Computerized Fluid Analysis for Determining Whether an Asset is Likely to Have a Fluid Issue

• US 20170292940A1
• Filed: 04/06/2016
• Published: 10/12/2017
• Est. Priority Date: 04/06/2016
• Status: Abandoned Application

• Current Assignee: Uptake Technologies, Inc.
• Original Assignee: Uptake Technologies, Inc.
• Inventors: Pandey, Aparna, Horrell, Michael, Gutfraind, Alexander
• Application Number:
  US15/092,593
• Publication Number:
  US 20170292940A1
• Time in Patent Office: Days
• CPC Class Codes: G01N 2035/00702 Curve-fitting; Parameter matching; Calibration constants
• CPC Class Codes: G01N 2035/00891 Displaying information to the operator
• CPC Class Codes: G01N 33/2888 Lubricating oil characteristics, e.g. deterioration lubricating properties G01N33/30
• CPC Class Codes: G01N 35/00584 Control arrangements for automatic analysers
• CPC Class Codes: G01N 35/00871 Communications between instruments or with remote terminals
• CPC Class Codes: G06F 2113/08 Fluids
• CPC Class Codes: G06F 2119/02 Reliability analysis or reliability optimisation; Failure analysis, e.g. worst case scenario performance, failure mode and effects analysis [FMEA]
• CPC Class Codes: G06F 30/27 using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model

Abstract

Disclosed herein are systems, devices, and methods related to a determination of whether an asset has a fluid issue. In particular, examples involve a platform defining a predictive model for outputting an indicator of whether an asset is likely to have a fluid issue based at least on historical fluid data for one or more assets. The historical fluid data may comprise at least one of a plurality of fluid reports for the one or more assets and an indication of a fluid issue for each fluid report. The platform may receive at least one fluid report associated with a given asset and based at least on the predictive model and the received at least one fluid report, make a determination that the given asset is likely to have a fluid issue. The platform may cause a computing device to output an indication of the determination.

Claims

1. A method comprising:

based at least on historical fluid data for one or more assets, defining a predictive model for outputting an indicator of whether an asset is likely to have a fluid issue, wherein the historical fluid data comprises at least one of (i) a plurality of fluid reports associated with the one or more assets and (ii) a plurality of indications, wherein each indication identifies whether an asset of the one or more assets has a fluid issue;

receiving at least one fluid report associated with a given asset;

based at least on the predictive model and the received at least one fluid report, making a determination that the given asset is likely to have a fluid issue; and

causing a computing device to output an indication of the determination.

2. The method of claim 1, wherein the indication of a fluid issue is determined based on an expert review of the fluid report.

3. The method of claim 1, wherein defining the predictive model comprises applying a regression technique to the historical fluid data.

4. The method of claim 1, wherein the historical fluid data comprises one or more of (i) a plurality of fluid reports for a same type of fluid;

(ii) a plurality of fluid reports for a same type of the given asset;

(iii) a plurality of fluid reports for the given asset; and

(iv) a plurality of fluid reports for a same type of subsystem of the given asset.

5. The method of claim 1, wherein each of the fluid reports comprises a plurality of fluid properties.

6. The method of claim 5, wherein the fluid properties comprises a particle count of particles in a fluid.

7. The method of claim 1, wherein each fluid report is for a given type of fluid taken from the given asset.

8. The method of claim 1, wherein the plurality of fluid reports comprises a sequence of fluid reports for the given asset.

9. The method of claim 1, wherein causing a computing device to output an indication of the determination comprises causing a computing device to display the determination on a display screen.

10. The method of claim 1, wherein making a determination that the given asset is likely to have a fluid issue based at least on the predictive model and the received at least one fluid report comprises:

applying the predictive model to the received at least one fluid report to output an indicator of whether the given asset is likely to have a fluid issue;

comparing the indicator to a threshold condition; and

determining that the indicator exceeds the threshold condition.

11. The method of claim 1, further comprising causing the computing device to output an indication of those properties of a given type of fluid of the given asset which influence the determination that the given asset is likely to have the fluid issue.

12. The method of claim 1, wherein the received at least one fluid report defines a plurality of properties of a fluid and a measure associated with each property, the method further comprising:

selecting a given property of the received at least one fluid report;

changing a given measure of the given property in the at least one fluid report;

making a determination that changing the given measure causes a probability that the given asset has the fluid issue to change by a threshold amount; and

causing the computing device to output an indication of the given property.

13. A platform comprising:

a network interface configured to facilitate communication with a data source and a computing device via a communication network;

at least one processor;

a non-transitory computer-readable medium; and

program instructions stored on the non-transitory computer-readable medium that are executable by the at least one processor to cause the platform to;

receive at least one fluid report associated with a given asset;

based at least on a predictive model which outputs an indicator of whether an asset is likely to have a fluid issue and the received at least one fluid report, make a determination that the given asset is likely to have a fluid issue, wherein the predictive model is defined based at least on historical fluid data for one or more assets received from the data source, wherein the historical fluid data comprises at least one of (i) a plurality of fluid reports associated with the one or more assets and (ii) a plurality of indications, wherein each indication identifies whether an asset of the one or more assets has a fluid issue; and

cause the computing device to output an indication of the determination.

14. The platform of claim 13, wherein the plurality of fluid reports comprises a time sequence of fluid reports for the given asset.

15. The platform of claim 13, wherein the program instructions for causing a computing device to output an indication of the determination comprises causing the computing device to display the determination on a display screen.

16. The platform of claim 13, wherein the historical fluid data comprises one or more of (i) a plurality of fluid reports for a same type of fluid;

(ii) a plurality of fluid reports for a same type of the given asset;

(iii) a plurality of fluid reports for the given asset; and

(iv) a plurality of fluid reports for a same type of subsystem of the given asset.

17. The platform of claim 13, wherein the program instructions for making a determination that the given asset is likely to have a fluid issue based at least on the predictive model and the received at least one fluid report comprises program instructions for:

applying the predictive model to the received at least one fluid report to output an indicator of whether the given asset is likely to have a fluid issue;

comparing the indicator to a threshold condition; and

determining that the indicator exceeds the threshold condition.

18. The platform of claim 13, further comprising program instructions for causing the computing device to output an indication of how properties of a given type of fluid in the given asset compare to properties of the given type of fluid in other assets based on the historical fluid data.

19. The platform of claim 13, wherein the received at least one fluid report defines a plurality of properties of a fluid and a measure associated with each property, the platform further comprising program instructions for:

selecting a given property of the received at least one fluid report;

changing a given measure of the given property in the at least one fluid report;

making a determination that changing the given measure causes a probability that the given asset has the fluid issue to change by a threshold amount; and

causing the computing device to output an indication of the given property.

20. A non-transitory computer-readable medium having instructions stored thereon that are executable to cause a platform to:

receive at least one fluid report associated with a given asset;

based at least on a predictive model which outputs an indicator of whether an asset is likely to have a fluid issue and the received at least one fluid report, make a determination that the given asset is likely to have a fluid issue, wherein the predictive model is defined based at least on historical fluid data for one or more assets received from a data source, wherein the historical fluid data comprises at least one of (i) a plurality of fluid reports associated with the one or more assets and (ii) a plurality of indications, wherein each indication identifies whether an asset of the one or more assets has a fluid issue; and

cause a computing device to output an indication of the determination.