The present invention relates to landing gear structures in aircraft, and more particularly, to systems and methods for determining, e.g., predicting, ground loads applied thereto.
Airframe manufacturers typically require that landing gear suppliers provide a detection system to determine if any overload condition occurs. Overload conditions refer to any combination of forces, e.g., stresses, strains and ground loads, which act on the landing gear that cause one or more components to reach design limits and, ultimately, yield. Typically, overload conditions occur during landing, ground maneuvers or towing operations.
Historically detection of overload conditions was limited to pilot opinion and reporting. However, more recent attempts that detect overload conditions use recorded flight data to assess a severity of a landing event which, in turn, is predicts whether an overload condition may have occurred. For example, U.S. Pat. No. 7,589,645 to Schmidt (hereinafter “Schmidt”) discloses an overload detection system that uses accelerometer measurements in combination with flight data from the avionics system to determine if a hard landing occurs. Occurrence of this hard landing can result in an overload condition. However, the approach disclosed in Schmidt proves highly inaccurate since it is predicated on only accelerometer measurements and flight and fails to provide quantitative information of actual loads experienced by the landing gear. In addition, accelerometer measurements and flight data are only available when accelerometers and avionic electronics are operational, e.g., power is on. Accordingly, Schmidt fails to detect if an overload occurs during towing operations whereby aircraft power is off. Further still, Schmidt failure to provide quantitative information of actual loads experienced by the landing gear results in an overwhelming number of erroneously detected overload conditions. Erroneous detection of overload conditions causes an increased cost of maintenance for the landing gear and, ultimately, a delay in future deployment for the aircraft due to required verification inspections that clear the landing gear prior to further flights. The required verification inspections are expensive, time-consuming and complex.
For example, if there are indications of overload conditions after initial visual ground inspections, subsequent inspections on the landing gear are performed during landing gear operation and while the aircraft is placed in suspension, e.g., on aircraft jacks. Thereafter, if these subsequent inspections indicate overload conditions, the entire landing gear is removed and sent to a qualified facility for detailed Non-Destructive Testing (NDT). At present, the entire landing gear is removed, even if only a single landing gear component fails, since, it is not possible to determine individual landing gear component loads and, thus, it is not possible to determine when individual landing gear components reach design limits and fail.
Therefore, there is a need for accurate detection of overload conditions, so as to eliminate unnecessary inspections. Moreover, there is a need for detection of loads upon individual components of the landing gear that are subjected to overload conditions, thereby allowing service technicians to quickly identify only particular component(s) that require further inspection or replacement.
It is also appreciated that, in general, airline industry customers are hesitant to implement new detection systems unless required by the airframe manufacturer and/or aviation authorities. Further, additional detection systems typically correlate to increased costs, such as, additional maintenance.
Therefore, there is a need for an inexpensive detection system that objectively and accurately assess the forces experienced by the landing gear and, further, the degree to which particular landing gear components approach design limits caused by the forces, e.g., an overload condition. Such a detection system can confirm or disprove pilot-made hard landing declarations, assure safe aircraft operation and, further, minimize maintenance costs associated therewith.
The present disclosure provides systems and methods for predicting loads experienced by a landing gear of an aircraft. The disclosed systems and methods provide sensors associated with the landing gear and, further, processing architecture for predicting the forces experienced by the landing gear.
The terms “strain gauge” or “strain sensors”, as used herein, are not limited to traditional strain gauges that measure resistance changes from an increase or decrease in strain, but, instead, these terms refer to any device that can be used to determine strain or displacement of a component at a given location. The term “force” refers to a measure of the interaction between bodies, and the term “load” refers to the force exerted on a surface or body, e.g., the landing gear. The terms “comprises” or “comprising” are to be interpreted as specifying the presence of the stated features, integers, steps or components, but not precluding the presence of one or more other features, integers, steps or components or groups thereof. The term “landing gear”, as used herein, is not limited to only an individual component of a traditional landing gear, but, instead, refers to a landing gear structure, including connecting components.
The present disclosure provides a system for predicting loading applied to a landing gear including, inter alia, a plurality sensors positioned proximate to the landing gear. The plurality of sensors measure strain experienced by the landing gear and each sensor yielding strain data. The system further includes a processor that receives the strain data from the plurality of sensors and predicts at least one ground load applied to the landing gear based on the strain data.
In some embodiments, at least one sensor of the plurality of sensors measures a hoop stress experienced by the landing gear structure and yields hoop stress data. The processor further receives the hoop stress data, and predicts the at least one ground load based on the hoop stress data and the strain data.
In other embodiments, the landing gear includes a bogie beam that has a pivot point and at least two axles. The plurality of sensors are positioned on either side of the pivot point, and the strain data includes measurements of loads from each of the at least two axles to yield individual axle data. The processor predicts the at least one ground load based on a summation of the individual axle data.
Alternatively, the landing gear can include a piston and a bogie beam that connects to the piston at a piston base. The bogie beam can include at least two axles and a pivot point. The plurality of sensors are positioned on either side of the pivot point and at least one of the plurality of sensors is positioned on the piston base.
The system can further include a power supply module, data acquisition circuitry, and a second processor. The power supply module provides power to the plurality of sensors, the data acquisition circuitry interrogates the plurality of sensors to acquire the strain data therefrom, and the second processor instructs the data acquisition circuitry as to the sampling rate and data resolution to be used to interrogate the plurality of sensors.
In some embodiments, the strain is measured at a sensor location and the processor further predicts an occurrence of an overload condition based on a model that relates a magnitude of the ground load to a design limit of the landing gear, e.g., a landing gear component, at the sensor location.
There is further disclosed a method for predicting a ground load applied to a landing gear. The method includes powering a plurality of sensors located proximate to the landing gear structure, interrogating the plurality of sensors via data acquisition circuitry to yield strain data, instructing the data acquisition circuitry as to a sampling rate and data resolution to be used for the interrogating, and, finally, processing the strain data to predict a ground load applied to the landing gear.
These and other aspects of the systems and methods of the present disclosure will become more readily apparent to those having ordinary skill in the art from the following detailed description taken in conjunction with the drawings, described below.
So that those having ordinary skill in the art can more readily understand how to employ the novel system and methods of the present disclosure, embodiments thereof are described in detail herein below with reference to the drawings, wherein:
In general, a component or a feature that is common to more than one drawing is indicated with the same reference number in each of the drawings.
Disclosed herein are detailed descriptions of specific embodiments of systems and methods for predicting the loads experienced by the landing gear which can be used to evaluate whether an overload condition has occurred.
The disclosed embodiments are merely examples of ways in which certain aspects of the disclosed systems and methods can be implemented and do not represent an exhaustive list of all of the ways the invention may be embodied. Indeed, it will be understood that the systems, devices, and methods described herein may be embodied in various and alternative forms. The figures, described above, are not necessarily to scale and some features may be exaggerated or minimized to show details of particular components. Well-known components, materials or methods are not necessarily described in great detail in order to avoid obscuring the present disclosure. Moreover, the figures illustrate some elements that are known and will be recognized by one skilled in the art. The detailed descriptions of such elements are not necessary to an understanding of the disclosure, and accordingly, are presented only to the degree necessary to facilitate an understanding of the novel features of the present disclosure.
To achieve the need for accurate detection of overload conditions, detection of the forces and loads applied to individual components of the landing gear, and, further, to provide simplified systems and methods that avoid unnecessary maintenance costs, the present disclosure provides systems and methods for accurate overload detection using a minimum number of sensors strategically placed proximate the landing gear.
The systems and methods provided by the present disclosure are illustrated conceptually in
The loads applied to landing gear 100 along each of the X axis, the Y axis and the Z axis include a vertical force (V), a drag force (D), a side force (S), respectively. In addition, the loads further include moments about each of the X, Y and Z axis that include a vertical moment (MV), a drag moment (MD) and a side moment (MS), respectively. All of these forces and moments represent a total load applied at aircraft wheels (not shown) that are attached to axle 120. The aircraft wheels are not illustrated, but, instead, a vertical wheel centerline 130 and a vertical wheel centerline 135 represent placement of an inboard wheel and an outboard wheel, respectively, on axle 120.
The total loading, including applied forces and resultant moments, is calculated as follows:
Σ_Fx=D=DAi(or DGi)+DAo(or DGo)
ΣFy=S=Si=So
ΣFz=V=Vi+Vo
ΣMx=MD=MDi+MDo+(Vi−Vo)Lw
ΣMy=MS=−(DGi+DGo)RR
ΣMz=MV=(Do+Di)Lw
Wherein:
D=DA (Drag force acting on axle centerline when brakes inactive)
D=DG (Drag force acting at the ground when brakes are active)
RR=Tire Rolling Radius (i.e. distance from axle centerline to tire contact point)
Lw=distance from shock strut centreline to wheel centerline 130 (inboard wheel centerline 130 equals outboard wheel centerline 135).
Note: an assumption is made that landing gear 100 includes two wheels.
The loads that are applied to landing gear 100 are transferred from the aircraft wheels to piston 110 and torque linkage 115. The aircraft wheels experience ground loads when an aircraft is landing. Accordingly, sensors are strategically placed at piston 110 and torque linkage 115.
ΣFx=D
ΣFy=S
ΣFz=V
ΣMx=MD+SL
ΣMy=MS−DL
ΣMz=0
Wherein:
L is an axle trail, e.g., the distance from the axle centerline to the piston centerline.
S is a total side load
D is a total drag load
MV is reacted by the torque linkage.
Mz is zero at piston strain measurement locations since the torque linkage transfers MV to an upper landing gear structure. Further, some designs carry MV through the sensor location, however, most designs do not.
In particular,
In some landing gear designs, however, oil in a shock strut is present throughout the entire length of the piston 110, and thereby causes hoop stress when compressed. According to Hooke's law, sensors 215 can be affected by this hoop stress since they are located on piston 110 Specifically, hoop stress affects uniaxial sensor measurements (uniaxial sensors are discussed with reference to
Referring now to
For example, the uniaxial stresses are as follows:
Accordingly, the total stress values are:
Thus, the total axial strain equation, from Hooke's Law, is as follows:
According to the total axial strain equation above and represented in Table 1, there are a total of five unknown variables, i.e., five load components acting on piston 110. These five unknown variables, or five load components, generate axial strain at piston 110, via bending or direct axial loading. Accordingly, sensors 215 are designed to include five sensors that measure strain and predict the five load components, and, therefore solves for the five unknown variables.
Moreover, as discussed above, hoop stress may exist if the shock strut design allows for internal pressure, i.e., presence of oil, at the sensor locations. If hoop stress is present, an additional sensor is required to account for an x-component of strain caused by the hoop stress.
Sensors 215 are arranged in accordance with the five force components of Table 1 (and five unknown variables of the above-discussed equation), and include five sensors having arrangements illustrated in
Preferably, sensors 215 include an arrangement having at least one shear sensor in combination with uniaxial gauges, e.g., arrangements 305 and 310. This arrangement provides a robust design since both D and an MS produce bending about the Y axis, while S and MD produce bending about the X axis. Incorporating at least one shear sensor decouples the D and S from the MS and MD.
Sensor locations, e.g., orientation, quantity and type depend on an airframe program which the disclosed monitoring system is installed. Moreover, each landing gear design is traditionally static load tested prior to implementation. The static load testing can determine areas of maximum stress experienced by landing gear 100 and, further, determine optimized locations and types of sensors. For example, in each of arrangements of
The sensors are employed to measure loads applied to landing gear 100. The sensors are not limited to uniaxial or shear sensors, but, instead, refer to any device that can be used to determine strain or displacement of a component at a given location. Typically, the sensors are electronic and translate an applied load (including strain or displacement) into electronic data, e.g., stress or strain data. In addition, the sensors typically communicate with processing architecture. The processing architecture, including algorithms, includes a processor that receives sensor data, e.g., stress or strain data, and predicts at least one ground load based on the received sensor data. In some embodiments, the processor may be a stand-alone component or as an integrated arrangement of a plurality of sub-ordinate components. For example, the processor may be part of a control unit, data acquisition circuitry, or a combination thereof. Data acquisition circuitry typically receives sensor data in memory according to a sampling rate and a specified data resolution. In addition, the processor may be part of a data concentrator unit that receives and stores data from the data acquisition circuitry.
Further still, the processing architecture can predict an occurrence of the overload condition. For example, the processor predicts the occurrence of the overload condition based on a model that relates a magnitude of the ground load to a design limit of the landing gear at a sensor location. The model can be generated from data determined by finite element analysis or static load testing of the landing gear. In addition, after the processor predicts the occurrence of the overload condition, the processor further transmits an alarm, or causes an alarm to trigger. This alarm can include, but is not limited to an audio alarm or a visual alarm, e.g., a light.
In other embodiments, the processor communicates with a database that stores overload detection health and maintenance (ODHM) status. In particular, the database stores the strain data and the processor analyzes the strain data over time to yield a health status of the landing gear. For example, the processor can compare changes in the strain data over a time period to a baseline model that determines structural integrity of landing gear components, e.g., strain in a component v. time, to yield the health status.
LAPEX is determined by, and directly related to, a stroke of shock strut 105. Various techniques are used to determine the shock strut stoke and can include measuring a torque linkage angle change, which, in conjunction with a known geometry of the structure, provides the shock strut stroke.
Placement of sensor 505 upon torque linkage 115 allows for a shear force, PAPEX, to be determined. Further, shear force PAPEX is related to moment MV, via statics: MV=PAPEX*LAPEX (LAPEX is discussed with reference to
The bending stress and strain on upper torque link 405 (at the location of sensor 505) is as follows:
Combining the above-equations yields:
Therefore, the measured strain can now be related to the MV moment as follows:
Note that generally speaking, NLG designs do not include brake installations. As a result, the MS moment is not measured since this moment is caused by braking events.
Combining the stress equations for piston 110 and torque linkage 115, discussed above, yields a general landing gear load algorithm as follows:
Further, if shock strut internal pressure influences the strain readings due to hoop stress the matrix becomes:
Variables ε1-e5 represent either uniaxial or shear strain measurements. As discussed above (with reference to
From the above-calculations, the following loads are applied to torque link 405 at the location of sensor 505:
MBX=PAPEX*L
PSY=PAPEX
Accordingly, MBX is directly proportional to PAPEX. This allows for sensor 505 to be calibrated to PAPEX. Calibration can initially be completed via FEA and subsequently verified during static testing. In addition, FEA can be used to determine optimal locations for sensor 505 (and any additional sensors). Further, if the initial sensor arrangement is based on an FEA model, an algorithm used in the ODHMS, disclosed herein, can later be calibrated with static load testing.
The above discussion emphasizes an application of multiple loads at and along specific locations of landing gear 100, and also provides strategic locations for placement of sensors, e.g., sensors 215 and sensor 505. The placement of sensors and measurement data therefrom can be analyzed using a finite element model (FEM), to yield a total load experienced by the landing gear structure. In addition, the application of multiple load components can further be generalized for other landing gear designs. For example, specific and strategic locations for placement of sensors, e.g. sensors 215, are provided for various landing gear structures illustrated in
In addition to piston and torque linkage locations for two-wheel landing gear designs, additional sensors may be required to account for landing gear designs that support greater than two wheels, i.e., four wheel designs having a bogie beam.
In particular,
Sensors such as those discussed above, e.g., uniaxial sensors and shear sensors, are strategically placed on either side of pivot point 810 on bogie beam 805, i.e., fore, aft, outbound and inbound. For example, sensors can be placed at sensor locations 825. The sensors can provide strain measurements in addition to, or, alternatively, instead of, sensors located on piston 815 and/or torque linkage 820. Sensors placed fore and aft of pivot point 810 (on bogie beam 805) measure individual axle loads. Typically, for the fore and aft measurement locations on the bogie beam, each location would need a minimum of six sensors. Therefore, a total of twelve sensors would be placed on the bogie beam itself. A summation of these loads determines the total load applied to landing gear 800.
Similar to
In addition to the loads applied to the torque linkage, the piston, and the bogie beam, loads are also applied to the aircraft axle, e.g., axle 120, via aircraft wheels.
In particular,
The total loads illustrated in
D=DA (Drag force acting on axle centerline when brakes inactive)
D=DG (Drag force acting at the ground when brakes are active)
S=(Applied side load at the ground)
V=(Applied vertical load at the ground)
MD=Ve+S×RR (Applied moment about the global X-axis)
MS=−DG×RR (Applied moment about the global Y-axis (brake torque))
MV≈0 (Applied moment about the global Z-axis is typically assumed to be 0)
Axle 1010 is illustrated with eight uniaxial sensors numbered numerically 1-8. Eight sensors are chosen to measure loads at section B-B. However, preferably, only six sensors are required since there are six unknown variables needed to calculate the loads applied at section B-B. Specifically, the equation for equilibrium loading present at section B-B is as follows:
ΣFx=S
ΣFy=D
ΣFz=V
ΣMx=0 (any torque due to braking is not transferred to the axle)
ΣMy=MD−V(L−e)=Ve+S×RR−V(L−e)=V(2e−L)+S×RR
ΣMz=MV+D(L−e)
Accordingly, the six unknown variables include D, S, V, MV, RR and e. Six uniaxial strain sensors placed at various locations about axle 1010 provide measurements necessary to solve for these unknowns variables.
The six unknowns are developed from fundamental stress analysis equations which represent loads applied to axle 1010 at section B-B. More specifically, uniaxial sensors measure strain on bending forces, axial strain and hoop stress. Each type of these is calculated as follows:
Bending:
Axial:
Hoop:
σH
Thus, the total loads applied to section B-B are determined as follows:
The total axial strain is then (from Hooke's Law):
The total axial strain, determined from Hooke's Law is as follows:
Although the hoop stress σH is also an unknown in the above-equation, the values of the expected hoop stress at each sensor can be determined by relating the applied loads to hoop stress via a finite element analysis (FEA). The FEA relates hoop stress to an applied load and is completed by applying combinations of vertical and drag ground loads to the model and applying combinations of MD and MV to the model. After FEA is conducted, and using the principle of superposition, the total axial strain can be related as follows:
As discussed above, solving for total axial strain only requires knowledge of six unknown quantities, i.e., D, S, V, MV, RR and e. Therefore, six sensors solve for all of the unknown variables, and are placed about axle 1010 at section B-B.
In addition, the FEA obviates a need to derive stress equations based on applied loads and moments and, instead, FEA results, based on a finite element model two step process: (i) apply combinations o vertical and drag ground loads to the FEM and (ii) apply combinations of MD and MV moments to the FEM.
The location of loads and forces applied to an aircraft axle correlates to strategic placement of sensors about the aircraft axle. Further, these loads, forces, and strategic locations are generalized for various landing gear designs. For example, strategic locations for placement of sensors are provided for various landing gear designs in
Landing gear 600 includes an axle 1105 and a sensor location 1110. Sensor location 1110 indicates the location of uniaxial sensors. Sensor location 1110 is shown on an inboard section of axle 1105, but it is not limited to such. For example, sensor location 1110 can also be on an outboard section of axle 1105. Preferably, six sensors are located around a section of axle 1105 and, further, the six sensors are spaced equidistantly apart in an arrangement similar to sensor arrangement 300.
Landing gear 700 includes an axle 1205 and a sensor location 1210. Sensor location 1210 is typically where uniaxial sensors are located. Sensor location 1210, similar to sensor location discussed in
In sum, the strategic locations for placement of sensors proximate to a landing gear include the piston, torque links (including attachment pins), the axle, or are strategically placed on either side, of a pivot point and also at the piston base. These designs provide a simple detection system (and methods directed thereto) that objectively and accurately assess the loads experienced by the landing gear and, further, the degree to which the landing gear components approach design limits caused by the loads.
The techniques described herein are exemplary, and should not be construed as implying any particular limitation on the present disclosure. It should be understood that various alternatives, combinations and modifications could be devised by those skilled in the art. For example, steps associated with the processes described herein can be performed in any order, unless otherwise specified or dictated by the steps themselves. The present disclosure is intended to embrace all such alternatives, modifications and variances that fall within the scope of the appended claims.
Although the system and methods of the present disclosure have been described with respect to the exemplary embodiments above, those skilled in the art will readily appreciate that changes and modifications may be made thereto without departing from the spirit and scope of this disclosure as defined by the appended claims.
This application is a divisional application of, claims priority to and the benefit of, U.S. application Ser. No. 13/267,561, now U.S. Pat. No. 10,131,419, filed Oct. 6, 2011 and entitled “SYSTEMS AND METHODS FOR DETECTING LANDING GEAR GROUND LOADS.” The '561 application claims priority to and the benefit of U.S. Provisional Application Ser. No. 61/455,169, filed Oct. 15, 2010 entitled “SYSTEMS AND METHODS FOR DETECTING LANDING GEAR GROUND LOADS.” The '561 application also claims priority to and the benefit of U.S. Provisional Application Ser. No. 61/455,170, filed Oct. 15, 2010 entitled “MONITORING SYSTEMS AND METHODS FOR AIRCRAFT LANDING GEAR.” The '561 application also claims priority to and benefit of U.S. Provisional Application Ser. No. 61/393,456, filed Oct. 15, 2010 entitled “CAPACITIVE SENSORS FOR MONITORING LOADS.” The contents of all are incorporated by reference herein in their entirety for all purposes.
Number | Name | Date | Kind |
---|---|---|---|
1884023 | Terry | Feb 1932 | A |
2295830 | Carlson | Sep 1942 | A |
2968031 | Higa | Jan 1961 | A |
3109984 | Mehr | Nov 1963 | A |
3280628 | Fred | Oct 1966 | A |
3433064 | Jacobson | Mar 1969 | A |
3471758 | Werner | Oct 1969 | A |
3577883 | Werner | May 1971 | A |
3584503 | Senour | Jun 1971 | A |
3729985 | Sikorra | May 1973 | A |
3783496 | Siler | Jan 1974 | A |
3995696 | Kainer et al. | Dec 1976 | A |
4114428 | Popenoe | Sep 1978 | A |
RE30183 | Popenoe | Jan 1980 | E |
4197753 | Harting et al. | Apr 1980 | A |
4269070 | Nelson et al. | May 1981 | A |
4312042 | Bateman | Jan 1982 | A |
4384496 | Gladwin | May 1983 | A |
4386386 | Akita | May 1983 | A |
4386533 | Jackson et al. | Jun 1983 | A |
4422341 | Espiritu Santo et al. | Dec 1983 | A |
4445386 | Nielsen | May 1984 | A |
4449413 | Pugh | May 1984 | A |
4480480 | Scott et al. | Nov 1984 | A |
4510814 | Espiritu Santo et al. | Apr 1985 | A |
4651402 | Bonfils | Mar 1987 | A |
4850552 | Darden et al. | Jul 1989 | A |
4925249 | Auspelmyer | May 1990 | A |
4944181 | Wnuk | Jul 1990 | A |
5010775 | Choisnet | Apr 1991 | A |
5086651 | Westermo et al. | Feb 1992 | A |
5205514 | Patzig et al. | Apr 1993 | A |
5289435 | Milner et al. | Feb 1994 | A |
5314115 | Moucessian | May 1994 | A |
5358637 | Hutzler et al. | Oct 1994 | A |
5388463 | Scott | Feb 1995 | A |
5392654 | Boyle | Feb 1995 | A |
5446666 | Bauer | Aug 1995 | A |
5477740 | Shioya et al. | Dec 1995 | A |
5518206 | Arnold et al. | May 1996 | A |
5815091 | Dames et al. | Sep 1998 | A |
6070662 | Ciglenec et al. | Jun 2000 | A |
6204771 | Ceney | Mar 2001 | B1 |
6279407 | Park et al. | Aug 2001 | B1 |
6289289 | Zweifel | Sep 2001 | B1 |
6334588 | Porte | Jan 2002 | B1 |
6349901 | Grossman | Feb 2002 | B1 |
6354152 | Herlik | Mar 2002 | B1 |
6415242 | Weldon, Jr. | Jul 2002 | B1 |
6516508 | Gandarillas | Feb 2003 | B1 |
6536292 | Richards et al. | Mar 2003 | B1 |
6581481 | Perusek | Jun 2003 | B1 |
6676075 | Cowan et al. | Jan 2004 | B2 |
6745153 | White et al. | Jun 2004 | B2 |
6880784 | Wilkinson et al. | Apr 2005 | B1 |
6902136 | Mackness | Jun 2005 | B2 |
6951145 | Kilmartin | Oct 2005 | B2 |
6959497 | Leidinger | Nov 2005 | B2 |
7208945 | Jones et al. | Apr 2007 | B2 |
7558687 | Bode | Jul 2009 | B1 |
7589645 | Schmidt | Sep 2009 | B2 |
7680630 | Schmidt | Mar 2010 | B2 |
7747396 | El-Bakry et al. | Jun 2010 | B2 |
7747415 | Churchill et al. | Jun 2010 | B1 |
7843363 | Grichener et al. | Nov 2010 | B2 |
8011255 | Arms et al. | Sep 2011 | B2 |
8286508 | Eriksen et al. | Oct 2012 | B2 |
8301914 | Gelonese | Oct 2012 | B2 |
8359932 | Ericksen et al. | Jan 2013 | B2 |
10131419 | Baird | Nov 2018 | B2 |
20010026163 | Sasaki et al. | Oct 2001 | A1 |
20020043112 | Schwarz et al. | Apr 2002 | A1 |
20020199131 | Kocin | Dec 2002 | A1 |
20030042354 | Cowan et al. | Mar 2003 | A1 |
20030069670 | Osinga | Apr 2003 | A1 |
20030071165 | Fiebick et al. | Apr 2003 | A1 |
20030083794 | Halm | May 2003 | A1 |
20030152145 | Kawakita | Aug 2003 | A1 |
20030172740 | Stevenson et al. | Sep 2003 | A1 |
20030191564 | Haugse et al. | Oct 2003 | A1 |
20030209063 | Adamson et al. | Nov 2003 | A1 |
20040011596 | Miller et al. | Jan 2004 | A1 |
20040012212 | Pratt et al. | Jan 2004 | A1 |
20040075022 | MacKness | Apr 2004 | A1 |
20040102918 | Stana | May 2004 | A1 |
20040129834 | Luce | Jul 2004 | A1 |
20040150529 | Benoit et al. | Aug 2004 | A1 |
20040187607 | Kilmartin | Sep 2004 | A1 |
20040225474 | Goldfine et al. | Nov 2004 | A1 |
20050030010 | Jones et al. | Feb 2005 | A1 |
20050162389 | Obermeyer et al. | Jul 2005 | A1 |
20060004499 | Trego et al. | Jan 2006 | A1 |
20060038410 | Pratt et al. | Feb 2006 | A1 |
20060144997 | Schmidt et al. | Jul 2006 | A1 |
20060187017 | Kulesz et al. | Aug 2006 | A1 |
20070006662 | Giazotto | Jan 2007 | A1 |
20070228825 | Jacques | Oct 2007 | A1 |
20080036617 | Arms et al. | Feb 2008 | A1 |
20080114506 | Davis et al. | May 2008 | A1 |
20080119967 | Long et al. | May 2008 | A1 |
20080196945 | Konstas | Aug 2008 | A1 |
20080282817 | Breed | Nov 2008 | A1 |
20090132129 | Breed | May 2009 | A1 |
20090173823 | Shetzer | Jul 2009 | A1 |
20090179751 | Forster | Jul 2009 | A1 |
20090183561 | Gregory et al. | Jul 2009 | A1 |
20090216398 | Lynch et al. | Aug 2009 | A1 |
20090265120 | O'Brien | Oct 2009 | A1 |
20090293642 | Schmitz | Dec 2009 | A1 |
20100026482 | Grichener et al. | Feb 2010 | A1 |
20100063777 | Berkcan et al. | Mar 2010 | A1 |
20100090822 | Benson et al. | Apr 2010 | A1 |
20100141377 | Andarawis et al. | Jun 2010 | A1 |
20100162824 | Jamshidi et al. | Jul 2010 | A1 |
20100162864 | Kozasa et al. | Jul 2010 | A1 |
20100288878 | Bennett | Nov 2010 | A1 |
20100315219 | Gowan et al. | Dec 2010 | A1 |
20110018741 | Grichener et al. | Jan 2011 | A1 |
20110035054 | Gal et al. | Feb 2011 | A1 |
20110044145 | Lin | Feb 2011 | A1 |
20110285527 | Arms et al. | Nov 2011 | A1 |
20120011946 | Ericksen et al. | Jan 2012 | A1 |
20120012700 | Ericksen et al. | Jan 2012 | A1 |
20120012701 | Ericksen et al. | Jan 2012 | A1 |
20120043417 | Ericksen et al. | Feb 2012 | A1 |
20120046799 | Alex et al. | Feb 2012 | A1 |
20120053784 | Schmidt et al. | Mar 2012 | A1 |
20120095702 | Baird | Apr 2012 | A1 |
20120095703 | Zakrzewski et al. | Apr 2012 | A1 |
20120101770 | Grabiner et al. | Apr 2012 | A1 |
20120121504 | Rader et al. | May 2012 | A1 |
20120306377 | Igaki et al. | Dec 2012 | A1 |
20130135994 | Michel et al. | May 2013 | A1 |
20130154829 | Mostov | Jun 2013 | A1 |
Number | Date | Country |
---|---|---|
1267362 | Sep 2000 | CN |
3239877 | May 1984 | DE |
3619233 | Dec 1986 | DE |
4035197 | Jan 1992 | DE |
0072634 | Feb 1983 | EP |
1839984 | Oct 2007 | EP |
2410297 | Jul 2010 | EP |
2420447 | Feb 2012 | EP |
2441671 | Apr 2012 | EP |
2365785 | Apr 1978 | FR |
2545170 | Nov 1984 | FR |
643615 | Sep 1950 | GB |
222641 | Jun 1990 | GB |
2226416 | Feb 1993 | GB |
2387912 | Oct 2003 | GB |
1469339 | Mar 1989 | SU |
WO-2002012043 | Feb 2002 | WO |
WO-2004013785 | Feb 2004 | WO |
WO-2006053433 | May 2006 | WO |
WO-2006067442 | Jun 2006 | WO |
WO-2007149256 | Dec 2007 | WO |
WO 2009009732 | Jan 2009 | WO |
WO-2010031179 | Mar 2010 | WO |
WO-2012051578 | Apr 2012 | WO |
Entry |
---|
Extended Search Report dated Feb. 8, 2012 in connection with EP Application No. 11250852.8. |
Extended Search Report dated Feb. 4, 2010 in connection with EP Application No. 05808070.6. |
Office Action dated Feb. 3, 2012 in connection with U.S. Appl. No. 13/271,468. |
Partial Search Report dated Nov. 2, 2011 in connection with EP Application No. 11250645.6. |
Office Action dated Mar. 19, 2012 in connection with U.S. Appl. No. 12/839,401. |
Extended Search Report dated Mar. 15, 2012 in connection with EP Application No. 11250645.6. |
Partial Search Report dated Nov. 2, 2011 in connection with EP Application No. 11250647.2. |
Extended Search Report dated Mar. 15, 2012 in connection with EP Application No. 11250647.2. |
First Office Action Pre-Interview Communication dated May 30, 2012 in Connection with U.S. Appl. No. 12/839,216. |
PEPPER+FUCHS, Mounting Accessories, Aug. 7, 2008, pp. 1-2. |
Free Dictionary definition of “pin” http://www.thefreedictionary.com/PIN. |
Bradley, W. Baird, Overload Detection/ Health Monitoring Landing Gear Sensor System Proposal, Jan. 1, 2008, Ryerson University. |
International Preliminary Report on Patentability issued by the Canadian Intellectual Property Office dated May 22, 2007 for Corresponding International App. No. PCT/CA2005/001750 filed Nov. 18, 2005. |
Exam Report for EP Patent App. No. 05808070.6 dated Nov. 1, 2013. |
Exam Report for EP Patent App. No. 05808070.6 dated Mar. 5, 2014. |
Exam Report for EP Patent App. No. 05808070.6 dated Aug. 26, 2014. |
Exam Report for EP Patent App. No. 11250852.8 dated Aug. 14, 2013. |
Extended Search Report for EP Patent App. No. 11250653.0 dated Apr. 11, 2014. |
Extended Search Report dated Dec. 9, 2014 in European Application No. 14170817.2. |
Extended Search Report dated Jan. 26, 2015 in European Application No. 11250850.2. |
Extended Search Report dated Jan. 26, 2015 in European Application No. 11250729.8. |
Office Action dated Feb. 17, 2015 in Chinese Application No. 201110236000.8. |
Intention to Grant dated Jul. 22, 2015 in European Application No. 11250653.0. |
Communication Pursuant to Article 94(3) EPC dated Dec. 10, 2015 in European Application No. 11250647.2. |
Communication Pursuant to Article 94(3) EPC dated Dec. 10, 2015 in European Application No. 11250645.6. |
Extended European Search Report dated Jan. 21, 2016 in European Application No. 11250849.4. |
Office Action dated Mar. 8, 2016 in Chinese Application No. 201110236000.8. |
Communication under Rule 71(3) EPC dated Jun. 20, 2016 in European Application No. 11250729.8. |
Communication under Rule 71(3) EPC dated Jun. 27, 2016 in European Application No. 11250850.2. |
Notification to Grant Patent Right for Invention dated Aug. 10, 2016 in Chinese Application No. 201110236000.8. |
USPTO; All Office Actions (Non-Final, Final, Advisory Actions, Restrictions/Elections, etc.), Notices of Allowance, 892s, 1449s and SB/08As from U.S. Appl. No. 12/857,793. |
Office Action dated Mar. 28, 2017 in Canadian Application No. 2755086. |
Article 97(1) EPC Decision to Grant dated Nov. 6, 2017 in EP Application No. 11250849.4. |
Office Action dated Jun. 6, 2017 in Canadian Application No. 2746037. |
Office Action dated Apr. 24, 2017 in Canadian Application No. 2755101. |
Canadian Patent Office, Notice of Allowance dated May 5, 2017 in Candadian Application No. 2,746,071. |
Office Action dated May 19, 2017 in Canadian Application 11250849.4-1757. |
Office Action dated Jun. 12, 2017 in Canadian Application No. 2746162. |
Communication pursuant to Aeticle 94(3) EPC dated Oct. 13, 2017 in EP Application No. 74.62.120512. |
Canadian Patent Office, Notice of Allowance dated Mar. 20, 2018 in Candadian Application No. 2,755,101. |
Canadian Patent Office, Notice of Allowance dated Mar. 29, 2018 in Candadian Application No. 2,746,037. |
Canadian Patent Office, Notice of Allowance dated Apr. 4, 2018 in Candadian Application No. 2,746,162. |
USPTO: Notice of Allowance dated Jul. 13, 2018 in U.S. Appl. No. 13/267,561. |
USPTO: Non-Final Office Action dated Jul. 14, 2014 in U.S. Appl. No. 13/267,561. |
USPTO: Non-Final Office Action dated May 6, 2015 in U.S. Appl. No. 13/267,561. |
USPTO: Non-Final Office Action dated Mar. 17, 2016 in U.S. Appl. No. 13/267,561. |
USPTO: Final Office Action dated Jan. 2, 2015 in U.S. Appl. No. 13/267,561. |
USPTO: Final Office Action dated Nov. 13, 2015 in U.S. Appl. No. 13/267,561. |
USPTO: Final Office action dated Jul. 14, 2016 in U.S. Appl. No. 13/267,561. |
USPTO: Advisory Action dated Mar. 20, 2015 in U.S. Appl. No. 13/267,561. |
USPTO: Advisory Action dated Feb. 1, 2016 in U.S. Appl. No. 13/267,561. |
Number | Date | Country | |
---|---|---|---|
20190031323 A1 | Jan 2019 | US |
Number | Date | Country | |
---|---|---|---|
61393456 | Oct 2010 | US | |
61455169 | Oct 2010 | US | |
61455170 | Oct 2010 | US |
Number | Date | Country | |
---|---|---|---|
Parent | 13267561 | Oct 2011 | US |
Child | 16152183 | US |