Search results for "Artificial"
showing 10 items of 7394 documents
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.
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…
Teleoperation of industrial robot manipulators based on augmented reality
2020
[EN] This research develops a novel teleoperation for robot manipulators based on augmented reality. The proposed interface is equipped with full capabilities in order to replace the classical teach pendant of the robot for carrying out teleoperation tasks. The proposed interface is based on an augmented reality headset for projecting computer-generated graphics onto the real environment and a gamepad to interact with the computer-generated graphics and provide robot commands. In order to demonstrate the benefits of the proposed method, several usability tests were conducted using a 6R industrial robot manipulator in order to compare the proposed interface and the conventional teach pendant…
Harsanyi Power Solutions for Cooperative Games on Voting Structures
2019
International audience; This paper deals with Harsanyi power solutions for cooperative games in which partial cooperation is based on specific union stable systems given by the winning coalitions derived from a voting game. This framework allows for analyzing new and real situations in which there exists a feedback between the economic influence of each coalition of agents and its political power. We provide an axiomatic characterization of the Harsanyi power solutions on the subclass of union stable systems arisen from the winning coalitions from a voting game when the influence is determined by a power index. In particular, we establish comparable axiomatizations, in this context, when co…
Intelligent virtual manufacturing cell formation in cloud-based design and manufacturing
2018
Abstract Cloud-based design and manufacturing (CBDM) can presumably stimulate greater intelligence in cloud-based models. This paper assumes that cloud-based design for cellular manufacturing can be referred to as a multiscale, uncertain, and dynamic service-oriented network where a set of CAD parts, modelled by set of features, can be manufactured in intelligent virtual manufacturing cells under certain constraints. Using the concepts of the holon and the attractor, integrating the uncertainty in the modelling of part design and part–manufacturing network, an approach to address intelligent virtual manufacturing cell formation in CBDM is proposed. The powerful role of the CAD features is e…
Scalable implementation of measuring distances in a Riemannian manifold based on the Fisher Information metric
2019
This paper focuses on the scalability of the Fisher Information manifold by applying techniques of distributed computing. The main objective is to investigate methodologies to improve two bottlenecks associated with the measurement of distances in a Riemannian manifold formed by the Fisher Information metric. The first bottleneck is the quadratic increase in the number of pairwise distances. The second is the computation of global distances, approximated through a fully connected network of the observed pairwise distances, where the challenge is the computation of the all sources shortest path (ASSP). The scalable implementation for the pairwise distances is performed in Spark. The scalable…
Haptic and Visual Feedback Assistance for Dual-Arm Robot Teleoperation in Surface Conditioning Tasks
2020
Contact driven tasks, such as surface conditioning operations (wiping, polishing, sanding, etc.), are difficult to program in advance to be performed autonomously by a robotic system, specially when the objects involved are moving. In many applications, human-robot physical interaction can be used for the teaching, specially in learning from demonstrations frameworks, but this solution is not always available. Robot teleoperation is very useful when user and robot cannot share the same workspace due to hazardous environments, inaccessible locations, or because of ergonomic issues. In this sense, this article introduces a novel dual-arm teleoperation architecture with haptic and visual feedb…
Machine Learning Approaches for Activity Recognition and/or Activity Prediction in Locomotion Assistive Devices—A Systematic Review
2020
Locomotion assistive devices equipped with a microprocessor can potentially automatically adapt their behavior when the user is transitioning from one locomotion mode to another. Many developments in the field have come from machine learning driven controllers on locomotion assistive devices that recognize/predict the current locomotion mode or the upcoming one. This review synthesizes the machine learning algorithms designed to recognize or to predict a locomotion mode in order to automatically adapt the behavior of a locomotion assistive device. A systematic review was conducted on the Web of Science and MEDLINE databases (as well as in the retrieved papers) to identify articles published…
Extreme minimal learning machine: Ridge regression with distance-based basis
2019
The extreme learning machine (ELM) and the minimal learning machine (MLM) are nonlinear and scalable machine learning techniques with a randomly generated basis. Both techniques start with a step in which a matrix of weights for the linear combination of the basis is recovered. In the MLM, the feature mapping in this step corresponds to distance calculations between the training data and a set of reference points, whereas in the ELM, a transformation using a radial or sigmoidal activation function is commonly used. Computation of the model output, for prediction or classification purposes, is straightforward with the ELM after the first step. In the original MLM, one needs to solve an addit…