The use of artificial neural network models to enrich the analytical and predictive capabilities
of decision support systems in manufacturing has increased. The growing complexity and …

In the era of Industry 4.0, highly complex production equipment is becoming increasingly
integrated and intelligent, posing new challenges for data-driven process monitoring and …

Artificial intelligence (AI) integration in the solar energy industry has created new
opportunities for reshaping the renewable energy sector. The numerous ways that AI is …

电力设备的运行状态与电力系统的稳定及安全密切相关. 全面, 准确地掌握电力设备的内外部多
源数据, 并通过科学的手段进行信息汇总和融合, 从而对设备的运行状态与变化趋势做出准确的 …

This paper presents a machine learning-based approach to power transformer fault
diagnosis based on dissolved gas analysis (DGA), a bat algorithm (BA), optimizing the …

Transformers are playing an increasingly significant part in energy conversion, transmission,
and distribution, which link various resources, including conventional, renewable, and …

The technical and financial management of power substations involves the evaluation of the
operational condition of power transformers. Evaluation is an essential stage for maintaining …

The growing interest in artificial intelligence has led to current data-driven predictive
maintenance (PdM) relying on machine learning (ML) algorithms. Although ML algorithms …

Energy is a basic necessity in every country. The worldwide demand for energy will rise due
to the developments of power generation in industrial, service, and residential sectors. A …

Predictive maintenance, as a form of pro-active maintenance, has increasing usage and
shows significant superiority over the corrective and preventive maintenance. However …