System and method to enable the application of optical tracking techniques for generating dynamic quantities of interest with alias protection

• US 9,852,330 B1
• Filed: 07/27/2015
• Issued: 12/26/2017
• Est. Priority Date: 07/27/2015
• Status: Active Grant

• Current Assignee: United Launch Alliance LLC
• Original Assignee: United Launch Alliance LLC
• Inventors: Shannon, Ryan Lee
• Primary Examiner(s): Harandi, Siamak
• Application Number:
  US14/809,563
• Time in Patent Office: 883 Days
• CPC Class Codes: G06F 18/22 Matching criteria, e.g. proximity measures
• CPC Class Codes: G06F 2218/08 Feature extraction
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/20064 Wavelet transform [DWT]
• CPC Class Codes: G06T 7/001 using an image reference approach
• CPC Class Codes: G06V 10/147 Details of sensors, e.g. sensor lenses fingerprint or palmprint sensors G06V40/13; vascular sensors G06V40/145; eye sensors G06V40/19
• CPC Class Codes: G06V 10/25 Determination of region of interest [ROI] or a volume of interest [VOI]
• CPC Class Codes: G06V 10/446 using Haar-like filters, e.g. using integral image techniques
• CPC Class Codes: G06V 10/62 relating to a temporal dimension, e.g. time-based feature extraction; Pattern tracking
• CPC Class Codes: G06V 10/761 Proximity, similarity or dissimilarity measures
• CPC Class Codes: G06V 2201/121 using special illumination

Abstract

Systems and methods for realizing practical applications of high speed digital image correlation (DIC) for dynamic quantities of interest are provided. In particular, a series of images are captured for a component of interest in which a non-filtered sensor and an analog low-pass filtered sensor are included within the region of interest for the series of images. Displacement signals are obtained for the component of interest, the non-filtered sensor, and the analog low-pass filtered sensor by applying digital image correlation processing to the series of images, which may also be wavelet filtered. Dynamic quantities of interest may be generated and derived from the displacement signals after having been wavelet filtered. Such dynamic quantities of interest based on the wavelet filtered DIC-derived displacement signal may be compared to sensor-derived dynamic quantities of interest to determine if aliasing is or is likely to be present.

Claims

1. A system comprising:

at least one camera focused on a region of interest;

a sensor located within the region of interest; and

a data processing system adapted to receive sensor data from the sensor, and to receive a series of images from the at least one camera, wherein each image includes the region of interest, the data processing system including;

at least one processor; and

memory storing one or more program instructions that when executed by the at least one processor, execute the steps of;

generating an optically-derived dynamic quantity of interest for the sensor based on the series of images provided from the at least one camera,

generating a dynamic quantity of interest based on sensor data provided from the sensor,

comparing the optically-derived dynamic quantity of interest for the sensor to the dynamic quantity of interest based on sensor data provided from the sensor,

generating an indication of aliasing based on a measure of similarity between the optically-derived dynamic quantity of interest for the sensor and the dynamic quantity of interest based on sensor data provided from the sensor, and

filtering data associated with at least one optically-derived dynamic quantity of interest based on the indication of aliasing.

2. The system of claim 1, wherein the sensor is an accelerometer.

3. The system of claim 1, further comprising:

generating an optically-derived dynamic quantity of interest for a second sensor based on the series of images provided from the at least one camera;

generating a dynamic quantity of interest based on analog low-pass filtered sensor data provided from the second sensor;

comparing the optically-derived dynamic quantity of interest for the second sensor to the dynamic quantity of interest based on sensor data provided from the second sensor; and

generating the indication of aliasing based on a measure of similarity between the optically-derived dynamic quantity of interest for the second sensor and the dynamic quantity of interest based on sensor data provided from the second sensor.

4. The system of claim 1, further comprising filtering a first displacement signal associated with the sensor, wherein the first displacement signal is generated from the series of images using at least one digital image correlation technique, and the optically-derived dynamic quantity of interest is generated based on the filtered first displacement signal.

5. The system of claim 4, further comprising filtering a second displacement signal associated with a second sensor, wherein the second displacement signal is generated from the series of images using the at least one digital image correlation technique and a second optically-derived dynamic quantity of interest is generated for the second sensor based on the filtered second displacement signal.

6. The system of claim 1, further comprising modifying at least one of a wavelet filter type and a wavelet decomposition level based on the optically-derived dynamic quantity of interest for the sensor and the dynamic quantity of interest based on sensor data provided from the sensor.

7. The system of claim 6, further comprising wavelet filtering a second displacement signal associated with a component of interest, wherein the second displacement signal is generated from the series of images using at least one digital image correlation technique.

8. The system according to claim 1, wherein the dynamic quantity of interest is a shock response spectrum.

9. The system according to claim 1, furthering comprising a second camera focused on the region of interest.

10. A method comprising:

generating a first dynamic quantity of interest for a sensor based on a series of images provided from at least one camera directed at a region of interest;

generating a second dynamic quantity of interest based on sensor data provided from the sensor;

comparing the first dynamic quantity of interest to the second dynamic quantity of interest;

generating an indication of aliasing based on a measure of similarity between the first dynamic quantity of interest and the second dynamic quantity of interest; and

based on the indication of aliasing, filtering data associated with at least one dynamic quantity of interest based on a series of images.

11. The method according to claim 10, further wherein the sensor data is analog low-pass filtered sensor data and the second dynamic quantity of interest is based on the analog low-pass filtered sensor data.

12. The method according to claim 11, is further comprising:

generating a third dynamic quantity of interest for a second sensor based on the series of images provided from the at least one camera directed at the region of interest, wherein the first and second sensors are included within the region of interest;

generating a fourth dynamic quantity of interest based on sensor data provided from the second sensor;

comparing the third dynamic quantity of interest to the fourth dynamic quantity of interest; and

generating the indication of aliasing based on a measure of similarity between the third dynamic quantity of interest and the fourth dynamic quantity of interest.

13. The method according to claim 12, wherein the sensor and the second sensor are first and second accelerometers.

14. The method according to claim 13, further comprising:

filtering a first displacement signal associated with the first accelerometer, wherein the first displacement signal is generated from the series of images using at least one digital image correlation technique and the first dynamic quantity of interest is generated based on the filtered first displacement signal; and

filtering a second displacement signal associated with the second accelerometer, wherein the second displacement signal is generated from the series of images using the at least one digital image correlation technique and the third dynamic quantity of interest is generated based on the filtered second displacement signal.

15. The method according to claim 14, further comprising:

modifying at least one of a wavelet filter type and a wavelet decomposition level based on one or more of the measure of similarity between the first dynamic quantity of interest and the second dynamic quantity of interest and the measure of similarity between the third dynamic quantity of interest and the fourth dynamic quantity of interest.

16. The method according to claim 15, further comprising:

wavelet filtering a third displacement signal associated with a component of interest, wherein the third displacement signal is generated from the series of images using the at least one digital image correlation technique.

17. The method according to claim 10, wherein the dynamic quantity of interest is a shock response spectrum.

18. The method according to claim 10, wherein the measure of similarity is a sum of the squared differences between the first dynamic quantity of interest and the second dynamic quantity of interest.

19. A computer-readable storage device comprising processor-executable instructions operable to perform the method of claim 10.

20. A system comprising:

at least one camera focused on a region of interest;

a first sensor and a second sensor;

a data processing system adapted to receive sensor data and a series of images, wherein the sensor data is from the first sensor and the second sensor and each image includes the region of interest, the data processing system including;

at least one processor; and

memory storing one or more program instructions that when executed by the at least one processor, execute the steps of;

determining a first dynamic quantity of interest for the first sensor based on a displacement signal derived from the series of images via a digital image correlation technique, wherein the displacement signal is wavelet filtered according to at least one of a wavelet filter type and a wavelet decomposition level,

determining a second dynamic quantity of interest for the second sensor based on a displacement signal derived from the series of images via the digital image correlation technique, wherein the displacement signal is wavelet filtered according to at least one of a wavelet filter type and a wavelet decomposition level,

determining a third dynamic quantity of interest for the first sensor based on analog low-pass filtered sensor data provided by the first sensor,

determining a fourth dynamic quantity of interest for the second sensor based on non-filtered sensor data provided by the second sensor,

comparing the first dynamic quantity of interest to the third dynamic quantity of interest,

comparing the second dynamic quantity of interest to the fourth dynamic quantity of interest,

generating an indication of aliasing based on one or more of a measure of similarity between the first dynamic quantity of interest and the third dynamic quantity of interest and a measure of similarity between the second dynamic quantity of interest and the fourth dynamic quantity of interest, and

modifying at least one of a wavelet filter type and a wavelet decomposition level based on the indication of aliasing,

wavelet filtering, according to the modified at least one of the wavelet filter type and the wavelet decomposition level, a displacement signal derived from the series of images via the digital image correlation technique, and

determining a fifth dynamic quantity of interest for a component of interest based on the wavelet filtered displacement signal.