Systems and methods for monitoring potential failure in a bearing or a component thereof
A system for monitoring potential failure in a machine or a component thereof, the system including: at least one optical sensor configured to be fixed on or in vicinity of the machine or the component thereof, at least one processor in communication with the sensor, the processor being executable to: receive signals from the at least one optical sensor, obtain data associated with characteristics of at least one mode of failure of the machine or the component thereof, identify at least one change in the received signals, for an identified change in the received signals, apply the at least one identified change to an algorithm configured to analyze the identified change in the received signals and to classify whether the identified change in the received signals is associated with a mode of failure of the machine or the component thereof, thereby labeling the identified change as a fault, based, at least in part, on the obtained data, and for an identified change is classified as being associated with a mode of failure, outputting a signal indicative of the identified change associated with the mode of failure.
1. A system for monitoring potential failure in a bearing or a portion thereof, the system comprising:
a bearing comprising:
an inner ring;
an outer ring; and
one or more intermediate elements positioned between the inner ring and the outer ring, configured to accommodate motion between the inner ring and the outer ring;
one or more image sensors positioned on a ring shaped body sized to fit near the vicinity of or about the bearing, to image at least a portion of the inner ring, the outer ring or the intermediate elements of the bearing; and
at least one processor in communication with said one or more image sensors,
the at least one processor being executable to:
receive signals from the at least one image sensor;
perform an image analysis of the received image signals to detect whether the received image signals comprise a fault associated with a mode of failure of the bearing; and
for a detected fault, output a signal indicative of the identified mode of failure.
2. A system according to claim 1 , wherein the body further comprises one or more light sources positioned to illuminate at least one or more specific portions of the bearing.
3. A system according to claim 2 , wherein the light sources operate at different times or pulses.
4. A system according to claim 1 , wherein the one or more image sensors are positioned such that the cumulative image signals received from the one or more image sensors is associated with a 360-degree view of the bearing.
5. A system according to claim 1 , wherein the system is configured to continuously monitor the bearing, and, if a fault is detected, monitor a progression of the detected fault.
6. The system according to claim 1 , wherein for a detected fault, said processor is executable to generate at least one model of a trend in the detected fault associated with a mode of failure.
7. The system according to claim 6 , further comprising alerting a user of a predicted failure based, at least in part, on the generated model.
8. The system according to claim 6 , further comprising outputting a prediction of when the detected fault is likely to lead to failure in the bearing, based, at least in part, on the generated model.
9. The system according to claim 1 , wherein the detected fault includes one or more of a structural damage, a crack, a defect, a predetermined crack size and/or length, crack growth rate, crack propagation, fracture, defect diameter, abrasion, wear, corrosion, oxidation, a change in dimension of at least a portion of the segment, a change in position of at least a portion of the bearing, a change in color of at least a portion of the bearing, a change in texture of at least a portion of the bearing, change in size of at least a portion of the bearing, a change in appearance of at least a portion of the bearing, linear movement of at least a portion of the bearing, or any combination thereof.
10. A computer implemented method for monitoring a bearing, the computer implemented method comprising:
providing a bearing comprising:
an inner ring;
an outer ring; and
one or more intermediate elements positioned between the inner ring and the outer ring, configured to accommodate motion between the inner ring and the outer ring;
receiving image signals from one or more image sensors positioned on a ring shaped body sized to fit near the vicinity of or about the bearing, to image at least a portion of the inner ring, the inner ring or the intermediate elements of the bearing;
performing an image analysis of the received image signals to detect whether the received image signals comprise a fault associated with a mode of failure of the bearing; and
for a detected fault, outputting a signal indicative of the identified mode of failure.
11. A method according to claim 10 , wherein the image analysis of the received image signals comprises:
identifying at least one change in the received image signals;
for the identified at least one change in the received image signals, analyzing the identified change in the received image signals and classifying whether the identified change in the received image signals is associated with a mode of failure of the machine or the component thereof.
12. A method according to claim 10 , wherein said receiving, analyzing and outputting is performed during operation of the machine in which the bearing is implemented.
13. A method according to claim 10 , wherein the body further comprises light sources configured to illuminate at least a portion of the bearing.
14. A method according to claim 10 , wherein the one or more sensors are positioned on the body configured to monitor 360 degrees of the bearing.
15. A method according to claim 10 , wherein the method is configured to continuously monitor the bearing, and, if a fault is detected, monitor a progression of the detected fault.
16. A method according to claim 10 , further comprising generating at least one model of a trend in the detected fault associated with a mode of failure and outputting a prediction of when the fault is likely to lead to a failure in the bearing.