Abstract:
A method of fusing information within a turbomachine health management system according to an exemplary aspect of the present disclosure includes, among other things, sending information collected within a first subsystem from the first subsystem to a system level reasoner, and adjusting a different, second subsystem based on the information from the first subsystem.

Description:
BACKGROUND 
       [0001]    This disclosure relative generally to turbomachine health and, more particularly, to a health management system that uses system-level diagnostic feedback to improve the performance of subsystem diagnosis and downstream Prognostics and Health Management systems consuming the improved diagnostic information, which produces improved overall engine system health assessment. 
         [0002]    Turbomachines, such as gas turbine engines, typically include a fan section, a compression section, a combustion section, and a turbine section. Turbomachines may employ a geared architecture connecting portions of the compression section to the fan section. 
         [0003]    A turbomachine may have an associated health management system. Information gathered by the health management systems may be used as diagnostic and prognostic information. Current health management systems have a hierarchical structure. These health management systems include several subsystems that may utilize sensors, for example, to collect information directly from the turbomachine. Information from the subsystems is sent upwards in the hierarchy and aggregated at system level. Diagnostic information exchange among subsystems can be utilized but is often error-prone due to lack of confidence and accuracy in individual subsystem diagnosis using local, incomplete information, as well as improper assumptions on extraneous variables when a fault occurs. 
       SUMMARY 
       [0004]    A method of fusing information within a turbomachine health management system according to an exemplary aspect of the present disclosure includes, among other things, sending information collected within a first subsystem from the first subsystem to a system level reasoner, and adjusting a different, second subsystem based on the information from the first subsystem. 
         [0005]    In a further non-limiting embodiment of either of the foregoing methods of communicating information within a turbomachine health management system, the adjusting comprises changing how the second subsystem collects information. 
         [0006]    In a further non-limiting embodiment of any of the foregoing methods of communicating information within a turbomachine health management system, the method includes substituting information sent from the second subsystem to the system level reasoner with information from the first subsystem. 
         [0007]    In a further non-limiting embodiment of any of the foregoing methods of communicating information within a turbomachine health management system, the method recognizes a sensor failure within the second subsystem utilizing information from the first subsystem. 
         [0008]    In a further non-limiting embodiment of any of the foregoing methods of communicating information within a turbomachine health management system, the adjusting is based further on information sent from the second subsystem to the system level reasoner. 
         [0009]    Another method of communicating information within a turbomachine health management system according to an exemplary aspect of the present disclosure includes, among other things, collecting information from at least one first subsystem at a system level, and providing diagnostic feedback to at least one second subsystem, the diagnostic feedback adjusted in response to information from at least one subsystem, the at least one first subsystem different than the at least one second subsystem. 
         [0010]    In a further non-limiting embodiment of the foregoing method of communicating information within a turbomachine health management system, the first subsystem and the second subsystem collect information from different groups of components. 
         [0011]    In a further non-limiting embodiment of the foregoing method of communicating information within a turbomachine health management system, the method includes collecting information at the system level using a system-level reasoner. 
         [0012]    In a further non-limiting embodiment of either of the foregoing methods of communicating information within a turbomachine health management system, the method includes collects information from the at least one second subsystem at the system level. 
         [0013]    In a further non-limiting embodiment of any of the foregoing methods of communicating information within a turbomachine health management system, the method uses the diagnostic feedback to improve the diagnostic accuracy of the at least one second subsystem. 
         [0014]    In a further non-limiting embodiment of any of the foregoing methods of communicating information within a turbomachine health management system, the method adjusts how the at least second subsystem collects information based on the diagnostic feedback. 
         [0015]    In a further non-limiting embodiment of any of the foregoing methods of communicating information within a turbomachine health management system, the method replaces information from the at least one second subsystem with information from the at least one first subsystem based on the diagnostic feedback. 
         [0016]    In a further non-limiting embodiment of any of the foregoing methods of communicating information within a turbomachine health management system, the method recognizes a sensor failure within the at least one second subsystem using the information from the at least one first subsystem. 
         [0017]    In a further non-limiting embodiment of any of the foregoing methods of communicating information within a turbomachine health management system, the at least one first subsystem and the at least one second subsystem collect at least some information from a turbomachine using a common sensor. 
         [0018]    A turbomachine health management system according to an exemplary aspect of the present disclosure includes, among other things, a first subsystem module configured to collect information from a first group of sensors within a turbomachine, a second subsystem module configured to collect information from a second group of sensors within the turbomachine, and a system module configured to adjust the first subsystem module based at least in part on information from the second subsystem module. 
         [0019]    In a further non-limiting embodiment of the foregoing turbomachine health management system, the first subsystem module may be a blade or vane health module. 
         [0020]    In a further non-limiting embodiment of either of the foregoing turbomachine health management system, the system module may be configured to adjust information received from the first subsystem based on information from the second subsystem. 
         [0021]    In a further non-limiting embodiment of any of the foregoing turbomachine health management systems, the system may include at least one sensor that communicates information to the first subsystem module. 
         [0022]    In a further non-limiting embodiment of any of the foregoing turbomachine health management systems, the system may include at least one sensor that communicates information to the first and the second subsystem modules. 
     
    
     
       DESCRIPTION OF THE FIGURES 
         [0023]    The various features and advantages of the disclosed examples will become apparent to those skilled in the art from the detailed description. The figures that accompany the detailed description can be briefly described as follows: 
           [0024]      FIG. 1  shows an example turbomachine. 
           [0025]      FIG. 2  shows a highly schematic view of an example health management system for use with the turbomachine of  FIG. 1 . 
           [0026]      FIG. 3  shows a detailed schematic view of an example of the health management system of  FIG. 2 . 
           [0027]      FIG. 4  shows a detailed schematic view of an example of the fusion of gas path performance monitoring, blade health monitoring and vibration monitoring and diagnostic feedback from system level reasoner to each subsystems. 
       
    
    
     DETAILED DESCRIPTION 
       [0028]      FIG. 1  schematically illustrates an example turbomachine, which is a gas turbine engine  20  in this example. The gas turbine engine  20  is a two-spool turbofan gas turbine engine that generally includes a fan section  22 , a compression section  24 , a combustion section  26 , and a turbine section  28 . 
         [0029]    Although depicted as a two-spool turbofan gas turbine engine in the disclosed non-limiting embodiment, it should be understood that the concepts described herein are not limited to use with turbofans. That is, the teachings may be applied to other types of turbomachines and turbine engines including three-spool architectures. Further, the concepts described herein could be used in environments other than a turbomachine environment and in applications other than aerospace applications. 
         [0030]    In the example engine  20 , flow moves from the fan section  22  to a bypass flowpath. Flow from the bypass flowpath generates forward thrust. The compression section  24  drives air along a core flowpath. Compressed air from the compression section  24  communicates through the combustion section  26 . The products of combustion expand through the turbine section  28 . 
         [0031]    The example engine  20  generally includes a low-speed spool  30  and a high-speed spool  32  mounted for rotation about an engine central axis A. The low-speed spool  30  and the high-speed spool  32  are rotatably supported by several bearing systems  38 . It should be understood that various bearing systems  38  at various locations may alternatively, or additionally, be provided. 
         [0032]    The low-speed spool  30  generally includes a shaft  40  that interconnects a fan  42 , a low-pressure compressor  44 , and a low-pressure turbine  46 . The shaft  40  is connected to the fan  42  through a geared architecture  48  to drive the fan  42  at a lower speed than the low-speed spool  30 . 
         [0033]    The high-speed spool  32  includes a shaft  50  that interconnects a high-pressure compressor  52  and high-pressure turbine  54 . 
         [0034]    The shaft  40  and the shaft  50  are concentric and rotate via bearing systems  38  about the engine central longitudinal axis A, which is collinear with the longitudinal axes of the shaft  40  and the shaft  50 . 
         [0035]    The combustion section  26  includes a circumferentially distributed array of combustors  56  generally arranged axially between the high-pressure compressor  52  and the high-pressure turbine  54 . 
         [0036]    In some non-limiting examples, the engine  20  is a high-bypass geared aircraft engine. In a further example, the engine  20  bypass ratio is greater than about six (6 to 1). 
         [0037]    The geared architecture  48  of the example engine  20  includes an epicyclic gear train, such as a planetary gear system or other gear system. The example epicyclic gear train has a gear reduction ratio of greater than about 2.3 (2.3 to 1). 
         [0038]    The low-pressure turbine  46  pressure ratio is pressure measured prior to inlet of low-pressure turbine  46  as related to the pressure at the outlet of the low-pressure turbine  46  prior to an exhaust nozzle of the engine  20 . In one non-limiting embodiment, the bypass ratio of the engine  20  is greater than about ten (10 to 1), the fan diameter is significantly larger than that of the low pressure compressor  44 , and the low-pressure turbine  46  has a pressure ratio that is greater than about 5 (5 to 1). The geared architecture  48  of this embodiment is an epicyclic gear train with a gear reduction ratio of greater than about 2.5 (2.5 to 1). It should be understood, however, that the above parameters are only exemplary of one embodiment of a geared architecture engine and that the present disclosure is applicable to other gas turbine engines including direct drive turbofans. 
         [0039]    In this embodiment of the example engine  20 , a significant amount of thrust is provided by the bypass flow B due to the high bypass ratio. The fan section  22  of the engine  20  is designed for a particular flight condition—typically cruise at about 0.8 Mach and about 35,000 feet. This flight condition, with the engine  20  at its best fuel consumption, is also known as “Bucket Cruise” Thrust Specific Fuel Consumption (TSFC). TSFC is an industry standard parameter of fuel consumption per unit of thrust. 
         [0040]    Fan Pressure Ratio is the pressure ratio across a blade of the fan section  22  without the use of a Fan Exit Guide Vane system. The low Fan Pressure Ratio according to one non-limiting embodiment of the example engine  20  is less than 1.45 (1.45 to 1). 
         [0041]    Low Corrected Fan Tip Speed is the actual fan tip speed divided by an industry standard temperature correction of Temperature divided by 518.7 ̂ 0.5. That is, [(Tram ° R)/(518.7° R)] 0.5 . The Temperature represents the ambient temperature in degrees Rankine. The Low Corrected Fan Tip Speed according to one non-limiting embodiment of the example engine  20  is less than about 1150 fps (351 m/s). 
         [0042]    Referring to  FIG. 2  with continuing reference to  FIG. 1 , an example health management system  60  for the engine  20  includes several groups of components  64   a ,  64   b , . . .  64   n . Sensors  68   a ,  68   b , . . .  68   n  collect information from one or more of the groups of components  64   a - 64   n . Subsystem diagnostic modules  70   a - 70   n  receive the collected information. The modules  70   a - 70   n  may diagnose performance, for example, of one or more of the groups of components  64   a - 64   n  based on the information form the sensors  68   a - 68   n . For example, vibration, temperature and spool speed of the group of components  64   a  may be measured by the sensors  68   a - 68   c . The module  70   a  may be tasked with communicating an alert in response to identifying extreme vibrations. 
         [0043]    The module  70   b  may collect information from different sensors  68   d - 68   e , and apply a correction factor to the collected information, etc. A system level reasoner  72  is in two-way communication with the modules  70   a - 70   n . The qualitative reasoning performed in system level reasoner  72  fuses the diagnostic information from modules  70   a - 70   n  to produced improved engine health diagnosis with higher confidence and accuracy. The system level reasoner  72  is configured to provide feedback to each of the modules  70   a - 70   n . The feedback may be based, at least in part, on information from other modules  70   a - 70   n . Each of the modules  70   a - 70   n  thus possesses a global awareness of the overall system  60 , which contributes to improved performance of each subsystem. 
         [0044]    Referring now to  FIG. 3  with continuing reference to  FIG. 2 , the example health management system  60   a  makes use of at least two models at two different levels of abstraction. One model  78  is a qualitative, relatively high-level model of the engine system  20 . This model  78  may be considered a qualitative reasoner, system level aggregator, or system-level reasoner. Some or all of the modules  70   a - 70   n  may include quantitative models. 
         [0045]    The qualitative model  78 , in some examples, provides feedback to one or more of the lower-level diagnostic modules  70   a - 70   n . The feedback may improve the accuracy of diagnoses by the diagnostic modules  70   a - 70   n.    
         [0046]    The feedback provided to the diagnostic module  70   a - 70   n , may be based, at least in part, on information collected through sensors  68   a - 68   n  in communication with at least some of the other diagnostic modules  70   a - 70   n.    
         [0047]    The feedback may change how the diagnostic module  70   a - 70   n  treats information communicated from one of the sensors  68   a - 68   n . For example, the sensor  68   a  may be providing the diagnostic module  70   a  with inaccurate information. The diagnostic module  70   a  only recognizes that the information is inaccurate because the diagnostic module  70   a  has received feedback indicating such from the system level reasoner  72 . The diagnostic module  70   a  is then able to adjust for the inaccurate information. An example of the adjusting includes changing how the component  64   a - 64   n  collect information. The diagnostic module  70   a  may, for example, use information from a sensor  68   d - 68   n  not previously associated with the diagnostic module  70   a.    
         [0048]    The system  60   a  may provide inputs to online, real-time propulsions fault accommodation, which is represented by block  84  in  FIG. 3 . The system  60  may also provide inputs to off-board Prognostics and Health Management (PHM) system and Condition-based Maintenance (CBM) system, which is represented by block  86  in  FIG. 3 . 
         [0049]    Other examples of variables monitored by the subsystems include gas path, tip clearances, chemical emissions, oil debris, etc. 
         [0050]    Referring to  FIG. 4 , an example method  60   b  shows the flow of how the example techniques of this disclosure may be used in connection with subsystems that monitor gas path performance monitoring  70   a , blade health  70   d , and vibration  70   b . The system level reasoner  72  may utilize the fusion of information passed through these subsystems to provide diagnostic feedback to of each subsystems. 
         [0051]    The monitored components may be components  64   b , which may be fan blade components, and the sensors  68   c - 68   e  associated with monitoring the health of the blade components. One of the sensors  68   c  measures fan speed. If the diagnostic module  70   d  determines that the sensor measuring fan speed has failed, the lower-level diagnostic module  70   d  estimates the correct fan speed using blade tip timing sensors and informs the qualitative model  78  of this failure. The model  78  then fuses the diagnostic information from all subsystems  70   a - 70   n  to diagnose the fan speed sensor fault and communicates estimated fan speed to all the subsystems needing this signal. Due to redundant sensor measurements, the module  70   d  is still able to monitor blade health even though its sensor  68   c  has failed. The model  78  has thus adjusted how the module  70   d  collects information. 
         [0052]    The substitution of information takes place in subsystem module  70   a  (which may be a gas path performance monitoring module) rather than within the module  70   d . The fan speed sensor information ( 68   c ) is substituted by estimated fan speed from module  70   d . The model  78  and the diagnostic module  70   d  have thus adjusted how the module  70   a  collects information. 
         [0053]    Features of the some of the disclosed examples include a system that can adjust the configuration or parameters of subsystem diagnostic modules (which are subject to restricted local information) based on fused results from system level (with global situation awareness) to ensure effectiveness and accuracy. For example, many subsystem diagnostic modules assume sensors are healthy. When a sensor fails, the diagnostic result from this module will no longer be trustworthy. In this case, if the system level reasoner can perform sensor diagnosis based on cross validation with other features, the faulty sensor can be either isolated or replaced by a redundant source to maintain the performance of the affected subsystem diagnostic module. 
         [0054]    The preceding description is exemplary rather than limiting in nature. Variations and modifications to the disclosed examples may become apparent to those skilled in the art that do not necessarily depart from the essence of this disclosure. Thus, the scope of legal protection given to this disclosure can only be determined by studying the following claims.