Novel adaptation of the demodulation technology for gear damage detection to variable amplitudes of mesh harmonics

Combet, François; Gelman, Leonid M.

doi:10.1016/j.ymssp.2010.07.008

Cited by 24 publications

(15 citation statements)

References 13 publications

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“…In addition, a sideband ratio was also calculated using Equation (7); this normalizes the sideband ratio by the gear mesh frequency peak. Prior work by Combet et al [31] has shown this sideband ratio feature to be an effective metric to quantify gear health since it is less susceptible to load fluctuations due to the sideband magnitude being divided by the gear mesh frequency peak [31]. Table 6.2 provides a listing of the frequency domain gear features; a total of 16 were calculated.…”

Section: Frequency Domain Methodsmentioning

confidence: 99%

Wind Turbine Gearbox Condition Monitoring Round Robin Study - Vibration Analysis

Sheng¹

2012

112

107

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NOTICEThis report was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States government or any agency thereof. Executive SummaryUtility-scale wind turbines have historically experienced premature component failures, which subsequently increase the cost of energy. The majority of these failures are caused by faults in the drivetrain, led by the main gearbox. To understand the possible causes for gearbox failures and recommend practices for improvement, the National Wind Technology Center (NWTC), at the National Renewable Energy Laboratory (NREL), started a project called the Gearbox Reliability Collaborative (GRC). Condition Monitoring (CM) is one research area under the GRC. It is a method to assess a system's health, which enables proactive maintenance planning, reduces downtime and operations and maintenance costs, and, to some extent, increases safety.To understand the dynamic responses of wind turbine gearboxes under different loading conditions, the GRC tested two identical gearboxes. One was tested on the NWTC's 2.5 MW dynamometer and the other was first tested in the dynamometer, and then field tested in a turbine in a nearby wind plant. In the field, the test gearbox experienced two oil loss events that resulted in damage to its internal bearings and gears. Since the damage was not catastrophic, the test gearbox was removed from the field and retested in the NWTC's dynamometer before it was disassembled. During the dynamometer retest, various condition monitoring systems, e.g., vibration and oil debris, collected data along with testing condition information. The vibrationbased condition monitoring system and the test condition data enabled NREL to launch a Wind Turbine Gearbox Condition Monitoring Round Robin project, as described in this report. The main objective of this project is to evaluate different vibration analysis algorithms used in wind turbine CM and determine whether typical practices are effective. With the involvement of both academic researchers and industrial partners, the Round Robin provides cutting edge research results to industry stakeholders.Under this project, the collected vibration and testing condition data, along with the test gearbox configuration information, were shared with partners who signed memoranda of understand...

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Section: Frequency Domain Methodsmentioning

confidence: 99%

Wind Turbine Gearbox Condition Monitoring Round Robin Study - Vibration Analysis

Sheng¹

2012

112

107

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“…Prior work has shown this sideband ratio feature to be an effective metric for quantifying gear health since it is less dependent on the torque load. 18 For each respective gear, four features were calculated, since the sideband ratio and sideband level were calculated for the gear mesh frequency and the first harmonic of the gear mesh frequency. Also, the frequency domain gear features were only calculated for the four gears on the parallel gearbox stage.…”

Section: Frequency Domain Methodsmentioning

confidence: 99%

“…In addition, a sideband ratio was also calculated using ; this normalizes the sideband ratio by the gear mesh frequency peak. Prior work has shown this sideband ratio feature to be an effective metric for quantifying gear health since it is less dependent on the torque load . For each respective gear, four features were calculated, since the sideband ratio and sideband level were calculated for the gear mesh frequency and the first harmonic of the gear mesh frequency.…”

Section: Vibration‐based Signal Processing and Feature Extraction Metmentioning

confidence: 99%

A comparative study on vibration‐based condition monitoring algorithms for wind turbine drive trains

et al. 2013

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The ability to detect and diagnose incipient gear and bearing degradation can offer substantial improvements in reliability and availability of the wind turbine asset. Considering the motivation for improved reliability of the wind turbine drive train, numerous research efforts have been conducted using a vast array of vibration‐based algorithms. Despite these efforts, the techniques are often evaluated on smaller‐scale test‐beds, and existing studies do not provide a detailed comparison between the various vibration‐based condition monitoring algorithms. This study evaluates a multitude of methods, including frequency domain and cepstrum analysis, time synchronous averaging narrowband and residual methods, bearing envelope analysis and spectral kurtosis‐based methods. A full‐scale baseline wind turbine drive train and a drive train with several gear and bearing failures are tested at the National Renewable Energy Laboratory (NREL) dynamometer test cell during the NREL Gear Reliability Collaborative Round Robin study. A tabular set of results is presented to highlight the ability of each algorithm to accurately detect the bearing and gear wheel component health. The results highlight that the cepstrum and the narrowband phase modulation signal were effective methods for diagnosing gear tooth problems, whereas bearing envelope analysis could confidently detect most of the bearing‐related failures. Copyright © 2013 John Wiley & Sons, Ltd.

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“…Thiringer and Linders focused on the control a wind turbine with fixed pitch angle through controlling rotor speed [4]. Combet and Gelman [5], studied the sideband ratio features to check gear health condition. Generally, in order to investigate the failure root causes and monitor the health condition of WT components, researches count on examined characteristics.…”

Section: Introductionmentioning

confidence: 99%

Application of Order Analysis to Diagnose Fatigue within Wind Turbine Gearbox

Salem

Abu-Siada

Islam

2017

Technol Econ Smart Grids Sustain Energy

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One of the most expensive and critical component in wind turbines is the gearbox. Gearbox failure may have significant impacts on the network in terms of continuity of power supply especially in islanded areas where the majority of power demand is supplied by wind farms. As such, an effective condition monitoring technique for wind turbine gearbox should be adopted to avoid any catastrophic failure to the gearbox and maintain system reliability. This paper presents a technique to monitor the gearbox condition through monitoring the shaft torque and the gearbox vibration signals. Practical measurement is conducted on a test rig that emulating real wind turbine operation. Model based control technique using voltage slider by injecting a current through the induction generator stator terminals is applied to emulate real fault conditions on the wind turbine blades such as icing accumulation, wind share and gust wind. Order analysis technique is used to analyse and compare the obtained signals during normal and abnormal operating conditions.

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Novel adaptation of the demodulation technology for gear damage detection to variable amplitudes of mesh harmonics

Cited by 24 publications

References 13 publications

Wind Turbine Gearbox Condition Monitoring Round Robin Study - Vibration Analysis

Wind Turbine Gearbox Condition Monitoring Round Robin Study - Vibration Analysis

A comparative study on vibration‐based condition monitoring algorithms for wind turbine drive trains

Application of Order Analysis to Diagnose Fatigue within Wind Turbine Gearbox

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