Review of condition monitoring of rolling element bearing using vibration analysis and other techniques

C Malla, I Panigrahi - Journal of Vibration Engineering & Technologies, 2019 - Springer
Background Different types of machines having rotary component are linked together in
process industries, to perform the process of manufacturing. The failure of any single …

The application of downhole vibration factor in drilling tool reliability big data analytics—A review

Y Ren, N Wang, J Jiang, J Zhu… - … -ASME Journal of …, 2019 - asmedigitalcollection.asme.org
In the challenging downhole environment, drilling tools are normally subject to high
temperature, severe vibration, and other harsh operation conditions. The drilling activities …

A discrepancy analysis methodology for rolling element bearing diagnostics under variable speed conditions

S Schmidt, PS Heyns, KC Gryllias - Mechanical Systems and Signal …, 2019 - Elsevier
Performing condition monitoring on critical machines such as gearboxes is essential to
ensure that the machines operate reliably. However, many gearboxes are exposed to …

Multimodal anomaly detection for assistive robots

D Park, H Kim, CC Kemp - Autonomous Robots, 2019 - Springer
Detecting when something unusual has happened could help assistive robots operate more
safely and effectively around people. However, the variability associated with people and …

A fault diagnosis method of industrial robot rolling bearing based on data driven and random intuitive fuzzy decision

X Sun, X Jia - IEEE Access, 2019 - ieeexplore.ieee.org
The industrial robot is a mechanized electronic device that functions as a human arm, wrist
and hand. Rolling bearings are an essential part of these flexible rotation. Due to the harsh …

An open set recognition methodology utilising discrepancy analysis for gear diagnostics under varying operating conditions

S Schmidt, PS Heyns - Mechanical Systems and Signal Processing, 2019 - Elsevier
Historical fault data are often difficult and expensive to acquire, which can prohibit the
application of supervised learning techniques in the condition-based maintenance field …

Fault detection of anti-friction bearing using adaboost decision tree

SS Patil, VM Phalle - … Theories, Applications and Future Directions-Volume …, 2019 - Springer
In this paper, decision tree (DT) based AdaBoost technique is used for anti-friction bearing
(AFB) fault detection. Time-domain feature extracted from raw vibration signal and …

A deep learning approach towards diagnostics of bearings operating under non-stationary conditions

S Baggerohr - 2019 - search.proquest.com
Faults in bearings usually manifest as marginal defects that intensify over time, allowing for
well-informed preventative actions with early Fault Detection and Diagnosis (FDD) protocols …

Development of a decision support tool for day-to-day planning of operations and maintenance logistics for offshore wind farms

R Dawid - 2019 - stax.strath.ac.uk
The offshore wind industry has grown rapidly in the past decade. Hundreds of turbines are
being built in the North Sea every year. Maintenance of offshore assets is often hindered by …

[引用][C] 基于小波包和并行隐马尔科夫的风力机易损部件健康状态评价

郑小霞, 李美娜 - 太阳能学报, 2019