Maintenance, Reliability and Condition Monitoring
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Influence of wheelset structural flexibility on dynamic properties of a wide-gauge six-axle heavy-haul locomotive
Get PDFWheelset structural flexibility, that is the elastic deformation of the wheelset as a structure, has an important influence on the dynamic properties of railway locomotive vehicles at medium and high frequencies. Based on the practical structural parameters, this paper proposes a multi-degree of freedom rigid-flexible coupling dynamic model of a wide-gauge freight electric locomotive with C0-C0 bogies with an axle suspension driving system. The wheelset with the interference-fit large gear is made flexible using the finite element method, and then the rigid-flexible coupling vehicle model with elastic wheelsets is established in the software SIMPACK 2020. A short-wave irregularity superposed on the American fifth-grade track irregularity is used as the track excitation to study the performance at higher frequencies. From the modal analysis of the vehicle, it is obtained that the lowest frequency at which the elastic deformation of the wheelset occurs is 24.631 Hz. The lateral vibration responses of the vehicle with elastic wheelsets are reduced mainly in the frequency range of 30-150 Hz. There are two resonances in the lateral vibration responses at the mode frequencies of the vehicle over 50 Hz, which are close to the wheelset’s first mode frequency. Taking the ГОСТ standard of wide-gauge countries as the main reference, simulations are separately taken in straight-line and curved-line cases. Results show that the wheelset structural flexibility mainly influences the vehicle lateral stability and safety
Research on lightweight pedestrian detection based on improved YOLOv5
Get PDFAiming at the problems of low detection accuracy and the large size of the pedestrian detection algorithm, to improve the edge intelligent recognition capability of the terminal, this paper proposes a lightweight pedestrian detection scheme based on the improved YOLOv5. In this paper, the algorithm first takes the original YOLOv5 as the basic framework and uses the Ghost Bottleneck module to replace the C3 module in the original YOLOv5 network to reduce the number of parameters, eliminate redundant features, and obtain a more lightweight model. Then the attention mechanism CBAM module is added to improve the feature extraction capability and detection accuracy of the algorithm. After experimental verification, the improved lightweight YOLOv5 algorithm significantly reduces the model size and computational cost while guaranteeing accuracy, which is suitable for deployment in edge devices
Joint effects of thermal diffusion and diffusion thermo on MHD three dimensional nanofluid flow towards a stretching sheet
Get PDFThis communication reports the joint effects of Thermal Diffusion and Diffusion Thermo on viscous and incompressible three-dimensional nanofluid flow towards a stretching sheet in connection to the influence of a magnetic field. In this study, nanofluid model is employed for the effects of thermophoresis and Brownian motion. Following that, similarity variables are chosen to turn the dimensional nonlinear system into dimensionless expressions and the resultant transformed equations are solved numerically using Finite Element method. Special emphasis has been given to the parameters of physical interest. These findings are visually presented through graphical representations, providing a clear and insightful understanding involved in this flow scenario. In addition, the final results are examined in light of past research and it is determined that they meet the convergence standards to an exceedingly satisfactory degree. The study’s findings are beneficial for many technical and commercial endeavours
A third-order shear deformation plate bending formulation for thick plates: first principles derivation and applications
Get PDFA third-order shear deformation plate bending formulation is presented in this study from the first principles. The derivation assumed a displacement field constructed using third-order polynomial function of the transverse (z) coordinate; and made to apriori satisfy the linear three-dimensional (3D) kinematics relations as well as the transverse shear stress free boundary conditions at the top and bottom plate surfaces. The formulation thus has no need for shear stress correction factors of the first-order shear deformation plate theories. The domain equations of equilibrium are obtained as a set of three coupled differential equations in terms of three unknown displacements. The system of coupled equations is solved for simply supported rectangular and square plates subjected to four cases of loading distributions: sinusoidal loading, uniformly distributed loading, linearly distributed loading and point load at the plate center. Navier’s double trigonometric series method is used to construct trial solutions for the three displacement functions such that the boundary conditions are satisfied identically. The integration problem is thus reduced to an algebraic problem and is solved for each considered loading. It is found that the present formulation gives exact results for the normal stresses σxx for sinusoidal and uniformly distributed loads. The study further showed that the results for deflection and stresses agreed with Krishna Murty’s higher order shear deformation plate theory results. The present formulation gave accurate results because of the inclusion of transverse normal strain effects in the formulation. The formulation gives a quadratic variation of the transverse shear stresses across the thickness in consonance with the theory of elasticity method
Genetic algorithm-based error correction algorithm for CNC turning machining of mechanical parts
Get PDFThis paper discusses how to improve the machining precision in the turning of slender shaft. The main cause of dimensional error in slender shaft machining is analyzed by establishing dimensional error model and using genetic algorithm to optimize cutting parameter selection. Based on this, the proportional-integral-differential control error compensation is proposed to reduce the error in the turning process of slender shaft. Through the simulation experiment, the machining size error of slender shaft under different cutting parameters is obtained. It is found that the increase of back blowing and feed rate will aggravate the dimensional error, while the increase of CS will reduce the dimensional error. The error after the proportional-integral-differential control error compensation is much smaller than that without the error compensation. The experimental results show that the method is reliable in reducing the errors in the turning of slender shaft, and can realize the machining mode with higher precision and efficiency. This is of great significance to the development of machinery manufacturing industry
Cross domain fault diagnosis method based on MLP-mixer network
Get PDFThe quality of rolling bearings determines the safety of mechanical equipment operation, and bearings with more precise structures are prone to damage due to excessive operation. Therefore, cross domain fault diagnosis of bearings has become a research hotspot. To better improve the accuracy of bearing cross domain fault diagnosis, this study proposes two models. One is a cross domain feature extraction model constructed using a mixed attention mechanism, which recognizes and extracts high-level features of bearing faults through channel attention and spatial attention mechanisms. The other is a bearing cross domain fault diagnosis model based on multi-layer perception mechanism. This model takes the feature signals collected by the attention mechanism model as input to identify and align the differences between the source and target domain features, facilitating cross domain transfer of features. The experimental results show that the mixed attention mechanism model has a maximum accuracy of 97.3 % for feature recognition of different faults, and can successfully recognize corresponding signal values. The multi-layer perception model can achieve the highest recognition accuracy of 99.5 % in bearing fault diagnosis, and it can reach a stable state when it iterates to 26, and the final stable loss value is 0.28. Therefore, the two models proposed in this study have good application value
Development of a method for online control of plastic deformations of a tank wall and assessment of its residual life
Get PDFA method of operational control of the residual resource of the tank is proposed. As a tool, the measurement of deformations of the tank wall, the assessment of plastic deformations are used. To determine the deformation, it is proposed to use a light guide installed on the wall, with the help of which the change in the curvature of the wall is measured. A device prototype containing a light guide and the necessary electronics has been developed, and the dependence of the device readings on the curvature of the light guide has been experimentally determined. The simulation of the tank in the computer simulation program was carried out in order to compare the integral of the relative deformation over the height of the tank with the readings of the device. An algorithm for processing measurements of device readings and estimating the residual life of the tank is proposed
Sustainability assessment of CO2 valorisation routes for Latvia: LCA, S-LCA and LCCA
Get PDFTo initiate and maintain the European Green Deal transformative policies, an evident-based multi-sectoral forecasting model needs to be timely and effectively deployed. The overall decarbonisation solutions proposed in this research can be defined as regional CO2 “value spots”– areas in regions where CO2 can be directly (CO2-based new products) or virtually (change in planning and implementation) utilised for the development of high-added value products, ensuring decarbonisation of rural areas, as well as promoting economic growth of the regions. Within the framework of this work, three scenarios for using carbon dioxide are analysed – its use in methanol production, cement production and open-air algae ponds. The analysis aims to assess the potential environmental impacts of CO2 utilisation and consider the impact on the environment, human health, labour rights, working conditions, social equity, and other social factors, as well as costs and economic sustainability. LCA provides a decision-making platform to understand the mid-term and long-term environmental effects of CO2 valorisation scenarios according to the ISO Standard 14044 standard requirements. Sensitivity analysis is performed to exclude high input data uncertainties (if any) and identify model behaviour factors. Effects of CO2 valorisation scenarios on social endpoints (well-being of stakeholders) are identified via S-LCA based on multi-regional input/output methods of qualitative and quantitative generic data. The S-LCA include health and safety, cultural heritage, and governance impact categories covering the interests of such stakeholder groups as workers, the local community, society, and consumers. Cost-effectiveness of CO2 valorisation scenarios is performed. Regional valorisation scenarios are assessed and benchmarked via regional development sustainability indicators. A comparative assessment of core indicators is performed
The CCS greensand project: CO2 pilot injection and monitoring
Get PDFCarbon capture and storage (CCS) is a proven, safe, reliable and affordable technology. CCS entails the capture of CO2 (e.g. from power plants or industrial facilities) as well as its long-term storage in subsurface geological structures, such as depleted gas and oil reservoirs or deep-lying rock strata known as saline aquifers. This technology enables the reliable and cost-effective decarbonisation of industrial sectors with CO2 emissions that are difficult or impossible to avoid. The International Energy Agency (IEA) and other leading organisations believe that CCS will play a key role in climate protection efforts and emphasising that ambitious climate targets cannot be achieved without CCS. In February 2023 INEOS Energy Denmark (Op.), Wintershall Dea and Nordseafonden (Danish State Participation) have been awarded the first Carbon Storage Exploration License (Iris) that covers the Siri oil fairway, a depleting oil production infrastructure hub, offshore Denmark. As part of the License work program it is planned to submit a Storage License Application by February 2024 to commission the first CO2 permanent storage facility in Denmark by 2025. Initial research studies to convert the depleted oil field Nini West, one of many oil segments in the Siri Fairway, into a permanent CO2 storage site started already in 2020 and is called Project Greensand Phase 1 and Phase 2, co-funded by the Danish Energy Development and Demonstration Programme (EUDP). Project Greensand Phase 2 is a large and comprehensive research and pilot project, consisting of 13 work packages and 120 individual tasks that are worked through by a consortium of 23 research partners, led by INEOS Energy Denmark, with altogether some hundreds of researchers and contributors involved. The project scopes are aiming to de-risk and specify all aspects related to carbon storage in the Nini West segment and to provide key documents ready for submission to the Danish mining authorities. Wintershall Dea is key partner in the research consortium, contributing to all work packages and is leading the monitoring related research scopes. The Greensand project has cleared a first major hurdle in fall 2020 with the independent 3rd Party certification of the Nini West reservoir as a feasible CO2 storage. This certification confirms that the reservoir is conceptually suitable for injecting 0.45 million tonnes CO2 per year per well for a period up to 10-years and that it can safely contain the CO2 injected. In August 2021, the consortium moved ahead to the pilot phase. The pilot's first offshore injection was successfully conducted in winter 2022/2023 by injecting 4.000 tons of CO2 into the depleted Nini West oil field and demonstrating the full value chain across international borders. This operation lasted 90 days and included 7 shipments of CO2 to the Nini site. The CO2 was captured and liquified in a chemical plant in Antwerp and loaded into 40 ISO-tanks that were mounted and piped together to an installed rack on a conventional coastal carrier. This low cost custom made transport concept successfully demonstrated temporary carrier solutions for CO2 shipments until dedicated low-emission CO2 cargo ships have been designed and constructed. The pilot injection was accompanied by a focused seismic monitoring program. Despite unfavorable weather conditions one baseline and two monitor seismic acquisitions have been successfully completed as part of Project Greensand to monitor the CO2 plume migration more frequently and with less impact on the environment [1, 2, 3]. The seismic data has been retrieved, processed and analyzed. Based on the results it is possible to detect the CO2 presence inside the reservoir [4, 5]. Prior to injection a dynamic simulation provided results on the expected areal coverage of the CO2 plume. A pattern of 7 spots was planned to detect the presence of the CO2 with our novel focused seismic concept. Some locations were expected to show an effect caused by the CO2 plume, some spots should confirm the absence of CO2. After processing of the monitoring spot gathers and evaluation of the difference traces, a qualitative result was provided for the individual spots. All spots were targeted more than once by different source and receiver locations to get a confirmation from measurements at different offsets and/or azimuths. A strong positive response can be seen directly at the injection location, a medium amplitude response for an up-dip spot towards north-east. All other spots do not show presence of CO2 in their spot seismic monitoring results as predicted by dynamic simulation. This spot seismic method has the potential to replace 4D seismic for CO2 plume monitoring and verification during the full field injection and post injection phases and could thus significantly reduce cost and environmental impact. Further, the partners in the Greensand research consortium of monitoring scopes are developing sea floor sensors [6] that are able to detect and record CO2 leakage and seismicity. These sensors will be connected to a power and data hub offshore to ensure data communication in real time. For INEOS Energy and Wintershall Dea, Greensand is a pioneering CCS project as it ranks among the most advanced CCS projects in EU. Beyond the Nini West storage complex, work is ongoing to mature the remaining depleted oil field and aquifer potential in the Siri Fairway with the view to expand the capacity to up to 8 MTA until 2030. The entire CCS value chain (capture, transport, and storage) will be implemented across borders
Fault diagnosis method for hydro-power plants with Bi-LSTM knowledge graph aided by attention scheme
Get PDFIn hydro-power systems, the fault of equipment is an important potential threat for the safe production of electricity. Therefore, the automation and intelligence of fault diagnosis becomes the popular issue in the research on hydro-power system. In this paper, a knowledge graph-based method is put forth to diagnose faults occurred in hydro-power systems, since the knowledge graph can store structured and unstructured data for better fault diagnosis and intelligently search the reasons of the faults. First, we model the knowledge graph for hydro-power plants, where the rational path for the fault reason is formulated. Then, the bi-directional long short-term memory (Bi-LSTM) with conditional random field (CRF) is used to extract the entities and relations to the given documents, which record the phenomenon and reasons for the occurred faults. Moreover, the attention scheme is employed in the Bi-LSTM to weigh the closer relationships to improve the diagnosis accuracy. An automatic diagnosis algorithm is developed to improve the diagnosing efficiency by constructing rational paths, with which directive and in-directive factors for occurring faults can be traced. Simulation results reveal that the intelligent search method with a knowledge graph can effectively find the reason, locate the position, and provide useful suggestions for the occurred faults