bambusa tulda Nutrition 0.000 description 1
- 241001330002 Bambuseae Species 0.000 description 1
- 235000015334 Phyllostachys viridis Nutrition 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 239000011425 bamboo Substances 0.000 description 1
- 238000005336 cracking Methods 0.000 description 1
- 230000032798 delamination Effects 0.000 description 1
- 230000006866 deterioration Effects 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
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- 239000000835 fiber Substances 0.000 description 1
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- 239000011148 porous material Substances 0.000 description 1
- 238000010248 power generation Methods 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M13/00—Testing of machine parts
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- 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
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
- G01H17/00—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves, not provided for in the preceding groups
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- 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
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Abstract
The invention discloses an on-line monitoring device for fan blades, which has the technical scheme that: the device comprises a fan blade data acquisition module, a transmission module, an edge end fault diagnosis module and a push alarm module; the fan blade data acquisition module is used for acquiring fan blade defect conditions and fan blade defect conditions, and comprises a blade voiceprint monitoring unit and a blade voiceprint vibration monitoring unit, wherein the blade voiceprint monitoring unit monitors blade sound data when the fan operates by using a voiceprint recognition algorithm through a plurality of voiceprint sensors, and the voiceprint monitoring technology can accurately judge discharge conditions and fault types by analyzing characteristics of frequency spectrum, amplitude, time domain and the like of discharge sound, so that the accuracy of fault diagnosis is improved; low cost: compared with the acoustic emission scheme, the number of sensors is small, and the price is low; the adaptability is wide, and the implementation is not limited: non-invasive monitoring.
Description
Technical Field
The invention relates to the technical field of fan blade defect detection, in particular to an on-line fan blade monitoring device.
Background
New energy wind power industry. Wind farms are typically distributed in areas with rare people and remote geographical locations and relatively rich wind resources. Severe working environment and weather factor influence, the problem that brings: many faults exist and inspection is difficult. The components that wind power equipment needs to detect are classified into three types: blade, transmission part, a tower section of thick bamboo. Wherein the blade defects are many: the sources of common defects of wind turbine blades can be divided into three types, namely a manufacturing process, a transportation and installation process and an operation process. In the manufacturing process, due to the huge size of the blade and the limitation of the manufacturing process, delamination, pores, fiber fracture, inclusion and the like often occur in the blade forming and die assembly bonding processes. Because of the huge size of the blade in the transportation and installation process, the blade cannot collide with other objects and be scratched in the hoisting and long-distance transportation processes, and serious damages such as micro-cracking at layering or bonding positions and microcracks on the surface of the blade can be formed on the blade. In the running process, the wind driven generator blade works in a field environment with complex conditions for a long time, and various severe environmental factors such as rain erosion, icing, thunder and fatigue can cause potential damage to the blade material. Blade defects are difficult to find. The bulge and crack of the blade cannot be detected from the outside when the bulge and crack are slight. The pitch bearing imperfections are not visible from the outside. Crack growth, blade fracture, risk of tower collapse, a process of progression deterioration. Once the blades are broken, serious consequences are caused, great economic loss is caused, and the risk of safety accidents is high. Therefore, the fan blades of the wind power plant are required to be effectively monitored in an on-line state, so that the failure rate is reduced, the stable operation of equipment is ensured, and the power generation benefit of the wind power plant is improved.
The traditional fan blade inspection mode mainly comprises manual visual inspection, and is divided into: high-power telescope inspection, high-altitude detouring descending visual inspection and blade maintenance platform inspection, and the inspection modes have the problems of low inspection efficiency, high economic cost, high-altitude falling potential safety hazard and the like, and are invalid for defects such as cracks, deformation and the like of the fan blade, so that a scheme capable of timely finding early defects of the blade is urgently needed in the industry. And no product can effectively solve the problem at present.
Disclosure of Invention
Aiming at the problems in the background art, the invention aims to provide an on-line monitoring device for fan blades, so as to solve the problems in the background art.
The technical aim of the invention is realized by the following technical scheme:
an online monitoring device for fan blades comprises a fan blade data acquisition module, a transmission module, an edge end fault diagnosis module and a push alarm module;
The fan blade data acquisition module is used for acquiring the defect condition of the fan blade and comprises a blade voiceprint monitoring unit and a blade voiceprint monitoring unit, wherein the blade voiceprint monitoring unit monitors blade sound data when the fan operates by using a voiceprint recognition algorithm through a plurality of voiceprint sensors, and the blade voiceprint monitoring unit monitors abnormal noise, vibration signals and infrared signal detection data of the blade through a plurality of voiceprint integrated sensors;
The transmission module is arranged on the fan hub and is used for wirelessly transmitting the fan blades and external data acquired by the fan blade data acquisition module to the edge end fault diagnosis module in real time, so that the problems of communication and data transmission between the fan hub and the fan cabin are solved;
The edge end fault diagnosis module is arranged in the fan cabin and is used for processing the data acquired by the fan blade data acquisition module, comprehensively analyzing and identifying fault precursor information in the running process of the blade, analyzing the frequency spectrum, amplitude and time domain characteristics of the discharge sound of the fan blade through the data acquired by the voiceprint sensor, and accurately judging the discharge condition and fault type of the fan blade, so that timely early warning is provided for the fault defect of the fan blade;
The pushing alarm module is used for pushing early warning information to alarm staff and uploading fault diagnosis data.
Preferably, the operation implementation steps of the blade voiceprint monitoring unit are as follows:
step one, blade sound data are collected in real time when the fan operates through a voiceprint sensor;
Step two, carrying out analog-digital conversion on sound data of the blade, and carrying out signal filtering, amplification and extraction;
Step three, extracting sound characteristic parameters of the sound data after signal processing, and reducing the data volume;
and step four, adopting a transmission module to wirelessly transmit the extracted blade sound characteristic parameters to an edge end fault diagnosis module.
Preferably, a wireless AP gateway is provided in the transmission module, and the wireless AP gateway is connected with the voiceprint sensors and the voiceprint sensors in a wireless communication manner.
Preferably, a first USP uninterrupted power supply is arranged in the fan hub, and the first USP uninterrupted power supply is electrically connected with the voiceprint sensors, the voiceprint sensors and the wireless AP gateway through wires respectively.
Preferably, the edge fault diagnosis module comprises edge network equipment, an anomaly detection unit and a trend analysis unit, wherein the edge network equipment is used for receiving and uploading data, the anomaly detection unit is used for detecting fan blade sound data, accurately judging fan discharge conditions and fault types in real time, and the trend analysis unit is used for comprehensively analyzing and identifying according to the results of the anomaly detection unit and providing early warning information.
Preferably, the edge network device employs two or more of a router, a routing switch, an integrated access device, a multiplexer, and various metropolitan area network and wide area network access devices.
Preferably, a second USP uninterruptible power supply is arranged in the fan cabin, and the second USP uninterruptible power supply is electrically connected with the edge network equipment through a wire.
Preferably, the system further comprises a processor and a storage device; the storage device has a program stored thereon, the program being executed by the processor.
Preferably, the blade voiceprint monitoring unit comprises a sound denoising subunit, wherein the sound denoising subunit is used for removing data noise signals acquired by the voiceprint sensor, improving the quality of the sound signals, and the noise reduction method comprises a filter and self-adaptive noise reduction.
Preferably, a plurality of the sound and vibration integrated sensors are respectively arranged on a pitch bearing and a pitch bolt of the fan.
In summary, the invention has the following advantages:
First, in this fan blade on-line monitoring device, can realize blade defect real-time supervision and early warning in advance through blade voiceprint monitoring unit and blade sound and shake monitoring unit. When the system is deployed, the sensor is convenient to install, has a large coverage area and controllable overall cost, is suitable for delivery, shutdown and operation at each stage, solves the problem of overlarge data quantity, has slow response time, and can not respond to the fault problem due to communication fault;
Secondly, in the fan blade online monitoring device, the sensitivity of device monitoring is higher, defects are found early, defect elimination is guided, and the device is convenient to install; the real-time monitoring cost is controllable, and the accuracy is high; the voiceprint monitoring technology can accurately judge the discharge condition and the fault type by analyzing the characteristics of the frequency spectrum, the amplitude, the time domain and the like of the discharge sound, so that the fault diagnosis accuracy is improved; low cost: compared with the acoustic emission scheme, the number of sensors is small, and the price is low; the adaptability is wide, and the implementation is not limited: non-invasive monitoring, relative optical fiber sensor mode needs pre-buried, also became invalid after the blade damages, can dispatch from the factory to pre-load, also can adorn after the environment that has already operated, can use under multiple scene: and (5) factory detection, shutdown detection and operation detection. In a word, the scheme for on-line monitoring of the defects of the blade by the voiceprint has the advantages of high accuracy, high sensitivity, low cost, wide adaptability and unlimited implementation.
Drawings
FIG. 1 is a block diagram of the structure of the present invention;
FIG. 2 is a block diagram of a fan blade data acquisition module of the present invention;
FIG. 3 is a working block diagram of the present invention;
Fig. 4 is a data processing workflow diagram of the present invention.
Detailed Description
The following description of the embodiments of the present invention 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 invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
1, Referring to fig. 1-4, an on-line monitoring device for fan blades includes a fan blade data acquisition module, a transmission module, an edge end fault diagnosis module and a push alarm module;
The fan blade data acquisition module is used for acquiring the defect condition of the fan blade and the defect condition of the fan blade, and comprises a blade voiceprint monitoring unit and a blade voiceprint monitoring unit, wherein the blade voiceprint monitoring unit monitors blade sound data when the fan operates by using a voiceprint recognition algorithm through a plurality of voiceprint sensors, and the blade voiceprint monitoring unit monitors abnormal noise, vibration signals and infrared signal detection data of the blade through a plurality of voiceprint integrated sensors;
The transmission module is arranged on the fan hub and is used for wirelessly transmitting the fan blades and the external data acquired by the fan blade data acquisition module to the edge end fault diagnosis module in real time, so that the problems of communication and data transmission between the fan hub and the fan cabin are solved;
The edge end fault diagnosis module is arranged in the fan cabin and is used for processing the data acquired by the fan blade data acquisition module, comprehensively analyzing and identifying fault precursor information in the running process of the blade, analyzing the frequency spectrum, amplitude and time domain characteristics of the discharge sound of the fan blade through the data acquired by the voiceprint sensor, and accurately judging the discharge condition and the fault type of the fan blade, so that timely early warning is provided for the fault defect of the fan blade;
The pushing alarm module is used for pushing early warning information to alarm staff and uploading fault diagnosis data.
Preferably, the operation implementation steps of the blade voiceprint monitoring unit are as follows:
step one, blade sound data are collected in real time when the fan operates through a voiceprint sensor;
Step two, carrying out analog-digital conversion on sound data of the blade, and carrying out signal filtering, amplification and extraction;
Step three, extracting sound characteristic parameters of the sound data after signal processing, and reducing the data volume;
and step four, adopting a transmission module to wirelessly transmit the extracted blade sound characteristic parameters to an edge end fault diagnosis module.
The wireless AP gateway is arranged in the transmission module and is respectively in wireless communication connection with the plurality of voiceprint sensors and the plurality of voicevibration integrated sensors.
The fan hub is internally provided with a first USP uninterruptible power supply, and the first USP uninterruptible power supply is electrically connected with the plurality of voiceprint sensors, the plurality of voicevibration integrated sensors and the wireless AP gateway through wires respectively.
The edge end fault diagnosis module comprises edge network equipment, an anomaly detection unit and a trend analysis unit, wherein the edge network equipment is used for receiving and uploading data, the anomaly detection unit is used for detecting fan blade sound data, accurately judging fan discharge conditions and fault types in real time, and the trend analysis unit is used for comprehensively analyzing and identifying according to the results of the anomaly detection unit and providing early warning information.
The edge network device adopts a router, a routing switch, an integrated access device and a wide area network access device.
The fan cabin is internally provided with a second USP uninterruptible power supply, and the second USP uninterruptible power supply is electrically connected with the edge network equipment through a wire.
The above also includes a processor and a storage device; the storage device has a program stored thereon, and the program is executed by the processor.
The blade voiceprint monitoring unit comprises a voice denoising subunit, wherein the voice denoising subunit is used for removing data noise signals acquired by the voiceprint sensor, improving the quality of the voice signals, and the denoising method comprises a filter and self-adaptive denoising.
The plurality of sound vibration integrated sensors are respectively arranged on a variable pitch bearing and a variable pitch bolt of the fan.
Embodiment 2, refer to fig. 1-4, an online monitoring device for fan blades, which comprises a fan blade data acquisition module, a transmission module, an edge end fault diagnosis module and a push alarm module;
The fan blade data acquisition module is used for acquiring the defect condition of the fan blade and the defect condition of the fan blade, and comprises a blade voiceprint monitoring unit and a blade voiceprint monitoring unit, wherein the blade voiceprint monitoring unit monitors blade sound data when the fan operates by using a voiceprint recognition algorithm through a plurality of voiceprint sensors, and the blade voiceprint monitoring unit monitors abnormal noise, vibration signals and infrared signal detection data of the blade through a plurality of voiceprint integrated sensors;
The transmission module is arranged on the fan hub and is used for wirelessly transmitting the fan blades and the external data acquired by the fan blade data acquisition module to the edge end fault diagnosis module in real time, so that the problems of communication and data transmission between the fan hub and the fan cabin are solved;
The edge end fault diagnosis module is arranged in the fan cabin and is used for processing the data acquired by the fan blade data acquisition module, comprehensively analyzing and identifying fault precursor information in the running process of the blade, analyzing the frequency spectrum, amplitude and time domain characteristics of the discharge sound of the fan blade through the data acquired by the voiceprint sensor, and accurately judging the discharge condition and the fault type of the fan blade, so that timely early warning is provided for the fault defect of the fan blade;
The pushing alarm module is used for pushing early warning information to alarm staff and uploading fault diagnosis data.
Preferably, the operation implementation steps of the blade voiceprint monitoring unit are as follows:
step one, blade sound data are collected in real time when the fan operates through a voiceprint sensor;
Step two, carrying out analog-digital conversion on sound data of the blade, and carrying out signal filtering, amplification and extraction;
Step three, extracting sound characteristic parameters of the sound data after signal processing, and reducing the data volume;
and step four, adopting a transmission module to wirelessly transmit the extracted blade sound characteristic parameters to an edge end fault diagnosis module.
The wireless AP gateway is arranged in the transmission module and is respectively in wireless communication connection with the plurality of voiceprint sensors and the plurality of voicevibration integrated sensors.
The fan hub is internally provided with a first USP uninterruptible power supply, and the first USP uninterruptible power supply is electrically connected with the plurality of voiceprint sensors, the plurality of voicevibration integrated sensors and the wireless AP gateway through wires respectively.
The edge end fault diagnosis module comprises edge network equipment, an anomaly detection unit and a trend analysis unit, wherein the edge network equipment is used for receiving and uploading data, the anomaly detection unit is used for detecting fan blade sound data, accurately judging fan discharge conditions and fault types in real time, and the trend analysis unit is used for comprehensively analyzing and identifying according to the results of the anomaly detection unit and providing early warning information.
The edge network device adopts a router and a routing switch.
The fan cabin is internally provided with a second USP uninterruptible power supply, and the second USP uninterruptible power supply is electrically connected with the edge network equipment through a wire.
The above also includes a processor and a storage device; the storage device has a program stored thereon, and the program is executed by the processor.
The blade voiceprint monitoring unit comprises a voice denoising subunit, wherein the voice denoising subunit is used for removing data noise signals acquired by the voiceprint sensor, improving the quality of the voice signals, and the denoising method comprises a filter and self-adaptive denoising.
The plurality of sound vibration integrated sensors are respectively arranged on a variable pitch bearing and a variable pitch bolt of the fan.
The use principle and the advantages are that:
The blade defect real-time monitoring and early warning can be realized through the blade voiceprint monitoring unit and the blade voicevibration monitoring unit. When the system is deployed, the sensor is convenient to install, the coverage area is large, the overall cost is controllable, the sensor is suitable for delivery, shutdown and operation at each stage, the problem of overlarge data quantity is solved, the response time is slow, the problem of failure can not be responded due to communication failure, the sensitivity of device monitoring is high, defects are found in early stage, defect elimination is guided, and the sensor is convenient to install; the real-time monitoring cost is controllable, and the accuracy is high; the voiceprint monitoring technology can accurately judge the discharge condition and the fault type by analyzing the characteristics of the frequency spectrum, the amplitude, the time domain and the like of the discharge sound, so that the fault diagnosis accuracy is improved; low cost: compared with the acoustic emission scheme, the number of sensors is small, and the price is low; the adaptability is wide, and the implementation is not limited: non-invasive monitoring, relative optical fiber sensor mode needs pre-buried, also became invalid after the blade damages, can dispatch from the factory to pre-load, also can adorn after the environment that has already operated, can use under multiple scene: and (5) factory detection, shutdown detection and operation detection. In a word, the scheme for on-line monitoring of the defects of the blade by the voiceprint has the advantages of high accuracy, high sensitivity, low cost, wide adaptability and unlimited implementation.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (9)
1. An on-line monitoring device for fan blades, which is characterized in that: the device comprises a fan blade data acquisition module, a transmission module, an edge end fault diagnosis module and a push alarm module;
The fan blade data acquisition module is used for acquiring the defect condition of the fan blade and comprises a blade voiceprint monitoring unit and a blade voiceprint monitoring unit, wherein the blade voiceprint monitoring unit monitors blade sound data when the fan operates by using a voiceprint recognition algorithm through a plurality of voiceprint sensors, and the blade voiceprint monitoring unit monitors abnormal noise, vibration signals and infrared signal detection data of the blade through a plurality of voiceprint integrated sensors;
The transmission module is arranged on the fan hub and is used for wirelessly transmitting the fan blades and external data acquired by the fan blade data acquisition module to the edge end fault diagnosis module in real time, so that the problems of communication and data transmission between the fan hub and the fan cabin are solved;
The edge end fault diagnosis module is arranged in the fan cabin and is used for processing the data acquired by the fan blade data acquisition module, comprehensively analyzing and identifying fault precursor information in the running process of the blade, analyzing the frequency spectrum, amplitude and time domain characteristics of the discharge sound of the fan blade through the data acquired by the voiceprint sensor, and accurately judging the discharge condition and fault type of the fan blade, so that timely early warning is provided for the fault defect of the fan blade;
The pushing alarm module is used for pushing early warning information to alarm staff and uploading fault diagnosis data.
2. The fan blade on-line monitoring device of claim 1, wherein: the operation implementation steps of the blade voiceprint monitoring unit are as follows:
step one, blade sound data are collected in real time when the fan operates through a voiceprint sensor;
Step two, carrying out analog-digital conversion on sound data of the blade, and carrying out signal filtering, amplification and extraction;
Step three, extracting sound characteristic parameters of the sound data after signal processing, and reducing the data volume;
and step four, adopting a transmission module to wirelessly transmit the extracted blade sound characteristic parameters to an edge end fault diagnosis module.
3. The fan blade on-line monitoring device of claim 1, wherein: the wireless AP gateway is arranged in the transmission module and is respectively in wireless communication connection with the voiceprint sensors and the voiceprint-vibration integrated sensors.
4. A fan blade on-line monitoring device according to claim 3, wherein: the fan hub is internally provided with a first USP uninterrupted power supply, and the first USP uninterrupted power supply is respectively and electrically connected with the voiceprint sensors, the voicevibration integrated sensors and the wireless AP gateway through wires.
5. The fan blade on-line monitoring device of claim 1, wherein: the edge end fault diagnosis module comprises edge network equipment, an anomaly detection unit and a trend analysis unit, wherein the edge network equipment is used for receiving and uploading data, the anomaly detection unit is used for detecting fan blade sound data and accurately judging fan discharge conditions and fault types in real time, and the trend analysis unit is used for comprehensively analyzing and identifying according to the results of the anomaly detection unit and providing early warning information.
6. The fan blade on-line monitoring device of claim 1, wherein: the edge network device adopts two or more of a router, a routing switch, an integrated access device, a multiplexer and various metropolitan area network and wide area network access devices.
7. The fan blade on-line monitoring device of claim 1, wherein: the system also comprises a processor and a storage device; the storage device has a program stored thereon, the program being executed by the processor.
8. The fan blade on-line monitoring device of claim 1, wherein: the blade voiceprint monitoring unit comprises a sound denoising subunit, wherein the sound denoising subunit is used for removing data noise signals acquired by the voiceprint sensor, improving the quality of the sound signals, and the denoising method comprises a filter and self-adaptive denoising.
9. The fan blade on-line monitoring device of claim 1, wherein: and the sound vibration integrated sensors are respectively arranged on a pitch bearing and a pitch bolt of the fan.
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| CN202410317706.4A CN117905656A (en) | 2024-03-20 | 2024-03-20 | On-line monitoring device for fan blade |
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| CN202410317706.4A CN117905656A (en) | 2024-03-20 | 2024-03-20 | On-line monitoring device for fan blade |
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113898537A (en) * | 2021-08-31 | 2022-01-07 | 大唐丰都新能源有限公司 | Remote intelligent inspection system for wind power plant |
| CN114562429A (en) * | 2021-11-19 | 2022-05-31 | 浙江运达风电股份有限公司 | Wind turbine generator blade damage early warning method based on clearance and sound vibration monitoring |
| CN115013259A (en) * | 2022-07-07 | 2022-09-06 | 中广核大悟阳平风力发电有限公司 | Fan blade health monitoring system |
| CN115641871A (en) * | 2022-09-29 | 2023-01-24 | 福建国电风力发电有限公司 | Fan blade abnormity detection method based on voiceprint |
| CN116625683A (en) * | 2023-04-11 | 2023-08-22 | 中国长江三峡集团有限公司 | Wind turbine generator system bearing fault identification method, system and device and electronic equipment |
| CN117006000A (en) * | 2023-08-07 | 2023-11-07 | 普镁(上海)科技有限公司 | Disconnect-type aerogenerator monitoring devices |
| CN117052608A (en) * | 2023-09-13 | 2023-11-14 | 北京英华达电力电子工程科技有限公司 | Acoustic-vibration-synergistic fan blade fracture early warning device and method |
-
2024
- 2024-03-20 CN CN202410317706.4A patent/CN117905656A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113898537A (en) * | 2021-08-31 | 2022-01-07 | 大唐丰都新能源有限公司 | Remote intelligent inspection system for wind power plant |
| CN114562429A (en) * | 2021-11-19 | 2022-05-31 | 浙江运达风电股份有限公司 | Wind turbine generator blade damage early warning method based on clearance and sound vibration monitoring |
| CN115013259A (en) * | 2022-07-07 | 2022-09-06 | 中广核大悟阳平风力发电有限公司 | Fan blade health monitoring system |
| CN115641871A (en) * | 2022-09-29 | 2023-01-24 | 福建国电风力发电有限公司 | Fan blade abnormity detection method based on voiceprint |
| CN116625683A (en) * | 2023-04-11 | 2023-08-22 | 中国长江三峡集团有限公司 | Wind turbine generator system bearing fault identification method, system and device and electronic equipment |
| CN117006000A (en) * | 2023-08-07 | 2023-11-07 | 普镁(上海)科技有限公司 | Disconnect-type aerogenerator monitoring devices |
| CN117052608A (en) * | 2023-09-13 | 2023-11-14 | 北京英华达电力电子工程科技有限公司 | Acoustic-vibration-synergistic fan blade fracture early warning device and method |
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