Abstract:
A method for monitoring the health of a turbine is provided. The method comprises monitoring a turbine engine having a plurality of engine modules and determining one or more health estimates, which may included trended data, for one or more of the engine modules, based on a plurality of engine parameters. The method further determining and transmitting appropriate notifications that indicate repairs to be made to the turbine engine.

Description:
BACKGROUND 
       [0001]    The invention relates generally to gas turbine engines, and more particularly to a system and method for monitoring the health of a turbine engine. 
         [0002]    As gas turbine engines operate, engine efficiency and performance may deteriorate over time. This degradation of performance may be due to various factors such as engine wear or engine component damage. Measurement of this degradation of performance may be useful in determining what type of maintenance should be performed on the turbine engine to restore the engine to its original operating efficiency. However, false turbine performance readings may result from the failure of turbine performance measuring devices. The failure of these turbine performance measuring devices may lead to erroneous turbine performance data being generated, which may lead to unnecessary maintenance on the turbine. Moreover, existing techniques for measuring engine performance can be tedious to setup and perform, and only provide limited data. Accordingly, there is a need for improved diagnostic systems and methods that reduce false efficiency readings, as well as generate more reliable efficiency readings. 
       BRIEF DESCRIPTION 
       [0003]    In one embodiment, a method for planning repair of an engine is provided. The method comprises monitoring a turbine engine having a plurality of engine modules and determining one or more engine module health estimates for one or more of the engine modules based on a plurality of engine parameters, wherein the one or more health estimates comprise trended data. The method further comprises determining failure types for the engine modules based on the health estimates and correcting specific failure types. 
         [0004]    In another embodiment, a system for monitoring an engine is provided. The system comprises an engine health estimator configured to determine one or more health estimates for one or more modules of the engine based on a plurality of engine parameters, wherein the one or more health estimates comprise trended data. The system further comprises a turbine analyzer configured to analyze the one or more health estimates to determine failure types for the engine modules. 
         [0005]    Additionally, a turbine system is provided. The turbine system comprises one or more engine modules adapted to generate rotational motion. The turbine system further comprises one or more sensors adapted to measure engine parameters for the one or more engine modules. Furthermore, the turbine system includes an engine health estimator configured to determine one or more health estimates for the one or more engine modules based the measured engine parameters, wherein the one or more health estimates comprise trended data. Finally, the turbine system includes a turbine analyzer configured to analyze the one or more health estimates to determine failure types for the engine modules. 
     
    
     
       DRAWINGS 
         [0006]    These and other features, aspects, and advantages of the present invention will become better understood when the following detailed description is read with reference to the accompanying drawings in which like characters represent like parts throughout the drawings, wherein: 
           [0007]      FIG. 1  is a block diagram of a turbine system in accordance with an embodiment of the present technique; 
           [0008]      FIG. 2  is a block diagram of health analysis components for use in monitoring the health of the turbine system of  FIG. 1 ; and 
           [0009]      FIG. 3  is a flow chart of illustrating health monitoring of the turbine system of  FIG. 1 . 
       
    
    
     DETAILED DESCRIPTION 
       [0010]    Health monitoring of a turbine engine is discussed below. Engine parameters corresponding to modules of the turbine engine may be monitored and measured. These measurements may then be combined into a trend for each of the modules of the engine. The trends may be compared to an engine model that may include model values representing the proper operating levels for each of the modules. Based on the measured values deviation from the model values, an expert tool may predict the type of problem that may be causing the deviation. The expert tool may also generate a recommendation that may be transmitted to a workstation that may permit for efficient rectification of a problem causing the deviation via specific repairs. In this manner, turbine engine that operates at less than an acceptable level of performance may be repaired in a manner that corrects a source problem. 
         [0011]    Turning now to the drawings and referring first to  FIG. 1 , a block diagram of an embodiment of turbine system  10  is illustrated. The turbine system  10  may, for example, be manufactured by General Electric Company of Evendale, Ohio under the designation LM6000. As depicted, the turbine system  10  may include a combustor  12 . The combustor  12  may receive fuel that has been mixed with air, for combustion in a chamber within combustor  12 . This combustion creates hot pressurized exhaust gases. The combustor  12  directs the exhaust gases through a high pressure (HP) turbine  14  and a low pressure (LP) turbine  16  toward an exhaust outlet  18 . The HP turbine  14  may be part of a HP rotor. Similarly, the LP turbine  16  may be part of a LP rotor. As the exhaust gases pass through the HP turbine  14  and the LP turbine  16 , the gases force turbine blades to rotate a drive shaft  20  along an axis of the turbine system  10 . As illustrated, drive shaft  20  is connected to various components of the turbine system  10 , including a HP compressor  22  and a LP compressor  24 . 
         [0012]    The drive shaft  20  may include one or more shafts that may be, for example, concentrically aligned. The drive shaft  20  may include a shaft connecting the HP turbine  14  to the HP compressor  22  to form a HP rotor. The HP compressor  22  may include blades coupled to the drive shaft  20 . Thus, rotation of turbine blades in the HP turbine  14  causes the shaft connecting the HP turbine  14  to the HP compressor  22  to rotate blades within the HP compressor  22 . This compresses air in the HP compressor  22 . Similarly, the drive shaft  20  includes a shaft connecting the LP turbine  16  to the LP compressor  24  to form a LP rotor. The LP compressor  24  includes blades coupled to the drive shaft  20 . Thus, rotation of turbine blades in the LP turbine  16  causes the shaft connecting the LP turbine  16  to the LP compressor  24  to rotate blades within the LP compressor  24 . The rotation of blades in the HP compressor  22  and the LP compressor  24  compresses air that is received via the air intake  26 . The compressed air is fed to the combustor  12  and mixed with fuel to allow for higher efficiency combustion. Thus, the turbine system  10  may include a dual concentric shafting arrangement, wherein LP turbine  16  is drivingly connected to LP compressor  24  by a first shaft in the drive shaft  20 , while the HP turbine  14  is similarly drivingly connected to the HP compressor  22  by a second shaft in the drive shaft  20  internal and concentric to the first shaft. Shaft  20  may also be connected to load  28 , which may be a vehicle or a stationary load, such as an electrical generator in a power plant or a propeller on an aircraft. Load  28  may be any suitable device that is powered by the rotational output of turbine system  10 . 
         [0013]    The engine turbine system  10  may also include a plurality of sensors, configured to monitor a plurality of engine parameters related to the operation and performance of the turbine system  10 . The sensors may include, for example, inlet sensors  30  and outlet sensors  32  positioned adjacent to, for example, the inlet and outlet portions of the HP turbine  14 , the LP turbine  16 , the HP compressor  22 , and/or the LP compressor  24 , respectively. The inlet sensors  30  and outlet sensors  32  may measure, for example, environmental conditions, such as ambient temperature and ambient pressure, as well as a plurality of engine parameters related to the operation and performance of the turbine system  10 , such as, exhaust gas temperature, rotor speeds, engine temperature, engine pressure, gas temperature, engine fuel flow, core speed, compressor discharge pressure, and turbine exhaust pressure. The plurality of sensors  30  and  32  may also be configured to monitor engine parameters related to various operational phases of the turbine system  10 . Measurements taken by the plurality of sensors  30  and  32  may be transmitted via module lines  34 - 40 . For example, module line  34  may be utilized to transmit measurements from the LP compressor  24 , while module line  36  may be utilized to transmit measurements from the HP compressor  22 . In a similar manner, module line  38  may be utilized to transmit measurements from the HP turbine  14 , while module line  40  may be utilized to transmit measurements from the LP turbine  16 . Thus, module lines  34 - 40  may transmit measurements from separate modules of the turbine system  10 . 
         [0014]      FIG. 2  illustrates health analysis components  42  that may be utilized in conjunction with the turbine system  10 . The health analysis components  42  may include a health estimator  44  of a turbine analyzer  46 , an engine model  48  of the turbine analyzer  46 , an expert analysis tool  50 , and a workstation  52 . The health estimator  44  receives measurements from the modules of the turbine system  10  via module lines  34 - 40 . These measurements may be recorded and/or processed by the health estimator  44 , which may be external to the turbine system  10 . In this manner, the health estimator  44  determines one or more module-specific health estimates for one or more of the modules of the turbine system  10  based on the measurements transmitted via module lines  34 - 40 . The measurements may include data representative of, for example, combustor flow, combustor efficiency, HP compressor flow, HP compressor efficiency, LP compressor flow, LP compressor efficiency, HP turbine flow, HP turbine efficiency, LP turbine flow, and LP turbine efficiency for the turbine system  10 . 
         [0015]    In one embodiment, the health estimator  44  may further utilize parameter identification techniques such as Kalman filtering, tracking filtering, regression mapping, neutral mapping, inverse modeling techniques, or a combination thereof. The filtering may be performed by a modified Kalman filter, an extended Kalman filter, or other filtering algorithm, or alternatively, the filtering may be performed by proportional and integral regulators or other forms of square (n-inputs, n-outputs) or non-square (n-input, m-outputs) regulators. The parameter identification techniques may further include generation of an instant model of the turbine system  10  based on the measurements received from the modules of the turbine system  10 . Thus, the health estimator  44  may solve for instantaneous conditions of the turbine system  10  to generate an initial model of the turbine system  10 . 
         [0016]    Additionally, the health estimator  44  may, for example, receive data corresponding to module measurements either continuously, or at a given sample rate. This sample rate may be, for example, one sample per minute. Regardless of whether the data is received continuously or at a given sample rate, the received data may be used for analysis of the health of the turbine system  10 . For example, an automated notice and/or an alarm may be issued based on unexpected received data values corresponding to failure or degradation of modules in the turbine system  10 . Additionally, this received data may be used to calculate operating trends of the modules. For example, the received data may be integrated analyzed with previously received data to update a generated model of the turbine system  10 . In this manner, trending, or changes over time, of the modules of the turbine system  10  may be recorded for analysis. 
         [0017]    For example, the health estimator  44  may represent the health of the HP turbine as a function of the HP turbine blade health, the HP turbine rotor health, and the HP turbine nozzle health. In another example, the health of the HP turbine blade may be represented by the health estimator  44  as a function of the blade tip rub and the blade creep. As stated above, measurements over time may be combined into trends for the HP turbine components. The health estimator  44  may monitor the health status of the modules of the turbine system  10  in this manner. 
         [0018]    The health status of the modules of the turbine system  10  may be transmitted to the turbine analyzer  46 . The turbine analyzer  46  may evaluate the health status of one or more of the modules of the turbine system  10 . In one embodiment, the turbine analyzer  46  may utilize, for example, a physics-based model, a data fitting model (such as a regression model or a neural network model), a rule-based model, and/or an empirical model to evaluate the health status of the one or more modules received from the health estimator  44 . A physics-based model, whereby each module of the turbine system  10  is individually modeled, may be used to relate turbine performance degradation parameters to physical wear or usage. Thus, changes in the performance of the specific modules of the turbine system  10  over time, i.e. the module trends, may be compared to an engine model  48  of the turbine analyzer  46 , such that the engine model  48  may incorporate an empirical model of the turbine system  10  functioning as intended. Thus, the engine model  48  may provide a baseline from which the health status of the modules of the turbine system  10  may be measured. Thus, in one embodiment, determining a desired level of repair comprises determining the extent of repair needed to achieve a desired level of engine performance associated with the engine model  48 . The engine model  48  may further be configured to include optimal values for the levels of repair needed for the engine modules, based on a plurality of optimization criteria. The optimization criteria may include, for example, the overall amount of life-cycle cost associated with the engine repair/overhaul and/or the cost of performing the repair. 
         [0019]    The turbine analyzer  46  may transmit any generated results to an analysis tool  50 . The analysis tool  50  may be an expert analysis tool that may analyze the results of the module trends. These trends and/or combinations of trends may be utilized by the analysis tool  50  to determine the health of the modules of the turbine system  10 , as well as the type of failures occurring in the turbine system  10 . For example, a HP compressor module may lose efficiency over time. Based on a comparison of the trends of the HP compressor module with, for example, the efficiency for a HP compressor module from the engine model  48 , the analysis tool  50  may determine that the efficiency of the HP compressor  22  is being impacted by dirty blades. Accordingly, a message may be transmitted to the workstation  52  indicating that the HP compressor  22  should be cleaned. In one embodiment, the analysis tool  50  may be one or more look-up charts that may be part of a computer program stored on a machine readable medium, such as a disk drive or memory. Alternatively, the analysis tool  50  may be part of an integrated circuit. 
         [0020]    The analysis tool  50  may be programmed to include alarms, repair notices, and/or notices for sensor or module failure. These different results programmed into the analysis tool  50  may represent programmed responses for predicted failure types of the turbine system  10 , based on differences between the results transmitted from the health estimator  44  and the engine model  48 . The analysis tool  50  may also be updated during the life of the turbine system  10  to adjust the analysis tool  50  prediction algorithm according to the tendencies of the turbine system  10 . 
         [0021]    As described above, when the analysis tool  50  applies a prediction algorithm to received data from the health estimator  44 , a result, such as, a fail notice, an alarm, and/or a repair notice may be issued and transmitted to the workstation  52 . The workstation  52  may be physically coupled to the turbine analyzer  46 . Alternatively, the workstation  52  may be wirelessly connected to the turbine analyzer. In another embodiment, the workstation  52  may remotely access the turbine analyzer, for example, online via an intranet or an internet connection. The workstation  52  may receive repair notices, alarms, and/or fail notices from the turbine analyzer  46 . Based on these received values, a desired level of repair for one or more of the modules of the turbine system  10  may be undertaken. For example, optimal values for the levels of repair needed for the modules, based on a plurality of optimization criteria, may be programmed into the analysis tool  50 , such that as overall turbine system  10  efficiency and performance may be improved. For example, if the LP compressor  24  efficiency degradation trend is estimated to be 5% after 5000 hours of use, then the workstation  52  may receive a repair notice outlining the predicted repair necessary to restore the LP compressor  24  efficiency by about 5%. This allows repairs of the turbine system  10  to be performed efficiently. For example, if the health estimate determined for the HP turbine  14  module is found to be normal by the analysis tool  50 , then repair to the HP turbine  14  may not be performed, even if other modules of the turbine system  10  require repair. In other words, the workstation  52  may receive information relating to portions of the turbine module  10  that require attention, therefore reducing unnecessary repairs. 
         [0022]      FIG. 3  illustrates process steps that may be used for determining if any repairs are necessary to make to the turbine system  10 . In step  54 , measurements are taken by sensors  30  and  32  regarding operating parameters of modules of the turbine system  10 . These measurements are transmitted to the health estimator  44  in step  56 . Based on the received measurements, estimates of the operation of the modules of the turbine system  10  are generated in step  58 . These estimates are then transmitted to the turbine analyzer  46  for analysis in step  60 . This analysis may include utilizing an analysis tool  50 , such as an expert tool, to compare the estimates with an engine module  48 . Based on the comparison, a prediction may be made as to any repairs or notices that may be sent to the workstation  52  in step  62  or to, for example, controllers of the turbine system  10 . Based on the received notice from the turbine analyzer  46 , designated repairs on the turbine system  10  may be accomplished. These designated repairs, or corrections, may include repair of the sensors  30  and/or  32 , or one or more of the modules of the turbine system  10 . These corrections may be made automatically in response to the received notice, for example, controllers coupled to the turbine system  10  may receive the notices and may perform corrective steps, such as reducing the fuel flowing into the combustor  12  or opening a recycle valve in either or both of the compressors  22  and  24  to release excess pressure. The corrections may also be analyzed for later implementation, such as indication of a misplaced sensor to be adjusted, for example, by a user. 
         [0023]    While only certain features of the invention have been illustrated and described herein, many modifications and changes will occur to those skilled in the art. It is, therefore, to be understood that the appended claims are intended to cover all such modifications and changes as fall within the true spirit of the invention.