Patent
System and Method for Calculating Remaining Useful Time of Objects
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TLDR
In this paper, a system and method for predicting the remaining useful time of bearing components based on available condition monitoring data is presented, which can be used to determine which columns of input information are the most significant for bearing lifetime prediction.Abstract:
An aspect of the present invention is to provide a system and method for predicting the remaining useful time of mechanical components such as bearings. Another aspect of the present invention is to provide a system and method for predicting the remaining useful time of bearings based on available condition monitoring data. Another aspect of the present invention is to provide a system and method for automatically deciding which columns of input information are the most significant for predicting the remaining useful life of bearings. Another aspect of the present invention is to provide a system and method for performing an analysis of both test bearings and training bearings and determining which training bearings are most similar to a given test bearing. Another aspect of the present invention is to provide a system and method for training an artificial neural network.read more
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References
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Journal ArticleDOI
A neural network approach for remaining useful life prediction utilizing both failure and suspension histories
TL;DR: In this article, the authors developed an ANN approach utilizing both failure and suspension condition monitoring histories, which can be used for remaining useful life prediction of other equipments, and validated using vibration monitoring data collected from pump bearings in the field.
Journal ArticleDOI
A Neural Network Integrated Decision Support System for Condition-Based Optimal Predictive Maintenance Policy
TL;DR: The integrated system consists of a heuristic managerial decision rule for different scenarios of predictive and corrective cost compositions and can be applied in various industries and different kinds of equipment that possess well-defined degradation characteristics.
Journal ArticleDOI
A Neural Network Degradation Model for Computing and Updating Residual Life Distributions
Nagi Gebraeel,Mark Lawley +1 more
TL;DR: This paper focuses on the development of a neural network-based degradation model that utilizes condition-based sensory signals to compute and continuously update residual life distributions of partially degraded components.
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Ensembles of neural networks with different input sets
TL;DR: In this article, robust neural network ensembles are described as a log synthesis method that comprises: receiving a set of downhole logs, applying a first subset of downholes logs to a first neural network to obtain an estimated log; applying a second, different subset of the downholes to a second neural network, and combining the estimated logs to obtain a synthetic log.