Search Results (300)

Rolling bearings are prone to failure, meaning that research on intelligent fault diagnosis is crucial in relation to this key transmission component in rotating machinery. The application of deep learning (DL) has significantly advanced the development of intelligent fault diagnosis. This paper proposes a novel method for rolling bearing fault diagnosis based on the fractional constant Q non-stationary Gabor transform (FCO-NSGT) and VMamba-Conv. Firstly, a rolling bearing fault experimental platform is established and the vibration signals of rolling bearings under various working conditions are collected using an acceleration sensor. Secondly, a kurtosis-to-entropy ratio (KER) method and the rotational kernel function of the fractional Fourier transform (FRFT) are proposed and applied to the original CO-NSGT to overcome the limitations of the original CO-NSGT, such as the unsatisfactory time–frequency representation due to manual parameter setting and the energy dispersion problem of frequency-modulated signals that vary with time. A lightweight fault diagnosis model, VMamba-Conv, is proposed, which is a restructured version of VMamba. It integrates an efficient selective scanning mechanism, a state space model, and a convolutional network based on SimAX into a dual-branch architecture and uses inverted residual blocks to achieve a lightweight design while maintaining strong feature extraction capabilities. Finally, the time–frequency graph is inputted into VMamba-Conv to diagnose rolling bearing faults. This approach reduces the number of parameters, as well as the computational complexity, while ensuring high accuracy and excellent noise resistance. The results show that the proposed method has excellent fault diagnosis capabilities, with an average accuracy of 99.81%. By comparing the Adjusted Rand Index, Normalized Mutual Information, F1 Score, and accuracy, it is concluded that the proposed method outperforms other comparison methods, demonstrating its effectiveness and superiority. Full article

Inter-turn short-circuit faults in induction motors might lead to overheating, torque imbalances, and eventual motor failure. This paper presents a fault detection framework for accurately identifying ITSC faults under various operating conditions. The proposed method integrates negative-sequence current analysis utilizing wavelet-based filtering and symmetrical component decomposition. A fault detection index to effectively monitor motor health and detect faults is presented. Moreover, the fault location is determined by phase angles of fundamental components of negative-sequence currents. Experimental validations were carried out for an inverter-fed induction motor under variable speed and load cases. These showed that the proposed approach has high sensitivity to early-stage inter-turn short circuits. This makes the framework highly suitable for real-time condition monitoring and predictive maintenance in inverter-fed motor systems, thereby improving system reliability and minimizing unplanned downtime. Full article

Electric motors play a decisive role in electric vehicles by converting electrical energy into mechanical motion across various drivetrain components. However, failures in these motors can interrupt the motor function, with approximately 40% of these failures stemming from bearing issues. Key contributors to bearing degradation include shaft voltage, bearing current, and electric discharge material spalling current, especially in motors powered by inverters or variable frequency drives. This review explores the tribological and vibrational aspects of bearing currents, analyzing their mechanisms and influence on electric motor performance. It addresses the challenges faced by electric vehicles, such as high-speed operation, elevated temperatures, electrical conductivity, and energy efficiency. This study investigates the origins of bearing currents, damage linked to shaft voltage and electric discharge material spalling current, and the effects of lubricant properties on bearing functionality. Moreover, it covers various methods for measuring shaft voltage and bearing current, as well as strategies to alleviate the adverse impacts of bearing currents. This comprehensive analysis aims to shed light on the detrimental effects of bearing currents on the performance and lifespan of electric motors in electric vehicles, emphasizing the importance of tribological considerations for reliable operation and durability. The aim of this study is to address the engineering problem of bearing failure in inverter-fed EV motors by integrating electrical, tribological, and lubrication perspectives. The novelty lies in proposing a conceptual link between lubricant breakdown and damage morphology to guide mitigation strategies. The study tasks include literature review, analysis of bearing current mechanisms and diagnostics, and identification of technological trends. The findings provide insights into lubricant properties and diagnostic approaches that can support industrial solutions. Full article

Hydrogen is a potential key component of a carbon-neutral energy carrier and an input to marine industrial processes. This study examines the consequences of coupled hydrogen release and marine environmental factors during floating photovoltaic hydrogen production (FPHP) system failures. A validated three-dimensional numerical model of FPHP comprehensively characterizes hydrogen leakage dynamics under varied rupture diameters (25, 50, 100 mm), transient release duration, dispersion patterns, and wind intensity effects (0–20 m/s sea-level velocities) on hydrogen–air vapor clouds. FLACS-generated data establish the concentration–dispersion distance relationship, with numerical validation confirming predictive accuracy for hydrogen storage tank failures. The results indicate that the wind velocity and rupture size significantly influence the explosion risk; 100 mm ruptures elevate the explosion risk, producing vapor clouds that are 40–65% larger than 25 mm and 50 mm cases. Meanwhile, increased wind velocities (>10 m/s) accelerate hydrogen dilution, reducing the high-concentration cloud volume by 70–84%. Hydrogen jet orientation governs the spatial overpressure distribution in unconfined spaces, leading to considerable shockwave consequence variability. Photovoltaic modules and inverters of FPHP demonstrate maximum vulnerability to overpressure effects; these key findings can be used in the design of offshore platform safety. This study reveals fundamental accident characteristics for FPHP reliability assessment and provides critical insights for safety reinforcement strategies in maritime hydrogen applications. Full article

A novel unified progressive hybrid censoring is introduced to combine both progressive and hybrid censoring plans to allow flexible test termination either after a prespecified number of failures or at a fixed time. This work develops both frequentist and Bayesian inferential procedures for estimating the parameters, reliability, and hazard rates of the inverted Nadarajah–Haghighi lifespan model when a sample is produced from such a censoring plan. Maximum likelihood estimators are obtained through the Newton–Raphson iterative technique. The delta method, based on the Fisher information matrix, is utilized to build the asymptotic confidence intervals for each unknown quantity. In the Bayesian methodology, Markov chain Monte Carlo techniques with independent gamma priors are implemented to generate posterior summaries and credible intervals, addressing computational intractability through the Metropolis—Hastings algorithm. Extensive Monte Carlo simulations compare the efficiency and utility of frequentist and Bayesian estimates across multiple censoring designs, highlighting the superiority of Bayesian inference using informative prior information. Two real-world applications utilizing rare minerals from gold and diamond durability studies are examined to demonstrate the adaptability of the proposed estimators to the analysis of rare events in precious materials science. By applying four different optimality criteria to multiple competing plans, an analysis of various progressive censoring strategies that yield the best performance is conducted. The proposed censoring framework is effectively applied to real-world datasets involving diamonds and gold, demonstrating its practical utility in modeling the reliability and failure behavior of rare and high-value minerals. Full article

The continuous, effective operation of grid-connected photovoltaic (GCPV) systems depends on dependable inverter failure detection. Early, precise fault diagnosis improves general system dependability, lowers maintenance costs, and saves downtime. Although computing efficiency remains a difficulty, particularly in resource-limited contexts, machine learning-based fault detection presents interesting prospects in accuracy and responsiveness. By streamlining data complexity and allowing faster and more effective fault diagnosis, dimensionality reduction methods play vital role. Using dimensionality reduction and ML techniques, this work explores inverter fault detection in GCPV systems. Photovoltaic inverter operational data was normalized and preprocessed. In the next step, dimensionality reduction using Principal Component Analysis (PCA) and autoencoder-based feature extraction were explored. For ML training four classifiers which include Random Forest (RF), logistic regression (LR), decision tree (DT), and K-Nearest Neighbors (KNN) were used. Trained on the whole standardized dataset, the RF model routinely produced the greatest accuracy of 99.87%, so efficiently capturing complicated feature interactions but requiring large processing resources and time of 36.47sec. LR model showed reduction in accuracy, but very fast training time compared to other models. Further, PCA greatly lowered computing demands, especially improving inference speed for LR and KNN. High accuracy of 99.23% across all models was maintained by autoencoder-derived features. Full article

This paper provides a reliability analysis of selected components in the electrical power supply systems used for railway traffic control equipment. It includes rectifiers, controllers, inverters, generators, batteries, sensors, and switching elements. The study used failure data from power supply system elements on selected railway lines. The analysis was performed using a mathematical model based on Markov processes. Based on the findings, recommendations were made to improve safety levels. The results presented in the paper could serve as a valuable source of information for operators of power supply systems in railway traffic control, helping them optimize maintenance processes and increase equipment reliability. Full article

Cracks and seepage in dam structures pose a serious risk to their safety, yet traditional inspection methods often fall short when it comes to detecting shallow or early-stage fractures. This study proposes a new approach that uses spectral response analysis to quickly identify signs of seepage in concrete dams. Researchers developed a three-layer model—representing the concrete, a seepage zone, and water—to better understand how cracks affect the way electrical signals behave, thereby inverting the state of the dam based on how electrical signals behave in actual engineering measurements. Through computer simulations and lab experiments, the team explored how changes in the resistivity and thickness of the seepage layer, along with the resistivity of surrounding water, influence key indicators like impedance and signal angle. The results show that the “spectrum-based method” can effectively detect seepage in concrete cracks of dams, and the measurement method of the “spectral quadrupole method” based on the “spectrum-based method” is highly sensitive to these variations, making it a promising tool for spotting early seepage. Field tests backed up the lab findings, confirming that this method is significantly better than traditional techniques at detecting cracks less than a meter deep and identifying early signs of water intrusion. It could provide dam inspectors with a more reliable way to monitor structural health and prevent potential failures. Full article

Tracking the state of the health of electrical insulation in high-power electric machines has always been a topic of great interest due to the high cost of downtime associated with unexpected failures. Over the years, there have been continuous efforts to develop and improve upon methods for testing and categorizing the health and expected lifetime of stator insulation. Methods such as partial discharge, surge, and dissipation factor testing are common examples. With the increasing use of high-specific-power electric machines in new applications such as traction and wind power generation, coupled with the increasing use of wide-bandgap semiconductor device-based inverters, some traditional methods for insulation health tracking may need adjustments or be combined with newer methods to remain accurate and useful. This paper outlines a review of the traditional insulation health tracking methods and newer methods and improvements that have been proposed to address the concerns and shortcomings of traditional methods. Full article

Metallurgical equipment foundations exposed to prolonged 300–500 °C environments are subject to explosion risks, necessitating materials that are resistant to thermo-shock-coupled loads. This study investigated the real-time dynamic compressive behavior of high-performance concrete (HPC) reinforced with steel fibers (SFs), polypropylene fibers (PPFs), polyvinyl alcohol fibers (PVAFs), and their hybrid systems under thermo-shock coupling using real-time high-temperature (200–500 °C) SHPB tests. The results revealed temperature-dependent dynamic responses: SFs exhibited a V-shaped trend in compressive strength evolution (minimum at 400 °C), while PPFs/PVAFs showed inverted V-shaped trends (peaking at 300 °C). Hybrid systems demonstrated superior performance: SF-PVAF achieved stable dynamic strength at 200–400 °C (dynamic increase factor, DIF ≈ 1.65) due to synergistic toughening via SF bridging and PVAF melt-induced pore energy absorption. Microstructural analysis confirmed that organic fiber pores and SF crack-bridging collaboratively optimized failure modes, reducing brittle fracture. A temperature-adaptive design strategy is proposed: SF-PVAF hybrids are prioritized for temperatures of 200–400 °C, while SF-PPF combinations are recommended for 400–500 °C environments, providing critical guidance for explosion-resistant HPC in extreme thermal–industrial settings. Full article

During the manufacturing process of oil-immersed current transformers, metallic particles may become embedded in the insulation wrapping, and the resulting electric field distortion is one of the primary causes of failure. Historically, the shape of metallic particles has often been simplified to a standard sphere, whereas in practice, these particles are predominantly irregular. In this study, ellipsoidal and flaky particles were selected to represent smooth and angular surfaces, respectively. Using COMSOL Multiphysics^® (version 6.2) software, a three-dimensional simulation model of an oil-immersed inverted current transformer was developed, and the influence of defect position and size on electric field characteristics was analyzed. The results indicate that both types of defects cause electric field distortion, with longer particles exerting a greater influence on the electric field distribution. Under the voltage of a 220 kV system, elliptical particles (9 mm half shaft) lead to the maximum electric field intensity of main insulation of up to 45.1 × 10⁶ V/m, while the maximum field strength of flaky particles (length 30 mm) is 28.9 × 10⁶ V/m. Additionally, the closer the particles are to the inner side of the main insulation, the more significant their influence on the electric field distribution becomes. The findings provide a foundation for fault analysis and propagation studies related to the main insulation of current transformers. Full article

In order to examine the fracture development law of overlying strata in goafs and to reasonably lay out a high gas-drainage roadway under gob-side entry retaining with roadside filling, the 91–105 working face of the Wangzhuang Coal Mine was selected as the engineering case study. The failure laws and fracture development characteristics of the overlying strata in both the strike and dip directions using gob-side entry retaining and roadside filling were studied through rock mechanic tests and PFC numerical simulations. The optimal layout of the high gas-drainage roadway was determined through theoretical analysis and coupled Fluent–PFC numerical simulations, and on-site monitoring was conducted to evaluate the extraction effects. The results indicate that the first weighting interval of the 91–105 working face was 40 m, while the periodic weighting interval was approximately 14 m. The height of the falling zone was 14.4 m, and the height of the gas-conducting fracture zone was 40.7 m. In the dip direction, compared with coal pillar retaining, gob-side entry retaining with roadside filling formed an inverted trapezoid secondary breaking zone above the retaining roadway. Using this method, the span of the separation zone increased to 30 m, and the collapse angle decreased to 52°, resulting in a shift in the separation zone—the primary space for gas migration—toward the goaf. It was determined that the optimal location of the high gas-drainage roadway was 28 m above the coal roof and 30 m horizontally from the return air roadway. Compared with the 8105 working face, this position was 10 m closer toward the goaf. On-site gas extraction monitoring data indicate that, at this optimized position, the gas concentration in the high gas-drainage roadway increased by 22%, and the net gas flow increased by 18%. Full article

This paper proposes a flattened power electronic design approach to enhance both power density and thermal management performance. As essential components in electrified energy conversion, evaluations of power converters are strongly based on their power density. Achieving a compact design typically requires a well-optimized printed circuit board (PCB) layout, optimal component design and selection, and an efficient thermal management system. During high-power operation, significant power losses can lead to substantial heat generation. Without effective thermal mitigation, this heat buildup may result in excessive temperature rises or even system failure. To address this challenge, this paper developed a flattened power converter design methodology to increase the effective heat-dissipation area without expanding the total volume consumption. This proposed design improves thermal performance and, in turn, enhances overall power density. A three-phase inverter prototype is developed and tested to demonstrate the effectiveness of the proposed method. Full article

This paper analyzes the electromagnetic characteristics of an interior permanent magnet synchronous motor (IPMSM) for electric vehicle traction under various control imbalance conditions in a twin inverter system, assuming that one of the inverters fails to operate properly. The imbalance conditions are first investigated through dynamometer experiments and then applied to finite element method (FEM) simulations to evaluate their electromagnetic effects. Since the focus is on scenarios where a single inverter malfunctions, a stator winding configuration is first redefined to ensure stable operation in a single inverter system by preventing voltage and current imbalances within the circuit. When the stator winding is configured with eight parallel paths, the dynamometer test results show a phase voltage imbalance. However, when the number of parallel circuits is reduced to four, this voltage imbalance disappears. Using this configuration, a twin inverter system is constructed, and various imbalance conditions are applied to intuitively examine the electromagnetic characteristics when one inverter fails to accurately control current magnitude or phase angle. The simulation results showed that applying unbalanced conditions to the current and current phase angle led to a decrease in torque and an increase in torque ripple. In addition, when one of the inverters was completely disconnected, the motor performance analysis showed that it operated with approximately half of its original performance. Based on dynamometer experiments and finite element method (FEM) simulations, the electromagnetic characteristics under inverter fault conditions and appropriate stator winding configurations were analyzed. When an optimal number of parallel circuits is applied to the stator winding and a twin inverter system is employed, the load on each individual inverter is reduced, enabling accurate control. This makes the application to high-voltage and high-current systems feasible, allowing higher performance. Moreover, even if one inverter fails, the system can still operate at approximately half its capacity, ensuring high operational reliability. Full article

In order to improve the efficiency of highway tunnel construction and ensure the construction quality, the design concept of a prefabricated inverted arch and partial cast-in-place lining of highway tunnels by a mining method is put forward. During the assembly of prefabricated tunnel invert arches, the longitudinal joints between adjacent invert sections were subjected to shear forces due to the combined effects of the invert’s self-weight and construction equipment loads. This study investigated the shear performance of these longitudinal joints under construction loads, with a particular focus on the influence of bolt-tightening torque. Three longitudinal joint specimens were designed and fabricated, varying the bolt-tightening torque as a key parameter, and subjected to shear tests. The failure modes, load–slip behavior, and shear capacity of the joints were analyzed in relation to the tightening torque of high-strength bolts. The results indicate that when the bolt-tightening torque was set to 50% and 70% of the standard torque, the upper bolts of the joint sheared off, while the threads of the lower bolts were damaged. When the torque reached the standard value, all bolts were sheared off. The ultimate shear capacity of the longitudinal joints increased with higher bolt-tightening torque, with the optimal torque range identified as 70% to 85% of the specified standard. Ultimately, a method of calculation for evaluating the shear-bearing capacity of inverted arch longitudinal joints was proposed, with computational outcomes demonstrating a conservative bias that aligns with structural safety requirements. Full article