Wind turbine and wind speed meter fault diagnosis method, device and equipment thereof

Abstract

The application provides a wind turbine and a wind speed meter fault diagnosis method, device and equipment thereof. The method comprises the following steps: acquiring a first wind speed data set and a second wind speed data set of a first wind speed meter and a second wind speed meter respectively within a set historical time; respectively grouping the first wind speed data set and the second wind speed data set at a set interval time to obtain M first wind speed data groups and M second wind speed data groups; cleaning the M first wind speed data groups and the M second wind speed data groups to obtain N first target wind speed data groups and N second target wind speed data groups; calculating a warning value according to the N first target wind speed data groups and the N second target wind speed data groups; and performing fault diagnosis on the first wind speed meter and the second wind speed meter according to the warning value. The method can accurately diagnose whether the wind speed meter is faulty, avoids false alarms of the wind speed meter, ensures that the wind turbine can be normally controlled, and guarantees the effectiveness of the evaluation result.

Description

Technical Field

[0001] This invention relates to the field of wind turbine generator technology, and in particular to a method, apparatus and equipment for diagnosing faults in wind turbine generators and their anemometers. Background Technology

[0002] Wind speed is an important parameter affecting the output of wind turbine generators. Anemometers are an important component of wind turbine generators. On the one hand, the wind speed measured by the anemometer is introduced into the control system as an important input for controlling the wind turbine generator. On the other hand, the wind speed measured by the anemometer is also used to evaluate the power generation performance of the wind turbine generator.

[0003] A malfunctioning anemometer can render wind turbines uncontrollable and affect the validity of assessment results. Therefore, the accuracy of anemometer measurements is crucial, and ensuring this accuracy hinges on accurately diagnosing anemometer malfunctions. Consequently, accurately diagnosing anemometer malfunctions is a pressing issue that needs to be addressed. Summary of the Invention

[0004] The present invention aims to solve, to a certain extent, the technical problems in the related technologies.

[0005] Therefore, the first objective of this invention is to provide a method for diagnosing anemometer faults in wind turbine generator sets. This method can accurately diagnose whether anemometers have malfunctioned, avoid false alarms from anemometer faults, ensure that wind turbine generator sets can be controlled normally, and guarantee the validity of the evaluation results.

[0006] The second objective of this invention is to provide a fault diagnosis device for anemometers in wind turbine generator sets.

[0007] The third objective of this invention is to provide a fault diagnosis device for anemometers in wind turbine generator sets.

[0008] The fourth objective of this invention is to provide a wind turbine generator set.

[0009] The fifth objective of this invention is to provide a computer-readable storage medium.

[0010] The sixth objective of this invention is to provide a computer program product.

[0011] To achieve the above objectives, a first aspect of the present invention proposes a method for diagnosing faults in an anemometers of wind turbine generators. The method includes: acquiring a first wind speed dataset and a second wind speed dataset from a first anemometer and a second anemometer within a set historical time period, respectively; grouping the first and second wind speed datasets at set intervals to obtain M first wind speed data groups and M second wind speed data groups; cleaning the M first wind speed data groups and M second wind speed data groups to obtain N first target wind speed data groups and N second target wind speed data groups; calculating a warning value based on the N first target wind speed data groups and N second target wind speed data groups; and performing fault diagnosis on the first and second anemometers based on the warning value; wherein M > N, and M and N are both positive integers.

[0012] The anemometer fault diagnosis method for wind turbine generators according to embodiments of the present invention first acquires first and second wind speed datasets from a first anemometer and a second anemometer within a set historical time period, respectively. The first and second wind speed datasets are then grouped at set intervals to obtain M first wind speed data groups and M second wind speed data groups. These M first and M second wind speed data groups are then cleaned to obtain N first target wind speed data groups and N second target wind speed data groups. Finally, a warning value is calculated based on the N first target wind speed data groups and N second target wind speed data groups, and fault diagnosis is performed on the first and second anemometers based on the warning value. Therefore, this method can accurately diagnose whether an anemometer has malfunctioned, avoid false alarms, ensure normal control of the wind turbine generator, and guarantee the validity of the evaluation results.

[0013] In addition, the anemometer fault diagnosis method for wind turbine generator sets proposed in the first aspect of the present invention may also have the following additional technical features:

[0014] According to one embodiment of the present invention, the step of cleaning M first wind speed data sets and M second wind speed data sets to obtain N first target wind speed data sets and N second target wind speed data sets includes:

[0015] The number of wind speed data samples in each of the first wind speed data groups and each of the second wind speed data groups is obtained respectively;

[0016] If the number of samples is less than the first set number, then the corresponding first wind speed data group and second wind speed data group are removed.

[0017] The remaining first wind speed data group and second wind speed data group are used as N first target wind speed data groups and N second target wind speed data groups.

[0018] According to an embodiment of the present invention, after removing the corresponding first wind speed data group and second wind speed data group, the method further includes:

[0019] Obtain the total number of wind speed data that are outside the set wind speed range in each of the first wind speed data groups and each of the second wind speed data groups;

[0020] If the total number exceeds the second set number, then the corresponding first wind speed data group and the second wind speed data group are removed.

[0021] According to one embodiment of the present invention, calculating the warning value based on N sets of first target wind speed data and N sets of second target wind speed data includes:

[0022] Calculate the first average value and the second average value corresponding to each of the first target wind speed data groups and each of the second target wind speed data groups;

[0023] If both the first average and the second average exceed a set average, then a ratio is calculated; wherein the ratio is the ratio of the absolute value of the difference between the first average and the second average to the ratio between the first average and the second average.

[0024] If the number of said proportions exceeds the third set number, then the root mean square of multiple said proportions is calculated as the warning value.

[0025] According to an embodiment of the present invention, the step of diagnosing faults in the first anemometer and the second anemometer based on the warning value includes:

[0026] If the warning value exceeds the set warning value, then it is determined that at least one of the first and second anemometers has malfunctioned; or,

[0027] If the warning value does not exceed the set warning value, it is determined that neither the first anemometer nor the second anemometer has malfunctioned.

[0028] According to one embodiment of the present invention, the set warning value includes a first set warning value, a second set warning value, and a third set warning value; wherein,

[0029] If the warning value exceeds the first preset warning value but does not exceed the second preset warning value, then a level one warning signal is generated and issued; or,

[0030] If the warning value exceeds the second preset warning value but does not exceed the third preset warning value, a secondary warning signal is generated and issued.

[0031] If the warning value exceeds the third preset warning value, a level three warning signal is generated and issued;

[0032] Wherein, the first set warning value is less than the second set warning value, and the second set warning value is less than the third set warning value.

[0033] To achieve the above objectives, a second aspect of the present invention provides a fault diagnosis device for anemometers of wind turbine generator sets. The device includes: a first acquisition module, configured to acquire a first wind speed dataset and a second wind speed dataset from the first anemometer and the second anemometer within a set historical time period, respectively; a processing module, configured to group the first wind speed dataset and the second wind speed dataset at set intervals to obtain M first wind speed data groups and M second wind speed data groups; a cleaning module, configured to clean the M first wind speed data groups and the M second wind speed data groups to obtain N first target wind speed data groups and N second target wind speed data groups; a second acquisition module, configured to calculate a warning value based on the N first target wind speed data groups and the N second target wind speed data groups; and a fault diagnosis module, configured to perform fault diagnosis on the first anemometer and the second anemometer based on the warning value; wherein M > N, and M and N are both positive integers.

[0034] The anemometer fault diagnosis device for wind turbine generators according to an embodiment of the present invention acquires first and second wind speed datasets from a first anemometer and a second anemometer within a set historical time period through a first acquisition module. A processing module groups the first and second wind speed datasets at set intervals to obtain M first wind speed data groups and M second wind speed data groups. A cleaning module cleans the M first and M second wind speed data groups to obtain N first target wind speed data groups and N second target wind speed data groups. A second acquisition module calculates a warning value based on the N first target wind speed data groups and N second target wind speed data groups. A fault diagnosis module performs fault diagnosis on the first and second anemometers based on the warning value. Therefore, this device can accurately diagnose whether the anemometer has malfunctioned, avoiding false alarms and ensuring normal control of the wind turbine generator, as well as guaranteeing the validity of the evaluation results.

[0035] In addition, the anemometer fault diagnosis device for wind turbine generator sets proposed in the second aspect embodiment of the present invention may also have the following additional technical features:

[0036] According to one embodiment of the present invention, when the cleaning module is used to clean M first wind speed data sets and M second wind speed data sets to obtain N first target wind speed data sets and N second target wind speed data sets, the cleaning module includes:

[0037] The number of wind speed data samples in each of the first wind speed data groups and each of the second wind speed data groups is obtained respectively;

[0038] When the number of samples is less than the first set number, the corresponding first wind speed data group and second wind speed data group are removed.

[0039] The remaining first wind speed data group and second wind speed data group are used as N first target wind speed data groups and N second target wind speed data groups.

[0040] According to an embodiment of the present invention, after the removal unit is used to remove the corresponding first wind speed data group and second wind speed data group, it is further used to:

[0041] The total number of wind speed data that are not within the set wind speed range in each of the first wind speed data groups and each of the second wind speed data groups is obtained respectively. When the total number exceeds the second set number, the corresponding first wind speed data group and second wind speed data group are removed.

[0042] According to one embodiment of the present invention, when the second acquisition module calculates a warning value based on N sets of first target wind speed data and N sets of second target wind speed data, it includes:

[0043] Calculate the first average value and the second average value corresponding to each of the first target wind speed data groups and each of the second target wind speed data groups;

[0044] If both the first average and the second average exceed a set average, then a ratio is calculated; wherein the ratio is the ratio of the absolute value of the difference between the first average and the second average to the ratio between the first average and the second average.

[0045] If the number of said proportions exceeds the third set number, then the root mean square of multiple said proportions is calculated as the warning value.

[0046] According to an embodiment of the present invention, when the fault diagnosis module is used to perform fault diagnosis on the first anemometer and the second anemometer based on the warning value, it includes:

[0047] When the warning value exceeds the set warning value, it is determined that at least one of the first anemometer and the second anemometer has malfunctioned; or...

[0048] If the warning value does not exceed the set warning value, it is determined that neither the first anemometer nor the second anemometer has malfunctioned.

[0049] According to one embodiment of the present invention, the set warning value includes a first set warning value, a second set warning value, and a third set warning value, and the device further includes: an alarm module; wherein,

[0050] The alarm module is used to generate and issue a level one warning signal when the warning value exceeds the first preset warning value but does not exceed the second preset warning value; or,

[0051] The alarm module is used to generate and issue a secondary warning signal when the warning value exceeds the second preset warning value but does not exceed the third preset warning value;

[0052] The alarm module is used to generate and issue a three-level warning signal when the warning value exceeds the third preset warning value;

[0053] Wherein, the first set warning value is less than the second set warning value, and the second set warning value is less than the third set warning value.

[0054] To achieve the above objectives, a third aspect of the present invention provides an anemometer fault diagnosis device for a wind turbine generator set, comprising: a processor and a memory; wherein the processor reads executable program code stored in the memory to run a program corresponding to the executable program code, so as to implement the above-described anemometer fault diagnosis method for the wind turbine generator set.

[0055] The anemometer fault diagnosis device for wind turbine generator sets according to the present invention employs the above-described anemometer fault diagnosis method for wind turbine generator sets. It can accurately diagnose whether the anemometer has malfunctioned, avoid false alarms of anemometer faults, ensure that the wind turbine generator set can be controlled normally, and guarantee the validity of the evaluation results.

[0056] To achieve the above objectives, a fourth aspect of the present invention provides a wind turbine generator set that employs the aforementioned anemometer fault diagnosis device for wind turbine generator sets.

[0057] The wind turbine generator set of this invention, by employing the above-mentioned wind turbine generator set anemometer fault diagnosis device, can accurately diagnose whether the anemometer has malfunctioned, avoid false alarms of anemometer faults, ensure that the wind turbine generator set can be controlled normally, and ensure the validity of the evaluation results.

[0058] To achieve the above objectives, a fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, characterized in that the computer program, when executed by a processor, implements the above-described method for diagnosing anemometer faults in wind turbine generator sets.

[0059] The computer-readable storage medium of this invention, using the above-described anemometer fault diagnosis method for wind turbine generator sets, can accurately diagnose whether the anemometer has malfunctioned, avoid false alarms of anemometer faults, ensure that the wind turbine generator set can be controlled normally, and guarantee the validity of the evaluation results.

[0060] To achieve the above objectives, a fifth aspect of the present invention provides a computer program product that, when executed by an instruction processor, performs the aforementioned method for diagnosing anemometer faults in a wind turbine generator set.

[0061] The computer program product of this invention, using the above-described anemometer fault diagnosis method for wind turbine generator sets, can accurately diagnose whether the anemometer has malfunctioned, avoid false alarms of anemometer faults, ensure that the wind turbine generator set can be controlled normally, and guarantee the validity of the evaluation results.

[0062] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0063] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0064] Figure 1 This is a flowchart of a method for diagnosing anemometer faults in a wind turbine generator set according to an embodiment of the present invention;

[0065] Figure 2 This is a flowchart of a method for diagnosing anemometer faults in a wind turbine according to an embodiment of the present invention;

[0066] Figure 3 This is a schematic diagram of a wind speed meter fault diagnosis device for a wind turbine generator set according to an embodiment of the present invention. Detailed Implementation

[0067] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0068] The following description, with reference to the accompanying drawings, describes a method for diagnosing an anemometer faults in a wind turbine generator set, a device for diagnosing anemometer faults in a wind turbine generator set, an equipment for diagnosing anemometer faults in a wind turbine generator set, a wind turbine generator set, and a computer-readable storage medium.

[0069] Figure 1This is a flowchart of a method for diagnosing anemometer faults in a wind turbine generator set according to an embodiment of the present invention.

[0070] The anemometer fault diagnosis method for wind turbine generator sets according to embodiments of the present invention can be executed by the anemometer fault diagnosis device for wind turbine generator sets according to embodiments of the present invention, which can be configured in the anemometer fault diagnosis equipment for wind turbine generator sets.

[0071] like Figure 1 As shown, the anemometer fault diagnosis method for wind turbine generator sets according to an embodiment of the present invention includes the following steps:

[0072] S101, respectively acquire the first wind speed dataset and the second wind speed dataset of the first anemometer and the second anemometer within a set historical time period.

[0073] The historical time period must be at least one day, for example, a 24-hour period.

[0074] For each wind turbine generator in the target wind farm, each wind turbine generator is equipped with a first anemometer and a second anemometer, which collect wind speed data. The anemometer fault diagnosis device for the wind turbine generator in this invention obtains the first wind speed data and the second wind speed data from the first anemometer and the second anemometer over the past 24 hours.

[0075] S102, the first wind speed dataset and the second wind speed dataset are grouped at a set interval to obtain M first wind speed data groups and M second wind speed data groups.

[0076] The interval time can be set according to actual needs; for example, it can be 10 minutes.

[0077] In other words, the first wind speed dataset and the second wind speed dataset are processed in groups at 10-minute intervals, resulting in 144 first wind speed dataset groups and 144 second wind speed dataset groups.

[0078] S103, clean the M first wind speed data sets and M second wind speed data sets to obtain N first target wind speed data sets and N second target wind speed data sets.

[0079] As one possible implementation of step S3, the number of wind speed data samples in each first wind speed data group and each second wind speed data group is obtained respectively; if the number of samples is less than the first set number, the corresponding first wind speed data group and second wind speed data group are removed; the remaining first wind speed data group and second wind speed data group are used as N first target wind speed data groups and N second target wind speed data groups.

[0080] The first set quantity is set according to actual needs. For example, it can be 85% of the required sampling. For instance, if the first and second anemometers each have a sampling time interval of 5 seconds, 120 points should be sampled in 10 minutes, and the first set quantity is 102. That is, if the sampling quantity of the first wind speed data group is less than 102, then the first wind speed data group and the second wind speed data group corresponding to the time of the first wind speed data group are removed; if the sampling quantity of the second wind speed data group is less than 102, then the second wind speed data group and the first wind speed data group corresponding to the time of the second wind speed data group are removed, ultimately resulting in N first target wind speed data groups and N second target wind speed data groups.

[0081] As another possible method for step S3, the number of wind speed data samples in each first wind speed data group and each second wind speed data group is obtained respectively. If the number of samples is less than the first set number, the corresponding first wind speed data group and second wind speed data group are removed. Then, the total number of wind speed data in each first wind speed data group and each second wind speed data group that are not in the set wind speed range is obtained respectively. If the total number exceeds the second set number, the corresponding first wind speed data group and second wind speed data group are removed. Finally, the remaining first wind speed data group and second wind speed data group are used as N first target wind speed data groups and N second target wind speed data groups.

[0082] In other words, if the number of samples in the first wind speed data group is less than 102, then the first wind speed data group and the second wind speed data group corresponding to the time of the first wind speed data group are removed; if the number of samples in the second wind speed data group is less than 102, then the second wind speed data group and the first wind speed data group corresponding to the time of the second wind speed data group are removed.

[0083] Next, the remaining first and second wind speed data sets are cleaned. Specifically, data in each first and second wind speed data set that are not in the range (0, 50 m / s) are removed. If the removal ratio exceeds the second set number (e.g., 120 wind speed data should be sampled in 10 minutes, and the removal ratio can be set to 10%, meaning the second set number is 12 wind speed data), then the first and second wind speed data sets are removed, resulting in N first target wind speed data sets and N second target wind speed data sets.

[0084] S104, Calculate the warning value based on N sets of first target wind speed data and N sets of second target wind speed data.

[0085] As one possible implementation of step S4, a warning value is calculated based on N first target wind speed data groups and N second target wind speed data groups, including: calculating the first average value and the second average value corresponding to each first target wind speed data group and each second target wind speed data group; if both the first average value and the second average value exceed a set average value, then a ratio is calculated; wherein, the ratio is the ratio between the absolute value of the difference between the first average value and the second average value and the first average value and the second average value; if the number of ratios exceeds a third set number, then the root mean square of multiple ratios is calculated as the warning value.

[0086] Specifically, the average wind speed of the first and second anemometers is calculated for each 10-minute interval. For the first anemometer, V11 = (V1 + V2 + ... + VL), resulting in a series of 10-minute averages: V11, V12, ..., V1N. Similarly, the average wind speed of the second anemometer for each 10-minute interval is obtained: V21, V22, ..., V2N. It should be noted that L represents the number of sampling points within 10 minutes. For example, if sampling occurs every 5 seconds, then L = 120. If data outside the range (0, 50 m / s) is removed during data cleaning, then L will be less than 120. In other words, L here represents the number of wind speed data points in the target wind speed data set.

[0087] For each pair of V1j and V2j, compare them. When both average wind speeds exceed a set average value (which can be set as needed, for example, a value between 5m / s and 10m / s), calculate the ratio K of the difference between the two to their average values. For example, if V11 = 5m / s and V21 = 7m / s, then the ratio K is 2 / 6 = 0.33.

[0088] Within a set historical time period, if the cumulative count P of the wind speed data of both channels exceeding the set average value does not exceed the third set number (the third set number can be set according to time needs, for example, it can be 10), then the process ends; if the cumulative count P of the wind speed data of both channels exceeding the set average value does not exceed the third set number, then the root mean square of multiple K values ​​is calculated: Kmean = (sqrt((K1^2 + K2^2 + ... + KP^2) / P)).

[0089] S105, based on the warning value, perform fault diagnosis on the first and second anemometers.

[0090] In this embodiment, if the warning value exceeds the set warning value, it is determined that at least one of the first and second anemometers has malfunctioned; or, if the warning value does not exceed the set warning value, it is determined that neither the first nor the second anemometer has malfunctioned.

[0091] The set warning values ​​can include a first set warning value, a second set warning value, and a third set warning value. If a warning value exceeds the first set warning value but does not exceed the second set warning value, a Level 1 warning signal is generated and issued; or, if a warning value exceeds the second set warning value but does not exceed the third set warning value, a Level 2 warning signal is generated and issued; if a warning value exceeds the third set warning value, a Level 3 warning signal is generated and issued. Maintenance personnel can inspect and maintain the first and second anemometers according to the warning signal level.

[0092] Therefore, the anemometer fault diagnosis method for wind turbine generator sets in this embodiment of the invention compares the consistency of wind speed data from two wind speed acquisition channels of the wind turbine generator set to determine whether the anemometer of the wind turbine generator set is faulty, and alerts maintenance personnel to check and maintain it through a site warning. The method reduces the false alarm rate by averaging the wind speed data. Considering that the measurement deviation is large when the wind speed is low, and the wind speed data has little effect on the wind turbine generator set at this time, a set average value is set. If the wind speed is less than the set average value, it is determined that the data set is ineffective. Considering that there may be large comparison deviations under drastic wind speed changes, a root mean square algorithm is designed for evaluation, and a third set limit is set to avoid false alarms caused by occasional or isolated large wind speed deviations.

[0093] Figure 2 This is a flowchart of a method for diagnosing anemometer faults in a wind turbine generator set according to an embodiment of the present invention.

[0094] like Figure 2 As shown, the anemometer fault diagnosis method for wind turbine generator sets according to this embodiment of the invention includes three parts: the first part is data preparation; the second part is algorithm implementation; and the third part is alarm threshold.

[0095] The first part includes the following steps:

[0096] S201, Historical data collection of the target wind farm (no less than 1 day).

[0097] S202, the field server stores data.

[0098] S203, divide the time series into M groups by continuously dividing it into groups of 10 minutes each.

[0099] S204, remove non-compliant data based on data sampling quality.

[0100] S205, cleans the out-of-limit data of the wind speed channel.

[0101] S206, obtain N target wind speed data sets for wind speed channels 1 and 2 respectively.

[0102] Part Two includes the following steps:

[0103] S207, calculate the average wind speed for each 10-minute interval for wind speed channels 1 and 2: V11 = average(V1 + V2 + ... + VL) / L, obtaining a series of 10-minute averages V11, V12, ..., V1N. Where L is the number of wind speed data points within each 10-minute interval. Similarly, obtain the averages V21, V22, ..., V2N for wind speed 2.

[0104] S208. For each pair of V1j and V2j, compare them. When V1j≥5 and V2j≥5, calculate K = abs(V1j-V2j) / average(V1j, V2j). Where j = 1, 2, ..., N.

[0105] S209, using days as the unit, calculate each K obtained by satisfying V1j≥5 and V2j≥5. When the cumulative number exceeds 10, that is, when P≥10, calculate the root mean square of K Kmean=sqrt((K1^2+K2^2+...+KP^2) / P); ​​if P<10, then Kmean=0.

[0106] Part Three includes the following steps:

[0107] S210, set three thresholds, namely K1, K2 and K3; where K3≥K2≥K1.

[0108] S211, Kmean≥K1 is a Level 1 warning (basic); Kmean≥K2 is a Level 2 warning (intermediate); Kmean≥K3 is a Level 3 warning (advanced).

[0109] In summary, the anemometer fault diagnosis method for wind turbine generators according to embodiments of the present invention first acquires first and second wind speed datasets from a first anemometer and a second anemometer within a set historical time period, respectively. The first and second wind speed datasets are then grouped at set intervals to obtain M first wind speed data groups and M second wind speed data groups. These M first and M second wind speed data groups are then cleaned to obtain N first target wind speed data groups and N second target wind speed data groups. Finally, a warning value is calculated based on the N first target wind speed data groups and N second target wind speed data groups, and fault diagnosis is performed on the first and second anemometers based on the warning value. Therefore, this method can accurately diagnose whether an anemometer has malfunctioned, avoid false alarms, ensure normal control of the wind turbine generator, and guarantee the validity of the evaluation results.

[0110] Figure 3This is a schematic diagram of a wind speed meter fault diagnosis device for a wind turbine generator set according to an embodiment of the present invention.

[0111] like Figure 3 As shown, the anemometer fault diagnosis device 300 for wind turbine generator sets according to an embodiment of the present invention includes: a first acquisition module 301, a processing module 302, a cleaning module 303, a second acquisition module 304, and a fault diagnosis module 305.

[0112] The system comprises the following modules: a first acquisition module 301 acquires first and second wind speed datasets from a first anemometer and a second anemometer within a set historical time period, respectively. A processing module 302 groups the first and second wind speed datasets at set intervals to obtain M first wind speed data groups and M second wind speed data groups. A cleaning module 303 cleans the M first and M second wind speed data groups to obtain N first target wind speed data groups and N second target wind speed data groups. A second acquisition module 304 calculates a warning value based on the N first and N second target wind speed data groups. A fault diagnosis module 305 performs fault diagnosis on the first and second anemometers based on the warning value. Where M > N, and M and N are both positive integers.

[0113] According to one embodiment of the present invention, when the cleaning module 303 is used to clean M first wind speed data sets and M second wind speed data sets to obtain N first target wind speed data sets and N second target wind speed data sets, it includes:

[0114] The number of wind speed data samples in each first wind speed data group and each second wind speed data group is obtained respectively;

[0115] When the number of samples is less than the first set number, the corresponding first wind speed data group and second wind speed data group are removed.

[0116] The remaining first and second wind speed data sets are used as N first target wind speed data sets and N second target wind speed data sets.

[0117] According to one embodiment of the present invention, after the removal unit is used to remove the corresponding first wind speed data group and second wind speed data group, it is further used to:

[0118] Obtain the total number of wind speed data that are outside the set wind speed range in each first wind speed data group and each second wind speed data group, and remove the corresponding first wind speed data group and second wind speed data group when the total number exceeds the second set number.

[0119] According to one embodiment of the present invention, when the second acquisition module 304 calculates a warning value based on N sets of first target wind speed data and N sets of second target wind speed data, it includes:

[0120] Calculate the first average value and the second average value corresponding to each first target wind speed data group and each second target wind speed data group;

[0121] If both the first average and the second average exceed the set average, then the ratio is calculated; where the ratio is the ratio of the absolute value of the difference between the first average and the second average to the ratio between the first average and the second average.

[0122] If the number of proportions exceeds the third set number, the root mean square of multiple proportions is calculated as the warning value.

[0123] According to one embodiment of the present invention, when the fault diagnosis module 305 performs fault diagnosis on the first anemometer and the second anemometer based on the warning value, it includes:

[0124] When the warning value exceeds the set warning value, it is determined that at least one of the first and second anemometers has malfunctioned; or...

[0125] If the warning value does not exceed the set warning value, it is determined that neither the first anemometer nor the second anemometer has malfunctioned.

[0126] According to one embodiment of the present invention, the set warning values ​​include a first set warning value, a second set warning value, and a third set warning value, and the device further includes: an alarm module; wherein,

[0127] The alarm module is used to generate and issue a level one warning signal when the warning value exceeds a first preset warning value but does not exceed a second preset warning value; or,

[0128] The alarm module is used to generate and issue a secondary warning signal when the warning value exceeds the second preset warning value but does not exceed the third preset warning value;

[0129] The alarm module is used to generate and issue a three-level warning signal when the warning value exceeds the third preset warning value;

[0130] Among them, the first set warning value is less than the second set warning value, and the second set warning value is less than the third set warning value.

[0131] It should be noted that for details not disclosed in the anemometer fault diagnosis device for wind turbine generator sets in this embodiment of the invention, please refer to the details disclosed in the anemometer fault diagnosis method for wind turbine generator sets in this embodiment of the invention, which will not be repeated here.

[0132] The anemometer fault diagnosis device for wind turbine generators according to an embodiment of the present invention acquires first and second wind speed datasets from a first anemometer and a second anemometer within a set historical time period through a first acquisition module. A processing module groups the first and second wind speed datasets at set intervals to obtain M first wind speed data groups and M second wind speed data groups. A cleaning module cleans the M first and M second wind speed data groups to obtain N first target wind speed data groups and N second target wind speed data groups. A second acquisition module calculates a warning value based on the N first target wind speed data groups and N second target wind speed data groups. A fault diagnosis module performs fault diagnosis on the first and second anemometers based on the warning value. Therefore, this device can accurately diagnose whether the anemometer has malfunctioned, avoiding false alarms and ensuring normal control of the wind turbine generator, as well as guaranteeing the validity of the evaluation results.

[0133] Based on the above embodiments, the present invention also proposes a fault diagnosis device for anemometers of wind turbine generator sets.

[0134] An embodiment of the present invention proposes a wind turbine generator set anemometer fault diagnosis device, which includes a processor and a memory; wherein the processor reads executable program code stored in the memory to run a program corresponding to the executable program code, so as to implement the above-mentioned wind turbine generator set anemometer fault diagnosis method.

[0135] The anemometer fault diagnosis device for wind turbine generator sets according to the present invention employs the above-described anemometer fault diagnosis method for wind turbine generator sets. It can accurately diagnose whether the anemometer has malfunctioned, avoid false alarms of anemometer faults, ensure that the wind turbine generator set can be controlled normally, and guarantee the validity of the evaluation results.

[0136] Based on the above embodiments, the present invention also proposes a wind turbine generator set.

[0137] The present invention provides a wind turbine generator set that uses the aforementioned anemometer fault diagnosis device for wind turbine generator sets.

[0138] The wind turbine generator set of this invention, by employing the above-mentioned wind turbine generator set anemometer fault diagnosis device, can accurately diagnose whether the anemometer has malfunctioned, avoid false alarms of anemometer faults, ensure that the wind turbine generator set can be controlled normally, and ensure the validity of the evaluation results.

[0139] Based on the above embodiments, the present invention also proposes a computer-readable storage medium.

[0140] The present invention provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described method for diagnosing anemometer faults in wind turbine generators.

[0141] The computer-readable storage medium of this invention, using the above-described anemometer fault diagnosis method for wind turbine generator sets, can accurately diagnose whether the anemometer has malfunctioned, avoid false alarms of anemometer faults, ensure that the wind turbine generator set can be controlled normally, and guarantee the validity of the evaluation results.

[0142] Based on the above embodiments, the present invention also proposes a computer program product.

[0143] The present invention provides a computer program product that, when executed by the instruction processor in the computer program product, performs the above-mentioned method for diagnosing the anemometer fault of a wind turbine generator set.

[0144] The computer program product of this invention, using the above-described anemometer fault diagnosis method for wind turbine generator sets, can accurately diagnose whether the anemometer has malfunctioned, avoid false alarms of anemometer faults, ensure that the wind turbine generator set can be controlled normally, and guarantee the validity of the evaluation results.

[0145] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0146] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0147] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of the invention pertain.

[0148] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer system, a system including a processor, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0149] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any of the following techniques known in the art, or a combination thereof: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0150] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0151] Furthermore, the functional units in the various embodiments of the present invention can be integrated into a single module, or each unit can exist physically separately, or two or more units can be integrated into a single module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0152] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for diagnosing faults in the anemometer of a wind turbine generator set, characterized in that, The wind turbine generator set is equipped with a first anemometer and a second anemometer, and the method includes: Acquire the first wind speed dataset and the second wind speed dataset of the first anemometer and the second anemometer within a set historical time period, respectively. The first wind speed dataset and the second wind speed dataset are grouped at set intervals to obtain M first wind speed data groups and M second wind speed data groups. Clean the M first wind speed data sets and the M second wind speed data sets to obtain N first target wind speed data sets and N second target wind speed data sets; Calculate the warning value based on N sets of first target wind speed data and N sets of second target wind speed data; Based on the warning value, perform fault diagnosis on the first anemometer and the second anemometer; Where M > N, and M and N are both positive integers; The step of cleaning the M first wind speed data sets and the M second wind speed data sets to obtain N first target wind speed data sets and N second target wind speed data sets includes: The number of wind speed data samples in each of the first wind speed data groups and each of the second wind speed data groups is obtained respectively; If the number of samples is less than the first set number, the corresponding first wind speed data group and the second wind speed data group are removed, and the total number of wind speed data in each first wind speed data group and each second wind speed data group that are not in the set wind speed range is obtained respectively. If the total number exceeds the second set number, the corresponding first wind speed data group and the second wind speed data group are removed. The remaining first wind speed data group and second wind speed data group are used as N first target wind speed data groups and N second target wind speed data groups; The step of calculating the warning value based on N sets of first target wind speed data and N sets of second target wind speed data includes: Calculate the first average value and the second average value corresponding to each of the first target wind speed data groups and each of the second target wind speed data groups; If both the first average and the second average exceed a set average, then a ratio is calculated; wherein the ratio is the ratio of the absolute value of the difference between the first average and the second average to the mean between the first average and the second average. If the number of said proportions exceeds the third set number, then the root mean square of multiple said proportions is calculated as the warning value; If the quantity of the stated proportion does not exceed the third predetermined quantity, then the process ends.

2. The method according to claim 1, characterized in that, The step of diagnosing faults in the first and second anemometers based on the warning value includes: If the warning value exceeds the set warning value, then it is determined that at least one of the first and second anemometers has malfunctioned; or, If the warning value does not exceed the set warning value, it is determined that neither the first anemometer nor the second anemometer has malfunctioned.

3. The method according to claim 2, characterized in that, The set warning values ​​include a first set warning value, a second set warning value, and a third set warning value; wherein... If the warning value exceeds the first preset warning value but does not exceed the second preset warning value, then a level one warning signal is generated and issued; or, If the warning value exceeds the second preset warning value but does not exceed the third preset warning value, a secondary warning signal is generated and issued. If the warning value exceeds the third preset warning value, a level three warning signal is generated and issued; Wherein, the first set warning value is less than the second set warning value, and the second set warning value is less than the third set warning value.

4. A fault diagnosis device for an anemometer of a wind turbine generator set, characterized in that, The anemometer fault diagnosis method for wind turbine generator sets as described in any one of claims 1-3, wherein the wind turbine generator set is equipped with a first anemometer and a second anemometer, the device comprising: The first acquisition module is used to acquire the first wind speed dataset and the second wind speed dataset of the first anemometer and the second anemometer within a set historical time period, respectively. The processing module is used to group the first wind speed dataset and the second wind speed dataset at a set interval to obtain M first wind speed data groups and M second wind speed data groups. The cleaning module is used to clean M sets of first wind speed data and M sets of second wind speed data to obtain N sets of first target wind speed data and N sets of second target wind speed data. The second acquisition module is used to calculate the warning value based on N sets of the first target wind speed data and N sets of the second target wind speed data; The fault diagnosis module is used to diagnose faults in the first anemometer and the second anemometer based on the warning value. Where M > N, and M and N are both positive integers.

5. A fault diagnosis device for anemometers in wind turbine generator sets, characterized in that, include: Processor and memory; The processor reads executable program code stored in the memory to run a program corresponding to the executable program code, so as to implement the anemometer fault diagnosis method for wind turbine generator sets as described in any one of claims 1-3.

6. A wind turbine generator set, characterized in that, include: The anemometer fault diagnosis device for wind turbine generator sets as described in claim 5.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the anemometer fault diagnosis method for wind turbine generator sets as described in any one of claims 1-3.

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