The growing complexity of machinery and the increasing demand for operational efficiency
and safety have driven the development of advanced fault diagnosis techniques. Among …

Green building design strives to optimize energy efficiency, emissions reduction, cost-
effectiveness, and thermal comfort by accurately predicting and optimizing building …

Pipeline feature recognition is crucial for the reliability and safety of long-distance natural
gas pipelines. Utilizing manual or machine learning methods to recognize pipeline features …

Milling tools are critical to machining and manufacturing processes. Accurate diagnosis and
identification of faults occurring in milling tools during their operation are of utmost …

As industrial development drives the increasing demand for steel, accurate estimation of the
material's fatigue strength has become crucial. Fatigue strength, a critical mechanical …

This paper introduces a novel network, DDFE-Transformer (Data-Driven Feature Extraction-
Transformer), for fault diagnosis using acoustic emission signals. The DDFE-Transformer …

With the escalating global demand for renewable energy, the active coordinated control of
wind turbine is poised to become a crucial factor in ensuring the stable operation of new …

In the context of carbon neutrality and emission reduction goals, energy consumption
optimization in the oil and gas industry is crucial for reducing carbon emissions and …

Horizontal gas-liquid two-phase flow is common in oilfield gathering and transportation
systems, and the flow pattern significantly impacts pipeline operation. To ensure the safety …

Machine Learning-based fault detection approaches in energy systems have gained
prominence for their superior performance. These automated approaches can assist …