Journal of Mechatronics and Artificial Intelligence in Engineering
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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
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
Vibration influence of different types of heavy-duty trucks on road surface damage
Get PDFUnder the interaction of the wheels of heavy-duty trucks on the random road surface when the vehicles are travelling, their generated vibrations not only affect the driver's ride comfort but also impact the road surface damage. To assess the vibration influence of different types of vehicles on the road surface damage, three dynamic models of the two axle, three axle, and four axle of heavy trucks have been build and computed via the Matlab/Simulink software. The dynamic tire load, dynamic load coefficient, and dynamic load-stress factor are chosen to assess the friendly load of different heavy trucks under the different operating conditions of the vehicle. The obtained result indicates that the dynamics parameters including suspension system, tires, and axle load distributions of heavy trucks have a greater effect on the dynamic tire force than the total weight of the vehicle. In order to ensure the road’s safety, the traffic management should intervene quickly to give a velocity limit for vehicles under the condition of the vehicle moving with the empty loaded on the poor road surface
Research on road damage recognition and classification based on improved VGG-19
Get PDFIn recent years, methods of road damage detection, recognition and classification have achieved remarkable results, but there are still problems of efficient and accurate damage detection, recognition and classification. In order to solve this problem, this paper proposes a road damage VGG-19 model construction method that can be used for road damage detection. The road damage image is processed by digital image processing technology (DIP), and then combined with the improved VGG-19 network model to study the method of improving the recognition speed and accuracy of VGG-19 road damage model. Based on the performance evaluation index of neural network model, the feasibility of the improved VGG-19 method is verified. The results show that compared with the traditional VGG-19 model, the road damage VGG-19 road damage recognition model proposed in this paper shortens the training time by 79 % and the average test time by 68 %. In the performance evaluation of the neural network model, the comprehensive performance index is improved by 2.4 % compared with the traditional VGG-19 network model. The research is helpful to improve the model performance of VGG-19 road damage identification network model and its fit to road damages
Vibration characteristics and seismic performance of historical buildings with brick-wood structures
Get PDFTo explore the vibration characteristics and seismic performance of historical buildings in Tianjin, we conducted on-site vibration testing under ambient vibration on three historical buildings with brick-wood structures in Tianjin. Specifically, we delved into the vibration characteristics and seismic performance of historic buildings with brick-wood structures by establishing the vibration analysis model, performing the theoretical calculations, and conducting seismic performance analysis. The results reveal that 1) the vibration frequencies of historical buildings with brick-wood structures are low, mainly concentrated in 2.0-8.0 Hz, which conforms to the vibration range of general buildings; 2) based on vibration analysis, it is concluded that the structural integrity of these buildings is good and there are no obvious structural defects; 3) the layout and storey height of historical buildings have great impacts on the vibration characteristics and seismic performance. 4) the comprehensive seismic capacity index of three buildings ranges from 0.91 to 1.75. The results of dynamic analysis under ambient vibration are consistent with those of theoretical analysis, providing a basis for preserving and reinforcing historical buildings
A mathematical model and microcontroller-based method for measuring dielectric permittivity and discharge characteristics with Arduino ATmega 328: a case study in a physics laboratory
Get PDFA microcontroller-based measuring instrument and a new mathematical model are used to investigate capacitor permittivity and dielectric materials' charge-discharge characteristics. In this study, a prototype capacitive permittivity measurement apparatus for dielectric materials was carefully developed using an Arduino microcontroller, a resistor, and a capacitor. The experimental setup comprises a capacitor-resistor circuit, wherein a 5-volt power supply sourced from the microcontroller interfaces with a computer. During the charging process, a comprehensive evaluation of model-data alignment was performed, yielding values of 0.54252156, 0.9951, and 111.2508701 for the sum of squares error (SSE), the coefficient of determination (R-squared), and the sum of squares total (SST), respectively. Similarly, the analysis extended to the discharging process, unveiling values of 5.10174756, 0.962805684, and 137.1647082 for SSE, R-squared, and SST, respectively. These findings confirm the accuracy of the microcontroller that was programmed by incorporating a model in precisely measuring the relative permittivity of dielectric materials and capacitance values, with an R-squared value above 0.95 following capacitor literature benchmarks. The novelty of this study is that this configuration enabled the precise assessment of both permittivity and the charge-discharge characteristics of the dielectric materials within the capacitor. This methodology made it possible to accurately measure the permittivity and charge-discharge characteristics of dielectric materials within a capacitor. The scientific significance of this research lies in its ability to provide a carefully developed instrument capable of investigating the permittivity of dielectric materials and capacitor capacitance measurements. Scholars, international engineering communities, and academics can use this technological breakthrough to advance research into dielectric material properties and capacitor characteristics
Extraction and diagnosis of rolling bearing fault signals based on improved wavelet transform
Get PDFAs the continuous growth of the machinery industry, the importance of rolling bearings as key connecting parts in machinery movement is also increasing. However, the extraction and diagnosis of rolling bearing fault signals are difficult, and how to use modern transform analysis methods to raise the extraction efficiency and diagnostic accuracy becomes the focus. For this, a rolling bearing fault signal extraction and diagnosis model is designed based on empirical wavelet transform. The diagnostic model is optimized by using support vector machine and quantum genetic algorithm to design a rolling bearing fault signal extraction and diagnosis model based on improved empirical wavelet transform-support vector machine. The test results show that the research method can obtain four component signals showing different anomalies when generating time domain diagrams. Only five component peaks are generated and one group is extracted as output when generating component peaks. The abnormal amplitude of envelope spectrum basically reaches 0.40×10-6 or above. The judgment accuracy of component diagnosis reaches 98.12%. The above results show that the research method has better fault signal extraction ability and better diagnostic accuracy when performing fault signal diagnosis, which can provide new technical support for rolling bearing fault signal extraction and diagnosis
Trajectory planning and control algorithm of industrial robot manipulator
Get PDFAs the industrial robot task becomes more complex, the difficulty of trajectory planning and tracking control of manipulator is gradually increasing. To minimize the vibration during the manipulator motion and improve the planning accuracy, the method of quintic polynomial combined with non-uniform B-spline interpolation is studied for joint space (JS) planning. The trajectory tracking system is easily affected by friction nonlinearity and parameters. So a JS trajectory tracking controller based on based on fuzzy neural network (FNN) is designed. Through simulation experiments, the curve obtained by the planning method studied is smoother and the planning error is minimum. The maximum position error is 0.09 rad, and the speed error is not more than 0.1 rad/s. The controller performance test results under different parameters show that the W^, c^, κ^ parameter in FNN can be adjusted in real time, and the value will not affect the performance of the controller. The fluctuation range of trajectory error of different joints is within ±0.2×10-5rad, which indicates that the performance of AFNNC controller studied is better. And its response time is the shortest and its robustness is better when the load changes suddenly
Research on high-speed railway vehicle emergency braking control based on rail surface foreign matter identification
Get PDFIn order to improve the operation stability of high-speed railway vehicles, an emergency braking control method for high-speed railway vehicles based on the identification of foreign matters on the track surface is proposed. The dynamic frame scanning method is used to build the image acquisition of abnormal objects on the high-speed rail track surface, and the visual sensor and vibration sensor are used to identify and process the features of foreign objects on the high-speed rail track surface. According to the abnormal feature extraction results, the command signal in case of foreign objects is transmitted to the terminal command library of the braking control system. According to the transfer switch of the emergency braking system to display the main emergency disposal output states such as the train emergency disposal information reception, emergency disposal level, emergency disposal type and other information, the joint control method of contact pressure distribution and non-uniform heat flux is adopted, and the joint control method of control system, drive system, disc friction system and signal acquisition system is adopted. The emergency braking control module is established to realize the emergency braking control of high-speed railway vehicles according to the feature recognition results of foreign matters on the rail surface. The test results show that the control module is less affected by the vehicle wheelbase characteristics, track structure characteristics and other factors when using this method for high-speed railway vehicle emergency braking control, and has a strong ability to identify the characteristics of foreign matters on the track surface, which improves the stability and real-time performance of emergency braking
Studying the impact of reservoir temperature, water salinity and CO2 dryness on CO2 injectivity during geological CO2 sequestration
Get PDFCarbon capture and storage (CCS) is proved to be effective measure for reducing CO2 emissions. whilst the world still highly depends on the use of fossil fuel energy, this method is necessary for reaching the world’s 1.5 °C goal. Saline aquifers among all possible underground formations are most common targeted ones for CO2 storage due to their frequent presence, and large storage capacity. However, this storage option suffers from sufficient well injectivity to inject large volumes of CO2 at acceptable rates through a minimum number of wells. The injectivity impairment/reinforcement happens through mineral dissolution, fine particle movement, salt precipitation and hydrate formation (known so far). Each of these mechanisms will be more dominant in injectivity alteration at different distance from the injection point depending on reservoir pressure and temperature, formation water salinity, rock mineralogy, and flow rate of CO2 injection as well as its dryness. In this study we have chosen a commercial software Eclipse 300 together with an open-source code to investigate the impact of formation characteristics, CO2 -Brine-Rock interaction, pressure, temperature as well as injection rate on injectivity alteration. The goal for this work is to provide a workflow which can help predicting injectivity alteration using the existing tools. Simulation results show that permeability is affected severely by salt precipitation during CO2 injection. Combined static and dynamic parameter study demonstrate that the injection rate plays a crucial role in size and expansion of CO2 plume as well as growth rate of dry out zone length, amount of salt precipitation and length of equilibrium region. The higher the injection rate, the quicker activation of the capillary and gravity force which leads to drag more brine to near well-bore resulting in higher volume fraction of salt precipitation. However, low injection rate could result in smaller CO2 plume, shorter dry out zone and longer equilibrium region in term of distance from injection point. Thus, optimizing the injection rate regarding reservoir parameters i.e., temperature, pressure and in-situ salinity, will lead to higher storage capacity as well as well performance and maintenance