non intrusive technique for monitoring vibration of...

Non Intrusive Method of Detecting Turbine Blade Vibration in an Operating Power Plant

A.Rama Rao, B.K.Dutta Bhabha Atomic Research Centre Mumbai India [email protected]

Abstract Steam turbine blades are one of the most critical components in power plants. Statistics has shown that LP blades are generally more susceptible to failure compared to blades in HP or IP turbines. The mechanism responsible for these failures is different and complex. A recent survey indicates that cause of over 40% of the blade failures is not fully understood. The two primary forces acting on the blades are the steady centrifugal forces due to rotation and the fluctuating steam bending forces. The paper is about a proposed innovative method of detecting the presence of blade vibration in operating turbine. The method is based on vibration analysis of the turbine casing. The casing vibration also includes the signals associated with the blade passing frequency (BPF) component. When the rotating blades vibrate, the analysis of changes in the BPF is a novel way of diagnosing blade vibrations. Signals captured from operating plants have been analysed and blade vibrations detected. Validation of the proposed technique through experiments demonstrates reliability of the technique as a robust diagnostics for turbine blades.

1. Introduction Steam turbine blades are one of the most critical components in power plant. Harsh working environment such as high temperatures, wet steam, fluctuating load and several cycles of off design operation exerts complex loading on the blades leading to premature failure. Stray blades out of hundreds of normal blade behave abnormally that can lead to a major break down. Statistics has shown that LP blades are generally more susceptible to failure compared to blades in HP or IP turbines. There are many mechanisms by which LP blades can fail. Nearly 50 % of the failures are related to fatigue, stress corrosion cracking and corrosion fatigue. It is also reported that failures initiate at different locations on the blade such as 26% in the shroud, 20% at lacing holes, 40% in the aerofoil region and 14% in the blade attachment or roots. The mechanism responsible for these failures is different and complex. A survey indicates that cause of over 40% of the blade failures is not fully understood. [1] The two primary forces acting on the blades are the steady centrifugal force due to rotation and the fluctuating steam bending forces. The intensity of steam bending force varies from middle of the blade to the free end of the blade. They are high in the middle and relatively low towards the free end. With ever changing load on the turbine, the steam bending force too vary significantly adding to fatigue loading on the blades. Over a long run under fluctuating load conditions, some of the stray blades set itself into self excited vibration in the lower modes. This induces sympathetic vibration in the neighboring blades which could prevail until the off-design condition exists in the turbine. From diagnostic point of view, it is very important to detect blade vibration whenever they happen and prompt for the need to take corrective action if feasible. The normal way of monitoring machinery vibration is to mount vibration transducers on the vibrating body and analyse the captured signals to establish the link between the cause and the effect. For the rotating blades direct measurement is out of question. Leading turbine manufactures have selectively used intrusive methods to aid in depth analysis of design changes in the blade or during special investigation. These methods are

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highly expensive and offer limited scope in investigating blade failure. [2] Primarily they do not directly provide the proof of blade vibration prior to failure. What is required is a reliable method of identifying the presence of blade vibration from the captured signal and link its cause with the possible process responsible for blade vibration. The paper is about a proposed innovative method of detecting the presence of blade vibration in operating turbine. The method is based on capturing turbine casing vibration and analyzing its content to identify blade vibration. The casing vibration also includes the signals associated with the blade passing frequencies (BPF) component. The steam leaving the blades strikes on the casing with a regularity corresponding to the number of blades in any stage. BPF thus is a characteristic feature of the blades in a stage. Every change in the BFP can be associated to the behavior of the rotating blades. When the rotating blades vibrate, the analysis of changes in the BPF is a novel way of diagnosing blade vibrations. The paper deals with results and observation of large number of laboratory experiments with rotating blades. A novel method of inducing vibration in the blades by vibrating air jet that can simulate steam pulsation on the blade is described. Vibration due to BPF is picked up by sensitive microphone sensors in the plane of the blades in the set up. The study described in the paper leads to innovative method of implementing on line turbine blade vibration monitoring system in an operating power plant especially for the low pressure turbine.

2. Turbine blades and sources of vibration With the growth of turbine rating, there has been constant search for better design of last stage blades to efficiently handle the increasing quantities of steam flow within a reasonable number of casings. The last stage blades of LP turbine that contribute approximately 10 % of the overall output of the plant are almost always surrounded by hostile aerodynamic loads due to transonic and often droplet laden flow field. The longest blades are both tapered and twisted to accommodate the demands of mechanical integrity and aerodynamic performance. Use of free standing blades in the last stage blades is very popular choice because of the clean aerodynamic shape; fewer stress concentration and relatively fewer vibratory modes. As the tips of the blades are more flexible, they tend to vibrate more in what is termed as flutter mode. Due to converging and diverging steam flow pattern between the long blades and due to the variation in the manufacturing tolerance in the blade, the tips of the blades are extremely sensitive to steam flow induced vibration. EPRI identified turbine blade failure as the major cause of plant outage. On suggestion of a working group on LP turbine blade problems, EPRI initiated a project to determine the source of blade vibration in operating turbine. [1] The ensuing report broadly classified the sources in three categories. They are harmonic, random and self excited type. The harmonic excitation is periodic and is related to speed of the machine and flow fluctuation synchronous with the speed. Manufacturers tune the blades to avoid harmonic excitations. Random excitations are caused by temporal unsteadiness of the steam flow. Self excitation occurs in any of the lower modes under proper condition. The random phenomenon organizes among the blades themselves into a systematic self-excitation. Self excitation does not need external excitation frequency; instead, the frequency is internally generated. For example, a blade perturbed from equilibrium will vibrate back to equilibrium at its natural frequency. If this vibration modulates the flow so that the resulting dynamic forces act to sustain the vibration, then the blade is vibrating in self excited manner. The vibration is maintained right at the natural frequency. Such a vibration associated with the turbine blades is called flutter and is well recognized cause for fatigue in the blade. Some blades would have the tendency to flutter more than the others and the process is not linearly related to the load. [3] Sudden changes in the stream extraction flow between the stages, off design condition when angle of steam flow into the blade significantly change etc cause stall flutter in the last stage blades. Off design operating condition is faced by almost all types of power plant. During the time the load on the turbine is well below the design conditions due to low demand. The flexibility of operating the plant at loads matching with demand actually causes harm to the turbine. This aspect of self excitation, either intentionally induced or prevailing due to load demand is investigated and analysed in this paper.

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3. Blade Vibrations 3.1 Casing Vibration and analysis of Blade signals The LP casing vibration is combination of harmonic and random excitation caused by the rotor, steam and the acoustics caused by the steam flow. The rotor related frequencies are low corresponding to its speed and couple of higher harmonics. Frequencies related to the blades are called blade passing frequencies (BPF). This corresponds to the product of number of blades in the particular stage and the operating speed. Blade vibrations are monitored indirectly by monitoring the amplitudes of BPF. This is the frequency with which the steam after working on the stage impinges on the casing in every second. The vibration amplitude of BPF is very sensitive to operating condition of the blade. Tuned blades normally do not vibrate during operation. But, when they vibrate due to non-synchronous disturbances such as steam flow instability in the flow passages the amplitude of BPF deviates from the normal value. There are also reported incidences of self-excited vibration under low load and high backpressure. Any deviation in the amplitude of BPF from its normal value is an indication of blade vibration. All such vibrations result in usage of fatigue life of the blade. In view of the high possibility of blade vibration in an operating steam turbine, it is very important to monitor and assess its severity.

3.2 Off design operation in nuclear power plant [4] The nuclear plant under study is originally 220 MWe PHWR consisting of one HP and one LP turbine. Due to limitations in the primary system, the plant was down rated to 170 MWe. The double flow LP rotor consists of 5 stages. The blades in the 5th stage are 945 mm long and the mean diameter of the stage is 2635 mm. This stage has lacing rods at the free end that binds all the 78 blades of the stage. The weight of each blade in this stage is 18.8 kg. As per the Campbell diagram provided by the supplier, the first nodal diameter frequency of the 5th stage is 107 Hz at 3000 rpm. LP casing vibrations were recorded for analysis. During the recording, the LP condenser vacuum was marginally lowered by flow reversal in the water box of the condenser. The process parameters acquired from the control room is shown in figure 1. It shows variation of power, speed and the condenser vacuum. It can be seen that for about 15 minutes between 17:29 o 17:44 hrs, the condenser vacuum dropped due to backwash in water box. Figure 2 shows the 3D spectrum of BPF of the last stage during the above 15 minutes. The prominent peak at 3882 Hz is the BPF. The amplitude of BPF shows variation. The duration of variation exactly matches with the duration of drop in the vacuum. The off design condition created in the condenser indeed vibrated the blades in the 5th stage at its natural frequency causing the variation in BPF. Figure 3 shows 3D spectrum in the band of 101 to 140 Hz. Frequency peak at 107 Hz can be seen emerging above the background during back washing of the condenser carried out to dip the vacuum. The duration of reduction in the amplitude of BPF and emergence of 107 Hz in the low frequency spectrum show a direct correlation establishing the link between cause and the effect. Thus, the analysis established that when the blades in a stage vibrate, amplitude of BPF changes.

MONITORING AND DIAGNOSTICS OF ROTATING MACHINERY 2939

Figure 1: Trend of TG process parameters, power, speed and condenser Vacuum.

Figure 2: 3-D spectrum of Amplitude Trend of BPF (3882 Hz) of LP blades.


Figure 3: Trend of Blade Natural frequency (107 Hz) during poor vacuum.

4. On line Detection of Defective blade [5] LP casing vibration is in fact a storehouse of information about everything inside an operating turbine. All the defects that are related to the rotor speed like rotor unbalance, sub harmonics related to steam or oil whirl and rotor instability appear with relatively strong amplitude. Signals associated to the blade like the BPF appear with low amplitudes. The only format to analyse BPF is the 3D spectrum generated by devices with high signal to noise ratio. As explained in the introduction, nearly 14 % of blade failures has happens at the root section of the blade. One LP turbine of 500MWe thermal power plant was monitored to assess the health of the blades. There was no previous data as reference on similar lines for comparison. In the double flow LP rotor, the last three stages have free standing blades with 48, 58 and 68 number of blades. The unit operates at 3000 rpm. The plant outage was planned in April and so the measurements were carried out in January. The LP casing vibrations were analysed to trend the BPFs of the last three stages. Figure 4 shows 3D spectrum plot with dominant BPF component. In addition to BPF, side bands of 20 Hz appear on the either side of BPF. In the language of signal analysis, this is termed as modulation of BPF by a low frequency component at 20 Hz. It is normal to see side band of 50 Hz to BPF as soon as steam enters LP casing indicating marginal rotor unbalance. The strong low frequency unbalance component is known to modulate high frequency components such as BPF. However, 20 Hz had no relation with the speed. In view of the unexpected spectrum plots, the blades were examined carefully during the planned outage. It was observed that there were 14 blades with crack in the root and 2 blades with more than 20 mm long crack on the leading edge of the blade. All the defects were visually identifiable. The defective blades were replaced and the unit was put back on power. On re-measurement and analysis of BPF, there were no side bands to the BPF. It was concluded that some phenomena in the LP casing with a frequency of 20Hz was impinging on the blades and so modulating BPF of the stage. Figure 5 shows 3 D spectrum after replacement of the defective blades. A clean frequency at BPF has no side bands indicating healthy condition of the blades.


Figure 4: Trend of BPF with side bands at 20 Hz.

Figure 5: Trend of BPF with no side bands after replacement of cracked blades.

5. Laboratory Experiments for validation of Field Observations. From signal analysis point of view, a rotating turbine blade or a rotating fan blade would give identical diagnostic information. In view of this, a setup was erected with an arrangement to rotate a fan with blades at variable speeds and monitor the pulsation in the air flow emerging from the tip of the blades. Figure 6 shows schematic of the setup. A sensitive microphone type of pressure sensor was mounted in the plane of the blades. The air jet was meant for exciting the blades during rotation. With a low frequency shaker connected to the air jet, the blades were excited at variable frequencies.


Figure 6: Set up for experiments on rotating blade

The experiment was carried out on a few numbers of fans with different number of blades. As the set up provided testing at variable speeds, the test speed was selected such that no other frequency component is present in the near vicinity of test speed and its harmonics to avoid mix-up of frequencies and wrong interpretation. Figure-F shows spectrum of pressure signal corresponding to BPF at 35.250 Hz. (11.75x3 Hz). During rotation of the fan, vibrating air jet was impinged on the blades. The air jet sinusoidal vibration was set at 5 Hz.

Figure 7: BPF of the fan with 3 blades rotating at 11.75 Hz


The change in the spectral content of the pressure signal is shown in figure-8. The sidebands to the BPF appear at 5 Hz on either side. The experiment is a proof of modulation of BPF by a strong low frequency component in this case at 5 Hz.

Figure 8: BPF accompanied by side bands at 5 Hz

Comparing the experimental observation with the side bands shown in figure-4 for LP turbine of 500 MWe thermal power station, it can be said that the LP blades were subjected to strong impingement at 20 Hz. It is thus construed that since the side bands disappeared after replacement of cracked blades, 20 Hz excitation has in some way connected to the cracked blades. The message however is, if BPF of any stage of turbine blade is found to be accompanied by side bands at other than rotations speed, the blades are supposed to be under excitation at the side band frequency. Yet in another set of experiment, a fan with 10 blades was tested at 22 Hz. (1320 rpm). The measured natural frequency (NF) of the blade was 179 Hz. Figure 9 shows the spectrum of pressure signal in which the test speed in RPM and BPF can be seen. The rotating blades were excited by steady air jet.

Figure 9: Spectrum plot showing speed of testing and BPF.


The changed spectral content is shown in figure-10. The amplitude of BPF has reduced while the amplitude of the blades natural frequency increases. The test thus establishes the link between the BPF component and the natural frequency of the blade.

Figure 10: Spectrum plot showing speed of testing, BPF and the blade natural frequency.

This also validates the observation made in figure-2 & figure-3 wherein the amplitude of BPF at 3882 Hz reduced due to drop in the vacuum in the condenser and at the same time, the amplitude of blades natural frequency at 107 Hz emerged from the back ground level to a measurable level. The difference in the two observations is that in the LP turbine, blade vibration at natural frequency was caused by the stall flutter where as in the experiment, the natural frequency of the blade excited by the air jet. The common observation in both is that BPF is a reliable parameter for monitoring the health of the blades.

Next, one of the blades in the fan was cut to introduce crack in the blade. The test was repeated at 830 rpm. During the test, the steady air jet was impinged on the fan. Figure-11 shows 3-D spectrum of the pressure signal. The blade passing frequency at 140 Hz showed increase in amplitude due to air jet and the blade natural frequency also shows an increase in amplitude. More tests are required to explain the observation with crack blades.


Figure 11: 3-D spectrum showing BPF and natural frequency of cracked blade

6. Conclusion The rotating turbine blades are prone to vibration related damages in all types of power plants. The LP blades, especially in nuclear plant where the last stage blades interact with wet steam, the chances s of blade vibration and failure is even higher. Intrusive health monitoring system provided by some suppliers has not proved reliable for providing early indications of high vibrations or failure. Besides, they are very expensive and intensive in data processing and interpretation. Blade health monitoring through LP casing vibrations has been shown to be a reliable method for early indication of blade vibration/failure. The method is non intrusive and easy to implement even in operating plants. As blade vibration is vital for safety and economy of the plant, it is advisable to invest in the technique which is less expensive than the bearing and shaft monitoring system for turbine generator set.

Acknowledgement Author would like to acknowledge the support and assistants provided by his colleagues in Vibration Laboratory of BARC, Mumbai, India in this analysis. The opportunity provided by ISTec, Germany to the author for analyzing turbine blade data is gratefully acknowledged.

References [1] R.C.Bates Steam Turbine Blades: Considerations in Design and a Survey of Blade Failures, EPRI project

report No 912-1 CS-1967 August 1981 [2] R.L. Leon, Keith Trainer: Monitoring Systems for steam turbine blade failures, 4th EPRI Annual

conference on incipient failure detection, Philadelphia, Oct 15, 1990


[3] EPRI proceeding: 3rd Incipient failure detection conference August 1988 [4] A. Rama Rao and S.K.Sinha: MAPS-1 & 2 LP Turbine Bearing and Blade Vibrations Report no.

RED/VLS/02-06/05 February 2006 [5] A.Rama Rao and B.C.B.N.Suryam: Turbine vibration analysis of Tata power thermal power plant, report

no. RED/VLS/07-04/05 July 2004


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