Methods and systems for monitoring operation of equipment

• US 9,053,468 B2
• Filed: 04/07/2011
• Issued: 06/09/2015
• Est. Priority Date: 04/07/2011
• Status: Active Grant

• Current Assignee: GE Digital Holdings LLC (GE Vernova, Inc.)
• Original Assignee: General Electric Company
• Inventors: Haynes, Leon Ericson, Tackett, Charles Edgar
• Primary Examiner(s): Teixeira Moffat, Jonathan C
• Assistant Examiner(s): Chang, Stephanie
• Application Number:
  US13/082,086
• Publication Number:
  US 20120259585A1
• Time in Patent Office: 1,524 Days
• Field of Search: 702/182
• US Class Current: 1/1
• CPC Class Codes: G06Q 10/20 Administration of product repair or maintenance
• CPC Class Codes: G06Q 50/40 Business processes related to the transportation industry shipping G06Q10/083

Abstract

A condition assessment system for use in monitoring the operation of at least one of a plurality of units included within a fleet of substantially similar units is described. The system includes an input device configured to receive a selection of at least one source of data related to the operation of at least one of the plurality of units. The system also includes at least one sensor associated with the at least one source of data and configured to sense data related to the operation of at least one of the plurality of units. The system also includes a condition assessment device configured to receive data from the at least one sensor, sample data associated with at least one data parameter from the received data, and generate a baseline parametric curve from the data associated with the at least one sampled data parameter.

Claims

1. A condition assessment system for monitoring the operation of at least one of a plurality of units included within a fleet of units, said system comprising:

an input device configured to receive a selection of at least one source of data related to the operation of at least one of the plurality of units;

a memory device including at least one parametric curve representing a baseline of normal operations of at least one of the plurality of units;

a plurality of sensors associated with the at least one source of data, said plurality of sensors configured to sense data related to the operation of at least one of the plurality of units; and

a condition assessment device configured to;

receive data from each of said plurality of sensors, wherein the received data represents current conditions that said each sensor of said plurality of sensors is subject to;

determine, based on a determination that received data exceeds a threshold and is an anomaly, whether to generate a new baseline parametric curve representing normal operation of the at least one of the plurality of units, based in part on data received from at least two of said plurality of sensors exceeding a threshold and being an anomaly;

sample data associated with at least one data parameter from the received data; and

generate, based on the determination of whether to generate, the new baseline parametric curve from the data associated with the at least one sampled data parameter.

2. A system in accordance with claim 1, wherein the fleet of units includes at least a first unit, a second unit, and a third unit, wherein the first and second units are located in a first geographic region, wherein the third unit is located in a second geographic region, and wherein each unit includes at least one sensor associated with at least one source of data, and wherein said condition assessment device is further configured to:

receive data from the first unit and the second unit; and

determine for the first unit whether to generate the new baseline parametric curve based in part on whether the received data from the first unit and the received data from the second unit exceed a threshold and being an anomaly.

3. A system in accordance with claim 2, wherein said condition assessment device is further configured to store the new baseline parametric curve for use in at least one of monitoring operation of the first unit, and monitoring operation of the plurality of units.

4. A system in accordance with claim 2, wherein said condition assessment device is further configured to at least one of identify a data acquisition logical flag within the received data that indicates that a change has been made to the first unit, and determine that a change has been made to the first unit.

5. A system in accordance with claim 4, wherein said condition assessment device is further configured to at least one of:

identify a change that exceeds a predefined level in data associated with one of the plurality of data parameters;

identify changes in data associated with more than one of the plurality of data parameters; and

apply a logic rule to the data associated with the plurality of data parameters.

6. A system in accordance with claim 1, wherein said condition assessment device is further configured to calculate the new baseline parametric curve from a stored set of base functions and from the current environmental condition data received from the at least one selected source of data.

7. A system in accordance with claim 1, wherein the condition assessment device is further configured to determine whether to generate a new baseline parametric curve based on a fuzzy logic rule.

8. A method of maintaining a new baseline parametric curve representing normal operation of a first unit, wherein the first unit has a parametric curve associated with it that represents a baseline of normal operation, and wherein the first unit is one of a plurality of units included in an equipment fleet, said method comprising:

receiving a selection of at least one source of data related to the operation of the first unit, wherein the at least one source of data is associated with a plurality of sensors configured to sense data related to the operation of the first unit;

receiving data from each of the plurality of sensors, wherein the received data represents current conditions that the first unit is subject to;

determining, based on a determination that data exceeds a threshold and is an anomaly, whether to generate the new baseline parametric curve representing normal operation of the first unit, based in part on received data from at least two of said plurality of sensors exceeding a threshold and being an anomaly;

sampling, using a computer program embodied on a non-transitory computer readable medium, data associated with at least one data parameter from the received data; and

generating, based on the determination of whether to generate, the new baseline parametric curve by fitting a curve to the data associated with the at least one sampled data parameter.

9. A method in accordance with claim 8, wherein the plurality of units included in the fleet includes a second unit and a third unit, wherein the first and second units are located in a first geographic region, wherein the third unit is located in a second geographic region, and wherein each unit includes at least one sensor associated with at least one source of data, and wherein receiving data from the at least one selected source of data comprises:

receiving data from the first unit and the second unit; and

determining for the first unit whether to generate the new baseline parametric curve based in part on whether the received data from the first unit and the received data from the second unit exceed a threshold and is an anomaly.

10. A method in accordance with claim 8, further comprising storing the new baseline parametric curve for use in at least one of monitoring the operation of the first unit and monitoring the operation of the plurality of units.

11. A method in accordance with claim 8, wherein determining the new baseline parametric curve by fitting a curve to the data associated with the at least one sampled data parameter comprises calculating the new baseline parametric curve from a stored set of base functions and from the data received from the at least one selected source of data.

12. A method in accordance with claim 8, wherein determining whether to generate the new baseline parametric curve representing normal operation of the first unit is further based on a fuzzy logic rule.

13. A method in accordance with claim 8, wherein determining whether to generate the new baseline parametric curve comprises at least one of:

identifying a data acquisition logical flag within the received data that indicates that a change has been made to the first unit; and

determining that a change has been made to the first unit.

14. A method in accordance with claim 8, wherein sampling data associated with the at least one data parameter from the received data comprises sampling data associated with a plurality of data parameters from the received data, and wherein determining that a change has been made to the first unit comprises at least one of:

identifying a change that exceeds a predefined level in one of the plurality of data parameters;

identifying changes in more than one of the plurality of data parameters; and

applying a logic rule to the plurality of data parameters.

15. A method in accordance with claim 8, wherein receiving data comprises receiving data representing a schedule of maintenance performed on the first unit, and data representing usage of the first unit.

16. A condition assessment device for monitoring the operation of at least one of a plurality of units included within a fleet of units, wherein the at least one of the plurality of units has a parametric curve associated with it that represents a baseline of normal operation, said device comprising a processing device configured to store at least one code segment configured to instruct said processing device to:

receive a selection, from an input device, of at least one source of data related to the operation of at least one of the plurality of units, wherein the at least one source of data is associated with a plurality of sensors configured to sense data related to the operation of the at least one of the plurality of units;

receive data from each of the plurality of sensors associated with the at least one source of data, wherein the received data represents current conditions that each sensor of the plurality of sensors is subject to;

determine, based on a determination that data exceeds a threshold and is an anomaly, whether to generate a new baseline parametric curve representing normal operation of the at least one of the plurality of units, based in part on received data from at least two of said plurality of sensors exceeding a threshold and is an anomaly;

sample data associated with at least one data parameter from the received data; and

generate, based on the determination of whether to generate, a new baseline parametric curve from the data associated with the at least one sampled data parameter.

17. A device in accordance with claim 16, wherein the at least one code segment is configured to instruct said processing device to:

receive data from a first unit and a second unit of the plurality of units; and

determine for the first unit whether to generate the new baseline parametric curve based in part on whether the received data from the first unit and the received data from the second unit exceed the a threshold and is an anomaly.

18. A device in accordance with claim 17, wherein the at least one code segment is configured to instruct said processing device to store the new baseline parametric curve for use in at least one of monitoring the operation of said first unit, and monitoring the operation of the plurality of units.

19. A device in accordance with claim 16, wherein the at least one code segment is configured to instruct said processing device to calculate the new baseline parametric curve from a stored set of base functions and from the data received from said at least one selected source of data.

20. A device in accordance with claim 16, wherein the at least one code segment is configured to instruct said processing device to determine whether to generate a new baseline parametric curve based on a fuzzy logic rule.