Abstract In the “Industry 4.0” era, autonomous and self-adaptive industrial machining attracts
significant attention in professional manufacturing. This trend originates from the rising …

Carbon neutrality has become a global consensus for green development, and solar
photovoltaic power generation has increasingly become one of the key technologies for …

In recent years, swarm intelligence algorithms have received extensive attention and
research. Swarm intelligence algorithms are a biological heuristic method, which is widely …

This paper introduces a new intelligent integration between an IoT platform and deep
learning neural network (DNN) algorithm for the online monitoring of computer numerical …

Transformer oil insulation condition may be deteriorated due to electrical and thermal faults,
which may lead to transformer failure and system outage. In this regard, the first part of this …

The wireless sensor nodes used for monitoring the condition of grid equipment always be
powered by disposable batteries. However, it introduces disadvantages, such as …

Power transformer represents an important equipment in electric power systems.
Transformers are not only a source of power outages for electric utilities, but they also affect …

Piezoelectric composites have become increasingly important in energy harvesting from
vibration and, more recently, flow-induced vibration. The compatibility of piezoelectric …

Fault diagnosis is important to the timely repair of the power transformer. However, machine
learning has not been exploited effectively for fault diagnosis due to the limitation of multi …

It is always challenging and meaningful to further enhance the feature extraction capability
of the convolutional neural network (CNN) and understand the internal working principle of …