AIMC Topic: Electricity

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Optically addressable dielectric elastomer actuator arrays using embedded percolative networks of zinc oxide nanowires.

Materials horizons Nov 28, 2022
Dielectric elastomer actuators (DEAs) are electrically driven soft actuators that generate fast and reversible deformations, enabling lightweight actuation of many novel soft robots and haptic devices. However, the high-voltage operation of DEAs comb...
Robotics Zinc Oxide Elastomers Electricity Nanowires
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Deep Scattering Spectrum Germaneness for Fault Detection and Diagnosis for Component-Level Prognostics and Health Management (PHM).

Sensors (Basel, Switzerland) Nov 22, 2022
Most methodologies for fault detection and diagnosis in prognostics and health management (PHM) systems use machine learning (ML) or deep learning (DL), in which either some features are extracted beforehand (in the case of typical ML approaches) or ...
Machine Learning Prognosis Health Status Acoustics Electricity
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A Deep Learning Approach to Detect Anomalies in an Electric Power Steering System.

Sensors (Basel, Switzerland) Nov 20, 2022
As anomaly detection for electrical power steering (EPS) systems has been centralized using model- and knowledge-based approaches, EPS system have become complex and more sophisticated, thereby requiring enhanced reliability and safety. Since most cu...
Reproducibility of Results Deep Learning ROC Curve Electricity
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Thermographic Fault Diagnosis of Shaft of BLDC Motor.

Sensors (Basel, Switzerland) Nov 5, 2022
A technique of thermographic fault diagnosis of the shaft of a BLDC (Brushless Direct Current Electric) motor is presented in this article. The technique works for the shivering of the thermal imaging camera in the range of 0-1.5 [m/s]. An electric s...
Neural Networks, Computer Electricity
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Electric-field-coupled oscillators for collective electrochemical perception in biohybrid robotics.

Bioinspiration & biomimetics Nov 2, 2022
This work explores the application of nonlinear oscillators coupled by an electric field in water, inspired by weakly electric fish. Such coupled oscillators operate in clear and colloidal (mud, bottom silt) water and represent a collective electroch...
Animals Water Robotics Perception Electricity Electric Fish
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K-Means Clustering and Bidirectional Long- and Short-Term Neural Networks for Predicting Performance Degradation Trends of Built-In Relays in Meters.

Sensors (Basel, Switzerland) Oct 25, 2022
The built-in relay in a meter is a key control component of a smart meter, and its reliability determines whether the user can use electricity safely and smoothly. In this paper, the degradation characteristics of the arc-burning energy are enhanced ...
Neural Networks, Computer Reproducibility of Results Cluster Analysis Electricity
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Individualized Short-Term Electric Load Forecasting Using Data-Driven Meta-Heuristic Method Based on LSTM Network.

Sensors (Basel, Switzerland) Oct 17, 2022
Short-term load forecasting is viewed as one promising technology for demand prediction under the most critical inputs for the promising arrangement of power plant units. Thus, it is imperative to present new incentive methods to motivate such power ...
Neural Networks, Computer Algorithms Forecasting Heuristics Electricity
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An open-source deep learning model for predicting effluent concentration in capacitive deionization.

The Science of the total environment Oct 1, 2022
To effectively evaluate the performance of capacitive deionization (CDI), an electrochemical ion separation technology, it is necessary to accurately estimate the number of ions removed (effluent concentration) according to energy consumption. Herein...
Water Purification Deep Learning Electrodes Ions Electricity
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GADF-VGG16 based fault diagnosis method for HVDC transmission lines.

PloS one Sep 23, 2022
Transmission lines are most prone to faults in the transmission system, so high-precision fault diagnosis is very important for quick troubleshooting. There are some problems in current intelligent fault diagnosis research methods, such as difficulty...
Neural Networks, Computer Algorithms Electricity
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Improving the Efficiency of Multistep Short-Term Electricity Load Forecasting via R-CNN with ML-LSTM.

Sensors (Basel, Switzerland) Sep 13, 2022
Multistep power consumption forecasting is smart grid electricity management's most decisive problem. Moreover, it is vital to develop operational strategies for electricity management systems in smart cities for commercial and residential users. How...
Humans Neural Networks, Computer Forecasting Disease Progression Electricity
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