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Overview of Equipment Health State Estimation and Remaining Life Prediction Methods

Jingyi Zhao, Chunhai Gao, Tao Tang, Xiao Xiao, Ming Luo, Binbin Yuan
2022 Machines  
These two technologies can provide a basis for condition-based maintenance and predictive maintenance of equipment, respectively.  ...  This work provides guidance for the selection of industrial equipment health assessment and remaining life prediction methods.  ...  [77] . ( 2) Deep learning The research on equipment remaining life prediction methods based on deep learning mainly include: methods based on deep neural network (DNN), methods based on deep belief  ... 
doi:10.3390/machines10060422 fatcat:smujjv2wnnbxtmeqj373wvqoii

Predictive Maintenance in the Automotive Sector: A Literature Review

Fabio Arena, Mario Collotta, Liliana Luca, Marianna Ruggieri, Francesco Gaetano Termine
2021 Mathematical and Computational Applications  
With the introduction of big data, it is possible to prevent potential failures and estimate the remaining useful life of the equipment by developing advanced mathematical models and artificial intelligence  ...  It provides a summary on these approaches, their main results, challenges, and opportunities, and it supports new research works for vehicle predictive maintenance.  ...  For this purpose, a novel deep learning architecture called a merged-LSTM (M-LSTM) network is proposed to build a TBF prediction model based on multisource data.  ... 
doi:10.3390/mca27010002 fatcat:sgr35l7wxjdhnda23myr7sekwa

Author Index

2020 2020 Global Reliability and Prognostics and Health Management (PHM-Shanghai)  
Research of Highly Accelerated Life Test on Civil Aircraft Airborne Equipment Lu, Minglei A Hyper-ellipsoidal Support Vector Data Description Incremental Learning Method for Bearing Direct Remaining Useful  ...  Matching for the Visual Odometry [280115] Kinematics Analysis and Simulation Verification for the Chassis of Mobile Robots Based on an Liu, Yajie A Deep Learning Method with Ensemble Learning for Capacity  ... 
doi:10.1109/phm-shanghai49105.2020.9280995 fatcat:7fprwk7zu5gx5gxehsto72ue3y

Author Index

2021 2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)  
Bi, Xinjie Visibility Graph based Feature Extraction for Fault Diagnosis of Rolling Bearings [570256] Bin, Jie Optimization Method of Virtual Sand Table Background Server Based on Unity 3D [571175] C  ...  RUSHAP: A Unified Approach to Interpret Deep Learning Model for Remaining Useful Life Estimation [570283] Liu, Li Design of Human Resource Management Information System Based on Decision Tree Algorithm  ...  570312] Yang, Yongsheng RUSHAP: A Unified Approach to Interpret Deep Learning Model for Remaining Useful Life Estimation [570283] Knowledge Graph Construction for Fault Diagnosis of Aircraft Environmental  ... 
doi:10.1109/phm-nanjing52125.2021.9612757 fatcat:h4xp5wbdvjdpvmsri2dktwupbi

A deep adversarial approach based on multi-sensor fusion for remaining useful life prognostics [article]

David Verstraete, Enrique Droguett, Mohammad Modarres
2019 arXiv   pre-print
We find that using the deep adversarial based approach results in higher performing remaining useful life predictions.  ...  These systems handle big machinery data and multi-sensor fusion and integrate remaining useful life prognostic capabilities. We introduce a deep adversarial learning approach to damage prognostics.  ...  We find that using the deep adversarial based approach results in higher performing remaining useful life predictions.  ... 
arXiv:1909.10246v2 fatcat:6llmsesznbhshkqfbpaobdncti

Proactive Maintenance Strategy Based on Resilience Empowerment for Complex Buildings [chapter]

Francesco Rota, Maria Cinzia Luisa Talamo, Giancarlo Paganin
2020 Smart Innovation, Systems and Technologies  
in the direction of a proactive maintenance approach.  ...  In this perspective, maintenance is therefore a key factor to assure building resilience by keeping systems and equipment in the required operational state.  ...  Benkedjouh et al. (2018) Sensor data Prediction of wear in milling operations CWT Data-driven prognostic method based on Bayesian approaches for direct remaining useful life prediction.  ... 
doi:10.1007/978-3-030-52869-0_21 fatcat:4dgcbwsennbgxekozpdjzs4d3q


Delanyo Kwame Bensah Kulevome, Hong Wang, Xuegang Wang
2021 Progress In Electromagnetics Research C  
remaining useful life (RUL).  ...  In this paper, we explore a new approach to implementing prognostics and health management (PHM) for electrolytic capacitors and propose a method of estimating the SOH leading to the prediction of the  ...  to monitor the degeneration of these components and estimate the remaining useful life (RUL).  ... 
doi:10.2528/pierc20120201 fatcat:kixnspevsrgmrlywjh6e3kgmc4

PHM-Qingdao 2019 Author Index

2019 2019 Prognostics and System Health Management Conference (PHM-Qingdao)  
construction method based on deep belief network for remaining useful life prediction Remaining Useful Life Prediction for Aircraft Engines Based on Grey Model [2 01 9 1 2 6 ] Peng, Rui Optimal preventive  ...  remaining useful life prediction [2019293] A similarity-based and model-based fusion prognostics framework for remaining useful life Bearing fault diagnosis based on adaptive variational mode decomposition  ... 
doi:10.1109/phm-qingdao46334.2019.8942830 fatcat:foexkfircjhvbocvagfdhddsjm

A Systematic Review on Predicting and Forecasting the Electrical Energy Consumption in the Manufacturing Industry

Jessica Walther, Matthias Weigold
2021 Energies  
This paper presents a systematic review of state-of-the-art of existing approaches to predict or forecast the energy consumption in the manufacturing industry.  ...  In the context of the European Green Deal, the manufacturing industry faces environmental challenges due to its high demand for electrical energy.  ...  The broadest concept Artificial Intelligence (AI) encompasses the two sub-fields Machine Learning (ML) and Deep Learning (DL), while Deep Learning (DL) is again a sub-field of Machine Learning (ML).  ... 
doi:10.3390/en14040968 fatcat:yawpatncdjfy7lqpgouwbtwvce

A Deep Learning Approach to the Transformer Life Prediction Considering Diverse Aging Factors

Lanfei He, Lie Li, Ma Li, Zhiwei Li, Xiao Wang
2022 Frontiers in Energy Research  
We developed a deep learningbased approach using a convolutional neural network for effective equipment life prediction.  ...  Combining with the average life of the equipment, the extracted features are used as indicators for the transformer reliability evaluations.  ...  AI-BASED APPROACH TO THE LIFE PREDICTION MODEL Convolutional Neural Network In recent years, with the rapid development of the computer field, deep learning has been applied to all aspects.  ... 
doi:10.3389/fenrg.2022.930093 fatcat:37fnzassizfpjelq2sf2nkal44

Classification prognostics approaches in aviation

Marcia L. Baptista, Elsa M.P. Henriques, Helmut Prendinger
2021 Measurement (London)  
Traditionally, prognostics approaches to predictive maintenance have focused on estimating the remaining useful life of the equipment.  ...  Abstract Traditionally, prognostics approaches to predictive maintenance have focused on estimating the remaining useful life of the equipment.  ...  Figure 1 : 1 Taxonomy of prognostics approaches. We distinguish between prognostics based on remaining useful life prediction and fault detection.  ... 
doi:10.1016/j.measurement.2021.109756 fatcat:67q3owko3vdk3lqztx3dnjahme

A Systematic Mapping of the Advancing Use of Machine Learning Techniques for Predictive Maintenance in the Manufacturing Sector

Milena Nacchia, Fabio Fruggiero, Alfredo Lambiase, Ken Bruton
2021 Applied Sciences  
In particular, based on predictive approach and facilitated by the nowadays growing capabilities of hardware, cloud-based solutions, and new learning approaches, maintenance can be scheduled—over cell  ...  Vibrational signal was marked as the most used data set for diagnosis in manufacturing machinery monitoring; furthermore, supervised learning is reported as the most used predictive approach (ensemble  ...  wear prediction, degradation prediction, failure prediction, Prognostics technique, Remaining Useful Life Prediction, fault detection, real-time Quality Predictive Maintenance Assessment, anomaly detection  ... 
doi:10.3390/app11062546 fatcat:ywelin4a5nbtnh3nm65wqnbsfu

Remaining Useful Life Estimation for Systems with Abrupt Failures

Wei Huang, Hamed Khorasgani, Chetan Gupta, Ahmed Farahat, Shuai Zheng
2018 Proceedings of the Annual Conference of the Prognostics and Health Management Society, PHM  
Data-driven Remaining Useful Life (RUL) estimation for systems with abrupt failures is a very challenging problem.  ...  As a case study, we apply the proposed method for RUL estimation in 2018 PHM Data Challenge.  ...  Remaining useful life estimation using long short-term memory deep learning.  ... 
doi:10.36001/phmconf.2018.v10i1.590 fatcat:f2ychssobfa6bgxtal77bbo3iq

Method for a cloud based remaining-service-life-prediction for vehicle-gearboxes based on big-data-analysis and machine learning

Daniel Vietze, Michael Hein, Karsten Stahl
2020 Forschung im Ingenieurwesen  
Within this method big-data and machine-learning approaches are used. The method is designed in a way, enabling an easy transfer to other machine elements and kinds of machinery.  ...  Most vehicle-gearboxes operating today are designed for a limited service-life.  ...  The damage can be calculated using a damage accumulation hypothesis or a machine learning based approach (see Sect. 4).  ... 
doi:10.1007/s10010-020-00415-0 fatcat:34rjp6gx45hhvkxdxn4s5saxwm

Learning analytics for IoE based educational model using deep learning techniques: architecture, challenges and applications

Mohd Abdul Ahad, Gautami Tripathi, Parul Agarwal
2018 Smart Learning Environments  
This paper presents a secured and agile architecture of an Internet of Everything (IoE) based Educational Model and a Learning Analytics System (LAS) model using the concept of deep learning which can  ...  Finally a feature wise comparison is provided between the proposed Learning Analytics (LA) based approach and conventional teaching-learning approach in terms of performance parameters like cognition,  ...  Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Received: 16 June 2018 Accepted: 26 July 2018  ... 
doi:10.1186/s40561-018-0057-y fatcat:gil33ymdz5ctfaa4c5gcgy527m
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