Measurement unit for tunable low frequency vibration detection with MEMS force coupled oscillators

Forke, Roman; Scheibner, Dirk; Dötzel, Wolfram; Mehner, Jan

doi:10.1016/j.sna.2009.08.028

Cited by 6 publications

(4 citation statements)

References 8 publications

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“…It is caused by the fact that the vibration signal can be easily measured by relatively cheap equipment [ 14 ]. There is a broad range of measurement technologies, starting from classical transducers like accelerometers [ 14 ], through optical fibers [ 14 ], piezoelectric strain sensors [ 15 ], micro-electro-mechanical systems (MEMS) sensors [ 16 , 17 ], up to touchless measurement methods realized, e.g., by laser Doppler vibrometry [ 18 ]. In addition, most frequently, the operating conditions cause the structure to vibrate, opening opportunity to possess diagnostic information without adding additional excitation energy.…”

Section: Introductionmentioning

confidence: 99%

Application of Teager–Kaiser’s Instantaneous Frequency for Detection of Delamination in FRP Composite Materials

Gałęzia

Orłowska-Gałęzia

2021

Materials

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Composite materials are widely used in many engineering applications and fields of technology. One of the main defects, which occur in fiber-reinforced composite materials, is delamination. It manifests itself in the separation of layers of material and the damaged structure once subjected to mechanical loads degrades further. Delamination results in lower stiffness and the decrease of structure’s carry load capability. Its early detection is one of the tasks of non-invasive structural health monitoring of layered composite materials. This publication discusses a new method for delamination detection in fiber-reinforced composite materials. The approach is based on analysis of energy signal, calculated with Teager–Kaiser energy operator, and comparison of change of the weighted instantaneous frequency for measurement points located in- and outside of delamination area. First, applicability of the developed method was tested using simple models of vibration signals, reflecting considered phenomena. Next, the authors’ weighted instantaneous frequency was applied for detection of deamination using signals obtained from FEM simulated response of the cantilever beam. Finally, the methods effectiveness were tested involving real experimental signals collected by the laser Doppler vibrometer (LVD) sensor measuring vibrations of the delaminated glass-epoxy specimens.

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Section: Introductionmentioning

confidence: 99%

Application of Teager–Kaiser’s Instantaneous Frequency for Detection of Delamination in FRP Composite Materials

Gałęzia

Orłowska-Gałęzia

2021

Materials

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“…The last decades have witnessed a tremendous attention devoted to the study of nonlinear coupled oscillators [2]- [17] with various related applications in diverse areas such as electrical engineering [18], [19], mechanics [15], electromechanics [14] and electronics [16], just to name a few. In some previous works [18]- [21], we have shown some interesting applications of the coupling between van der Pol and Duffing oscillators in both electronics and electromechanics.…”

Section: Introductionmentioning

confidence: 99%

A novel image processing approach combining a 'coupled nonlinear oscillators'-based paradigm with cellular neural networks for dynamic robust contrast enhancement

Kyamakya

Chedjou

Latif

et al. 2010

2010 12th International Workshop on Cellular Nanoscale Networks and Their Applications (CNNA 2010)

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In this paper, a systematic discussion of both pros and cons of two well-known traditional approaches for image contrast enhancement is conducted. The first approach is based on the CNN paradigm and the second one is based on the coupled nonlinear oscillators' paradigm for image processing. In the later case an extensive bifurcation analysis is carried out and analytical formulas are derived to define the various states of the system. Both equilibrium and oscillatory states of the system are depicted. It is shown that each of these states has a significant impact on the quality of the resulting image contrast enhancement. A benchmarking is considered whereby a comparison is performed between the results obtained by a CNNbased processing, on one side, with those obtained by a 'coupled non linear oscillators' based processing, on the other side. The superiority of the later approach (for contrast enhancement) is demonstrated both analytically and through various experiments. A major drawback of the CNN based image processing is the practical inability to adjust/re-calculate templates in real-time in face of a dynamic scene with input images experiencing visibility and/or lighting related spatio-temporal dynamics. Finally, a novel hybrid approach integrating both schemes in an efficient way is proposed: the 'coupled nonlinear oscillators' based image processing is the main processing scheme that is however realized on top of a CNN processors' framework. The hybrid approach does prove to overcome key practical problems faced by both original approaches.

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“…The last decades have witnessed significant attention devoted to the study of nonlinear coupled oscillators [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17] with various related applications in diverse areas such as electrical engineering [18,19], mechanics [15], electromechanics [14] and electronics [16], to name a few. In some previous works [18][19][20][21], we have shown some interesting applications of the coupling between van der Pol and Duffing oscillators in both electronics and electromechanics.…”

Section: Introductionmentioning

confidence: 99%

A novel method combining cellular neural networks and the coupled nonlinear oscillators’ paradigm involving a related bifurcation analysis for robust image contrast enhancement in dynamically changing difficult visual environments

Chedjou¹,

Kyamakya²

2010

Phys. Scr.

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It is well known that a machine vision-based analysis of a dynamic scene, for example in the context of advanced driver assistance systems (ADAS), does require real-time processing capabilities. Therefore, the system used must be capable of performing both robust and ultrafast analyses. Machine vision in ADAS must fulfil the above requirements when dealing with a dynamically changing visual context (i.e. driving in darkness or in a foggy environment, etc). Among the various challenges related to the analysis of a dynamic scene, this paper focuses on contrast enhancement, which is a well-known basic operation to improve the visual quality of an image (dynamic or static) suffering from poor illumination. The key objective is to develop a systematic and fundamental concept for image contrast enhancement that should be robust despite a dynamic environment and that should fulfil the real-time constraints by ensuring an ultrafast analysis. It is demonstrated that the new approach developed in this paper is capable of fulfilling the expected requirements. The proposed approach combines the good features of the ‘coupled oscillators’-based signal processing paradigm with the good features of the ‘cellular neural network (CNN)’-based one. The first paradigm in this combination is the ‘master system’ and consists of a set of coupled nonlinear ordinary differential equations (ODEs) that are (a) the so-called ‘van der Pol oscillator’ and (b) the so-called ‘Duffing oscillator’. It is then implemented or realized on top of a ‘slave system’ platform consisting of a CNN-processors platform. An offline bifurcation analysis is used to find out, a priori, the windows of parameter settings in which the coupled oscillator system exhibits the best and most appropriate behaviours of interest for an optimal resulting image processing quality. In the frame of the extensive bifurcation analysis carried out, analytical formulae have been derived, which are capable of determining the various states of the system (e.g. quenching state, non-zero equilibrium state, oscillatory states, etc). Both equilibrium and oscillatory states of the system have been depicted. It could be shown that each of these states has a significant impact on the quality of the resulting image contrast enhancement. A benchmark has been considered, whereby a comparison is performed between the results’ quality obtained by traditional CNN-based processing, on the one hand, with those obtained by ‘coupled nonlinear oscillators’-based processing, on the other hand. Thus, the superiority of the latter approach in terms of ensuring a constantly high enhancement quality despite luminosity-related spatio-temporal scene dynamics has been demonstrated both analytically/conceptually and through various experiments. A key drawback of the latter approach is, however, the potentially huge and challenging computing effort necessary for solving the coupled nonlinear and highly stiff ODEs when one attempts to solve them numerically on ‘von Neumann’-type computing platforms; this is evide...

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Measurement unit for tunable low frequency vibration detection with MEMS force coupled oscillators

Cited by 6 publications

References 8 publications

Application of Teager–Kaiser’s Instantaneous Frequency for Detection of Delamination in FRP Composite Materials

Application of Teager–Kaiser’s Instantaneous Frequency for Detection of Delamination in FRP Composite Materials

A novel image processing approach combining a 'coupled nonlinear oscillators'-based paradigm with cellular neural networks for dynamic robust contrast enhancement

A novel method combining cellular neural networks and the coupled nonlinear oscillators’ paradigm involving a related bifurcation analysis for robust image contrast enhancement in dynamically changing difficult visual environments

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