Journal of Engineering and Thermal Sciences
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Multi frequency weak signals detection based on under-sampling bistable stochastic resonance
Get PDFSignal detection has a wide range of practical applications. Compared with traditional weak signal detection, the nonlinear effect of noise in the bistable system is typical and easy to extend, so bistable stochastic resonance detection technique has a wider applicability. In this paper, the multi-frequency weak signals detection based on under-sampling bistable stochastic resonance is studied. Based on the theory of bistable stochastic resonance, a simulation model is established to simultaneously detect multiple low-frequency weak signals. The spectrum of input and output signals is obtained through numerical simulation calculation, and the system characteristics are analyzed. When the large parameter signal does not meet the adiabatic approximation theory, the appropriate sampling coefficient can be selected to directly under-sample the input signal to make it conform to the conditions, and then the scale inverse transformation can be carried out. Finally, combined with the simulation analysis, the correctness of the under-sampling bistable stochastic resonance system to detect the multi-frequency weak signals is verified, the sampling rate is reduced, and the complexity is effectively decreased
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
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
Material selection in sensor design for additive manufacturing
Get PDFSurface acoustic sensor technology plays a crucial role in numerous mechatronic systems as it enables the detection of physical interactions with the environment. These sensors, operating at micro scales, can be seamlessly integrated into various industrial applications. To harness their full potential, it is essential to establish a systematic approach for the design and manufacturing of these sensors to meet the demands of cutting-edge applications. This study focuses on creating a finite element analysis-based model, aiming to identify the most suitable Interdigital Transducer (IDT) material for the production of surface acoustic wave sensors using additive manufacturing techniques. By leveraging statistical methods, the research seeks to optimize material selection. The structural design parameters of the chosen material will then be utilized to evaluate the performance of the surface acoustic wave sensor. The study also delves into the prospective applications of this technology in diverse fields, shedding light on its promising future
Exploring CO2 storage potential in Lithuanian deep saline aquifers using digital rock volumes: a machine learning guided approach
Get PDFThe increasing significance of carbon capture, utilization and storage (CCUS) as a climate mitigation strategy has underscored the importance of accurately evaluating subsurface reservoirs for CO2 sequestration. In this context, digital rock volumes, obtained through advanced imaging techniques such as micro-Xray computed tomography (MXCT), offer intricate insights into the porous and permeable structures of geological formations. This study presents a comprehensive methodology for assessing CO2 storage viability within Lithuanian deep saline aquifers, namely Syderiai and Vaskai, by utilizing petrophysical properties estimated from digital rock volumes of samples from analogous formations. It also demonstrates the potential of integrating advanced imaging techniques, machine learning, and numerical modeling for accurate assessment and effective management of subsurface CO2 storage
Discrete sliding mode control method for particle swarm optimization-based brushless DC motor of electric vehicle
Get PDFBrushless DC motor (BLDCM) is a multivariable nonlinear time-varying system, which is difficult to control. The discrete sliding mode control method for BLDCM of electric vehicle on the basis of particle swarm optimization (PSO) is studied to improve the application of BLDCM in electric vehicle. The mathematical model of BLDCM of electric vehicle is established using the state formula. Based on the mathematical model of BLDCM, through the analysis of electromagnetic torque control of BLDCM, it is clear that controlling the angle between rotor flux and stator flux can accurately control the electromagnetic torque of BLDCM. The adaptive discrete sliding mode controller (SMC) is set to control the electromagnetic torque of BLDCM of electric vehicle, and the PSO algorithm is adopted to obtain the optimal parameters of the adaptive discrete SMC to realize the discrete sliding mode control of BLDCM of electric vehicle. According to experimental results, the proposed method can achieve the accurate control of torque and speed of BLDCM of electric vehicle, and increase the application of BLDCM in electric vehicle
Longitudinal deformation of Shield tunnel based on construction monitoring data
Get PDFThe rapid development of urbanization has changed the traffic and transportation in the central area. The change of the surrounding rock and structural stress state of the project under construction caused by the tunnel construction in the same period has caused great harm to its safe use and casualties. Shield construction technology can achieve safe excavation and lining, with high degree of automation. And it is a relatively common construction method at present. But its adaptability to section size and section environmental conditions is poor. In view of this, from the analysis of construction monitoring data, the study established a longitudinal model considering lateral effects from the perspective of lateral characteristics. It also achieved stress assessment and improvement through lateral deformation calculation, segment ring bolt calculation and formula correction. The experimental results showed that the opening at the circumferential seam of the right line of the test tunnel under this method is 8.9 mm. The radius of curvature is 758 mm, and the safety assessment level of longitudinal deformation is 3. This method can effectively guarantee the safety of shield tunnel construction and has good guiding value for tunnel management and maintenance
Transportation of hydrogen by main gas pipelines as a methane-hydrogen mixture
Get PDFDue to the emergence of new technologies that make it possible to obtain hydrogen from associated petroleum gas, it has become necessary to store and transport it. As a solution to this problem, the possibility of hydrogen transportation as a methane-hydrogen mixture was considered, i.e. natural gas with a certain hydrogen content. The article considers the issues of methane-hydrogen mixture (MHM) transportation through existing main gas pipelines at various percentages of hydrogen to natural gas. As an example, the Urengoyskoye field was chosen, where it is possible to produce hydrogen from the associated gas of gas condensate fields, and a section of the Novopskovskiy corridor, through which it is possible to transport MHM. In the work, the influence of the hydrogen content in the methane-hydrogen mixture on the gas-dynamic characteristics of the pipeline, mainly on the pressure and throughput capacity of gas in the pipeline, as well as the influence of its content on the operating mode of the compressor station and the power of the gas turbine, when using MHM for the station's own needs, was studied. The obtained results show an insignificant effect of the hydrogen percentage in the mixture on the pressure and throughput of the gas pipeline, which is a weighty argument in favor of the possibility of transporting hydrogen through existing gas pipelines
Overview of the prospects for the introduction of ultrasonic oil treatment in the main pipeline transport
Get PDFThis paper considers the most common methods of pipeline transport of high solidified oil existing at the moment. The effects of treating oil with magnetic and electric fields are given. The positive and negative effects of ultrasonic treatment in oil transport processes are considered. The totality and quality of the facts requires much more in-depth analysis on a number of issues in this area because with a lot of positive effects are present and negative, which do not allow to implement
Optimizing and reliability analysis by firefly and genetic algorithms for a quadcopter
Get PDFOur study aims to obtain the highest level of reliability for a quadcopter, taking financial and mass limitations into account, to achieve the highest level of reliability with the lowest mass and cost. For this purpose, we first calculated the reliability and the relationships that govern it, and based on these relationships, we determined the reliability of the quadcopter subsystems. In order to achieve the highest level of reliability, we utilized optimization algorithms. It is possible to increase the reliability of a system through several methods, such as enhancing the quality of parts and components, using surplus components, improving the quality of parts and components by always using surplus components, and redesigning the system. This study examines the possibility of increasing quadcopter reliability by using additional parts and optimizing it using the firefly algorithm. Lastly, in order to validate the results obtained from the firefly algorithm, we implemented the problem once again using the genetic algorithm and compared the results obtained from both algorithms. After 20 times of running the algorithms, the optimal reliability values were 0.99925 for the firefly algorithm and 0.99999 for the genetic algorithm