ISSN 1507-2711
ISSN online 2956-3860

JOURNAL DOI: dx.doi.org/10.17531/ein

JCR Journal Profile


Członek(Member of): Europejskiej Federacji Narodowych Towarzystw Eksploatacyjnych  - European Federation of National Maintenance Societies  Wydawca(Publisher):Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne (Warszawa) - Polish Maintenance Society (Warsaw)   Patronat Naukowy(Scientific supervision): Polska Akademia Nauk o/Lublin  - Polish Akademy of Sciences Branch in Lublin  Członek(Member of): Europejskiej Federacji Narodowych Towarzystw Eksploatacyjnych  - European Federation of National Maintenance Societies


 We verify submissions originality with the use of iThenticate plagiarism checker


 All accepted articles are published Open Access under the Creative Commons Licence: CC-BY 4.0

Publisher:
Polish Maintenance Society
(Warsaw)

Scientific supervision:
Polish Academy of Sciences Branch in Lublin

Member of:
European Federation
of National Maintenance Societies


Attention!

In accordance with the requirements of citation databases, proper citation of publications appearing in our Quarterly should include the full name of the journal in Polish and English without Polish diacritical marks, i.e. "Eksploatacja i Niezawodnosc – Maintenance and Reliability".


 

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The average number of weeks from article submission to the final decision: 4 weeks




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MOST CITED

Update: 2021-07-01

1. COMPUTER-AIDED MAINTENANCE AND RELIABILITY MANAGEMENT SYSTEMS FOR CONVEYOR BELTS
By: Mazurkiewicz, Dariusz

EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY
Volume: 16   Issue: 3   Pages: 377-382   Published: 2014

Times Cited: 59
2. ON APPROACHES FOR NON-DIRECT DETERMINATION OF SYSTEM DETERIORATION
By: Valis, David; Koucky, Miroslav; Zak, Libor

EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY
Volume 14, Issue: 1   Pages: 33-41   Published: 2012

Times Cited: 53
3. A NEW FAULT TREE ANALYSIS METHOD: FUZZY DYNAMIC FAULT TREE ANALYSIS
By: Li, Yan-Feng; Huang, Hong-Zhong; Liu, Yu; et al.

EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY
Volume 14, Issue: 3 Pages: 208-214 Published: 2012

Times Cited: 51
4. INNOVATIVE METHODS OF NEURAL RECONSTRUCTION FOR TOMOGRAPHIC IMAGES IN MAINTENANCE OF TANK INDUSTRIAL REACTORS
By: Rymarczyk, Tomasz; Klosowski, Grzegorz

EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY
Volume: 21 Issue: 2 Pages: 261-267 Published: 2019

Times Cited: 50
5. APPLICATION OF NEURAL RECONSTRUCTION OF TOMOGRAPHIC IMAGES IN THE PROBLEM OF RELIABILITY OF FLOOD PROTECTION FACILITIES
By: Rymarczyk, Tomasz; Klosowski, Grzegorz

EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY
Volume: 20 Issue: 3 Pages: 425-434 Published: 2018

Times Cited: 45
6. ASSESSMENT MODEL OF CUTTING TOOL CONDITION FOR REAL-TIME SUPERVISION SYSTEM
By: Kozlowski, Edward; Mazurkiewicz, Dariusz; Zabinski, Tomasz; Prucnal, Slawomir; Sep, Jaroslaw

EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY
Volume: 21 Issue: 4 Pages: 679-685 Published: 2019

Times Cited: 40
7. PREDICTING THE TOOL LIFE IN THE DRY MACHINING OF DUPLEX STAINLESS STEEL
By: Krolczyk, Grzegorz; Gajek, Maksymilian; Legutko, Stanislaw

EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY
Volume: 15 Issue: 1 Pages: 62-65 Published: 2013

Times Cited: 39
8. MAINTENANCE DECISION MAKING BASED ON DIFFERENT TYPES OF DATA FUSION
By: Galar, Diego; Gustafson, Anna; Tormos, Bernardo; et al.
EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY 
Volume 14, Issue: 2   Pages: 135-144   Published:2012

Times Cited: 38
9. TESTS OF EXTENDABILITY AND STRENGTH OF ADHESIVE-SEALED JOINTS IN THE CONTEXT OF DEVELOPING A COMPUTER SYSTEM FOR MONITORING THE CONDITION OF BELT JOINTS DURING CONVEYOR OPERATION
By: Mazurkiewicz, Dariusz

EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY
Issue: 3 Pages: 34-39 Published: 2010

Times Cited: 37
10. RELIABILITY ANALYSIS OF RECONFIGURABLE MANUFACTURING SYSTEM STRUCTURES USING COMPUTER SIMULATION METHODS
By: Gola, Arkadiusz

EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY
Volume 21, Issue: 1, Pages: 90-102, Published: 2019

Times Cited: 36

 

 



Task „Implementation of procedures ensuring  the originality of scientific papers published in the quarterly „Eksploatacja i Niezawodność – Maintenance and Reliability” financed under contract 532/P-DUN/2018 from the funds of the Minister of Science and Higher Education for science dissemination activities.


Shigang Zhang

An anomaly detection method based on random convolutional kernel and isolation forest for equipment state monitoring

Anomaly detection plays an essential role in health monitoring and reliability assurance of complex system. However, previous researches suffer from distraction by outliers in training and extensively relying on empiric-based feature engineering, leading to many limitations in the practical application of detection methods. In this paper, we propose an unsupervised anomaly detection method that combines random convolution kernels with isolation forest to tackle the above problems in equipment state monitoring. The random convolution kernels are applied to generate cross-dimensional and multi-scale features for multi-dimensional time series, with combining the time series decomposing method to select abnormally sensitive features for automatic feature extraction. Then, anomaly detection is performed on the obtained features using isolation forests with low requirements for purity of training sample. The verification and comparison on different types of datasets show the performance of the proposed method surpass the traditional methods in accuracy and applicability.


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