2018
DOI: 10.1007/978-3-319-96292-4_26
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Dimension Reduction Techniques for Signal Separation Algorithms

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Cited by 5 publications
(3 citation statements)
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“…For the evaluation of the frequency spectra from the resonance method, a feature extraction method was used to obtain the key characteristic parameters of the spectra under consideration. This method is commonly used during the dimensionality reduction of large datasets [ 25 ] and is widely used in the prediction of the lifetime of structures in both civil and mechanical engineering. Thus, in addition to the dominant resonant frequency, other parameters such as amplitude, peak width at mid-peak prominence, and peak prominence were extracted from all spectra.…”
Section: Methodsmentioning
confidence: 99%
“…For the evaluation of the frequency spectra from the resonance method, a feature extraction method was used to obtain the key characteristic parameters of the spectra under consideration. This method is commonly used during the dimensionality reduction of large datasets [ 25 ] and is widely used in the prediction of the lifetime of structures in both civil and mechanical engineering. Thus, in addition to the dominant resonant frequency, other parameters such as amplitude, peak width at mid-peak prominence, and peak prominence were extracted from all spectra.…”
Section: Methodsmentioning
confidence: 99%
“…For objective machine assessment of the optimal setup with variations in handle-tip-impact force, it is necessary to select suitable monitored signal parameters. In general, this means a reduction in dimensionality [ 34 ], which entails the search for a way to separate representative parameters, the so-called symptoms, from the complex comprehensive information. The term symptom extraction is derived from this.…”
Section: Equipment and Software Usedmentioning
confidence: 99%
“…2. In this paper were observed features such as: root mean square of signal (rms); dominant frequency (frequency); standard deviation of signal (std); mean of signal (mean); kurtosis of signal (kurt); skewness of signal (skew); clearance factor of signal; impulse factor; attenuation of signal [15].…”
mentioning
confidence: 99%