AIMC Topic: Electricity

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Fabric tearing performance state perception and classification driven by multi-source data.

PloS one
The tear strength of textiles is a crucial characteristic of product quality. However, during the laboratory testing of this indicator, factors such as equipment operation, human intervention, and test environment can significantly influence the resu...

Flexible large-area ultrasound arrays for medical applications made using embossed polymer structures.

Nature communications
With the huge progress in micro-electronics and artificial intelligence, the ultrasound probe has become the bottleneck in further adoption of ultrasound beyond the clinical setting (e.g. home and monitoring applications). Today, ultrasound transduce...

Non-invasive load monitoring based on deep learning to identify unknown loads.

PloS one
With the rapid development of smart grids, society has become increasingly urgent to solve the problems of low energy utilization efficiency and high energy consumption. In this context, load identification has become a key element in formulating sci...

Training Universal Deep-Learning Networks for Electromagnetic Medical Imaging Using a Large Database of Randomized Objects.

Sensors (Basel, Switzerland)
Deep learning has become a powerful tool for solving inverse problems in electromagnetic medical imaging. However, contemporary deep-learning-based approaches are susceptible to inaccuracies stemming from inadequate training datasets, primarily consi...

Non-fragile guaranteed cost control of microbial fuel cells.

ISA transactions
A microbial fuel cell (MFC), which is a new type of energy source, utilises electrogenic bacteria in sewage or soil to convert chemical energy into electrical energy. MFCs typically require an external controller to provide a stable output voltage to...

Selection/control concurrent optimization of BLDC motors for industrial robots.

PloS one
This paper aims to concurrently select and control off-the-shelf BLDC motors of industrial robots by using a synergistic model-based approach. The BLDC motors are considered with trapezoidal back-emf, where the three-phase (a,b,c) dynamics of motors ...

Techno-economic optimization of a new waste-to-energy plant for electricity, cooling, and desalinated water using various biomass for emission reduction.

Chemosphere
A newly developed waste-to-energy system using a biomass combined energy system designed and taken into account for electricity generation, cooling, and freshwater production has been investigated and modeled in this project. The investigated system ...

Application of artificial intelligence-based methods in bioelectrochemical systems: Recent progress and future perspectives.

Journal of environmental management
Bioelectrochemical Systems (BESs) leverage microbial metabolic processes to either produce electricity by degrading organic matter or consume electricity to assist metabolism, and can be used for various applications such as energy production, wastew...

Condition Monitoring of Wind Turbine Systems by Explainable Artificial Intelligence Techniques.

Sensors (Basel, Switzerland)
The performance evaluation of wind turbines operating in real-world environments typically relies on analyzing the power curve, which shows the relationship between wind speed and power output. However, conventional univariate models that consider on...

A New NILM System Based on the SFRA Technique and Machine Learning.

Sensors (Basel, Switzerland)
In traditional nonintrusive load monitoring (NILM) systems, the measurement device is installed upstream of an electrical system to acquire the total aggregate absorbed power and derive the powers absorbed by the individual electrical loads. Knowing ...