Online System Prognostics with Ensemble Models and Evolving Clustering

نویسندگان

چکیده

An online evolving clustering (OEC) method equivalent to ensemble modeling is proposed tackle prognostics problems of learning and the prediction remaining useful life (RUL). During phase, OEC extracts predominant operating modes as multiple clusters (EC). Each EC associated with its own Weibull distribution-inspired degradation (survivability) model that will receive incremental modifications signals become available. Example case studies from machining (drilling) automotive brake-pad wear are used validate effectiveness method.

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

The ensemble clustering with maximize diversity using evolutionary optimization algorithms

Data clustering is one of the main steps in data mining, which is responsible for exploring hidden patterns in non-tagged data. Due to the complexity of the problem and the weakness of the basic clustering methods, most studies today are guided by clustering ensemble methods. Diversity in primary results is one of the most important factors that can affect the quality of the final results. Also...

متن کامل

Online Evolving Clustering of Web Documents

In this paper an approach that is using evolving, incremental (on-line) clustering to automatically group relevant Web-based documents is proposed. It is centred on a recently introduced evolving fuzzy rule-based clustering approach and borrows heavily from the Nature in the sense that it is evolution-inspired. That is, the structure of the clusters and their number is not predefined, but it se...

متن کامل

A new ensemble clustering method based on fuzzy cmeans clustering while maintaining diversity in ensemble

An ensemble clustering has been considered as one of the research approaches in data mining, pattern recognition, machine learning and artificial intelligence over the last decade. In clustering, the combination first produces several bases clustering, and then, for their aggregation, a function is used to create a final cluster that is as similar as possible to all the cluster bundles. The inp...

متن کامل

A Framework for Online Clustering Based on Evolving Semi-Supervision

The huge amount of currently available data puts considerable constraints on the task of information retrieval. Automatic methods to organize data, such as clustering, can be used to help with this task allowing timely access. Semi-supervised clustering approaches employ some additional information to guide the clustering performed based on data attributes to a more suitable data partition. How...

متن کامل

An Evolving Neuro-Fuzzy System with Online Learning/Self-learning

A new neuro-fuzzy system’s architecture and a learning method that adjusts its weights as well as automatically determines a number of neurons, centers’ location of membership functions and the receptive field’s parameters in an online mode with high processing speed is proposed in this paper. The basic idea of this approach is to tune both synaptic weights and membership functions with the hel...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Machines

سال: 2022

ISSN: ['2075-1702']

DOI: https://doi.org/10.3390/machines11010040