The present invention is concerned with method and apparatus for monitoring gas turbine blades, in particular for monitoring blades such as compressor blades mounted on the gas turbine shaft in such a way that they can swivel relative to the shaft on which they are mounted. Embodiments of the invention can be used to monitor the health of the compressor blades mounted on a gas turbine, and as part of arrangements for monitoring the speed of rotation of a gas turbine shaft.
Particular preferred embodiments of the invention allow one to detect when a blade may be damaged or worn. Information on damaged or worn blades is very important to the gas turbine user because it could affect operation of the turbine. This type of damage could easily happen when a small metal object is ingested by the turbine inlet and passes to the compressor where it could cut or bend the tips of several blades. As a result of this damage, the efficiency of the turbine would be reduced and the turbine could suffer severe vibrations due to the lost balance.
The detection of damaged or worn blades may also be used to improve the accuracy of arrangements which monitor the movement of the turbine blades to determine the speed of rotation of the shaft on which the blades are mounted.
The speed of a rotating gas turbine shaft can be monitored by monitoring the movement of the electrically conductive blades through a constant magnetic flux pattern using sensors such as those described in, for example, GB 2,265,221, GB 2,223,103, U.S. Pat. No. 3,984,713 and GB 1,386,035. The sensor monitors the changes in a magnetic field generated by eddy currents induced in a blade as it passes through a constant magnetic field. It is also possible to use a magnetic field generated by an a.c. supply to a coil. The passage of each blade generates a probe signal pulse and the probe signal train is used to calculate the rotational speed of the shaft by measuring the time between successive pulses, or counting a number of pulses in a fixed time. Preferred embodiments of the invention easily and effectively compensate for missing pulses which arise when a signal train omits a pulse corresponding to gas turbine's full complement of blades. Such so-called “missing pulses” situation may arise because of sensing errors, or deterioration and/or breakage of a blade or blades.
The present invention provides a method as defined in the independent claims to which reference should now be made. Preferred features of the invention are defined in the dependent claims.
Preferred embodiments of the invention of the subject application provide an effective method of identifying that gas turbine blade pulses or signal peaks are missing. This can be used both to monitor the health of the blades and for compensating for such errors in the use of the sensed signals to determine the gas turbine's speed.
Known methods and apparatus for monitoring the speed of rotation of a gas turbine shaft, operate by measuring the time period between successive pulses corresponding to successive blades, and dividing it by the known separation between the blades. However, if the pulse corresponding to a particular blade is missing, the respective time period will not correspond to the known separation between two adjacent blades. For example, if a single blade pulse is missing then the separation between blade pulse signal will correspond to double the separation between two adjacent blades. Failure to pick up that pulses are missing and to then compensate for missing pulses could then have a potentially dramatic effect on the calculated speed as the distance would be wrong.
An important advantage of the invention is that it allows one to detect when a blade may be damaged or worn. Information on damaged or worn blades is very important to the gas turbine user because it could affect operation of the turbine. This type of damage could easily happen when a small metal object is ingested by the turbine inlet and passes to the compressor where it could cut or bend the tips of several blades. As a result of this damage, the efficiency of the turbine would be reduced and the turbine could suffer severe vibrations due to the lost balance.
Presently, damaged or worn blades are detected by vibration sensors which pick up the vibrations which arise when a sufficient number of blades is/are damaged for the turbine to be unbalanced. When the vibration level is too high a pre-set alarm trips and stops the turbine. However it is important to know about the damage to the blades as soon as possible to avoid damage to other parts of the turbine such as bearings. The subject invention could be part of an engine health monitoring system which detects damaged blades and provides information well before the dangerous vibration level is reached
It is possible to envisage that such a monitoring system could evaluate the severity of the blade damage by changing the level of detection of the receiving pulse amplitude until the condition of ‘missing pulse’ occurs. Since the pulse amplitude depends on the air gap between the tip of the blade and the sensor, the damage to the blade will result in a larger air gap and therefore smaller signal amplitude. The monitoring system should be able to detect not only impact damage but also any unusual slow wear and erosion of the tip of the blades affecting only some of the blades.
Preferred embodiments of the invention are particularly advantageous in monitoring gas turbine blades whose tips can more relatively to each other. They allow for a fast and accurate measurement which compensates for the errors arising from such movement.
Preferred embodiments of the present invention will be described, by way of example only, with reference to the attached figures. The figures are only for the purposes of explaining and illustrating preferred embodiments of the invention and are not to be construed as limiting the claims. The skilled man will readily and easily envisage alternative embodiments of the invention in its various aspects.
In the figures:
a and 1b are a schematic illustration of a speed sensor set up to determine the time intervals between successive tips of the blades of a turbine as they move past the sensor, in which
In a preferred embodiment of the present invention, the speed of a gas turbine shaft having, say, twenty-nine compressor blades mounted thereon is calculated based on measurements from a speed sensor (or speed sensors) such as the eddy current sensor described in GB 2,265,221. The sensor(s) produce a signal when a blade passages them in the manner described in GB 2,265,221. Data processing coupled to the sensor(s) output either measure the time interval between the passage of successive sensed blades, or the time interval between the passage of a blade past two sensors separated by a known distance. Passage of the blade(s) past the sensor(s) causes changes in the voltage or current induced in the sensor output. The sensors have their output connected to data processing apparatus. The data processing apparatus may be a digital engine control unit, or a separate data processing unit delivering signal to a digital engine control unit.
Referring to
A speed sensor 5 (see
In this text, reference is made to signals, signal pulses or peaks. For a magnetic sensor, what happens is that as a features approaches and then moves away from the sensor, a signal similar to a single sine wave results (i.e. having positive and negative peaks). The position of the signal or pulse for the purposes of the described embodiments is usually taken to be the zero crossing point between the positive and negative peaks. Blade periods are measured between successive zero crossings.
The fixing of the compressor blades of a gas turbine by a pin attachment (see
As shown in
A data processor (not shown) is coupled to the speed sensor 5 to receive as an input the sequence of pulses generated by the sensor. There may be significant time variation errors produced by the jitter effect, and missing pulses, as illustrated in
To simplify the following description of the preferred embodiment, normalised times will be used, where ‘1’ shall represent the nominal time period between perfectly positioned blades passing the sensors.
For example, if there is assumed to be ±7.5% blade jitter on each blade (i.e. blade jitter expressed as a percentage of nominal or theoretical blade separation) as shown in
BP
min=1−2×0.075=1−0.15=0.85 (1)
and a maximum blade period of:
BP
max=1+2×0.075=1+0.15=1.15 (2)
However, when one missing pulse (13) is present, as shown in
BP
min=1+1−(2×0.075)=1.85 (3)
and a maximum blade period is calculated by:
BP
max=1+1+2×0.075=2.15 (4)
Therefore, the presence of a single missing pulse gives a nominal normalised blade period of 2; two missing pulses give a nominal BP of 3; and so on.
In the following discussions of methods embodying the invention, ‘AV’ is used for the number of blade periods over which an average blade period is taken, and ‘M’ is the total number of missing pulses present in that sample taken over AV blade periods (see
One method of detecting missing pulses Is based on finding the ratio, R, of the latest blade period (LBP) to the average blade period over the last AV periods of measurements (BPAV) (see
As each successive blade tip passes the sensor 5, a pulse is generated and the attached circuitry measures the latest blade period LBP (the elapsed time between successive blades passing the sensor) and these values are stored in a memory.
When a predetermined number AV of blades have been detected by the sensor, an average blade period over the AV periods is calculated.
If there are ‘M’ missing pulses in a compressor disc having ‘K’ blades and in the latest blade period, there are ‘D’ missing pulses (see
LBP=D+1±2×j (5)
where: j is the maximum value of blade jitter
The total of the blade periods to be averaged is:
T=AV+M±2×j (6)
The average blade period over the last AV periods is then:
BP
AV
=T/AV (7)
The values of LBP and BPAV are then used to calculate the Ratio, R, of the latest blade period (LBP) to the average blade period over the last AV periods of measurements (BPAV) is then:
Ratio=LBP/BPAV=(LBP/T)×AV (8)
This ratio is at a maximum when LBP has its largest value and T has its smallest value:
This ratio is at a minimum when LBP has its smallest value and T has its largest value:
By way of an example of the detection of the total number of missing pulses in AV blade periods, equations (9) and (10) set out above have been used to calculate the Ratiomax and Ratiomin for various values of blade jitter and various values of D (number of missing pulses in last blade period) and M (number of missing pulses in a single revolution of compressor disc).
For each value of D, the ‘relevant lines’ are the outermost lines (e.g. lines 7, 8 for D=1, where 7 is the line corresponding to D=1, M=5, minimum, and 8 is the line corresponding to D=1, M=1, maximum) plotted for that value of D, (see
As each successive blade passes sensor 6, the value of R (see equation 8) for the latest blade period is calculated by the system's data processors
If the calculated value of R would, if plotted on the graph of
For example (see
For a turbine compressor disc having, say, twenty-nine blades, AV must be less than 29-M, but the larger it is the better resolution it has, so 20 is a compromise, The M and D values are selected as 0 to 5 because, in practice, when 5 out of 29 blades are damaged, turbine vibrations are so large that the turbine must be shut down. M and/or D could however be equal to 6, 7, 8 or 9.
To simplify the process described above of determining the value of D, the value of D that corresponds to a range of values of R for the latest blade period can put in a table format as shown below in Table 1 below. Software implementing the invention would use a look-up table corresponding to such a table.
As described above, K is only possible to determine D for a value of R where the jitter value does not exceed the given maximum jitter value given in Table 1, which corresponds to the jitter limit of the hatched regions A to F (
The maximum value of jitter for a given turbine is established during a separate test. In practice, the blade jitter experienced by the turbine blades during shaft rotation is much smaller than the limits given in Table 1.
To establish the number of missing pulses, M, in a full revolution of the bladed shaft, the calculations have to be performed K−ΣD times, where: K is the number of blades attached to the compressor disc, and ΣD is the sum of detected missing pulses in the Latest Blade Period. D is measured during every measurement, so the sum of Ds should give M, but the calculations are performed K−ΣD times to try and avoid counting the same Ds twice.
In a second method embodying the invention, for detecting the presence of missing pulses, the number of blade periods to be averaged, AV, includes the Latest Blade Period as shown in
In this method, the cumulative total of the blade periods to be averaged is:
T=AV+(M−D)±2×j (11)
The average blade period is calculated by:
BP
AV
=T/AV (12)
The ratio of the latest blade period to the average blade period over the last AV periods of measurements is then calculated by:
Ratio=LBP/BPAV=LBP/T×AV (13)
Again, this ratio is at a maximum when LBP has its largest value and T has its smallest value and the ratio is at a minimum when LBP has its smallest value and T has its largest value.
The same process as that described for the above method is then used to ascertain the values of D and M for use in calculating the shaft rotational speed.
When the blade jitter values are larger than the maximum permissible values listed in Table 1, or it is possible that more than 5 missing pulses may be present in K periods, it may be more reliable to use a method based on the measurements of blade to blade times using the predictor-limiter method of GB 2,414,300. The predictor limiter-method removes missing pulses blade periods and therefore blade to blade time measurements give us a Reference Period.
The predictor-limiter arrangement of GB 2,414,300 works by predicting blade time periods from historical sensed blade time periods. Only sensed blade time periods which fall within a defined range of acceptable values are used to calculate predicted time periods with blade time periods outside the range of acceptable values being ignored as likely to correspond to a missing pulse or blade. If a sensed period is outside the _acceptable range of values, its predicted value is used in place of that sensed value to predicts its future value. The predicted blade time periods are used as the output measure of blade periods. The sensed blade time periods are only used for predictions. It is the predicted blade periods which are used as the measure of blade time period which can then be used, to monitor or to measure shaft speed or, as described below, determine missing pulses to calculate the speed of the shaft.
Using this method, the number of missing pulses present in one period is obtained by calculation of the ratio:
The latest blade period is the elapsed time between pulses produced by successive blades passing a single sensor and is calculated by:
LBP=D+1±2×j (17)
where: D is the number of missing pulses, and
The Reference Period is obtained using predictor-limiter calculations as described in more detail in GB 2,414,300 whose contents are hereby incorporated in their entirety by way of reference. In normalised notation, the reference period of equation 16 is equal to 1, hence the ratio of Equation 16 is simply equal to the latest blade period.
The calculations must be performed K−ΣD times to establish M as for method 1 described above.
As described above, a data processor 6 (see
The number of required historical values used to produce the trend line must be optimised to provide accurate tracking speed and response to rapid speed changes. The number of historical values used to calculate the trend line is the length (a number of averaged periods) of the trend line. A short trend line will result in largely noisy predicted values, because it is averaging over a small number of data points. A long trend line will cause slow response in case of speed changes and a large error in case the average slope of the time interval curve is not linear. The length of the trend line must be set for each type of engine using its experimental data.
The ‘Length’ of the predictor is determined by the time needed for the averaged value of noise to be close to zero. For example, for a turbine shaft with 29 blades the average jitter value is zero after 29 periods, therefore the predictor length should be 29 periods for a system measuring the speed of such a turbine.
For the gas turbine shaft of
y=m×+b (17)
where x is the blade period number.
Any of the known trend line generation methods may be used. The trend line also need not be linear. Clearly in certain circumstances the trend line may be a curve (i.e. a quadratic or higher order trend line).
For example using the values of
for x=36
y=0.0044*36+2.016
y=1.8576 (18)
Next the limiter is applied. For a limiter set at 40% the algorithm looks like follows:
IF the new value is larger than the predicted value times 1.4, OR is smaller than the predicted value times 0.6, THEN the new value is rejected and the predicted value is accepted as a new value. ELSE a new value is accepted.
Next, the accepted value is used to calculate the next trend line for periods 8 to 36
For the accepted value=1.407
a new trend line is y=−0.0073x+2.063
the predicted value for x=37, y=1.7929
and the above process is repeated.
Length (a number of averaged periods) of the trend line
The chosen value of the limiter is determined by the value of maximum jitter. During normal operation the limiter should not limit the jitter but should detect missing pulses and spurious pulses.
The limit shown on
As a result of performing the above described calculations the measured time signal shown in
The accuracy of speed calculation depends on the amount of jitter, acceleration/deceleration rate, the length of a trend line and the level of limit.
The results of calculations of the ratios of equation 16 is shown in
As with the previous methods of determining the number of missing pulses, the value of D is only admissible where the maximum blade jitter value is not exceeded. In practice, blade jitter of 0.25 is never observed, hence the value of D should always be ascertainable from Table 2. Software implementing the invention can therefore work with an equivalent look-up table.
Embodiments of the invention could include a determination of the jitter associated with each blade by measuring the blade to blade separation. This could either be done for a particular set of gas turbine blades on a test bed, or during the initial running of an engine when it is unlikely that blades will be sufficiently worn or damaged for there to be any missing pulses to affect the blade to blade separation measurements using time periods past the sensor and the known nominal blade to blade separation. Tests suggest that the where the blade jitter is up to about 12%, the first method described above in connection with
Whichever method of determining the number of missing pulses present is employed, the result is the total number of missing pulses, M, that result from a complete revolution of the bladed shaft.
For embodiments of the invention which are used to monitor the health of gas turbine blades, the pulses train could be connected to a variable level pulses detection system. The system would record an average or peak signal amplitude and determine when (and the number of) signals having their amplitude, say, 10%, 20&, 30% etc lower than the reference amplitude and that could be used as an indication of the level of damage to the blades. The relation between level of signal and the level of damage would be established empirically and used to populate a look-up table against which the sensed signal amplitudes could be compared.
Features of preferred embodiments of the invention in its various aspects are set out in the following numbered paragraphs:
Number | Date | Country | Kind |
---|---|---|---|
0725073.1 | Dec 2007 | GB | national |