Under complex drilling working conditions, it is difficult to completely describe the working
state of the drilling pump fluid end with a single-source signal to achieve a high fault …

Abstract Convolutional Neural Network (CNN) is a prevalent topic in deep learning (DL)
research for their architectural advantages. CNN relies heavily on hyperparameter …

With the increasing demand for automated manufacturing and logistics system, interior
permanent magnet synchronous motors (IPMSMs) are being actively researched because of …

Fault diagnosis and detection in electrical power systems need a development of new and
robust supervision structures. In the last years, different intelligent monitoring methods have …

This paper establishes a framework to analyze the state of grinding equipment by vibration
signals of multi-sensors, which aims to solve the difficult problem of online quality monitoring …

The transmission line is an essential and long element that plays a vital role in the operation
of an electric power system. Quick and accurate fault detection along with classification …

Background The significant nonlinearity between the monitoring variables introduces
challenges in the task of features extraction when implementing fault detection for an …

After installation, the long-term efficient operation dominates the profitability of photovoltaic
(PV) generation systems. Unlike large-scale PV plants, distributed PV systems are relatively …

This paper investigates the application of one-dimensional convolutional neural networks
(1D CNNs) for damage detection in standardized structural components, addressing the …

Regular inspection and monitoring of various critical equipment (porcelain insulators
including pins or discs) available on power grid lines is required for several reasons, such …