Multi-parameter-adjusting stochastic resonance in a standard tri-stable system and its application in incipient fault diagnosis

Lai, Zhihui; Liu, J. S.; Zhang, H. T.; Zhang, C. L.; Zhang, J. W.; Duan, Dawei

doi:10.1007/s11071-019-04906-w

Cited by 57 publications

(24 citation statements)

References 37 publications

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“…The climate system has a chaotic nature, where a very small perturbation can be amplified. This chaotic character is taken into account both explicitly, by introducing a noise term, or indirectly, by introducing small variations in the initial conditions or in some physical parameters; in this latter case, one usually copes with a huge number of runs for the same prevision and performs a probabilistic analysis [61][62][63][64][65][66]. In order to modelize the climate cycle behavior and the effects connected with the global temperature trend, in this section, we adapted the stochastic differential Langevin's equation, which originally took into account only a systematic and a random contribution, to a dynamic case in which, besides a friction and a stochastic term, an external contribution and a double well potential were present [67][68][69][70][71]:…”

Section: Numerical Simulation Of Climate Changes and Resultsmentioning

confidence: 99%

On the Breaking of the Milankovitch Cycles Triggered by Temperature Increase: The Stochastic Resonance Response

Caccamo

Magazù

2021

Climate

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Recent decades have registered the hottest temperature variation in instrumentally recorded data history. The registered temperature rise is particularly significant in the so-called hot spot or sentinel regions, characterized by higher temperature increases in respect to the planet average value and by more marked connected effects. In this framework, in the present work, following the climate stochastic resonance model, the effects, due to a temperature increase independently from a specific trend, connected to the 105 year Milankovitch cycle were tested. As a result, a breaking scenario induced by global warming is forecasted. More specifically, a wavelet analysis, innovatively performed with different sampling times, allowed us, besides to fully characterize the cycles periodicities, to quantitatively determine the stochastic resonance conditions by optimizing the noise level. Starting from these system resonance conditions, numerical simulations for increasing planet temperatures have been performed. The obtained results show that an increase of the Earth temperature boosts a transition towards a chaotic regime where the Milankovitch cycle effects disappear. These results put into evidence the so-called threshold effect, namely the fact that also a small temperature increase can give rise to great effects above a given threshold, furnish a perspective point of view of a possible future climate scenario, and provide an account of the ongoing registered intensity increase of extreme meteorological events.

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Section: Numerical Simulation Of Climate Changes and Resultsmentioning

confidence: 99%

On the Breaking of the Milankovitch Cycles Triggered by Temperature Increase: The Stochastic Resonance Response

Caccamo

Magazù

2021

Climate

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“…us, the adaptive diagnosis of an inner ring fault is realized by using the AMPASR method of Duffing system. Moreover, the same date has been analyzed in [27] using a manual adjusted tristable SR system. e output SNR in that reference (− 25.43 dB) is much smaller than that in Figure 10 Moreover, the same vibration signal with inner ring fault can be also detected by the proposed AMPASR method of Langevin system.…”

Section: Case 1: Inner Ring Fault Diagnosismentioning

confidence: 99%

“…Furthermore, researchers found that, for the signals with inappropriate amplitude and large frequency, it is necessary to introduce amplitude-transformation coefficient and scale-transformation coefficient, respectively, to transform the amplitude and frequency of the characteristic signal to an appropriate range [25]. Combining the amplitude-transformation coefficient and scale-transformation coefficient, multiparameter-adjusting SR methods are further proposed and the multiparameters adjustment rules are fully studied theoretically [26,27]. According to the qualitative adjustment rules, SR can be achieved by manually adjusting the multiparameters for different noisy signals.…”

Section: Introductionmentioning

confidence: 99%

Rolling Bearing Fault Diagnosis Based on Adaptive Multiparameter-Adjusting Bistable Stochastic Resonance

Lai

Wang

Zhang

et al. 2020

Shock and Vibration

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The weak-signal detection technologies based on stochastic resonance (SR) play important roles in the vibration-based health monitoring and fault diagnosis of rolling bearings, especially at their early-fault stage. Aiming at the parameter-fixed vibration signals in practical engineering, it is feasible to diagnose the potential rolling bearing faults through adaptively adjusting the SR system parameters, as well as other generalized parameters such as the amplitude-transformation coefficient and scale-transformation coefficient. However, extant adaptive adjustment methods focus on the system parameters, while the adjustments of other adjustable parameters have not been fully studied, thus limiting the detection performance of the adaptive SR method. In order to further enhance the detection performance of adaptive SR methods and extend their application in rolling bearing fault diagnosis, an adaptive multiparameter-adjusting SR (AMPASR) method for bistable systems based on particle swarm optimization (PSO) algorithm is proposed in this paper. This method can produce optimal SR output through adaptively adjusting multiparameters, thus realizing fault feature extraction and further fault diagnosis. Furthermore, the influence of algorithm parameters on the optimization results is discussed, and the optimization results of the Langevin system and the Duffing system are compared. Finally, we propose a weak-signal detection method based on the AMPASR of the Duffing system and employ three diagnosis examples involving inner ring fault, outer ring fault, and rolling element fault diagnoses to demonstrate its feasibility in rolling bearing fault diagnosis.

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“…In addition, more and more methods to improve LBP have emerged in recent years, such as local maximum edge cooccurance patterns, 12 local gradient patterns, 13 scale-adaptive local binary patterns, 14 local directional extrema number pattern (LDIRENP), 15 graph based structure binary pattern, 16 and other variants. [17][18][19][20][21][22][23][24][25][26][27][28][29][30][31] Ernst Weber, a 19th century experimental psychologist, observed that the ratio of incremental threshold to background intensity is a constant. This relationship is known as Weber's law and can be expressed as E Q -T A R G E T ; t e m p : i n t r a l i n k -; e 0 0 1 ; 1 1 6 ; 4 0 7…”

Section: Introductionmentioning

confidence: 99%

Local image descriptor developed from Fechner’s law

Gao

Guo

et al. 2023

J. Electron. Imag.

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.Human perception of visual stimulus and its physical characteristics have a nonlinear-logarithmic relation as stated in Fechner’s law, which is a psychophysical law of perception (i.e., subjective sensation). Inspired by Fechner’s law, we use the salient differences among pixels in images as the physical characteristics to mimic the human pattern perception and propose a Fechner local image descriptor (FLID) for face image representation. FLID is a nonlinear descriptor, so the represented image is more hierarchical than the general linear one. In addition, a threshold method is used to divide the features into four different intervals, which can effectively reduce the effects of noise and illumination. However, considering that FLID only extracts the local features of single-scale blocks, we incorporate multi-scale block into FLID and propose a multi-scale block Fechner local image descriptor (MB-FLID) to extract more global structural features. In the experimental part, we verified the performance of FLID and MB-FLID on the Face Recognition Technology (FERET), extended Yale-B, Olivetti Research Laboratories, Yale, and AR face databases, and compared them with a host of other local feature descriptors. The experimental results show that the proposed FLID and MB-FLID outperform the compared descriptors.

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Multi-parameter-adjusting stochastic resonance in a standard tri-stable system and its application in incipient fault diagnosis

Cited by 57 publications

References 37 publications

On the Breaking of the Milankovitch Cycles Triggered by Temperature Increase: The Stochastic Resonance Response

On the Breaking of the Milankovitch Cycles Triggered by Temperature Increase: The Stochastic Resonance Response

Rolling Bearing Fault Diagnosis Based on Adaptive Multiparameter-Adjusting Bistable Stochastic Resonance

Local image descriptor developed from Fechner’s law

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