System and method of determining rotor loads and motion

Patent metadata

Field	Value
Publication number	US-10023305-B2
Application number	US-201213468698-A
Country	US
Kind code	B2
Filing date	May 10, 2012
Priority date	May 10, 2012
Publication date	Jul 17, 2018
Grant date	Jul 17, 2018

Abstract

A system for reconstructing sensor data in a rotor system that comprises a rotating component of the rotor system, a plurality of sensors in the rotating component to sense at least one of loads and motion characteristics in the rotating component and to generate sensor data, and an analysis unit to generate reconstructed sensor data from the sensor data using numerical analysis for low-rank matrices.

First claim

What is claimed is:

1. A system for reconstructing sensor data in a rotor system of a rotary wing aircraft having a number of aircraft states, comprising:
a plurality of rotor blades of the rotor system of the rotary wing aircraft;
a plurality of sensors mounted to each of the plurality of rotor blades, the plurality of sensors sensing at least one of loads and motion characteristics in the corresponding one of the one or more of the plurality of rotor blades and generate a number of sensor samples on each rotor revolution; and
an analysis unit to generate, through a processor, reconstructed sensor data from the sensor data using numerical analysis for low-rank matrices, wherein the plurality of sensors are wireless sensors to transmit the sensor data from the corresponding one of the one or more of the plurality of rotor blades to the analysis unit;
wherein the plurality of sensors includes a number of sensors with the number of sensors multiplied by the number of sensor samples for each sensor generated on each rotor revolution being greater than the number of aircraft states;
wherein the analysis unit generates the reconstructed sensor data by generating a matrix with the sensor data and performing numerical methods for low-rank matrices, wherein the reconstructed sensor data corrects for corrupted wireless transmissions from the wireless sensors;
wherein the analysis unit further generates a fault-free matrix, a fault matrix, and a noise matrix from the matrix generated with the sensor data;
wherein each row of the matrix contains sensor data generated in one revolution of the rotor system for each of the plurality of sensors, and the number of rows corresponds to a plurality of revolutions of the rotor system;
wherein each column of the matrix contains data sampled from one of the plurality of sensors at a selected rotor azimuth location;
wherein sensor data is sampled at multiple azimuth positions through a single revolution of the rotor system; and
a data output unit operable to output the reconstructed sensor data to fault detection system.

2. The system of claim 1 , wherein the sensor data includes at least one of erroneous data and holes corresponding to missing sensor data, and
the reconstructed sensor data includes at least one of corrected data and substitute data corresponding, respectively, to the erroneous sensor data and the missing sensor data.

3. The system of claim 1 , wherein one or more of the plurality of sensor is mounted at a rotor shaft of the rotor system, and the loads and motion characteristics include at least one of blade flap, blade pitch, blade lead lag, main rotor shaft bending, main rotor shaft torque, and pitch rod loads.

4. The system of claim 1 , wherein the analysis unit generates the reconstructed sensor data using at least one of principal component pursuit, matrix completion, and nuclear-norm regularized multivariate linear regression.

5. The system of claim 4 , wherein a computational efficiency of an optimization problem for at least one of principal component pursuit and matrix completion is enhanced by solving an equivalent optimization problem using a relatively small, pre-determined matrix derived from a covariance matrix of a relatively large matrix of loads and motion data.

6. The system of claim 4 , wherein convex optimization problems for reconstruction of missing or corrupted data include a term which induces matrix sparsity over groups of matrix entries, each group corresponding to measurements obtained from a particular sensor over a particular rotor revolution.

7. The system of claim 1 , wherein the analysis unit is configured to isolate at least one of a sensor fault and a structural fault in the rotor system using at least one of the fault-free matrix, the fault matrix, and the noise matrix.

8. The system of claim 1 , wherein data collected from the plurality of sensors for determining loads and motion characteristics is collected from a selected linear regime.

9. A method of reconstructing sensor data of a rotor system of a rotary wing aircraft having a number of aircraft states, comprising:
collecting sensor data from a plurality of wireless sensors mounted to a rotor blade of the rotor system of the rotary wing aircraft, wherein collecting sensor data includes receiving the sensor data via a wireless receiver; and
generating, through a processor of an analysis unit, reconstructed loads and motion data of the rotor blade by applying numerical methods for low-rank matrices to the sensor data, wherein the reconstructed loads and motion data correct for corrupted wireless transmissions from the wireless sensors;
generating through the processor of the analysis unit a fault-free matrix, a fault matrix, and a noise matrix from the matrix generated with the sensor data;
wherein the plurality of sensors includes a number of sensors with the number of sensors multiplied by the number of sensor samples for each sensor generated on each rotor revolution being greater than the number of aircraft states;
wherein generating, though the processor of the analysis unit, reconstructed loads and motion data of the rotor blade includes generating, through the processor, a matrix with the sensor data from the sensors and performing the numerical methods on the matrix;
wherein each row of the matrix contains sensor data generated in one revolution of the rotor system for each of the plurality of wireless sensors, and the number of rows corresponds to a plurality of revolutions of the rotor system;
wherein each column of the matrix contains data sampled from one of the plurality of sensors at a selected rotor azimuth location;
wherein sensor data is sampled at multiple azimuth positions through a single revolution of the rotor system; and
wherein generating the reconstructed loads and motion data includes outputting the reconstructed loads and sensor data to a fault detection system.

10. The method of claim 9 , wherein the sensor data includes at least one of faulty sensor data and holes corresponding to missing sensor data, and
generating, through the processor, reconstructed loads and motion data of the rotor blade includes applying the numerical methods to provide at least one of corrected values to remedy the faulty sensor data and replacement values to remedy the holes.

11. The method of claim 9 , wherein the numerical methods include at least one of principal component pursuit, matrix completion, and nuclear-norm regularized multivariate linear regression.

12. The method of claim 11 , wherein a computational efficiency of an optimization problem for at least one of principal component pursuit and matrix completion is enhanced by solving an equivalent optimization problem using a relatively small, pre-determined matrix derived from a covariance matrix of a relatively large matrix of loads and motion data.

13. The method of claim 11 , wherein convex optimization problems for reconstruction of missing or corrupted data include a term which induces matrix sparsity over groups of matrix entries, each group corresponding to measurements obtained from a particular sensor over a particular rotor revolution.

14. The method of claim 9 , further comprising using the reconstructed loads and motion data to perform at least one of isolating sensor faults and identifying structural faults in the rotor system.

15. The method of claim 9 , further comprising: collecting data from a selected linear regime of the plurality of sensors to determine load and motion characteristics.

Assignees

• Isom Joshua D
• Shishkin Sergey
• Sikorsky Aircraft Corp

Inventors

• Isom Joshua D
• Shishkin Sergey

Classifications

• G01P15/00

  Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration · CPC title

• B64C27/006 Primary

  Safety devices · CPC title

• B64C27/008

  Rotors tracking or balancing devices · CPC title

• G01L5/133

  for measuring thrust of propulsive devices, e.g. of propellers (aeroplanes B64C; marine propulsion B63H; jet-engines F02K) · CPC title