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This paper aims to study the influence of supply voltage variations on the external magnetic field emitted by grid-powered induction machines (IMs).

Two models are developed in the paper to analyse, for different supply voltage values, the influence of the variations of the magnetizing voltage for which there is a link with the tangential component of the external flux. The first is an analytical model based on the IM single-phase-equivalent circuit with variable magnetizing reactance to take into account the saturation of the magnetic circuit. The second is a numerical finite element simulation to model the same phenomenon. Results of both models are analysed with experimental measures of the external flux.

The study shows that the amplitude of the external field strongly depends on supply voltage values.

The investigation is mainly focused on the tangential component of the external magnetic field which is of high importance concerning the applicability of non-invasive methods of diagnosis, as electromagnetic torque estimation developed by the authors or internal fault determination.

The originality of the paper concerns the characterization of the external flux with the supply voltage for IMs. It is shown that the magnetic circuit radiates external flux differently with the load and with the supply voltage.

The purpose of this paper is to suggest a procedure which makes it possible to reduce the radial vibrations of doubly salient switched reluctance motors (SRMs).

An analytical method for the SRM radial vibration determination is first described. It is then extended to the active vibration reduction. An auxiliary winding equips the stator. The paper explains how the corresponding currents have to be adjusted to achieve a simple and robust control, with a special emphasis about the compatibility of the main and auxiliary supplies and about the reduction control principle. At last, an example of drastic noise reduction is presented.

The proposed method makes possible to define the theoretical vibration spectrum of SRM and thus it gives the major components to be reduced. The feasibility of automating the principle of active reduction is shown. The process of active reduction shows that a vibration component can be diminished by over 90 percent.

The active reduction is applied for reducing one component of the vibration spectrum. Future developments will focus on the simultaneous reduction of several components of vibration spectrum.

The method offers an automated process to reduce considerably the component of highest amplitude in the vibration spectrum.

This paper aims to investigate the efficacy of teeth flux sensors in detecting, locating and assessing the severity of short-circuit faults in the stator windings of induction machines.

The experimental study involves inducing short-circuit winding turn variations on the induction machine’s stator and continuously measuring the RMS values across teeth flux sensors. Two crucial steps are taken for machine diagnosis: measurements under load operating conditions for fault detection and measurements under no-load conditions to determine fault location and severity.

The experimental results demonstrate that the proposed approach using teeth flux sensors is reliable and effective in detecting, locating and evaluating the severity of stator winding faults.

While this study focuses on short-circuit faults, future research could explore other fault types and alternative sensor configurations to enhance the comprehensiveness of fault diagnosis.

The methodology outlined in this paper holds the potential to significantly reduce maintenance time and costs for induction machines, leading to substantial savings for companies.

This research contributes to the field by presenting an innovative approach that uses teeth flux sensors for a comprehensive fault diagnosis in induction machines. The originality lies in the effectiveness of this approach in providing reliable fault detection, location and severity evaluation.

The built environment is responsible for approximately 40% of the world’s energy consumption, 30% of raw material use, 25% of solid waste, 25% of water use, 12% of land use and 33% of greenhouse gas emissions. Thus, environmental improvement and decarbonization are becoming increasingly critical objectives for the construction industry. Sustainable construction can be achieved through several practices, including: considering life-cycle assessment, circular construction, resource efficiency and waste management and providing eco-efficient materials, reducing energy demands and consumption and incorporating low-carbon technologies and renewable energy sources. To achieve sustainable construction goals, it is critical to educate the future workforce about decarbonization, circular construction and how to overcome the challenges involved in transitioning to sustainable construction. This study aims to understand the gap in student knowledge related to decarbonization and circular construction and the importance of incorporating these topics in civil engineering and construction management curricula.

This study surveyed 120 undergraduate and graduate students at one of the largest minority-serving institutions in the USA to understand the gap in student knowledge related to decarbonization and circular construction as well as the importance of incorporating these topics in civil engineering and construction management curricula. The authors conducted several statistical measures to assess the consistency, reliability and adequacy of the sample size, including the Kaiser–Meyer–Olkin measure of sampling adequacy, the normality test to evaluate the appropriateness of using an ordered probit regression analysis and a multicollinearity test to observe the correlation between independent variables. The data was analyzed using ordered probit regression analysis to investigate the need for a curriculum that serves in educating students about decarbonization and circular construction.

The results of this research highlight the gaps in students’ knowledge pertaining to sustainable practices and the importance of providing future construction workforce with such knowledge to tackle global inevitable challenges.

The findings of this study contribute to sustainable construction bodies of knowledge by advocating for a reformed curriculum to prepare the future workforce and adopt less carbonized, more circular approaches within the engineering and construction industry.

Despite the wide dissemination and application of current signature analysis (CSA) in general industry, CSA is not commonly used in the wind industry, where the use of vibration signals predominates. Therefore, the purpose of this paper is to review the use of generator CSA (GCSA) in the online fault detection and diagnosis of wind turbines (WTs).

This is a bibliographical investigation in which the use of GCSA for the maintenance of WTs is analyzed. A section is dedicated to each of the main components, including the theoretical foundations on which GCSA is based and the methodology, mathematical models and signal processing techniques used by the proposals that exist on this topic.

The lack of appropriate technology and mathematical models, as well as the difficulty involved in performing actual studies in the field and the lack of research projects, has prevented the expansion of the use of GCSA for fault detection of other WT components. This research area has yet to be explored, and the existing investigations mainly focus on the gearbox and the doubly fed induction generator; however, modern signal treatment and artificial intelligence techniques could offer new opportunities in this field.

Although literature on the use of GCSA for the detection and diagnosis of faults in WTs has been published, these papers address specific applications for each of the WT components, especially gearboxes and generators. For this reason, the main contribution of this study is providing a comprehensive vision for the use of GCSA in the maintenance of WTs.

The purpose of this paper is to obtain an integrated method for inter-turn short circuit fault detection for the cage-rotor induction machine (CRIM) considering saturation effect.

The magnetic equivalent circuit (MEC) is proposed for machine modeling and nonlinear B-H curve is considered for saturation effect. The machine has some differential equations which are converted to algebraic type by trapezoidal method. On the other hand, some nonlinear equations are present due to saturation effect. A set of nonlinear algebraic equation should be solved by numerical method. Therefore, the Newton-Raphson technique is used for equation solving during of the considered time step.

Generally, the operating point of electrical machines is close to the saturation zone due to designing considerations. Moreover, some current and torque harmonics will be produced due to time and space harmonics combination, which cannot be studied when saturation modeling is neglected. Considering both space and time harmonics, a method is proposed for inter-turn short circuit fault detection based on the stator current signatures and the machine performance is analyzed in healthy and faulty cases. In order to obtain the integrated method, two sample machines (two and also four-pole machines) are modeled and finally the accuracy of the proposed method is verified through the experimental results.

The calculations have been done in this work is limited to CRIM considering. However, the presented modeling method can be used for another types of electrical machines by some minor modifications.

Obtaining of an integrated formula for the inter-turn short circuit fault detection which has been presented for first time is the more advantages of present work. Moreover, in order to saturation effect considering, a new method is presented for solving of nonlinear equations which is another novelty of paper.

This paper aims to develop a comprehensive model of a magnetic sensor array that will be operational for a multitude of electric components in continuous and nonintrusive condition monitoring (CM) or in readiness assessment (RA) applications.

A universal nonintrusive model of a flexible antenna array is introduced to monitor and identify failures in electric machine drives. An adjustable sensor is designed to serve as a RA for a vast range of electrical elements in a typical power system by capturing the low-frequency radiated magnetic fields.

The optimal placement of the most sensitive radiated fields from several components has been discovered in this case study, enabling the detection of healthy current flow throughout. Thereafter, the short-circuit investigation, representing faulty situations, is implemented and compared with healthy cases.

This sensing technique can be used for nonintrusive CM of components that are out of reach and cannot have the sensor to be held around it such as components in offshore winds, wind energy generation and power and chemical plants.

The results are provided for three commonly used machines with a single sensor array with numerous settings. The three dimensional (3 D) finite element analysis is applied in the structuring of the sensor, detection of the optimum location and recognition of faults in the machines. Finally, based on the setup design, 3 D printing is used for the construction of the sensor array. Thus, the sensor array with fault detection avoids major component failures and increases system reliability/resiliency.

When implemented effectively and systematically across a curriculum, high impact practices (HIP) have the potential to increase student engagement and result in higher student achievement. The United States Air Force Academy (USAFA) is a four-year military university with a large liberal education core curriculum that provides the foundation for service and officership in the United States Air or Space Forces. Building on the liberal education core, the civil engineering (CE) major’s courses begin with the cornerstone field engineering course, paired with a two-week co-curricular experience for students at an Air or Space Force installation. With its motto “construct first, design later,” the field engineering course is an HIP and quintessential experiential learning course that gives students a practical frame-of-reference for future analysis and design courses. The CE major culminates with another HIP, the capstone design course, which gives students the opportunity to demonstrate their skills, building confidence in their ability to successfully apply those skills to the increasingly complex problems they will face after graduation. This book chapter provides a case study of the CE major at the USAFA, documenting the HIPs across the majors’ program, and highlighting the key elements and benefits of each.