FAILURE MODELING BY INCORPORATION OF TERRESTRIAL CONDITIONS

• US 20160283915A1
• Filed: 06/22/2015
• Published: 09/29/2016
• Est. Priority Date: 03/23/2015
• Status: Active Application

• Current Assignee: Utopus Insights, Inc. (Vestas Wind Systems A/S)
• Original Assignee: International Business Machines Corporation
• Inventors: Aggarwal, Aanchal, Kim, Younghun, Kumar, Tarun, Raman, Abhishek
• Application Number:
  US14/745,688
• Publication Number:
  US 20160283915A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/29 Geographical information databases
• CPC Class Codes: G06Q 10/0635 Risk analysis of enterprise or organisation activities
• CPC Class Codes: G06Q 10/1093 Calendar-based scheduling for persons or groups
• CPC Class Codes: G06Q 10/20 Administration of product repair or maintenance

Abstract

A system and method to schedule inspections for a plurality of assets at a corresponding plurality of outdoor locations are described. The method includes retrieving location attributes of each of the plurality of assets, retrieving terrestrial geotagged images that include one or more of the plurality of assets, obtaining parameters associated with each of the plurality of assets based on information from the images, and determining risk factors associated with each of the plurality of assets based on the associated parameters and a failure mapping. The method also includes determining a risk score for each of the plurality of assets based on the corresponding risk factors, and scheduling inspections of the plurality of assets based on the risk score associated with each of the plurality of assets.

Claims

1. A system to schedule inspection of a plurality of assets at a corresponding plurality of outdoor locations, the system comprising:

an input interface configured to obtain a selection of the plurality of assets;

a processor configured to obtain terrestrial geotagged images that include one or more of the plurality of assets, obtain parameters associated with each of the plurality of assets based on information from the images, determine risk factors associated with each of the plurality of assets based on the associated parameters and a failure mapping, and determine a risk score for each of the plurality of assets based on the corresponding risk factors; and

an output interface configured to output an inspection schedule for the plurality of assets based on their corresponding risk score.

2. The system according to claim 1, further comprising a memory device, wherein the processor obtains the images from the memory device.

3. The system according to claim 1, wherein the processor obtains the images from the input interface via a geographic information system (GIS) application.

4. The system according to claim 1, wherein the processor obtains the parameters based on the information from the images by parameterizing a distance from each of the plurality of assets to a corresponding nearest road and a distance from each of the plurality of assets to a corresponding nearest intersection.

5. The system according to claim 1, wherein the processor obtains the parameters based on the information from the images by parameterizing a ratio of a size of an area comprising woods, water, or grass to a total size of an area of the corresponding image.

6. The system according to claim 1, wherein the processor is further configured to determine risk points associated with each of the plurality of assets based on the associated parameters.

7. The system according to claim 6, wherein the processor determines the risk score of each of the plurality of assets based on the corresponding risk factors and the corresponding risk points of each of the plurality of assets.

8. The system according to claim 1, wherein the processor determines the failure mapping (F) based on inspecting and analyzing a set of assets.

9. The system according to claim 8, wherein the processor determines risk factors of the set of assets (R) and parameters of the set of assets (P) and solves for the failure mapping F by minimizing

|R−

FP|_p

wherein p indicates the norm.