Search results for " Network"
showing 10 items of 6428 documents
Neural modelling of friction material cold performance
2008
The complex and highly non-linear phenomena involved during braking are primarily caused by friction materials’ characteristics. The final friction materials' characteristics are determined by their compositions, manufacturing, and the brake's operating conditions. Analytical models of friction materials' behaviour are difficult, even impossible, to obtain for the case of different brakes' operating conditions. That is why, in this paper, all relevant influences on the friction materials' cold performance have been integrated by means of artificial neural networks. The influences of 26 input parameters, defined by the friction materials' composition (18 ingredients), manufacturing (five pa…
Quasi-Static Displacement Self-Sensing Measurement for a 2-DOF Piezoelectric Cantilevered Actuator
2017
This paper proposes a self-sensing measurement technique to perform the precise estimation of the displacements along two axes in a two-degrees-of-freedom (2-DOF) piezoelectric actuator. For that, a new electrical circuit scheme that permits charge amplification is first proposed to match the different electrodes combination of the 2-DOF actuator. Then, a new bivariable observer that precisely estimates the displacements is calculated and implemented experimentally in a cascade with the electrical circuit to complete the self-sensing. The experimental tests and results verification with external sensors revealed that the measured displacements given by the developed self-sensing measurement…
Data-based modeling and estimation of vehicle crash processes in frontal fixed-barrier crashes
2017
Abstract As a complex process, vehicle crash is challenging to be described and estimated mathematically. Although different mathematical models are developed, it is still difficult to balance the complexity of models and the performance of estimation. The aim of this work is to propose a novel scheme to model and estimate the processes of vehicle-barrier frontal crashes. In this work, a piecewise model structure is predefined to represent the accelerations of vehicle in frontal crashes. Each segment in the model is corresponding to the energy absorbing component in the crashworthiness structure. With the help of Ensemble Empirical Mode Decomposition (EEMD), a robust scheme is proposed for …
Regularized LMS methods for baseline wandering removal in wearable ECG devices
2016
The acquisition of electrocardiogram (ECG) signals by means of light and reduced size devices can be usefully exploited in several health-care applications, e.g., in remote monitoring of patients. ECG signals, however, are affected by several artifacts due to noise and other disturbances. One of the major ECG degradation is represented by the baseline wandering (BW), a slowly varying change of the signal trend. Several BW removal algorithms have been proposed into the literature, even though their complexity often hinders their implementation into wearable devices characterized by limited computational and memory resources. In this study, we formalize the BW removal problem as a mean-square…
Adaptive consensus-based distributed detection in WSN with unreliable links
2016
Event detection is a crucial tasks in wireless sensor networks. The importance of a fast response makes distributed strategies, where nodes exchange information just with their one-hop neighbors to reach local decisions, more adequate than schemes where all nodes send observations to a central entity. Distributed detectors are usually based on average consensus, where all nodes iteratively communicate to asymptotically agree on a final result. In a realistic scenario, communications are subject to random failures, which impacts the performance of the consensus. We propose an alternative detector, which adapts to the statistical properties of the consensus and compensate deviations from the …
Reliable diagnostics using wireless sensor networks
2019
International audience; Monitoring activities in industry may require the use of wireless sensor networks, for instance due to difficult access or hostile environment. But it is well known that this type of networks has various limitations like the amount of disposable energy. Indeed, once a sensor node exhausts its resources, it will be dropped from the network, stopping so to forward information about maybe relevant features towards the sink. This will result in broken links and data loss which impacts the diagnostic accuracy at the sink level. It is therefore important to keep the network's monitoring service as long as possible by preserving the energy held by the nodes. As packet trans…
Graph Filtering of Time-Varying Signals over Asymmetric Wireless Sensor Networks
2019
In many applications involving wireless sensor networks (WSNs), the observed data can be modeled as signals defined over graphs. As a consequence, an increasing interest has been witnessed to develop new methods to analyze graph signals, leading to the emergence of the field of Graph Signal Processing. One of the most important processing tools in this field is graph filters, which can be easily implemented distributedly over networks by means of cooperation among the nodes. Most of previous works related to graph filters assume the same connection probability in both link directions when transmitting an information between two neighboring nodes. This assumption is not realistic in practice…
Online fitted policy iteration based on extreme learning machines
2016
Reinforcement learning (RL) is a learning paradigm that can be useful in a wide variety of real-world applications. However, its applicability to complex problems remains problematic due to different causes. Particularly important among these are the high quantity of data required by the agent to learn useful policies and the poor scalability to high-dimensional problems due to the use of local approximators. This paper presents a novel RL algorithm, called online fitted policy iteration (OFPI), that steps forward in both directions. OFPI is based on a semi-batch scheme that increases the convergence speed by reusing data and enables the use of global approximators by reformulating the valu…
An Ontology to Support Semantic Management of FMEA Knowledge
2016
<p>Risk mitigation has always been a special concern for organization’s strategic management. Various tools and techniques have been developed to manage risk in an effective way. Failure Mode and Effects Analysis (FMEA) is one of the tools used for effective assessment of risk. It analyzes all potential failure modes, their causes, and effects on a product or process. Moreover it recommends actions to mitigate failures in order to enhance product reliability. Organizations spend their resources and domain experts make their efforts to complete this analysis. It further helps organizations identify the expected risks and plan strategies in advance to tackle them. But unfortunately the …
Modeling and control of uncertain nonlinear systems
2018
A survey of the methodologies associated with the modeling and control of uncertain nonlinear systems has been given due importance in this paper. The basic criteria that highlights the work is relied on the various patterns of techniques incorporated for the solutions of fuzzy equations that corresponds to fuzzy controllability subject. The solutions which are generated by these equations are considered to be the controllers. Currently, numerical techniques have come out as superior techniques in order to solve these types of problems. The implementation of neural networks technique is contributed in the complex way of dealing the appropriate coefficients and solutions of the fuzzy systems.