Characteristics of the Vold-Kalman order tracking filter

Herlufsen, H.; Gade, Svend; Konstantin-Hansen, H.; Vold, Håvard

doi:10.1109/icassp.2000.860254

Cited by 39 publications

(49 citation statements)

References 6 publications

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“…The choice of filter bandwidth needs to be done very carefully. For example analysis the reader may refer to [11] and for details on the choice of the filter bandwidth, the reader may refer to [7]. Figure 3(c) displays the result of COT, namely that there are two clear peaks in the order spectrum at the 3 rd and 6 th orders respectively.…”

Section: Simulation Of a Single Degree-of-freedom (Sdof) Rotor Model mentioning

confidence: 99%

“…Secondly, the structural equation enforces successive digital points of filtered order signal by fitting a low order polynomial. A low order polynomial enforcement to signal sequence is a sufficient condition for smoothness of filtered order [7]. By considering the data and structural equations, one may conclude that the order components extracted from the Vold-Kalman filter are smooth and harmonic waves, but they may be non-stationary.…”

Section: Vold-kalman Filter-based Order Trackingmentioning

confidence: 99%

“…Herlufsen et al [7] describe order tracking as the art and science of extracting the sinusoidal content of measurements, with the sinusoidal content or orders/harmonics at frequencies that are multiples of the fundamental rotational frequency. To this end, VKF-OT relies on two equations to complete the filtering, namely the data equation and the structural equation.…”

Section: Vold-kalman Filter-based Order Trackingmentioning

confidence: 99%

“…This comparatively new order tracking technique has been studied over the past ten years [4, 5, and 6]. The characteristics of Vold-Kalman filters were also considered by Herlufsen et al [7]. Recently, Tůma [5] dealt with the often-neglected issue of setting the filter pass band, which is fundamental to the theory of the MATLAB-based Vibratools scripts [8].…”

Section: Introductionmentioning

confidence: 99%

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The combined use of order tracking techniques for enhanced Fourier analysis of order components

Wang

Heyns

2011

Mechanical Systems and Signal Processing

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Order tracking is one of the most important vibration analysis techniques for diagnosing faults in rotating machinery. It can be performed in many different ways, each of these with distinct advantages and disadvantages. However, in the end the analyst will often use Fourier analysis to transform the data from a time series to frequency or order spectra. It is therefore surprising that the study of the Fourier analysis of order-tracked systems seems to have been largely ignored in the literature. This paper considers the frequently used Vold-Kalman filter-based order tracking and computed order tracking techniques. The main pros and cons of each technique for Fourier analysis are discussed and the sequential use of Vold-Kalman filtering and computed order tracking is proposed as a novel idea to enhance the results of Fourier analysis for determining the order components. The advantages of the combined use of these order tracking techniques are demonstrated numerically on an SDOF rotor simulation model. Finally, the approach is also demonstrated on experimental data from a real rotating machine.

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Section: Simulation Of a Single Degree-of-freedom (Sdof) Rotor Model mentioning

confidence: 99%

Section: Vold-kalman Filter-based Order Trackingmentioning

confidence: 99%

Section: Vold-kalman Filter-based Order Trackingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The combined use of order tracking techniques for enhanced Fourier analysis of order components

Wang

Heyns

2011

Mechanical Systems and Signal Processing

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“…This means that the ratio of the instantaneous absolute filter bandwidth to the instantaneous rotational speed frequency is 0.2. (See [15] and [16] for more details of the choice of the filter bandwidth). In the top figure of Figure 6(a), the spectra of the 1 st IMF and 3 rd order are superimposed together and therefore the relationship between them can be seen.…”

Section: Further Decomposition Of An Imfmentioning

confidence: 99%

Application of computed order tracking, Vold–Kalman filtering and EMD in rotating machine vibration

Wang

Heyns

2011

Mechanical Systems and Signal Processing

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This paper presents a study on rotating machine vibration signals by using computed order tracking, Vold-Kalman filtering and intrinsic mode functions from the empirical mode decomposition method. Through the sequential use of intrinsic mode function and order tracking methods, both speed synchronous and non-synchronous vibrations that modulate orders in rotating machine vibrations are distinguished, which is difficult when using each of the techniques in isolation alone. Simulation and experimental studies demonstrate the ability of extracting vibrations that modulate order signals through combining the techniques.

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Design of new sound metric and its application for quantification of an axle gear whine sound by utilizing artificial neural network

2009

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The gear whine sound of an axle system is one of the most important sound qualities in a sport utility vehicle (SUV). Previous work has shown that, because of masking effects, it is difficult to evaluate the gear whine sound objectively by using only the A-weighted sound pressure level. In this paper, a new objective evaluation method for this sound was developed by using new sound metrics, which are developed based on the increment of signal to noise ration and the psychoacoustic parameters in the paper, and the artificial neural network (ANN) used for the modeling of the correlation between objective and subjective evaluation. This model developed by using ANN was applied to the objective evaluation of the axle-gear whine sound for real SUVs and the output of the model was compared with subjective evaluation. The results indicate a good correlation of over 90 percent between the subjective and objective evaluations.

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Characteristics of the Vold-Kalman order tracking filter

Cited by 39 publications

References 6 publications

The combined use of order tracking techniques for enhanced Fourier analysis of order components

The combined use of order tracking techniques for enhanced Fourier analysis of order components

Application of computed order tracking, Vold–Kalman filtering and EMD in rotating machine vibration

Design of new sound metric and its application for quantification of an axle gear whine sound by utilizing artificial neural network

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