CN116576075B - Fan blade life prediction method based on blade vibration signals - Google Patents
Fan blade life prediction method based on blade vibration signals Download PDFInfo
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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
- F03D—WIND MOTORS
- F03D17/00—Monitoring or testing of wind motors, e.g. diagnostics
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- G—PHYSICS
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- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
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- 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
- F05B2260/82—Forecasts
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
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- F05B2270/00—Control
- F05B2270/30—Control parameters, e.g. input parameters
- F05B2270/334—Vibration measurements
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Abstract
The invention provides a fan blade life prediction method based on blade vibration signals, which comprises the steps of acquiring blade acceleration signals in real time by utilizing a vibration sensor arranged on a blade of a generator set, processing the blade acceleration signals to acquire blade deformation, calculating blade load according to the blade deformation, and calculating the fatigue life of the blade by utilizing a rain flow calculation method. According to the fan blade life prediction method based on the blade vibration signals, the vibration sensor is utilized to monitor the blade acceleration data in real time, the blade acceleration data are extracted based on the mode, the blade root load of the fan blade is calculated, the fatigue damage of the blade is calculated and accumulated for a long time, and the functions of monitoring the health state of the blade and predicting the life are achieved.
Description
Technical Field
The invention relates to the technical field of wind turbine generator blade life monitoring, in particular to a fan blade life prediction method based on blade vibration signals.
Background
The blades are important parts of the fan generator set, and along with the continuous increase of the capacity of the generator set, the length and the weight of the blades are also continuously increased. The blade is often caused to have abnormal problems such as abnormal vibration of the blade, unbalance of the impeller and the like due to manufacturing problems and structural problems. And serious accidents such as tower sweeping and tower reversing of the unit are easy to occur in severe cases. Therefore, it is particularly important to evaluate the health of the blade.
In blade monitoring, the most commonly used method is to evaluate the health of the blade by monitoring the amplitude of vibration in the blade flapping and edgewise directions. In this blade state monitoring method, only the blade is monitored instantaneously, and calculation of the load of the blade and damage evaluation cannot be achieved. At present, the control and protection of the whole fan are carried out in a mode of analyzing the vibration signals of the blades by using the cabin acceleration signals, but effective information of the impeller surface which can be obtained from the cabin acceleration data of the unit is limited, and the vibration conditions of the blades and the impeller surface cannot be comprehensively reflected. In addition, there are video monitoring methods, audio monitoring methods, etc., the video monitoring methods can only identify the surface fault characteristics of the blade, the fault identification coverage is insufficient, and the audio identification monitoring methods are not easy to identify due to serious surrounding noise.
Disclosure of Invention
In order to solve the defects of the prior art, the invention provides a fan blade life prediction method based on a blade vibration signal, which utilizes a vibration sensor to monitor blade acceleration data in real time, extracts the blade acceleration data based on a mode, calculates blade root load of a fan blade, calculates blade fatigue damage and accumulates for a long time, and realizes the functions of monitoring the health state of the blade and predicting the life.
The invention adopts the technical proposal for solving the technical problems that: the fan blade life prediction method based on the blade vibration signals comprises the following steps:
S1, acquiring a blade acceleration signal in real time by using a vibration sensor arranged on a blade of a generator set;
S2, processing the blade acceleration signals to obtain the blade deformation;
s3, calculating the blade load according to the deformation of the blade;
And S4, calculating the fatigue life of the blade by using a rain flow calculation method.
In step S1, the installation position of the vibration sensor is determined according to the blade mode, and the vibration sensor is installed in the range of the maximum blade deformation under the first-order mode and the second-order mode.
The step S2 specifically comprises the following steps:
S2.1, carrying out FFT conversion on the blade acceleration signals to obtain frequency domain amplitude values under each frequency, wherein the frequency domain amplitude values comprise an acceleration frequency domain amplitude value a 1st under the first-order modal frequency of the blade and an acceleration frequency domain amplitude value a 2nd under the second-order modal frequency of the blade,
S2.2, screening the frequency domain amplitude values under each frequency, and screening out an external excitation frequency a excition, a blade first-order modal frequency omega 1st and a blade second-order modal frequency omega 2nd;
s2.3, converting the frequency domain amplitude of the external excitation frequency into the corresponding amplitude of the modal frequency through an amplification coefficient by the following formula:
a1st-excition＝βa-1sta1st
a2nd-excition＝βa-2ndand
Wherein a 1st-excition and a 2nd-excition are the frequency amplitude of the first-order mode of the blade corresponding to external excitation and the frequency amplitude of the second-order mode of the blade corresponding to external excitation, and β a-1st and β a-2nd are the acceleration amplification factor of the first-order mode frequency of the blade and the acceleration amplification factor of the second-order mode frequency of the blade respectively, and are obtained by the following formulas:
Wherein lambda 1st is the ratio of the external excitation frequency domain to the first-order modal frequency of the blade, lambda 1st＝aexcition/a1st,λ2nd is the ratio of the external excitation frequency domain to the first-order modal frequency of the blade, lambda 2nd＝aexcition/a2nd, For damping ratio, the empirical value is 0.002;
S2.4, calculating the corresponding amplitude of the converted modal frequency to obtain the blade deformation under the first-order modal frequency and the blade deformation under the second-order modal frequency of the vibration sensor installation position through the following formulas, and summing the blade deformation to obtain the actual deformation of the blade:
Wherein S 1st and S 2nd are respectively the blade deformation at the first-order mode frequency and the blade deformation at the second-order mode frequency at the vibration sensor mounting position, and ω 1st and ω 2nd are respectively the blade first-order mode frequency and the blade first-order mode frequency;
S2.5, obtaining a first-order vibration mode and a second-order vibration mode of the blade by utilizing the blade model, and calculating the deformation of the whole blade by combining the actual deformation of the blade.
The step S3 specifically comprises the following steps:
s3.1, when the blade generates first-order vibration, calculating the curvature radius rho of each section of the blade through the first-order mode shape and amplitude;
s3.2, calculating the load of each section of the blade according to the following formula:
where M is the section load, EI is the bending stiffness, obtained from the blade material parameters, ρ is the radius of curvature, calculated from the radius of curvature formula of the blade mode shape curve y=y (x):
Wherein,
The invention has the beneficial effects based on the technical scheme that:
(1) According to the fan blade life prediction method based on the blade vibration signals, the installation position of the vibration sensor is determined through the blade mode, so that the sensor can accurately reflect the change response of the wind turbine generator blade;
(2) The fan blade life prediction method based on the blade vibration signal can be used for verifying whether the actual deformation of the new model blade is matched with the design deformation of the blade;
(3) The fan blade life prediction method based on the blade vibration signal can be used for monitoring the fatigue damage of the blade and predicting the residual life of the blade.
Drawings
FIG. 1 is a schematic diagram of a process flow of a fan blade life prediction method based on a blade vibration signal.
Fig. 2 is a schematic view of a vibration sensor mounting position.
FIG. 3 is a simplified model schematic of blade vibration.
Detailed Description
The invention is further described below with reference to the drawings and examples.
Since the blade model can be simplified as a bending deformation of the cantilever beam with the bottom fixed, its simplified model is shown in fig. 3. The cantilever beam is decomposed into a multi-degree-of-freedom dynamic system, and the total vibration is the linear superposition effect of the vibration of each mode. Since the energy proportion of the first order and the second order of the blade is maximum in the actual vibration, the blade vibration can be calculated through the first order and the second order modes of the blade.
Based on the principle, the invention provides a fan blade life prediction method based on a blade vibration signal, and referring to fig. 1, the method comprises the following steps:
S1, acquiring a blade acceleration signal in real time by using a vibration sensor arranged on a blade of the generator set. Referring to fig. 2, the installation position of the vibration sensor is determined according to the blade mode, and is installed in the range of the maximum deformation amount interval of the blade in the first-order mode and the second-order mode.
S2, processing the blade acceleration signals to obtain the blade deformation. The method specifically comprises the following steps:
S2.1, carrying out FFT conversion on the blade acceleration signals to obtain frequency domain amplitude values under each frequency, wherein the frequency domain amplitude values comprise an acceleration frequency domain amplitude value a 1st under the first-order modal frequency of the blade and an acceleration frequency domain amplitude value a 2nd under the second-order modal frequency of the blade,
S2.2, screening the frequency domain amplitude values under each frequency, and screening out an external excitation frequency a excition, a blade first-order modal frequency omega 1st and a blade second-order modal frequency omega 2nd;
s2.3, converting the frequency domain amplitude of the external excitation frequency into the corresponding amplitude of the modal frequency through an amplification coefficient by the following formula:
a1st-excition＝βa-1sta1st
a2nd-excition＝βa-2ndand
Wherein a 1st-excition and a 2nd-excition are the frequency amplitude of the first-order mode of the blade corresponding to external excitation and the frequency amplitude of the second-order mode of the blade corresponding to external excitation, and β a-1st and β a-2nd are the acceleration amplification factor of the first-order mode frequency of the blade and the acceleration amplification factor of the second-order mode frequency of the blade respectively, and are obtained by the following formulas:
Wherein lambda 1st is the ratio of the external excitation frequency domain to the first-order modal frequency of the blade, lambda 1st＝aexcition/a1st,λ2nd is the ratio of the external excitation frequency domain to the first-order modal frequency of the blade, lambda 2nd＝aexcition/a2nd, The damping ratio is a blade parameter, and the empirical value is 0.002;
S2.4, calculating the corresponding amplitude of the converted modal frequency to obtain the blade deformation under the first-order modal frequency and the blade deformation under the second-order modal frequency of the vibration sensor installation position through the following formulas, and summing the blade deformation to obtain the actual deformation of the blade:
Wherein s 1st and s 2nd are respectively the blade deformation under the first-order mode frequency and the blade deformation under the second-order mode frequency at the installation position of the vibration sensor, and ω 1st and ω 2nd are respectively the blade first-order mode frequency and the blade first-order mode frequency;
S2.5, obtaining a first-order vibration mode and a second-order vibration mode of the blade by utilizing the blade model, and calculating the deformation of the whole blade by combining the actual deformation of the blade.
And S3, calculating the blade load according to the blade deformation. The method specifically comprises the following steps:
s3.1, when the blade generates first-order vibration, calculating the curvature radius rho of each section of the blade through the first-order mode shape and amplitude;
s3.2, calculating the load of each section of the blade according to the following formula:
where M is the section load, EI is the bending stiffness, obtained from the blade material parameters, ρ is the radius of curvature, calculated from the radius of curvature formula of the blade mode shape curve y=y (x):
Wherein,
And S4, calculating the fatigue life of the blade by using a rain flow calculation method.
According to the fan blade life prediction method based on the blade vibration signals, the vibration sensor is utilized to monitor the blade acceleration data in real time, the blade acceleration data are extracted based on the mode, the blade root load of the fan blade is calculated, the fatigue damage of the blade is calculated and accumulated for a long time, and the functions of monitoring the health state of the blade and predicting the life are achieved.
Claims (3)
1. A fan blade life prediction method based on a blade vibration signal is characterized by comprising the following steps:
S1, acquiring a blade acceleration signal in real time by using a vibration sensor arranged on a blade of a generator set;
s2, processing the blade acceleration signals to obtain the blade deformation; the method specifically comprises the following steps:
S2.1, carrying out FFT (fast Fourier transform) on the blade acceleration signal to obtain frequency domain amplitude values under each frequency, wherein the frequency domain amplitude values comprise the acceleration frequency domain amplitude values under the first-order mode frequency of the blade And the frequency domain amplitude of acceleration at the second order modal frequency of the blade，
S2.2, screening the frequency domain amplitude values under each frequency to screen out the external excitation frequencyFirst order modal frequencies of bladeBlade second order modal frequencies；
S2.3, converting the frequency domain amplitude of the external excitation frequency into the corresponding amplitude of the modal frequency through an amplification coefficient by the following formula:
，
，
Wherein, AndThe frequency amplitude of the external excitation corresponding to the first-order mode of the blade and the frequency amplitude of the external excitation corresponding to the second-order mode of the blade are respectively obtained,AndThe method is characterized in that the method comprises the steps of respectively obtaining an acceleration amplification factor under the first-order modal frequency of the blade and an acceleration amplification factor under the second-order modal frequency of the blade through the following formula:
，
，
Wherein, Is the ratio of the external excitation frequency domain to the first-order modal frequency of the blade,，Is the ratio of the external excitation frequency domain to the first-order modal frequency of the blade,，Is the damping ratio;
S2.4, calculating the corresponding amplitude of the converted modal frequency to obtain the blade deformation under the first-order modal frequency and the blade deformation under the second-order modal frequency of the vibration sensor installation position through the following formulas, and summing the blade deformation to obtain the actual deformation of the blade:
，
Wherein the method comprises the steps of AndRespectively the blade deformation under the first-order modal frequency and the blade deformation under the second-order modal frequency at the installation position of the vibration sensor,AndRespectively the first-order modal frequency of the blade and the first-order modal frequency of the blade;
S2.5, obtaining a first-order vibration mode and a second-order vibration mode of the blade by utilizing the blade model, and calculating the deformation of the whole blade by combining the actual deformation of the blade;
s3, calculating the blade load according to the deformation of the blade;
And S4, calculating the fatigue life of the blade by using a rain flow calculation method.
2. The fan blade life prediction method based on blade vibration signals according to claim 1, wherein: in step S1, the installation position of the vibration sensor is determined according to the blade mode, and the vibration sensor is installed in the range of the maximum blade deformation under the first-order mode and the second-order mode.
3. The fan blade life prediction method based on blade vibration signals according to claim 1, wherein: the step S3 specifically comprises the following steps:
s3.1, when the blade generates first-order vibration, calculating the curvature radius rho of each section of the blade through the first-order mode shape and amplitude;
s3.2, calculating the load of each section of the blade according to the following formula:
，
wherein M is the section load, EI is the bending stiffness, and is obtained from the blade material parameters, ρ is the radius of curvature, and the blade mode shape curve Is calculated by a curvature radius formula:
，
Wherein, ，。
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| CN107061185A (en) * | 2017-04-14 | 2017-08-18 | 广州特种承压设备检测研究院 | A kind of pneumatic equipment bladess state monitoring method and system based on vibration detection and transmission of wireless signals |
| CN107454925A (en) * | 2015-04-13 | 2017-12-08 | 乌本产权有限公司 | For the method for the remaining life for determining wind energy plant |
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| AU2019478946B2 (en) * | 2019-12-16 | 2024-04-11 | Envision Energy Technology Pte Ltd. | Method and system for monitoring health state of blade root fastener |
| CN113323816A (en) * | 2021-06-09 | 2021-08-31 | 东方电气集团科学技术研究院有限公司 | Blade detection method based on blade load analysis |
| CN115478984B (en) * | 2022-08-04 | 2025-04-01 | 明阳智慧能源集团股份公司 | Method and system for attenuating second-order vibration and load in the front-to-back direction of wind turbine tower |
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| CN107454925A (en) * | 2015-04-13 | 2017-12-08 | 乌本产权有限公司 | For the method for the remaining life for determining wind energy plant |
| CN107061185A (en) * | 2017-04-14 | 2017-08-18 | 广州特种承压设备检测研究院 | A kind of pneumatic equipment bladess state monitoring method and system based on vibration detection and transmission of wireless signals |
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