The damper (or amortisseur) winding of synchronous motors (SM) is a critical component required for starting the motor. Several cases of forced outage of industrial processes due to starting failure of salient pole SMs caused by damper bar failure have recently been reported. Detection of broken damper bars is difficult since they are active only during rotor acceleration, and off-line visual inspection is the only means of testing available in the field. It was recently shown that broken damper bars can be detected from the airgap flux, but this requires installation of airgap flux sensors inside the motor. In this paper, a method based on analysis of the stator starting current is proposed for detecting broken damper bars. In addition, an electrical detection method based on signal injection from the motor terminals is proposed. The new methods have been devised to provide remote testing from the motor control center without motor disassembly required in existing tests. Finite element (FE) analysis and experimental testing performed on 1 MW and 30 kW salient pole SMs with emulated broken damper bars show that the proposed methods can provide sensitive and reliable detection of damper bar failures.

Industrial manufacturing processes have evolved and improved since the disruption of the Industry 4.0 paradigm, while energy has progressively become a strategic resource required to maintain industrial competitiveness while maximizing quality and minimizing environmental impacts. In this context of global changes leading to social and economic impact in the short term and an unprecedented climate crisis, Digital Twins for Energy Efficiency in manufacturing processes provide companies with a tool to address this complex situation. Nevertheless, already existing Digital Twins applied for energy efficiency in a manufacturing process lack a flexible structure that easily replicates the real behavior of consuming machines while integrating it in complex upper-level environments. This paper presents a combined multi-paradigm approach to industrial process modeling developed and applied during the GENERTWIN project. The tool allows users to predict energy consumption and costs and, at the same time, evaluates the behavior of the process under certain productive changes to maximize consumption optimization, production efficiency and process flexibility.

The transition to decarbonized and distributed energy systems has increased interest in flexibility markets as a key tool to manage variability and coordinate distributed energy resources. However, the fast growth and conceptual fragmentation of this field hinder the building of coherent models and scalable solutions. This paper presents a scoping review of 243 peer-reviewed articles published between 2013 and 2025, applying the TEAM Framework and Business Model Canvas. Through a structured data matrix of 35 variables, we analyze how flexibility is defined and modelled, the coordination mechanisms applied, and how business dimensions are integrated. The results reveal major inconsistencies in terminology, actor roles, price formation, and interoperability modelling. We identify critical gaps in cost modelling and business model integration, especially in low-TRL studies. This review provides a comprehensive and cross-cutting synthesis of existing approaches, offering a reference framework for future research, policy design, and market implementation of distributed flexibility mechanisms.

This work presents several case studies related to condition monitoring of induction motors operating in a chemical plant. Analysis of the stator current is applied to diagnose several types of faults, especially rotor damages and mixed eccentricities. The considered current-based techniques include both the conventional method that relies on the analysis of the steady-state current (Motor Current Signature Analysis, MCSA, that will be employed as main tool), as well as recently developed methodologies based on the analysis of transient currents (Advanced Transient Current Signature Analysis, ATCSA, that will be used as complementary tool). The combination of both methods enables to reach a high reliability in the diagnostics, avoiding eventual false indications of a single method. The motors considered in the paper range from small-sized machines till large motors (rated up to several MW). Also, a diversity of operation conditions is considered, including diverse loading conditions as well as different operating options. The results show the powerfulness of current analysis for diagnosing a wide range of failures in asynchronous motors operating in petrochemical plants.

Sweep Frequency Response Analysis (SFRA) applied to rotating machine diagnosis and monitoring lacks of widespread industrial applicability up to this date. Several authors identify the rotor position influence as one of the main obstacles for an on-site and reliable diagnosis. This work provides a thorough investigation on how the rotor affects the broadband impedance for different rotor topologies. The rotor DC field is identified as a strong influence on the measured broadband impedance. First, a theoretical analysis is performed to study the effect of an external DC field in the broadband impedance. Then, a 4.7 kW PMSM is thoroughly analyzed including magnetostatic Finite Element Analysis (FEA) and experimental measurements. Finally, the influence of magnetic remanence on the broadband impedance is experimentally studied. To this aim, two induction machines with two different rotor types (i.e., wound-rotor and squirrel cage) are analyzed. This collection of results is aimed to clarify the physics behind the rotor position influence and to enhance the reliability of SFRA diagnosis for rotating machinery.