Patent Description:
Traditional maintenance scheduling for aircraft engines includes a combination of life expectancy and observational scheduling, with the life expectancy scheduling being predetermined based on an expected use case and the structure of the component, and the observational being based on routine and periodic observation of specific components to identify damage.

Observational scheduling generally includes high frequency maintenance intended to prevent failure in components prone to Foreign Object Damage (FOD). Observational scheduling assumes a worst-case scenario of engine operation and FOD when defining inspection frequency and damage limits. Due to the worst-case scenario assumptions, observed FOD can lead to immediate unscheduled maintenance that may not be required to prevent component failure.

Predetermined, or life expectancy based, maintenance schedules are generally low frequency, primarily intended to prevent failure in components from damage incurred during an assumed engine operation, which may be conservative, e.g., aggressive use in harsh environments with more FOD assumed than experience might dictate.

In scheduling both life expectancy and observational based maintenance, assumptions are made in-terms of both the stress-state from vibration modes and stress increase due to FOD exposure and severity. These assumptions can result in increased fleet sustainment cost through unnecessary inspection and repair operations.

<CIT> discloses a prior art system and method for planning engine borescope inspections based on FOD probability estimation.

<CIT> discloses prior art predictive part maintenance.

From one aspect, there is provided a process for scheduling engine inspection for a gas turbine engine as recited in claim <NUM>.

There is also provided a computer system for determining maintenance schedules for a gas turbine engine not presently claimed.

<FIG> illustrates an exemplary gas turbine engine <NUM>, including a compressor section <NUM> connected to a combustor section <NUM> and a turbine section <NUM> via a first shaft <NUM> and a second shaft <NUM>. The exemplary compressor section includes a low pressure compressor <NUM> fluidly connected to a high pressure compressor <NUM>. An output of the high pressure compressor <NUM> is provided to at least one combustor <NUM> within the combustor section <NUM>. The at least one combustor <NUM> mixes the output of the high pressure compressor <NUM> with a fuel and combusts the mixture. The resultant combustion products are provided to a high pressure turbine <NUM> along the flowpath. The high pressure turbine expands the combustion products which drives rotation of the high pressure turbine and the second shaft <NUM>. Similarly, the output of the high pressure turbine <NUM> is provided to a low pressure turbine <NUM> and expanded. The expansion across the low pressure turbine <NUM> drives rotation of the low pressure turbine <NUM> and rotation of the first shaft <NUM>. The second shaft <NUM> is connected to the high pressure compressor <NUM> and drives rotation of the high pressure compressor <NUM>. Similarly, the first shaft <NUM> is connected to, and drives rotation of the low pressure compressor <NUM>. A fan <NUM> is disposed upstream of the low pressure compressor <NUM> and is driven to rotate via a geared connection <NUM> to the first shaft <NUM>. In alternate examples, the fan <NUM> can be connected via a direct drive, omitting the geared connection <NUM>.

The gas turbine engine <NUM> described above, and illustrated in <FIG> is exemplary in nature, and it is appreciated that the following systems and processes can be applied similarly to any other aircraft engine, even when the other engine deviates substantially from the generally described construction. Due to the design and operating environment of the engine <NUM>, certain components such as fan blades and compressor blades are subject to damage from debris and other ingested objects. The damage is referred to as foreign object damage (FOD).

During operation of the gas turbine engine <NUM>, a data recorder <NUM> that is either local to the engine <NUM> (as in the example of <FIG>), or within the aircraft and connected to sensors within the engine, stores flight operational data including, but not limited to rotor speed, time history, total engine flight hours, engine flight hours at maximum operating conditions, pressure and temperature at <NUM> or more engine station, aircraft altitude and mach number or forward velocity, crosswind speed, direction and any similar metrics. Flight operational data is at least partially determined via onboard sensors according to any known sensor configuration. Additional flight operational data can be inferred from one or more sensors according to known correlations and/or derived at least partially from engine control signals throughout the flight. After the flight, the data recorder is physically removed from the aircraft and provided to a computer system for analysis. In alternative examples, the aircraft can be physically connected to the computer system upon landing via a communication connection, or the data recorder can communicate wirelessly with the land-based computer system. In yet further alternative designs, a computer or controller onboard the aircraft can perform the process described below.

Rather than following a predefined time or flight hours-based maintenance and inspection schedule, the system described herein applies usage data from the flight data recorder to determine a probability of damage or risk of component failure ("risk"). Risk is then used to order maintenance as needed. This is referred to herein as "usage-based scheduling". Usage-based scheduling offers reduced maintenance frequency by accounting for actual engine use to reduce or eliminate conservative assumptions that are necessary to define an observational or predetermined maintenance schedule.

<FIG> provides a general overview of the usage-based scheduling system for determining when manual inspections and maintenance are required to identify and repair foreign object damage for a given engine in a gas turbine engine, such as the engine <NUM> illustrated in <FIG>. After each flight the aircraft data recorder is connected to a computer, and the flight data is provided to an analysis system in a "Provide Aircraft Usage Data" step <NUM>.

The aircraft usage data includes engine metrics measured by conventional engine sensors, such as those described above. By way of example, one engine metric that can be used is rotor speed which infers exposure to vibrational modes which can also be correlated to various types of foreign object damage or debris ingestion events. The total stress state, defined by the combination of active vibrational modes and foreign object damage which acts as a stress riser, is determined throughout a time history. The stress time history is then used to calculate a damage increment. In practice, usage data is applied to a set of models to compute the expected damage increment for the specific flight in a "Compute Damage Increment" step <NUM>. The expected damage increment is calculated using a probabilistic foreign object damage model at least partially dependent on and continuously calibrated to, statistical data sets of previous inspection and usage data and assuming that foreign object damage has occurred for each flight and at each potential foreign object damage zone of the component. In examples using vibrational modes to correlate with occurrences of foreign object damage and/or debris ingestion, the expected damage increment is calculated at each mode of vibration that is excited in the engine by measuring or computing the time history of the response. In some examples, the foreign object damage model is an engineering model.

The damage is summed for contributing modes of vibration to determine the damage increment for the specific flight. In some examples, after a certain number of iterations, the engineering model for foreign object damage is manually revised based on empirical results in the field to account for new inspection and usage data. This update can be performed manually, automatically, or both, depending on the type of inspection and usage data acquired.

Once the expected damage increment has been calculated, the system applies the increment to the damage history of the engine in a "Compute Cumulative Damage" step <NUM>. The cumulative damage represents the total deterioration over time of the engine components since the previous maintenance. In a practical example there are a large number of cumulative damage values that are independently tracked, and the complexity resulting from the amount of tracked values would take longer to calculate manually than there is time between flights and the process could not be practicably achieved without computer assistance.

After determining the cumulative damage values, the probability of failure of the components in a subsequent flight is determined in a "Compute Probability of Failure" step <NUM>. The probability of failure is calculated for each possible foreign object damage location from each flight that has occurred since the previous maintenance. This process is repeated for each airfoil or airfoil type separately, and in the aggregate, as well as for any other components that are susceptible to foreign object damage. By way of example, if any components, such as blades include unique information or attributes, each of the components that have unique information is analyzed independently to account for the special information. Alternatively, when an assembly such as a bladed wheel includes, as a whole, a defining feature such as intentional mistuning, the components of the assembly driving the defining feature are analyzed in the aggregate.

When the probability of failure on the next flight (alternately referred to as "risk") exceeds a predefined threshold, the system <NUM> outputs an inspection requirement in an "Output Inspection Requirement" step <NUM>. In one example, the risk threshold is in the range of <NUM>/<NUM> to <NUM>/<NUM>, although specific implementations may stray from that range depending on the particular usage of the engine and aircraft in question, as well as the applicable industry or internal standards. When the probability of failure is below the risk threshold an inspection is not ordered, and the process is reiterated after the next flight.

When an inspection is ordered, manual inspection and maintenance is performed on the aircraft during which any damage, including foreign object damage, is manually identified and repaired by one or more technician in a "Perform Maintenance" step <NUM>. Once any identified damage is repaired, or the corresponding components are replaced, the historical record of damage data is reset to <NUM> in a "Reset" step <NUM>, and the process <NUM> reiterates with the next flight.

With continued reference to the process <NUM> of <FIG> illustrates an example cycle over <NUM> sequential flights. After each flight, the cumulative risk (RISK) increases until the fourth flight, where the cumulative risk exceeds the predefined threshold <NUM>. After the fourth flight, the computer system operating the process orders an inspection and maintenance is performed. In one example, the computer system assumes <NUM>% effective inspection and maintenance and causes the cumulative risk to be reset to no cumulative risk prior the fifth flight. In other examples, the reset can account for "imperfect" maintenance by resetting to a cumulative damage value above zero. In yet further examples, the system can wait for a confirmation that the maintenance operation was successful before resetting the cumulative risk. As each damage increment is dependent on the total aircraft usage data from the corresponding flight, the number of flights or the number of flight hours between maintenance is not uniform, and the occurrence of costly and time-consuming manual inspections and maintenance is limited to times when the risk of foreign object damage exceeds an acceptable level.

With continued reference to <FIG>, <FIG> schematically illustrates an exemplary model computer system <NUM> for implementing the process <NUM> of <FIG> including both physical components and software modules. The computer system <NUM> includes a flight data recorder <NUM> connected to the computer system <NUM> either via a physical data transfer connection <NUM> or via a wireless, or similar, data transfer connection. The aircraft usage data is provided to foreign object damage module <NUM> that computes the damage increment from the given flight based on the aircraft usage data, and a set of correlation models <NUM> including a material capability model <NUM>, a vibratory response characterization model <NUM>, and any other models <NUM> able to determine expected magnitudes of foreign object damage based on the aircraft usage data. Also included in the foreign object damage module <NUM> is a rate, severity, and location assessment module <NUM> that uses the models <NUM> to determine the expected rate, severity, and location of foreign object damage. In some examples, the models <NUM> are combined with inlet debris monitoring system readings and the exhaust distress monitoring systems data from the aircraft usage data to determine the expected rate severity, and location of foreign object damage.

Summed foreign object damage across all contributing modes of vibration that are generated by the foreign object damage module <NUM> is stored within a data storage component <NUM> during each iteration, creating a set of historical damage calculations. The data storage component <NUM> can be any form of data storage, and can be located internal to the computer system <NUM>, internal to the flight data recorder <NUM> storing the aircraft usage data, or external to both systems.

In addition to the data storage element <NUM>, the incremental damage that is calculated is passed to a cumulative damage module <NUM>. The cumulative damage module <NUM> retrieves the stored historical damage increments from the data storage element <NUM> and generates the total cumulative damage, which is then provided to a risk calculation module <NUM>. The risk calculation module <NUM> determines the probability of failure based on the total cumulative damage, as described above, and compares the probability of failure to the acceptable risk. When the probability exceeds the acceptable risk, the computer system provides an alert at an output system <NUM> that informs the technician that a manual inspection is required.

To determine the damage increment based on the material capability of the blades, a fatigue damage accumulation rule, such as Miner's Rule, is applied at each time point of a predetermined frequency and the time points are summed for each mode. In the Miner's rule example, the damage at a given time point i is defined as: <MAT>. The material capability model determines "cycles to failure" using a stress-life modeling system. In other examples, alternative modeling systems can be utilized to similar effect. Most time points have negligible damage levels of zero or approximately zero, however every time point is summed regardless of whether the damage level is approximately zero or is substantial. <FIG> illustrates the damage increments for one zone at two modes of vibration according to an exemplary Goodman analysis model. As can be seen the illustrated two modes include spikes, or plateaus, where the damage levels are meaningful but are still primarily filled with de minimus damage levels.

In addition to Goodman modeling, a standard stress-life model defines the distribution for cycles to failure at all stress levels. Standard stress-life models are used to relate the logarithm of life to stress or the logarithm of stress. Similarly, scatter in life is quantified using standard distributions such as the lognormal, Weibull, or smallest extreme value. Model forms, as well as specific values for numeric constants are determined from specimen and/or component fatigue testing.

With continued reference to <FIG>, <FIG> illustrate an exemplary process for determining an aggregate risk (<FIG>) based on the cumulative damage (<FIG>). For the sake of explanation, in the example of <FIG>, each flight produces the same damage increment (i.e., <NUM>), with the set of lines in <FIG> corresponding to a first FOD occurring on flight <NUM> (D<NUM>,j,<NUM>), a first FOD occurs on flight <NUM> (D<NUM>,j,<NUM>),. , and a first FOD occurs on flight <NUM> (D<NUM>,j,<NUM>). Each cumulative damage sum line from <FIG> has an associated conditional probability of failure curve. In a practical example, the increment will not be identical between flights.

<FIG> illustrates the conditional probabilities of failure based on the first FOD occurring on flight <NUM> (p<NUM>,j), the first FOD occurring on flight <NUM> (p<NUM>,j),. and the first FOD occurring on flight <NUM> (p<NUM>,j). As can be seen, each curve asymptotically approaches <NUM>, as the failure is an eventual certainty. As the process is performed without determining or sensing actual foreign object damage occurrences it is unknown when, or if, the foreign object damage occurs. Thus, the risk curves across all <NUM> flights from <FIG> are aggregated into a single risk curve, illustrated in <FIG>. The risk is aggregated using the standard rules of probability: Total Risk at Flight j = Prob(HCF @ Flight j | FOD on <NUM>) × Prob(FOD on <NUM>) + Prob( HCF @ Flight j | FOD on <NUM>) × Prob(FOD on <NUM>) +. + Prob( HCF @ Flight j | FOD on j) × Prob(FOD on j).

The aggregated risk is the value that is compared with the acceptable risk to determine whether an inspection and maintenance is required after each flight.

By using the above described process and system, the usage based maintenance scheduling reduces maintenance cost and increase fleet readiness by replacing traditional schedule based inspection with the above described process that predicts the need for inspection based on engine usage.

Claim 1:
A computer-implemented process for scheduling engine inspection for a gas turbine engine (<NUM>) comprising:
computing an expected damage increment based on aircraft usage data of a single flight, wherein the aircraft usage data omits foreign object strike detection;
computing a cumulative expected damage by summing the expected damage increment with a total set of historical expected damage increments since a previous maintenance;
determining an aggregate risk of failure based on the computed cumulative expected damage; and
signaling a manual inspection in response to the aggregate risk of failure exceeding an acceptable risk threshold (<NUM>),
wherein computing the expected damage increment comprises determining an expected damage increment at each mode of vibration that is excited in the engine, and summing the increment over all modes to determine the expected damage increment for a specific flight.