Improving the weak feature extraction by adaptive stochastic resonance in cascaded piecewise-linear system and its application in bearing fault detection

In mechanical engineering field, early fault features are extremely weak and submerged in heavy noise, and the weak feature extraction is quite challenging. In this work, we apply the adaptive stochastic resonance in cascaded piecewise-linear system to extract the weak features. The adaptive stochastic resonance is realized by the quantum particle swarm algorithm. By optimizing system parameters, the efficiency of the feature extraction is improved greatly. As a result, the weak features can be easily extracted eventually. The effectiveness and the high-performance of the proposed method are verified by the numerical simulation and experimental data of rolling element bearings. The bearing fault under different motor loads is detected effectively, consequently confirming the robustness of the proposed method

Improved SNR to detect the unknown characteristic frequency by SR

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/166241/1/smt2bf00608.pd

Lost in translation: Toward a formal model of multilevel, multiscale medicine

For a broad spectrum of low level cognitive regulatory and other biological phenomena, isolation from signal crosstalk between them requires more metabolic free energy than permitting correlation. This allows an evolutionary exaptation leading to dynamic global broadcasts of interacting physiological processes at multiple scales. The argument is similar to the well-studied exaptation of noise to trigger stochastic resonance amplification in physiological subsystems. Not only is the living state characterized by cognition at every scale and level of organization, but by multiple, shifting, tunable, cooperative larger scale broadcasts that link selected subsets of functional modules to address problems. This multilevel dynamical viewpoint has implications for initiatives in translational medicine that have followed the implosive collapse of pharmaceutical industry 'magic bullet' research. In short, failure to respond to the inherently multilevel, multiscale nature of human pathophysiology will doom translational medicine to a similar implosion

Plantar Pressure, Cutaneous Sensation and Stochastic Resonance: An Examination of Factors Influencing the Control and Perception of Posture

The goal of this dissertation was to understand how people control posture in the context of sensory loss. To do so we explored three potential influences on the detection of external information and how they relate to the control of posture and perception of body orientation: 1) does changing posture alter the forces under the foot, and do these changes impact the ability to detect external vibrations? 2) Does decreasing the temperature of the foot influence the ability to detect external vibrations, the perception of body orientation, and the control of posture? And 3) does stochastic resonance (SR) improve the perception of body orientation and the control of posture when the sensory thresholds are elevated to clinical levels through cooling of the feet? The results of the experiments indicate that: 1) increasing the pressure under the feet, elicited by changes in posture, elevates the cutaneous sensory threshold, and that the forefoot appears to be more sensitive than the rearfoot to changes in weighting; 2) decreasing the temperature of the skin elevates cutaneous sensory thresholds, and impacts postural control by constraining the fluctuations of the medial-lateral center of pressure; and 3) applying SR to the soles of the feet improves the ability to perceive body position, with greater amounts of skin cooling resulting in greater improvements in postural performance due to SR. This dissertation demonstrates that decreasing plantar loading lowers cutaneous sensory thresholds, indicating that the changes in postural fluctuations frequently observed among those with clinical sensory loss may serve as a mechanism that allows for improved access to external information if they prove to reduce the pressure under sensory impaired portions of the feet. Additionally, we add to the growing body of literature identifying SR as a means to improve postural performance when cutaneous sensory function is impaired. From a clinical perspective, the results presented here indicate that aids designed to apply SR to the soles of the feet, as a means to improve posture and gait, should modulate their signal such that they apply a signal amplitude appropriate to the amount of loading the foot experiences

Detecting Unspecified Structure in Low-Count Images

Unexpected structure in images of astronomical sources often presents itself upon visual inspection of the image, but such apparent structure may either correspond to true features in the source or be due to noise in the data. This paper presents a method for testing whether inferred structure in an image with Poisson noise represents a significant departure from a baseline (null) model of the image. To infer image structure, we conduct a Bayesian analysis of a full model that uses a multiscale component to allow flexible departures from the posited null model. As a test statistic, we use a tail probability of the posterior distribution under the full model. This choice of test statistic allows us to estimate a computationally efficient upper bound on a p-value that enables us to draw strong conclusions even when there are limited computational resources that can be devoted to simulations under the null model. We demonstrate the statistical performance of our method on simulated images. Applying our method to an X-ray image of the quasar 0730+257, we find significant evidence against the null model of a single point source and uniform background, lending support to the claim of an X-ray jet