WO1982001416A1 - Procede et appareil pour la detection et l'identification des aubes d'une turbo-machine vibrant excessivement - Google Patents

Procede et appareil pour la detection et l'identification des aubes d'une turbo-machine vibrant excessivement Download PDF

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Publication number
WO1982001416A1
WO1982001416A1 PCT/US1980/001341 US8001341W WO8201416A1 WO 1982001416 A1 WO1982001416 A1 WO 1982001416A1 US 8001341 W US8001341 W US 8001341W WO 8201416 A1 WO8201416 A1 WO 8201416A1
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WO
WIPO (PCT)
Prior art keywords
signal
blade
vibrating blade
detecting
turbomachine
Prior art date
Application number
PCT/US1980/001341
Other languages
English (en)
Inventor
Inst Franklin
Original Assignee
Leon Robert L
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Leon Robert L filed Critical Leon Robert L
Priority to DE19803050608 priority Critical patent/DE3050608A1/de
Priority to PCT/US1980/001341 priority patent/WO1982001416A1/fr
Priority to JP4567081A priority patent/JPS5767825A/ja
Publication of WO1982001416A1 publication Critical patent/WO1982001416A1/fr

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Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
    • G01H1/00—Measuring characteristics of vibrations in solids by using direct conduction to the detector
    • G01H1/003—Measuring characteristics of vibrations in solids by using direct conduction to the detector of rotating machines
    • G01H1/006—Measuring characteristics of vibrations in solids by using direct conduction to the detector of rotating machines of the rotor of turbo machines

Definitions

  • This invention relates generally to a method and apparatus for detecting and identifying excessively vibrating blades in a turbomachine and, more particularly, to such a method and apparatus which is employed while the turbomachine is operating.
  • turbomachinery blade failures are a major problem and, particularly in the steam turbine generator area, are the cause of many forced outages for U.S. electrical generating ⁇ utilities.
  • the blade will experience cracks, which may be the result of high cycle fatigue or stress corrosion combined with fatigue. In either event, it is undesir ⁇ able and excessive blade vibration that leads to the formation of a fatigue crack and to eventual blade failure.
  • High amplitude, resonant, order related blade vibration results when one of the forcing frequencies that act on a rotating turbomachinery blade coincides with one of the blade's many natural frequencies.
  • the forcing frequencies which may cause such excessive blade vibration comprise all of the multiples of nozzle passing frequency, and all of the multiples of running speed.
  • the former arise from the series of kicks that each blade receives in passing the nozzle wakes, while the latter are due to flow non-uniformi ⁇ ties arising from the horizontal split of the nozzle diaphragms and casing, internal struts, inlet or exhaust openings, nozzle plates, or the like.
  • the multiples, or harmonics of the fundamental forcing frequency are caused by the non-sinusoidal nature of the forcing waveform.
  • the values of all these forcing frequencies are precisely known for each blade stage. This is not the case, however, for the natural frequencies of the various blades.
  • the amplification factor indicates how the vibration amplitude varies with the degree of match. For example, for just a 1% difference between the forcing frequency and the natural frequency, the vibration amplitude drops to 25% of its full resonant value for an amplification factor of 200, and to 12% of its full ' resonant value for an amplification factor of 400.
  • the turbomachine may be operated in a safer, more efficient manner while avoiding the inconvenient and expensive outages which may result from unanticipated turbine blade failures.
  • the present invention provides a method and apparatus for detecting and identifying one or more accidentally vibrating blades of the rotating portion of a turbomachine by analysis of the characteristic Doppler waveform as sensed by a nearby stationary acoustic sensor.
  • the Doppler waveform is the result of the single frequency acoustic energy radiated by the blades, and the changing position and velocity of the blades relative to the sensor.
  • the method comprises sensing the total acoustic energy at a fixed location proximate the rotating portion of the turbomachine to generate a composite electrical signal. Signal manipulations are then performed upon the composite signal in both the time domain and the frequency domain to remove the- undesirable noise generated components in order to reveal the characteristic Doppler waveform.
  • the signal manipulations include: detecting the composite signal; synchronous time averaging to remove random noise and undesirable non-order related components and blanking out the order related noise components.
  • the resulting characteristic Doppler waveform is then displayed for interpretation by the operator, or it may be additionally manipulated prior to display to further aid in its interpretation.
  • Fig. 1 is an axial sectional view of a portion of a steam turbine
  • Fig. 2 is a sectional view of the steam turbine of Fig. 1 taken along line 2-2;
  • Fig. 3 is a schematic block diagram of a first method of detecting and identifying excessively vibrating blades of a turbomachine
  • Fig. 4A j _ is a graphic representation of the waveform at point A of Fig. 3:
  • Fig. 4A2 is a graphic representation of the frequency spectrum at point A of Fig. 3;
  • Fig. 4B ⁇ _ is a graphic representation of the waveform at point B of Fig. 3;
  • Fig. 4B2 is a graphic representation of the frequency spectrum at point B of Fig. 3;
  • Fig. 4C-L is a graphic representation of the waveform at point C of Fig. 3;
  • Fig. 4C2 is a graphic representation of the frequency spectrum at point C of Fig. 3;
  • Fig. 4D ] _ is a graphic representation of the waveform at point D of Fig. 3;
  • Fig. 4D 2 is a graphic representation of the frequency spectrum at point D of Fig. 3;
  • Fig. 4E j _ is a graphic representation of the waveform at point E of Fig. 3;
  • Fig. 4E 2 is a graphic representation of the frequency spectrum at point E of Fig. 3
  • Fig. 5 is a schematic block diagram of a second embodiment of the present invention.
  • a portion of a turbomachine for example, a steam turbine 10.
  • the steam turbine 10 is of a type generally well known in the art and a detailed explanation of all of its structure and operation is not necessray for a complete understanding of the present invention.
  • a pressurized operating fluid in this case steam
  • the steam flows to the right or axially downstream over a plurality of generally radially directed circumferentially distributed guide vanes or nozzles 12 which terminate in a ring 13 and are arranged to concentrate and properly orient the steam flow.
  • the concentrated and properly oriented steam then flows over a plurality of generally outwardly radially extending buckets or turbine blades 14 which are attached through a suitable rotor disk 16 to a centrally located axially rotating turbine shaft 18.
  • energy is removed from the steam and is imparted through the blades to drive the shaft 18 into rotation.
  • the steam may then pass downstream to subsequent stages of nozzles and blades (not shown) where additional energy may be removed from the steam and imparted to the rotating shaft 18.
  • the rotating turbine shaft 18 may be employed to do useful work, for example, by driving an electric generator unit (not shown) .
  • the present invention involves a method for pinpointing the specific individual blades of an operating turbomachine that are vibrating excessively, utilizing the acoustic energy radiated by the vibrations of the blades as determined by a fixed dynamic pressure transducer or sensor 20.
  • the sensor 20 may be mounted in the turbine casing 11 slightly downstream from the rotating blades 14.
  • any rotating turbo ⁇ machinery blade that is vibrating excessively will radiate acoustic energy into the surrounding fluid environment at the frequency of its vibration. If the radiated energy is to be detected by a relatively fixed or stationary sensor 20 and if the energy radiating blade is simultaneously rotating such that it has a velocity component along a line joining the moving blade and the fixed sensor 20, then the frequency of the energy radiated from the blade as detected by the sensor 20 will be altered from the frequency actually radiated from the blade.
  • V is the velocity of sound in the operating fluid.
  • the blade As the vibrating blade moves around to position B, the blade is closer to the sensor 20 and has a significant instantaneous velocity component toward the sensor 20. Thus, both the amplitude and the frequency of the energy radiated from the blade as detected by the sensor 20 are substantially increased.
  • the vibrating blade reaches position C, it is closer yet to the sensor 20 and its instantaneous velocity component toward the sensor 20 is at its maximum.
  • the amplitude of the energy radiated from the vibrating blade as received by the sensor 20 is increased and the frequency of the radiated energy as detected by the sensor 20 is at its maximum.
  • the vibrating blade At position D, the vibrating blade is instantan- eously at its closest distance to the sensor 20 so the amplitude of the radiat ' ed energy received by the sensor 20 from the vibrating blade is at its maximum value. However, since there is no instantaneous velocity component of the vibrating blade in the direction toward the sensor 20, the frequency of the blade vibrations as detected by the sensor 20 is the actual frequency of the vibrating blade.
  • the distance from the sensor 20 and thus the amplitude of • the energy received by the sensor 20 is the same as it was at position- C.
  • the frequency detected by the sensor 20 is at its minimum.
  • the amplitude of the energy received by the sensor 20 is the same as it was at position B but the negative instantaneous velocity component of the blade results in the frequency detected by the sensor 20 being below the actual blade vibrating frequency.
  • the present invention involves a straightforward method for manipulating the output signal from the sensor 20 in order to circumvent the above-discussed real world operational problems involved in employing the moving source Doppler technique to detect and identify one or more excessively vibrating turbine blades.
  • the turbine 10 is assumed to comprise 64 nozzles and 67 blades, each blade having an effective radius of .762 m (30 inches).
  • the turbine shaft 18 is assumed to be rotating at a constant 3000 rpm, thereby establishing the circumfer ⁇ ential velocity of the blades 14 at 239.4 meters/second (9,425 inches/second).
  • the radius of the turbine casing at the location of the sensor 20 is .838 meters (33 inches).
  • the velocity of sound in the steam is assumed to be 381 m/s (15,000 in/s), and, since the absolute velocity of the steam leaving the blades 14 is mostly axial, the steam serves to increase the effective sound velocity only when a vibrating blade is near the sensor 20. For simplicity, this is neglected in the ensuing discussion.
  • FIG. 3 there.is shown a functional block diagram of the method " of the present invention.
  • the first step shown in functional block 30 is the sensing of the composite acoustical signals at a single fixed location slightly downstream from the turbine stage, for example, by sensor 20.
  • Fig. 4A ⁇ _ shows the single revolution waveform at point A of Fig. 3 resulting from the sensing of the aggregate acoustical signal. It is clear from Fig. 4A ⁇ _ that no characteristic Doppler waveform is readily discernable.
  • Fig. 4 is a representation of the corresponding frequency spectrum of the single revolution waveform signal at point A of Fig. 3. As expected, the broadbanded frequency spectrum in this form is not particularly helpful in detecting or identifying the three excessively vibrating turbine blades.
  • the random steam flow noise component may be substantially reduced from the sensed acoustic signal at point A of Fig. 3 through the application of the known procedure of synchronous time domain averaging as shown in functional block 32.
  • a once per revolution phase reference signal is generated (as shown in functional block 34 of Fig. 3) and is utilized in the time domain averaging procedure.
  • the phase reference signal may be accomplished by known sensing methods.
  • a fixed fiberoptical probe (not shown) may be employed to sense the passing of a small reflective tape segment located at a fixed position on the turbine shaft 18.
  • the phase reference sensing results in the generation of a pulse each time the same portion of the turbine shaft 18 passes by the probe, thereby
  • the phase * reference pulses are employed in the synchronous time averaging process to indicate the beginning of each revolution of the turbine shaft 18 and the beginning of each sampling process.
  • the number of samples in a record may .be any value, but it is, usually some power of two.
  • 512 samples per record are assumed for this example. Additionally, the sampling interval or time spacing between each of the 512 samples may be any fixed value; however, it is preferred to have the sampling interval such that all 512 samples comprise exactly one revolution. This is accomplished by frequency multiplying the phase reference signal by 512 (functional block 36), the resultant signal serving as the sampling clock.
  • the waveform must be low pass filtered at less than half this sampling rate prior to its being sampled to prevent aliasing.
  • the synchronous time domain averaging process involves a repetition of sampled records, each starting at the phase reference, with the corresponding sampled points of each then added algebraically and divided by the total number of. averages. The result is that any signal which is not repeated at the exact same point in the rotational cycle eventually averages to zero. Obviously, the random steam flow noise as well as any other random or non-synchronous noise signals fall into this category.
  • the repetitive Doppler waveform from any blades that are vibrating excessively at some multiple of running speed, as well as any other order related signals remain undiminished by the time domain averaging process*. It will be appreciated that the length of time that the time domain averaging process is continued may vary depending upon the relative amplitudes of the random noise signals to the desirable Doppler waveform signals. Obviously, the longer the time averaging is continued, the less significant the randon noise signals become. In the case of a turbine operating at 3000 rpm, up to 10,000 averages could be completed in less than seven minutes.
  • FIG. 43 j _ A representation of the single revolution waveform at point B of Fig. 3 resulting after significant synchronous time domain averaging is shown on Fig. 43 j _. As shown, although the synchronous time averaging process is effective in removing the random noise, the resulting signal is still insufficient to reveal the needed information regarding the excessively vibrating blades.
  • Fig. 4B2 shows the corresponding frequency spectrum. Even though only the magnitude is shown in Fig. 4B2 the frequency spectrum actually includes both magnitude and phase information because of the known. starting position as established with the phase reference sensing of functional block 34. Thus, it is possible to go back and forth between the frequency domain and the time domain at will in order to perform signal manipulations in either domain.
  • Fig. 4B2 shows the characteristic Doppler spectrum of the waveform of Fig. 4B ⁇ _, but gives no clear indication of how many turbine blades may be vibrating excessively or in what positions the vibrating blades may be located. In fact, it shows no clear evidence of Doppler at all. The problem, of course, relates to the presence of a few large discrete components, clearly visible in the spectrum.
  • Fig. 4C 2 shows the modified spectrum at point C of Fig. 3 and Fig. 4C ⁇ _ shows the corresponding modified reconstructed time waveform obtained by inverse transforming of the modified spectrum of Fig. 4C2 «
  • the three Doppler signatures that were buried in the original time waveforms of Fig. 4A ⁇ _ and 4B ] _ are now readily apparent, with no shifting in the time domain occurring from the frequency domain blanking and inverse transform procedure.
  • the capability of locating the three excessively vibrating blades remains unimpaired despite the frequency blanking process.
  • the essence of the technique should now be clear.
  • the Doppler mechanism transforms the single frequency of the vibrating blades into a broadband multi-frequen ⁇ cy function which contains information as to the location of the vibrating blades. Like the original frequency, all the new frequencies are order related since the waveform retains its rotationally repetitive nature in the time domain. Thus, it is at once possible to use synchronous time domain averaging to remove the non-rotational masking effects, and to use discrete frequency blanking to remove the order related masking effects, the latter process hardly distorting the desired signal since the information in the Doppler signature is spread so broadly in the frequency domain.
  • a key feature of the present invention is its ability to identify the location of the excessively vibrating blades.
  • the object is to know exactly when the vibrating blade is directly beneath the sensor. This does not coincide with the maximum frequency point or with the minimum frequency point, each of which is difficult to ascertain from the waveform anyway. Rather, it coincides with the maximum of the amplitude envelope of the waveform, corrected by the time it takes for sound to travel to the sensor from a blade directly beneath it (see formula 1 above) . In this example, this correction time is .0762 (3 in.) divided by 381 m/s, (15,000 in/s) , or 0.20 ms.
  • the amplitude envelope of the waveform may be developed, as shown in Fig. 4D ⁇ _, by first detecting
  • Detecting has the dual effect of shifting the frequency of the original Doppler signature upward, while adding in a new frequency band as shown in the corresponding frequency spectrum of 4D 2 »
  • the resulting waveform of Fig. 4E- j _ is then displayed (functional block 44 of Fig. 3) for purposes of analysis by an operator.
  • the three time markers of Fig. 4E ⁇ _ at 5.20 ms, 7.59 s, and 10.27 ms (w- ⁇ th 0.20 ms added for the travel time correction) , correspond to the .times from the beginning of the record (when the phase reference pulse appears) that the three excessively vibrating blades pass beneath the sensor 20.
  • the resolution from one blade to the next is 0.30 ms in this example.
  • the enhanced characteristic Doppler waveform detects the vibrating blades, indicates their relative vibration level and pinpoints their location.
  • the displayed signal may be analyzed over a period of time to determine changes in the relative amplitude of a blade's vibration. As discussed above, the changes are indicative of the initiation or propagation of a blade crack.
  • the above-described method may be employed to detect and identify excessively vibrating turbomachin ⁇ ery blades in cases in which the vibrations are order related.
  • the above-described method may be employed to detect and identify such vibrating blades where the vibrations are caused by nozzle passing frequency, running speed, or any harmonics thereof.
  • the above-described method is not effective in detecting and identifying such vibrating blades where the vibrations are non-order related.
  • self-excited vibration of a turbine blade at its own natural frequency independent of the running speed or flutter is such a non-order related vibration which ' may not be detected by the above-described method.
  • the single sensor 20 detects the non-order related vibrations as well as the order related vibrations, the subsequent signal manipulation steps as described above are established to isolate the order related vibrations and to eliminate non-order related signals. Accordingly, to employ the moving source Doppler technique for the detection and identi- fication of excessive non-order related vibrations in the blades, it is necessary to slightly modify the above-described method of manipulating the signal from the sensor.
  • Fig. 5 shows another embodiment of the present invention which may be employed for the detection and identification of either order related or non-order related vibrations in rotating turbomachinery blades.
  • the method makes use of the fact that the envelope of the Doppler waveform is order related even though the waveform itself may not be.
  • the signal manipulation steps of the method of Fig. 5 are substantially the same as those of the above-described method as shown in Fig. 3, except that the order of the steps is slightly rearranged. Accordingly, the functional blocks of Fig. 5 will be identified using the same reference numerals as were used on Fig. 3 with the addition of primes thereto.
  • the dynamic pressure sensing 30' phase reference sensing 34' and frequency multiplying 36' operations, as well as the sampling rate, are exactly the same as the corresponding operations of the embodiment of Fig. 3.
  • the signal from the dynamic pressure sensing 30' are first passed through a detecting operation 40' wherein the signals are essentially full wave rectified.
  • the subsequent synchronous time averaging operation 32' averages the Doppler waveform to the mean value of its envelope and the random noise to a D.C. value (rather than to zero as is done in the embodiment of Fig. 3) .
  • the detected and envelope time averaged signal is then passed to the order related noise blanking operation 38' wherein, operating in the frequency domain as described above, the. undesirable, now doubled, order related components of the signal (i.e., blade passing component) , as well as the D.C. component resulting from the time averaging of the random noise components, are blanked out of the signal.
  • the order related noise blanking operation 38' wherein, operating in the frequency domain as described above, the. undesirable, now doubled, order related components of the signal (i.e., blade passing component) , as well as the D.C. component resulting from the time averaging of the random noise components, are blanked out of the signal.
  • OM related noise blanking operation 38' yields a time domain waveform which, in the case of non-order related vibrations, will be similar to the waveform of Fig. 4E ] _.
  • the time domain waveform may be directly displayed and interpreted to determine the location of the excessively vibrating blades.
  • a reconstruction of the frequency domain signal remaining after the order related noise blanking operation 38' yields a time domain waveform which is similar to the waveform of Fig. 4D* j _.
  • An inverse transformation of the signal remaining after the high frequency blanking operation results in a time domain waveform similar to that of Fig. 4E- j _ which may then be displayed and interpreted.
  • the present invention comprises a method and apparatus for detecting and identifying excessively ' vibrating turbomachinery blades which is relatively simple to employ and requires only a single stationary sensor for each rotating blade stage. It will be recognized by those skilled in the art that changes or modifications may be made to the above-described embodiments without departing from the broad inventive concepts of the invention. It is understood, therefore, that this invention is not limited to the

Abstract

Procede et appareil pour detecter et identifier une ou plusieurs aubes (14) de la partie rotative d'une turbo-machine (10) animees de vibrations excessives, utilisant l'analyse de l'onde caracteristique de Doppler qui resulte du passage de l'aube (14) en vibration et en rotation devant un capteur (20) immobile. L'energie acoustique dans le voisinage de la partie rotative de la turbo-machine (10) est captee pour produire un signal electrique composite representant le spectre acoustique a bande large. Ensuite les composantes indesirables du signal composite sont eliminees a la fois dans le domaine du temps et de la frequence. Le signal resultant est ensuite affiche pour reveler l'onde caracteristique de Doppler des vibrations de l'aube (14), onde qui peut etre analysee pour indiquer l'emplacement de l'aube (14) animee de vibrations excessives ainsi que l'amplitude de ces vibrations. Une evolution de cette amplitude dans le temps indique l'amorce ou la propagation d'une fissure dans l'aube.
PCT/US1980/001341 1980-10-10 1980-10-10 Procede et appareil pour la detection et l'identification des aubes d'une turbo-machine vibrant excessivement WO1982001416A1 (fr)

Priority Applications (3)

Application Number Priority Date Filing Date Title
DE19803050608 DE3050608A1 (de) 1980-10-10 1980-10-10 Method and apparatus for detecting and identifying excessively vibrating blades of a turbomachine
PCT/US1980/001341 WO1982001416A1 (fr) 1980-10-10 1980-10-10 Procede et appareil pour la detection et l'identification des aubes d'une turbo-machine vibrant excessivement
JP4567081A JPS5767825A (en) 1980-10-10 1981-03-30 Method of and apparatus for detecting and discriminating excessively vibrating blades of turvo machine

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
WOUS80/01341801010 1980-10-10
PCT/US1980/001341 WO1982001416A1 (fr) 1980-10-10 1980-10-10 Procede et appareil pour la detection et l'identification des aubes d'une turbo-machine vibrant excessivement

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DE (1) DE3050608A1 (fr)
WO (1) WO1982001416A1 (fr)

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
GB2248110A (en) * 1990-09-19 1992-03-25 Rolls Royce Plc Vibration analysis system for a multi-shaft turbine
GB2318873A (en) * 1996-11-02 1998-05-06 Asea Brown Boveri Method and device for measuring rotor blade vibrations
GB2322988A (en) * 1997-03-06 1998-09-09 Marconi Gec Ltd Damage assessment using radar
GB2476555A (en) * 2009-12-22 2011-06-29 Gen Electric Acoustic detection of turbomachine blade crack
WO2014018727A1 (fr) * 2012-07-25 2014-01-30 Siemens Energy, Inc. Procédé et système de surveillance d'état de lame rotative
CN114746625A (zh) * 2019-12-05 2022-07-12 西门子能源美国公司 用于识别裂纹的涡轮叶片健康监测系统

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4413519A (en) * 1981-07-29 1983-11-08 Westinghouse Electric Corp. Turbine blade vibration detection apparatus

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US3400578A (en) * 1965-12-06 1968-09-10 Curtiss Wright Corp Acoustical analyser for indicating faults in operative parts of highspeed engines
US3731526A (en) * 1971-08-05 1973-05-08 United Aircraft Corp Variable center frequency filter

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US3400578A (en) * 1965-12-06 1968-09-10 Curtiss Wright Corp Acoustical analyser for indicating faults in operative parts of highspeed engines
US3731526A (en) * 1971-08-05 1973-05-08 United Aircraft Corp Variable center frequency filter

Cited By (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
GB2248110A (en) * 1990-09-19 1992-03-25 Rolls Royce Plc Vibration analysis system for a multi-shaft turbine
GB2248110B (en) * 1990-09-19 1994-08-31 Rolls Royce Plc Engine vibration analysis system for a multi shaft turbine
GB2318873A (en) * 1996-11-02 1998-05-06 Asea Brown Boveri Method and device for measuring rotor blade vibrations
GB2322988A (en) * 1997-03-06 1998-09-09 Marconi Gec Ltd Damage assessment using radar
GB2476555A (en) * 2009-12-22 2011-06-29 Gen Electric Acoustic detection of turbomachine blade crack
US8074499B2 (en) 2009-12-22 2011-12-13 General Electric Company Method and system for detecting a crack on a turbomachine blade
GB2476555B (en) * 2009-12-22 2013-06-05 Gen Electric Method and system for detecting a crack on a turbomachine blade
WO2014018727A1 (fr) * 2012-07-25 2014-01-30 Siemens Energy, Inc. Procédé et système de surveillance d'état de lame rotative
US9739167B2 (en) 2012-07-25 2017-08-22 Siemens Energy, Inc. Method and system for monitoring rotating blade health
CN114746625A (zh) * 2019-12-05 2022-07-12 西门子能源美国公司 用于识别裂纹的涡轮叶片健康监测系统
CN114746625B (zh) * 2019-12-05 2024-02-20 西门子能源美国公司 用于识别裂纹的涡轮叶片健康监测系统

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JPS5767825A (en) 1982-04-24
DE3050608A1 (de) 1982-11-04

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