CN115929569A - Fault diagnosis method for variable pitch system of wind turbine generator - Google Patents
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Abstract
The invention discloses a fault diagnosis method for a variable pitch system of a wind turbine generator, which comprises the following steps: acquiring an actual value and a design value of a wind energy utilization coefficient of a wind turbine generator; calculating the residual error of the wind energy utilization coefficient according to the actual value and the design value; judging whether a variable pitch system of the wind turbine generator is in an abnormal state or not based on a preset threshold value of a sliding time window according to the residual error of the wind energy utilization coefficient; when the wind turbine generator pitch system is in an abnormal state, the abnormal reason of the wind turbine generator pitch system is obtained based on the consistency of the pitch angle, the consistency of the pitch torque and the consistency of the temperature of the pitch motor. According to the method, whether the state of the variable pitch system is abnormal or not is judged by calculating the residual error between the actual value and the design value of the wind energy utilization coefficient, and if the state is abnormal, abnormal analysis is further performed, so that field operation and maintenance personnel are helped to find the abnormal state unit, the investigation range is reduced, the operation and maintenance efficiency is improved, and serious fault accidents of the variable pitch system are avoided.
Description
Technical Field
The invention relates to a fault diagnosis method for a variable pitch system of a wind turbine generator, and belongs to the technical field of variable pitch systems of wind turbine generators.
Background
Clean low carbon is the inevitable trend of global energy transformation development, and wind power is the main energy for constructing a novel power system, and is the main force for supporting the power system to decarbonize first and further promote the energy system. The wind power installation machine is lifted on a large scale, but the operation and maintenance staff in the wind power industry have fewer staff and higher operation and maintenance working pressure.
The variable pitch system is an important component of the wind generating set, not only ensures the effective utilization of wind energy by the wind generating set, but also is responsible for ensuring the self safety of the fan under extreme conditions and avoiding overspeed runaway and tower collapse accidents. Meanwhile, the variable pitch system is one of subsystems with the highest failure occurrence rate of the wind turbine generator, is arranged at the high altitude which is dozens of meters away from the ground, and is difficult to maintain after failure and high in maintenance cost. When the wind power SCADA sends out system alarm, the variable pitch system is usually damaged irreversibly, so the abnormal state identification and diagnosis of the variable pitch system of the wind turbine are needed, the preventive maintenance is carried out before major accidents happen, meanwhile, the excessive maintenance is avoided when the healthy state of the variable pitch system is kept, the possibility of accidents of the variable pitch system of the wind turbine is reduced, and the operation and maintenance cost of the wind turbine is saved.
The prior art mainly comprises the following schemes: 1. and acquiring abnormal alarm and related fault information of the pitch control system through the SCADA of the wind turbine generator. The method has hysteresis, when the SCADA gives out fault alarm, the fault of the variable pitch system often happens, the unit is possibly shut down and large loss is caused, the cost for overhauling and maintaining the unit is very high, and the caused loss can not be recovered. 2. The method comprises the steps of carrying out characteristic screening of state recognition of the variable pitch system through an artificial intelligence algorithm, carrying out training and verification on an early warning diagnosis model through a large amount of data to obtain an early warning diagnosis model, and inputting operation data into the model to obtain an early warning diagnosis result. The scheme lacks the support of a physical theory of a unit, the accuracy of the model is greatly influenced by the quality of sample data, a selected algorithm and parameter adjustment, the generated early warning diagnosis model cannot be universal, the condition of false alarm and missing alarm generally exists, and the actual use is difficult.
Chinese patent document CN202110689916.2 discloses a fault determination method and system for a variable pitch system of a wind turbine generator, a dynamic model and a convolutional neural network of the variable pitch system of the wind turbine generator are combined, a fan variable pitch system fault diagnosis method based on the convolutional neural network is provided, and a system fault diagnosis result can be obtained by comparing a pitch angle estimation value given by the convolutional neural network with a pitch angle output by the actual variable pitch system of the wind turbine generator. The technical scheme does not relate to the aspects of unit SCADA data preprocessing, abnormal analysis of a variable pitch system, consistency analysis of the pitch angle, temperature consistency analysis of a variable pitch motor and the like according to the speed ratio of the blade tip, the pitch angle and the wind energy utilization coefficient, the output result of the method is whether the system has a fault or not, and the fault reason is not further analyzed.
Chinese patent document CN202110656862.X discloses a pitch system fault prediction method based on a neural network, which comprises the steps of utilizing operating data of an SCADA system to carry out data preprocessing, dividing the data into a training set and a test set, constructing a process memory matrix, constructing an initial pitch fault diagnosis model, utilizing the test set to train the pitch fault diagnosis model, obtaining a pitch fault diagnosis model, and inputting the operating data of a pitch system into the pitch fault diagnosis model to obtain a fault diagnosis result. The technical scheme does not relate to a specific wind turbine SCADA data preprocessing method, only marks fault and normal data, does not relate to the judgment of the abnormal operation state of the variable pitch system in a wind energy utilization coefficient mode, and does not relate to the aspects of pitch angle consistency analysis, variable pitch motor temperature consistency analysis and the like.
The information disclosed in this background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art that is already known to a person skilled in the art.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provide a fault diagnosis method for a variable pitch system of a wind turbine generator, which is used for judging whether the state of the variable pitch system is abnormal or not by calculating the residual error between the actual value and the design value of a wind energy utilization coefficient, and further performing abnormal analysis if the state is abnormal, so that field operation and maintenance personnel can be helped to find the abnormal state of the variable pitch system, the investigation range is reduced, the operation and maintenance efficiency is improved, and serious fault accidents of the variable pitch system are avoided.
In order to achieve the purpose, the invention adopts the following technical scheme:
the invention discloses a fault diagnosis method for a variable pitch system of a wind turbine generator, which comprises the following steps:
acquiring an actual value and a design value of a wind energy utilization coefficient of a wind turbine generator;
calculating a wind energy utilization coefficient residual error according to the actual value and the design value;
judging whether the variable pitch system of the wind turbine generator is in an abnormal state or not based on a preset threshold value of a sliding time window according to the wind energy utilization coefficient residual error;
and when the wind turbine generator pitch system is in an abnormal state, obtaining the abnormal reason of the wind turbine generator pitch system based on the diagnosis and analysis of the consistency of the pitch angle, the consistency of the pitch torque and the temperature consistency of the pitch motor.
Further, the obtaining of the actual value and the design value of the wind energy utilization coefficient of the wind turbine generator system includes the following steps:
acquiring basic data and real-time parameters of a wind turbine generator;
judging whether the wind turbine generator is in a steady-state wind speed working condition or not according to the real-time parameters;
the method comprises the steps of responding to the condition that the wind turbine generator is in a steady-state wind speed, and obtaining the air density of the wind turbine generator; calculating to obtain an actual value of the wind energy utilization coefficient of the wind turbine generator according to the air density and the basic data;
and calculating a tip speed ratio according to the basic data and the real-time parameters, and designing a curve based on a preset coefficient to obtain a design value of the wind energy utilization coefficient of the wind turbine generator.
Further, the expression of the actual value of the wind energy utilization coefficient of the wind turbine generator is as follows:
wherein, C ρ An actual value representing the wind energy utilization factor; ρ represents the air density in kg/m 3 (ii) a Nu represents the actual wind speed and has the unit of m/s; r represents the length of the fan blade and is m; pi represents a circumferential ratio; p represents the fan output power in W.
Further, the method for acquiring the air density comprises the steps of directly acquiring SCADA data of the wind turbine generator, and/or calculating the air density according to real-time parameters of the wind turbine generator;
the expression of the air density is as follows:
where ρ represents the air density in kg/m 3 (ii) a B represents the atmospheric pressure of the current environment of the wind turbine generator in unit Pa; t represents ambient temperature in units of; r 0 The gas constant of the drying air is represented and is 287.05J/(kg.K).
Further, the expression of the tip speed ratio is as follows:
wherein λ represents a tip speed ratio of the fan; pi represents a circumferential ratio; r represents the length of the fan blade and is m; n is wt Expressing the rotating speed of the wind wheel in r/min; v represents the actual wind speed in m/s.
Further, judging whether the pitch system of the wind turbine generator is in an abnormal state or not, comprising the following steps:
obtaining a residual error threshold value in each time window based on a 3 sigma principle according to the width and the sliding step length of a preset time window;
and in response to the fact that the residual of the wind energy utilization coefficient is larger than the maximum value of the residual threshold value or smaller than the minimum value of the residual threshold value, judging that the variable pitch system of the wind turbine generator is in an abnormal state.
Further, the expression of the wind energy utilization coefficient residual is as follows:
d＝|C P -C P '|
wherein d represents the residual of the wind energy utilization coefficient; c P Representing an actual value of a wind energy utilization coefficient of the wind turbine; c P ' represents a design value of a wind energy utilization coefficient of the wind turbine;
the expression of the maximum value of the residual threshold is as follows:
the expression for the minimum value of the residual threshold is as follows:
wherein d is max Represents the maximum value of the residual threshold;
representing the mean of the residuals within a time window; s represents the mean residual error value in a time window; d min Represents the minimum of the residual threshold.
Further, the diagnostic analysis of the consistency of the pitch angle comprises the following steps:
acquiring historical pitch angle data of a plurality of blades preprocessed by a wind turbine generator; wherein the preprocessing comprises data screening, data cleaning and data alignment;
obtaining a first ICC value based on a single measurement standard model of coefficients in an ICC group according to the historical pitch angle data;
when the first ICC value is larger than or equal to a preset first threshold value, determining that no abnormal condition exists in the variable pitch angle of the variable pitch system of the wind turbine generator; and when the first ICC value is smaller than a preset first threshold value, determining that the variable pitch angle of the variable pitch system of the wind turbine generator is abnormal.
Further, the diagnostic analysis of the pitch torque consistency comprises the following steps:
acquiring historical pitch variation torque data of a plurality of blades preprocessed by a wind turbine generator; wherein the preprocessing comprises data screening, data cleaning and data alignment;
obtaining a second ICC value based on a single measurement standard model of a coefficient in an ICC group according to the historical variable pitch torque data;
when the second ICC value is larger than or equal to a preset second threshold value, determining that abnormal conditions do not exist in the variable pitch torque of the variable pitch system of the wind turbine generator; and when the second ICC value is smaller than a preset second threshold value, determining that abnormal conditions exist in the variable pitch torque of the variable pitch system of the wind turbine generator.
Further, the diagnosis and analysis of the temperature consistency of the variable pitch motor comprises the following steps:
acquiring historical variable pitch motor temperature data of a plurality of blades preprocessed by a wind turbine generator; wherein the preprocessing comprises data screening, data cleaning and data alignment;
obtaining a third ICC value based on an ICC group internal coefficient single measurement standard model according to the historical variable pitch motor temperature data;
when the third ICC value is larger than or equal to a preset third threshold value, determining that the temperature of a variable pitch motor of a variable pitch system of the wind turbine generator is not abnormal; and when the third ICC value is smaller than a preset third threshold value, determining that the temperature of a variable pitch motor of the variable pitch system of the wind turbine generator is abnormal.
Compared with the prior art, the invention has the following beneficial effects:
according to the method, whether the state of the variable pitch system is abnormal or not is judged by calculating the residual error between the actual value and the design value of the wind energy utilization coefficient, and if the state is abnormal, abnormal analysis of the consistency of the variable pitch angle, the consistency of the variable pitch torque and the temperature consistency of the variable pitch motor is further performed, so that field operation and maintenance personnel are helped to find the abnormal state unit, the investigation range is reduced, the operation and maintenance efficiency is improved, and serious fault accidents of the variable pitch system are avoided.
Drawings
FIG. 1 is a flow chart of a wind turbine generator pitch system fault diagnosis method.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
Examples
The embodiment provides a fault diagnosis method for a variable pitch system of a wind turbine generator, which comprises the following steps:
acquiring an actual value and a design value of a wind energy utilization coefficient of a wind turbine generator;
calculating a wind energy utilization coefficient residual error according to the actual value and the design value;
judging whether a variable pitch system of the wind turbine generator is in an abnormal state or not based on a preset threshold value of a sliding time window according to the wind energy utilization coefficient residual error;
and when the wind turbine generator pitch system is in an abnormal state, obtaining the abnormal reason of the wind turbine generator pitch system based on the diagnosis and analysis of the consistency of the pitch angle, the consistency of the pitch torque and the temperature consistency of the pitch motor.
The technical conception of the invention is as follows: whether the state of the variable pitch system is abnormal is judged by calculating the residual error between the actual value and the design value of the wind energy utilization coefficient, and if the state is abnormal, the abnormal analysis of the consistency of the variable pitch angle, the consistency of the variable pitch torque and the temperature consistency of the variable pitch motor is further carried out, so that the abnormal state machine set is found by field operation and maintenance personnel, the investigation range is reduced, the operation and maintenance efficiency is improved, and the serious fault accident of the variable pitch system is avoided.
The specific steps are as follows, as shown in figure 1:
step one.
And acquiring basic data and real-time parameters of the wind turbine generator.
Acquiring real-time operation parameters of the wind turbine generator set by using a supervisory control and data acquisition (SCADA) system (data acquisition and monitoring system), wherein the real-time operation parameters comprise the state of the wind turbine generator set, the wind speed, the pitch angle, the output power, the ambient temperature, the atmospheric pressure and the rotating speed of a wind wheel; and acquiring the length of the wind turbine blade according to the basic data of the wind turbine.
Because the sensor installed in the unit may have abnormal conditions, the abnormal value judgment needs to be performed on the acquired real-time data, and the data which obviously exceeds the data threshold value is cleaned.
It should be noted that, assuming that the wind turbine SCADA data provides the air density value, the ambient temperature and the atmospheric pressure are not required.
And step two.
(1) And judging the current running state of the unit according to the unit state parameters, if the unit is in a non-stop state, continuing to perform the next calculation, if the unit is in a non-power generation state, not performing the next calculation, wherein the non-power generation state comprises standby, fault stop, overhaul stop, communication interruption and the like, and when the unit state acquired next time is a power generation state, continuing to perform the next calculation.
(2) And (5) judging the steady-state wind speed condition.
The steady-state wind speed determination conditions are as follows: defining the steady-state wind speed working condition at the moment t as follows: [ t-2min, t]Wind speed V within time max -V min Is less than 2m/s. Wherein V max The maximum value V of the wind speed of the wind power generation set in a time interval 2 minutes before the steady state judgment moment min And for the minimum wind speed of the wind power generation set in the time interval 2 minutes before the steady-state judgment moment, continuing to further calculate when the wind power generation set is in the steady-state wind speed, and skipping the current calculation for the unsteady-state wind speed until the wind power generation set is judged to be in the steady-state wind speed working condition for further calculation next time.
(3) And calculating the current air density of the unit according to the current ambient temperature and atmospheric pressure parameters of the unit. The method for acquiring the air density comprises the steps of directly acquiring SCADA data of the wind turbine generator and/or calculating the air density according to real-time parameters of the wind turbine generator.
In actual production, only a few SCADA data provide the air density value of the current unit, and if the SCADA data do not provide the air density, the air density is calculated according to the following mode:
wherein ρ represents an air density in kg/m 3 (ii) a B represents the atmospheric pressure of the current environment of the wind turbine generator in unit Pa; t represents ambient temperature in units of; r is 0 The gas constant of the dry air is represented by 287.05J/(kg. K).
(4) And calculating the wind energy utilization coefficient.
Wherein, C ρ An actual value representing the wind energy utilization factor; ρ represents the air density in kg/m 3 (ii) a Nu represents the actual wind speed and has the unit of m/s; r represents the length of the fan blade and is m; pi represents a circumferential ratio; p represents the output power of the fan and has the unit of W.
And step three.
Judging the state of a variable pitch system of the wind turbine generator: and judging the running state of the variable pitch system of the unit according to the actual value of the wind energy utilization coefficient obtained by calculation and by combining a tip speed ratio-wind energy utilization coefficient design value provided by a manufacturer.
(1) Calculating the tip speed ratio of the current set
Wherein λ represents a tip speed ratio of the fan; pi represents a circumferential ratio; r represents the length of the fan blade and is m; n is wt The rotating speed of the wind wheel is expressed in unit r/min; v represents the actual wind speed in m/s.
(2) Searching a design curve of the tip speed ratio-wind energy utilization coefficient provided by a manufacturer according to the current pitch angle and the tip speed ratio of the unit to obtain a design value C of the wind energy utilization coefficient of the unit under the current working condition P '。
(3) Calculating design value C of wind energy utilization coefficient P ' and actual value C ρ And determining a threshold value according to a sliding time window method, and judging the current variable pitch system state of the unit.
Firstly, calculating a design value and an actual value residual d of a wind energy utilization coefficient:
d＝|C P -C P '|
wherein d represents the residual of the wind energy utilization coefficient; c P Representing an actual value of a wind energy utilization coefficient of the wind turbine; c P ' represents a design value of a wind energy utilization coefficient of the wind turbine;
secondly, determining the width n of the time window, namely the number of data in one time window and the sliding step length t, and obtaining a residual error threshold value in each time window based on a 3 sigma principle. And in response to the fact that the residual of the wind energy utilization coefficient is larger than the maximum value of the residual threshold value or smaller than the minimum value of the residual threshold value, judging that the variable pitch system of the wind turbine generator is in an abnormal state.
The expression for the maximum value of the residual threshold is as follows:
the expression for the minimum of the residual thresholds is as follows:
wherein,
d max represents the maximum value of the residual threshold;
representing the mean of the residuals within a time window; s represents the mean residual error value in a time window; d is a radical of min Represents the minimum of the residual threshold; n represents the width of the time window; t represents a sliding step; d i Representing the ith residual.
The width of the time window in this embodiment is preferably 300, and the sliding step size is preferably 1, which can be adjusted according to actual production needs.
And finally, if the state of the variable pitch system is judged to be abnormal, continuing the subsequent diagnosis process, and if the state of the variable pitch system is judged to be normal, skipping the subsequent calculation until the state of the variable pitch system is judged to be abnormal.
Step four: and (5) carrying out abnormity diagnosis on the variable pitch system. The abnormal reasons of the pitch system are diagnosed in the aspects of the consistency of the pitch angle, the consistency of the pitch torque, the consistency of the temperature of the pitch motor and the like, and the investigation range of the abnormal reasons is reduced.
(1) Uniformity of pitch angle
Acquiring historical pitch angle data of a plurality of blades preprocessed by a wind turbine generator; wherein the preprocessing comprises data screening, data cleaning and data alignment;
obtaining a first ICC value based on a single measurement standard model of coefficients in an ICC group according to the historical pitch angle data;
when the first ICC value is larger than or equal to a preset first threshold value, determining that no abnormal condition exists in the variable pitch angle of the variable pitch system of the wind turbine generator; and when the first ICC value is smaller than a preset first threshold value, determining that the variable pitch angle of the variable pitch system of the wind turbine generator is abnormal.
The method specifically comprises the following steps:
and acquiring the variable pitch angle data of three blades of the target wind turbine within five days, and preprocessing the data. Data preprocessing includes data screening, data cleansing, and data alignment. The data screening mainly comprises the steps of eliminating data in a non-power generation state; the data cleaning mainly comprises the step of cleaning data obviously exceeding a limit value; data alignment is required to ensure that the data timestamps of the set of pitch angles participating in the calculation are consistent.
The method comprises the steps that an ICC (C, 1) single measurement standard model is adopted to analyze the absolute consistency of the variable pitch angle, the number of fan blades is generally 3, so that C =3, and according to the production practice and an ICC evaluation standard, when the value of the ICC is greater than or equal to 0.9, the consistency of the pitch angle is considered to be good, and the abnormal condition of the variable pitch angle does not exist; when the ICC value is smaller than 0.9, the consistency of the pitch angle is considered to be poor, and operation and maintenance personnel are advised to check the pitch meshing teeth, check the pitch bearing and reset the position of the limit switch of the pitch system.
(2) Pitch torque uniformity
The diagnosis and analysis of the consistency of the variable pitch torque comprises the following steps:
acquiring historical pitch variation torque data of a plurality of blades preprocessed by a wind turbine generator; wherein the preprocessing comprises data screening, data cleaning and data alignment;
obtaining a second ICC value based on a single measurement standard model of a coefficient in an ICC group according to the historical variable pitch torque data;
when the second ICC value is larger than or equal to a preset second threshold value, determining that abnormal conditions do not exist in the variable pitch torque of the variable pitch system of the wind turbine generator; and when the second ICC value is smaller than a preset second threshold value, determining that abnormal conditions exist in the variable pitch torque of the variable pitch system of the wind turbine generator.
The method comprises the following specific steps:
and acquiring the variable pitch torque data of three blades of the target wind turbine within five days, and preprocessing the data. Data preprocessing includes data screening, data cleansing, and data alignment. The data screening mainly comprises the steps of eliminating data in a non-power generation state; the data cleaning mainly comprises the step of cleaning data obviously exceeding a limit value; data alignment is required to ensure that the data timestamps of the set of pitch torques participating in the calculation are consistent.
Carrying out consistency analysis on the variable pitch torques of the three blades of the target unit within five days by utilizing ICC (C, 1), and according to production practice and ICC evaluation standards, when the value of the ICC is greater than or equal to 0.9, considering that the consistency of the variable pitch torques is good and the mechanical abnormal condition of a variable pitch system does not exist; when the ICC value is smaller than 0.9, the consistency of the variable pitch torque is considered to be poor, and at the moment, operation and maintenance personnel are recommended to check the variable pitch bearing, inject a lubricant, fasten the bearing, replace worn parts and the like.
(3) And (5) the temperature of the variable pitch motor is consistent.
The diagnosis and analysis of the temperature consistency of the variable pitch motor comprises the following steps:
acquiring historical variable-pitch motor temperature data of a plurality of blades preprocessed by a wind turbine generator; wherein the preprocessing comprises data screening, data cleaning and data alignment;
obtaining a third ICC value based on an ICC group internal coefficient single measurement standard model according to the historical variable pitch motor temperature data;
when the third ICC value is larger than or equal to a preset third threshold value, the temperature of a variable pitch motor of a variable pitch system of the wind turbine generator is determined to be abnormal; and when the third ICC value is smaller than a preset third threshold value, determining that the temperature of a variable pitch motor of the variable pitch system of the wind turbine generator is abnormal.
The method comprises the following specific steps:
and acquiring temperature data of three blade pitch-variable motors of the target wind turbine generator within five days, and preprocessing the data. Data preprocessing includes data screening, data cleansing, and data alignment. The data screening mainly comprises the steps of eliminating data in a non-power generation state; the data cleaning mainly comprises the step of cleaning data obviously exceeding a limit value; data alignment is required to ensure that the time stamps of the data for a set of pitch motor temperatures involved in the calculation are consistent.
Utilizing ICC (C, 1) to carry out consistency analysis on the temperature of the variable pitch motor of the three blades in five days of the target unit, and according to the actual production and ICC evaluation standard, when the value of the ICC is more than or equal to 0.9, considering that the temperature consistency of the variable pitch motor is good and the abnormal condition of the variable pitch motor does not exist; when the ICC value is less than 0.9, the consistency of the variable pitch motor is considered to be poor, and operation and maintenance personnel are advised to check the variable pitch motor and confirm whether the short circuit and insulation aging conditions exist in the motor; checking whether the variable-pitch gearbox is jammed; it is checked whether the encoders are synchronized.
In summary, in the scheme of the present invention, the SCADA data of the wind turbine generator, such as wind speed, air density, wind wheel rotation speed, output power, ambient temperature, pitch angle, etc., is used to calculate the actual wind energy utilization coefficient of the wind turbine generator, calculate the residual between the actual wind energy utilization coefficient and the design value by using the relationship between the tip speed ratio and the wind energy utilization coefficient provided by the manufacturer, determine the residual threshold by using the sliding time window mode, determine whether the state of the pitch system is abnormal, perform consistent analysis on the pitch angle, the pitch torque and the pitch motor temperature by using the consistency determination mode in the ICC group if the state is abnormal, perform abnormal analysis on the pitch motor and the displacement sensor, determine the failure cause, and provide the relevant operation and maintenance suggestions.
The method can be used for diagnosing the fault of abnormal state recognition of the variable pitch system of the wind turbine generator on line, is simple in calculation method, does not need to accumulate long-time running data, avoids the defects of large workload of sample marking, difficult parameter adjustment, poor model applicability and the like when an intelligent model is used for early warning diagnosis of the variable pitch system, solves the problems of large workload, high safety risk, high delay, waste of wind resources and the like of the conventional regular manual detection method of the variable pitch system, can help field operation and maintenance personnel to find the abnormal state machine set, reduce the detection range, improve the operation and maintenance efficiency and avoid serious fault accidents of the variable pitch system.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only of the preferred embodiments of the present invention, and it should be noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the invention and these are intended to be within the scope of the invention.
Claims (10)
1. A fault diagnosis method for a variable pitch system of a wind turbine generator is characterized by comprising the following steps:
acquiring an actual value and a design value of a wind energy utilization coefficient of a wind turbine generator;
calculating a wind energy utilization coefficient residual error according to the actual value and the design value;
judging whether the variable pitch system of the wind turbine generator is in an abnormal state or not based on a preset threshold value of a sliding time window according to the wind energy utilization coefficient residual error;
and when the wind turbine generator pitch system is in an abnormal state, obtaining the abnormal reason of the wind turbine generator pitch system based on the diagnosis and analysis of the consistency of the pitch angle, the consistency of the pitch torque and the temperature consistency of the pitch motor.
2. The method for diagnosing the fault of the variable pitch system of the wind turbine generator according to claim 1, wherein the step of obtaining the actual value and the design value of the wind energy utilization coefficient of the wind turbine generator comprises the following steps:
acquiring basic data and real-time parameters of a wind turbine generator;
judging whether the wind turbine generator is in a steady-state wind speed working condition or not according to the real-time parameters;
the method comprises the steps of responding to the condition that the wind turbine generator is in a steady-state wind speed, and obtaining the air density of the wind turbine generator; calculating to obtain an actual value of the wind energy utilization coefficient of the wind turbine generator according to the air density and the basic data;
and calculating a tip speed ratio according to the basic data and the real-time parameters, and designing a curve based on a preset coefficient to obtain a design value of the wind energy utilization coefficient of the wind turbine generator.
3. The wind turbine generator system pitch system fault diagnosis method according to claim 2, wherein the expression of the actual value of the wind energy utilization coefficient of the wind turbine generator is as follows:
wherein, C ρ An actual value representing the wind energy utilization factor; ρ represents the air density in kg/m 3 (ii) a V represents the actual wind speed in m/s; r represents the length of the fan blade and is m; pi represents a circumferential ratio; p represents the fan output power in W.
4. The wind turbine generator pitch system fault diagnosis method according to claim 2, wherein the air density acquisition method comprises directly acquiring from SCADA data of the wind turbine generator and/or calculating the air density according to real-time parameters of the wind turbine generator;
the expression for the air density is as follows:
where ρ represents the air density in kg/m 3 (ii) a B represents the atmospheric pressure of the current environment of the wind turbine generator in unit Pa; t represents ambient temperature in units of; r 0 The gas constant of the dry air is represented by 287.05J/(kg. K).
5. The method for fault diagnosis of the pitch system of the wind turbine generator set according to claim 2, wherein the expression of the tip speed ratio is as follows:
wherein λ represents a tip speed ratio of the fan; pi represents a circumferential ratio; r represents the length of the fan blade and is m; n is a radical of an alkyl radical wt Expressing the rotating speed of the wind wheel in r/min; v represents the actual wind speed in m/s.
6. The method for diagnosing the fault of the variable pitch system of the wind turbine generator according to claim 1, wherein the step of judging whether the variable pitch system of the wind turbine generator is in an abnormal state comprises the following steps:
obtaining a residual error threshold value in each time window based on a 3 sigma principle according to the width and the sliding step length of a preset time window;
and in response to the fact that the residual of the wind energy utilization coefficient is larger than the maximum value of the residual threshold value or smaller than the minimum value of the residual threshold value, judging that the variable pitch system of the wind turbine generator is in an abnormal state.
7. The method for fault diagnosis of a wind turbine generator pitch system according to claim 6, wherein the wind energy utilization coefficient residual error is expressed as follows:
d＝|C P -C P '|
wherein d represents a wind energy utilization coefficient residual error; c P Representing an actual value of a wind energy utilization coefficient of the wind turbine; c P ' represents a design value of a wind energy utilization coefficient of the wind turbine;
the expression of the maximum value of the residual threshold is as follows:
the expression for the minimum value of the residual threshold is as follows:
wherein d is max Represents the maximum value of the residual threshold;
representing the mean of the residuals within a time window; s represents the mean residual error value in a time window; d min Represents the minimum of the residual threshold.
8. The method for diagnosing the fault of the pitch system of the wind turbine generator set according to claim 1, wherein the diagnosis and analysis of the consistency of the pitch angle comprises the following steps:
acquiring historical pitch angle data of a plurality of blades preprocessed by a wind turbine generator; wherein the preprocessing comprises data screening, data cleaning and data alignment;
obtaining a first ICC value based on a single measurement standard model of a coefficient in an ICC group according to the historical pitch angle data;
when the first ICC value is larger than or equal to a preset first threshold value, determining that no abnormal condition exists in the variable pitch angle of the variable pitch system of the wind turbine generator; and when the first ICC value is smaller than a preset first threshold value, determining that the variable pitch angle of the variable pitch system of the wind turbine generator is abnormal.
9. The method for diagnosing the fault of the pitch system of the wind turbine generator set according to claim 1, wherein the diagnosis and analysis of the consistency of the pitch torque comprises the following steps:
acquiring historical pitch variation torque data of a plurality of blades preprocessed by a wind turbine generator; wherein the preprocessing comprises data screening, data cleaning and data alignment;
obtaining a second ICC value based on a single measurement standard model of a coefficient in an ICC group according to the historical variable pitch torque data;
when the second ICC value is larger than or equal to a preset second threshold value, determining that abnormal conditions do not exist in the variable pitch torque of the variable pitch system of the wind turbine generator; and when the second ICC value is smaller than a preset second threshold value, determining that abnormal conditions exist in the variable pitch torque of the variable pitch system of the wind turbine generator.
10. The wind turbine generator system pitch system fault diagnosis method according to claim 1, wherein the diagnosis and analysis of the temperature consistency of the pitch motor comprises the following steps:
acquiring historical variable-pitch motor temperature data of a plurality of blades preprocessed by a wind turbine generator; wherein the preprocessing comprises data screening, data cleaning and data alignment;
obtaining a third ICC value based on an ICC group internal coefficient single measurement standard model according to the historical variable pitch motor temperature data;
when the third ICC value is larger than or equal to a preset third threshold value, determining that the temperature of a variable pitch motor of a variable pitch system of the wind turbine generator is not abnormal; and when the third ICC value is smaller than a preset third threshold value, determining that the temperature of a variable pitch motor of the variable pitch system of the wind turbine generator is abnormal.
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