CN108956075A - Movable vane piece crackle inline diagnosis method - Google Patents
Movable vane piece crackle inline diagnosis method Download PDFInfo
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- CN108956075A CN108956075A CN201811007564.2A CN201811007564A CN108956075A CN 108956075 A CN108956075 A CN 108956075A CN 201811007564 A CN201811007564 A CN 201811007564A CN 108956075 A CN108956075 A CN 108956075A
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- G—PHYSICS
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- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M7/00—Vibration-testing of structures; Shock-testing of structures
- G01M7/02—Vibration-testing by means of a shake table
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Abstract
The present invention relates to rotating machinery movable vane piece field of fault detection, to establish movable vane piece crackle sample database, it is tested by vibration measuring and obtains blade vibration information, judge whether blade cracks, and realize blade cracks length, the online quantitative Diagnosis of location information, the present invention, movable vane piece crackle inline diagnosis method, steps are as follows: modeling to intact leaf；Further, vibration characteristics and vibration-mode analysis are carried out to the leaf model with different crack positions, different depth crackle, obtains the relationship of Natural Frequency of Blade and crack depth and crack position under the different vibration shapes；Further, the Natural Frequency of Blade that analysis obtains is saved with the relationship of crack depth and position as Blade Crack Fault sample, establishes blade cracks sample database by the relationship for analyzing Natural Frequency of Blade and crack depth and crack position under the different vibration shapes.Present invention is mainly applied to blade faults to detect occasion.
Description
Technical field
The present invention relates to rotating machinery movable vane piece field of fault detection, especially a kind of movable vane piece crackle is quantitative online
Diagnostic method.
Background technique
In the large rotating machineries such as aero-engine, gas turbine, steam turbine, flue gas turbine expander, movable vane piece is as core
Working element, working environment is severe, and especially when aero-engine is run, blade working is in high temperature, high pressure, high centrifugal force
In the extreme environment of high aerodynamic loading, high cycle fatigue damage easily occurs under alternating force effect, cracks, with splitting
The development of line, blade may be broken, and cause serious accident, bring very big influence to the operation of entire engine health.
It is directed to the detection method of blade cracks at present, it is commonly used to belong to off-line checking method more.Such as current vortex inspection
It surveys, generates alternating electromagnetic field using coil, generate current vortex in blade surface to be measured, when blade surface is there are when crackle, generate
Current vortex can change, using coil detection current vortex change situation, it can be achieved that blade cracks detection.Ultrasonic wave inspection
Survey method is encountered the principle that can be reflected when acoustic impedance changes in transmission process based on ultrasonic wave, utilizes ultrasonic waves
Energy device emits ultrasonic wave to blade, and when blade cracks, ultrasonic wave can be reflected in cracks, and be connect by energy converter
It receives, realizes blade cracks detection.X-ray detection method generates latent image using x-ray bombardment blade and on film, when blade goes out
When existing crackle, blade cracks detection can be realized by observation film.Infrared thermal wave detection method, by being heated to blade, benefit
It is transmitted with the heat wave on the method measurement blade of infrared imaging, when, there are when crackle, heat wave transmitting and normal blade are not on blade
Together, it thus can realize that blade cracks detect.In addition there are the methods of Magnetic testings, fluorescent penetrant detection, metal magnetic memory test.
Above method is only capable of measuring under relevant device shutdown status, can not rotor blade health status to real-time motion into
Row detection.
And in terms of blade cracks on-line checking, it there is no mature technology at present.Since fissuring rate can change leaf
The original mechanics parameter of piece, and then change the vibration characteristics of blade, so being generally based on blade vibration on-line detecting system, lead to
It crosses analysis blade vibration and other relevant parameters diagnoses blade cracks, but can only all realize etiologic diagnosis, cannot achieve
Quantitative Diagnosis.
Summary of the invention
In order to overcome the deficiencies of the prior art, the present invention is directed to using intrinsic frequency as fault signature, establish movable vane piece crackle sample
Database is tested by vibration measuring and obtains blade vibration information, judges whether blade cracks, and realize that blade cracks are long
The online quantitative Diagnosis of degree, location information.For this reason, the technical scheme adopted by the present invention is that movable vane piece crackle inline diagnosis method,
Steps are as follows:
Intact leaf is modeled, then on this basic model, chooses the crackle that different location adds different depth,
One group of leaf model with different crack positions, different crack depths is obtained with this；
Further, vibration characteristics and vibration are carried out to the leaf model with different crack positions, different depth crackle
Dynamic model analysis, obtains the relationship of Natural Frequency of Blade and crack depth and crack position under the different vibration shapes；
Further, the relationship for analyzing Natural Frequency of Blade and crack depth and crack position under the different vibration shapes will be analyzed
Natural Frequency of Blade out is saved with the relationship of crack depth and position as Blade Crack Fault sample, is established blade and is split
Grain pattern database；
Further, machining and the consistent one group of simulation blade of basic model parameter, the selected part in this group of blade
Blade adds crackle, and crack position is different from crack depth on different leaves, by all blade stowages in the same leaf dish, with
This obtains the test board for having intact leaf and crackle blade；
Further, test board is installed on whirling test stand, and is equipped with vibration stimulus source on testing stand；
Further, testing stand is opened, revolving speed is drawn high, opens driving source, makes blade edge rotation side vibration；
Further, vibration measuring experiment is carried out to all blades using foil gauge vibration measuring system or Tip-Timing vibration measuring system etc.,
Obtain the vibration informations such as the vaned vibration shape of institute, vibration frequency；
Further, for certain branch blade, by the vibration information of the obtained blade, in conjunction with blade cracks sample database
In sample data, judge whether the blade has crackle, if there is crackle, also can determine blade cracks depth and position believe
Breath realizes the quantitative Diagnosis of blade cracks information.
The features of the present invention and beneficial effect are:
(1) on-line checking of movable vane piece crackle is realized.Equipment, can real-time monitoring foliaceous without shutting down, carrying, dismantle
State carries out fault pre-alarming, is that the health control creation of large rotating machinery equipment may.Can condition maintenarnce, improve detection efficiency,
Reduce the cost of labor of periodic maintenance and detection.
(2) quantitative Diagnosis of movable vane piece crackle is realized.By establishing the blade difference vibration shape and blade cracks position and depth
Mapping relations, carry out quantitative Diagnosis, can accurate judgement blade fault position and depth information, for blade fatigue life prediction mention
For data supporting.
Detailed description of the invention:
Fig. 1 shows the blade cracks inline diagnosis method using intrinsic frequency as fault signature.
Specific embodiment
It, can be with intrinsic frequency because influence of the crackle of different length, different location to blade frequencies is different in the present invention
Rate is fault signature, establishes movable vane piece crackle sample database, is tested by vibration measuring and obtains blade vibration information, judges that blade is
It is no to crack, and realize blade cracks length, the online quantitative Diagnosis of location information.
In order to overcome the deficiencies of the prior art, the present invention proposes a kind of to exist by the movable vane piece crackle of fault signature of intrinsic frequency
Radiodiagnosis x method, primarily to the online quantitative Diagnosis of blade cracks position and depth.
To reach above-mentioned target, the technical method that the present invention takes is as shown in Figure 1.
Further, intact leaf is modeled by softwares such as SolidWorks, Pro/Engineer or Ansys, so
Afterwards on this basic model, chooses different location (in the middle part of blade root, blade or blade tip) and add different depth (0-3 millimeters)
Crackle obtains one group of leaf model with different crack positions, different crack depths with this；
Further, this group is imported in Ansys software with the leaf model of different crack positions, different depth crackle,
Carry out vibration characteristics and vibration-mode analysis, obtain under the different vibration shapes (torsional oscillation, bending vibration and complex vibration) Natural Frequency of Blade with
The relationship of crack depth and crack position；
Further, Natural Frequency of Blade and crack depth and crackle position under the different vibration shapes analyzed according to Ansys software
The relationship set can be learnt if can determine that the intrinsic frequency of blade under a certain vibration shape, just can determine that out crack position and crackle
Limited solution of depth；If can determine that the intrinsic frequency of blade under a variety of vibration shapes, it just can determine that out that crack position and crackle are deep
The unique solution of degree.The relationship of Natural Frequency of Blade and crack depth and position that above-mentioned analysis is obtained is as Blade Crack Fault
Sample is saved, and blade cracks sample database is established；
Further, machining and the consistent one group of simulation blade of basic model parameter, the selected part in this group of blade
Blade adds crackle, and crack position is different from crack depth on different leaves.By all blade stowages in the same leaf dish, with
This obtains the test board for having intact leaf and crackle blade；
Further, test board is installed on whirling test stand (generally by motor, bracket, pedestal composition), and in testing stand
Upper outfit vibration stimulus source (gas stimulus or electromagnetic coil driving source)；
Further, testing stand is opened, revolving speed is drawn high, opens driving source, makes blade edge rotation side vibration；
Further, vibration measuring experiment is carried out to all blades using foil gauge vibration measuring system or Tip-Timing vibration measuring system etc.,
Obtain the vibration informations such as the vaned vibration shape of institute, vibration frequency；
Further, for certain branch blade, by the vibration information of the obtained blade, in conjunction with blade cracks sample database
In sample data, that is, can determine whether the blade has crackle, if there is crackle, also can determine depth and the position of blade cracks
Information realizes the quantitative Diagnosis of blade cracks information.
In order to overcome the deficiencies of the prior art, the present invention proposes a kind of to exist by the movable vane piece crackle of fault signature of intrinsic frequency
Radiodiagnosis x method, mainly solving the technical problems that:
(1) on-line checking of movable vane piece crackle is realized.Equipment, can real-time monitoring foliaceous without shutting down, carrying, dismantle
State carries out fault pre-alarming, is that the health control creation of large rotating machinery equipment may.Can condition maintenarnce, improve detection efficiency,
Reduce the cost of labor of periodic maintenance and detection.
(2) quantitative Diagnosis of movable vane piece crackle is realized.By establishing the blade difference vibration shape and blade cracks position and depth
Mapping relations, carry out quantitative Diagnosis, can accurate judgement blade fault position and depth information, for blade fatigue life prediction mention
For data supporting.
The present invention is implemented as follows:
Further, intact leaf is modeled by softwares such as Ansys, then on this basic model, is chosen different
The crackle of different depth (0-3 millimeters) is added in position (in the middle part of blade root, blade or blade tip), obtains one group with difference with this
The leaf model of crack position, different crack depths；
Further, this group is carried out in Ansys software with the leaf model of different crack positions, different depth crackle
Vibration characteristics and vibration-mode analysis obtain Natural Frequency of Blade and crackle under the different vibration shapes (torsional oscillation, bending vibration and complex vibration)
The relationship of depth and crack position；
Further, Natural Frequency of Blade and crack depth and crackle position under the different vibration shapes analyzed according to Ansys software
The relationship set can be learnt if can determine that the intrinsic frequency of blade under a certain vibration shape, just can determine that out crack position and crackle
Limited solution of depth；If can determine that the intrinsic frequency of blade under a variety of vibration shapes, it just can determine that out that crack position and crackle are deep
The unique solution of degree.The relationship of Natural Frequency of Blade and crack depth and position that above-mentioned analysis is obtained is as Blade Crack Fault
Sample is saved, and blade cracks sample database is established；
Further, machining and the consistent one group of simulation blade of basic model parameter, choose three in this group of blade
Blade adds crackle in blade root position, and crack depth is respectively 1 millimeter, 2 millimeters and 3 millimeters.By all blade stowages same
In a leaf dish, the test board for having intact leaf and crackle blade is obtained with this；
Further, test board is installed on whirling test stand, and is equipped with Gas Vibration driving source on testing stand；
Further, testing stand is opened, driving source is opened, at the uniform velocity draws high revolving speed to 15000 revs/min, drawing high rate is 200
Rev/min, make blade edge rotation side vibration；
Further, vibration measuring experiment is carried out to all blades using foil gauge vibration measuring system or Tip-Timing vibration measuring system etc.,
Obtain the vibration informations such as the vaned vibration shape of institute, vibration frequency；
Further, for certain branch blade, by the vibration information of the obtained blade, in conjunction with blade cracks sample database
In sample data, that is, can determine whether the blade has crackle, if there is crackle, also can determine depth and the position of blade cracks
Information realizes the quantitative Diagnosis of blade cracks information.
Claims (1)
1. a kind of movable vane piece crackle inline diagnosis method, characterized in that steps are as follows:
Intact leaf is modeled, then on this basic model, the crackle that different location adds different depth is chosen, with this
Obtain one group of leaf model with different crack positions, different crack depths；
Further, vibration characteristics and vibration mould are carried out to the leaf model with different crack positions, different depth crackle
State analysis, obtains the relationship of Natural Frequency of Blade and crack depth and crack position under the different vibration shapes；
Further, the relationship for analyzing Natural Frequency of Blade and crack depth and crack position under the different vibration shapes obtains analysis
Natural Frequency of Blade is saved with the relationship of crack depth and position as Blade Crack Fault sample, and blade cracks sample is established
Database；
Further, machining and the consistent one group of simulation blade of basic model parameter, the selected part blade in this group of blade
Crackle is added, crack position is different from crack depth on different leaves, by all blade stowages in the same leaf dish, obtains with this
The test board of intact leaf and crackle blade is had to one；
Further, test board is installed on whirling test stand, and is equipped with vibration stimulus source on testing stand；
Further, testing stand is opened, revolving speed is drawn high, opens driving source, makes blade edge rotation side vibration；
Further, vibration measuring experiment is carried out to all blades using foil gauge vibration measuring system or Tip-Timing vibration measuring system etc., obtained
The vibration informations such as the vaned vibration shape of institute, vibration frequency；
Further, for certain branch blade, by the vibration information of the obtained blade, in conjunction in blade cracks sample database
Sample data, judges whether the blade has crackle, if there is crackle, also can determine the depth and location information of blade cracks, real
The quantitative Diagnosis of existing blade cracks information.
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110068439A (en) * | 2019-04-25 | 2019-07-30 | 西安交通大学 | Rotor blade multiple modal vibrations exciting bank and its motivational techniques |
| CN111239249A (en) * | 2020-03-18 | 2020-06-05 | 北京工业大学 | Ventilator blade crack fault diagnosis method based on Hilbert-Huang transform |
| CN111413404A (en) * | 2020-03-27 | 2020-07-14 | 天津大学 | Blade crack online measurement method based on blade tip timing and support vector machine principle |
| CN111426459A (en) * | 2020-04-13 | 2020-07-17 | 天津大学 | Blade crack online measurement method based on blade tip timing and naive Bayes algorithm |
| CN111636932A (en) * | 2020-04-23 | 2020-09-08 | 天津大学 | Blade crack online measurement method based on blade tip timing and integrated learning algorithm |
| CN112855922A (en) * | 2021-02-11 | 2021-05-28 | 中国人民解放军陆军装甲兵学院 | Planetary gear crack depth evaluation method |
| CN113504302A (en) * | 2021-06-30 | 2021-10-15 | 上海电气风电集团股份有限公司 | Method and system for monitoring fan blade state, electronic equipment and storage medium |
| CN114167026A (en) * | 2021-11-23 | 2022-03-11 | 哈尔滨工程大学 | Experimental device for turbine blade crack quantity online identification |
| CN114166941A (en) * | 2021-11-23 | 2022-03-11 | 哈尔滨工程大学 | Blade crack length parameter online identification method |
| CN114184763A (en) * | 2021-11-23 | 2022-03-15 | 哈尔滨工程大学 | Experimental device and method for online identification of crack positions of turbine blade |
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110068439A (en) * | 2019-04-25 | 2019-07-30 | 西安交通大学 | Rotor blade multiple modal vibrations exciting bank and its motivational techniques |
| CN111239249A (en) * | 2020-03-18 | 2020-06-05 | 北京工业大学 | Ventilator blade crack fault diagnosis method based on Hilbert-Huang transform |
| CN111413404A (en) * | 2020-03-27 | 2020-07-14 | 天津大学 | Blade crack online measurement method based on blade tip timing and support vector machine principle |
| CN111426459A (en) * | 2020-04-13 | 2020-07-17 | 天津大学 | Blade crack online measurement method based on blade tip timing and naive Bayes algorithm |
| CN111636932A (en) * | 2020-04-23 | 2020-09-08 | 天津大学 | Blade crack online measurement method based on blade tip timing and integrated learning algorithm |
| CN112855922A (en) * | 2021-02-11 | 2021-05-28 | 中国人民解放军陆军装甲兵学院 | Planetary gear crack depth evaluation method |
| CN113504302A (en) * | 2021-06-30 | 2021-10-15 | 上海电气风电集团股份有限公司 | Method and system for monitoring fan blade state, electronic equipment and storage medium |
| CN114167026A (en) * | 2021-11-23 | 2022-03-11 | 哈尔滨工程大学 | Experimental device for turbine blade crack quantity online identification |
| CN114166941A (en) * | 2021-11-23 | 2022-03-11 | 哈尔滨工程大学 | Blade crack length parameter online identification method |
| CN114184763A (en) * | 2021-11-23 | 2022-03-15 | 哈尔滨工程大学 | Experimental device and method for online identification of crack positions of turbine blade |
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