scholarly journals Methods of Hidden Periodicity Discovering for Gearbox Fault Detection

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6138
Author(s):  
Ihor Javorskyj ◽  
Ivan Matsko ◽  
Roman Yuzefovych ◽  
Oleh Lychak ◽  
Roman Lys
Keyword(s):  
Fault Detection ◽  
Covariance Structure ◽  
Random Processes ◽  
Wind Turbine Gearbox ◽  
Practical Applications ◽  
Stochastic Recurrence ◽  
Amplitude Spectra ◽  
Gearbox Vibration ◽  
Time Changes ◽  
Periodically Correlated Random Processes

It is shown that the models of gear pair vibration, proposed in literature, are particular cases of the bi-periodically correlated random processes (BPCRPs), which describe its stochastic recurrence with two periods. The possibility of vibration and analysis within the framework of BPCRP approximation, in the form of periodically correlated random processes (PCRPs), is grounded and the implementation of vibration processing procedures using PCRP techniques, which are worked out by the authors, is given. Searching for hidden periodicities of the first and the second orders was considered as the main issue of this approach. The estimation of the non-stationary period (basic frequency) allowed us to carry out a detailed analysis of the deterministic part, the covariance structure of the stochastic part, and to form, using their parameters, the sensitive indicators for fault detection. The results of the processing of the wind turbine gearbox vibration signals are presented. The amplitude spectra of the deterministic oscillations and the time changes of the stochastic part power for different fault stages are analyzed. The most efficient indicators, which are formed using the amplitude spectra for practical applications, are proposed. The presented approach was compared with known in literature cyclostationary analysis and envelope techniques, and its advantages are shown.

scholarly journals Fault severity detection of a worm gearbox based on several feature extraction methods through a developed condition monitoring system

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Berkan Hızarcı ◽  
Rafet Can Ümütlü ◽  
Zeki Kıral ◽  
Hasan Öztürk
Keyword(s):  
Fault Detection ◽  
Condition Monitoring ◽  
Extraction Methods ◽  
Poincaré Plot ◽  
Vibration Data ◽  
Sliding Motion ◽  
Fault Severity ◽  
Fault Features ◽  
Gearbox Vibration ◽  
Condition Monitoring System

AbstractThis study presents the severity detection of pitting faults on worm gearbox through the assessment of fault features extracted from the gearbox vibration data. Fault severity assessment on worm gearbox is conducted by the developed condition monitoring instrument with observing not only traditional but also multidisciplinary features. It is well known that the sliding motion between the worm gear and wheel gear causes difficulties about fault detection on worm gearboxes. Therefore, continuous monitoring and observation of different types of fault features are very important, especially for worm gearboxes. Therefore, in this study, time-domain statistics, the features of evaluated vibration analysis method and Poincaré plot are examined for fault severity detection on worm gearbox. The most reliable features for fault detection on worm gearbox are determined via the parallel coordinate plot. The abnormality detection during worm gearbox operation with the developed system is performed successfully by means of a decision tree.

scholarly journals Electrostatic Sensor Application for On-Line Monitoring of Wind Turbine Gearboxes

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3574 ◽  
Author(s):  
Huijie Mao ◽  
Hongfu Zuo ◽  
Han Wang
Keyword(s):  
Wind Turbine ◽  
Wear Debris ◽  
Bench Test ◽  
Recognition Method ◽  
Wind Turbine Gearbox ◽  
Practical Applications ◽  
Electrostatic Induction ◽  
Oil Flow ◽  
On Line ◽  
Application Potential

The oil-line electrostatic sensor (OLES) is a new online monitoring technology for wear debris based on the principle of electrostatic induction that has achieved good measurement results under laboratory conditions. However, for practical applications, the utility of the sensor is still unclear. The aim of this work was to investigate in detail the application potential of the electrostatic sensor for wind turbine gearboxes. Firstly, a wear debris recognition method based on the electrostatic sensor with two-probes is proposed. Further, with the wind turbine gearbox bench test, the performance of the electrostatic sensor and the effectiveness of the debris recognition method are comprehensively evaluated. The test demonstrates that the electrostatic sensor is capable of monitoring the debris and indicating the abnormality of the gearbox effectively using the proposed method. Moreover, the test also reveals that the background signal of the electrostatic sensor is related to the oil temperature and oil flow rate, but has no relationship to the working conditions of the gearbox. This research brings the electrostatic sensor closer to practical applications.

The Effect of Directional Spreading on Interaction of Focused Wave Groups With a Cylinder

2004 ◽  
Author(s):  
Eugeny V. Buldakov ◽  
Rodney Eatock Taylor ◽  
Paul H. Taylor
Keyword(s):  
Numerical Solutions ◽  
Amplitude Spectrum ◽  
Wave Group ◽  
Helmholtz Equations ◽  
Incoming Wave ◽  
Wave Groups ◽  
Practical Applications ◽  
Amplitude Spectra ◽  
Focused Wave ◽  
Focused Wave Group

The problem of diffraction of a directionally spread focused wave group by a bottom-seated circular cylinder is considered from the view point of second-order perturbation theory. After applying the time Fourier transform and separation of vertical variable the resulting two-dimensional non-homogeneous Helmholtz equations are solved numerically using finite differences. Numerical solutions of the problem are obtained for JONSWAP amplitude spectra for the incoming wave group with various types of directional spreading. The results are compared with the corresponding results for a unidirectional wave group of the same amplitude spectrum. Finally we discuss the applicability of the averaged spreading angle concept for practical applications.

The Effect of Operational Parameters on Vibration Signals of Wind Turbine Gearboxes

2019 ◽  
Author(s):  
Sofia Koukoura ◽  
Eric Bechhoefer ◽  
James Carroll ◽  
Alasdair McDonald
Keyword(s):  
Wind Turbine ◽  
Operating Conditions ◽  
Operating Costs ◽  
Normal Operation ◽  
Operational Parameters ◽  
Wind Turbine Gearbox ◽  
Vibration Signals ◽  
Gearbox Vibration ◽  
Maintenance Decisions ◽  
Yaw Angle

Abstract Vibration signals are widely used in wind turbine drivetrain condition monitoring with the aim of fault detection, optimization of maintenance actions and therefore reduction of operating costs. Signals are most commonly sampled by accelerometers at high frequency for a few seconds. The behavior of these signals varies significantly, even within the same turbine and depends on different parameters. The aim of this paper is to explore the effect of operational and environmental conditions on the vibration signals of wind turbine gearboxes. Parameters such as speed, power and yaw angle are taken into account and the change in vibration signals is examined. The study includes examples from real wind turbines of both normal operation and operation with known gearbox faults. The effects of varying operating conditions are removed using kalman filtering as a state observer. The findings of this paper will aid in understanding wind turbine gearbox vibration signals, making more informed decisions in the presence of faults and improving maintenance decisions.

scholarly journals The Effect of Parallel-Axis Helix Gear Pair on Wind Turbine Gearbox Vibration Control

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Zheng Li ◽  
Tianhe Zhang ◽  
Yang Chen ◽  
Lijuan Song
Keyword(s):  
Wind Turbine ◽  
Helix Angle ◽  
Drive Train ◽  
Gear Pair ◽  
Wind Turbine Gearbox ◽  
Multibody Dynamic ◽  
Gearbox Vibration ◽  
Basic Parameters ◽  
Parallel Axis

This article studies the effects of some basic parameters of a parallel-axis helix gear stage on wind turbine gearbox vibration in a case study: a multibody dynamic model is constructed to simulate the drive train of a faulted multistage wind turbine gearbox with serious vibrations. The significant vibration behaviour of the drive train for typical excitations is calculated, and the results according to specified geometric parameters of the gears are analysed in detail to investigate effective solutions for vibration reduction. The results indicate that the helix angle and numbers of teeth of a gear pair are the most significant factors for solving the problem. The effectiveness of the proposed solutions and relevant mechanisms are discussed and validated by a prototype vibration test.

Fault detection of planetary subassemblies in a wind turbine gearbox using TQWT based sparse representation

2021 ◽  
Vol 490 ◽  
pp. 115707
Author(s):  
Wei Teng ◽  
Yiming Liu ◽  
Yike Huang ◽  
Lei Song ◽  
Yibing Liu ◽  
...  
Keyword(s):  
Fault Detection ◽  
Wind Turbine ◽  
Sparse Representation ◽  
Wind Turbine Gearbox
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