Fault diagnosis and location play a pivotal role in expediting fault restoration and enhancing power system resilience. However, integrating distributed generation and diverse load profiles has led to more complicated distribution networks, intensifying fault diagnosis and location challenges. Hence, there is a need to transform traditional distrib...
Multi-three-phase motor drives are experiencing a significant development among the multiphase solutions since they are configured as multiple three-phase units operating in parallel. Although the literature reports several torque controllers able to deal with multi-three-phase motors, most of them obtain high performance of torque regulation as lo...
As more deep learning algorithms enter safety-critical application domains, the importance of analyzing their resilience against hardware faults cannot be overstated. Most existing works focus on bit-flips in memory, fewer focus on compute errors, and almost none study the effect of hardware faults on adversarially trained convolutional neural netw...
Dealing with time-varying high dimensional data is a big problem for real time pattern recognition. Non-stationary topological representation can be addressed in two ways, according to the application: life-long modeling or by forgetting the past. The G-EXIN neural network addresses this problem by using life-long learning. It uses an anisotropic c...
This paper focuses on power system fault diagnosis based on Weighted Corrective Fuzzy Reasoning Spiking Neural P Systems with real numbers (rWCFRSNPSs) to propose a graphic fault diagnosis method, called FD-WCFRSNPS. In the FD-WCFRSNPS, an rWCFRSNPS is proposed to model the logical relationships between faults and potential warning messages trigger...
Ensemble empirical mode decomposition (EEMD) is a newly developed noise assisted method aimed to solve mode mixing problem exists in empirical mode decomposition (EMD) method. Although EEMD has been utilized in various applications successfully, small defects of bearings are not able to be detected, especially in automatic defect detection, when on...
Roller bearings are widely used in rotating machinery and are very important so that one of the major reasons for machine breakdown is their failure. Although numerous studies have been done for damage identification using empirical mode decomposition (EMD) and feature extraction from intrinsic mode functions (IMFs), EMD has some drawbacks such as ...
The continues improvement of manufacturing technologies allows the realization of integrated circuits containing an ever increasing number of transistors. A major part of these devices is devoted to realize SRAM blocks. Test and diagnosis of SRAM circuits are therefore an important challenge for improving quality of next generation integrated circu...
The continues improvement in manufacturing process density for very deep sub micron technologies constantly leads to new classes of defects in memory devices. Exploring the effect of fabrication defects in future technologies, and identifying new classes of realistic functional fault models with their corresponding test sequences, is a time consumi...
