Fault early warning method and device for yaw system of wind turbine generator set

Abstract

The invention provides a fault early warning method and device for a yaw system of a wind power generator set, and the method comprises the steps: monitoring the real-time data of the yaw system of the wind power generator set, the real-time data comprises effective output power and incoming flow wind speed, and the incoming flow wind speed comprises the average incoming flow wind speed at the effective output power and the average incoming flow wind speed at the rated power; inputting the effective output power, the average incoming flow wind speed at the effective output power and the average incoming flow wind speed at the rated power to a pre-constructed fault recognition model, and outputting a fault recognition result; based on the fault identification result, performing fault early warning; the early warning is carried out through the fault identification model, so that the timeliness of fault early warning is effectively ensured, corresponding prevention and maintenance can be adopted in the fault incubation period, the safety of the yaw system is ensured, and the fault early warning model is determined by various data, so that the accuracy of fault early warning is further improved.

Description

Technical Field

[0001] The present invention relates to the technical field of fault warning, and in particular to a method and device for warning fault of a yaw system of a wind turbine generator set. Background Art

[0002] The yaw system, also known as the wind pointing device, is a part of the nacelle of a wind turbine. Its main function is to quickly and smoothly adjust the wind turbine to align it with the wind direction when the direction of the wind speed vector changes, so that the wind rotor can obtain the maximum wind energy. The yaw system usually includes a wind vane that senses the wind direction and an actuator for the yaw system. The design of the yaw system needs to consider the structural form, cable unwinding and cable twisting protection, yaw speed, yaw damping, azimuth detection and technical requirements of major components. The yaw system is an important subsystem in a wind turbine generator set and is crucial to improving the efficiency and performance of a wind turbine generator set.

[0003] A yaw system failure may cause the wind turbine to be unable to properly align with the wind direction, thereby reducing the wind energy received by the wind rotor and reducing power generation efficiency. A yaw system failure may cause the wind turbine to shut down and wait for maintenance, which will extend the downtime and reduce power generation.

[0004] Therefore, how to timely and accurately provide fault warning for the status of the yaw system has become a technical problem that technical personnel in this field need to solve urgently. Summary of the invention

[0005] The present invention provides a method and device for early warning of a yaw system fault of a wind turbine generator set, which are used to solve the defect of poor accuracy of early warning of a yaw system fault in the prior art.

[0006] In a first aspect, the present invention provides a method for early warning of a yaw system fault of a wind turbine generator set, comprising:

[0007] Monitor the real-time data of the yaw system of the wind turbine generator set, the real-time data including the effective output power and the incoming wind speed, the incoming wind speed including the average incoming wind speed at the effective output power and the average incoming wind speed at the rated power;

[0008] Inputting the effective output power, the average wind speed at the effective output power, and the average wind speed at the rated power into a pre-built fault identification model, and outputting a fault identification result;

[0009] Based on the fault identification result, a fault warning is performed;

[0010] Wherein, the fault identification model is:

[0011]

[0012] Where V represents the fault identification result, and its value range is (0,1); P represents the effective output power, P0 is the rated power of the wind turbine, Indicates the average incoming wind speed when the effective output power is Indicates the average incoming wind speed at rated power.

[0013] According to a wind turbine generator set yaw system fault early warning method provided by the present invention, the effective output power of the wind turbine generator set is monitored in the following manner:

[0014]

[0015] The rated power of the wind turbine generator set is monitored in the following manner:

[0016]

[0017] Where ρ is the air density under standard atmospheric pressure, r is the radius of the wind turbine impeller, C p is the wind energy utilization coefficient under normal operating conditions, and θ is the angle between the wind direction and the nacelle position.

[0018] According to a wind turbine generator set yaw system fault warning method provided by the present invention, the fault warning is performed based on the fault identification result, including:

[0019] If the fault identification result is a fault, performing a first classification on the fault identification result to determine a first fault type, wherein the first fault type includes an actuator fault of a yaw system and a wind vane fault;

[0020] Fault warnings are respectively performed based on the actuator failure and the wind vane failure.

[0021] According to a fault warning method for a yaw system of a wind turbine generator set provided by the present invention, performing a first classification on the fault identification result to determine a first fault type includes:

[0022] Acquire first wind direction data of a wind vane of a yaw system of a wind turbine generator set in a first period of time, and construct a first wind direction sequence;

[0023] Acquire second wind direction data of the wind direction of the wind farm during the first period of time, and construct a second wind direction sequence;

[0024] Determining a similarity value between the first wind direction sequence and the second wind direction sequence;

[0025] If the similarity value is greater than or equal to the similarity threshold, determining that the first fault type is an actuator fault of the yaw system;

[0026] If the similarity value is less than the similarity threshold, it is determined that the first fault type is a wind vane fault.

[0027] A wind turbine generator set yaw system fault early warning method according to the present invention also includes:

[0028] If the first fault type is an actuator fault of the yaw system, a second classification is performed on the actuator fault of the yaw system to determine a second fault type; the second fault type includes a transmission system fault and a positioning system fault;

[0029] Based on the transmission system failure and positioning system failure, a fault warning is performed.

[0030] According to a wind turbine generator set yaw system fault early warning method provided by the present invention, the transmission system fault is identified by the following formula:

[0031]

[0032] Among them, i' represents the calculated transmission ratio, i represents the designed transmission ratio, ω in represents the angular velocity at the input of the transmission system, ω out represents the angular velocity at the output end of the transmission system, T out Represents the torque at the output end of the transmission system, J out represents the moment of inertia of the output end of the transmission system, α out Represents the angular acceleration at the output of the transmission system.

[0033] A wind turbine generator set yaw system fault early warning method according to the present invention also includes:

[0034] Acquire historical data of the yaw system of the wind turbine generator set, wherein the historical data includes a design transmission ratio of the transmission system, and an angular acceleration of an output end of the transmission system during normal operation and abnormal operation of the transmission system;

[0035] According to the angular acceleration of the output end of the transmission system during normal operation and abnormal operation of the transmission system, an angular acceleration fault threshold of the output end of the transmission system is set;

[0036] Compare the calculated transmission ratio with the designed transmission ratio. If they are different, the transmission system is faulty.

[0037] If they are the same, determining the relationship between the angular acceleration at the output end of the transmission system and the angular acceleration fault threshold at the output end of the transmission system;

[0038] If the calculated angular acceleration at the output of the transmission system is outside the angular acceleration fault threshold at the output of the transmission system, the transmission system is faulty.

[0039] According to a wind turbine generator set yaw system fault early warning method provided by the present invention, the positioning system fault is identified by the following formula:

[0040]

[0041] Among them, G(s) represents the transfer function of the positioning system, K represents the feedback coefficient of the positioning system, which represents the proportional relationship between the output signal and the input signal, Γ represents the feedback filter time constant, and s represents the complex variable in the Laplace transform.

[0042] A wind turbine generator set yaw system fault early warning method according to the present invention also includes:

[0043] Acquire historical data of the yaw system of the wind turbine generator set, wherein the historical data includes historical amplitude-frequency characteristics of the positioning system;

[0044] Calculate the amplitude-frequency characteristics of the real-time positioning system of the positioning system;

[0045] The historical amplitude-frequency characteristics of the positioning system and the amplitude-frequency characteristics of the real-time positioning system are compared. If the two do not match, the positioning system fails.

[0046] In a second aspect, the present invention further provides a fault warning device for a yaw system of a wind turbine generator set, comprising:

[0047] A detection module, used to monitor the real-time data of the yaw system of the wind turbine generator set, wherein the real-time data includes the effective output power and the incoming wind speed, wherein the incoming wind speed includes the average incoming wind speed at the effective output power and the average incoming wind speed at the rated power;

[0048] An identification module, used for inputting the effective output power, the average wind speed at the effective output power and the average wind speed at the rated power into a pre-built fault identification model, and outputting a fault identification result;

[0049] An early warning module, used for providing a fault early warning based on the fault identification result;

[0050] Wherein, the fault identification model is:

[0051]

[0052] Where V represents the fault identification result, and its value range is (0,1); P represents the effective output power, P0 is the rated power of the wind turbine, Indicates the average incoming wind speed when the effective output power is Indicates the average incoming wind speed at rated power.

[0053] In a third aspect, the present invention further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a fault warning method for the yaw system of a wind turbine generator set as described above is implemented.

[0054] In a fourth aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the wind turbine generator set yaw system fault warning method as described in any one of the above is implemented.

[0055] In a fifth aspect, the present invention further provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements any of the above-mentioned wind turbine generator set yaw system fault warning methods.

[0056] The present invention provides a fault warning method and device for a yaw system of a wind turbine generator set. The method comprises: monitoring real-time data of the yaw system of the wind turbine generator set, the real-time data comprising effective output power and incoming wind speed, the incoming wind speed comprising an average incoming wind speed at effective output power and an average incoming wind speed at rated power; inputting the effective output power, the average incoming wind speed at effective output power and the average incoming wind speed at rated power into a pre-constructed fault identification model, and outputting a fault identification result; performing a fault warning based on the fault identification result; since a warning is performed through the fault identification model, the timeliness of the fault warning is effectively guaranteed, corresponding preventive maintenance can be taken during the fault latent period, thereby ensuring the safety of the yaw system, and the fault warning model is determined by a variety of data, thereby further improving the accuracy of the fault warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0058] Figure 1 is a schematic flow chart of a fault warning method for a yaw system of a wind turbine generator set provided in this embodiment;

[0059] Figure 2 is a schematic structural diagram of a fault warning device for a yaw system of a wind turbine generator set provided in this embodiment;

[0060] Figure 3 It is a schematic diagram of the structure of the electronic device provided in this embodiment. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0062] Figure 1 It is a flow chart of the fault warning method of the yaw system of the wind turbine generator set provided in this embodiment.

[0063] like Figure 1 As shown, the wind turbine generator set yaw system fault warning method provided by the embodiment of the present invention mainly includes the following steps:

[0064] 101. Monitor the real-time data of the yaw system of the wind turbine generator set. The real-time data includes the effective output power and the incoming wind speed. The incoming wind speed includes the average incoming wind speed at the effective output power and the average incoming wind speed at the rated power.

[0065] In a specific implementation process, the yaw system is an important component of a wind turbine generator set. Its function is to control the nacelle of the wind turbine generator set so that it can automatically adjust its direction according to the change of wind direction to maximize the capture of wind energy. The yaw system includes a wind vane and an actuator, and the actuator includes at least a transmission system and a positioning system.

[0066] The monitoring method of the effective output power of the wind turbine generator set is formula (1):

[0067]

[0068] The monitoring method of the rated power of the wind turbine generator set is formula (2):

[0069]

[0070] Where ρ is the air density under standard atmospheric pressure, r is the radius of the wind turbine impeller, C p is the wind energy utilization coefficient under normal operating conditions, and θ is the angle between the wind direction and the nacelle position.

[0071] The incoming wind speed may be acquired by using a sensor.

[0072] 102. Input the effective output power, the average wind speed at the effective output power, and the average wind speed at the rated power into a pre-built fault identification model, and output the fault identification result.

[0073] The fault identification model is formula (3):

[0074]

[0075] Where V represents the fault identification result, and its value range is (0,1); P represents the effective output power, P0 is the rated power of the wind turbine, Indicates the average incoming wind speed when the effective output power is Indicates the average incoming wind speed at rated power.

[0076] When there is no fault in the yaw system, V=0; when a serious fault occurs in the yaw system, V=1. Therefore, the size of V reflects the degree of fault in the yaw system. Therefore, in order to accurately determine whether there is a fault, a fault threshold of the fault identification model can be set; if the output result of the fault identification model is greater than the fault threshold of the fault identification model, it is judged as a fault; if the output result of the fault identification model is less than or equal to the fault threshold of the fault identification model, it is judged as not a fault.

[0077] In this embodiment, the setting is performed by obtaining historical data of the yaw system of the wind turbine generator set, for example, the fault threshold of the fault identification model is set to 0.2. By setting the fault threshold of the fault identification model, the model can give a clear fault judgment, that is, if it is greater than 0.2, it is considered a fault, and if it is less than or equal to 0.2, it is normal. The model outputs the probability of a fault occurring, which provides a quantitative measure for assessing the risk of a fault. The fault threshold of the fault identification model can be adjusted according to the actual situation to balance the underreporting and false alarm rates.

[0078] 103. Based on the fault identification results, a fault warning is issued.

[0079] By comparing the output value of the fault identification model with the fault threshold of the fault identification model, it is accurately determined whether a fault has occurred. If the fault identification result is a fault, the fault identification result is first classified to determine the first fault type, which includes the actuator fault and the wind vane fault of the yaw system; it is identified whether the fault belongs to the actuator of the yaw system or the wind vane, which helps to narrow the scope of troubleshooting. Then, based on the actuator fault and the wind vane fault, fault warnings are performed respectively. The actuator fault may involve the reduction transmission device and positioning device of the yaw system. The wind vane is an important part of the yaw system, which is used to detect the wind direction and adjust the direction of the wind turbine accordingly to capture more wind energy. Different fault types can adopt different alarm methods to intuitively and quickly prompt relevant personnel that a fault has occurred.

[0080] In this embodiment, since early warning is carried out through the fault identification model, the timeliness of the fault early warning is effectively guaranteed, and corresponding preventive maintenance can be taken during the fault latent period, thereby ensuring the safety of the yaw system. In addition, the fault early warning model is determined by multiple data, which further improves the accuracy of the fault early warning.

[0081] Further, on the basis of the above embodiments, the fault identification results in this embodiment are subjected to a first classification to determine a first fault type, including: obtaining first wind direction data of a wind vane of a yaw system of a wind turbine generator set in a first period of time, and constructing a first wind direction sequence; obtaining second wind direction data of a wind farm in a first period of time, and constructing a second wind direction sequence, wherein each wind farm includes a plurality of wind turbine generator sets; real-time data of the wind direction of the wind farm can be obtained by installing a meteorological station in the wind farm, equipped with an anemometer and a wind vane, which can monitor the wind speed and wind direction in real time and transmit the data to a control center; and wind direction and wind speed information of the area where the wind farm is located can also be obtained through satellite remote sensing technology.

[0082] Determine a similarity value between the first wind direction sequence and the second wind direction sequence; if the similarity value is greater than or equal to a similarity threshold, determine that the first fault type is an actuator fault of the yaw system; if the similarity value is less than the similarity threshold, determine that the first fault type is a wind vane fault.

[0083] The similarity is calculated using formulas (4), (5), (6), and (7):

[0084]

[0085] F AV (l)~l α (5)

[0086] Among them, α is the similarity value, and the value range of α is (0,1).

[0087]

[0088] Among them, D A (i) is the wind vane sequence, D V (i) is the wind farm sequence, d A (l) is the cumulative sequence of wind vane, d V (l) is the accumulated sequence of wind vane; l is the sampling step, l = 1, 2, ..., N; represents the mean of the weather vane sequence, represents the mean of the wind farm series.

[0089] For example, the similarity threshold can be set to 0.5. If the similarity value is greater than or equal to 0.5, the fault type is an actuator fault of the yaw system; if the similarity value is less than 0.5, the fault type is a wind vane fault. The larger the similarity value, the higher the possibility of an actuator fault of the yaw system.

[0090] Furthermore, if the first fault type is an actuator fault of the yaw system, a second classification is performed on the actuator fault of the yaw system to determine a second fault type; the second fault type includes a transmission system fault and a positioning system fault; and a fault warning is performed based on the transmission system fault and the positioning system fault.

[0091] The transmission system fault is identified by the following formula (8):

[0092]

[0093] Among them, i' represents the calculated transmission ratio, i represents the designed transmission ratio, ω in represents the angular velocity at the input of the transmission system, ω out represents the angular velocity at the output end of the transmission system, T out Represents the torque at the output end of the transmission system, J out represents the moment of inertia of the output end of the transmission system, α out Represents the angular acceleration at the output of the transmission system.

[0094] The specific judgment steps are:

[0095] Obtain historical data of the yaw system of the wind turbine generator set, the historical data including the design transmission ratio of the transmission system, and the angular acceleration of the output end of the transmission system during normal operation and abnormal operation of the transmission system;

[0096] According to the angular acceleration of the output end of the transmission system during normal operation and abnormal operation of the transmission system, an angular acceleration fault threshold of the output end of the transmission system is set;

[0097] Compare the calculated transmission ratio with the designed transmission ratio. If they are different, the transmission system is faulty.

[0098] If they are the same, determining the relationship between the angular acceleration at the output end of the transmission system and the angular acceleration fault threshold at the output end of the transmission system;

[0099] If the calculated angular acceleration of the transmission system output end is outside the angular acceleration fault threshold of the transmission system output end, the transmission system is faulty; if the calculated angular acceleration of the transmission system output end is within the angular acceleration fault threshold of the transmission system output end, the transmission system is not faulty.

[0100] Positioning system failure is identified by the following formula (9):

[0101]

[0102] Among them, G(s) represents the transfer function of the positioning system, K represents the feedback coefficient of the positioning system, which represents the proportional relationship between the output signal and the input signal, Γ represents the feedback filter time constant, and s represents the complex variable in the Laplace transform.

[0103] The judgment steps are:

[0104] Obtain historical data of the yaw system of the wind turbine generator set, including the historical amplitude-frequency characteristics of the positioning system;

[0105] Calculate the amplitude-frequency characteristics of the real-time positioning system of the positioning system, that is, the modulus |G(s)| of the positioning system G(s);

[0106] Compare the historical amplitude-frequency characteristics of the positioning system with the amplitude-frequency characteristics of the real-time positioning system. If the two do not match, the positioning system is faulty. If the two match, the positioning system is not faulty.

[0107] s is a complex variable in the Laplace domain and is expressed as Indicates that the positioning system is The response of the input signal is obtained by analyzing the frequency response of the positioning system transfer function to obtain the response of the positioning system to different frequency inputs. Model It indicates the amplitude-frequency characteristic of the system gain, that is, the gain amplitude at different frequencies. If the amplitude-frequency characteristic of the positioning system does not match the preset one, it indicates that there is a fault in the positioning system.

[0108] The present invention improves the accuracy of early warning by constructing a fault identification model. By early identifying potential faults, preventive maintenance measures can be taken to avoid expensive emergency repairs, thereby reducing maintenance costs. Furthermore, the real-time data of the yaw system of the wind turbine generator set is used for fault identification. The fault model calculation is simple. Because the yaw mechanism has many structures, the fault identification model of this embodiment is used to reduce the calculation amount of the first step of fault identification. After identifying whether there is a fault, the fault type is classified. When classifying the fault, the first classification is first performed to determine whether it is an actuator fault of the yaw system or a wind vane fault. Because the structure of the actuator is relatively complex, it is first determined whether it is a wind vane fault. If so, there is no need to perform the next step of fault classification, reducing the calculation amount and improving the efficiency of fault identification. Furthermore, if it is an actuator fault, the actuator fault is also classified in the second classification, which can provide more specific fault information for operation and maintenance personnel, so that they can take targeted maintenance measures.

[0109] Based on the same general inventive concept, the present invention also protects a wind turbine generator set yaw system fault warning device. The wind turbine generator set yaw system fault warning device provided by the present invention is described below. The XX device described below and the wind turbine generator set yaw system fault warning method described above can be referenced to each other.

[0110] Figure 2 It is a structural schematic diagram of a fault warning device for a yaw system of a wind turbine generator set provided in this embodiment.

[0111] like Figure 2 As shown, this embodiment provides a wind turbine generator set yaw system fault warning device, comprising:

[0112] The detection module 201 is used to monitor the real-time data of the yaw system of the wind turbine generator set, the real-time data includes the effective output power and the incoming wind speed, the incoming wind speed includes the average incoming wind speed at the effective output power and the average incoming wind speed at the rated power;

[0113] The identification module 202 is used to input the effective output power, the average wind speed at the effective output power and the average wind speed at the rated power into a pre-built fault identification model, and output a fault identification result;

[0114] The early warning module 203 is used to provide early warning of faults based on the fault identification result;

[0115] Among them, the fault identification model is:

[0116]

[0117] Where V represents the fault identification result, and its value range is (0,1); P represents the effective output power, P0 is the rated power of the wind turbine, Indicates the average incoming wind speed when the effective output power is Indicates the average incoming wind speed at rated power.

[0118] Figure 3 It is a schematic diagram of the structure of the electronic device provided in this embodiment.

[0119] like Figure 3 As shown, the electronic device may include: a processor 310, a communication interface 320, a memory 330 and a communication bus 340, wherein the processor 310, the communication interface 320 and the memory 330 communicate with each other through the communication bus 340. The processor 310 may call the logic instructions in the memory 330 to execute the fault warning method of the yaw system of the wind turbine generator set, the method comprising: monitoring the real-time data of the yaw system of the wind turbine generator set, the real-time data comprising the effective output power and the incoming wind speed, the incoming wind speed comprising the average incoming wind speed at the effective output power and the average incoming wind speed at the rated power; inputting the effective output power, the average incoming wind speed at the effective output power and the average incoming wind speed at the rated power into a pre-built fault identification model, outputting a fault identification result; and performing a fault warning based on the fault identification result.

[0120] In addition, the logic instructions in the above-mentioned memory 330 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0121] On the other hand, the present invention also provides a computer program product, which includes a computer program, and the computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the wind turbine generator set yaw system fault warning method provided by the above methods, and the method includes: monitoring real-time data of the wind turbine generator set yaw system, the real-time data including effective output power and incoming wind speed, the incoming wind speed including the average incoming wind speed at effective output power and the average incoming wind speed at rated power; inputting the effective output power, the average incoming wind speed at the effective output power, and the average incoming wind speed at the rated power into a pre-constructed fault identification model, and outputting a fault identification result; and performing a fault warning based on the fault identification result.

[0122] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the wind turbine generator set yaw system fault warning method provided by the above-mentioned methods, the method comprising: monitoring real-time data of the wind turbine generator set yaw system, the real-time data comprising effective output power and incoming wind speed, the incoming wind speed comprising an average incoming wind speed at effective output power and an average incoming wind speed at rated power; inputting the effective output power, the average incoming wind speed at effective output power and the average incoming wind speed at rated power into a pre-constructed fault identification model, and outputting a fault identification result; and performing a fault warning based on the fault identification result.

[0123] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0124] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0125] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A wind turbine generator set yaw system fault warning method, characterized in that: include: Monitor the real-time data of the yaw system of the wind turbine generator set, the real-time data including the effective output power and the incoming wind speed, the incoming wind speed including the average incoming wind speed at the effective output power and the average incoming wind speed at the rated power; Inputting the effective output power, the average wind speed at the effective output power, and the average wind speed at the rated power into a pre-built fault identification model, and outputting a fault identification result; Based on the fault identification result, a fault warning is performed; Wherein, the fault identification model is: Where V represents the fault identification result, and its value range is (0,1); P represents the effective output power, P0 is the rated power of the wind turbine, Indicates the average incoming wind speed when the effective output power is Indicates the average incoming wind speed at rated power.

2. The wind turbine generator set yaw system fault warning method according to claim 1, characterized in that: The monitoring method of the effective output power of the wind turbine generator set is: The rated power of the wind turbine generator set is monitored in the following manner: Where ρ is the air density under standard atmospheric pressure, r is the radius of the wind turbine impeller, C p is the wind energy utilization coefficient under normal operating conditions, and θ is the angle between the wind direction and the nacelle position.

3. The wind turbine generator set yaw system fault warning method according to claim 1, characterized in that: The performing of a fault warning based on the fault identification result includes: If the fault identification result is a fault, performing a first classification on the fault identification result to determine a first fault type, wherein the first fault type includes an actuator fault of a yaw system and a wind vane fault; Fault warnings are respectively performed based on the actuator failure and the wind vane failure.

4. The wind turbine generator set yaw system fault warning method according to claim 3, characterized in that: The first classification of the fault identification result to determine the first fault type includes: Acquire first wind direction data of a wind vane of a yaw system of a wind turbine generator set during a first period of time, and construct a first wind direction sequence; Acquire second wind direction data of the wind direction of the wind farm during the first period of time, and construct a second wind direction sequence; Determining a similarity value between the first wind direction sequence and the second wind direction sequence; If the similarity value is greater than or equal to the similarity threshold, determining that the first fault type is an actuator fault of the yaw system; If the similarity value is less than the similarity threshold, it is determined that the first fault type is a wind vane fault.

5. The wind turbine generator set yaw system fault warning method according to claim 3, characterized in that: Also includes: If the first fault type is an actuator fault of the yaw system, performing a second classification on the actuator fault of the yaw system to determine a second fault type; The second fault type includes a transmission system fault and a positioning system fault; Based on the transmission system failure and positioning system failure, a fault warning is performed.

6. The wind turbine generator set yaw system fault warning method according to claim 5, characterized in that: The transmission system fault is identified by the following formula: Among them, i' represents the calculated transmission ratio, i represents the designed transmission ratio, ω in represents the angular velocity at the input of the transmission system, ω out represents the angular velocity at the output end of the transmission system, T out Represents the torque at the output end of the transmission system, J out represents the moment of inertia of the output end of the transmission system, α out Represents the angular acceleration at the output of the transmission system.

7. The wind turbine generator set yaw system fault warning method according to claim 6, characterized in that: Also includes: Acquire historical data of the yaw system of the wind turbine generator set, wherein the historical data includes a design transmission ratio of the transmission system, and an angular acceleration of an output end of the transmission system during normal operation and abnormal operation of the transmission system; According to the angular acceleration of the output end of the transmission system during normal operation and abnormal operation of the transmission system, an angular acceleration fault threshold of the output end of the transmission system is set; Compare the calculated transmission ratio with the designed transmission ratio. If they are different, the transmission system is faulty. If they are the same, determining the relationship between the angular acceleration at the output end of the transmission system and the angular acceleration fault threshold at the output end of the transmission system; If the calculated angular acceleration of the output of the transmission system is outside the angular acceleration fault threshold of the output of the transmission system, the transmission system is faulty.

8. The wind turbine generator set yaw system fault warning method according to claim 5, characterized in that: The positioning system failure is identified by the following formula: Among them, G(s) represents the transfer function of the positioning system, K represents the feedback coefficient of the positioning system, which represents the proportional relationship between the output signal and the input signal, Γ represents the feedback filter time constant, and s represents the complex variable in the Laplace transform.

9. The wind turbine generator set yaw system fault warning method according to claim 8, characterized in that: Also includes: Acquire historical data of the yaw system of the wind turbine generator set, wherein the historical data includes historical amplitude-frequency characteristics of the positioning system; Calculate the amplitude-frequency characteristics of the real-time positioning system of the positioning system; The historical amplitude-frequency characteristics of the positioning system and the amplitude-frequency characteristics of the real-time positioning system are compared. If the two do not match, the positioning system fails.

10. A fault warning device for the yaw system of a wind turbine generator set, characterized in that: include: A detection module, used to monitor the real-time data of the yaw system of the wind turbine generator set, wherein the real-time data includes the effective output power and the incoming wind speed, wherein the incoming wind speed includes the average incoming wind speed at the effective output power and the average incoming wind speed at the rated power; An identification module, used for inputting the effective output power, the average wind speed at the effective output power and the average wind speed at the rated power into a pre-built fault identification model, and outputting a fault identification result; An early warning module, used for providing a fault early warning based on the fault identification result; Wherein, the fault identification model is: Where V represents the fault identification result, and its value range is (0,1); P represents the effective output power, P0 is the rated power of the wind turbine, Indicates the average incoming wind speed when the effective output power is Indicates the average incoming wind speed at rated power.

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