CN111287912A - Fault diagnosis method for variable pitch system of wind driven generator - Google Patents

Fault diagnosis method for variable pitch system of wind driven generator Download PDF

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CN111287912A
CN111287912A CN202010100372.7A CN202010100372A CN111287912A CN 111287912 A CN111287912 A CN 111287912A CN 202010100372 A CN202010100372 A CN 202010100372A CN 111287912 A CN111287912 A CN 111287912A
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variable pitch
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叶伟文
李茂东
李录平
杨波
刘瑞
王志刚
伍振凌
钟志强
张志达
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Guangzhou Special Equipment Testing And Research Institute Guangzhou Special Equipment Accident Investigation Technology Center Guangzhou Elevator Safety Operation Monitoring Center
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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
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    • F03D17/00—Monitoring or testing of wind motors, e.g. diagnostics
    • G—PHYSICS
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    • G06Q50/06—Energy or water supply
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
    • F05B2260/00—Function
    • F05B2260/80—Diagnostics
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
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    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
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Abstract

The invention provides a fault diagnosis method for a variable pitch system of a wind driven generator, which comprises the following steps: step 1: acquiring historical operating data of an SCADA system of the wind driven generator; step 2: constructing a fault characteristic model by using historical operating data of the SCADA system; and step 3: constructing a fault diagnosis model by using the fault feature model; and 4, step 4: acquiring real-time fault alarm data of an SCADA system of the wind driven generator, inputting the real-time fault alarm data into a fault characteristic model, and calculating to acquire real-time fault characteristics; and 5: and (4) inputting the real-time fault characteristics obtained in the step (4) into the fault diagnosis model to obtain a fault diagnosis result. According to the fault diagnosis method for the variable pitch system of the wind driven generator, the fault characteristics are extracted by using the wind driven generator operation data measured by the SCADA and are input into the fault model, so that the real-time diagnosis of the fault reason and the fault position of the wind driven generator is realized.

Description

Fault diagnosis method for variable pitch system of wind driven generator
Technical Field
The invention relates to the field of fault diagnosis of wind driven generators, in particular to a fault diagnosis method for a variable pitch system of a wind driven generator.
Background
In the prior art, a wind driven generator is an ideal energy collecting device, and the installation environment of a wind power generation system is a remote and unsmooth unmanned area or sea, so that the working environment of the wind driven generator is very severe, and the stress condition of the wind driven generator is complex and variable. Referring to fig. 1 and 2, the main structure of the wind turbine includes: the wind power generation system comprises a nacelle 1, a tower body 2 and blades 3, wherein the tower body 2 is arranged on the ground, the nacelle 1 is arranged on the tower body 2 and is vertical to the tower body, and the blades 3 comprise ground to third blades and are arranged on the nacelle 1. When the wind driven generator works, the blades 3 are driven by external wind to rotate, wind energy is converted into kinetic energy of the blades, and the kinetic energy is transmitted into the wind driven generator to finish wind energy collection. The variable pitch system comprises a variable pitch mechanical component, a variable pitch power supply system and a variable pitch control system, wherein a variable pitch system 4 and a hub 5 are arranged in a cabin body of the cabin 1, the hub 5 is installed on the inner side of the front end of the cabin body of the cabin 1, the hub 5 is connected with blades 3 through a variable pitch bearing, the variable pitch system 4 is arranged in the hub 5, the variable pitch system 4 comprises a first variable pitch system, a second variable pitch system, a third variable pitch system and a third variable pitch system, the first variable pitch system, the second variable pitch system and the third variable pitch system are respectively connected with the first blade, the second variable pitch system and the third blade through a variable pitch bearing, each variable pitch system comprises a variable pitch mechanical component, a. The variable-pitch mechanical component mainly comprises a gear box 6 and a variable-pitch bearing, the gear box is driven by the variable-pitch power supply system and is connected with the variable-pitch bearing through a main shaft (namely a low-speed shaft), and the angle of a corresponding blade can be adjusted through the variable-pitch bearing.
In actual operation, due to randomness and uncertainty of wind speed and wind direction, the variable pitch system is easy to damage when performing variable pitch action along with frequent change of the wind speed. Meanwhile, the fault problem of other parts of the fan often needs the variable pitch system to perform brake braking to protect the safety of the unit, which causes the fault rate of the variable pitch system in the actual fault operation of the variable pitch system to be always high, easily causes huge safety accidents, and affects the safe production and economic benefit of the wind power plant. Therefore, real-time monitoring and fault early warning of the variable pitch system are necessary.
In the prior art, an SCADA (supervisory Control and Data acquisition) system is adopted to monitor and Control wind power generation equipment, and can acquire various fan operation Data, adjust operation parameters of the wind power generation system and realize fault alarm. Specifically, the SCADA system may measure an average wind speed, a wind direction signal, and a pitch angle (pitch angle measurement data includes three rotary encoders, also referred to as an a encoder, and three redundant encoders, also referred to as a B encoder, and a measured pitch angle), the a encoders are respectively disposed at top ends of three pitch motors of the wind turbine generator, and are configured to measure the pitch angle of each blade according to motor rotation information, the B encoders are respectively disposed on a hub and are respectively engaged with the pitch bearing through a gear, and are capable of measuring the pitch angle of each blade according to rotation information of a low-speed shaft, a low-speed shaft rotation speed, a generator active power, a voltage and a current of the pitch motor, a pitch motor temperature, a blade converter temperature, a pitch battery voltage, a pitch bearing oil pump outlet oil pressure, and a pitch gear oil pump outlet oil pressure. However, although the SCADA system can acquire the various kinds of collected information, the fault alarm provided by the SCADA system usually contains a lot of mixed information, and the user cannot specify the true fault cause and locate the fault position, so that the fault can not be timely and accurately repaired.
Disclosure of Invention
Based on the above, the invention aims to provide a fault diagnosis method for a variable pitch system of a wind driven generator, which can diagnose the cause of the fault of a wind turbine and locate the fault position.
A fault diagnosis method for a pitch system of a wind driven generator comprises the following steps: step 1: acquiring historical operating data of an SCADA system of the wind driven generator; step 2: constructing a fault characteristic model by using historical operating data of the SCADA system; and step 3: constructing a fault diagnosis model by using the fault feature model; and 4, step 4: acquiring real-time fault alarm data of an SCADA system of the wind driven generator, inputting the real-time fault alarm data into a fault characteristic model, and calculating to acquire real-time fault characteristics; and 5: and (4) inputting the real-time fault characteristics obtained in the step (4) into the fault diagnosis model to obtain a fault diagnosis result.
According to the fault diagnosis method for the variable pitch system of the wind driven generator, the fault characteristics are extracted by using the wind driven generator operation data measured by the SCADA system and the fault characteristics are input into the fault model to complete fault diagnosis, so that the real-time diagnosis of the fault reason and the fault position of the wind driven generator is realized.
Further, in step 1, the historical operating data of the SCADA system includes: the wind power generator comprises one or more of average wind speed outside a nacelle of the wind power generator, wind direction, pitch angles of first to third blades of the wind power generator, rotating speed of a low-speed shaft, active power of the generator, voltage and current of a variable pitch motor, temperature of the variable pitch motor, temperature of a blade converter, voltage of a variable pitch battery, oil pressure at an outlet of a variable pitch bearing grease pump and oil pressure at an outlet of the variable pitch gear grease pump.
Further, the method for extracting the fault features comprises the following steps:
the method for constructing the fault feature model comprises the following steps:
1) constructing a theoretical deviation fault characteristic model of the pitch angle:
the pitch angle data of the blades of the wind driven generator comprise pitch angle data measured by an encoder A
Figure BDA0002386678470000021
And B encoder data measured by the encoder
Figure BDA0002386678470000022
Acquiring a group of average wind speed data in historical operation of a fan, and acquiring each average wind speed data
Figure BDA0002386678470000023
The following equations are substituted, respectively, to solve for a set of corresponding pitch angles β:
Figure BDA0002386678470000024
Figure BDA0002386678470000025
wherein rho is air density, η is transmission efficiency, R is wind wheel diameter, P is rated power of the wind driven generator, c1-c8Is the characteristic coefficient of the wind wheel, lambdaiThe tip speed of the ith blade is the tip speed of the ith blade, and lambda is the tip speed ratio of the wind wheel;
at the set of average wind speeds
Figure BDA0002386678470000031
Is independent variable, and the calculated group of pitch angles β are used as dependent variables, and fitting is carried out by a least square method polynomial to obtain a theoretical value β of the pitch anglethThe calculation formula of (2):
Figure BDA0002386678470000032
wherein,
Figure BDA0002386678470000033
the rated wind speed of the wind driven generator;
using theoretical value of pitch angle βthConstructing theoretical deviation value of pitch angle
Figure BDA0002386678470000034
The pitch angle theoretical deviation fault characteristic model is taken as a calculation model of (1):
Figure BDA0002386678470000035
where Δ β is the pitch angle absolute deviation limit,
Figure BDA0002386678470000036
the data of the pitch angle measured by the ith encoder A is obtained;
in the same way, the method for preparing the composite material,
Figure BDA0002386678470000037
where Δ β is the pitch angle absolute deviation limit,
Figure BDA0002386678470000038
the data of the pitch angle measured by the ith B encoder is obtained;
and/or
2) Constructing a low-speed shaft rotating speed fault characteristic model:
the low-speed shaft rotating speed fault characteristic model comprises a wind wheel rotating speed relative deviation calculation model and a wind wheel rotating speed relative fluctuation calculation model;
constructing a wind wheel rotating speed relative deviation calculation model:
Figure BDA0002386678470000039
wherein, δ nlsIs the relative deviation of the rotational speed of the rotor, nlsFor the low-speed shaft speed data,
Figure BDA00023866784700000310
the theoretical value of the rotating speed of the low-speed shaft meets the following formula:
Figure BDA00023866784700000311
wherein n is0Is the rated rotating speed of the low-speed shaft,
Figure BDA00023866784700000312
for the wind generator to cut into the wind speed,
Figure BDA00023866784700000313
cutting wind speed for the wind driven generator;
constructing a wind wheel rotating speed relative fluctuation calculation model:
Figure BDA00023866784700000314
wherein, δ Δ nmsIs the relative fluctuation value of the rotating speed of the wind wheel,
Figure BDA00023866784700000315
is the maximum value in the low-speed shaft speed data for several seconds,
Figure BDA0002386678470000041
is the minimum value in the low-speed shaft speed data within seconds; preferably, the first and second electrodes are formed of a metal,
Figure BDA0002386678470000042
is the maximum value in the low-speed shaft speed data for 60 seconds,
Figure BDA0002386678470000043
is the minimum value in the low speed shaft speed data for 60; and/or
3) Constructing a pitch angle deviation fault characteristic model:
the pitch angle data of the blades of the wind driven generator further comprise pitch angle data measured by three B encoders
Figure BDA0002386678470000044
The pitch angle deviation fault characteristic model comprises a pitch angle relative deviation calculation model and a pitch angle absolute deviation calculation model;
constructing a pitch angle relative deviation calculation model of the first blade to the third blade of the wind driven generator:
Figure BDA0002386678470000045
Figure BDA0002386678470000046
wherein,
Figure BDA0002386678470000047
the average pitch angle of the data is measured for three a encoders,
Figure BDA0002386678470000048
the average pitch angle of the data is measured for the three B encoders,
Figure BDA0002386678470000049
for the pitch angle relative deviation from the a encoder measurement data,
Figure BDA00023866784700000410
the relative deviation of the pitch angle obtained by the data measured by the B encoder;
constructing a pitch angle absolute deviation calculation model of the first blade to the third blade of the wind driven generator:
Figure BDA00023866784700000411
and/or
4) Constructing a fault characteristic model of the variable-pitch battery pack:
Figure BDA0002386678470000051
wherein, Vbp0Is changed into a first pitch to a third pitchThe normal voltage of the battery pack is set,
Vbp1-Vbp3the voltage data of the first to the third pitch-variable batteries included in the voltage number of the pitch-variable batteries is delta Vbp1-δVbp3The voltage relative deviation of the first variable-pitch battery pack, the second variable-pitch battery pack and the third variable-pitch battery pack is obtained; and/or
5) Constructing a converter temperature fault characteristic model delta t of a variable pitch motorf cbi：
Figure BDA0002386678470000052
Wherein, tf cb0Is the upper temperature limit, t, of the converterf cbiFor said converter temperature data, δ tf cbiThe temperature deviation of a current transformer of the ith variable pitch motor is obtained; and/or
6) Constructing a temperature deviation fault characteristic model of the variable pitch motor:
the temperature data of the variable pitch motors comprise temperature data t of the first to third variable pitch motorsm1-tm3；
The temperature deviation fault characteristic model of the variable pitch motor is as follows:
Figure BDA0002386678470000053
wherein, tm0For the temperature deviation limit, δ t, of the pitch motorm1-δtm3The temperature deviation of the first variable pitch motor, the second variable pitch motor and the third variable pitch motor is obtained; and/or
7) Constructing a variable pitch motor current fault characteristic model:
the variable pitch motor current data comprise current data I of the first to third variable pitch motorsm1-Im3；
The current fault characteristic model of the variable pitch motor is as follows:
Figure BDA0002386678470000061
wherein, Im0Is the current deviation limit value, delta, of the pitch motorIm1-δIm3The current deviation of the first variable pitch motor, the second variable pitch motor and the third variable pitch motor is obtained; and/or
8) Constructing a variable pitch motor rotating speed characteristic model:
the variable pitch motor rotating speed data comprises rotating speed data n of a first variable pitch motor, a second variable pitch motor, a third variable pitch motor and a fourth variable pitch motorm1-nm3；
The variable pitch motor rotating speed characteristic model is as follows:
Figure BDA0002386678470000062
wherein n ism0Is the average rotating speed of a variable pitch motor and meets the requirement
Figure BDA0002386678470000063
δnm1-δnm3The rotating speed deviation of the first variable pitch motor, the second variable pitch motor and the third variable pitch motor is obtained;
and/or
9) Constructing a fault characteristic model of the variable-pitch bearing grease pump:
Figure BDA0002386678470000064
wherein,
Figure BDA0002386678470000065
respectively is the upper limit value and the lower limit value of the pressure at the outlet of the ith variable-pitch bearing grease pump, pbgpiFor the ith variable pitch bearing grease pump outlet pressure data,
Figure BDA0002386678470000066
and
Figure BDA0002386678470000067
the pressure upper limit deviation and the pressure lower limit deviation of the ith variable pitch shaft oil pump are obtained;
and/or
10) Constructing a pressure fault characteristic model of an outlet of a variable pitch gear grease pump:
Figure BDA0002386678470000071
wherein,
Figure BDA0002386678470000072
respectively is the upper limit value and the lower limit value of the pressure at the outlet of the ith variable pitch gear grease pump, pggpiFor the ith pitch gear grease pump outlet pressure data,
Figure BDA0002386678470000073
and
Figure BDA0002386678470000074
and the pressure upper limit deviation and the pressure lower limit deviation of the ith variable pitch gear grease pump.
Further, in step 3, the method for constructing the fault diagnosis model includes the following steps:
1) constructing a fault diagnosis model of the variable pitch gearbox:
when the current deviation of the ith variable pitch motor and the temperature deviation of the ith variable pitch motor meet the following conditions:
Figure BDA0002386678470000075
the fault of the ith variable pitch gearbox can be judged;
if the upper limit deviation and the lower limit deviation of the ith variable pitch gear grease pump meet the following requirements at the same time:
Figure BDA0002386678470000076
or
Figure BDA0002386678470000077
Figure BDA0002386678470000078
It can be further judged that: an ith pitch gearbox fault; and/or
2) Constructing a fault diagnosis model of the variable-pitch bearing:
the following equation holds:
the current deviation of the first to the third variable pitch motors satisfies
Figure BDA0002386678470000079
And the temperature deviation of the first to the third variable pitch motors meets the requirement
Figure BDA00023866784700000710
And the upper limit deviation and the lower limit deviation of the first to third variable pitch shaft oil pumps meet the conditions:
Figure BDA00023866784700000711
or
Figure BDA00023866784700000712
And the fault of the variable pitch bearing can be judged.
Further, in step 3, the method for constructing the fault diagnosis model further includes constructing a fault diagnosis model of a mechanical component of the pitch system:
1) constructing a fault diagnosis model of the variable pitch gearbox:
when the current deviation of the ith variable pitch motor and the temperature deviation of the ith variable pitch motor meet the following conditions:
Figure BDA00023866784700000713
the fault of the ith variable pitch gearbox can be judged;
if the upper limit deviation and the lower limit deviation of the ith variable pitch gear grease pump meet the following requirements at the same time:
Figure BDA0002386678470000081
or
Figure BDA0002386678470000082
Figure BDA0002386678470000083
It can be further judged that: an ith pitch gearbox fault; and/or
2) Constructing a fault diagnosis model of the variable-pitch bearing:
the following equation holds:
the current deviation of the first to the third variable pitch motors satisfies
Figure BDA0002386678470000084
And the temperature deviation of the first to the third variable pitch motors meets the requirement
Figure BDA0002386678470000085
And the upper limit deviation and the lower limit deviation of the first to third variable pitch shaft oil pumps meet the conditions:
Figure BDA0002386678470000086
or
Figure BDA0002386678470000087
And the fault of the variable pitch bearing can be judged.
Further, in step 3, the method for constructing the fault diagnosis model further includes constructing a fault diagnosis model of a control system of the pitch system:
1) constructing a variable pitch angle difference fault diagnosis model:
when the relative deviation of the pitch angle and the deviation of the pitch angle delta βbiSatisfies the following formula:
Figure BDA0002386678470000088
and is
Figure BDA0002386678470000089
Judging that the B encoder of the ith blade has a fault;
relative and absolute Pitch Angle deviations Δ βbiSatisfies the following formula:
Figure BDA00023866784700000810
and is
Figure BDA00023866784700000811
Judging the failure of an encoder A of the ith blade, wherein a is the allowable error of the variable pitch angle;
and/or
2) Constructing a blade limit switch trigger early fault diagnosis model:
if the pitch angle relative deviation and blade angle satisfy the following equation:
Figure BDA00023866784700000812
Figure BDA00023866784700000813
the fault cause can be diagnosed as early triggering of the paddle limit switch; and/or
3) Constructing a high-temperature fault diagnosis model of the variable pitch motor:
if: variable pitch motor temperature deviation deltatmiThe temperature of the variable-pitch motor is more than or equal to 10.0 percent, and the high-temperature fault of the variable-pitch motor can be judged to occur in the ith blade;
if the temperature deviation of the variable pitch motor and the current deviation of the variable pitch motor meet the following conditions:
Figure BDA0002386678470000091
the high-temperature fault of the pitch motor of the ith blade can be judged, and the fault is mostly caused by the fault of the pitch gearbox; and/or
4) Constructing a fault diagnosis model for overhigh rotating speed of a variable pitch motor:
if the following two equations hold:
the rotating speed deviation of the variable pitch motor meets the requirement
Figure BDA0002386678470000092
And the rotating speed of the variable pitch motor meets
Figure BDA0002386678470000093
The fault that the rotating speed of the variable pitch motor is too high can be judged, and the fault is mostly caused by the fault of an A encoder, wherein a is the allowable rotating speed deviation of the wind driven generator; and/or
5) Constructing a variable pitch failure diagnosis model:
the following equation holds:
the relative deviation of the pitch angle measured by the A encoder satisfies
Figure BDA0002386678470000094
And the relative deviation of the pitch angle measured by the B encoder satisfies
Figure BDA0002386678470000095
And the theoretical deviation of the pitch angles of the first to third blades satisfies
Figure BDA0002386678470000096
Then the occurrence of a pitch failure fault can be judged; and/or
6) Constructing a pitch system signal transmission fault diagnosis model:
the following equation holds:
the relative deviation of the rotating speed of the low-speed shaft meets delta nlsNot less than 10.0% and the rotation speed deviation of the variable pitch motor meets delta nmsAnd if the pitch control signal transmission fault is more than or equal to 10.0 percent, the occurrence of the pitch control signal transmission fault can be judged.
Further, in step 5, when the real-time fault characteristics are input into the fault diagnosis model, firstly, the real-time fault characteristics are input into the fault diagnosis model of the variable pitch power system and the fault diagnosis model of the mechanical component of the variable pitch system, and the fault type of the real-time fault characteristics is judged; and if the real-time fault characteristics are judged not to belong to the two types of fault models, inputting the real-time fault characteristics into a control system fault diagnosis model of the variable pitch system for diagnosis.
Further, in step 5, the fault diagnosis result includes a fault reason and a fault location.
Further, in step 2, the historical operating data is subjected to preprocessing and then fault feature extraction is carried out; the preprocessing comprises denoising, filtering, translating and amplifying the electric signals of the historical operating data to obtain standard operating data with the amplitude range of 0-5V.
Further, in the steps 1-5, the data collector is adopted to obtain the wind driven generator operation data measured by all the SCADA systems, and the computer is adopted to store and complete data storage, fault diagnosis and result display.
For a better understanding and practice, the invention is described in detail below with reference to the accompanying drawings.
Drawings
FIG. 1 is a schematic view of a wind turbine;
FIG. 2 is a schematic structural diagram of a pitch system of a wind turbine;
FIG. 3 is a flowchart of a fault diagnosis method for a pitch system of a wind turbine according to the present invention.
Detailed Description
According to the fault diagnosis method for the variable pitch system of the wind driven generator, disclosed by the invention, the fault characteristics are extracted and the fault diagnosis model of each part of the variable pitch system is constructed by utilizing various historical operating data of the wind driven generator, which are acquired by the SCADA system, so that the specific fault reason and the fault position of the variable pitch system of the wind driven generator can be accurately judged in the real-time operating process of the wind driven generator.
Specifically, the fault diagnosis method for the pitch system of the wind driven generator comprises the following steps:
step 1: acquiring historical operating data of an SCADA system of the wind driven generator, wherein the historical operating data comprises average wind speed and wind direction outside a cabin of the wind driven generator, a pitch angle of a blade of the wind driven generator, the rotating speed of a low-speed shaft of a variable pitch system, active power of the generator, voltage and current of a variable pitch motor, the temperature of the variable pitch motor, the temperature of a blade converter, the voltage of a variable pitch battery, the oil pressure of an outlet of a variable pitch bearing grease pump and the oil pressure of an outlet of a variable pitch; the pitch angle data of the blades of the wind driven generator comprise encoder data obtained by measuring a pitch angle data of an encoder A and an encoder B.
Wherein the paddle of the wind driven generator bladeThe pitch angle data comprises pitch angle data measured by an A encoder
Figure BDA0002386678470000101
And B encoder data measured by the encoder
Figure BDA0002386678470000102
The variable pitch battery voltage number comprises voltage data V of the first to third variable pitch batteriesbp1-Vbp3(ii) a The blade converter temperature data comprises converter temperature data t of the first to third variable pitch motorsf cb1-tf cb3(ii) a The temperature data of the variable pitch motors comprise temperature data t of the first to third variable pitch motorsm1-tm3(ii) a The variable pitch motor current data comprise current data I of the first to third variable pitch motorsm1-Im3(ii) a The variable pitch motor rotating speed data comprises rotating speed data n of a first variable pitch motor, a second variable pitch motor, a third variable pitch motor and a fourth variable pitch motorm1-nm3(ii) a The oil pressure at the outlet of the variable-pitch bearing grease pump comprises
Step 2: firstly, preprocessing the historical operating data: denoising, filtering, translating and amplifying the measurement signal of each historical operation data to obtain standard operation data with the amplitude range of 0-5V; and then, constructing a fault characteristic model of each position of the wind driven generator variable pitch system by using the standard operation data. The method for constructing the fault characteristic model specifically comprises the following steps:
1) constructing a theoretical deviation fault characteristic model of the pitch angle:
acquiring a group of average wind speed data in historical operation of a fan, and acquiring each average wind speed data
Figure BDA0002386678470000111
The following equations are substituted, respectively, to solve for a set of corresponding pitch angles β:
Figure BDA0002386678470000112
Figure BDA0002386678470000113
wherein rho is air density, η is transmission efficiency, R is wind wheel diameter, P is rated power of the wind driven generator, c1-c8Is the characteristic coefficient of the wind wheel, lambdaiThe tip speed of the ith blade is the tip speed of the ith blade, and lambda is the tip speed ratio of the wind wheel;
at the set of average wind speeds
Figure BDA0002386678470000114
Is independent variable, and the calculated group of pitch angles β are used as dependent variables, and fitting is carried out by a least square method polynomial to obtain the theoretical value β of the pitch anglethExpression (c):
Figure BDA0002386678470000115
wherein,
Figure BDA0002386678470000116
the rated wind speed of the wind driven generator;
using theoretical value of pitch angle βthConstructing theoretical deviation value of pitch angle
Figure BDA0002386678470000117
The pitch angle theoretical deviation fault characteristic model is taken as a calculation model of (1):
Figure BDA0002386678470000118
where Δ β is the pitch angle absolute deviation limit,
Figure BDA0002386678470000119
the data of the pitch angle measured by the ith encoder A is obtained;
Figure BDA00023866784700001110
Figure BDA00023866784700001111
where Δ β is the pitch angle absolute deviation limit,
Figure BDA00023866784700001112
is the pitch angle data measured by the ith B encoder. When the blade pitch angle is normal, the theoretical deviation value of the pitch angle
Figure BDA00023866784700001113
Theoretical offset value of pitch angle
Figure BDA00023866784700001114
Is one of the conditions that the pitch angle is abnormal.
2) Constructing a low-speed shaft rotating speed fault characteristic model:
the low-speed shaft rotating speed fault characteristic model comprises a wind wheel rotating speed relative deviation calculation model and a wind wheel rotating speed relative fluctuation calculation model;
constructing a wind wheel rotating speed relative deviation calculation model:
Figure BDA00023866784700001115
wherein, δ nlsIs the relative deviation of the rotational speed of the rotor, nlsFor the low-speed shaft speed data,
Figure BDA00023866784700001116
the theoretical value of the rotating speed of the low-speed shaft meets the following formula:
Figure BDA0002386678470000121
wherein n is0Is the rated rotating speed of the low-speed shaft,
Figure BDA0002386678470000122
for the wind generator to cut into the wind speed,
Figure BDA0002386678470000123
cutting wind speed for the wind driven generator;
constructing a wind wheel rotating speed relative fluctuation calculation model:
Figure BDA0002386678470000124
wherein, δ Δ nmsIs the relative fluctuation value of the rotating speed of the wind wheel,
Figure BDA0002386678470000125
is the maximum value in the low-speed shaft speed data in n seconds,
Figure BDA0002386678470000126
is the minimum value in the low-speed shaft speed data within n seconds. Preferably, the first and second electrodes are formed of a metal,
Figure BDA0002386678470000127
is the maximum value in the low-speed shaft speed data for 60 seconds,
Figure BDA0002386678470000128
is the minimum value in the low speed shaft speed data for 60 seconds.
3) Constructing a pitch angle deviation fault characteristic model:
the pitch angle deviation fault characteristic model comprises a pitch angle relative deviation calculation model and a pitch angle absolute deviation calculation model;
constructing a pitch angle relative deviation calculation model of the first blade to the third blade of the wind driven generator:
Figure BDA0002386678470000129
Figure BDA00023866784700001210
wherein,
Figure BDA00023866784700001211
the average pitch angle of the data is measured for three a encoders,
Figure BDA00023866784700001212
Figure BDA00023866784700001213
the average pitch angle of the data is measured for the three B encoders,
Figure BDA00023866784700001214
Figure BDA00023866784700001215
for the pitch angle relative deviation from the a encoder measurement data,
Figure BDA0002386678470000131
the relative deviation of the pitch angle obtained by the data measured by the B encoder;
constructing a pitch angle absolute deviation calculation model of the first blade to the third blade of the wind driven generator:
Figure BDA0002386678470000132
4) constructing a fault characteristic model of the variable-pitch battery pack:
the variable pitch battery voltage number comprises voltage data V of the first to third variable pitch batteriesbp1-Vbp3，
The fault characteristic model of the variable-pitch battery pack is as follows:
Figure BDA0002386678470000133
wherein, Vbp0Is the normal voltage of the first to third pitch battery packs,
δVbp1-δVbp3and the voltage relative deviation of the first variable pitch battery pack, the second variable pitch battery pack and the third variable pitch battery pack.
5) Constructing a converter temperature fault characteristic model delta t of a variable pitch motorf cbi：
Figure BDA0002386678470000134
Wherein, tf cb0Is the upper temperature limit, t, of the converterf cbiFor the converter temperature data of the ith variable pitch motor, deltatf cbiAnd the current transformer temperature deviation of the ith variable pitch motor is obtained.
6) Constructing a temperature deviation fault characteristic model of the variable pitch motor:
the temperature data of the variable pitch motors comprise temperature data t of the first to third variable pitch motorsm1-tm3；
The temperature deviation fault characteristic model of the variable pitch motor is as follows:
Figure BDA0002386678470000141
wherein, tm0For the temperature deviation limit, delta, of the pitch motortm1-δtm3The temperature deviation of the first variable pitch motor, the second variable pitch motor and the third variable pitch motor.
7) Constructing a variable pitch motor current fault characteristic model:
the variable pitch motor current data comprise current data I of the first to third variable pitch motorsm1-Im3；
The current fault characteristic model of the variable pitch motor is as follows:
Figure BDA0002386678470000142
wherein, Im0Is the current deviation limit, delta I, of the pitch motorm1-δIm3The current deviation of the first pitch motor, the second pitch motor and the third pitch motor.
8) Constructing a variable pitch motor rotating speed characteristic model:
the variable pitch motor rotating speed data comprises rotating speed data n of a first variable pitch motor, a second variable pitch motor, a third variable pitch motor and a fourth variable pitch motorm1-nm3；
The variable pitch motor rotating speed characteristic model is as follows:
Figure BDA0002386678470000143
wherein n ism0Is the average rotating speed of a variable pitch motor and meets the requirement
Figure BDA0002386678470000144
δnm1-δnm3The rotating speed deviation of the first variable pitch motor, the second variable pitch motor and the third variable pitch motor.
9) Constructing a fault characteristic model of the variable-pitch bearing grease pump:
Figure BDA0002386678470000145
wherein,
Figure BDA0002386678470000151
respectively is the upper limit value and the lower limit value of the pressure at the outlet of the ith variable-pitch bearing grease pump, pbgpiFor the ith variable pitch bearing grease pump outlet pressure data,
Figure BDA0002386678470000152
and
Figure BDA0002386678470000153
and the pressure upper limit deviation and the pressure lower limit deviation of the ith variable pitch shaft oil pump are obtained.
10) Constructing a pressure fault characteristic model of an outlet of a variable pitch gear grease pump:
Figure BDA0002386678470000154
wherein,
Figure BDA0002386678470000155
respectively is the upper limit value and the lower limit value of the pressure at the outlet of the ith variable pitch gear grease pump, pggpiFor the ith pitch gear grease pump outlet pressure data,
Figure BDA0002386678470000156
and
Figure BDA0002386678470000157
pressure upper limit of ith variable pitch gear grease pumpDeviation from the lower pressure limit.
And step 3: constructing a fault diagnosis model by using the fault characteristics, which comprises the following specific steps:
1) constructing a fault diagnosis model of a variable pitch power supply system:
1.1 constructing a variable pitch battery fault diagnosis model:
if the battery pack for the ith blade has:
the relative voltage deviation of the first variable-pitch battery pack, the second variable-pitch battery pack and the third variable-pitch battery pack meets delta Vbpi≥100％*(Vs-Vd)/VsThen, it can be judged that the ith battery pack has a fault, wherein VsIs the rated voltage, V, of the battery packdThe end-of-discharge voltage of the battery pack, when the battery pack voltage is less than or equal to the end-of-discharge voltage at the time of operation, indicates that the battery pack has been damaged.
1.2, constructing a fault diagnosis model of a variable-pitch battery charger:
because the first to third become oar group battery independent work, do not have mutual influence, rare the condition that breaks down simultaneously, consequently, when the voltage relative deviation of first to third become oar group battery satisfies:
Figure BDA0002386678470000158
and judging that the variable pitch battery charger is in fault.
1.3, constructing a high-temperature fault diagnosis model of the converter:
because the converter has thermal overload protection, in order to prevent that the thermal overload protection system starts to influence the normal operation of aerogenerator, need in time report an emergency and ask for help or increased vigilance when the converter temperature exceeds temperature limit 10%, consequently, the converter temperature deviation when first to third become oar motor satisfies:
δtf cbiand if the current transformer of the ith variable pitch motor has a high-temperature fault, judging that the current transformer of the ith variable pitch motor has the high-temperature fault.
2) Constructing a fault diagnosis model of a mechanical component of a variable pitch system:
2.1 constructing a fault diagnosis model of the variable pitch gearbox:
the maximum current allowed by the variable pitch motor is generally 110% of the rated current, and when the current of the variable pitch motor is greater than 10% of the rated current, the temperature of the variable pitch motor exceeds the temperature limit value by 10% and reaches an alarm value, so that the characteristic can be used as a fault judgment index. Therefore, when the current deviation of the ith variable pitch motor and the temperature deviation of the ith variable pitch motor meet the following conditions:
Figure BDA0002386678470000161
the fault of the ith variable pitch gearbox can be judged.
If the upper limit deviation and the lower limit deviation of the ith variable pitch gear grease pump meet the following requirements at the same time:
Figure BDA0002386678470000162
or
Figure BDA0002386678470000163
Figure BDA0002386678470000164
It can be further judged that: failure of the ith pitch gearbox.
2.2, constructing a fault diagnosis model of the variable pitch bearing:
three become oar bearings mutually independent, each other does not influence, and the rare three condition that becomes the oar bearing and break down simultaneously, consequently, when following the formula and hold:
the current deviation of the first to the third variable pitch motors satisfies
Figure BDA0002386678470000165
And the temperature deviation of the first to the third variable pitch motors meets the requirement
Figure BDA0002386678470000166
And the upper limit deviation and the lower limit deviation of the first to third variable pitch shaft oil pumps meet the conditions:
Figure BDA0002386678470000167
or
Figure BDA0002386678470000168
And the fault of the variable pitch bearing can be judged.
3) Constructing a control system fault diagnosis model of a variable pitch system:
when the variable pitch system has faults, after the faults of the variable pitch power supply system in 1) and the mechanical parts of the variable pitch system in 2) are eliminated, if the variable pitch system still has fault points, the faults are considered as the faults of the control system of the variable pitch system. The specific diagnosis method comprises the following steps:
3.1 constructing a variable pitch angle difference fault diagnosis model:
the pitch angle deviation delta β of the existing wind generating set is knownbiThe upper limit value of the pitch angle deviation is 2 degrees, the allowable deviation of the pitch angle is set to be a percent, the upper limit value of the pitch angle deviation is limited to be 2a percent, and when the relative deviation of the pitch angle and the deviation delta β of the pitch angle are achievedbiSatisfies the following formula:
Figure BDA0002386678470000169
and is
Figure BDA00023866784700001610
Judging that the B encoder of the ith blade has a fault;
when the relative deviation of the pitch angle and the deviation of the pitch angle delta βbiSatisfies the following formula:
Figure BDA00023866784700001611
and is
Figure BDA0002386678470000171
The failure of the encoder A of the ith blade is judged.
Preferably, a has a value of 5.
3.2, constructing a blade limit switch trigger early fault diagnosis model:
in the existing wind power generation system, the setting value of the limiter of the blade angle is generally 91 degrees, if the relative deviation of the pitch angle and the blade angle satisfy the following formula:
Figure BDA0002386678470000172
Figure BDA0002386678470000173
namely, the encoder works normally, the paddle does not reach the normal action value of the paddle limit switch at the moment, the fault alarm occurs at the moment, and the diagnosis fault reason is that the trigger of the paddle limit switch is earlier.
3.3 constructing a high-temperature fault diagnosis model of the variable pitch motor:
if: variable pitch motor temperature deviation deltatmiThe temperature of the variable pitch motor is more than or equal to 10.0 percent, namely the temperature of the variable pitch motor exceeds the temperature limit value by 10 percent, and the high-temperature fault of the variable pitch motor can be judged to occur in the ith blade;
if the temperature deviation of the variable pitch motor and the current deviation of the variable pitch motor meet the following conditions:
Figure BDA0002386678470000174
the high-temperature fault of the variable pitch motor of the ith blade can be judged, and the fault is mostly caused by the fault of the variable pitch gearbox.
3.4, constructing a high-rotating-speed fault diagnosis model of the variable pitch motor:
generally, the allowable rotation speed deviation of the existing wind power generator is the same as the a%, and the rotation speed of the pitch motor is limited not to exceed 31(deg/s), if the following two formulas are satisfied:
the rotating speed deviation of the variable pitch motor meets
Figure BDA0002386678470000175
And the rotating speed of the variable pitch motor meets
Figure BDA0002386678470000176
The fault that the rotating speed of the variable pitch motor is too high can be judged, and the fault is mostly caused by the fault of the A encoder.
3.5 constructing a variable pitch failure diagnosis model:
when the encoder works well and the blade deviation exceeds a limit value, the variable-pitch failure condition is determined, namely the following formula is satisfied:
the relative deviation of the pitch angle measured by the A encoder satisfies
Figure BDA0002386678470000177
And the relative deviation of the pitch angle measured by the B encoder satisfies
Figure BDA0002386678470000181
And the theoretical deviation of the pitch angles of the first to third blades satisfies
Figure BDA0002386678470000182
It can be judged that a pitch failure fault has occurred.
3.6 constructing a pitch system signal transmission fault diagnosis model:
the following equation holds:
the relative deviation of the rotating speed of the low-speed shaft meets delta nlsNot less than 10.0 percent and the relative fluctuation of the rotating speed of the wind wheel meets delta nmsAnd if the pitch control signal transmission fault is more than or equal to 10.0 percent, the occurrence of the pitch control signal transmission fault can be judged.
And 4, step 4: and acquiring real-time fault alarm data of an SCADA system of the wind driven generator, inputting the real-time fault alarm data into a fault characteristic model, and calculating to acquire real-time fault characteristics.
And 5: and (4) inputting the real-time fault characteristics obtained in the step (4) into the fault diagnosis model to obtain a fault diagnosis result, wherein the fault diagnosis result comprises a fault reason and a fault position.
In this embodiment, the data collector is used to obtain the operating data of the various wind power generators measured by the SCADA system, and the computer is used to store and complete data storage, fault diagnosis and result display.
Compared with the prior art, the fault diagnosis method for the variable pitch system of the wind driven generator acquires the required fan operation data from the existing SCADA system, extracts the fault characteristics of fault high-occurrence positions in the power system of the variable pitch system, the mechanical components of the variable pitch system and the control system of the variable pitch system, constructs a comprehensive fault characteristic model, can diagnose the real-time fault position of the wind driven generator set to the fault reason, and improves the overhaul efficiency.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention.

Claims (10)

1. A fault diagnosis method for a pitch system of a wind driven generator is characterized by comprising the following steps:
step 1: acquiring historical operating data of an SCADA system of the wind driven generator;
step 2: constructing a fault characteristic model by using historical operating data of the SCADA system;
and step 3: constructing a fault diagnosis model by using the fault feature model;
and 4, step 4: acquiring real-time fault alarm data of an SCADA system of the wind driven generator, inputting the real-time fault alarm data into a fault characteristic model, and calculating to acquire real-time fault characteristics;
and 5: and (4) inputting the real-time fault characteristics obtained in the step (4) into the fault diagnosis model to obtain a fault diagnosis result.
2. The wind turbine pitch system fault diagnosis method according to claim 1, characterized in that: in step 1, the historical operating data of the SCADA system includes: the wind power generator comprises one or more of average wind speed outside a nacelle of the wind power generator, wind direction, pitch angles of first to third blades of the wind power generator, rotating speed of a low-speed shaft, active power of the generator, voltage and current of a variable pitch motor, temperature of the variable pitch motor, temperature of a blade converter, voltage of a variable pitch battery, oil pressure at an outlet of a variable pitch bearing grease pump and oil pressure at an outlet of the variable pitch gear grease pump.
3. The wind turbine pitch system fault diagnosis method according to claim 2, characterized in that:
the method for constructing the fault feature model comprises the following steps:
1) constructing a theoretical deviation fault characteristic model of the pitch angle:
the pitch angle data of the blades of the wind driven generator comprise pitch angle data measured by an encoder A
Figure FDA0002386678460000011
And B encoder data measured by the encoder
Figure FDA0002386678460000012
Acquiring a group of average wind speed data in historical operation of a fan, and acquiring each average wind speed data
Figure FDA0002386678460000013
The following equations are substituted, respectively, to solve for a set of corresponding pitch angles β:
Figure FDA0002386678460000014
Figure FDA0002386678460000015
wherein rho is air density, η is transmission efficiency, R is wind wheel diameter, P is rated power of the wind driven generator, c1-c8Is the characteristic coefficient of the wind wheel, lambdaiThe tip speed of the ith blade is the tip speed of the ith blade, and lambda is the tip speed ratio of the wind wheel;
at the set of average wind speeds
Figure FDA0002386678460000016
Is independent variable, and the set of pitch angles β calculated is dependent variable, and is polynomial by least squares methodFitting is carried out to obtain theoretical value β of pitch anglethThe calculation formula of (2):
Figure FDA0002386678460000017
wherein,
Figure FDA0002386678460000018
the rated wind speed of the wind driven generator;
using theoretical value of pitch angle βthConstructing theoretical deviation value of pitch angle
Figure FDA0002386678460000019
The pitch angle theoretical deviation fault characteristic model is taken as a calculation model of (1):
Figure FDA0002386678460000021
where Δ β is the pitch angle absolute deviation limit,
Figure FDA0002386678460000022
the data of the pitch angle measured by the ith encoder A is obtained;
Figure FDA0002386678460000023
where Δ β is the pitch angle absolute deviation limit,
Figure FDA0002386678460000024
the data of the pitch angle measured by the ith B encoder is obtained;
and/or
2) Constructing a low-speed shaft rotating speed fault characteristic model:
the low-speed shaft rotating speed fault characteristic model comprises a wind wheel rotating speed relative deviation calculation model and a wind wheel rotating speed relative fluctuation calculation model;
constructing a wind wheel rotating speed relative deviation calculation model:
Figure FDA0002386678460000025
wherein, δ nlsIs the relative deviation of the rotational speed of the rotor, nlsFor the low-speed shaft speed data,
Figure FDA0002386678460000026
the theoretical value of the rotating speed of the low-speed shaft meets the following formula:
Figure FDA0002386678460000027
wherein n is0Is the rated rotating speed of the low-speed shaft,
Figure FDA0002386678460000028
for the wind generator to cut into the wind speed,
Figure FDA0002386678460000029
cutting wind speed for the wind driven generator;
constructing a wind wheel rotating speed relative fluctuation calculation model:
Figure FDA00023866784600000210
wherein, δ Δ nmsIs the relative fluctuation value of the rotating speed of the wind wheel,
Figure FDA00023866784600000211
is the maximum value in the low-speed shaft speed data for several seconds,
Figure FDA00023866784600000212
is the minimum value in the low-speed shaft speed data within seconds;
and/or
3) Constructing a pitch angle deviation fault characteristic model:
the pitch angle deviation fault characteristic model comprises a pitch angle relative deviation calculation model and a pitch angle absolute deviation calculation model;
constructing a pitch angle relative deviation calculation model of the first blade to the third blade of the wind driven generator:
Figure FDA0002386678460000031
Figure FDA0002386678460000032
wherein,
Figure FDA0002386678460000033
the average pitch angle of the data is measured for three a encoders,
Figure FDA0002386678460000034
the average pitch angle of the data is measured for the three B encoders,
Figure FDA0002386678460000035
for the pitch angle relative deviation from the a encoder measurement data,
Figure FDA0002386678460000036
the relative deviation of the pitch angle obtained by the data measured by the B encoder;
constructing a pitch angle absolute deviation calculation model of the first blade to the third blade of the wind driven generator:
Figure FDA0002386678460000037
and/or
4) Constructing a fault characteristic model of the variable-pitch battery pack:
the variable pitch battery voltage number comprises voltage data V of the first to third variable pitch batteriesbp1-Vbp3，
The fault characteristic model of the variable-pitch battery pack is as follows:
Figure FDA0002386678460000038
wherein, Vbp0Is the normal voltage of the first to third pitch battery packs,
δVbp1-δVbp3the voltage relative deviation of the first variable-pitch battery pack, the second variable-pitch battery pack and the third variable-pitch battery pack is obtained; and/or
5) Constructing a converter temperature fault characteristic model delta t of a variable pitch motorfcbi：
Figure FDA0002386678460000041
Wherein, tfcb0Is the upper temperature limit, t, of the converterfcbiFor the converter temperature data of the ith variable pitch motor, deltatfcbiThe temperature deviation of a current transformer of the ith variable pitch motor is obtained; and/or
6) Constructing a temperature deviation fault characteristic model of the variable pitch motor:
the temperature data of the variable pitch motors comprise temperature data t of the first to third variable pitch motorsm1-tm3；
The temperature deviation fault characteristic model of the variable pitch motor is as follows:
Figure FDA0002386678460000042
wherein, tm0For the temperature deviation limit, δ t, of the pitch motorm1-δtm3The temperature deviation of the first variable pitch motor, the second variable pitch motor and the third variable pitch motor is obtained; and/or
7) Constructing a variable pitch motor current fault characteristic model:
the variable pitch motor current data comprise current data I of the first to third variable pitch motorsm1-Im3；
The current fault characteristic model of the variable pitch motor is as follows:
Figure FDA0002386678460000043
wherein, Im0Is the current deviation limit, delta I, of the pitch motorm1-δIm3The current deviation of the first variable pitch motor, the second variable pitch motor and the third variable pitch motor is obtained; and/or
8) Constructing a variable pitch motor rotating speed characteristic model:
the variable pitch motor rotating speed data comprises rotating speed data n of a first variable pitch motor, a second variable pitch motor, a third variable pitch motor and a fourth variable pitch motorm1-nm3；
The variable pitch motor rotating speed characteristic model is as follows:
Figure FDA0002386678460000051
wherein n ism0Is the average rotating speed of a variable pitch motor and meets the requirement
Figure FDA0002386678460000052
δnm1-δnm3The rotating speed deviation of the first variable pitch motor, the second variable pitch motor and the third variable pitch motor is obtained;
and/or
9) Constructing a fault characteristic model of the variable-pitch bearing grease pump:
Figure FDA0002386678460000053
wherein,
Figure FDA0002386678460000054
respectively is the upper limit value and the lower limit value of the pressure at the outlet of the ith variable-pitch bearing grease pump, pbgpiFor the ith variable pitch bearing grease pump outlet pressure data,
Figure FDA0002386678460000055
and
Figure FDA0002386678460000056
the pressure upper limit deviation and the pressure lower limit deviation of the ith variable pitch shaft oil pump are obtained;
and/or
10) Constructing a pressure fault characteristic model of an outlet of a variable pitch gear grease pump:
Figure FDA0002386678460000057
wherein,
Figure FDA0002386678460000058
respectively is the upper limit value and the lower limit value of the pressure at the outlet of the ith variable pitch gear grease pump, pggpiFor the ith pitch gear grease pump outlet pressure data,
Figure FDA0002386678460000059
and
Figure FDA00023866784600000510
and the pressure upper limit deviation and the pressure lower limit deviation of the ith variable pitch gear grease pump.
4. The wind turbine pitch system fault diagnosis method according to claim 3, wherein: in the step 3, the step of the method is that,
the method for constructing the fault diagnosis model comprises the following steps of constructing the fault diagnosis model of the variable pitch power supply system:
1) constructing a variable-pitch battery fault diagnosis model:
if the battery pack for the ith blade has:
the relative voltage deviation of the first variable-pitch battery pack, the second variable-pitch battery pack and the third variable-pitch battery pack meets delta Vbpi≥100％*(Vs-Vd)/Vs，
It can be judged that the ith battery pack has a failure, wherein VsIs the rated voltage, V, of the battery packdIs the discharge termination voltage of the battery; and/or
2) Constructing a fault diagnosis model of the variable-pitch battery charger:
when the voltage relative deviation of the first variable pitch battery pack, the second variable pitch battery pack and the third variable pitch battery pack meets the following conditions:
Figure FDA0002386678460000061
judging that the variable-pitch battery charger has a fault; and/or
3) Constructing a high-temperature fault diagnosis model of the converter:
when the converter temperature deviation of the ith variable pitch motor meets the following conditions: δ tfcbiAnd if the current transformer of the ith variable pitch motor has a high-temperature fault, judging that the current transformer of the ith variable pitch motor has the high-temperature fault.
5. The wind turbine pitch system fault diagnosis method according to claim 4, wherein: in the step 3, the step of the method is that,
the method for constructing the fault diagnosis model further comprises the following steps of constructing the fault diagnosis model of the mechanical component of the variable pitch system:
1) constructing a fault diagnosis model of the variable pitch gearbox:
when the current deviation of the ith variable pitch motor and the temperature deviation of the ith variable pitch motor meet the following conditions:
Figure FDA0002386678460000062
the fault of the ith variable pitch gearbox can be judged;
if the upper limit deviation and the lower limit deviation of the ith variable pitch gear grease pump meet the following requirements at the same time:
Figure FDA0002386678460000063
or
Figure FDA0002386678460000064
Figure FDA0002386678460000065
It can be further judged that: an ith pitch gearbox fault; and/or
2) Constructing a fault diagnosis model of the variable-pitch bearing:
the following equation holds:
the current deviation of the first to the third variable pitch motors satisfies
Figure FDA0002386678460000066
And the temperature deviation of the first to the third variable pitch motors meets the requirement
Figure FDA0002386678460000067
And the upper limit deviation and the lower limit deviation of the first to third variable pitch shaft oil pumps meet the conditions:
Figure FDA0002386678460000068
or
Figure FDA0002386678460000069
And the fault of the variable pitch bearing can be judged.
6. The wind turbine pitch system fault diagnosis method according to claim 5, wherein: in the step 3, the step of the method is that,
the method for constructing the fault diagnosis model further comprises the following steps of constructing a control system fault diagnosis model of the variable pitch system:
1) constructing a variable pitch angle difference fault diagnosis model:
when the relative deviation of the pitch angle and the deviation of the pitch angle delta βbiSatisfies the following formula:
Figure FDA0002386678460000071
and is
Figure FDA0002386678460000072
Judging that the B encoder of the ith blade has a fault;
relative and absolute Pitch Angle deviations Δ βbiSatisfies the following formula:
Figure FDA0002386678460000073
and is
Figure FDA0002386678460000074
Judging the failure of an encoder A of the ith blade, wherein a is the allowable error of the variable pitch angle; and/or
2) Constructing a blade limit switch trigger early fault diagnosis model:
if the pitch angle relative deviation and blade angle satisfy the following equation:
Figure FDA0002386678460000075
Figure FDA0002386678460000076
the fault cause can be diagnosed as early triggering of the paddle limit switch; and/or
3) Constructing a high-temperature fault diagnosis model of the variable pitch motor:
if: variable pitch motor temperature deviation deltatmiThe temperature of the variable-pitch motor is more than or equal to 10.0 percent, and the high-temperature fault of the variable-pitch motor can be judged to occur in the ith blade;
if the temperature deviation of the variable pitch motor and the current deviation of the variable pitch motor meet the following conditions:
Figure FDA0002386678460000077
the high-temperature fault of the pitch motor of the ith blade can be judged, and the fault is mostly caused by the fault of the pitch gearbox;
4) constructing a fault diagnosis model for overhigh rotating speed of a variable pitch motor:
if the following two equations hold:
the rotating speed deviation of the variable pitch motor meets the requirement
Figure FDA0002386678460000078
And the rotating speed of the variable pitch motor meets
Figure FDA0002386678460000079
The fault that the rotating speed of the variable pitch motor is too high can be judged, and the fault is mostly caused by the fault of an A encoder, wherein a is the allowable rotating speed deviation of the wind driven generator; and/or
5) Constructing a variable pitch failure diagnosis model:
the following equation holds:
the relative deviation of the pitch angle measured by the A encoder satisfies
Figure FDA00023866784600000710
And the relative deviation of the pitch angle measured by the B encoder satisfies
Figure FDA0002386678460000081
And the theoretical deviation of the pitch angles of the first to third blades satisfies
Figure FDA0002386678460000082
Then the occurrence of a pitch failure fault can be judged; and/or
6) Constructing a pitch system signal transmission fault diagnosis model:
the following equation holds:
the relative deviation of the rotating speed of the low-speed shaft meets delta nlsNot less than 10.0% and the relative fluctuation value of the wind wheel speed satisfies delta nmsAnd if the pitch control signal transmission fault is more than or equal to 10.0 percent, the occurrence of the pitch control signal transmission fault can be judged.
7. The wind turbine pitch system fault diagnosis method according to claim 6, wherein: step 5, when the real-time fault characteristics are input into the fault diagnosis model, firstly, the real-time fault characteristics are input into the fault diagnosis model of the variable pitch power system and the fault diagnosis model of the mechanical component of the variable pitch system, and the fault type of the real-time fault characteristics is judged; and if the real-time fault characteristics are judged not to belong to the two types of fault models, inputting the real-time fault characteristics into a control system fault diagnosis model of the variable pitch system for diagnosis.
8. The wind turbine pitch system fault diagnosis method according to claim 7, wherein: in step 5, the fault diagnosis result includes a fault reason and a fault position.
9. The wind turbine pitch system fault diagnosis method according to claim 8, wherein: in step 2, the historical operating data is subjected to preprocessing and then fault feature extraction is carried out; the preprocessing comprises denoising, filtering, translating and amplifying the electric signals of the historical operating data to obtain standard operating data with the amplitude range of 0-5V.
10. The wind turbine pitch system fault diagnosis method according to claim 9, wherein: in the steps 1-5, the data collector is adopted to obtain the wind driven generator operation data measured by all the SCADA systems, and the computer is adopted to store and finish data storage, fault diagnosis and result display.
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