Search Results (128)

A particularly important activity carried out by railway infrastructure managers to maintain railway devices in full working order is the diagnostic process. It increases the level of railway safety. The diagnostic process involves collecting information about the equipment through inspections, tests, functional trials, parameter measurements, and analysis of the working environment, followed by comparing the obtained information with the required parameters or permissible conditions. This activity also enables the formulation of a technical diagnosis regarding the current ability of the devices to perform its intended functions, taking into account the impact of its technical condition on railway traffic safety. This is especially important in the case of railway traffic control devices, as these devices are largely responsible for ensuring railway traffic safety. The collection of data on the condition of railway traffic control devices in the form of Big Data sets and diagnostic inference is an effective factor in making operational decisions for such devices. It enables the acquisition of complete information about the actual course of the exploitation process and allows for obtaining reliable information necessary to manage this process, particularly in the areas of diagnostics forecasting of devices conditions, renewal, and organization of maintenance and repair facilities. To support this, a service data acquisition and analysis system for railway traffic control devices (SADEK) was developed. This system can serve as a software platform for maintenance needs in the railway sector. Full article

RC piers in mountainous coastal or saline areas face the dual threats of rockfall impacts and chloride-induced steel corrosion, but their combined effects on dynamic response and residual bearing capacity remain unquantified. This study aims to investigate these combined effects over a 90-year service time and propose a damage assessment formula. A validated numerical model (relative error ≤14.7%) of corroded RC columns under impact is developed using ABAQUS, based on which the dynamic response and residual bearing capacity of an actual RC pier subjected to rockfall impacts during the service time of 90 years incorporating corrosion initiation (via Life-365 software 2.2) and propagation are analyzed, with the consideration of various impact energies (1–5 t mass, 5–15 m/s velocity). Results show that (1) increasing impact mass/velocity expands damage and increases displacement (e.g., the velocity of increases peak displacement by 33.41 mm in comparison to 5 m/s); (2) a 90-year service time leads to >50% severe surface damage and 47.1% residual capacity loss; and (3) the proposed and validated damage formula assessment formula for the residual bearing capacity enables lifecycle maintenance guidance. This work provides a validated framework for assessing combined corrosion-rockfall effects, aiding design and maintenance of structures. Full article

To investigate how severe wear at No. 12 turnout frogs in an urban rail transit line operating at speeds over 120 km/h on the dynamic performance of the vehicle, a vehicle–frog coupled dynamic model was established by employing the 2021 version of SIMPACK software. Profiles of No. 12 alloy steel frogs and metro wheel rims were measured to simulate wheel–rail interactions as the vehicle traverses the turnout, using both brand-new and worn frog conditions. The experimental results indicate that increased service life deepens frog wear, raises equivalent conicity, and intensifies wheel–rail forces. When a vehicle passes through the frog serviced for over 17 months at the speed of 120 km/h, the maximum derailment coefficient, lateral acceleration of the car body, and lateral and vertical wheel–rail forces increased by 0.14, 0.17 m/s², 9.52 kN, and 105.76 kN, respectively. The maximum contact patch area grew by 35.73%, while peak contact pressure rose by 236 MPa. To prevent dynamic indicators from exceeding safety thresholds and ensure train operational safety, it is recommended that the frog maintenance cycle be limited to 12 to 16 months. Full article

Earthen flood protection structures are planned and constructed with an expected service life of several decades while being exposed to environmental impacts that may lead to structural or hydraulic failure. Current maintenance procedures involve only repairing external damage, leaving internal processes contributing to structural damage often undetected. Through structural health monitoring (SHM), structural deficits can be detected before visible damage occurs. To improve maintenance workflows and support predictive maintenance of dikes, this paper reports on the integration of digital twin concepts with SHM strategies, referred to as “digital-twin-based SHM”. A digital twin concept, including a standard-compliant building information model, is proposed and implemented in terms of a digital twin environment. For integrating monitoring and sensor data into the digital twin environment, a customized webform is designed. A communication protocol links preprocessed sensor data stored on a server with the digital twin environment, enabling model-based visualization and contextualization of the sensor data. As will be shown in this paper, a digital twin environment is set up and managed in the context of SHM in compliance with technical standards and using well-established software tools. In conclusion, digital-twin-based SHM, as proposed in this paper, has proven to advance predictive maintenance of dikes, contributing to the resilience of critical infrastructure against environmental impacts. Full article

Enhancing the seismic resilience of urban water distribution networks (WDNs) requires the improvement of both earthquake resistance and rapid recovery capabilities within the system. This paper proposes a multi-objective method to enhance the seismic resilience of the WDNs, focusing on system restoration capabilities while comprehensively considering the hydraulic recovery index, maintenance time, and maintenance cost. The method utilizes a random simulation approach to generate various damage scenarios for the WDN, considering pipe leakage, pipe bursts, and variations in node flow resulting from changes in water pressure. It characterizes the functions of the WDN through hydraulic service satisfaction and quantifies system resilience using a performance response function. Additionally, it determines the optimal dispatch strategy for emergency repair teams and the optimal emergency repair sequence for earthquake-damaged networks using a genetic algorithm. Furthermore, a comprehensive computational platform has been developed to systematically analyze and optimize seismic resilience strategies for WDNs. The feasibility of the proposed method is demonstrated through an example involving the WDN in Xi’an City. The results indicate that the single-objective seismic resilience improvement method based on the hydraulic recovery index is the most effective for enhancing the seismic resilience of the WDN. In contrast, the multi-objective method proposed in this article reduces repair time by 17.9% and repair costs by 3.4%, while only resulting in a 0.2% decrease in the seismic resilience of the WDN. This method demonstrates the most favorable comprehensive restoration effect, and the success of our method in achieving a symmetrically balanced restoration outcome demonstrates its value. The proposed methodology and software can provide both theoretical frameworks and technical support for urban WDN administrators. Full article

This scientific research presents the most significant aspects of the structural analysis and verification of the main steel railway bridges in Peru in accordance with the American standard. To this end, linear and finite element analyses (FEMs) were performed using calculation notes in MATHCAD and structural validation software (SAP2000, CSI Bridge, IDEA STATICA and GE05), among others, based on on-site inspections, which allowed results to be obtained to analyze, evaluate and determine the structural performance factors (RF) of the main railway bridges in Peru. For this, data obtained from several railway corridors in Peru were taken into consideration, such as the lines of the Southern Railway Train, Central Andean Railway, Huancayo–Huancavelica Railway Train and the Tacna–Arica Train; in addition to the feasibility studies on the Interoceanic Train project: Iquitos–Yurimaguas; projects administered through Public–Private Partnership PPP as well as by the Regionals Government and MTC-Peru. These data were used in order to be able to warn of certain technical aspects that would influence the recommendations for a locomotive replacement project in which new units had different load distributions between the axles, which would make it necessary to review the tracks and bridges of the same in order to determine if they would be able to withstand the new forces safely, as well as to reinforce structural elements according to the material and the structural condition, and finally, to assess the variation in the increase in train speed in some road corridors to achieve a better FRA (Federal Railway Administration) classification of Class 3, where the presence of structures dating back to the last century has been verified as well (1851–1856–1908). Likewise, the seismic criteria and geotechnical conditions of the most representative areas of the country (acceleration 0.30 g) were included in order to also be able to make technical recommendations that would allow us to ensure the useful life of the structure in service, operation and maintenance conditions. Full article

Progressive advancements in the global economy and technology have propelled human civilization forward; however, they have also inflicted significant harm on the global ecological environment. In the present era, electric vehicle (EV) technology is playing a vital role due to its environmentally friendly technological advances. However, widespread adoption of EVs has been hindered by their limited travel range, inadequate charging infrastructure, and high costs. This can be closely observed when we assess the adoption of electric vehicles (EVs) among motorcycle taxi drivers, commonly called ‘pilots,’ in Goa, India. Motorcycle taxis are crucial in Goa’s transportation network, providing affordable, efficient, and door-to-door services, especially in regions with limited public transport options. However, the rising costs of petrol and vehicle maintenance have adversely affected the income of these pilots, prompting concerns about their willingness to adopt EVs. This study aims to analyze the factors prompting the behavioral intention to adopt EVs by motorcycle taxi pilots in Goa, India, focusing on six key determinants: charging infrastructure, effort expectancy, performance expectancy, price value, social influence, and satisfaction with incentive policies. A quantitative approach was employed, utilizing stratified proportionate random sampling techniques to collect data from 242 motorcycle taxi pilots registered with the Goa State Government Transport Department. It was analyzed using partial least squares-structural equation modeling (PLS-SEM) through Smart-PLS 4.0 software. The research highlights that performance expectancy and price value are the potential motivators for the adoption of electric vehicles. These findings suggest that pilots are more likely to embrace EVs when they perceive tangible benefits in performance and find the cost reasonable in relation to the value offered. The results offer actionable insights for policymakers, manufacturers, and other stakeholders. These insights can guide strategic decisions and policy frameworks aimed at fostering a sustainable and user-centric transportation ecosystem. Full article

In the operation process of modern industrial equipment, as the core transmission component, the operation state of the gearbox directly affects the overall performance and service life of the equipment. However, the current gear operation is still faced with problems such as poor monitoring, a single detection index, and low data utilization, which lead to incomplete evaluation results. In view of these challenges, this paper proposes a shape and property integrated gearbox monitoring system based on digital twin technology and artificial intelligence, which aims to realize real-time fault diagnosis, performance prediction, and the dynamic visualization of gear through virtual real mapping and data interaction, and lays the foundation for the follow-up predictive maintenance application. Taking the QPZZ-ii gearbox test bed as the physical entity, the research establishes a five-layer architecture: functional service layer, software support layer, model integration layer, data-driven layer, and digital twin layer, forming a closed-loop feedback mechanism. In terms of technical implementation, combined with HyperMesh 2023 refinement mesh generation, ABAQUS 2023 simulates the stress distribution of gear under thermal fluid solid coupling conditions, the Gaussian process regression (GPR) stress prediction model, and a fault diagnosis algorithm based on wavelet transform and the depth residual shrinkage network (DRSN), and analyzes the vibration signal and stress distribution of gear under normal, broken tooth, wear and pitting fault types. The experimental verification shows that the fault diagnosis accuracy of the system is more than 99%, the average value of the determination coefficient (R²) of the stress prediction model is 0.9339 (driving wheel) and 0.9497 (driven wheel), and supports the real-time display of three-dimensional cloud images. The advantage of the research lies in the interaction and visualization of fusion of multi-source data, but it is limited to the accuracy of finite element simulation and the difficulty of obtaining actual stress data. This achievement provides a new method for intelligent monitoring of industrial equipment and effectively promotes the application of digital twin technology in the field of predictive maintenance. Full article

The adjustment of counterweights in bucket wheel stacker reclaimers is crucial for the equipment’s load-bearing capacity, vibration, and overall stability. To enhance operational reliability and safety while reducing failure rates and maintenance costs, this study employs finite element analysis (FEA) software and multibody dynamics (MBD) software to develop a rigid–flexible coupling model of the bucket wheel stacker reclaimer. By simulating the excavation forces generated by different materials, the dynamic response of the equipment during operation was analyzed. The results indicate that during the initial startup phase, significant fluctuations in the system’s parameters occur due to vibrations, but these stabilize after 40 s of damping. Comparative analysis of four excavation forces and various counterweight values during the reclaiming process identifies the optimal counterweight as 170 t. The study further reveals that under rotary working conditions, as the excavation force increases, the failure counterweight value increases by 8.3%. This research provides a theoretical basis for optimizing the adjustment of counterweights in bucket wheel stacker reclaimers, guiding operational practices under actual working conditions, ensuring efficient operation across different scenarios, and extending the equipment’s service life. Full article

The majority of freight trains are characterized by a braking system that does not guarantee synchronous braking between different wagons. This results in the generation of considerable in-train forces during emergency braking operations, which are sometimes imposed by the railway infrastructure due to certain running speeds being exceeded. The magnitude of in-train forces is contingent upon a number of factors, the most significant ones being the length, mass and load composition of the trainset, in addition to the specific braking imposed. The application of excessive compressive in-train forces has the potential to cause the wagon to derail, particularly if the wagon is lightweight and traversing a small radius curve. Similarly, excessive tensile in-train forces applied to the screw couplers can cause them to fail, typically through fatigue, resulting in train disruption and necessitating the recovery of both portions of the trainset. The objective of this study is to perform a preliminary analysis of the UIC (International Union of Railways) unified screw couplers fatigue phenomenon, employing load spectra computed by the UIC 1.4.6 software TrainDy. A possible future development is developing a maintenance model functional to predict the extent of damage in freight wagon screw couplers during their service life. Full article

Symmetry in IT system design is essential for improving efficiency, consistency, and manageability in data center operations. Symmetry guarantees that all system elements—be it hardware, software, or network configurations—are crafted to be consistent, thereby minimizing variability and streamlining operations. This principle is especially pertinent in cluster computing, where uniform server configurations facilitate efficient maintenance and consistent system performance. Symmetric designs reduce variations among nodes, alleviating performance discrepancies and resource imbalances commonly encountered in heterogeneous environments. This paper examines the advantages of symmetric configurations via an experimental analysis of the lifecycle management process. The findings indicate that clusters constructed with a symmetric server architecture enhance operational efficiency. From a lifecycle management standpoint, symmetry streamlines hardware provisioning and maintenance, diminishing complexities related to Day-1 and Day-2 operations. Furthermore, by guaranteeing consistent performance across all servers, symmetric designs facilitate a more predictable quality of service (QoS), reducing bottlenecks and improving overall system stability. Experimental results indicate that, when properly configured, symmetric clusters surpass asymmetric configurations in sustaining QoS, especially during peak loads or hardware failures, owing to their enhanced resource allocation and failover mechanisms. This research highlights the significance of symmetry as a fundamental principle in cluster-based data center architecture. Full article

With the wide application of a new generation of information technology, remote technical services are receiving an increasing amount of attention in the manufacturing field. In view of the fact that most mechanical and electrical equipment manufacturing enterprises still need to send a substantial number of employees to the site to provide operation and maintenance services for customers, and the operation and maintenance costs of enterprises remain high, a remote operation and maintenance method of mechanical and electrical equipment based on digital twin technology is proposed. A digital twin remote operation and maintenance services model is constructed, and digital twin remote operation and maintenance technology is divided into four basic levels: virtual simulation, software/hardware-in-the-loop virtual commissioning, virtual and real synchronization, and cloud–end interconnection. With this, we conduct in-depth research on the key technologies involved in these four levels. The digital twin remote operation and maintenance service platform has been built; this platform can provide maintenance, repair, overhaul, and operation services for enterprise equipment. The feasibility of both the digital twin remote operation and maintenance services model and the digital twin remote operation and maintenance service platform was verified through cases, which provided an efficient and feasible solution for enterprises to improve service efficiency and reduce labor costs. Full article

The impact of temperature on bridges represents one of the main long-term challenges of structural health monitoring (SHM). Temperature is an environmental variable that changes both throughout the day and between different seasons, and its variations can induce thermal loads on bridges, potentially resulting in considerable displacements and deformations. Therefore, it is essential to obtain current data on the impact of daily and seasonal temperature variations on bridge displacements. Unfortunately, the maintenance costs associated with using precise estimates of thermal loads in a bridge design are quite high. The introduction of more accessible structural monitoring services is imperative to increase the number of observed structures. Viable solutions to make SHM more efficient include minimizing the costs of equipment, sensors, data loggers, data transmission systems, or monitoring data processing software. This research aims to improve the time intervals for collecting data on external temperature variations measured on a bridge structure through a sensor-based detection system and the integration of results into a regression analysis model. The paper aims to determine the appropriate interval for capturing and transmitting the structural response influenced by temperature variations over a year and to develop a behavioral mathematical model for the concrete structural components of a monitored bridge. The structural behavior was modeled using the statistical software TableCurve 2D, v.5.01. The results indicate that extending the data collection periods from 15 min to 4 h, in a static regime, maintains the accuracy of the regression model; instead, the effects of this integration are a significant reduction in the costs of data collection, transmission, and processing. The practical implications of this study consist of improving the monitoring of the structural behavior of bridges and the prediction under thermal stress, aiding in the design of more resilient structures, and enabling the implementation of efficient maintenance strategies. Full article

Maintenance and service are important tasks for any industrial enterprise. This article presents a methodology for technical maintenance that employs a smart glove equipped with tactile sensors, an electronic unit responsible for processing and transmitting information, and a unit designed to interpret the results. Tactile sensors are graphene-based. The main idea of the method is to use sensors to record the strength of contact between the operator’s fingertips and the equipment. Afterwards, these values are recorded, transferred to processing, and the output signal from the sensors is compared with the steps of various repair works. The work contains methods for creating each component of the glove, their effectiveness is evaluated, and experiments are described to assess the feasibility of using the developed device for the maintenance and repair of equipment. The device discussed in this work is a wearable device. The obtained results demonstrate the applicability of the smart glove for equipment maintenance and repair. Full article

Microservices have gained widespread adoption in enterprise software systems because they encapsulate the expertise of specific organizational subunits. This approach offers valuable insights into internal processes and communication channels. The advantage of microservices lies in their self-contained nature, streamlining management and deployment. However, this decentralized approach scatters knowledge across microservices, making it challenging to grasp the holistic system. As these systems continually evolve, substantial changes may affect not only individual microservices but the entire system. This dynamic environment increases the complexity of system maintenance, emphasizing the need for centralized assessment methods to analyze these changes. This paper derives and introduces quantification metrics to serve as indicators for investigating system architecture evolution across different system versions. It focuses on two holistic viewpoints of inter-service interaction and data perspectives derived through static analysis of the system’s source code. The approach is demonstrated with a case study using established microservice system benchmarks. Full article