A Decentralized Fault Detection and Prediction Scheme for Nonlinear Interconnected Continuous-time Systems

Complex nonlinear systems such as an aircraft, trains, automobiles, power plants and chemical plants are represented as nonlinear interconnected subsystems. Therefore, in this paper a novel decentralized fault diagnosis and prognosis (FDP) methodology is proposed for such large-scale systems. Current FDP approaches require the knowledge of the entire state or its estimated vector. But the main goal in this work is to design a local fault detector (LFD) or observer for each subsystem based on the measured local states of the subsystem alone. a local residual signal is generated via the measured states of the local subsystem and the estimated states provided by the LFD. a fault is detected when this local residual exceeds a predefined threshold. the adaptive online approximator in each LFD is activated upon detection to compensate the fault dynamics due to local and non-local faults. a novel update law for tuning the parameters of the online approximator is derived. Upon detection, faults local to the subsystem and to other subsystems are isolated. in addition, the proposed scheme provides the time to failure (or remaining useful life) information by using local measurements and the parameter update law of the LFD. Simulation results verify the effectiveness of the proposed decentralized FDP scheme. © 2012 IEEE

Online Optimal Neuro-Fuzzy Flux Controller for DTC Based Induction Motor Drives

In this paper a fast flux search controller based on the Neuro-fuzzy systems is proposed to achieve the best efficiency of a direct torque controlled induction motor at light load. In this method the reference flux value is determined through a minimization algorithm with stator current as objective function. This paper discusses and demonstrates the application of Neurofuzzy filtering to stator current estimation. Simulation and experimental results are presented to show the fast response of proposed controller

A Block-Wise random sampling approach: Compressed sensing problem

The focus of this paper is to consider the compressed sensing problem. It is stated that the compressed sensing theory, under certain conditions, helps relax the Nyquist sampling theory and takes smaller samples. One of the important tasks in this theory is to carefully design measurement matrix (sampling operator). Most existing methods in the literature attempt to optimize a randomly initialized matrix with the aim of decreasing the amount of required measurements. However, these approaches mainly lead to sophisticated structure of measurement matrix which makes it very difficult to implement. In this paper we propose an intermediate structure for the measurement matrix based on random sampling. The main advantage of block-based proposed technique is simplicity and yet achieving acceptable performance obtained through using conventional techniques. The experimental results clearly confirm that in spite of simplicity of the proposed approach it can be competitive to the existing methods in terms of reconstruction quality. It also outperforms existing methods in terms of computation time

Sparse multichannel source separation using incoherent K-SVD method

In this paper the problem of sparse source separation of linear mixtures is addressed. We propose to apply K-SVD, which is a leading dictionary learning method, for this purpose. Further, a modified gradient-based K-SVD scheme for incoherent dictionary learning and source separation is proposed. The promising results on random synthetic signals reveal the ability of this technique for utilizing in source separation framework. We also suggest BOLD detection fMRI as an application for this method. The preliminary results confirm the successful separation of this type of data

TRPV1 activation by capsaicin mediates glucose oxidation and ATP production independent of insulin signalling in mouse skeletal muscle cells

Background: Insulin resistance (IR), a key characteristic of type 2 diabetes (T2DM), is manifested by decreased insulin-stimulated glucose transport in target tissues. Emerging research has highlighted transient receptor potential cation channel subfamily V member (TRPV1) activation by capsaicin as a potential therapeutic target for these conditions. However, there are limited data on the effects of capsaicin on cell signalling molecules involved in glucose uptake. Methods: C2C12 cells were cultured and differentiated to acquire the myotube phenotype. The activation status of signalling molecules involved in glucose metabolism, including 5’ adenosine monophosphate-activated protein kinase (AMPK), calcium/calmodulin-dependent protein kinase 2 (CAMKK2), extracellular signal-regulated protein kinases 1 and 2 (ERK1/2), protein kinase B (AKT), and src homology phosphatase 2 (SHP2), was examined. Finally, activation of CAMKK2 and AMPK, and glucose oxidation and ATP levels were measured in capsaicin-treated cells in the presence or absence of TRPV1 antagonist (SB-452533). Results: Capsaicin activated cell signalling molecules including CAMKK2 and AMPK leading to increased glucose oxidation and ATP generation independent of insulin in the differentiated C2C12 cells. Pharmacological inhibition of TRPV1 diminished the activation of CAMKK2 and AMPK as well as glucose oxidation and ATP production. Moreover, we observed an inhibitory effect of capsaicin in the phosphorylation of ERK1/2 in the mouse myotubes. Conclusion: Our data show that capsaicin-mediated stimulation of TRPV1 in differentiated C2C12 cells leads to activation of CAMKK2 and AMPK, and increased glucose oxidation which is concomitant with an elevation in intracellular ATP level. Further studies of the effect of TRPV1 channel activation by capsaicin on glucose metabolism could provide novel therapeutic utility for the management of IR and T2DM

Capsaicin and zinc promote glucose uptake in C2C12 skeletal muscle cells through a common calcium signalling pathway

Capsaicin and zinc have recently been highlighted as potential treatments for glucose metabolism disorders; however, the effect of these two natural compounds on signalling pathways involved in glucose metabolism is still uncertain. In this study, we assessed the capsaicin- or zinc- induced activation of signalling molecules including calcium/calmodulin-dependent protein kinase 2 (CAMKK2), cAMP-response element-binding protein (CREB), and target of rapamycin kinase complex 1 (TORC1). Moreover, the expression status of genes associated with the control of glucose metabolism was measured in treated cells. The activation of cell signalling proteins was then evaluated in capsaicin- or zinc treated cells in the presence or absence of cell-permeant calcium chelator (BAPTA-AM) and the CAMKK inhibitor (STO-609). Finally, capsaicin- and zinc-induced glucose uptake was measured in the cells pre-treated with or without BAPTA-AM. Our results indicate that calcium flux induced by capsaicin or zinc led to activation of calcium signalling molecules and promoting glucose uptake in skeletal muscle cells. Pharmacological inhibition of CAMKK diminished activation of signalling molecules. Moreover, we observed an increase in intracellular cAMP levels in the cells after treatment with capsaicin and zinc. Our data show that capsaicin and zinc mediate glucose uptake in C2C12 skeletal muscle cells through the activation of calcium signalling

Segmented compressive sensing

This paper presents an alternative way of random sampling of signals/images in the framework of compressed sensing. In spite of usual random samplers which take p measurements from the input signal, the proposed method uses M different samplers each taking pi'(i = 1, 2, 3 ... M) samples. Therefore, the overall number of samples will be q = M pmacr'. Using this method a variable sampling criterion based on the content of the segments is achievable. Following this idea, the calculated measurement (or sensing) matrix is also more incoherent in columns comparing to other conventional methods which is a desired feature. Our experiments show that the reconstructed signal using this method has a better SNR and is more robust compared to the systems using one sampler