Proportional bandwidth properties of fault indicating tones in a ball bearing system

Ladd, Mark D.; Wilson, Gary R.

doi:10.1109/acssc.1994.471414

Cited by 3 publications

(3 citation statements)

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“…For single period estimation, the maximum likelihood (ML) estimate minimizes the two norm of the distance between and [12]. The ML estimate minimizes (1) where is the projection of onto , which is the subspace corresponding to signals of period (i.e., mod , and ). Minimizing (1) is equivalent to maximizing the square of the 2-norm of (2)…”

Section: Single Period Estimationmentioning

confidence: 99%

“…T HE ANALYSIS of machine vibrations has proven to be a valuable application of signal processing. A variety of well-known techniques used in this area [1], [2] require that good period and periodic subsignal estimates can be made. Other applications of period estimation techniques are separation of periodic waveforms with overlapping spectra, finding musical rhythms, and generally finding patterns in a wide variety of data sources.…”

Section: Introductionmentioning

confidence: 99%

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Orthogonal, exactly periodic subspace decomposition

Muresan¹,

Parks

2003

IEEE Trans. Signal Process.

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The detection and estimation of machine vibration multiperiodic signals of unknown periods in white Gaussian noise is investigated. New estimates for the subsignals (signals making up the received signal) and their periods are derived using an orthogonal subspace decomposition approach. The concept of exactly periodic signals is introduced. This in turn simplifies and enhances the understanding of periodic signals.

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Section: Single Period Estimationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Orthogonal, exactly periodic subspace decomposition

Muresan¹,

Parks

2003

IEEE Trans. Signal Process.

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“…Since its introduction in the mid-1980s the theory of wavelets has grown very rapidly in almost every field of signal processing and recently research has begun in areas of mechanical vibration analysis (see, e.g. [11][12][13][14][15][16][17][18]). …”

Section: Introductionmentioning

confidence: 99%

Towards automatic detection of local bearing defects in rotating machines

Ericsson

Grip

Johansson

et al. 2005

Mechanical Systems and Signal Processing

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In this paper we derive and compare several different vibration analysis techniques for automatic detection of local defects in bearings.Based on a signal model and a discussion on to what extent a good bearing monitoring method should trust it, we present several analysis tools for bearing condition monitoring and conclude that wavelets are especially well suited for this task. Then we describe a large-scale evaluation of several different automatic bearing monitoring methods using 103 laboratory and industrial environment test signals for which the true condition of the bearing is known from visual inspection. We describe the four best performing methods in detail (two wavelet-based, and two based on envelope and periodisation techniques). In our basic implementation, without using historical data or adapting the methods to (roughly) known machine or signal parameters, the four best methods had 9-13% error rate and are all good candidates for further finetuning and optimisation. Especially for the wavelet-based methods, there are several potentially performance improving additions, which we finally summarise into a guiding list of suggestion. r

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Orthogonal subspace decomposition of periodic signals

Muresan

Parks²

Conference Record of the Thirty-Third Asilomar Conference on Signals, Systems, and Computers (Cat. No.CH37020)

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Proportional bandwidth properties of fault indicating tones in a ball bearing system

Cited by 3 publications

References 5 publications

Orthogonal, exactly periodic subspace decomposition

Orthogonal, exactly periodic subspace decomposition

Towards automatic detection of local bearing defects in rotating machines

Orthogonal subspace decomposition of periodic signals

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