A repeated single-channel mechanical signal blind separation method based on morphological filtering and singular value decomposition

Dong, Shaojiang; Tang, Baoping; Zhang, Yan

doi:10.1016/j.measurement.2012.05.003

Cited by 35 publications

(22 citation statements)

References 32 publications

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“…To maintain the probe effect of the SE to the morphological filter function, the SE length should be far less than the filter function (the length equal to the signal been analyzed), and greater than the width of the disturbance pulse. Generally, the pulse width of the vibration signal is very narrow [6]. So the SE length needs not to be selected too long, usually the length of SE selected as the length of several sampling points [7,8].…”

Section: Remove the High-frequency Noisementioning

confidence: 99%

Removal of power line interference of space bearing vibration signal based on the morphological filter and blind source separation

Dong

Sun

et al. 2017

IOP Conf. Ser.: Earth Environ. Sci.

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Abstract. Aiming at the problem that it is difficult to extract the feature information from the space bearing vibration signal because of different noise, for example the running trend information, high-frequency noise and especially the existence of lot of power line interference (50Hz) and its octave ingredients of the running space simulated equipment in the ground. This article proposed a combination method to eliminate them. Firstly, the EMD is used to remove the running trend item information of the signal, the running trend that affect the signal processing accuracy is eliminated. Then the morphological filter is used to eliminate high-frequency noise. Finally, the components and characteristics of the power line interference are researched, based on the characteristics of the interference, the revised blind source separation model is used to remove the power line interferences. Through analysis of simulation and practical application, results suggest that the proposed method can effectively eliminate those noise. IntroductionBearing is widely used in rotating machinery. In order to eliminate the power line interference, the conventional method of eliminating such interference is through the use of a notch filter, Jacek proposed using the multiple-notch filtering methods to remove the harmonic powerline interference [1][2]. However, the nature of this approach in the time domain is consistent to the notch filter. So, the above method can't effectively eliminate the noise, in order to eliminate the noise, we should know the properties of the noise.Additionally, the exist of the running trend information and the high-frequency noise also affect the feature extraction effect. The EMD method is used to remove the running trend item information in Section 1. The morphological filter is used to eliminate high-frequency noise is described in Section 2. The blind source separation model is used to remove the power line interferences in Section 3. The case study is presented in Section 4, in which the proposed method is validated. Finally, the conclusions are given in Section 5.

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Section: Remove the High-frequency Noisementioning

confidence: 99%

Removal of power line interference of space bearing vibration signal based on the morphological filter and blind source separation

Dong

Sun

et al. 2017

IOP Conf. Ser.: Earth Environ. Sci.

Self Cite

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show abstract

“…There are various kinds of SEs, such as flat SEs, triangular SEs and semicircular SEs, etc. In the present, the flat SEs is employed because it appears to be quite appropriate for detecting impulses [37][38][39]. In order to retain the shape characters of the signal entirely, all the height of the flat SE is defined as zeros [39,41].…”

Section: Morphological Filtermentioning

confidence: 99%

“…In the present, the flat SEs is employed because it appears to be quite appropriate for detecting impulses [37][38][39]. In order to retain the shape characters of the signal entirely, all the height of the flat SE is defined as zeros [39,41]. All the studies show that the length of SEs is important for the morphological method [39][40][41], and the scholar developed various rules or guidelines for choosing the length of SEs.…”

Section: Morphological Filtermentioning

confidence: 99%

“…In order to retain the shape characters of the signal entirely, all the height of the flat SE is defined as zeros [39,41]. All the studies show that the length of SEs is important for the morphological method [39][40][41], and the scholar developed various rules or guidelines for choosing the length of SEs. In theory, the shorter length of SEs, the more impulse features will be extracted when using the DIF filter.…”

Section: Morphological Filtermentioning

confidence: 99%

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Fault diagnosis of rolling bearing based on second generation wavelet denoising and morphological filter

et al. 2015

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Defective rolling bearing response is often characterized by the presence of periodic impulses. However, the in-situ sampled vibration signal is ordinarily mixed with ambient noises and easy to be interfered even submerged. The hybrid approach combining the second generation wavelet denoising with morphological filter is presented. The raw signal is purified using the second generation wavelet. The difference between the closing and opening operator is employed as the morphology filter to extract the periodicity impulsive features from the purified signal and the defect information is easily to be extracted from the corresponding frequency spectrum. The proposed approach is evaluated by simulations and vibration signals from defective bearings with inner race fault, outer race fault, rolling element fault and compound faults, respectively. Results show that the ambient noises can be fully restrained and the defect information of the above defective bearings is well extracted, which demonstrates that the approach is feasible and effective for the fault detection of rolling bearing.

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“…A rolling bearing is a key mechanical part of a 'rotor-bearing' system in rotating machinery because the heavy load bearing is also the unit that usually fails during operation [1][2][3]. As these failures will result in a high industrial cost or even disaster, considerable attention has been paid to the condition monitoring and fault prediction of a bearing [4,5].…”

Section: Introductionmentioning

confidence: 99%

The application of a general mathematical morphological particle as a novel indicator for the performance degradation assessment of a bearing

Wang

et al. 2017

Mechanical Systems and Signal Processing

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A repeated single-channel mechanical signal blind separation method based on morphological filtering and singular value decomposition

Cited by 35 publications

References 32 publications

Removal of power line interference of space bearing vibration signal based on the morphological filter and blind source separation

Removal of power line interference of space bearing vibration signal based on the morphological filter and blind source separation

Fault diagnosis of rolling bearing based on second generation wavelet denoising and morphological filter

The application of a general mathematical morphological particle as a novel indicator for the performance degradation assessment of a bearing

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