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This research describes a deep learning-based artificial neural network (ANN) approach for the detection, classification, and localization of series faults (open conductor faults) in power distribution networks. The ANN ...

Arc fault, especially series arc fault, has been the primary cause of electrical fire, which is intermittent, hidden, random and uncertain, difficult to detect, and serious harm. The characteristics of arc fault are firs...

Abstract A precise detection of the fault feature parameter of motor current is a new research hotspot in the broken rotor bar (BRB) fault diagnosis of induction motors. Discrete Fourier transform (DFT) is the most popul...

Abstract Rolling element bearings are key components of mechanical equipment. The bearing fault characteristics are affected by the interaction in the vibration signals. The low harmonics of the bearing characteristic fr...

Abstract Adaptive wavelet filtering is a very important fault feature extraction method in the domain of condition monitoring; however, owing to the time-consuming computation and difficulty of choosing criteria used to ...

Web spam degrades the reliability of search engine results by manip- ulating ranking algorithms to raise webpage positions artificially. TrustRank is a popular link-based anti-spam method, its ability to demote highly ra...

Fault Detection and Diagnosis (FDD) is crucial for ensuring safe, reliable, and energy-efficient operation of collaborative robots, especially with the growth of Industry 4.0. Industrial robots are nonlinear, complex, an...

Regression testing plays a critical role in ensuring the reliability and quality of software following continuous integration and development. However, executing all test cases during regression testing can be time-consu...

The aim of this study is the early detection of developing insulation defects in high-voltage oil-filled bushings based on the analysis of the temporal behavior of diagnostic indicators rather than only their comparison ...

Most of the control schemes for chemical plants are developed under the assumption that the sensors and the actuators are free from faults. However, the occurrence of faults will cause degradation in the closed-loop perf...

Abstract This paper presents an eyebolt structural fault detection system, based on the analysis of multiple electromagnetic parameters through a random forest classifier trained by both measurements and high-fidelity si...

This paper presents measured data and electromagnetic FEM field calculations as techniques for detecting and analyzing eccentricity in three-phase induction motors. Also it presents experimental results for detecting bro...

The detection of high impedance faults (HIFs) plays a crucial role in modern active distribution systems to prevent risks like equipment failures, fire incidents, and disruptions in service, while maintaining a stable po...

Abstract Supervised fault diagnosis typically assumes that all the types of machinery failures are known. However, in practice unknown types of defect, i.e., novelties, may occur, whose detection is a challenging task. I...

In modern industrial process monitoring of multivariate time series, the effectiveness of data-driven event detection is often constrained by scarce labels and the dynamic complexity of real-world telemetry. While unsupe...

Nowadays, the use of renewable energy is increasing, especially distributed power generation (DG) connected to the power grid. There are several problems when DG is connected to the grid. The principal obstacle pertains ...

The tools for fault impact analysis are important for the deployment of critical mission systems. These tools can be also used as a development phase aid. We introduce several concepts related to "business alarms". Busin...

Abstract This study presents a tracking and fault-tolerant controller architecture for uncertain steer-by-wire (SbW) systems using model predictive control in the presence of actuator malfunction and the nonlinear proper...

Abstract Synchronous reluctance motors (SynRMs) are increasingly critical in industrial and traction applications due to their high efficiency, magnet-free construction, and thermal robustness. However, fault diagnosis f...

Abstract Effective fault diagnosis and fault-tolerant control method for aeronautics electromechanical actuator is concerned in this paper. By borrowing the advantages of model-driven and data-driven methods, a fault tol...

Abstract Robustness against measurement uncertainties is crucial for gas turbine engine diagnosis. While current research focuses mainly on measurement noise, measurement bias remains challenging. This study proposes a n...

Abstract Considerable studies have been carried out on fault diagnosis of gears, with most of them concentrated on conventional vibration analysis. However, besides the complexity of gear dynamics, the diagnosis results ...

Use cases for emerging quantum computing platforms become economically relevant as the efficiency of processing and availability of quantum computers increase. We assess the performance of Restricted Boltzmann Machines (...

Power transformers are critical components of power systems, and their safe and reliable operation is essential for both industrial and residential applications. Real-time condition monitoring and early fault detection a...