Abstract:
A method and system for surge detection within a gas turbine engine, comprises: measuring the compressor discharge pressure (CDP) of the gas turbine over a period of time; determining a time derivative (CDP D  ) of the measured (CDP) correcting the CDP D  for altitude, (CDP DCOR ); estimating a short-term average of CDP DCOR   2 ; estimating a short-term average of CDP DCOR ; and determining a short-term variance of corrected CDP rate of change (CDP roc ) based upon the short-term average of CDP DCOR  and the short-term average of CDP DCOR   2 . The method and system then compares the short-term variance of corrected CDP rate of change with a pre-determined threshold (CDP proc ) and signals an output when CDP roc &gt;CDP proc . The method and system provides a signal of a surge within the gas turbine engine when CDP roc  remains&gt;CDP proc  for pre-determined period of time.

Description:
GOVERNMENT RIGHTS 
     This invention was made with Government support under Contract No. DE-FC02-97EE50470 awarded by the Department of Energy. The U.S. Government has certain rights in this invention. 
    
    
     BACKGROUND OF THE INVENTION 
     The present invention generally relates to methods and systems for surge detection during the operation of turbomachinery. More specifically, the present invention relates to methods and systems for surge detection during the operation of a gas turbine engine by monitoring the short-term variance of altitude-corrected compressor discharge pressure rate of change. 
     Turbomachinery, such as gas turbine engines, APUs and certain types of compressors can experience an undesirable operating condition called surge or stall. Surge typically occurs when a compression stage airflow and pressure become mismatched, i.e., not enough airflow for a given pressure ratio (exit pressure/inlet pressure) or too much pressure ratio for a given airflow. Surge disrupts the operation,of the turbomachine. Characteristics of a single pop surge include rapid drops in compressor discharge pressure (CDP), followed by a rapid recovery of CDP. Severe surge events are multiple pop or locked-in surge, where CDP repeatedly falls and recovers, then falls again and recovers, on and on, at rates up to 10 or more times per second. Surge typically causes a momentary or sustained loss of power and can cause mechanical damage to the turbomachinery. 
     Many turbomachinery control systems attempt to either anticipate an impending surge and initiate corrective action, or detect the initial stages of a current surge condition and take corrective action. Many of the available turbomachinery control systems have limitations such as frequent occurrence of false alarms, measurement of multiple parameters and use various additional components. 
     U.S. Pat. No. 6,231,306 to Khalid (the &#39;306 patent) discloses a control system for preventing a compressor stall in a gas turbine engine. The &#39;306 patent discusses a control system which attempts to detect an impending surge condition in a gas turbine engine and initiates corrective action. The control system of the &#39;306 patent monitors a normalized magnitude of compressor static pressure fluctuations in a frequency band determined by engine speed In order to detect an impending surge condition. The control system of the &#39;306 patent utilizes a signal indicative of the amplified low-pressure compressor disturbances in order to predict an impending surge condition. 
     U.S. Pat. No. 6,059,522 to Gertz et al. (the &#39;522 patent) discloses techniques for diagnosing and avoiding stall In rotary compressors such as aircraft jet engines. The &#39;522 patent discusses the use of a control system that measures compressor flow characteristics by placing one or more pressure sensors in the compressor flow pattern, monitoring the magnitude of compressor pressure fluctuations in a frequency range determined by engine speed. The resultant magnitude signals are compared to known values for the compressor in order to indicate stall susceptibility. 
     U.S. Pat. No. 5,726,891 to Sisson et al. (the &#39;891 patent) discloses a control system for detecting an occurrence of surge in a gas turbine engine. The method of the &#39;891 patent obtains filtered derivatives of engine operating characteristics, principally fan speed and exhaust temperature, compares the filtered derivatives to threshold values and increments a count only if both derivatives exceed their respective threshold values. A surge condition is signaled only if the count is equal to a predetermined value. 
     CDP measurements are commonly used to detect surge. Methods include monitoring for a high rate of change of CDP, a rapid drop in CDP, or rapid drops and recoveries in CDP. Modern turbomachinery control systems monitor CDP pressure, with a bandwidth or sampling rate much higher than that at which the CDP signal changes during operation. This oversampling results in high autocorrelation of CDP (and CDP rate of change) over the short term. Inversely, short-term average signal variance is quite small during normal operation. A surge event causes the short-term autocorrelation to drop dramatically, and causes the short-term variance to soar CDP corrected for altitude (CDP/turbomachine inlet pressure) provides an even better indication of surge. 
     As can be seen, there is a need for an improved method and system in order to detect surge conditions within turbomachinery. The improved method and system should reduce the occurrence of false alarms, i.e., the Incorrect signaling of surges, and quickly detect severe surge conditions by monitoring minimal engine parameters and using minimal sensing components. 
     SUMMARY OF THE INVENTION 
     In one aspect of the present invention, a method of surge detection within a turbomachine compressor comprises: measuring a compressor discharge pressure (CDP) of the turbomachine over a period of time: determining a time derivative (CDP D ) of the measured (CDP); correcting the CDP D  for altitude, (CDP DCOR ), inputting CDP DCOR   2  into a first filter algorithm (FFA); inputting CDP DCOR  into a second filter algorithm (SFA); estimating a short-term average of CDP DCOR   2  by using the FFA; estimating a short-term average of CDP DCOR  by using the SFA; determining a short-term variance of corrected CDP rate of change (CDP roc ) based upon the short-term average of CDP DCOR  and the short-term average of CDP DCOR   2 ; comparing the short-term variance of CDP DCOR  rate of change with a predetermined threshold(CDP proc ); signaling an output when CDP roc &gt;CDP proc ; and signaling an occurrence of a surge within the turbomachine compressor when CDP roc  remains&gt;COP proc  for pre-determined period of time. 
     In another aspect of the present invention, a method of surge detection within a turbomachine compressor comprises: measuring the compressor discharge pressure (CDP) of the turbomachine compressor over a period of time; determining a time derivative (CDP D ) of the measured (CDP); correcting the CDP D  for altitude, (CDP DCOR ); estimating a short-term average of CDP DCOR   2  by using a first filter algorithm (FFA); estimating a short-term average of CDP DCOR  by using the a second filter algorithm (SFA); determining a short-term variance of corrected CDP D  (CDP proc ) based upon the short-term average of CDP DCOR  and the short-term average of CDP DCOR   2 ; comparing the short-term variance of corrected CDP rate of change with a pre-determined short-term variance of CDP rate of change threshold (CDP proc ); signaling an output when CDP roc &gt;CDP proc ; and signaling an occurrence of a surge within the turbomachine compressor when CDP roc  remains&gt;CDP proc  for predetermined period of time. 
     In another aspect of the present invention, a method of surge detection within a turomachine compressor comprises: measuring the compressor discharge pressure (CDP) of the turbomachinery compressor over a period of time; determining a time derivative (CDP D ) of the measured (CDP); correcting the CDP D  for altitude, (CDP DCOR ); estimating a short-term average of CDP DCOR   2 ; estimating a short-term average of CDP DCOR ; determining a short-term variance of corrected CDP rate of change (CDP D )based upon the short-term average of CDP DCOR  and the short-term average of CDP DCOR   2 ; comparing the short-term variance of corrected CDP rate of change with a pre-determined threshold (CDP proc ); signaling an output when CDP roc &gt;CDP proc ; and signaling an occurrence of a surge within the turbomachinery compressor when CDP roc  remains&gt;CDP proc  for pre-determined period of time. 
     In another aspect of the present invention, a method of surge detection within a turbomachine compressor comprises: digitally sampling the compressor discharge pressure (CDP) of the compressor over a period of time (T sample ) by using a compressor discharge pressure probe; determining a time derivative (CDP D ) of the measured (CDP), where CDP D  (n)=(CDP(n)−CDP(n−1))/T sample , CDP(n) and CDP(n−1) are the nth and (n−1)th sample of CDP respectively and CDP D (n) is the nth sample of CDP D ; correcting the CDP D  for altitude, (CDP DCOR ); inputting CDP DCOR   2  into a first filter algorithm (FFA); inputting CDP DCOR  into a second filter algorithm (SFA); calculating or estimating a short-term average of CDP DCOR   2  (E[CDP DCOR   2 ](n)) by using the FFA which uses a rolling average of the z most recent CDP DCOR   2 , E[CDP DCOR   2 ](n)=[CDP DCOR   2 (n)+CDP DCOR   2 (n−1)+CDP DCOR   2  (n−2) . . . +CDP DCOR   2  (n−(z−1))]/z or a bilinear transform implementation of a first order lag E[CDP DCOR   2 ](n)=c1*E[CDP DCOR   2 ](n−1)+((1−c) 1 /2)*CDP DCOR   2 (n)+((1−c 1 )/2)*CDP DCOR   2 (n−1); calculating or estimating a short-term average of CDP DCOR  (E[CDP DCOR ](n)) by using the SFA which uses a rolling average of the z most recent CDP DCOR , E[CDP DCOR ](n)=[CDP DCOR  (n)+CDP DCOR  (n−1)+CDP DCOR  (n−2) . . . +CDP DCOR  (n−(z−1))]/z or a bilinear transform implementation of a first order lag E[CDP DCOR ](n)=c1*E[CDP DCOR ](n−1)+((1−c 1 )/2)*CDP DCOR (n)+((1−c 1 )/2)*CDP DCOR (n−1); determining a short-term variance of corrected CDP rate of change (Var[CDP DCOR ]) based upon E 2 [CDP DCOR ] and E[CDP DCOR   2 ], Var[CDP DCOR ]=E[CDP DCOR   2 ]−E 2 [CDP DCOR ]; comparing the short-term variance of corrected CDP rate of change with a pre-determined threshold (CDP proc ); signaling an output when Var[CDP DCOR ]&gt;CDP proc ; and signaling an occurrence of a surge within the turbomachine compressor when Var[CDP DCOR ] remains&gt;CDP proc  for pre-determined period of time. 
     In another aspect of the present invention, a system for surge detection within a turbomachine compressor comprises: a compressor discharge probe that measures the compressor discharge pressure (CDP) of the turbomachine compressor over a period of time; a signal processor that receives the CDP measurements from the compressor discharge probe, determines a time derivative (CDP D ) of the measured CDP and corrects the CDP D  for altitude, (CDP DCOR ); a first filter which receives CDP DCOR   2  and performs a first filter algorithm (FFA) that estimates a short-term average of CDP DCOR   2 ; and a second filter which receives CDP DCOR  and performs a second filter algorithm (SFA) that estimates a short-term average of CDP DCOR , wherein the signal processor determines a short-term variance of CDP DCOR  (CDP roc ) based upon the short-term average of CDP DCOR  and the short-term average of CDP DCOR   2 ; compares the short-term variance of corrected CDP rate of change (CDP roc )with a pre-determined threshold (CDP proc ); signals an output when CDP roc &gt;CDP proc ; and signals an occurrence of a surge within the turbomachine compressor when CDP roc  remains&gt;CDP proc  for pre-determined period of time. 
     These and other features, aspects and advantages of the present invention will become better understood with reference to the following drawings, description and claims. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS 
     FIG. 1 shows an exemplary cross sectional view of a gas turbine engine; 
     FIG. 2 a  shows a block diagram of an exemplary variance detector according to the present invention; 
     FIG. 2 b  shows a block diagram of an exemplary variance detector as applied to compressor discharge pressure according to the present invention; 
     FIG. 3 a  shows a graph of the variance of compressor discharge pressure during a severe surge on a hard acceleration; and 
     FIG. 3 b  shows a graph of the variance of compressor discharge pressure during a surge-free hard acceleration. 
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     The following detailed description is of the best currently contemplated modes of carrying out the invention. The description is not to be taken in a limiting sense, but is made merely for the purpose of illustrating the general principles of the invention, since the scope of the invention is best defined by the appended claims. 
     The present invention generally provides a new, robust method for surge detection based on a short-term estimate of the variance of the altitude-corrected rate of change of CDP. During normal operation, CDP changes slowly and smoothly relative to the bandwidth or sampling rate of turbomachinery control systems. The resulting autocorrelation of CDP and CDP rate of change is relatively high over the short term (Autocorrelation is a statistical measure of the relatedness of samples of a signal at different points in time). This autocorrelation drops dramatically during a surge, providing an excellent means of detecting surge. Autocorrelation is difficult to calculate in a real time environment. However, short-term signal variance is inversely proportional to short-term autocorrelation, and is easily calculated, thus providing an outstanding surge detection mechanism. 
     The improved method and system of the present invention provides surge detection where fewer false alarms occur and a single parameter and sensor are used for detection. The present invention provides an effective method and system which detect undesirable surges that may occur during the operation of turbomachinery. By using the present invention for surge detection, control systems within the turbomachinery may take appropriate corrective action to eliminate the surge and return the turbomachinery back to an acceptable operating condition. The present invention provides the control system of the turbomachinery with quick and accurate detection of surge conditions, thereby preventing or minimizing any sustained power losses or mechanical damage to the turbomachinery. 
     Referring to FIG. 1, an exemplary cross sectional view of a gas turbine engine is shown. The gas turbine engine  10  may include various components for control purposes. Electronic control unit (ECU)  11  can transmit control signals to the engine in order to control the various components and systems for the gas turbine engine  10  during operation. The ECU  11  can also receive signals from various sensors positioned within the gas turbine engine  10  in order to activate corrective measures and signal operating conditions. Surge bleed valves  13  are used during normal operation and may also be activated during surge periods in order to counter surge conditions that may occur during operation. The activation of the surge bleed valves  13  helps to stabilize compression stage airflow and pressure and limits the period of the surge condition by balancing the airflow and pressure ratio of the gas turbine engine  10 . Compressor discharge pressure (CDP) may be monitored by a CDP probe  18 . This probe may be mounted at the compressor or located within the ECU, connected to the compressor with a pneumatic line. The CDP probe  18  may transmit signals to a signal processor  22  found in the ECU  11 . Signal processor  22  can perform the variance detection functions as described below. 
     Referring to FIG. 2 a , a block diagram of an exemplary variance detector of the present invention is shown. The variance detector of FIG. 2 a may be based upon the standard statistical calculation of variance: 
     
       
         Variance[ x]=E[x   2   ]−E   2   [x]   
       
     
     where E is the statistical expectation operator and x is an input signal. The present invention may seek to calculate “short term variance” which is defined as the variance of a time-varying sequence or signal over a short interval. The set of numbers x (x 1 , x 2 , x 3 , x 4  . . . x n ) used in the calculation of the short-term variance is not a static set of numbers, but a set of the “most recent” x&#39;s. The expectation operators may be implemented as rolling averages of x and x 2 , where the rolling averages may be easily implemented in digital systems by using filters such as a finite impulse response filter or a rolling average filter. Other alternative filters may include a first order lag in digital systems or a simple first order filter in analog systems. 
     Signal x, block  30 , may be input into time derivative block  31 . The time derivative block  31  may take the time derivative x 1  (dx/dt) of the input signal x, where the time derivative may be calculated by using either of the following equations: 
     
       
           x   1 ( n )=( x ( n )− x ( n −−1))/T sample , digital system where x(n) is the nth sample of x, x(n−1) is the n−1 th sample of x; or 
       
     
     X 1 (s)=s X(s), analog system, where s indicates the time differentiation operation in the frequency domain (via standard LaPlace transformation methods), X(s) is the frequency-domain representation of the input data stream, and X 1 (s) is the frequency-domain representation of the derivative of the input data stream 
     The resultant time derivative x 1  may be sent through a second filter algorithm (SFA)  34  and a multiplier  32  which may square x 1  and which may be sent through a first filter algorithm (FFA)  33 . 
     The FFA  33  may estimate the short-term average of x 1   2 . The short-term average of z readings may be found by using a rolling average: 
     
       
           E[x   1   2 ]( n )=[ x   1   2 ( n )+ x   1   2 ( n −1)+ x   1   2  ( n −2) . . . + X   1   2  ( n −( z −1))]/ z . 
       
     
     The short-term average of x 1   2  may also be estimated by using a standard filter such as a first order lag: 
     
       
           E[x   1   2 ]( n )− c   1   *E[x   1   2 ]( n −1)+((1 −c   1 )/2)* x   1   2 ( n )+((1 −c   1 )/2 *x   1   2  ( n −1) 
       
     
     which is a bi-linear realization of a first-order lag and c 1  is the filter coefficient. The FFA  33  may also be implemented through an analog system where the short term average of x 1   2  may be estimated by: 
     
       
           E[X   1   2 ]( s )− X   1   2 ( s )/( Ts +1) 
       
     
     where T is the time constant of the filter. 
     The SFA  34  may estimate the short-term average of x 1 . The short-term average of z readings may be found by using a rolling average: 
       E[x   1 ]( n )=[ x   1 ( n )+ x   1 ( n −1)+ x   1 ( n −2) . . . + x   1 ( n −( z −1))]/ z . 
     The short-term average of xi may also be estimated by using a standard filter such as a first order lag: 
     
       
           E[x   1 ]( n )˜ c   1   *E[x   1 ]( n −1)+((1 −c   1 )/2)* x   1 ( n )+((1 −c   1 )/2)* x   1 ( n −1) 
       
     
     which may be a bi-linear realization of a first-order lag. The SFA  34  may also be implemented through an analog system where the short-term average of x 1  may be estimated by: 
     
       
           E[X   1 ]( s )˜ X   1 ( s )/( Ts +1) 
       
     
     In order to obtain the short-term variance, the resultant of the SFA  34  may be squared through multiplier  35 , E 2 [x 1 ] and subtracted from E[x 1   2 ] where Var[x 1 ]=E[x 1   2 ]−E 2 [x 1 ]. A threshold detector  37   b  may then receive the values for Var[xi] and a pre-determined threshold value of variance V L    37   a . The Var[x 1 ] may be then compared to V L , and the threshold detector  37   b  may output a signal (output c =1) to an output timer  38  when Var[x 1 ]&gt;V L . The output timer  38  may signal an output (output T =1) indicating an excessive variance  39  after output timer  38  has received an input of output c =1 for a pre-determined amount of time or percentage of time over a given time interval. By utilizing the above method one may avoid false alarms and reliable signals of variance detection may therefore be produced. 
     Referring to FIG. 2 b , a block diagram of an exemplary variance detector as applied to compressor discharge pressure according to the present invention is shown. Similar to FIG. 2 a , the CDP  40  may be input to CDP time derivative  41  which represents signal processor  22  of FIG.  1  and CDP  40  may be the result of signal readings received by the CDP sensor  18 . The CDP sensor  18 , in one exemplary application, may be sampled every 20-30 ms . Accordingly, the CDP time derivative function  41   a  may take the time derivative of the input signal CDP, where the CDP time derivative (CDP D ) may be calculated by using either of the following equations: 
     
       
           CDP   D ( n )=( CDP ( n )− CDP ( n −1))/ T   sample , digital system; or 
       
     
     
       
           CDP   D ( s )= s CDP ( s ), analog system 
       
     
     The resultant time derivative CDP D  may be corrected for altitude to improve altitude surge detection via; an altitude correction  41   b , where the altitude corrected CDP D  (CDP DCOR ) may be calculated by using the following equation: 
     CDP DCOR =CDP D /PT 2 , where PT 2  is the engine inlet pressure The resultant altitude-corrected time derivative CDP DCOR  may be sent through a CDP second filter algorithm (SFA)  44  and a multiplier  42  which squares CDP DCOR  and which may be sent through a CDP first filter algorithm (FFA)  43 . 
     The CDP FFA  43  may estimate the short-term average of CDP DCOR   2 . The short-term average of z readings may be found by using a rolling average: 
     
       
           E[CDP   DCOR   2 ]( n )=[ CDP   DCOR   2 ( n )+ CDP   DCOR   2 ( n −1)+ CDP   DCOR   2 ( n −2) . . . + CDP   DCOR   2 ( n ( z −1))]/ z   
       
     
     where CDP DCOR   2 (n) is the n th  sample of CDP DCOR   2 . The short-term average of CDP DCOR   2  may also be estimated by using a standard filter such as a first order lag: 
     
       
           E[CDP   DCOR   2 ]( n )˜ c   1   *E[CDP   DCOR   2 ]( n −1)+((1 −c   1 )/2)* CDP   DCOR   2 ( n )+((1 −c   1 )/2)* CDP   DCOR   2  ( n −1) 
       
     
     which is a bi-linear realization of a first-order lag. The CDP FFA  43  may also be implemented through an analog system where the short term average of CDP DCOR   2  may be estimated by: 
     
       
           E[CDP   DCOR   2 ]( s )˜ CDP   DCOR   2 ( s )/( Ts +1). 
       
     
     The CDP SFA  44  may estimate the short term average of CDP DCOR . The short-term average of z readings may be found by using a rolling average: 
     
       
           E[CDP   DCOR ]( n )=[ CDP   DCOR ( n )+ CDP   DCOR ( n −1)+ CDP   DCOR ( n −2) . . . + CDP   DCOR ( n −( z −1))]/ z   
       
     
     where CDP DCOR (n) is the n th  sample of CDP DCOR . The short-term average of CDP DCOR  may also be calculated by using a standard filter such as a first order lag: 
     
       
           E[CDP   DCOR ]( n )˜ c   1   *E[CDP   DCOR ]( n −1)+((1 −c   1 )/2)* CDP   DCOR ( n )+((1 −c   1 )/2)* CDP   DCOR ( n −1) 
       
     
     which may be a bi-linear realization of a first-order lag. The CDP SFA  44  may also be implemented through an analog system where the short term average of CDP DCOR  may be calculated by: 
     
       
           E[CDP   DCOR ]( s )˜ CDP   DCOR ( s )/( Ts +1). 
       
     
     In order to obtain the short term variance of the corrected CDP rate of change, the resultant of the CDP SFA  44  may be squared through second multiplier  45 , E 2 [CDP DCOR ] and subtracted from E[CDP DCOR   2 ] where Var[CDP DCOR ]=E[CDP DCOR   2 ]−E 2 [CDP DCOR ]. A CDP threshold detector  47   b may then receive the values for Var[CDP DCOR ] and a pre-determined value of variance V L    47   a . The Var[CDP D ] may then be compared to V L , and the CDP threshold detector  47   b  may output a signal (output c =1) to a CDP output timer  38  when Var[CDP D ]&gt;V L . The CDP output timer  48  may signal an output (output T =1) indicating an excessive CDP variance  49  after CDP output timer  48  has received an input of output c =1 for a pre-determined amount of time or percentage of time over a given time interval. 
     The implementation of this variance detection may assist in accurately determining the occurrence of surge within the gas turbine engine  10 . The measurement of short-term variance of corrected CDP or corrected CDP rate of change may easily distinguish surge occurrences from normal operation of the gas turbine engine  10 . Measurement of short-term variance of the corrected CDP rate of change may help to eliminate false alarms and may provide reliable signals of surges that occur during operation of gas turbine engine  10 . 
     EXAMPLES 
     Referring now to FIG. 3 a , a graph of the variance of compressor discharge pressure altitude-corrected rate of change during a severe surge on a hard acceleration is shown. Referring to FIG. 3 b , a graph of the variance of compressor discharge pressure altitude-corrected rate of change during a surge-free hard acceleration is shown. FIGS. 3 a  and  3   b  show typical variance of the corrected compressor discharge pressure rate of change during a severe surge event and normal operation of an exemplary gas turbine engine  10 , where P3DOT/Pamb/14.696 psia) is the corrected compressor discharge pressure rate of change, 96 ms is the data sample rate, and bi-linear implementation of first order lag (Tau of 0.125 sec) is the method of averaging E[x] and E[x 2 ]. The high signal noise ratio of the variance detector of the present invention makes it ideal for detecting engine surge. 
     It should be understood, of course, that the foregoing relates to preferred embodiments of the invention and that modifications may be made without departing from the spirit and scope of the invention as set forth in the following claims.