Wind generating set blade monitoring system and wind generating set

Abstract

The utility model discloses a wind generating set blade monitoring system and a wind generating set. The wind generating set blade monitoring system comprises a switch and at least two sensor subsystems. Each sensor subsystem comprises a sensor and a data processing module connected with the sensor, the sensors collect physical information in the leaf, the data processing modules judge the health state of the leaf based on the physical information collected by the sensors, and the sensors in different sensor subsystems collect different physical information; and the data processing module in each sensor subsystem is connected with the switch through the Ethernet. According to the blade monitoring system of the wind generating set, the multi-dimensional physical information of the blade is obtained by the multiple sensor subsystems at the same time, the health state of the blade is judged based on the multi-dimensional physical information, and the problems that the analysis view angle is limited and the analysis result is one-sided due to the fact that single physical information is relied on are solved; and the blade damage detection precision and reliability are effectively improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of wind power generation, and particularly relates to a wind turbine blade monitoring system and a wind turbine. BACKGROUND

[0002] The blades of a wind turbine are affected by self-gravity, rotational centrifugal force, aerodynamic force, rain, snow, salt mist, sand, lightning and the like in the external environment during operation, so that the blade body is easily damaged and accidents such as breakage and falling occur, which leads to a decrease in the performance of the wind turbine and may even endanger personnel safety. In order to reduce the risk of blade damage, monitoring and early warning protection of the health status of the blade during operation have become a hot spot in the industry.

[0003] In the related art, a single physical information of the blade is mainly collected by a sensor, and the health status of the blade is determined based on the single physical information. However, this method has the problems of single analysis dimension and relatively one-sided determination result, and the reliability of the determination result is low. CONTENT OF THE INVENTION

[0004] The wind turbine blade monitoring system and the wind turbine provided by the embodiments of the application simultaneously acquire multi-dimensional physical information of the blade by using multiple sensor subsystems, and determine the health status of the blade based on the multi-dimensional physical information, thereby solving the problems of limited analysis perspective and one-sided analysis result caused by relying on single physical information, and effectively improving the accuracy and reliability of blade damage detection.

[0005] In a first aspect, the embodiments of the application provide a wind turbine blade monitoring system, which comprises a switch and at least two sensor subsystems.

[0006] Each sensor subsystem comprises a sensor and a data processing module connected to the sensor. The sensor collects physical information inside the blade, and the data processing module determines the health status of the blade based on the physical information collected by the sensor. The sensors in different sensor subsystems collect different physical information.

[0007] The data processing module in each sensor subsystem is connected to the switch through an Ethernet.

[0008] As a possible implementation manner, the switch is connected to a main control system of a wind turbine to which the blade belongs through an Ethernet.

[0009] As a possible implementation manner, the at least two sensor subsystems comprise at least two of the following sensor subsystems: an illumination subsystem, an image subsystem, a voiceprint subsystem, a sound emission subsystem, a vibration subsystem and a load subsystem.

[0010] The sensor of the light intensity subsystem comprises a light intensity sensor, and the data processing module of the light intensity subsystem comprises a controller.

[0011] The sensor of the image subsystem comprises a visual sensor, and the data processing module of the image subsystem comprises an image collector.

[0012] The sensor of the voiceprint subsystem comprises a voiceprint sensor, and the data processing module of the voiceprint subsystem comprises a voiceprint collector.

[0013] The sensor of the acoustic emission subsystem comprises an acoustic emission sensor, and the data processing module of the acoustic emission subsystem comprises an acoustic emission collector.

[0014] The sensor of the vibration subsystem comprises a vibration sensor, and the data processing module of the vibration subsystem comprises a vibration collector.

[0015] The sensor of the load subsystem comprises a fiber-optic load sensor, and the data processing module of the load subsystem comprises a load demodulator.

[0016] As a possible implementation manner, the at least two sensor subsystems comprise a controller;

[0017] The controller is connected to a main control system of the wind turbine unit to which the blade belongs through a process field bus.

[0018] As a possible implementation manner, the at least two sensor subsystems further comprise a vibration subsystem;

[0019] The vibration sensor is connected to the controller through the field bus.

[0020] As a possible implementation manner, the at least two sensor subsystems further comprise a load subsystem;

[0021] The load demodulator is connected to the controller through the field bus.

[0022] As a possible implementation manner, the wind turbine unit blade monitoring system further comprises an industrial computer;

[0023] The industrial computer is connected to a switch through an Ethernet.

[0024] As a possible implementation manner, the wind turbine unit blade monitoring system further comprises a router, and the router is connected to the industrial computer.

[0025] As a possible implementation manner, the industrial computer is connected to a remote maintenance device.

[0026] In a second aspect, the embodiments of the present application provide a wind turbine unit comprising a blade and the wind turbine unit blade monitoring system of the first aspect.

[0027] The wind turbine blade monitoring system and wind turbine of this application embodiment include a switch and at least two types of sensor subsystems. Each sensor subsystem includes a sensor and a data processing module connected to the sensor. The sensor collects physical information inside the blade, and the data processing module determines the health status of the blade based on the physical information collected by the sensor. Sensors in different sensor subsystems collect different physical information. The data processing module in each sensor subsystem is connected to the switch via Ethernet. According to the embodiments of this application, the wind turbine blade monitoring system simultaneously utilizes multiple sensor subsystems to acquire multi-dimensional physical information of the blade, and determines the health status of the blade based on the multi-dimensional physical information. This solves the problems of limited analytical perspective and one-sided analytical results caused by relying on single physical information, effectively improving the accuracy and reliability of blade damage detection. Attached Figure Description

[0028] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0029] Figure 1 This is a schematic diagram of the topology of a wind turbine blade monitoring system provided in some embodiments of this application;

[0030] Figure 2 This is a schematic diagram of the topology of the illuminance subsystem 121 provided in an embodiment of this application;

[0031] Figure 3 This is a schematic diagram of the topology of the image subsystem 122 provided in an embodiment of this application;

[0032] Figure 4 This is a schematic diagram of the topology of the voiceprint subsystem 123 provided in the embodiments of this application;

[0033] Figure 5 This is a schematic diagram of the topology of the acoustic emission subsystem 124 provided in an embodiment of this application;

[0034] Figure 6 This is a schematic diagram of the topology of the vibration subsystem 125 provided in an embodiment of this application;

[0035] Figure 7 This is a schematic diagram of the topology of the load subsystem 126 provided in an embodiment of this application;

[0036] Figure 8 This is a schematic diagram of the topology of a wind turbine blade monitoring system provided in some other embodiments of this application. Detailed Implementation

[0037] The features and exemplary embodiments of various aspects of the present application will be described below in detail, in order to make the purposes, technical solutions and advantages of the present application more clear and apparent, the present application will be further described in detail below in combination with the drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, but not to limit the present application. For those skilled in the art, the present application can be implemented without some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by showing examples of the present application.

[0038] It should be noted that, in this paper, the relationship terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between the entities or operations. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or equipment including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or equipment. Without more limitations, the elements defined by the statement "include" do not exclude the presence of other identical elements in the process, method, article or equipment including the elements.

[0039] Before describing the technical solutions provided by the embodiments of the present application, in order to facilitate the understanding of the embodiments of the present application, the present application first specifically describes the problems existing in the prior art:

[0040] As described above, the inventors of the present application found that in the related art, when judging the health state of the blade, the monitoring system mainly collects single physical information of the blade, and judges the health state of the blade based on the single physical information. For example, the commonly used monitoring methods at present mainly include the following:

[0041] The strain information of the blade is collected by the resistance strain monitoring system, and the health state of the blade is judged based on the strain information;

[0042] The strain information of the blade is collected by the optical fiber strain monitoring system, and the health state of the blade is judged based on the strain information;

[0043] The vibration information of the blade is collected by the vibration monitoring system, and the health state of the blade is judged based on the vibration information;

[0044] The sound wave information of the blade is collected by the acoustic emission detection system, and the health state of the blade is judged based on the sound wave information;

[0045] The sound information of the blade is collected by the voiceprint detection system, and the health state of the blade is judged based on the sound information;

[0046] The SCADA data of the blade is collected by a SCADA data detection system, and the health state of the blade is determined based on the SCADA data;

[0047] The image information of the blade is collected by an infrared thermal imaging detection system, and the health state of the blade is determined based on the image information;

[0048] Or, the image information of the blade is collected by a machine vision monitoring system, and the health state of the blade is determined based on the image information.

[0049] The above monitoring methods all use a monitoring system to collect only single physical information of the blade to determine the health state of the blade of the unit, and the monitoring range of the resistance strain monitoring system is limited, and the resistance strain monitoring system is not sensitive to internal defects of the blade and has poor sensor reliability; the monitoring range of the optical fiber strain monitoring system is limited, the manufacturing process of the optical fiber strain monitoring system is complex, and quantitative diagnosis is difficult; the manufacturing process of the vibration monitoring system is complex, and the detection area of the vibration monitoring system is small; the data processing amount of the acoustic emission monitoring system is large, the number of sensor installations is large, and the mechanism is complex; the noise signal of the acoustic fingerprint monitoring system is greatly affected by the environment, and it is difficult to establish a sample library by removing noise; the SCADA data monitoring system has a large amount of data and requires high data processing capacity; the infrared thermal imaging monitoring system is sensitive to the detection environment, and there is a micro-local measurement blind area; and the data processing amount of the machine vision monitoring system is large, and the machine vision monitoring system is greatly affected by the environment and weather, and has high cost, and the monitoring range of one machine vision monitoring system is limited, and the installation of multiple machine vision monitoring systems is difficult. Therefore, the health state of the blade of the unit is determined by single physical information, which has the disadvantages of single analysis dimension and relatively one-sided judgment result.

[0050] Therefore, in order to improve the reliability of the monitoring result, the embodiment of the present application provides a wind turbine blade monitoring system and a wind turbine for monitoring the blade of the wind turbine.

[0051] Referring to Figure 1 The structure diagram of the wind turbine blade monitoring system provided by the embodiment of the present application is shown in Figure 1 The wind turbine blade monitoring system 100 includes a switch 110 and a sensor assembly 120, and the sensor assembly 120 includes at least two sensor subsystems. Each sensor subsystem can collect physical information of the blade during operation of the blade of the wind turbine, and determine the health state of the blade based on the collected physical information. Different sensor subsystems are used to collect different physical information of the blade, and determine the health state of the blade based on different physical information. The health state of the blade is used to indicate whether the blade is damaged during operation.

[0052] In some embodiments of the present application, the sensor assembly 120 includes any two of the following six sensor subsystems as shown in Figure 1 The illumination subsystem 121 collects illumination information of the blade and determines the health state of the blade based on the illumination information; the image subsystem 122 collects image information of the blade and determines the health state of the blade based on the image information; the voiceprint subsystem 123 collects voice information of the blade and determines the health state of the blade based on the voice information; the acoustic emission subsystem 124 collects acoustic wave information of the blade and determines the health state of the blade based on the acoustic wave information; the vibration subsystem 125 collects vibration information of the blade and determines the health state of the blade based on the vibration information, considering that early micro-damage of the blade is not obvious in low-frequency vibration information, the vibration information collected by the vibration subsystem 125 can include low-frequency vibration information and high-frequency vibration information; and the load subsystem 126 collects deformation information and load information of the blade and determines the health state of the blade based on the deformation information and / or the load information.

[0053] In the present embodiment, the number and type of sensor subsystems included in the sensor assembly 120 can be set according to actual needs, and two or more sensor subsystems can be included. For example, the six sensor subsystems as shown in Figure 1 may be used to detect damage of the blade at different stages, wherein the illumination subsystem 121 is suitable for detecting middle and late damage. The image subsystem 122 is suitable for detecting middle and late damage. The voiceprint subsystem 123 is suitable for detecting middle and late damage. The acoustic emission subsystem 124 is suitable for detecting early and middle damage and can detect late damage. The low-frequency vibration information of the vibration subsystem 125 is suitable for detecting middle and late damage, and the high-frequency vibration information is suitable for detecting early and middle damage. The load subsystem 126 is suitable for detecting middle and late damage. Based on this, preferably, the sensor assembly 120 can include at least one of the following sensor subsystems suitable for detecting early damage: the acoustic emission subsystem 124, the vibration subsystem 125, and at least one of the following sensor subsystems suitable for detecting middle and late damage: the illumination subsystem 121, the image subsystem 122, the voiceprint subsystem 123, and the load subsystem 126. In this way, the sensor assembly 120 can efficiently detect damage at early, middle, and late stages of the blade, and the monitoring system adaptation period is widened.

[0054] In addition, it can be understood that, in addition to the above six sensor subsystems, the sensor assembly 120 can also include other sensor subsystems capable of determining the health state of the blade, for example, a thermal imaging subsystem can also be included.

[0055] In this embodiment, each sensor subsystem includes a sensor and a data processing module connected to the sensor. The sensor is used to collect physical information inside the blade, and the data processing module is used to determine the health status of the blade based on the physical information collected by the connected sensor.

[0056] For example, such as Figure 1 As shown, the illuminance subsystem 121 includes at least one illuminance sensor 1211, and its data processing module includes a controller 1212. The illuminance sensor 1211 collects illuminance information inside the blades. Illuminance information refers to data related to the intensity of light illuminating the wind turbine blades, and can be an analog or digital signal. For example, the illuminance sensor 1211 may include, but is not limited to, photodiode sensors, photoresistor sensors, and silicon photovoltaic cells. The controller 1212 can be a monitoring cabinet controller for the wind turbine generator set. The controller 1212 has data analysis and processing capabilities, and is used to receive the illuminance information collected by at least one illuminance sensor 1211 and determine the health status of the blades based on this information.

[0057] The imaging subsystem 122 includes at least one vision sensor 1221, and its data processing module includes an image acquisition unit 1222. The vision sensor 1221 is used to acquire image information of the interior of the blade. Exemplarily, the vision sensor 1221 includes, but is not limited to, a black-and-white camera, a color camera, or other similar thermal imaging instruments. The resolution of the vision sensor 1221 is preferably greater than or equal to 20 million pixels. The image acquisition unit 1222 has data analysis and processing capabilities, used to receive image information acquired by at least one vision sensor 1221, and to determine the health status of the blade based on the image information.

[0058] The acoustic signature subsystem 123 includes at least one acoustic signature sensor 1231, and its data processing module includes an acoustic signature collector 1232. The acoustic signature sensor 1231 is used to collect sound information from inside the blade. Exemplarily, the acoustic signature sensor 1231 includes, but is not limited to, a microphone that uses an internal microphone to collect sound from the internal cavity of the blade during operation, thus obtaining sound information from inside the blade. The acoustic signature collector 1232 has data analysis and processing capabilities, used to receive sound information collected by at least one acoustic signature sensor 1231, and to determine the health status of the blade based on the sound information.

[0059] The sensor of the acoustic emission subsystem 124 includes at least one acoustic emission sensor 1241, and the data processing module of the acoustic emission subsystem 124 includes an acoustic emission collector 1242. The acoustic emission sensor 1241 is configured to collect acoustic wave information inside the blade structure. The acoustic emission collector 1242 has data analysis and processing capabilities, and is configured to receive the acoustic wave information collected by the at least one acoustic emission sensor 1241, and determine the health state of the blade based on the acoustic wave information.

[0060] The sensor of the vibration subsystem 125 includes at least one vibration sensor 1251, and the data processing module of the vibration subsystem 125 includes a vibration collector 1252. The vibration sensor 1251 is configured to collect vibration information inside the blade, which can be an analog signal or a digital signal. Exemplarily, the vibration sensor 1251 includes, but is not limited to, a dual-axis vibration acceleration sensor, a three-axis vibration acceleration sensor, etc. The vibration collector 1252 has data analysis and processing capabilities, and is configured to receive the vibration information collected by the at least one vibration sensor 1251, and determine the health state of the blade based on the vibration information. If the vibration information is an analog quantity, the vibration collector 1252 can also convert the vibration information into a digital acceleration signal.

[0061] The sensor of the load subsystem 126 includes at least one optical fiber load sensor 1261, and the data processing module of the load subsystem 126 includes a load demodulator 1262. The optical fiber load sensor 1261 is configured to collect deformation information and load information inside the blade. The load demodulator 1262 has data analysis and processing capabilities, and is configured to receive the deformation information and load information collected by the at least one optical fiber load sensor 1261, and determine the health state of the blade based on the deformation information and / or load information. When the blade is subjected to stress, the blade structure will deform, which will cause a change in the optical wavelength of the optical fiber load sensor 1261. Therefore, the deformation information and load information collected by the optical fiber load sensor 1261 can be an optical wavelength signal, and the load demodulator 1262 can demodulate and convert the optical wavelength signal into an electrical signal.

[0062] In this embodiment, the data processing module in each sensor subsystem is connected to the switch 110 through Ethernet. In this way, each sensor subsystem can interact with other devices in the wind turbine generator blade monitoring system 100 through the switch 110. The wind turbine generator blade monitoring system 100 can reduce, increase or replace sensor subsystems as needed through the switch 110, thereby improving the adaptability of the system.

[0063] The wind turbine blade monitoring system 100 provided by the embodiments of the present application can effectively improve the accuracy and reliability of blade damage detection by combining multiple sensor data to determine the health status of the blade from the functional perspective. From the system design perspective, the wind turbine blade monitoring system 100 can reduce, increase or replace sensor subsystems according to requirements, thereby improving system adaptability. From the platform construction perspective, the wind turbine blade monitoring system 100 promotes the construction and development of the blade state monitoring platform, thereby improving product creativity. From the unit safety perspective, the wind turbine blade monitoring system 100 can identify blade damage earlier, reduce blade fracture and crash accidents, and improve unit safety. From the cost perspective, the wind turbine blade monitoring system 100 greatly reduces the blade troubleshooting and unit operation and maintenance costs, thereby improving product competitiveness.

[0064] In some embodiments, referring to Figure 1 , the image collector 1222, the voiceprint collector 1232, the acoustic emission collector 1242, the vibration collector 1252 and the load demodulator 1262 are deployed based on a Linux system.

[0065] In some embodiments, the sensors and the data processing modules of each sensor subsystem can be connected through a wireless mode or a wired mode.

[0066] For example, referring to Figure 2 , the illumination sensor 1211 is in communication connection with the controller 1212 through an RS485 protocol.

[0067] Referring to Figure 3 , the visual sensor 1221 includes a network port or a WiFi connected to the image collector 1222. For example, as shown in Figure 3 , the visual sensor 1221 includes an RJ45 network port, and the image collector 1222 includes six RJ45 network ports. One of the six RJ45 network ports of the image collector 1222 is connected to the switch 110, and the other five RJ45 network ports are used to connect the visual sensor 1221. One of the five RJ45 network ports can be connected to one visual sensor 1221, so that multiple visual sensors 1221 can be simultaneously arranged in the image subsystem 122. Figure 3 In the embodiment, only one visual sensor 1221 is arranged as an example.

[0068] Referring to Figure 4 , the voiceprint sensor 1231 is connected to the voiceprint collector 1232 through a network port. As shown in Figure 4 , the voiceprint subsystem 123 includes multiple voiceprint sensors 1231. Figure 4For example, each voiceprint sensor 1231 includes two RJ45 network interfaces, and the voiceprint sensors 1231 are connected in series through the RJ45 network interfaces. The voiceprint collector 1232 includes six RJ45 network interfaces, one of which is connected to the switch 110, and the other five are used to connect the voiceprint sensors 1231. One RJ45 network interface can be connected to one voiceprint sensor 1231. Therefore, multiple voiceprint sensors 1231 can be simultaneously arranged in the voiceprint subsystem 123. Figure 4 For example, only one voiceprint sensor 1231 is arranged in the voiceprint subsystem 123.

[0069] Referring to FIG. 12, the acoustic emission sensor 1241 is connected to the acoustic emission collector 1242 through a coaxial cable. Figure 5 As shown in FIG. 12, multiple acoustic emission collectors 1242 can be connected in series in the acoustic emission subsystem 124. Figure 5 For example, two acoustic emission collectors 1242 are connected in series in the acoustic emission subsystem 124. The acoustic emission collectors 1242 are connected through RCA interfaces, and the acoustic emission collector 1242 is connected to the switch 110 through an RJ45 network interface. Figure 5 As shown in FIG. 12, multiple acoustic emission collectors 1242 can be connected in series in the acoustic emission subsystem 124. Figure 5 For example, only one acoustic emission sensor 1241 is arranged in the acoustic emission subsystem 124. Figure 5

[0070] Referring to FIG. 13, the vibration sensor 1251 is connected to the vibration collector 1252. Figure 6 Referring to FIG. 14, the optical fiber load sensor 1261 is connected to the optical port of the load demodulator 1262.

[0071] Figure 7 In some embodiments, the physical information collected by the sensor can be stored in the data processing module connected to the sensor.

[0072] For example, the controller 1212 reads the light intensity information collected by the light intensity sensor 1211 at intervals, and records the read light intensity information in the controller 1212 in txt format.

[0073] For example, the controller 1212 reads the light intensity information collected by the light intensity sensor 1211 at intervals, and records the read light intensity information in the controller 1212 in txt format.

[0074] The image information collected by the visual sensor 1221 is stored in the image collector 1222 in jpg format.

[0075] ​​The voiceprint information collected by the voiceprint sensor 1231 is stored in the voiceprint collector 1232 in the wav format.

[0076] The acoustic emission information collected by the acoustic emission sensor 1241 is stored in the acoustic emission collector 1242 in the tdms format.

[0077] The vibration sensor 1251 can collect the vibration information in the low frequency band and the vibration information in the high frequency band at the same time, considering that the early slight damage of the blade is not reflected in the vibration information in the low frequency band. The vibration information in the high frequency band collected by the vibration sensor 1251 can be stored in the vibration collector 1252.

[0078] By storing the collected physical information in the data processing module, it is convenient to view the physical information subsequently.

[0079] In some embodiments, a warning model can be deployed in the data processing module, and the data processing module judges the health state of the blade by using the warning model. The warning model includes but is not limited to a single-blade change trend model and a three-blade consistency model. The single-blade change trend model refers to comparing the current physical information of the blade with the physical information of the blade in the initial health state, and judging whether the blade is damaged based on the difference of the physical information of the blade in different time dimensions. The three-blade consistency model refers to comparing the current physical information of the target blade with the current physical information of other blades in the same wind turbine generator unit, and judging whether the target blade is damaged based on the difference between different blades. The target blade is any blade in the wind turbine generator unit.

[0080] For example, a light intensity warning model is deployed in the controller 1212. The single-blade change trend model in the light intensity warning model compares the current light intensity information of the blade with the light intensity information of the blade in the initial health state, and judges whether the blade is damaged based on the difference between the current light intensity information of the blade and the light intensity information in the initial health state. The three-blade consistency model in the light intensity warning model compares the current light intensity information of the blade to be monitored with the current light intensity information of other blades in the same wind turbine generator unit, and judges whether the target blade is damaged based on the difference between the current light intensity information of the blade to be monitored and the current light intensity information of other blades in the same wind turbine generator unit.

[0081] The image collector 1222 internally deploys an image early warning model. A single-blade change trend model in the image early warning model compares current image information of a blade with image information of the blade in an initial healthy state, and determines whether the blade is damaged based on a difference between the current image information of the blade and the image information of the blade in the initial healthy state; a three-blade consistency model in the image early warning model compares current image information of a to-be-monitored blade with current image information of other blades in the same wind turbine generator unit, and determines whether the target blade is damaged based on a difference between the current image information of the to-be-monitored blade and the current image information of the other blades in the same wind turbine generator unit.

[0082] The voiceprint collector 1232 internally deploys a voiceprint early warning model. A single-blade change trend model in the voiceprint early warning model compares current voice information of a blade with voice information of the blade in an initial healthy state, and determines whether the blade is damaged based on a difference between the current voice information of the blade and the voice information of the blade in the initial healthy state; a three-blade consistency model in the voiceprint early warning model compares current voice information of a to-be-monitored blade with current voice information of other blades in the same wind turbine generator unit, and determines whether the target blade is damaged based on a difference between the current voice information of the to-be-monitored blade and the current voice information of the other blades in the same wind turbine generator unit.

[0083] The acoustic emission collector 1242 internally deploys an acoustic emission early warning model. A single-blade change trend model in the acoustic emission early warning model compares current acoustic wave information of a blade with acoustic wave information of the blade in an initial healthy state, and determines whether the blade is damaged based on a difference between the current acoustic wave information of the blade and the acoustic wave information of the blade in the initial healthy state; a three-blade consistency model in the acoustic emission early warning model compares current acoustic wave information of a to-be-monitored blade with current acoustic wave information of other blades in the same wind turbine generator unit, and determines whether the target blade is damaged based on a difference between the current acoustic wave information of the to-be-monitored blade and the current acoustic wave information of the other blades in the same wind turbine generator unit.

[0084] The vibration collector 1252 internally deploys a vibration early warning model. A single-blade change trend model in the vibration early warning model compares current vibration information of a blade with vibration information of the blade in an initial healthy state, and determines whether the blade is damaged based on a difference between the current vibration information of the blade and the vibration information of the blade in the initial healthy state; a three-blade consistency model in the vibration early warning model compares current vibration information of a to-be-monitored blade with current vibration information of other blades in the same wind turbine generator unit, and determines whether the target blade is damaged based on a difference between the current vibration information of the to-be-monitored blade and the current vibration information of the other blades in the same wind turbine generator unit.

[0085] The load demodulator 1262 internally deploys a load early warning model. The single-blade change trend model in the load early warning model compares the current deformation information and / or load information of the blade with the deformation information and / or load information of the blade in the initial healthy state, and determines whether the blade is damaged based on the difference between the current deformation information and / or load information of the blade and the deformation information and / or load information in the initial healthy state; the three-blade consistency model compares the current deformation information and / or load information of the blade to be monitored with the current deformation information and / or load information of other blades in the same wind turbine generator set, and determines whether the target blade is damaged based on the difference between the current deformation information and / or load information of the blade to be monitored and the current deformation information and / or load information of other blades in the same wind turbine generator set.

[0086] In the above manner, the data processing module can determine the health status of the blade through the deployed model, thereby improving the accuracy of the determination result. In addition, the three-blade consistency early warning model can solve the problem of inaccurate diagnosis conclusion caused by only focusing on the change of a single blade feature parameter, and make up for the deficiency of the single-blade early warning model.

[0087] In some embodiments, the acoustic emission subsystem 124 includes a plurality of array-deployed acoustic emission sensors 1241, and the acoustic emission collector 1242 can also use an acoustic emission early warning model to locate the damage position of the blade from the perspective of acoustic wave information in combination with the working condition data of the wind turbine generator set.

[0088] In some embodiments, the data processing module can also compare the received physical information with a preset threshold value, and determine that the blade may be damaged when the physical information exceeds the set threshold value.

[0089] In some embodiments, each sensor subsystem can also include a lightning protection box, which can reduce the risk of lightning strikes and thereby improve the safety of the wind turbine generator blade monitoring system 100. The lightning protection box can be integrated in the sensor of the sensor subsystem, or can be arranged between the sensor and the data processing module. For example, as shown in Figure 6 The lightning protection box 1253 in the vibration subsystem 125 is arranged between the vibration sensor 1251 and the vibration collector 1252.

[0090] In some embodiments, the data processing module in each sensor subsystem can increase the local storage capacity by adding an SD card or mounting a hard disk, etc. For example, as shown in Figure 5 The acoustic emission subsystem 124 includes a hard disk 1243, which is connected to the acoustic emission collector 1242 through a USB interface.

[0091] In some embodiments, a signal amplifier can also be arranged between the acoustic emission sensor 1241 and the acoustic emission collector 1242. The acoustic wave information collected by the acoustic emission sensor 1241 is transmitted to the acoustic emission collector 1242 after being amplified by the signal amplifier. In this way, the signal strength of the acoustic wave information can be improved. The signal amplifier and the acoustic emission collector 1242 can also have multiple channels, which can simultaneously connect multiple acoustic emission sensors 1241.

[0092] In some embodiments, referring to Figure 8 , the switch 110 is connected to the main control system 200 of the wind turbine to which the blade belongs through Ethernet. In this way, the wind turbine blade monitoring system 100 can interact with the main control system 200 of the wind turbine, and the main control system 200 can optionally require the data processing module to pre-process the physical information collected by the sensor. The main control system 200 can optionally receive the physical information collected by the sensor subsystem, and the main control system 200 can obtain the physical information and / or analysis results collected by multiple sensor subsystems. Thus, relying on the computing power of the main control system 200, the information transmitted by the sensor subsystem and the operating condition data of the wind turbine can be combined to analyze and determine the health status of the blade as a whole through multi-data fusion. The operating condition data includes but is not limited to wind direction, wind speed, impeller speed, yaw state, blade angle, and active power of the wind turbine, etc. In this way, the operating condition data of the wind turbine can be effectively utilized to further improve the reliability of the blade health status monitoring. In addition, the wind turbine blade monitoring system 100 can also modify the internal time of the data processing module in each sensor subsystem based on the time of the central control system or the main control system 200, thereby improving the synchronization of data collection and reducing the difficulty of analysis.

[0093] In some embodiments, the wind turbine blade monitoring system 100 includes a controller 1212, referring to Figure 8 , the controller 1212 is connected to the main control system 200 of the wind turbine to which the blade belongs through a field bus. In this way, the controller 1212 can be synchronized with the central control system or the main control system 200, and serve as a time server for each device in the wind turbine blade monitoring system 100. The field bus includes but is not limited to CANopen, Profibus_DP, EtherCAT, Powerlink, and other bus types.

[0094] In some embodiments, the sensor assembly 120 includes a vibration subsystem 125, referring to Figure 8The vibration collector 1252 in the vibration subsystem 125 is connected with the controller 1212 through a field bus. In this way, the vibration collector 1252 can forward the sampled vibration information to the host system 200 through the controller 1212, and the host system 200 receives and saves the vibration information. In this way, the vibration information can be stored in the host system 200 and locally in the vibration collector 1252. The field bus includes but is not limited to CANopen, Profibus_DP, EtherCAT, Powerlink, and other bus types.

[0095] In some embodiments, the sensor assembly 120 includes a load subsystem 126, referring to Figure 8 The load demodulator 1262 in the load subsystem 126 is connected with the controller 1212 through a field bus. In this way, the load demodulator 1262 can forward the sampled deformation information and load information to the host system 200 through the controller 1212, and the host system 200 receives and saves the deformation information and load information. In this way, the deformation information and load information can be stored in the host system 200 and locally in the load demodulator 1262. The field bus includes but is not limited to CANopen, Profibus_DP, EtherCAT, Powerlink, and other bus types.

[0096] In some embodiments, referring to Figure 8 The wind turbine blade monitoring system 100 further includes an industrial computer 130. The industrial computer 130 is connected with the switch 110 through Ethernet. The industrial computer 130 can be a remote maintenance system including functions such as upgrading firmware and modifying parameters, and the data processing module can view and modify the configuration system parameters through the page tool of the industrial computer 130. In addition, the industrial computer 130 can also upload specified data to the cloud platform.

[0097] In some embodiments, referring to Figure 8 The wind turbine blade monitoring system 100 further includes a router 140 connected with the industrial computer 130, which is used to provide wired or wireless network for the industrial computer 130. The router 140 can include multiple network interfaces.

[0098] In some embodiments, referring to Figure 8 The industrial computer 130 is further connected with a remote maintenance device 300. The remote maintenance device 300 can be a personal computer, and the industrial computer 130 can be controlled through the remote maintenance device 300 to realize remote maintenance of the wind turbine blade monitoring system 100.

[0099] In some embodiments, the sensors in the wind turbine blade monitoring system 100 are arranged in the inner cavity of the blade, and devices other than the sensors, such as the data processing module, the switch 110, the industrial computer 130, and the router 140, can be arranged in the monitoring cabinet of the wind turbine.

[0100] For example, the light intensity sensor 1211 is fixed in the inner cavity of the blade by pressing with a bracket. Depending on the monitoring area, the light intensity sensor 1211 can be installed at the windward surface, the leeward surface, or the web.

[0101] The bottom of the visual sensor 1221 contains a mounting bracket, and the visual sensor 1221 is installed in the inner cavity of the blade through the mounting bracket at the bottom. Depending on the monitoring area, the visual sensor 1221 can be installed at the root baffle, the windward surface, the leeward surface, or the web through the mounting bracket at the bottom.

[0102] The acoustic emission sensor 1241 is fixed in the inner cavity of the blade by pressing with a bracket. Depending on the monitoring area, the acoustic emission sensor 1241 can be installed at the windward surface, the leeward surface, or the web.

[0103] The bottom of the visual sensor 1221 contains a mounting bracket, and the visual sensor 1221 is installed in the inner cavity of the blade through the mounting bracket at the bottom. Depending on the monitoring area, the visual sensor 1221 can be installed at the root baffle, the windward surface, the leeward surface, or the web through the mounting bracket at the bottom.

[0104] The optical fiber load sensor 1261 is installed at the middle of the inner cavity of the blade or at the root position of the blade. Depending on the monitoring area, the optical fiber load sensor 1261 can be installed at the windward surface, the leeward surface, or the web.

[0105] By arranging the sensors in the inner cavity of the blade, the influence of the external environment on the sensors can be reduced, the service life of the sensors can be prolonged, the interference of the external environment on the information collected by the sensors can be reduced, the accuracy of the information collected by the sensors can be improved, and the sensors arranged in the inner cavity of the blade do not need to be punched on the outside of the blade, and the wiring is also simpler. In addition, by arranging the devices other than the sensors in the monitoring cabinet, subsequent maintenance and management can be facilitated.

[0106] Based on the wind turbine blade monitoring system provided in the above embodiments, correspondingly, the application also provides a specific implementation mode of the wind turbine.

[0107] The wind turbine provided in the embodiments of the application comprises a blade and the wind turbine blade monitoring system 100 provided in any of the above embodiments.

[0108] The wind turbine provided in the embodiments of the application can realize Figures 1 to 8The various processes implemented by the wind turbine blade monitoring system 100 embodiment of the present application are not repeated here to avoid redundancy.

[0109] The above describes only a specific implementation of the present application. For the convenience and brevity of description, the specific working processes of the above-described system, module, and unit can refer to the corresponding processes in the foregoing method embodiments, which will not be repeated here. It should be understood that the protection scope of the present application is not limited in this way. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical range disclosed by the present application, and these modifications or replacements should be covered within the protection scope of the present application.

Claims

1. A wind turbine blade monitoring system, characterized in that, The wind turbine blade monitoring system comprises: a switch and at least two sensor subsystems; each of the sensor subsystems comprises a sensor and a data processing module connected to the sensor, the sensor collects physical information inside the blade, and the data processing module determines the health status of the blade based on the physical information collected by the sensor connected thereto, and the sensors in different sensor subsystems collect different physical information; the data processing module in each of the sensor subsystems is connected to the switch through Ethernet.

2. The system of claim 1, wherein, The switch is connected to the main control system of the wind turbine to which the blade belongs through Ethernet.

3. The system of claim 1, wherein, The at least two sensor subsystems comprise at least two of the following sensor subsystems: an illumination subsystem, an image subsystem, a voiceprint subsystem, a sound emission subsystem, a vibration subsystem, and a load subsystem; the sensor of the illumination subsystem comprises an illumination sensor, and the data processing module of the illumination subsystem comprises a controller; the sensor of the image subsystem comprises a visual sensor, and the data processing module of the image subsystem comprises an image collector; the sensor of the voiceprint subsystem comprises a voiceprint sensor, and the data processing module of the voiceprint subsystem comprises a voiceprint collector; the sensor of the sound emission subsystem comprises a sound emission sensor, and the data processing module of the sound emission subsystem comprises a sound emission collector; the sensor of the vibration subsystem comprises a vibration sensor, and the data processing module of the vibration subsystem comprises a vibration collector; the sensor of the load subsystem comprises an optical fiber load sensor, and the data processing module of the load subsystem comprises a load demodulator.

4. The system of claim 3, wherein, The at least two sensor subsystems comprise a controller; The controller is connected to the main control system of the wind turbine to which the blade belongs through a field bus.

5. The system of claim 4, wherein, The at least two sensor subsystems further comprise the vibration subsystem; The vibration collector is connected to the controller through a field bus.

6. The system of claim 4, wherein, The at least two sensor subsystems further comprise the load subsystem; The load demodulator is connected to the controller through a field bus.

7. The system of any of claims 1-6, wherein, The wind turbine blade monitoring system further comprises an industrial computer; The industrial computer is connected to the switch through Ethernet.

8. The system of claim 7, wherein, The wind turbine blade monitoring system further comprises a router, and the router is connected to the industrial computer.

9. The system of claim 7, wherein, The industrial computer is connected to a remote maintenance device.

10. A wind power unit, characterized in that The wind turbine blade monitoring system comprises a blade and the wind turbine blade monitoring system according to any one of claims 1-9.

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