Abstract:
Methods and apparatus are provided for monitoring an aircraft accessory. The apparatus comprises a processor associated with said aircraft accessory, a transducer coupled to said processor and operable to produce parametric data relating to said aircraft accessory and a memory coupled to said processor having baseline parametric data residing therein, wherein said baseline parametric data comprises the parametric data obtained during an acceptance test procedure. The method comprises installing a transducer configured to produce parametric data relating to said aircraft accessory, coupling said transducer to a processor associated with said aircraft accessory, coupling said processor to a memory associated with said aircraft accessory, recording baseline parametric data relating to said aircraft accessory in said memory during an acceptance test procedure for said aircraft accessory.

Description:
TECHNICAL FIELD  
       [0001]     The present invention generally relates to aircraft maintenance, and more particularly relates to real-time monitoring of aircraft engine accessories to predict maintenance and logistical requirements.  
       BACKGROUND  
       [0002]     Substantial costs can be incurred by aircraft owners and operators due to periods of aircraft unavailability, or down-time. Aircraft down-time is sometimes related to aircraft engine system down-time. The aircraft engine system includes the engine and engine accessories, such as a starter or a generator. To reduce the likelihood and/or frequency of costs and downtime, preventive maintenance programs have been implemented.  
         [0003]     Preventive maintenance is periodically performed on aircraft engine accessories based upon average wear rates, lubricant usage rates, and similar averages. Variable burdens on aircraft and their components due to loads, weather, and various other factors inevitably mean that some aircraft parts will wear at differential rates than others. Worn parts can lead to aircraft down-time.  
         [0004]     In addition to maintenance, logistical support for aircraft engines, such as production and distribution of spare parts and lubricants, can also impact downtime. Unavailability of spare parts and lubricants can extend down-time.  
         [0005]     Some mathematical methods for predicting maintenance and logistical requirements are known in the art. However, these methods require data regarding wear and consumption rates that may be only forensically known, either after expensive operational failures or expensive testing programs.  
         [0006]     Some methods of gathering useful data are known, but are conventionally adapted to laboratory and test facility use. Some real-time data gathering methods are also known, such as sensing oil pressure, oil temperature, and shaft speed. However, systems for real-time data collection for real-time data analysis and real-time prediction of maintenance and logistical requirements have eluded the industry.  
         [0007]     Accordingly, it is desirable to minimize aircraft accessory downtime. In addition, it is desirable to predict preventive maintenance requirements and logistical requirements to minimize downtime. Furthermore, other desirable features and characteristics of the present invention will become apparent from the subsequent detailed description and the appended claims, taken in conjunction with the accompanying drawings and the foregoing technical field and background.  
       BRIEF SUMMARY  
       [0008]     An apparatus is provided for monitoring an aircraft accessory. The apparatus comprises a processor associated with said aircraft accessory, a transducer coupled to said processor and operable to produce parametric data relating to said aircraft accessory and a memory coupled to said processor having baseline parametric data residing therein, wherein said baseline parametric data comprises the parametric data obtained during an acceptance test procedure;  
         [0009]     A method is provided for monitoring an aircraft accessory. The method comprises recording, in a memory coupled to a processor coupled to sensors adapted to gather data relating to the aircraft accessory, baseline parametric data produced by the processor from the data gathered by the one or more sensors during operation of the aircraft accessory while undergoing an acceptance test procedure and comparing, in the processor and during operation of the aircraft accessory in an aircraft, real-time operational parametric data produced by the coupled processor from the data gathered by the one or more sensors with the baseline parametric data.  
     
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0010]     The present invention will hereinafter be described in conjunction with the following drawing figures, wherein like numerals denote like elements, and  
         [0011]      FIG. 1  is a diagram of an exemplary apparatus for monitoring an aircraft accessory;  
         [0012]      FIG. 2A  is a partial block diagram of an exemplary method for monitoring an aircraft accessory;  
         [0013]      FIG. 2B  is a partial block diagram of the exemplary method of for monitoring an aircraft accessory of  FIG. 2A ;  
         [0014]      FIG. 3  is a process flow diagram for an exemplary characterization mode of an exemplary apparatus for monitoring an aircraft accessory;  
         [0015]      FIG. 4  is a process flow diagram for an exemplary monitoring mode of an exemplary apparatus for monitoring an aircraft accessory; and  
         [0016]      FIG. 5  is a graph of a parameter versus time for superimposing actual data and model data.  
         [0017]      FIG. 6  is a block diagram of an avionics system adapted to monitor a plurality of aircraft accessories. 
     
    
     DETAILED DESCRIPTION  
       [0018]     The following detailed description is merely exemplary in nature and is not intended to limit the invention or the application and uses of the invention. Although described as implemented in an aircraft turbine starter (ATS), the present invention also applies to various other aircraft accessories include, without limitation, starters, auxiliary power units, valves, hydraulic pumps, and actuators generally. Aircraft accessories support the operation of various aircraft systems including engines and thrust reverser systems. Furthermore, there is no intention to be bound by any expressed or implied theory presented in the preceding technical field, background, brief summary or the following detailed description.  
         [0019]     Turning now to the description,  FIG. 1  depicts a simplified block diagram of an exemplary accessory monitor  230  configured to monitor an exemplary aircraft accessory  206 , which in this case is an air turbine starter  206 . The air turbine starter  206  is adapted to receive compressed air  205  from compressed air source  202 . The compressed air  205  is supplied to the turbine vanes  204 , which are mounted rotationally in the air turbine starter  206 . The pressure of the compressed air  205  is sensed by a pressure sensor  203 , which is coupled to a monitor data interface  232  of the aircraft accessory monitor  230  by a communications channel  220 . One or more parameters associated with the turbine vanes  204  such as, for example, strain forces on selected vanes, rotational speed, or rotational acceleration, may be monitored. In the depicted embodiment, the rotational speed of the turbine vane  204  is sensed by sensor  211 , such as, for example, a tachometer, which is coupled to the monitor data interface  232  by communications channel  222 . Various other parameters associated with the air turbine starter are also monitored. For example, oil temperature is sensed by sensor  213  and communicated to the monitor data interface  232  over communications channel  224 . Oil pressure is sensed by sensor  215  and communicated to the monitor data interface  232  over communications channel  226 . In some embodiments, chip detectors may be employed to detect a larger than normal amount of metallic chips in the oil and conductivity sensors may be used to determine oil viscosity. Moreover, as is generally known, the output of the aircraft engine starter  206  is a shaft  209  exerting a torque on a load  212 , which may be an aircraft engine (not illustrated). Thus, the shaft rotation may additionally be parameterized as to torque, speed, deflection, vibration, and torsion, to name a few examples. In the depicted embodiment, a torque sensor  210  senses torque and communicates the sensed torque data to the monitor data interface  232  over communications channel  228 . The selected sensors and parameters and the number thereof are exemplary and are not intended to limit the present invention. The communications channels  220 ,  222 ,  224 ,  226 , and  228  conventionally use wired connections but may be wireless or fluidic in some embodiments. While the aircraft accessory monitor  230  is depicted as discrete, the monitor  230 , the memory  234 , the processor  236 , or any combination thereof may be at least partially integral to the aircraft engine accessory  206 . In an alternate embodiment, one monitor may  230  serve for a plurality of aircraft engine accessories having associated sensors.  
         [0020]     The data arriving at the monitor data interface  232  may be pre-processed to produce data that are useful to processor  236 . For example, if the processor  236  and the memory  234  are electronic digital components, analog-to-digital conversion of raw sensor data may be performed as part of the monitor data interface  232  functions. Other conversions, such as the conversion of raw digital sensor signals into other digital signals representing parameters in conventional units may be performed in the monitor data interface  232 . For example, shaft speed may be sensed as a rate of pulses caused by reflection of a diode laser light off a reflective strip on shaft  209 . Conversion of the raw output pulses into units of revolutions per second may be performed in the monitor data interface  232 . Alternatively, some data conversions may be performed by processing circuitry integral to the sensor. For example, some tachometers convert electrical pulses into revolutions per second or revolutions per minute. Some data conversions may take place in dedicated components (not shown) coupled in series with the appropriate communications channel. Still other data conversions may be performed in the processor  236 . For example, some data analysis routines may use data representative of revolutions per second, others may use revolutions per minute, and conversion between those units may be performed in the processor  236 .  
         [0021]     The monitor data interface  232  transfers the data it receives onto the bus  233  automatically or on demand. The monitor data interface  232  may be designed for high-speed data acquisition and transfer. Increased speed in the data acquisition process may be accomplished by parallel data input or by interleaving time slots during which various communications channels are open. The monitor data interface  232  is preferably sized for real-time data rates for all sensors. In any of these cases, the data that is transferred onto the bus  233  may be stored in the memory  234  or processed immediately by the processor  236 .  
         [0022]     Memory  234  may be any of numerous conventional types and may be packaged discretely, integrated, or distributed, and is preferably at least partially non-volatile. Memory  234  may be partially read-only memory, and may include recordable removable media, such as CD-ROM or other disk, stick, card, or tape memory. Memory  234  is also preferably selected to survive the end-use operational environment. Memory  234  may be flash memory. Memory  234  is used to store, among other things, various types of real-time and model parametric data, including baseline parametric data, model parametric data, and operational models, if any. These data and models are discussed in more detail further below. A non-volatile portion of memory  234  may be attached to aircraft engine starter  206  as part of the aircraft accessory monitor  230 , which itself may be attached to aircraft engine starter  206 . Attachment of the memory  234  to the aircraft accessory  206  includes attachment to structural elements associated with the aircraft accessory  206 , such as brackets, cowlings, fittings, and similar articles used to install an aircraft accessory  206 . When the aircraft accessory  206  is installed or removed, it is preferred that the memory be automatically installed or removed with the accessory by virtue of attachment. In an embodiment where the aircraft accessory  206  is integral with the engine, the memory  234  may be attached to the engine or its inherently associated structures.  
         [0023]     In addition to real-time parametric data, the memory  234  additionally stores data representative of a bill of materials for the accessory. These data are available for download through download interface  236 , which may provide for burst mode data transfer to data customer  242 . In some embodiments, memory  234  may be attached to the aircraft accessory  206  and connected by a data bus  233  to the remaining components of a remotely located aircraft accessory monitor  230 . A data customer  242 , which may be, for example, an aircraft mechanic or maintenance analyst, can download data when the aircraft is on the ground. Alternatively, the data customer  242  may retrieve the data by radio frequency communication while the aircraft is in flight. In some embodiments, the data customer  242  is an off-line processor that performs non-real-time analysis of the real-time data.  
         [0024]     The processor  236  may be any one of various known processors and may be packaged discretely, integrated, or distributed, and should be sized and configured to handle real-time data processing loads. The processor  236  may be collocated with the memory  234  in the aircraft accessory monitor  230  or as a distributed part of the aircraft accessory monitor  230 . The processor  236  may drive a reporter  240 , such as a display, to provide analysis results to users. The reporter  240  may comprise other devices instead of, or in addition to, the display  240 . For example, the reporter  240  may include audible alarms, flashing lights, instrument panel displays, emergency flight data recorder inputs, or voice messages to the pilot or ground personnel.  
         [0025]     It will be appreciated that the aircraft accessory monitor  230  may be packaged discretely, integrated with the aircraft accessory  206 , or distributed throughout the aircraft accessory  206 . The aircraft accessory monitor  230  may be produced as a standardized unit and used for a wide variety of similar aircraft engine accessories  206  or may be customized to each aircraft accessory  206  and its particular operational environment.  
         [0026]     Having described the aircraft accessory monitor  230 , and its interface to a particular accessory, a detailed description of the processes implemented by the aircraft accessory monitor will now be provided. In a particular preferred embodiment, the aircraft accessory monitor  230  may be operated alternatively in either a characterization mode  302  or a monitor mode  402 . An overall view of an exemplary method of aircraft accessory monitoring  100  will be described first followed by more detailed description of the characterization mode  302 , which is depicted in  FIG. 3 , and the monitor mode  402 , which is depicted in  FIG. 4 .  
         [0027]     Turning now to  FIGS. 2A and 2B , an exemplary method of aircraft accessory monitoring  100  according to an exemplary embodiment is depicted in flowchart form. The method  100  begins at step  102  the engine accessory monitor  230  depicted in  FIG. 1  is energized. Though not explicitly depicted, step  102  when may include self-tests at start-up, such as one or more of a random access memory test, data acquisition self test, one or more sensor tests, and a test to determine if characterization has been completed. In this exemplary embodiment  100 , the depicted method  100  proceeds with a characterization mode  302 , which includes steps  110 - 111 . The characterization mode  302  is described in more detail below. If the characterization mode  302  has been previously completed, it may not be necessary to perform the characterization mode  302  at each start-up, and in another exemplary embodiment, the completed characterization test result in step  102  may branch to a later step such as step  112 . In step  110 , baseline parametric data is recorded during an acceptance test procedure. Baseline parametric data  504 , which is graphically depicted in  FIG. 5 , is data that describes the performance of the aircraft engine accessory, such as the aircraft engine starter at a particular point in time, such as when it is new or refurbished. The baseline parametric data  504  describes the system and provides a starting point from which wear and performance changes over time may be measured. The baseline parametric data is stored in the memory  234  associated with the air turbine starter  206  or other aircraft accessory. In some circumstances, the baseline parametric data may also be stored offline so that it can be re-recorded in step  110  after the contents of memory  234  has been compromised by adverse environmental effects.  
         [0028]     In step  111 , a bill of materials for the particular aircraft accessory is loaded into the non-volatile memory associated therewith. Each part making up the aircraft accessory may be listed in the bill of materials, along with specifications and dates of installation for lubricants and other elements that are replaceable in the operational environment, such as filters. The bill of materials data as to replaced elements may be updated in the field, and a history of the replacements may be maintained in the bill of materials. In a particular embodiment, the bill of materials may only be updated  111  at a predetermined factory as to factory-replaceable parts.  
         [0029]     When the characterized aircraft accessory monitor is installed in an operational aircraft, step  112  collects real-time operational parametric data  510  (see  FIG. 5 ) relating to the aircraft engine accessory  206  using engine accessory monitor  230 . Step  112  begins the monitoring mode  402  of the aircraft accessory monitor, which is more fully described further below. In step  112 , the aircraft accessory, with associated sensors, memory, and processor has been installed in an operational aircraft, and the sensors transduce real-time operational parametric data  510  as the aircraft accessory operates. The real-time operational parametric data  510  may parallel the baseline parametric data  504  recorded during the acceptance test procedures as to source and type. Preferably, the same sensors are used during normal operations as in acceptance testing.  
         [0030]     In step  114 , the real-time operational parametric data  510  is recorded in the memory  234 . The recorded real-time operational parametric data  510  may be downloaded for further analysis, perhaps with the bill of materials and the baseline parametric data  504 . In an alternate embodiment, step  114  may be omitted, and data analysis may be performed in near real-time and the analysis results recorded  114 . In some embodiments, normative data is not stored  114  and only deviations from the norm are recorded  114 . Hybrid data collection, where some data is saved by exception and some is saved by selection may also be employed. The real-time operational parametric data is preferably stored  114  in a format conducive to high-speed data transfer.  
         [0031]     In step  116 , the real-time operational parametric data  510  and baseline parametric data  504  are analyzed for relationships that may signal a need for operator or maintenance action. For example, an oil pressure exceeding a first predetermined limit may signal the need for operator attention. For further example, a prolonged event during which oil temperature exceeds a second predetermined limit may indicate the need for an early oil change. The analysis  116  of real-time operational parametric data contemplates a wide variety of analysis tools ranging from simple limit checks to Kalman filters and data mining. Each analysis method  116  may not have to be real-time, even though it operates on real-time data, because a plurality of analytical processes may be spawned; Analysis step  116  may take into account only data from one accessory, or may correlate data from a plurality of accessories on one engine, or on a plurality of engines.  
         [0032]     In step  117 , analysis results of immediate interest may be reported to a flight crew or other operator. The analysis result may be the primary information reported, or the real-time operational parametric data  510 , perhaps graphed against time  500  as shown in  FIG. 5 , may be reported  117 . Conventional means of data reporting, such as video displays, flashing lights, and audible alarms are contemplated within step  117 . In step  119 , analysis results may be used to initiate fault isolation procedures, which may include automatic determination of a failed component or a root cause determination using a diagnostic engine.  
         [0033]     In step  118 , maintenance requirements are determined based, at least in part, on the analysis of relationships between the baseline parametric data  504  and the real-time operational parametric data  510 . For example, if a shaft rotational velocity shows particular variations, a bearing replacement may be indicated. Thus, maintenance which was formerly performed based on raw operational hours or calendar days may be made adaptive to actual maintenance needs, resulting in reduced downtime and costs and improved flight safety. Moreover, the bill of materials data may be used to determine maintenance requirements. For example, the real-time operational parametric data  510  may be associated with a part, or element on the bill of materials, to indicate what part in the aircraft accessory may need maintenance.  
         [0034]     In step  120 , logistical requirements are determined based, at least in part, on the analysis of relationships between the baseline parametric data  504  and the real-time operational parametric data  510 . For example, an analysis  116  showing indications of premature bearing wear-out in an aircraft engine starter may indicate the need for a spare part. Correlation with similar starter bearings on other engines in the same aircraft may indicate that all of the starters on the aircraft have early bearing wear, requiring a plurality of spare parts. Off-line correlation with starter bearings in other aircraft with the same model starter may indicate, for example, a starter design problem, a bearing manufacturing problem, or merely that the aircraft is in service in cold weather and the bearing lubricant needs to be adapted for low temperature service.  
         [0035]     In a simpler embodiment, step  120  may be the last step in the method  100 . The exemplary method  100  was constructed to illustrate that the method includes analyzing real-time operational parametric data  510  relationships to baseline parametric data  504 , and/or real-time operational parametric data  510  relationships to model parametric data  502 ,  506  and  508 . However, a simpler embodiment ending at step  120  would analyze only real-time operational parametric data  510  relationships to baseline parametric data  504 .  
         [0036]     Step  122  includes storing model parametric data  502 ,  506  and  508  in the non-volatile memory. Step  122  may be done before step  112  as part of the characterization mode  302 , but can be performed, repeated, or upgraded at any time. One of the preferred data models  502  is a six-sigma model, but other models may be used, adaptive to requirements. A six-sigma model is preferred. For example, a model based upon historical data may be useful for modeling wear of moving parts and a model extrapolated from a physics-based simulation may be useful for expressing expectations for a completely new device. The model stored in step  122  may stand alone  502  as a reference for real-time operational parametric data  510  or may be incorporated as limits  506  and  508  to either the baseline parametric data  504 , the model parametric data  502 , or both. In an alternate embodiment, more than one model may be used.  
         [0037]     In step  124 , relationships between baseline parametric data  504  and model parametric data  502 ,  506  and  508  are analyzed for indications of a need for operator or maintenance action. Analysis results from step  124  indicating a need for operator action may be reported directly to an operator or flight crew member in step  125 . Analysis results from step  124  indicating a need for maintenance action may be stored in an onboard maintenance log, radioed to the maintaining organization, or printed out as part of a flight log in step  126 . Analysis results indicating a fault may be provided as input to a fault isolation subsystem  127 , which may use additional analysis results from steps  116  and  124  to isolate a faulty component.  
         [0038]     In step  126 , maintenance requirements may be determined from analysis of relationships between baseline parametric data  504  and model parametric data  502 ,  506  and  508 . For example, model parametric data  502 ,  506  and  508  may include a parameter representing maintenance requirements as a function of operational time above a particular shaft rotation speed. The corresponding real-time operational parametric data  510  may be obtained from a tachometer coupled to a counter that activates above a selected or predetermined shaft speed. When a predetermined limit on shaft over-speed time has been exceeded, the cognizant maintenance organization is notified. For a less simple example, the predetermined limit on shaft over-speed time may be adjusted as a function of peak shaft drive torque and peak back-drive shaft torque to make the maintenance call earlier for highly stressed shafts.  
         [0039]     In step  128 , analysis results from step  124  are used to determine logistical requirements for parts and consumables. Wear and consumption models may be developed historically or prospectively from physics-based simulations. The need for spare parts and consumables, such as lubricants, filters, seals, and chemicals consumed during maintenance, can be specified as a function of the condition of the aircraft accessory. Baseline parametric data  504  may be compared with model parametric data  502 ,  506  and  508  to estimate the points in time when spare parts and consumables will be needed and the cognizant logistics organization may schedule acquisition of parts and consumables accordingly. A particular embodiment of the method ends with step  128 .  
         [0040]     In step  130 , relationships between real-time operational parametric data  510 , baseline parametric data  504 , and model parametric data  502 ,  506  and  508  may be performed. There are many ways to combine the three data types for analysis. For example, six-sigma limits  506  and  508  from the model parametric data may be associated with the baseline parametric data  504  instead of the model parametric centerline data  502 , to indicate when the aircraft accessory may be exceeding its particular limits. In a further example, the model parametric data  502 ,  506 , and  508  may be used as a reference to smooth real-time parametric data  510  into an updated or additional operational baseline. Operational baseline data may then be compared with acceptance test baseline data  504  to identify weaknesses in acceptance test procedures.  
         [0041]     Note that analysis results from steps  116 ,  124 , and as discussed below, step  130 , may provide data for making new models or improving old ones. In an alternate embodiment, at least one of the models represented by model parametric data  502 ,  506  and  508  may be self-updating. For example, a stream of data for a given parameter may be filtered to improve the original estimate of its curve  502 , and the improved curve  502  may replace the previous version of curve  502 . In most embodiments, step  130  may include step  116  and step  124  in a single analysis step  130 .  
         [0042]     Results of analysis step  130  may be reported to crew members or others in step  131 . The step of reporting  117 ,  125 , or  131  may include initiating alarms, as appropriate. If a fault, such as a parameter exceeding limits is found in step  130 , fault isolation is initiated in step  133 . Step  132  is similar to steps  118  and  124  and may provide additional information into maintenance requirements based upon the use of both model parametric data  502 ,  506 , and  508  and baseline parametric data  504  with real-time operational data  510 . Step  134  is similar to steps  118  and  124  and may provide additional information into logistical requirements based upon the use of both model parametric data  502 ,  506 , and  508  and baseline parametric data  504  with real-time operational data  510 . Exemplary process  100  ends at step  136 . The pattern of steps for further analysis using additional models will be understood by those of ordinary skill in the art from the patterns of steps  116 - 122 ,  124 - 128 , and  130 - 134 .  
         [0043]     As was noted above, steps  110  and  111  represent generally the process that is performed in the characterization mode  302 . A descriptioin of this mode will now be provided in more detail.  FIG. 3  shows a flow chart of the characterization mode  302 . Characterization mode  302  may be used at the factory to acquire baseline parametric data  504 , model data  502 ,  506  and  508 , bill of materials data, and to couple to a test set during acceptance test procedures (ATP). The process  300  begins with the aircraft accessory monitor  230  being placed in characterization mode  302 , by signal or manual switch. No matter the particular manner in which this mode  300  is reached, when it is, one or more acceptance test procedures are performed, which generate baseline parametric data  504 . These baseline parametric data are stored, or recorded in the memory  234 . It will be appreciated that the specific types of data that constitute parametric data may be different for each aircraft accessory and even each accessory model. For example, an aircraft engine starter, such as the one described above, may be parametrically described by shaft speed, shaft torque, turbine pressure, oil temperature, oil pressure, vane strain, and histories and extrema of each parameter, just to name a few. A valve, for further example, may be parameterized by actuation force, pintle position, and flow rate, as well as histories and extrema of each parameter. The baseline parametric data gathered and recorded during each acceptance test procedure is intended to remain with the aircraft accessory for the life of the aircraft accessory.  
         [0044]     During the characterization mode  302 , a bill of materials for the particular aircraft accessory is also loaded into the memory  234 . Each part making up the aircraft accessory may be listed in the bill of materials, along with specifications and dates of installation for lubricants and other elements that are replaceable in the operational environment, such as filters. The monitor  230  may be configured such that the bill of materials data as to replaced elements may be updated in the field, and a history of the replacements may be maintained in the bill of materials. In a particular embodiment, the bill of materials may only be updated at a predetermined factory as to factory-replaceable parts.  
         [0045]     If the load flag is determined to be set in step  304 , then high frequency burst data acquisition  306  may be used to upload six-sigma model  308 , to upload bill of materials  310 , and to upload a fault isolation degradation model  312 . In some embodiments, fewer models may be uploaded. In other embodiments, additional models may be uploaded. For example, a model derived from real-time operational data acquired by a predecessor aircraft accessory monitor  230  on a predecessor aircraft accessory  206  being replaced by the aircraft accessory monitor  230  which is in characterization mode  302  may be uploaded. Data relating to the structure of the baseline parametric data model  504 , or baseline model  504 , may be uploaded when the load flag is set. In some embodiments, the baseline parametric data model  504 , may be loaded using high speed burst data acquisition  306 . Likewise, in some embodiments, one or more steps  308 ,  310 ,  312 , and  320  may be accomplished without using high speed burst mode data acquisition  306 .  
         [0046]     If the load flag is determined in step  304  to not be set, then step  330  determines if the aircraft accessory monitor  230  is communicating with a test set, such as a test set used for ATP. If not, then characterization mode ends at step  342 . Otherwise, test set commands are entered by a user in step  332  for both setting parameters in step  336  and organizing data acquisition for the parameters set in step  334 . In other embodiments, step  334  may follow step  336  linearly. In other embodiments, the parameters may all be set in step  336  and then different test set commands from step  332  may cause step  334  to be executed for all set parameters. The validity of the parameters set in step  336  and associated with data streams in step  334  may be tested in step  338  by verifying that each parameter has an associated data stream that does represent the parameter and that each desired parameter has been set. These parametric data streams may be used to fill in the structure of the baseline model  320  in step  340 . The baseline model is based upon the data acquired during ATP, and provides parameters representing the actual performance of the specific aircraft accessory under test. The baseline model  320  may be associated with other models. For example, six sigma limits from the six-sigma model derived from previous tests of all similar aircraft accessories may be added to the baseline model  320  to provide an estimate of the six-sigma limits of the specific aircraft accessory under test. Any associations between models, such as associating six-sigma model limits with the baseline parametric model, may also be performed in step  340 . After all models are finalized and the baseline model has been populated in step  340 , process  300  ends at step  342 , and the monitor mode  402  may be commenced.  
         [0047]     As was noted above, steps  112 - 136  represent generally the process that is performed in the monitor mode  402 .  FIG. 4  shows a flow chart of the monitoring mode  402 . Monitoring mode  402  is the normal operational mode of the aircraft accessory monitor  230 . The process  400  begins with the aircraft accessory monitor  230  being placed in monitoring mode  402 , by signal or manual switch. If step  404  determines that a start command has been invoked, sensors, such as pressure sensor  203 , tachometer  211 , oil temperature sensor  213 , and oil pressure sensor  215  as shown in  FIG. 2 , are energized and high speed data acquisition of the real time data arriving at monitor data interface  232  begins in step  406 . At least a portion of the real-time parametric data  510  may be stored in memory  234  as part of step  408 . The portion of real-time parametric data  510  selected to be stored in step  408  may represent exceptional conditions, such as parameters out of limits, or may represent data focused on a particular parameter or group of parameters. The real-time parametric data  510  is tested against the baseline parametric data  504  in step  410 . Step  410  may be a sub-step of step  116  or step  130 . The real-time parametric data  510  is also tested against the model parametric data  502 ,  506  and  508  in step  412 . Step  412  may be a sub-step of step  124  or step  130 .  
         [0048]     If real-time data or model comparisons indicate a fault in step  414 , step  416  runs the fault isolation model in step  416 . The fault isolation model is machine-executable logic which responds to real-time parametric data  510  and possibly other data to determine what component, part, or phenomenon caused the indicated fault. If no fault is detected, a data flag indicating the absence of a fault (e.g., a “good” flag) may be stored in memory  234  along with a time stamp in step  422 . The periodicity with which the “good” flag may be set in step  422  may be set as a parameter in step  336 . In some embodiments, the flag periodicity may be set in software that is used to operate the aircraft accessory monitor  230 . After the “good” flag is set, process  400  continues at step  406 .  
         [0049]     If step  404  determines that the start command has not been invoked, step  418  determines if the serial command has been invoked. The serial command may be invoked by field maintenance workers or remotely by any data customer  242 . If step  418  determines that the serial command has been invoked, data is downloaded in step  420  over the download interface  238 . The downloaded data may include stored real-time operational data or model data, as selected by data customer  242 . After the data download, process  400  continues through node  430  to step  402 .  
         [0050]     If step  418  determines that the serial command has not been invoked, step  426  determines if the bill of materials command, or BOM command, has been invoked. If so, the bill of materials may be downloaded over download data interface  238  or reported on display  240  at the option of data customer  242 . After the BOM has been reviewed in step  424 , process  400  continues through node  430  at step  402 .  
         [0051]      FIG. 5  shows a graph of an exemplary parameter against time. The graph superimposes one real-time parametric data stream  510  over baseline parametric data  504  and model parametric data  502  having upper and lower limits  508  and  506 . The graph illustrates one parameter among a plurality of parameters and their associated baseline  504  and six-sigma  502 ,  506 , and  508  models. Curves for other parameters may be substantially different from the depicted embodiment. For example, some parameters may be binary. Some curves may reflect a function of several parameters. Those of ordinary skill in the art of data analysis will appreciate the various forms that parametric curves may take. The depicted embodiment illustrates the relationships between parametric data from different sources and is not intended to limit the invention to the models  502 ,  506 ,  508 , and  504  depicted.  
         [0052]      FIG. 6  shows a diagram of exemplary aircraft accessories supplying data along sensor communications links  620  (only one is labeled) to a centralized avionics system  602  which performs the role of monitor  230  in addition to other avionic functions. Aircraft accessories including main engine  604 , air turbine starter  606 , air turbine starter valve  608 , auxiliary power unit  610 , environmental control system  612 , and air management system  614  may supply data from one or more sensors associated with each aircraft accessory to one or more processors and one or more memories in the avionics suite  602 . Avionics suite  602  may be, for example, a Primus EPIC avionics suite manufactured by Honeywell, International of Phoenix, Ariz. The aircraft accessories shown are not intended to be limiting. Other aircraft accessories, such as thrust reversers and actuators generally, may be connected to a centralized avionics suite. In alternate embodiment, each aircraft accessory may have a dedicated and possibly integrated monitor  230  which sends results of the monitoring process to the avionics suite  602  over communications links  620 .  
         [0053]     While at least one exemplary embodiment has been presented in the foregoing detailed description, it should be appreciated that a vast number of variations exist. It should also be appreciated that the exemplary embodiment or exemplary embodiments are only examples, and are not intended to limit the scope, applicability, or configuration of the invention in any way. Rather, the foregoing detailed description will provide those skilled in the art with a convenient road map for implementing the exemplary embodiment or exemplary embodiments. It should be understood that various changes can be made in the function and arrangement of elements without departing from the scope of the invention as set forth in the appended claims and the legal equivalents thereof.