Theory of synchronous averaging

Hochmann, David; Sadok, Mokhtar

doi:10.1109/aero.2004.1368181

Cited by 36 publications

(17 citation statements)

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“…Time synchronous averaging (TSA) techniques previously implemented in 012003-6 applications such as structural health monitoring are employed here as a means of reducing a periodic signal into one discernible waveform (Refs. 10,11). For a deterministic signal χ (t) of period T , a measurement model can be written as…”

Section: Flight Dynamics Analysismentioning

confidence: 99%

Effects of Planform Geometry on Mechanical Samara Autorotation Efficiency and Rotational Dynamics

Ulrich¹,

Pines²

2012

j am helicopter soc

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An experimental methodology intended to characterize the autorotation efficiency and vehicle dynamics of samara-like micro-air vehicles is presented. The scale inherent in these vehicles precludes the use of most conventional in situ sensors, so data collection is limited to external observation. The studies presented herein demonstrate a new technique for collecting flight data from a vision-based, motion-capture system. A test apparatus has been constructed to yield repeatable initial conditions, minimizing uncertainty of the samara's dynamic state prior to data collection. The test specimen is constructed of an ultraviolet-cured liquid polymer, which is dispensed and cured via the use of a rapid prototyping machine. The mechanical samaras in this study are compared on the basis of equal wing loading. The results of these experiments identify a geometry for a minimal descent rate as well as producing a quantitative Fourier series representation of the roll and pitch. In addition, a new relationship has been established, which elucidates trends in samara descent velocity not captured by wing loading or disk loading. This information will aid in the development and validation of an inflow model for the mechanical samara.

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Section: Flight Dynamics Analysismentioning

confidence: 99%

Effects of Planform Geometry on Mechanical Samara Autorotation Efficiency and Rotational Dynamics

Ulrich¹,

Pines²

2012

j am helicopter soc

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“…Regardless, the availability of the shaft encoder/key phaser is crucial to both analog and digital synchronous sampling approaches. With the synchronously sampled data, a common way to enhance the signal components of interest is through time synchronous averaging [10]. With a shaft encoder/key phaser, the vibration signal detected contains three major components: the synchronous coherent signal component, the synchronous, non-coherent component, and random noise.…”

Section: Synchronous Samplingmentioning

confidence: 99%

“…The initial step in this algorithm is to calculate the short time Fourier Transform of the vibration signal, denoted by H(t,f). Equation (10) indicates that the average value of the fourth power of H(t,f) is divided by the mean square value of H(t,f), which provides a kurtosis value as a function of frequency. The Wiener filter is constructed using the kurtosis values for each frequency bin, as shown in Equation (11); the frequency bin is only included if the kurtosis value is above a statistical threshold at a given confidence level [30].…”

Section: Spectral Kurtosis Filteringmentioning

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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“…This result also demonstrates the utility of spatial synchronous averaging. Through multiple rotations, the presence of asynchronous content in the estimate can be dramatically reduced [16]. Spatial synchronous averaging through a range of velocities ensures that content not synchronized with position will be attenuated.…”

Section: Spatial Re-sampling Reference Positionmentioning

confidence: 98%

Using the motor drive as a sensor to extract spatially dependent information during servo operation

Wolf

Lorenz

2010

2010 IEEE Energy Conversion Congress and Exposition

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This paper presents a methodology for extracting useful spatial signals using the motor drive as the sensor during servo operation. Spatially dependent phenomena yield nonstationary frequency content during servo operation. With variable frequency and frequency dependent amplitude in the current and torque signals, the underlying, valuable spatial information is difficult to extract using conventional frequency domain approaches. The methodology presented uses the motor drive to estimate the spatially dependent disturbance torque information during servo operation using spatial domain resampling of temporal domain signals internal to the motor drive. Spatial domain information is speed invariant, making it accessible even during servo operation. Additionally, this paper develops a framework to operate through varying speeds to help isolate the systematic, spatially dependent content using spatial synchronous averaging. These methods and concepts are evaluated through simulation as well as experimentation. This methodology can be utilized to provide robust control of machines through identification of spatial components, as well as improve diagnostics of machine and load degradation.

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Theory of synchronous averaging

Cited by 36 publications

References 1 publication

Effects of Planform Geometry on Mechanical Samara Autorotation Efficiency and Rotational Dynamics

Effects of Planform Geometry on Mechanical Samara Autorotation Efficiency and Rotational Dynamics

Wind Turbine Gearbox Condition Monitoring Round Robin Study - Vibration Analysis

Using the motor drive as a sensor to extract spatially dependent information during servo operation

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