Search results for "Computer science"
showing 10 items of 22367 documents
Surrogate models for the compressive strength mapping of cement mortar materials
2021
Despite the extensive use of mortar materials in constructions over the last decades, there is not yet a robust quantitative method available in the literature, which can reliably predict their strength based on the mix components. This limitation is attributed to the highly nonlinear relation between the mortar’s compressive strength and the mixed components. In this paper, the application of artificial intelligence techniques for predicting the compressive strength of mortars is investigated. Specifically, Levenberg–Marquardt, biogeography-based optimization, and invasive weed optimization algorithms are used for this purpose (based on experimental data available in the literature). The c…
Tutorial on dynamic analysis of the Costas loop
2016
Abstract Costas loop is a classical phase-locked loop (PLL) based circuit for carrier recovery and signal demodulation. The PLL is an automatic control system that adjusts the phase of a local signal to match the phase of the input reference signal. This tutorial is devoted to the dynamic analysis of the Costas loop. In particular the acquisition process is analyzed. Acquisition is most conveniently described by a number of frequency and time parameters such as lock-in range, lock-in time, pull-in range, pull-in time, and hold-in range. While for the classical PLL equations all these parameters have been derived (many of them are approximations, some even crude approximations), this has not…
Rotation estimation and vanishing point extraction by omnidirectional vision in urban environment
2012
International audience; Rotation estimation is a fundamental step for various robotic applications such as automatic control of ground/aerial vehicles, motion estimation and 3D reconstruction. However it is now well established that traditional navigation equipments, such as global positioning systems (GPSs) or inertial measurement units (IMUs), suffer from several disadvantages. Hence, some vision-based works have been proposed recently. Whereas interesting results can be obtained, the existing methods have non-negligible limitations such as a difficult feature matching (e.g. repeated textures, blur or illumination changes) and a high computational cost (e.g. analyze in the frequency domai…
Towards the Design of Robotic Drivers for Full-Scale Self-Driving Racing Cars
2019
Autonomous vehicles are undergoing a rapid development thanks to advances in perception, planning and control methods and technologies achieved in the last two decades. Moreover, the lowering costs of sensors and computing platforms are attracting industrial entities, empowering the integration and development of innovative solutions for civilian use. Still, the development of autonomous racing cars has been confined mainly to laboratory studies and small to middle scale vehicles. This paper tackles the development of a planning and control framework for an electric full scale autonomous racing car, which is an absolute novelty in the literature, upon which we report our preliminary experim…
Novel Threshold Calculations for Remaining Useful Lifetime Estimation of Rolling Element Bearings
2018
The prognostics objective is to avoid sudden machinery breakdowns and to estimate the remaining useful life after initial degradation. Typically, physical health indicators are derived from available sensor data, and a mathematical model is tuned to fit them. The time it takes for the model to reach a failure threshold is the estimated remaining useful life. The failure threshold may be determined from historical failure data, but that is not always readily available. ISO standard 10816–3 defines permissible velocity vibration levels for machines that may be used as a failure threshold. However, velocity vibration is not suitable for bearing prognostics due to the effect of integration from…
Autonomous Bearing Fault Diagnosis Method based on Envelope Spectrum
2017
Abstract Rolling element bearings are one of the fundamental components of a machine, and their failure is the most frequent cause of machine breakdown. Monitoring the bearing condition is vital to preventing unexpected shutdowns and improving their maintenance planning. Specifically, the bearing vibration can be measured and analyzed to diagnose bearing faults. Accurate fault diagnosis can be achieved by analyzing the envelope spectrum of a narrowband filtered vibration signal. The optimal narrow-band is centered at the resonance frequency of the bearing. However, how to determine the optimal narrow-band is a challenge. Several methods aim to identify the optimal narrow-band, but they are …
Multi-Component Fault Detection in Wind Turbine Pitch Systems Using Extended Park's Vector and Deep Autoencoder Feature Learning
2018
Pitch systems are among the wind turbine components with most frequent failures. This article presents a multicomponent fault detection for induction motors and planetary gearboxes of the electric pitch drives using only the three-phase motor line currents. A deep autoencoder is used to extract features from the extended Park's vector modulus of the motor three-phase currents and a support vector machine to classify faults. The methodology is validated in a laboratory setup of a scaled pitch drive, with four commonly occurring faults, namely, the motor stator turns fault, broken rotor bars fault, planetary gearbox bearing fault and planet gear faults, under varying load and speed conditions.
Ant Colony Optimisation-Based Classification Using Two-Dimensional Polygons
2016
The application of Ant Colony Optimization to the field of classification has mostly been limited to hybrid approaches which attempt at boosting the performance of existing classifiers (such as Decision Trees and Support Vector Machines (SVM)) — often through guided feature reductions or parameter optimizations.
Reducing the observation error in a WSN through a consensus-based subspace projection
2013
An essential process in a Wireless Sensor Network is the noise mitigation of the measured data, by exploiting their spatial correlation. A widely used technique to achieve this reduction is to project the measured data into a proper subspace. We present a low complexity and distributed algorithm to perform this projection. Unlike other algorithms existing in the literature, which require the number of connections at every node to be larger than the dimension of the involved subspace, our algorithm does not require such dense network topologies for its applicability, making it suitable for a larger number of scenarios. Our proposed algorithm is based on the execution of several consensus pro…
Advanced teleoperation and control system for industrial robots based on augmented virtuality and haptic feedback
2021
[EN] There are some industrial tasks that are still mainly performed manually by human workers due to their complexity, which is the case of surface treatment operations (such as sanding, deburring, finishing, grinding, polishing, etc.) used to repair defects. This work develops an advanced teleoperation and control system for industrial robots in order to assist the human operator to perform the mentioned tasks. On the one hand, the controlled robotic system provides strength and accuracy, holding the tool, keeping the right tool orientation and guaranteeing a smooth approach to the workpiece. On the other hand, the advanced teleoperation provides security and comfort to the user when perf…