An Enhanced Evolutionary Technique for the Generation of Compact Reconfigurable Scan-Network Tests

Nowadays many Integrated Systems embed auxiliary on-chip instruments whose function is to perform test, debug, calibration, configuration, etc. The growing complexity and the increasing number of these instruments have led to new solutions for their access and control, such as the IEEE 1687 standard. The standard introduces an infrastructure composed of scan chains incorporating configurable elements for accessing the instruments in a flexible manner. Such an infrastructure is known as Reconfigurable Scan Network or RSN. Since permanent faults affecting the circuitry can cause malfunction, i.e., inappropriate behaviour, detecting them is of utmost importance. This paper addresses the issue of generating effective sequences for testing the reconfigurable elements within RSNs using evolutionary computation. Test configurations are extracted with automatic test pattern generation (ATPG) and used to guide the evolution. Postprocessing techniques are proposed to improve the evolutionary fittest solution. Results on a standard set of benchmark networks show up to 27% reduced test time with respect to test generation based on RSN exploratio

Reproducing Failures in Fault Signatures

Software often fails in the field, however reproducing and debugging field failures is very challenging: the failure-inducing input may be missing, and the program setup can be complicated and hard to reproduce by the developers. In this paper, we propose to generate fault signatures from the failure locations and the original source code to reproduce the faults in small executable programs. We say that a fault signature reproduces the fault in the original program if the two failed in the same location, triggered the same error conditions after executing the same selective sequences of failure-inducing statements. A fault signature aims to contain only sufficient statements that can reproduce the faults. That way, it provides some context to inform how a fault is developed and also avoids unnecessary complexity and setups that may block fault diagnosis. To compute fault signatures from the failures, we applied a path-sensitive static analysis tool to generate a path that leads to the fault, and then applied an existing syntactic patching tool to convert the path into an executable program. Our evaluation on real-world bugs from Corebench, BugBench, and Manybugs shows that fault signatures can reproduce the fault for the original programs. Because fault signatures are less complex, automatic test input generation tools generated failure-inducing inputs that could not be generated by using the entire programs. Some failure-inducing inputs can be directly transferred to the original programs. Our experimental data are publicly available at https://doi.org/10.5281/zenodo.5430155

Vibration Fault Diagnosis in Wind Turbines based on Automated Feature Learning

A growing number of wind turbines are equipped with vibration measurement systems to enable a close monitoring and early detection of developing fault conditions. The vibration measurements are analyzed to continuously assess the component health and prevent failures that can result in downtimes. This study focuses on gearbox monitoring but is applicable also to other subsystems. The current state-of-the-art gearbox fault diagnosis algorithms rely on statistical or machine learning methods based on fault signatures that have been defined by human analysts. This has multiple disadvantages. Defining the fault signatures by human analysts is a time-intensive process that requires highly detailed knowledge of the gearbox composition. This effort needs to be repeated for every new turbine, so it does not scale well with the increasing number of monitored turbines, especially in fast growing portfolios. Moreover, fault signatures defined by human analysts can result in biased and imprecise decision boundaries that lead to imprecise and uncertain fault diagnosis decisions. We present a novel accurate fault diagnosis method for vibration-monitored wind turbine components that overcomes these disadvantages. Our approach combines autonomous data-driven learning of fault signatures and health state classification based on convolutional neural networks and isolation forests. We demonstrate its performance with vibration measurements from two wind turbine gearboxes. Unlike the state-of-the-art methods, our approach does not require gearbox-type specific diagnosis expertise and is not restricted to predefined frequencies or spectral ranges but can monitor the full spectrum at once

The Global Positioning System observations on the 2011 Tohoku M9 earthquake genesis process with Physical Wavelets

Tohoku is at the eastern edge of a continental tectonic plate overriding a subducting oceanic plate. The GPS observations on the 2011 Tohoku M9 earthquake are the daily displacements at the stations in Tohoku and the Northwest Pacific Ocean. For the noisy and non-differentiable time series, a mathematical tool named Physical Wavelets defines the equations quantifying the earthquake genesis process of nine months and the event predictability. Tohoku is still under the 2011 event. As of May 22, 2021, the GPS observations on the Pacific and the Philippine Sea Plate suggest no imminent megathrust ruptures in the subduction zones.Comment: 72 pages, 45 figures, an update from part of the patent (130 pages, 85 figures) here https://patents.google.com/patent/JP5798545B2/e

On testing effectiveness of metamorphic relations: A case study

One fundamental challenge for software testing is the oracle problem which means that either there does not exist a mechanism (called oracle) to verify the test output given any possible program input or it is very expensive if not impossible to apply the oracle. Metamorphic testing is an innovative approach to oracle problem. In metamorphic testing metamorphic relations are derived from the innate characteristics of the software under test. These relations can help to generate test data and verify the correctness of the test result without the need of oracle. The effectiveness of metamorphic relations can play a significant role in the testing process. It has been argued that the metamorphic relations that cause different software execution behaviors should have high fault detection ability. In this paper we conduct a case study to analyze the relationship between the execution behavior and the fault-detection effectiveness of metamorphic relations. Some code coverage criteria are used to reflect the execution behavior. It is shown that there is a certain degree of correlation between the code coverage achieved by a metamorphic relation and its fault-detection effectiveness

Relationship between earthquake fault triggering and societal behavior using ant colony optimization

In this analysis, we use the ant behaviour in simulating a framework for analysis of complex interplay amongst short time-scale deformation, long time- scale tectonics for positive stress coupling and slip interactions in earthquake genesis modeling. Using the proposed improved ant colony algorithm for global optimization the best solution ants within the search and the circulation of the optimal solution as the initial solution search, to expand its search, to avoid falling into local optimum  of  trigger zones analysis for earthquake occurrences. In order to validate the avalanche behaviour and corresponding nucleation we  best solution as the initial solution is adopted in order to widen searching scope to avoid getting into local optimum . In this proposed framework, an ant colony model is simulated to identify the physical framework of identifying trigger basins for the precursors to geodynamic model of propagation for precursory stress-strain signals. The disturbances at trigger basins cause the collapse of a subsystem leading to stress evolution and slip nucleation. Trigger basins help identify the zone of earthquake source nucleation as an index of ? and ? for strain analysis. The stress strain network can be interpreted by the increase in steady-state energy transmitted due to redistribution of stress accumulation into the earth tectonic framework. Sand pile behaviour model has been modeled through ant colony optimization for forecasting of likelihood time of triggering influences of lithosphere on the basis of critical zones of lithosphere where dump of elastic pressure is possible. The ant colony adaptive framework consisted of vertices representing the stress-strain component and edges, representing scored transformations for global coupling effects have been constructed for dynamic monitoring of stress and strain behaviour. Triggering basins serve as harbingers of large earthquake where stress-strain interactions have been analyzed by the quasi-static mechanics of seismic precursory stress-strain propagation in the crustal lithosphere. The study shows that dynamic variation of stress drop due to saved up pressure can be modeled by ant colony framework for steady state release due to trigger and global correlation framework. The simulation framework shows that with time, spatial triggering points can be negatively coupled and these interact with lesser impact, while positive coupling occurs only with more distant zones of stress generation for geodynamic frameworks, suggesting that the structural heterogeneities within the causative rocks associated with cracks and pores can dictate the pattern of stress – strain interactions and earthquake generating processes. Keywords: crack–porous, ant colony, geo-dynamical framework, stress-strain transmission, emergenc

Advances in the Field of Electrical Machines and Drives

Electrical machines and drives dominate our everyday lives. This is due to their numerous applications in industry, power production, home appliances, and transportation systems such as electric and hybrid electric vehicles, ships, and aircrafts. Their development follows rapid advances in science, engineering, and technology. Researchers around the world are extensively investigating electrical machines and drives because of their reliability, efficiency, performance, and fault-tolerant structure. In particular, there is a focus on the importance of utilizing these new trends in technology for energy saving and reducing greenhouse gas emissions. This Special Issue will provide the platform for researchers to present their recent work on advances in the field of electrical machines and drives, including special machines and their applications; new materials, including the insulation of electrical machines; new trends in diagnostics and condition monitoring; power electronics, control schemes, and algorithms for electrical drives; new topologies; and innovative applications