Journal of Mechanical Engineering, Automation and Control Systems
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Capillary force method to improve the green density of binder jet additive manufacturing
Get PDFThis study investigates the impact of capillary adhesion force on the green part density in metal powder binder jetting 3D printing. Gas atomized Co-Cr-Mo, SS316L, and pure Cu powders were used to print various samples. The printed samples were then treated with water, 1-Hexanol, and n-Amyl alcohol vapor for 24 hours to nucleate capillary bridges between particles and shrink samples uniformly. The volume change was calculated for each sample, and up to –3.1 % volume change was observed. The proposed method can be used to improve green part densities directly on printed parts before sintering
Automatic vibration control method for grasping end of flexible joint robot
Get PDFBecause flexible robots have flexible components such as reducers, there are problems of accuracy deviation and end vibration in the process of external interference and trajectory tracking. This leads to the proposal of a Sliding Mode Control Approach Based on RBF Neural Network (SMC-RBF) parameter optimization. This method is mainly applied to reduce the end vibration and running position error of flexible robot. Firstly, the Newton-Euler method is used to establish the dynamic model of robot considering joint flexibility. At the same time, the experiment optimizes the Sliding Mode Control (SMC) method through RBF neural network. The experiments verify the control methods of the two-joint flexible robot and the six-joint flexible robot respectively. In the control of two-joint robot, the maximum tracking curve error of SMC is only about 0.25 rad under the interference of pulse signal; And the recovery time is only about 1 s. In the control of 6-joint robot, the maximum error of RBF-sliding mode control method on XYZ axis is 0.7 mm, 0.25 mm and 1.25 mm respectively; The error on three axes is smaller than that of traditional PD control method. The results demonstrate that the tracking error of the improved mode control is small, the chattering phenomenon of the robot system is weakened as well
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
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
DIC measurement method based on binocular stereo vision for image 3D displacement detection
Get PDFThe deformation detection of large machinery is usually achieved using three-dimensional displacement measurement. Binocular stereo vision measurement technology, as a commonly used digital image correlation method, has received widespread attention in the academic community. Binocular stereo vision achieves the goal of three-dimensional displacement measurement by simulating the working mode of the human eyes, but the measurement is easily affected by light refraction. Based on this, the study introduces particle swarm optimization algorithm for target displacement measurement on Canon imaging dataset, and introduces backpropagation neural network for mutation processing of particles in particle swarm algorithm to generate fusion algorithm. It combines the four coordinate systems of world, pixel, physics, and camera to establish connections. Taking into account environmental factors and lens errors, the camera parameters and deformation coefficients were revised by shooting a black and white checkerboard. Finally, the study first conducted error analysis on binocular stereo vision technology in three dimensions, and the relative error remained stable at 1 % within about 60 seconds. At the same time, three algorithms, including the spotted hyena algorithm, were introduced to conduct performance comparison experiments using particle swarm optimization and backpropagation network algorithms. The experiment shows that the three-dimensional error of the fusion algorithm gradually stabilizes within the range of [–0.5 %, 0.5 %] over time, while the two-dimensional error generally hovers around 0 value. Its performance is significantly superior to other algorithms, so the binocular stereo vision of this fusion algorithm can achieve good measurement results
The effect of glass fiber on fresh properties of industrial based geopolymer concrete
Get PDFThis research study is primarily focused on evaluating the fresh properties of industrial-based 3D printable geopolymer concrete by adding glass wool strings and glass fibers activated by sodium silicate solution with a molar ratio of 2.4-2.6 (31 % SiO2 and 13 % Na2O). The glass wool strings, and recycled glass fiber are added to industrial-based geopolymer concrete at a dosage of 1 % to 5 % by volume of the concrete. The fresh concrete properties such as open time, setting time and shape stability of industrial-based geopolymer concrete (GPC) with glass wool and glass fibers were compared with those of industrial-based GPC without glass wool strings and glass fibers. The results show that the addition of glass wool increases the setting time of the concrete mix at room temperature. The deformation of the specimens at room temperature decreased by 39 %. The addition of glass fiber in geopolymers also increases the stiffness by 74 % compared to GPC without glass fiber
The CCS greensand project: CO2 pilot injection and monitoring
No full textCarbon 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
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
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
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