Control logic for thrust link crossbar hinge positioning for improved clearance

Abstract

A system and method for optimizing clearance within an engine includes: an adjustable coupling configured to couple a thrust link to an aircraft engine; an actuator coupled to the adjustable coupling, wherein movement generated by the actuator adjusts a hinge point of the adjustable coupling; a sensor configured to capture real-time flight data; and an electronic control unit. The electronic control unit receives the flight data from the sensor, implements a machine learning model trained to predict clearance values ​​within the engine based on the received flight data, predicts the clearance values ​​within the engine based on the received flight data using the machine learning model, determines an actuator position based on the clearance values, and adjusts the actuator to the determined actuator position.

Description

Technical Field

[0001] The present disclosure relates to systems and methods for controlling the pivot position of an adjustable coupling to optimize clearance within an aircraft engine. Background Art

[0002] Optimizing turbine blade tip clearance results in better engine performance and fuel efficiency. Specifically, during different thrust phases, the engine is exposed to loads such as heat and centrifugal forces, which can cause expansion of certain components and shift component alignment, such as the position of the shaft within the high-pressure compressor. For example, the shaft in the high-pressure compressor can shift laterally, causing a change in alignment between the rotor blades and the centerline of the stator flow path.

[0003] In order to adjust the gap between the tips of rotating turbine blades (e.g., rotor blades of a high-pressure compressor) and a turbine casing, such as a shroud (which affects the stator flow path), an active clearance control (ACC) system can provide thermal control air that impinges on the turbine casing with the goal of adjusting the position of the casing and the shroud relative to the rotor blade tips. More specifically, an engine controller (e.g., an electronic engine controller (EEC) or an electronic control unit (ECU) equipped with a full authority digital engine control (FADEC)) can utilize a clearance algorithm to calculate the instantaneous turbine blade tip clearance. The calculated clearance can then be compared to a blade tip clearance target. If the calculated clearance is inconsistent with the clearance target, the ACC system can adjust the blade tip clearance to force the calculated clearance to be consistent with the clearance target. In this way, the shroud is adjusted relative to the blade tip.

[0004] While ACC systems have the ability to control blade tip clearance, clearance targets are typically set without considering how the engine actually or uniquely operates. Instead, every engine of a particular engine model is targeted to the same blade tip clearance, regardless of how the engine operates. Furthermore, engine designs must account for cold build clearances to avoid causing rubbing in the open clearances while the engine is operating.

[0005] Thus, improved active clearance control logic for adjusting blade tip clearance may provide greater improvements in efficiency and fuel use. Summary of the Invention

[0006] In one embodiment, a system for optimizing clearances within an aircraft engine includes: an adjustable coupling configured to couple a thrust link to the aircraft engine; an actuator coupled to the adjustable coupling, wherein movement generated by the actuator adjusts a hinge point of the adjustable coupling; one or more sensors configured to capture real-time flight data; and an electronic control unit communicatively coupled to the actuator and the one or more sensors. The electronic control unit is configured to receive the flight data from the one or more sensors, implement a machine learning model trained to predict one or more clearance values ​​within the aircraft engine based on the received flight data, predict the one or more clearance values ​​within the aircraft engine based on the received flight data using the machine learning model, determine an actuator position based on the one or more clearance values, and adjust the actuator to the determined actuator position.

[0007] In one embodiment, a method for optimizing clearances within an aircraft engine includes: receiving, with an electronic control unit, flight data from one or more sensors; implementing, with the electronic control unit, a machine learning model trained to predict one or more clearance values ​​within the aircraft engine based on the flight data; predicting, with the machine learning model, the one or more clearance values ​​within the aircraft engine based on the flight data; determining, with the electronic control unit, an actuator position based on the one or more clearance values; and causing, with the electronic control unit, an actuator to adjust to the determined actuator position.

[0008] In one embodiment, an aircraft includes an aircraft engine coupled to a wing using at least one thrust link and an adjustable coupling, wherein the adjustable coupling includes at least one aperture for coupling to the at least one thrust link and a slot defining a hinge point of the adjustable coupling; an actuator including a pivot pin slidably coupled within the slot, wherein movement of the actuator adjusts a position of the pivot pin within the slot, thereby changing the hinge point of the adjustable coupling; one or more sensors configured to capture real-time flight data; and an electronic control unit communicatively coupled to the actuator and the one or more sensors. The electronic control unit is configured to receive the flight data from the one or more sensors, implement a machine learning model trained to predict one or more clearance values ​​within the aircraft engine based on the received flight data, predict the one or more clearance values ​​within the aircraft engine based on the received flight data using the machine learning model, determine an actuator position based on the one or more clearance values, and cause the actuator to adjust to the determined actuator position.

[0009] These and other features and characteristics of the present technology, as well as the methods of operation and function of the related elements of the structure and combination of parts and the economy of manufacturing, will become more apparent after considering the following description and the appended claims with reference to the accompanying drawings, all of which form a part of this specification and in which like reference numerals indicate corresponding parts in the various figures. However, it is to be expressly understood that the drawings are for illustration and description purposes only and are not intended as a definition of the limits of the present disclosure. As used in the specification and claims, the singular forms "a", "an", and "the" may include plural referents unless the context clearly dictates otherwise. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The embodiments illustrated in the accompanying drawings are illustrative and exemplary in nature and are not intended to limit the subject matter defined by the claims. The following detailed description of the illustrative embodiments may be understood when read in conjunction with the following drawings, in which like structures are represented by like reference numerals, and in which:

[0011] Figure 1 schematically depicts an example aircraft system according to one or more embodiments shown and described herein;

[0012] Figure 2A depicts an illustrative example of a cross-section of an aircraft engine according to one or more embodiments shown and described herein;

[0013] Figure 2B depicts an illustrative example of an aircraft engine coupled to a wing of an aircraft, the aircraft engine including a thrust link whiffle tree for adjusting a shaft centerline of the aircraft engine in accordance with one or more embodiments shown and described herein;

[0014] Figure 3 schematically depicts a functional block diagram of an engine control system configured to include an electronic control unit for optimizing clearances within an aircraft engine, according to one or more embodiments shown and described herein;

[0015] Figure 4 is an illustrative system diagram for controlling the pivot position of a variable thrust link crossbar to optimize clearances within an aircraft engine in accordance with one or more embodiments shown and described herein;

[0016] Figure 5 depicts a graph illustrating gap reduction by optimizing centering of the stator and rotor in the horizontal (lateral) direction according to one or more embodiments shown and described herein; and

[0017] Figure 6Depicted is a graph illustrating clearance reduction for multiple stages of a high pressure compressor of an aircraft engine according to one or more embodiments shown and described herein. DETAILED DESCRIPTION

[0018] Embodiments of the present disclosure include systems and methods for optimizing clearances within an aircraft engine to improve specific fuel consumption (SFC) and increase the operating efficiency of the engine. More specifically, the systems and methods disclosed herein relate to optimizing clearances by controlling the hinge point of a thrust link hinge, referred to herein as an adjustable connector, e.g., a crossbar. The present disclosure further provides control logic for adjusting the hinge position of the crossbar, as described in more detail herein. The hinge position of the crossbar provides better control over the horizontal centering of the rotor to the stator by reducing cold clearances. That is, tighter cold clearances will reflect tighter cruise clearances, thereby reducing SFC and improving efficiency. For example, in some embodiments described herein, clearances in a high pressure compressor can be improved by ~3-5 mils, e.g., providing an SFC improvement of 0.05 to 0.1%.

[0019] Reference will now be made in detail to the present embodiments of the invention, one or more examples of which are illustrated in the accompanying drawings. The detailed description uses numerical and letter designations to refer to features in the drawings. Like or similar designations in the drawings and the description have been used to refer to like or similar parts of the invention. As used herein, the terms "first," "second," "third," etc. may be used interchangeably to distinguish one component from another and are not intended to indicate the position or importance of the various components. The terms "upstream" and "downstream" refer to the relative flow direction relative to the flow of a fluid in a fluid path. For example, "upstream" refers to the flow direction from which the fluid is flowing, and "downstream" refers to the flow direction toward which the fluid is flowing. "HP" means high pressure and "LP" means low pressure.

[0020] Additionally, as used herein, the terms "axial" or "axially" refer to a dimension along the longitudinal axis of the engine. The term "front" used in conjunction with "axial" or "axially" refers to a direction toward the engine inlet, or toward a component that is relatively closer to the engine inlet than another component. The terms "rear" or "rearward" used in conjunction with "axial" or "axially" refer to a direction toward the engine nozzle, or toward a component that is relatively closer to the engine nozzle than another component. The terms "radial" or "radially" refer to a dimension extending between the central longitudinal axis (or centerline) of the engine and the outer circumference of the engine. "Radially inward" is toward the longitudinal axis, and "radially outward" is away from the longitudinal axis.

[0021] Exemplary aspects of the present disclosure relate to systems and methods for adjusting blade tip clearance targets by controlling the hinge position of a crossbar link. In one embodiment, a crossbar includes at least one aperture for coupling to one or more thrust links, which may be further coupled to an aircraft wing and / or fuselage. The crossbar also includes a slot defining a hinge point. An actuator including a pivot pin is slidably coupled within the crossbar slot. Movement generated by the actuator adjusts the position of the pivot pin within the crossbar slot, thereby changing the crossbar hinge point. One or more sensors configured to capture real-time flight data generate signals and transmit the signals to an electronic control unit communicatively coupled to the actuator. The electronic control unit is configured to receive flight data from the one or more sensors, implement a machine learning model trained to predict one or more clearance values ​​within an aircraft engine based on the received flight data, utilize the machine learning model to predict one or more clearance values ​​within the aircraft engine based on the received flight data, determine an actuator position based on the one or more clearance values, and adjust the actuator to the determined actuator position.

[0022] Referring now to the drawings, embodiments of the present disclosure relating to aircraft, systems, and methods for optimizing clearances in aircraft engines will be depicted and described in detail.

[0023] Figure 1 An illustrative aircraft system 100 is depicted. Figure 1 In the illustrated embodiment, aircraft system 100 generally includes an aircraft 130, which may include a fuselage 132, wing assemblies 138, and one or more engines 140. Figure 1 The aircraft 130 is depicted as a fixed-wing aircraft having two wing assemblies 138, with one engine 140 mounted on each wing assembly 138 (two engines 140 total), but other configurations are also contemplated. For example, other configurations and / or aircraft may include high-speed compound rotorcraft with supplemental translational thrust systems, dual contra-rotating-coaxial rotor system aircraft, turboprop-tilt-rotor-tilt-wing aircraft, conventional take-off and landing aircraft, and other turbine-driven machines that would also benefit from the present disclosure. Furthermore, other configurations may include more than two wing assemblies 138, more than two engines 140 (e.g., trijet engines, quadjet engines, etc.), engines 140 not mounted to the wing assemblies 138 (e.g., mounted to the fuselage 132, mounted to the tail, mounted to the nose, etc.), non-fixed wings (e.g., rotorcraft), and / or the like.

[0024] Back to Figure 1The depicted aircraft systems are shown, and as shown, controls 160 for controlling the aircraft 130 are included in the cockpit 134 and are operable by a pilot located therein. It should be understood that the term "controls" as used herein is a general term intended to encompass all aircraft control components, particularly those typically found in the cockpit 134.

[0025] A plurality of additional aircraft systems 144 that enable proper operation of aircraft 130, as well as an engine control system 136 and a communication system with an aircraft wireless communication link 166, may also be included in aircraft 130. Additional aircraft systems 144 may generally be any system that affects the control of one or more components of aircraft 130 (e.g., cabin pressure control, elevator control, rudder control, flap control, spoiler control, landing gear control, heat exchanger control, and / or the like). In some embodiments, the avionics of aircraft 130 may be encompassed by one or more additional aircraft systems 144. Aircraft wireless communication link 166 may generally be any air-to-ground communication system now known or later developed. Illustrative examples of aircraft wireless communication link 166 include, but are not limited to, transponders, very high frequency (VHF) communication systems, aircraft communication addressing and reporting systems (ACARS), controller-pilot data link communication (CPDLC) systems, future air navigation systems (FANS), and / or the like. Engine control system 136 may be communicatively coupled to the plurality of aircraft systems 144 and engines 140. In some embodiments, the engine control system 136 may be mounted on one or more engines 140 or within the aircraft 130 and communicatively coupled to the engines 140. Figure 1 The embodiment depicted in FIG. 1 specifically relates to engine control system 136 , but it should be understood that other controllers may also be included within aircraft 130 to control various other aircraft systems 144 not specifically related to engines 140 .

[0026] The engine control system 136 typically includes one or more components for controlling each engine 140, such as a diagnostic computer, an engine-related digital electronic unit installed on one or more engines 140 or aircraft 130, and / or the like. The engine control system 136 may also be referred to as a digital engine control system. Other illustrative components within the engine control system that may work with the engine control system 136 and may require software to operate include, but are not limited to, electronic control units (ECUs) and other controller devices. The software implemented in any of these components may be software distributed between the components and the controllers.

[0027] The engine control system 136 may also be connected to other controllers of the aircraft 130. In an embodiment, the engine control system 136 may include a processor 330 and / or a non-transitory memory component 340 including non-transitory memory. In some embodiments, the non-transitory memory component 340 may include random access memory (RAM), read-only memory (ROM), flash memory, or one or more different types of portable electronic memory, such as a disk, DVD, CD-ROM, etc., or any suitable combination of these types of memory. The processor 330 may execute one or more programmed instructions stored on the non-transitory memory component 340, thereby causing the operation of the engine control system 136. That is, the processor 330 and the non-transitory memory component 340 within the engine control system 136 are operable to perform the various processes described herein with respect to the engine control system 136, including operating various components of the aircraft 130 (e.g., the engine 140 and / or components thereof), monitoring the health of various components of the aircraft 130 (e.g., the engine 140 and / or components thereof), monitoring the operation of the aircraft 130 and / or components thereof, installing software, installing software updates, modifying records in a distributed ledger to indicate that software has been installed and / or updated, executing processes based on the installed and / or updated software, and / or the like.

[0028] In some embodiments, the engine control system 136 may be a full authority digital engine control (FADEC) system. Such a FADEC system may include various electronic components, one or more sensors, and / or one or more actuators that control each engine 140. In some embodiments, the FADEC system includes an electronic control unit (ECU), as well as one or more additional components configured to control various aspects of the performance of the engine 140. The FADEC system typically has full authority over the operating parameters of the engine 140 and cannot be manually overridden. The FADEC system typically functions by receiving multiple input variables of the current flight conditions, including but not limited to air density, throttle lever position, engine temperature, engine pressure, and / or the like. These inputs are received, analyzed, and used to determine operating parameters, such as, but not limited to, fuel flow, stator vane position, bleed valve position, and / or the like. The FADEC system may also control the start or restart of the engine 140. The operating parameters of the FADEC may be modified by installing and / or updating software (e.g., software distributed by the aircraft system 100 described herein). Thus, the FADEC may be programmed to determine engine limitations, receive engine health reports, receive engine maintenance reports, and / or the like, to take certain measures and / or actions under certain conditions.

[0029] The software executed by the engine control system 136 (e.g., executed by the processor 330 and stored in the non-transitory memory component 340) may include a computer program product that includes a machine-readable medium for carrying or having machine-executable instructions or data structures. Such machine-readable media can be any available medium that can be accessed by a general-purpose or special-purpose computer or other machine having a processor. Generally, such computer programs may include routines, programs, objects, components, data structures, algorithms, and / or the like that have the technical effect of performing specific tasks or achieving specific abstract data types. Machine-executable instructions, associated data structures, and programs represent examples of program code for performing the information exchanges disclosed herein. Machine-executable instructions may include, for example, instructions and data that cause a general-purpose computer, a special-purpose computer, or a special-purpose processing machine to perform certain functions or groups of functions. In some embodiments, the computer program product may be provided by a component external to the engine control system 136 and installed for use by the engine control system 136. For example, the computer program product may be provided by the ground support equipment 170, as described in more detail herein. The computer program product can generally be updated via software updates received from one or more components of the aircraft system 100 (e.g., ground support equipment 170), as described in greater detail herein. The software is generally updated by the engine control system 136 by installing the update such that the update supplements and / or overwrites one or more portions of the existing program code of the computer program product. The software update can allow the computer program product to more accurately diagnose and / or predict failures, provide additional functionality not initially provided, and / or the like.

[0030] In an embodiment, each engine 140 may include a fan 142 and one or more sensors for sensing various characteristics of the fan 142 during operation of the engine 140. Illustrative examples of the one or more sensors include, but are not limited to, a fan speed sensor 152, a temperature sensor 154, a pressure sensor 156, a crosswind sensor 158, and / or other aircraft or flight sensors. The fan speed sensor 152 is generally a sensor that measures the rotational speed of the fan 142 within the engine 140. The temperature sensor 154 may be a sensor that measures the temperature of a fluid within the engine 140 (e.g., engine air temperature), the temperature of a fluid (e.g., air) at an engine intake, the temperature of a fluid (e.g., air) within a compressor, the temperature of a fluid (e.g., air) within a turbine, the temperature of a fluid (e.g., air) within a combustion chamber, the temperature of a fluid (e.g., air) at an engine exhaust, the temperature of a cooling fluid and / or a heating fluid used in a heat exchanger in or around the engine, and / or the like. Pressure sensors 156 may be sensors that measure fluid pressure (e.g., air pressure) at various locations in and / or around engine 140, such as fluid pressure (e.g., air pressure) at the engine intake, fluid pressure (e.g., air pressure) within the compressor, fluid pressure (e.g., air pressure) within the turbine, fluid pressure (e.g., air pressure) within the combustion chamber, fluid pressure (e.g., air pressure) at the engine exhaust, and / or the like. Crosswind sensors 158 may be one or more sensors that measure and / or facilitate calculation of crosswind as the aircraft traverses the flight path.

[0031] In some embodiments, each engine 140 may have multiple sensors associated therewith (including one or more fan speed sensors 152, one or more temperature sensors 154, one or more pressure sensors 156, and / or one or more crosswind sensors 158). That is, more than one sensor of the same type may be used to sense characteristics of an engine 140 (e.g., a sensor for each of different areas of the same engine 140). In some embodiments, one or more sensors may be used to sense characteristics of more than one engine 140 (e.g., a single sensor may be used to sense characteristics of two engines 140). In some embodiments, an engine 140 may also include additional components not specifically described herein, and may include one or more additional sensors in conjunction with such additional components or configured to sense such additional components.

[0032] In an embodiment, each sensor (including but not limited to fan speed sensor 152, temperature sensor 154, pressure sensor 156, crosswind sensor 158, and / or other sensors) may be communicatively coupled to one or more components of aircraft 130 such that signals and / or data related to one or more sensed characteristics are transmitted from the sensor for the purpose of determining, detecting, and / or predicting faults, as well as performing one or more other actions based on software requiring the sensor information. Figure 1 As indicated by the dashed lines extending between various sensors (e.g., fan speed sensor 152, temperature sensor 154, pressure sensor 156, crosswind sensor 158, and / or other sensors) and aircraft systems 144 and engine control system 136 in the illustrated embodiment, in some embodiments, the various sensors may be communicatively coupled to aircraft systems 144 and / or engine control system 136. Thus, the various sensors may be coupled to aircraft systems 144 and / or engine control system 136 via wired or wireless communications to transmit signals and / or data to aircraft systems 144 and / or engine control system 136 via an aircraft bus.

[0033] An aircraft bus enables an aircraft and / or one or more components of an aircraft to interface with one or more external systems via wireless or wired means. As used herein, an aircraft bus can be formed from any medium configured to transmit signals. As non-limiting examples, an aircraft bus can be formed from wires, conductive traces, optical waveguides, and the like. An aircraft bus can also refer to a range of electromagnetic radiation and its corresponding electromagnetic waves that propagate therein. Furthermore, an aircraft bus can be formed from a combination of media configured to transmit signals. In one embodiment, an aircraft bus includes a combination of conductive traces, wires, connectors, and buses that cooperate to allow electrical data signals to be transmitted to and from various components of the engine control system 136. Additionally, it should be noted that the term "signal" refers to a waveform (e.g., electrical, optical, magnetic, mechanical, or electromagnetic) configured to propagate through a medium (e.g., DC, AC, a sine wave, a triangle wave, a square wave, a vibration, and the like).

[0034] For example, the interconnectivity of components coupled via a network may include a wide area network (e.g., the Internet), a local area network (LAN), a mobile communication network, a public service telephone network (PSTN), and / or other networks, and may be configured to electronically connect components. Illustrative components that may be connected via a network include, but are not limited to, ground systems 120 communicating with aircraft 130 (e.g., via ground wireless communication link 122 and aircraft wireless communication link 166), and / or ground support equipment 170 via a wired or wireless system.

[0035] It should be understood that aircraft 130 represents only one illustrative embodiment, which may be configured to implement an embodiment or portion of an embodiment of the apparatus, systems, and methods described herein. During operation, as a non-limiting example, control mechanism 160 may be used to operate one or more of aircraft systems 144. Various sensors, including but not limited to fan speed sensor 152, temperature sensor 154, pressure sensor 156, and / or crosswind sensor 158, may output data related to various characteristics of engine 140 and / or other aircraft systems 144. Engine control system 136 may utilize input from control mechanism 160, fan speed sensor 152, temperature sensor 154, pressure sensor 156, crosswind sensor 158, various aircraft systems 144, one or more databases, and / or information from airline control, flight operations, etc., to diagnose, detect, and / or predict faults that may be unknown to airline maintenance personnel. Among other things, the engine control system 136 may analyze data output by various sensors (e.g., fan speed sensor 152, temperature sensor 154, pressure sensor 156, crosswind sensor 158, etc.) over a period of time to determine the timing of drifts, trends, steps, or spikes in the operation of the engine 140 and / or various other aircraft systems 144. The engine control system 136 may also analyze system data to determine historical pressures, historical temperatures, pressure differentials between multiple engines 140 on the aircraft 130, temperature differentials between multiple engines 140 on the aircraft 130, and / or the like, and based thereon diagnose, detect, and / or predict faults in the engine 140 and / or various other aircraft systems 144. The aircraft wireless communication link 166 and the ground wireless communication link 122 may transmit data so that data and / or information related to the fault may be transmitted from the aircraft 130.

[0036] Although Figure 1 The embodiments described herein relate specifically to components within aircraft 130, but the present disclosure is not limited thereto. That is, the various components depicted with respect to aircraft 130 may be incorporated into various other types of aircraft and may function in a similar manner to deliver and install new and / or updated software to engine control system 136 as described herein. For example, the various components described herein with respect to aircraft 130 may be present in a watercraft, spacecraft, and / or the like without departing from the scope of the present disclosure.

[0037] Furthermore, it should be understood that although particular aircraft have been illustrated and described, other configurations and / or aircraft, such as high-speed compound rotor aircraft with supplemental translational thrust systems, dual contra-rotating-coaxial rotor system aircraft, turboprop-tilt-rotor-tilt-wing aircraft, conventional take-off and landing aircraft, and other turbine-driven machines will also benefit from the present disclosure.

[0038] Still refer to Figure 1 , the ground system 120 is typically a transmission system located on the ground that is capable of transmitting signals to and / or receiving signals from the aircraft 130. That is, the ground system 120 may include a ground wireless communication link 122 that is communicatively coupled to the aircraft wireless communication link 166 to wirelessly transmit and / or receive signals and / or data. In some embodiments, the ground system 120 may be an air traffic control (ATC) tower and / or one or more components or systems thereof. Thus, the ground wireless communication link 122 may be a VHF communication system, an ACARS unit, a CPDLC system, a FANS, and / or the like. Using the ground system 120 and the ground wireless communication link 122, Figure 1 The various non-aircraft components depicted in the embodiments of FIG may also be communicatively coupled to the aircraft 130 even while the aircraft 130 is airborne and in flight, thereby allowing for on-demand transfer of software and / or software updates when such software and / or software updates may be needed. However, it should be understood that Figure 1 The embodiment depicted in FIG is merely illustrative. In other embodiments, aircraft 130 may be communicatively coupled to various other components of aircraft system 100 and physically coupled to one of the components of aircraft system 100, such as ground support equipment 170, while on the ground.

[0039] Ground support equipment (GSE) 170 is an external device used to support and test engine control system 136 and / or other components of aircraft systems 100. Ground support equipment 170 is configured to provide software updates to engine control system 136 and download data acquired by engine control system 136 during flight. As another non-limiting example, GSE 170 may include production support equipment for limited data monitoring, test support equipment for comprehensive data monitoring and changing adjustable parameters, and an integrated test bench for system and software testing. In an embodiment, GSE 170 may be connected to engine control system 136 via a wired local area network or Ethernet. GSE 170 may communicate with engine control system 136 using an Ethernet protocol. GSE 170 may be a portable maintenance access terminal. GSE 170 may test the trajectory mode of the aircraft by directly communicating with ECU 200 of engine control system 136, as will be described in more detail herein.

[0040] Now refer to Figure 2A , depicts an illustrative cross-section of an aircraft engine 140 coupled to an aircraft wing 138. For the sake of brevity, repeated descriptions of similar elements employed in other embodiments described herein are omitted. Aircraft engine 140 includes an inlet 202, a fan 142, a compressor 206, a combustor 208, a turbine 210, and a nozzle 212.

[0041] During operation, a volume of air is drawn in through the inlet 202 of the fan section. The inlet 202 can continuously draw air into the aircraft engine 140 through the inlet 202 and ensure smooth airflow into the aircraft engine 140. As the volume of air passes through the fan 142, a first portion of the air can be directed or routed to a bypass airflow passage located outside the compressor 206. A second portion of the air is directed or routed to the compressor 206. The pressure of the second portion of air is then increased as it is directed from the low-pressure section of the compressor 206, through the high-pressure section of the compressor 206, and into the combustor 208. The fan 142 and the compressor 206 are composed of rotating blades and stationary vanes. The compressor 206 has a rotor including rotating blades having rotor blade tips 216 separated by a predetermined cold clearance from a stator 226. The stator 226 may include a casing, stationary vanes, a shroud, and / or the like. In a static, non-operating mode, rotating components such as fan 142 , compressor 206 , combustor 208 , and turbine 210 , as well as the stator, may be positioned and centered along shaft assembly 209 and centerline “C.” The pressure and temperature of the air increases as it moves through compressor 206 .

[0042] Combustor 208 can continuously add fuel to the compressed air and combust it. The combustion gases produced in combustor 208 are directed from combustor 208 along a hot gas path through turbine 210. In turbine 210, a portion of the thermal and / or kinetic energy from the combustion gases is extracted through sequential stages of turbine stator blades coupled to outer casing 226 and turbine rotor blades 211 coupled to shaft assembly 209, thereby rotating shaft assembly 209 and supporting the operation of compressor 206, combustor 208, and turbine 210. Some of this energy can also be used to drive compressor 206. Cooling air or coolant from compressor 206 can be used to cool the turbine blades of turbine 210. Exhaust gases from turbine 210 pass through nozzle 212 to produce a high-speed jet. For example, the combustion gases are then directed through a jet exhaust nozzle 212 of the turbine engine to provide propulsive thrust.

[0043] As described in greater detail below, during operation, internal and external forces, such as asymmetric thermal and mechanical loads, including, for example, but not limited to, air torque, gyroscopes, thermal bonding, inlet aerodynamics, crosswind, inertial loads, and the like, cause lateral relative motion between the rotor blade tips 216 and the stator flow path (e.g., through the stationary vanes of the stator 226). For example, lateral motion, as depicted by arrow 230, causes the clearance between the rotor blade tips 216 and the stator 226 to change. Therefore, aircraft engines 140 are designed with margins, referred to herein as cold clearances, to compensate for lateral motion that would otherwise result in undesirable contact, i.e., friction, between the rotor blade tips 216 and the stator 226, as well as other portions of the aircraft engine 140. These cold clearances can be reduced by implementing the systems and methods described herein. Specifically, the systems and methods described herein provide a means for actively optimizing clearances within an aircraft engine 140 by adjusting the hinge points of the crossbars, such that the clearance between the rotor and stator in the horizontal direction of the aircraft engine 140 is continuously adjusted to better center the rotor and stator.

[0044] By implementing the actively adjustable crossbar and the control logic for controlling it described herein, the required cold clearance of the design can be reduced, thus minimizing the clearance, thereby reducing SFC and improving efficiency. Figure 2B , depicting Figure 1 and Figure 2A An illustrative example of an aircraft engine 140 coupled to a wing of an aircraft including a thrust link crossbar for adjusting the alignment of a shaft centerline of the aircraft engine 140 is shown in FIG. , according to one or more embodiments. Figure 2BThe embodiment depicted in FIG2 depicts an aircraft engine 140 mounted on a wing 138 of an aircraft. However, other embodiments may include an aircraft engine 140 mounted to the fuselage, tail, or nose of the aircraft. Regardless of the embodiment, the aircraft engine 140 can be mounted via one or more thrust links 260, 262 that are connected to the aircraft (e.g., wing 138) at one end and to a hole 251 of a crossbar 250 at an opposite end. The crossbar 250 further includes a slot 252 configured to receive a pivot pin 253 that is controllably positioned within the slot 252 by an actuator 254. The actuator 254 can be coupled to the aircraft engine 140 such that extending and retracting the actuator 254 adjusts the position of the pivot pin 253 within the slot 252. Changing the position of the pivot pin 253 within the slot 252 adjusts the hinge point of the crossbar 250. Furthermore, changing the hinge point of the crossbar 250 changes the force distribution along each of the thrust links 260, 262, which in turn increases or decreases the amount of torque M (e.g., the direction of the torque is depicted by arrow 230). The first thrust link 260 is attached to the wing at a predetermined distance "D" from the second thrust link 262, which is attached to the same wing. The holes 251 of the crossbar have a predetermined spacing from each other that defines the length "L" of the opposite ends to which the thrust links 260, 262 are attached. Furthermore, when the pivot pin 253 is moved, the pivot pin 253 is displaced a distance "δ" from the centerline "C" by extension or retraction of the actuator 254. Thus, the thrust along the first thrust link 260 can be represented by the following equation: And the thrust along the second thrust link 262 can be similarly expressed by the following equation: “Thrust” is the amount of thrust produced by aircraft engine 140. Torque (e.g., depicted by arrow 230) may be determined by the following equation: In some embodiments, when When the rotor (e.g., shaft 209) is adjusted to a predetermined position, the rotor (e.g., shaft 209) may generate an offset of approximately 3-5 mils, approximately 3 mils, approximately 4 mils, or approximately 5 mils. For example, adjusting the actuator to a certain actuator position may cause the pivot pin to be displaced from the centerline "C" by approximately 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 11%, 12%, 13%, 14%, or 15% of the length "L" between the holes in the crossbar. However, this is merely an example, as a greater or lesser offset of the rotor may be achieved by configuring the spacing "L" between the holes 251 in the crossbar to be smaller or larger, the distance "D" between the thrust links 260, 262 attached to the wing 138, and dynamically changing the displacement "δ" of the pivot pin 253 from the centerline "C."

[0045] It should now be understood how adjusting the pivot pin 253 changes the hinge point of the crossbar 250 and affects the torque "M" and clearance within the aircraft engine 140. Figure 3-4 How to determine and control the amount of displacement “δ” of the pivot pin 253 from the centerline “C” to dynamically adjust clearances within the aircraft engine 140 during operation of the engine aircraft 140 (e.g., during flight) to better center the rotor (e.g., shaft 209) and stator 226 will be depicted and described.

[0046] refer to Figure 3 , depicts a functional block diagram of an engine control system 136 including an electronic control unit 300 for optimizing clearances within an aircraft engine 140 according to one or more embodiments. The engine control system 136 receives various inputs, including signals generated by one or more sensors 350 on the aircraft. The sensor inputs may include signals from a fan speed sensor 152 of the aircraft engine 140, a temperature sensor 154 within the aircraft engine 140, and those sensors configured to sample the external environment of the aircraft, a pressure sensor 156, a crosswind sensor 158, and other aircraft sensors. Some of the other aircraft sensors may include sensors capable of determining angle of attack, engine thrust, winding torque, inertia, angular rate, angular velocity, etc. Selected ones of the sensor signals may be fed to a centerline offset model 400, which will be referenced. Figure 4 Described in more detail, to predict real-time clearances within the aircraft engine under sensed operating conditions, which are ultimately used to determine an actuator position corresponding to an amount of displacement “δ” of the pivot pin 253 from the centerline “C”, which actuator position transmits an offset to the shaft 209 and / or stator 226, thereby improving the clearance between the rotor blade tip 216 and the stator 226 to improve SFC and prevent friction therebetween.

[0047] According to the embodiment shown and described herein, the engine control system 136 includes an electronic control unit 300 that can utilize hardware, software, and / or firmware to optimize clearances within an aircraft engine. While in some embodiments, the electronic control unit 300 can be configured as a general-purpose computer with the necessary hardware, software, and / or firmware, in some embodiments, the electronic control unit 300 can be configured as a dedicated computer specifically designed to perform the functions described herein.

[0048] Also like Figure 3As shown, the electronic control unit 300 may include a processor 330, input / output hardware 332, network interface hardware 334, a data storage component 336 (which stores simulated flight data 338a, real-time flight data 338b, actuator positions 338c, and gap values ​​338d), and a memory component 340. The memory component 340 may be a machine-readable memory (which may also be referred to as a non-transitory processor-readable memory). The memory component 340 may be configured as volatile and / or non-volatile memory, and thus may include random access memory (including SRAM, DRAM, and / or other types of random access memory), flash memory, registers, compact disks (CDs), digital versatile disks (DVDs), and / or other types of storage components. In addition, the memory component 240 may be configured to store operating logic 242, as well as logic for implementing the centerline offset model 400 and actuator position logic 440 (each of which may be implemented as a computer program, firmware, or hardware, as examples). The local interface 346 may also be included in the local interface 346. Figure 3 and may be implemented as a bus or other interface to facilitate communication among the components of the electronic control unit 300 .

[0049] The processor 330 may include any processing component configured to receive and execute programmed instructions (e.g., from the data storage component 336 and / or the memory component 340). The instructions may be in the form of a machine-readable instruction set stored in the data storage component 336 and / or the memory component 340. The input / output hardware 332 may include a monitor, keyboard, mouse, printer, camera, microphone, speaker, and / or other device for receiving, sending, and / or presenting data. The network interface hardware 334 may include any wired or wireless network hardware, such as a modem, a LAN port, a Wi-Fi card, a WiMax card, mobile communication hardware, and / or other hardware for communicating with other networks and / or devices.

[0050] It should be understood that the data storage component 336 may reside locally on the electronic control unit 300 and / or remotely from the electronic control unit 300 and may be configured to store one or more pieces of data for access by the electronic control unit 300 and / or other components. Figure 3As shown, data storage component 336 stores simulated flight data 338a. Simulated flight data 338a may include simulated data of the aircraft engine under various operating conditions and flight path parameters. Simulated flight data 338a may also include flight data, sensor readings, and measured clearance values ​​from previous flights. Simulated flight data 338a may be used to train centerline offset model 400, a machine learning model, such as a neural network configured to predict clearances within aircraft engine 140. Data storage component 336 may also include real-time flight data 338b, which may include data obtained via signals received from one or more sensors 350 or predefined flight parameters that may affect the operation of aircraft engine 140. While in some embodiments, signals received from one or more sensors 350 may be fed directly to centerline offset model 400, embodiments may also record real-time flight data for future use by engine control system 136 or for validation during the training process of centerline offset model 400.

[0051] Data storage component 336 may also include actuator positions 338c. Actuator positions 338c may be a set of preset values ​​that define the operating range of actuator 254 based on the implementation of actuator 254, crossbar 250, and aircraft engine 140. In other words, these may be calibration values ​​that define the relationship between the extended and retracted positions of the actuator arm relative to the position of pivot pin 253 within slot 252 of crossbar 250. For example, the actuator arm extension distance "X" may correspond to the displacement position "δ" of pivot pin 253 within slot 252 of crossbar 250 away from centerline "C." In other words, the position of pivot pin 253 within slot 252 of crossbar 250 defines the hinge point of crossbar 250.

[0052] The data storage component 336 may also include a clearance value 338d. The clearance value 338d includes a predicted value generated by the centerline offset model 400 during operation. The clearance value 338d can be defined as the amount and direction of lateral movement of the shaft 209 relative to the centerline "C" of the aircraft engine. The clearance value 338d predicted by the centerline offset model 400 can be used by the actuator position logic 440. Based on the predicted current clearance value 338d of the shaft 209 of the aircraft engine, the actuator position logic 440 determines the position where the pivot pin 253 should be positioned to adjust the shaft 209 to compensate for (i.e., overcome or counteract) a torque "M" that would cause the shaft 209 to deviate from the centerline "C" by more than an acceptable amount. In other words, if the operating conditions of the aircraft engine 140 would cause the clearance within the engine to decrease below an acceptable predetermined value (e.g., less than 8 mils), the actuator 254 can reposition the pivot pin 253 so that lateral movement of the shaft 209 can maintain the clearance within an acceptable range for the aircraft engine 140 (e.g., greater than or equal to 8 mils).

[0053] Included in the memory component 340 is operating logic 342, as well as logic for implementing the centerline offset model 400 and the actuator position logic 440. The operating logic 342 may include an operating system and / or other software for managing the components of the electronic control unit 300. Figure 4 The centerline offset model 400 is described in more detail. As described above, the actuator position logic 440 includes logic for determining the position of the pivot pin 253 based on the predicted current lash value 338d that accounts for (i.e., overcomes or counteracts) a torque "M" that would cause the shaft 209 to deviate from the centerline "C" by more than an acceptable amount.

[0054] The system implements a machine learning model trained to predict one or more clearance values ​​within an aircraft engine based on received flight data. As used herein, the term "machine learning model" refers to one or more mathematical models configured to find patterns in data and apply the identified patterns to new data sets to form predictions. Depending on the nature of the problem being solved and the type and volume of data, different approaches, also known as categories of machine learning, are implemented. Categories of machine learning models include, for example, supervised learning, unsupervised learning, reinforcement learning, deep learning, or combinations thereof.

[0055] Supervised learning utilizes a target or outcome variable, such as a dependent variable, also known as an independent variable, to be predicted from a given set of predictors. This set of variables is used to generate a function that maps labeled inputs to desired outputs. The training process is iterative and continues until the model achieves the desired level of accuracy on the training data. Machine learning models categorized as supervised learning algorithms and models include, for example, neural networks, regression, decision trees, random forests, k-nearest neighbors (kNN), logistic regression, and many others.

[0056] Unlike supervised learning, unsupervised learning is a learning algorithm that doesn't use labeled data, allowing it to determine structure from the input. In other words, the goal of unsupervised learning is to find hidden patterns in the data through methods such as clustering. Some examples of unsupervised learning include the Apriori algorithm or K-means. Reinforcement learning refers to machine learning models that are trained to make specific decisions. Machine learning models are exposed to an environment where they are continuously trained using trial and error. Such models learn from past experience and attempt to acquire the best possible knowledge to make accurate business decisions. Examples of reinforcement learning include Markov decision processes.

[0057] Deep learning is a machine learning method that combines neural networks in successive layers to iteratively learn from data. Deep learning can learn patterns from unstructured data. Deep learning algorithms repeatedly perform a task, gradually improving the results through deeper layers that support progressive learning. Deep learning can include aspects of supervised or unsupervised learning. Some deep learning machine learning models include artificial neural networks (ANNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory / gated recurrent units (GRUs), self-organizing maps (SOMs), autoencoders (AEs), and restricted Boltzmann machines (RBMs).

[0058] A machine learning model is understood to mean any kind of mathematical model with at least one nonlinear operation (e.g., a nonlinear activation layer in the case of a neural network). A machine learning model is trained or optimized by minimizing one or more loss functions that are separate from the model itself (e.g., minimizing the cross entropy loss or the negative log likelihood). The training or optimization process aims to optimize the model to reproduce known results (low bias) and enable the model to make accurate predictions from unseen experiences (low variance). The output of the model can be various things related to the task, such as predicted values, classifications, sequences, etc. In this embodiment, the output can be a gap value and / or a confidence level associated with the predicted gap value.

[0059] Now refer to Figure 4, depicts an illustrative system diagram for controlling the pivot position of a variable thrust link crossbar to optimize clearances within an aircraft engine, according to one or more embodiments. Figure 4 The illustrative system depicted in shows an embodiment in which the implemented machine learning model is a neural network model. However, it should be understood that utilization of a neural network model is merely one example of a machine learning model that is trained to predict one or more clearance values ​​within an aircraft engine based on received flight data. The system includes implementing a neural network model, referred to herein as a centerline offset model 400, to predict a clearance value 338d within an aircraft engine under current operating conditions, such as real-time flight data 338b that includes signals from one or more sensors 350 of the aircraft. Actuator position logic 440 utilizes the predicted clearance value 338d that would be produced under the current operating conditions to determine a pivot pin 253 position that would offset all or a portion of the predicted clearance value 338d (i.e., an axis offset) that would result in less than optimal alignment between the rotor blade tip 216 and the stator 226. In other words, the actuator position logic 440 determines a pivot pin 253 position that optimizes the alignment of the rotor blade tip 216 and the stator 226 such that they are aligned in the horizontal direction (Y axis, Figure 2A and 2B ) to better center it.

[0060] In training mode, simulated flight data 338a is used to provide operating conditions and simulated sensor readings to centerline offset model 400. Centerline offset model 400 can be trained using supervised or unsupervised methods, optionally using a feedback loop to adjust the weights of the nodes of centerline offset model 400 to achieve accurate predictions of gap values ​​338d under actual operating conditions.

[0061] The centerline deviation model 400 (e.g., a neural network) can include one or more layers 405, 410, 415, 420 having one or more nodes 401 connected by node connections 402. The one or more layers 405, 410, 415, 420 can include an input layer 405, one or more hidden layers 410, 415, and an output layer 420. The centerline deviation model 400 can be a deep neural network, a convolutional neural network, or another type of neural network. The centerline deviation model 400 can include one or more convolutional layers and one or more fully connected layers. The input layer 405 represents the raw information fed into the neural network 400. For example, real-time flight data 338b, including signals from one or more sensors 350, can be input into the centerline deviation model 400 at the input layer 405.

[0062] Real-time flight data 338b processes raw information received at input layer 405 via nodes 401 and node connections 402. Real-time flight data 338b can be highly nonlinear and interdependent on flight maneuvering conditions. Therefore, a machine learning model can systematically ingest nonlinear data and identify patterns that can be used to predict one or more clearance values ​​within an aircraft engine based on received flight data 338b. For example, one or more hidden layers 410, 415 perform computational activities based on input from input layer 405 and weights on node connections 402. In other words, hidden layers 410, 415 perform computations and transmit information from input layer 405 to output layer 420 via their associated nodes 401 and node connections 402.

[0063] Generally, when the centerline shift model 400 is learning, the centerline shift model 400 is identifying and determining patterns within the raw information received at the input layer 405. In response, one or more parameters, such as weights associated with the node connections 402 between nodes 401, can be adjusted through a process called backpropagation. It should be understood that there are many different processes by which learning can occur, but two general learning processes include association mapping and regularity detection. Association mapping refers to the learning process by which the centerline shift model 400 learns to produce a specific pattern on the input set whenever another specific pattern is applied to the input set. Regularity detection refers to the learning process by which the neural network learns to respond to specific properties of the input pattern. In association mapping, the neural network stores the relationships between patterns, while in regularity detection, the response of each unit has a specific "meaning." This type of learning mechanism can be used for feature discovery and knowledge representation.

[0064] Neural networks learn through forward and backward propagation to update weights and biases to fit the training data. This information is stored in the neural network's weight matrix, W. Learning is accomplished by optimizing the weights. Based on how learning is performed, two major categories of neural networks can be distinguished: 1) fixed networks, where weights cannot be changed (i.e., dW / dt = 0), and 2) adaptive networks, where weights can be changed (i.e., dW / dt does not = 0). In fixed networks, the weights are fixed a priori based on the problem being solved.

[0065] To train the centerline shift model 400 to perform a task, the weights are adjusted in a way that reduces the error between the desired output and the actual output. This process may require the centerline shift model 400 to calculate the error derivative (EW) of the weights. In other words, it must calculate how the error changes with each slight increase or decrease in the weight. The backpropagation algorithm is one method used to determine the EW.

[0066] The algorithm calculates each EW by first calculating the error derivative (EA), the rate at which the error changes as the activity level of the unit changes. For an output unit, the EA is simply the difference between the actual output and the expected output. To calculate the EA of a hidden unit in the layer before the output layer, all the weights between the hidden unit and the output units to which it is connected are first identified. These weights are then multiplied by the EAs of these output units, and these products are added together. This sum equals the EA of the selected hidden unit. After calculating all the EAs in the hidden layers before the output layer, the EAs of the other layers can be calculated in a similar manner, moving from layer to layer in the opposite direction to how the activity propagates through the centerline shift model 400, thus "back propagating". Once the EA has been calculated for a unit, the EW of each incoming connection of that unit can be calculated directly. The EW is the product of the EA and the activity through the incoming connections. It should be understood that this is just one way to train the centerline shift model 400 to perform a task.

[0067] Still refer to Figure 4 , the centerline offset model 400 may include one or more hidden layers 410, 415 that feed into one or more nodes 401 of an output layer 420. There may be one or more output layers 420 depending on the specific outputs generated by configuring the centerline offset model 400. In this embodiment, the outputs may include predicted clearance values ​​338d related to the amount of horizontal or lateral movement of a component within the aircraft engine 140 relative to the centerline "C."

[0068] As described above, the predicted clearance value 338d is then used by the actuator position logic 440 to determine the actuator position 338c that optimizes the hinge position of the crossbar 250 to provide optimized stator and rotor clearance.

[0069] The functional blocks and / or flow chart elements described herein can be translated into machine-readable instructions. As non-limiting examples, the machine-readable instructions can be written using any programming protocol, such as: descriptive text to be parsed (e.g., Hypertext Markup Language, Extensible Markup Language, etc.), (ii) assembly language, (iii) object code generated by a compiler from source code, (iv) source code written using the syntax of any suitable programming language for execution by an interpreter, (v) source code for compilation and execution by a just-in-time compiler, and the like. Alternatively, the machine-readable instructions can be written in a hardware description language (HDL), such as logic implemented by a field programmable gate array (FPGA) configuration or an application-specific integrated circuit (ASIC) or their equivalents. Therefore, the functions described herein can be implemented in any conventional computer programming language, as pre-programmed hardware elements, or as a combination of hardware and software components.

[0070] Figure 5A graph illustrating the reduction of clearance by optimizing the centering of the stator and rotor in the horizontal (lateral) direction according to one or more embodiments described herein is depicted. The graph depicts predicted clearance values ​​using short dashed lines. Optimal clearance is represented by long dashed lines. In operation, the centerline offset model 400 will predict the predicted clearance value, and the actuator position logic 440 will determine the adjustment and new position of the pivot pin 253 within the slot 252 of the crossbar 250 to adjust the predicted real-time clearance value to better center the optimal clearance, at least in the horizontal direction.

[0071] Now refer to Figure 6 , depicts a graph illustrating clearance reduction for multiple stages of a high pressure compressor of an aircraft engine according to one or more embodiments. It should be understood that while the present disclosure describes systems and methods with reference to optimizing alignment and better centering clearances within a compressor 206 portion of an aircraft engine 140, the same systems and methods can be applied to optimizing clearances within a fan 142, a combustor 208, a turbine 210, or other sections of an aircraft engine 140. Furthermore, it is known that a compressor 206 can include multiple stages and each stage includes blades having rotor blade tips 216 that are clear of a stator 226 (e.g., a stationary vane). Figure 6 The graph depicted in depicts the resulting clearances per stage when dynamic control of the crossbar 250 is implemented within the aircraft engine 140 as depicted and described herein. That is, by implementing dynamic control of the crossbar 250, cold clearances can be reduced from a "baseline" value to improve SFC and engine efficiency because the engine operates with less open clearances.

[0072] It should now be understood that the present disclosure relates to systems and methods for adjusting blade tip clearance targets by controlling the hinge position of a crossbar link. In one embodiment, a crossbar having at least one aperture is coupled to one or more thrust links, which may be further coupled to an aircraft wing and / or fuselage. The crossbar also includes a slot defining a hinge point. An actuator including a pivot pin is slidably coupled within the crossbar slot. Movement generated by the actuator adjusts the position of the pivot pin within the crossbar slot, thereby changing the crossbar hinge point. One or more sensors configured to capture real-time flight data generate signals and transmit the signals to an electronic control unit communicatively coupled to the actuator. The electronic control unit is configured to receive flight data from the one or more sensors, implement a machine learning model trained to predict one or more clearance values ​​within an aircraft engine based on the received flight data, utilize the machine learning model to predict one or more clearance values ​​within the aircraft engine based on the received flight data, determine an actuator position based on the one or more clearance values, and cause the actuator to adjust to the determined actuator position.

[0073] It will be apparent to those skilled in the art that various modifications and variations can be made without departing from the spirit or scope of the present disclosure. Since modifications, combinations, sub-combinations and variations of the disclosed embodiments that incorporate the spirit and substance of the present disclosure may occur to those skilled in the art, the present disclosure should be construed as including all within the scope of the appended claims and their equivalents.

[0074] Further aspects of the invention are provided by the subject matter of the following clauses:

[0075] A system for optimizing clearances within an aircraft engine includes: an adjustable coupling configured to couple a thrust link to the aircraft engine; an actuator coupled to the adjustable coupling, wherein movement generated by the actuator adjusts a hinge point of the adjustable coupling; one or more sensors configured to capture real-time flight data; and an electronic control unit communicatively coupled to the actuator and the one or more sensors. The electronic control unit is configured to: receive the flight data from the one or more sensors, implement a machine learning model trained to predict one or more clearance values ​​within the aircraft engine based on the received flight data, predict the one or more clearance values ​​within the aircraft engine based on the received flight data using the machine learning model, determine an actuator position based on the one or more clearance values, and cause the actuator to adjust to the determined actuator position.

[0076] A system as in any preceding clause, wherein one or more clearance values ​​within the aircraft engine define lateral movement of the shaft relative to a centerline of the aircraft engine.

[0077] System according to any of the preceding clauses, wherein the electronic control unit is configured to generate and transmit a control signal to the actuator to adjust the actuator to the determined actuator position.

[0078] A system according to any of the preceding clauses, wherein the adjustable connector includes at least one hole for connecting to the thrust link and a slot defining a hinge point of the adjustable connector, and adjusting the actuator to a determined actuator position causes the pivot pin slidably connected in the slot to shift from the center line "C" by approximately 10% of the length "L" between the holes of the adjustable connector.

[0079] A system as in any preceding clause, wherein adjusting the actuator to a determined actuator position displaces the pivot pin from the centerline "C" by approximately 5% of the length "L" between the apertures of the adjustable coupler.

[0080] The system of any preceding clause, wherein the one or more sensors include at least one of a fan speed sensor, a temperature sensor, a pressure sensor, or a crosswind sensor.

[0081] The system of any of the preceding clauses, wherein adjusting the actuator to the determined actuator position improves one or more gap values ​​by 3 to 5 mils.

[0082] A method for optimizing clearances within an aircraft engine includes: receiving, with an electronic control unit, flight data from one or more sensors; implementing, with the electronic control unit, a machine learning model trained to predict one or more clearance values ​​within the aircraft engine based on the flight data; predicting, with the machine learning model, the one or more clearance values ​​within the aircraft engine based on the flight data; determining, with the electronic control unit, an actuator position based on the one or more clearance values; and adjusting, with the electronic control unit, an actuator to the determined actuator position.

[0083] A method as in any preceding clause, wherein the actuator adjusts the position of the pivot pin within the slot of the adjustable coupling, thereby changing the hinge point of the adjustable coupling.

[0084] The method of any of the preceding clauses, further comprising generating, with the electronic control unit, a control signal for adjusting the actuator to the determined actuator position.

[0085] A method according to any of the preceding clauses, wherein adjusting the actuator to a determined actuator position displaces a pivot pin slidably coupled within the slot from a centre line "C" by approximately 10% of a length "L" between the apertures of the adjustable coupler.

[0086] A method as in any preceding clause, wherein adjusting the actuator to the determined actuator position displaces the pivot pin from the centerline "C" by approximately 5% of the length "L" between the apertures of the adjustable coupler.

[0087] A method as in any preceding clause, wherein the one or more sensors include at least one of a fan speed sensor, a temperature sensor, a pressure sensor, or a crosswind sensor.

[0088] The method of any of the preceding clauses, wherein adjusting the actuator to the determined actuator position improves one or more gap values ​​by 3 to 5 mils.

[0089] An aircraft includes an aircraft engine coupled to a wing using at least one thrust link and an adjustable coupling, wherein the adjustable coupling includes at least one aperture for coupling to the at least one thrust link and a slot defining a hinge point of the adjustable coupling; an actuator including a pivot pin slidably coupled within the slot, wherein movement of the actuator adjusts a position of the pivot pin within the slot, thereby changing the hinge point of the adjustable coupling; one or more sensors configured to capture real-time flight data; and an electronic control unit communicatively coupled to the actuator and the one or more sensors. The electronic control unit is configured to: receive flight data from the one or more sensors, implement a machine learning model trained to predict one or more clearance values ​​within the aircraft engine based on the received flight data, predict the one or more clearance values ​​within the aircraft engine based on the received flight data using the machine learning model, determine an actuator position based on the one or more clearance values, and cause the actuator to adjust to the determined actuator position.

[0090] An aircraft according to any of the preceding clauses, wherein the electronic control unit is configured to generate a control signal and transmit the control signal to the actuator to adjust the actuator to the determined actuator position.

[0091] An aircraft as claimed in any preceding clause, wherein adjusting the actuator to a determined actuator position displaces the pivot pin from the centre line 'C' by approximately 10% of the length 'L' between the apertures of the adjustable coupler.

[0092] An aircraft as claimed in any preceding clause, wherein adjusting the actuator to a determined actuator position displaces the pivot pin from the centre line 'C' by approximately 5% of the length 'L' between the apertures of the adjustable coupler.

[0093] An aircraft as described in any preceding clause, wherein the one or more sensors include at least one of a fan speed sensor, a temperature sensor, a pressure sensor, or a crosswind sensor.

[0094] An aircraft as defined in any preceding clause, wherein adjusting the actuator to the determined actuator position improves one or more gap values ​​by 3 to 5 mils.

Claims

1. A system for optimizing clearances within an aircraft engine, characterized in that include: an adjustable coupler configured to couple a thrust link to the aircraft engine, wherein the adjustable coupler includes at least one aperture for coupling to the thrust link and a slot defining a hinge point of the adjustable coupler; an actuator coupled to the adjustable coupler, wherein movement produced by the actuator adjusts a hinge point of the adjustable coupler; one or more sensors configured to capture real-time flight data; and an electronic control unit communicatively coupled to the actuator and the one or more sensors, wherein the electronic control unit is configured to: receiving flight data from the one or more sensors, implementing a machine learning model trained to predict one or more clearance values ​​within the aircraft engine based on received flight data, predicting, using the machine learning model, the one or more clearance values ​​within the aircraft engine based on received flight data, determining an actuator position based on the one or more clearance values, and The actuator is adjusted to a determined actuator position, wherein adjusting the actuator to the determined actuator position displaces a pivot pin slidably coupled within a slot from a centerline "C" by a length "L" between the holes of the adjustable coupler.

2. The system according to claim 1, wherein: in, The one or more clearance values ​​within the aircraft engine define lateral movement of a shaft relative to a centerline of the aircraft engine.

3. The system according to claim 1, wherein: in, The electronic control unit is configured to generate a control signal and transmit the control signal to the actuator to adjust the actuator to a determined actuator position.

4. The system according to claim 1, wherein: in, Adjusting the actuator to a determined actuator position displaces the pivot pin slidably coupled within the slot from the centerline "C" by approximately 10% of the length "L" between the holes of the adjustable coupler.

5. The system according to claim 4, characterized in that in, Adjusting the actuator to a determined actuator position displaces the pivot pin from centerline "C" by approximately 5% of the length "L" between the holes of the adjustable coupler.

6. The system according to claim 1, wherein: in, The one or more sensors include at least one of a fan speed sensor, a temperature sensor, a pressure sensor, or a crosswind sensor.

7. The system according to claim 1, wherein: in, Adjusting the actuator to a determined actuator position improves the one or more gap values ​​by 3 to 5 mils.

8. A method for optimizing clearances in an aircraft engine, characterized in that include: receiving flight data from one or more sensors using an electronic control unit; implementing, with the electronic control unit, a machine learning model trained to predict one or more clearance values ​​within the aircraft engine based on the flight data; predicting, using the machine learning model, the one or more clearance values ​​within the aircraft engine based on the flight data; determining, with the electronic control unit, an actuator position based on the one or more clearance values; and Using the electronic control unit, the actuator is adjusted to a determined actuator position, wherein the actuator adjusts the position of a pivot pin within a slot of an adjustable coupler, thereby changing a hinge point of the adjustable coupler, and wherein adjusting the actuator to the determined actuator position causes the pivot pin slidably coupled within the slot to be displaced from a centerline "C" by a distance "L" between the holes of the adjustable coupler.

9. The method according to claim 8, characterized in that Further including: With the electronic control unit, a control signal is generated for adjusting the actuator to a determined actuator position.

10. The method according to claim 8, characterized in that in, Adjusting the actuator to a determined actuator position displaces the pivot pin slidably coupled within the slot from the centerline "C" by approximately 10% of the length "L" between the holes of the adjustable coupler.

11. The method according to claim 10, characterized in that in, Adjusting the actuator to a determined actuator position displaces the pivot pin from centerline "C" by approximately 5% of the length "L" between the holes of the adjustable coupler.

12. The method according to claim 8, characterized in that in, The one or more sensors include at least one of a fan speed sensor, a temperature sensor, a pressure sensor, or a crosswind sensor.

13. The method according to claim 8, characterized in that in, Adjusting the actuator to a determined actuator position improves the one or more gap values ​​by 3 to 5 mils.

14. An aircraft, characterized in that: include: an aircraft engine coupled to a wing using at least one thrust link and an adjustable coupler, wherein the adjustable coupler includes at least one aperture for coupling to the at least one thrust link and a slot defining a hinge point for the adjustable coupler; an actuator comprising a pivot pin slidably coupled within a slot, wherein movement produced by the actuator adjusts a position of the pivot pin within the slot, thereby changing the hinge point of the adjustable coupler; one or more sensors configured to capture real-time flight data; and an electronic control unit communicatively coupled to the actuator and the one or more sensors, wherein the electronic control unit is configured to: receiving flight data from the one or more sensors, implementing a machine learning model trained to predict one or more clearance values ​​within the aircraft engine based on received flight data, predicting, using the machine learning model, the one or more clearance values ​​within the aircraft engine based on received flight data, determining an actuator position based on the one or more clearance values, and Adjusting the actuator to a determined actuator position, wherein adjusting the actuator to the determined actuator position displaces the pivot pin slidably coupled within the slot from a centerline "C" by a length "L" between the holes of the adjustable coupler.

15. The aircraft according to claim 14, characterized in that in, The electronic control unit is configured to generate a control signal and transmit the control signal to the actuator to adjust the actuator to a determined actuator position.

16. The aircraft according to claim 14, characterized in that in, Adjusting the actuator to a determined actuator position displaces the pivot pin from centerline "C" by approximately 10% of the length "L" between the holes of the adjustable coupler.

17. The aircraft according to claim 14, characterized in that in, Adjusting the actuator to a determined actuator position displaces the pivot pin from centerline "C" by approximately 5% of the length "L" between the holes of the adjustable coupler.

18. The aircraft according to claim 14, characterized in that in, The one or more sensors include at least one of a fan speed sensor, a temperature sensor, a pressure sensor, or a crosswind sensor.

19. The aircraft according to claim 14, characterized in that in, Adjusting the actuator to a determined actuator position improves the one or more gap values ​​by 3 to 5 mils.

Images