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Estimating remaining useful life using genetic programming

A life and sensor technology, applied in the field of estimating RUL, can solve problems such as difficulties and difficulties in the service life of penetrating components

Inactive Publication Date: 2015-05-13
SIEMENS AG
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, even if identified, it can be difficult to accurately gauge when a failure is imminent from these predictive features down to the moment of failure
Therefore, feature selection is based primarily on engineering judgment, and it can be difficult to accurately estimate the RUL throughout the lifetime of the component

Method used

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  • Estimating remaining useful life using genetic programming
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  • Estimating remaining useful life using genetic programming

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Embodiment Construction

[0032] In describing the embodiments of the invention illustrated in the drawings, specific terminology is used for the sake of clarity. However, the invention is not intended to be limited to the specific terms so selected, but it is to be understood that each specific element includes all technical equivalents operating in a similar manner.

[0033] Embodiments of the present invention seek to automate the selection of predictive features that can be used to accurately estimate the remaining useful life (RUL) throughout the entire useful life of a component of an electromechanical machine. This selection can be based on the principles of genetic programming, where different predictive feature candidates can be tried, their suitability can be measured, and the feature candidates are recursively modified as the measured suitability is optimized. However, when none of the feature candidates reach the predefined suitability threshold even after a significant number of recursive ...

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Abstract

A method for estimating a remaining useful life of a system includes monitoring sensor data from sensors deployed within a system. A plurality of features are extracted from the sensor data. Tree graphs are generated including mathematical operators and features as nodes and a advanced feature is produced from each of the tree graphs by transforming the tree graphs into equations. A recursive operation including analyzing a fitness of each of the advanced features, performing crossover / mutation on the tree graphs, producing advanced features from the altered tree graphs, and analyzing the fitness of the altered tree graphs to produce at least one final advanced feature is performed. A remaining useful life of the system is calculated based on the final advanced feature.

Description

[0001] Cross References to Related Applications [0002] This application is based on Provisional Application Serial No. 61 / 678,742, filed August 2, 2012, the entire contents of which are hereby incorporated by reference. technical field [0003] The present invention relates to estimating remaining useful life (RUL), and more particularly, to estimating RUL from predictive features discovered using genetic programming. Background technique [0004] Components of electromechanical machines often require unscheduled maintenance or replacement. Performing maintenance and replacement too often can result in higher maintenance costs and avoidable service interruptions, while performing maintenance and replacement too late can lead to failures with potentially catastrophic consequences. Therefore, it is important to estimate with high precision when maintenance / replacement should be performed. [0005] In determining when a component should be serviced, the remaining useful lif...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/28
CPCG01M13/00G05B23/0283G06N3/126G01M99/00
Inventor 廖林峡Z.埃德蒙森
Owner SIEMENS AG