CN108731919A - A kind of axial fan blade fault detect experimental bench and method - Google Patents
A kind of axial fan blade fault detect experimental bench and method Download PDFInfo
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- CN108731919A CN108731919A CN201710262820.1A CN201710262820A CN108731919A CN 108731919 A CN108731919 A CN 108731919A CN 201710262820 A CN201710262820 A CN 201710262820A CN 108731919 A CN108731919 A CN 108731919A
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- experimental bench
- wind turbine
- laser sensor
- fan blade
- fault detect
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- 238000000034 method Methods 0.000 title abstract description 10
- 238000004458 analytical method Methods 0.000 claims abstract description 10
- 238000002474 experimental method Methods 0.000 claims description 9
- 238000012360 testing method Methods 0.000 claims description 6
- 230000001105 regulatory effect Effects 0.000 claims description 3
- 241001075561 Fioria Species 0.000 claims 1
- 241000883990 Flabellum Species 0.000 claims 1
- 230000008450 motivation Effects 0.000 claims 1
- 238000001514 detection method Methods 0.000 abstract description 5
- 238000005065 mining Methods 0.000 abstract description 5
- 230000007613 environmental effect Effects 0.000 abstract 1
- 230000007797 corrosion Effects 0.000 description 3
- 238000005260 corrosion Methods 0.000 description 3
- 206010021703 Indifference Diseases 0.000 description 2
- 238000003745 diagnosis Methods 0.000 description 2
- 238000009434 installation Methods 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 230000000737 periodic effect Effects 0.000 description 2
- 238000010183 spectrum analysis Methods 0.000 description 2
- 230000006641 stabilisation Effects 0.000 description 2
- 238000011105 stabilization Methods 0.000 description 2
- 208000037656 Respiratory Sounds Diseases 0.000 description 1
- 230000015556 catabolic process Effects 0.000 description 1
- 239000003245 coal Substances 0.000 description 1
- 238000010835 comparative analysis Methods 0.000 description 1
- 230000000052 comparative effect Effects 0.000 description 1
- 238000002405 diagnostic procedure Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 230000007257 malfunction Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000011022 operating instruction Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000001681 protective effect Effects 0.000 description 1
Classifications
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- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21F—SAFETY DEVICES, TRANSPORT, FILLING-UP, RESCUE, VENTILATION, OR DRAINING IN OR OF MINES OR TUNNELS
- E21F1/00—Ventilation of mines or tunnels; Distribution of ventilating currents
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04D—NON-POSITIVE-DISPLACEMENT PUMPS
- F04D25/00—Pumping installations or systems
- F04D25/02—Units comprising pumps and their driving means
- F04D25/08—Units comprising pumps and their driving means the working fluid being air, e.g. for ventilation
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M13/00—Testing of machine parts
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- Engineering & Computer Science (AREA)
- Mining & Mineral Resources (AREA)
- Mechanical Engineering (AREA)
- General Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Life Sciences & Earth Sciences (AREA)
- Geochemistry & Mineralogy (AREA)
- Geology (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)
- Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
Abstract
The present invention is a kind of laser sensor ranging fan blade fault detect experimental bench and Examination on experimental operation, belong to Mining Axial-Flow Fanner's field of fault detection, including frequency converter, axial fan and shield, power supply adaptor, signal sampler, computer, sensor, sensor advancement mechanism and wind turbine fixed station.The experimental bench of the present invention, the distance feature signal in addition to the common single failure of blade can be extracted, moreover it is possible to analyze the fault-signal of various faults mixing.By modern signal analysis method, the fault-signal feature of corresponding fault type is extracted, then applies to engineering and is verified in practice, it was demonstrated that the reliability of this experimental bench and method.Experimental bench of the present invention has many advantages, such as strong to environmental suitability, simple in structure, easy to operate, while detecting that fault type is more, does not have particular/special requirement to the mine ventilator of detection, huge impetus is played to the detection of modern wind turbine blade fault.
Description
Technical field
The invention belongs to Mining Axial-Flow Fanner's field of fault detection, including fault detect experimental bench and the inspection of corresponding failure
Survey method.
Background technology
During coal mining, the air circulation under mine is most important, consequently found that ensureing that wind turbine runs well and energy is pre-
Know that the method for fan trouble becomes particularly important.Currently in order to ensureing the normal operation of wind turbine, generally use periodic maintenance and more
The method changed.For some wind turbines, since the severe either other reasons of working environment can go out before periodic maintenance or replacement
Existing failure, jeopardizes the life security of people；There are also wind turbines can also continue to use after replacement, cause the wave being not necessarily to
Take.This experimental bench using sensor measurement blade tip arrive sensor distance change, to reach blade breakdown judge and
Prediction.For the fault type that Mining Axial-Flow Fanner's are likely to occur, acquires, handles in an experiment respectively, analyzing respective institute
Corresponding distance change feature, then apply in actual Fault Diagnosis of Fan, in the premise for ensureing people's personal safety
Under, increase the service life of wind turbine.
Invention content
The purpose of this patent is to provide a kind of biography that can be used for detecting, monitor and prejudging axial fan blade failure
Sensing is away from experimental bench.Since the fault type of axial fan blade is relatively more, there are crackle, fracture, spot corrosion etc., so experimental bench
Blade must be it is dismountable, simultaneously because failure caused by vibration it is larger, so safeguard procedures must be installed additional.This sensing
Range finding experiments platform includes mainly：Frequency converter, axial fan and shield, power supply adaptor, signal sampler, computer, sensing
Device, sensor advancement mechanism.Wind turbine is fixed on Special experimental platform；Upper ranging hole is opened every 90 degree in surveyed wind turbine barrel, totally two；
Sensor advancement mechanism is mounted on the top in ranging hole；Wind turbine realizes the testing requirements of different rotating speeds by Frequency Converter Control；It passes
Sensor is connected with signal sampler, realizes the acquisition of distance signal；Signal passes through computer analyzing processing, realizes different wind turbine leaves
The feature extraction of piece different faults.
The adjustment of X, Z-direction, the cooperation that adjustment passes through screw thread and screw thread pair may be implemented in the sensor advancement mechanism
Rotation is realized.
The step of extracting signal using sensing Range finding experiments platform is as follows：
Step 1：Experimental bench is connect with ground, it is ensured that experimental bench non-loosening during the experiment；Secure the fan to experimental bench
On, ensure that experimental bench is integrated with wind turbine；Protective cover is mounted on fan blade end；Sensor advancement mechanism is fixed on wind turbine
Ranging hole above, within the position to sensor measurement range that adjusts sensor and blade end.
Step 2：Connect frequency converter, main circuit of the air blower；Connect power supply adaptor, sensor, signal sampler, computer
Measuring circuit.
Step 3：The distance signal of normal blade, each failure blade is acquired respectively.It is logical that one ranging hole corresponds to a signal
The signal in road, and one group of Blade measuring is multiple, compares the signal in each group of data and unlike signal channel, selects best analysis
Signal.
Step 4：By computer, the feature of signal Analysis compares the feature of normal blade, when summing up single failure
Signal characteristic.
Step 5：Failure blade and good blade are subjected to random combine, analyze fault-signal feature when multiple faults, with
And the extracting method under interference signal.
Step 6：The correctness of check test in engineer application.
Advantages of the present invention：
The present invention obtains fault detection method using the method for sensor instrument distance, compared to analysis of vibration signal, small with interference,
The simple advantage of equipment；The adjusting of both direction may be implemented in the regulating device of sensor；This experiment measure distance mainly by
The effect of centrifugal force and realize variation, and centrifugal force is related with speed, and the application of frequency converter allows fault measuring range to increase；Together
When, in mechanical failure diagnostic method, analysis of vibration signal method has been achieved for huge achievement, therefore the distance letter measured
Number, it can also be analyzed with the analysis method of vibration signal.
Description of the drawings
Fig. 1 is the general structure figure of Mining Axial-Flow Fanner's；
Fig. 2 is sensor fitting arrangement；
Fig. 3 is sensor both direction regulating mechanism；
Fig. 4 is testing stand entirety explanatory note figure；
Description of symbols in attached drawing.In Fig. 1：1-into air duct；2-level-one air ducts；3-two level air ducts；4-three-level air ducts；5-expand
Dissipate cylinder.In Fig. 2：1-air duct holder；2-protective covers；3-forward-backward adjustment bolts；4-mounting brackets；5-up and down adjustment bolts.
In Fig. 3：1-mounting bracket；2-forward-backward adjustment bolts；3-sensor mounting plates；4-installation fixed blocks；5-up and down adjustment spiral shells
Bolt.
Specific implementation mode
The blade material of this experiment is ZL, and 6 blades are installed on each impeller, it is common can to extract fan blade
Single failure characteristic signal and combined fault characteristic signal.Power of motor is 1.1KW, rated speed 1450r/min, specified
Voltage is 220V；Frequency converter uses single-phase 820MV23015L types frequency converter, power 1.5KW；Signal acquisition is using one ocean of Beijing
The YSV dynamic signal acquisitions instrument and its analysis system of company.
Using blade fault type as rippling, failure blade number is 1 progress operating instruction：
（One）, installation 6 intact blades
1. with reference to figure 4, the part of various pieces, adjustment sensor to the height of blade tip to 30 ~ 50mm are installed；
2. powering on, frequency converter is adjusted, it is made to arrive rated speed, waits for stabilization of speed；
3. connecting the power supply of sensor, signal sampler, computer, the signal in two channels is acquired, after comparing basic indifference,
Interception preserves for use；
4. the analysis method of applying vibration signal carries out spectrum analysis.
（Two）5 intact, 1 spot corrosion blades are installed
1. being replaced with a piece of spot corrosion blade a piece of in above-mentioned blade；
2. powering on, frequency converter is adjusted, it is made to arrive rated speed, waits for stabilization of speed；
3. connecting the power supply of sensor, signal sampler, computer, the signal in two channels is acquired, after comparing basic indifference,
Interception preserves for use；
4. the analysis method of applying vibration signal carries out spectrum analysis.
（Three）The data of many experiments comparative analysis obtain the fault signature of a piece of pitting fault blade.
（Four）The fault-signal that practical wind turbine is measured in engineering analyzes the accuracy of contrast test.
Continue the fault signature of test multi-disc pitting fault blade, the also feature of other failure blades, and combination event
Hinder the fault signature of blade.
In summary, by after this experiment, we can obtain a set of standard for judging fan blade failure, Wo Menke
To carry out fault diagnosis and malfunction monitoring with it.The blade fault type of wind turbine is diversified, how to extract main event
It is also important to hinder type.In engineering, it is only necessary to which then measuring distance signal carries out Comparative result and is assured that wind
The fault type of machine blade.For important events, it can also be monitored in real time, manpower and financial resources is greatly saved.
Claims (10)
1. a kind of laser sensor ranging fan blade fault detect experimental bench, including wind turbine fixed station, which is characterized in that wind turbine
Fixed station is closely connect with ground, and wind turbine is fixed on wind turbine fixed station；Motor and wind turbine one；Laser sensor passes through biography
Sensor regulating device keeps correct position with wind turbine；The signal that laser sensor detects is transmitted to meter by signal sampler
Calculation machine, finally corresponding fault signature is extracted in analysis on computers.
2. laser sensor ranging fan blade fault detect experimental bench according to claim 1, which is characterized in that described
Motor is two-phase alternating current motivation.
3. according to claim 1 and the laser sensor ranging fan blade fault detect experimental bench described in 2, feature is required to exist
In motor is fixedly connected with blower fan cylinder, and must keep being reliably connected with wind turbine fixed station.
4. laser sensor ranging fan blade fault detect experimental bench according to claim 3, which is characterized in that electronic
Machine is mounted in blower fan cylinder, and concentric with flabellum rotational trajectory, is axial-flow type laser sensor ranging fan blade fault detect
Experimental bench.
5. laser sensor ranging fan blade fault detect experimental bench according to claim 1, which is characterized in that wind turbine
With motor, motor should be connect with wind turbine fixed station using bolt and nut.
6. laser sensor ranging fan blade fault detect experimental bench according to claim 1, which is characterized in that experiment
Platform must can detect a variety of fan leaf failures.
7. laser sensor ranging fan blade fault detect experimental bench according to claim 6, which is characterized in that wind turbine
Blade is necessary for replaceable, and to have ready failure blade.
8. laser sensor ranging fan blade fault detect experimental bench according to claim 6, which is characterized in that wind turbine
Speed governing must can be carried out by frequency converter.
9. laser sensor ranging fan blade fault detect experimental bench according to claim 8, which is characterized in that laser
The picking rate of sensor has to the requirement for reaching highest rotation speed of fan.
10. laser sensor ranging fan blade fault detect experimental bench according to claim 9, which is characterized in that real
Requirement will be reached by testing the integral rigidity of platform, and nut must be locking.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710262820.1A CN108731919A (en) | 2017-04-20 | 2017-04-20 | A kind of axial fan blade fault detect experimental bench and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710262820.1A CN108731919A (en) | 2017-04-20 | 2017-04-20 | A kind of axial fan blade fault detect experimental bench and method |
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| Publication Number | Publication Date |
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| CN108731919A true CN108731919A (en) | 2018-11-02 |
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| CN201710262820.1A Pending CN108731919A (en) | 2017-04-20 | 2017-04-20 | A kind of axial fan blade fault detect experimental bench and method |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109443735A (en) * | 2018-12-21 | 2019-03-08 | 杭州戬威机电科技有限公司 | A kind of detection device of blade of wind-driven generator surface defect |
-
2017
- 2017-04-20 CN CN201710262820.1A patent/CN108731919A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109443735A (en) * | 2018-12-21 | 2019-03-08 | 杭州戬威机电科技有限公司 | A kind of detection device of blade of wind-driven generator surface defect |
| CN109443735B (en) * | 2018-12-21 | 2024-03-19 | 杭州戬威机电科技有限公司 | Detection device for surface defects of wind driven generator blade |
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| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20181102 |
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| WD01 | Invention patent application deemed withdrawn after publication |