Motion Machine Research Articles

How the digital economy enhances the grain supply chain resilience in China: exploring the moderating effects of government innovation-driven

IntroductionEnsuring food security in the new development paradigm urgently requires increasing the grain supply chain resilience. In order to clarify how can significantly enhance grain supply chain resilience, to demonstrate the relationship between the digital economy, government innovation-driven and grain supply chain resilience is necessary. To specify how the government can effectively perform its macro-regulatory functions, the government innovation-driven is reflected by government innovation-driven planning and government innovation-driven investment, respectively.MethodsThe data of 31 provinces in China from 2011 to 2021 have been used. The panel fixed effects model, moderating effects model and threshold effects model have been selected to analyze.ResultsDigital economy has a stronger enhancement effect on grain supply chain resilience; Government innovation-driven has an increased moderating effect on digital economy enhance grain supply chain resilience; The enhancement effect of digital economy and the moderating effect of government innovation-driven are differentiated between China’s functional zones of grain production; And the threshold effect of government innovation-driven planning shows a process of digestion and absorption, which accumulating to 0.018 will emerge a multiplier effect. Government innovation-driven investment is higher than 0.026, which can have a promoted moderating effect.DiscussionTo expand the depth of integration of the digital economy, accurately government innovation-driven, the focus should be on attracting innovative talent, who can construct the perpetual motion machine mode of “external promote + internal drive,” so as to strengthen the robustness of the grain supply chain.

Design of a mixed robotic machining system and its application in support removal from metal additive manufactured thin-wall parts

Robotic machining could provide a solution for removing supports from metal additive manufactured workpieces, replacing labor-intensive work. However, the robot’s intrinsic weaknesses of low positioning accuracy and structural rigidity primarily restrict its applications. Improving the accuracy of robotic machining remains an unresolved issue. A mixed solution is proposed, in which a portable CNC machine with the capability of visual feature recognition is equipped with a universal industrial robot. The robot implements positioning motions in a large space, while the portable CNC fulfills accurate machining motions on a local feature of the workpiece. A sizeable weight of the portable CNC exerts a moderate load on the industrial robot’s joints, increasing joint stiffness. The mixed machining system exhibits high accuracy and stiffness when milling a steel/titanium alloy workpiece, achieving tolerances up to ±0.04 mm on a 60×80 mm U-shaped path without exciting any structural vibration modes. When the dimension of the workpiece exceeds the machining range of the portable CNC, a combined algorithm of coarse-fine registration based visual identification and robot error compensation is designed to align the spatial coordinates of the machining motion with that of the positioning motion, thereby extending the machining range with high accuracy. Through the proposed mixed robot machining method, experiments of doubling the machining range have been done to verify that the mixed machining robotic system is able to slot a 550 mm-long path with accuracy of ±0.1 mm. Furthermore, the mixed robotic machining system is applied to recognize and remove multiple supports of lattices, grids and ribs from a titanium-alloy additive manufactured thin-wall workpiece with high accuracy and high efficiency.

Prototyping disruptive self-sufficiency power machines composed by cascaded power units based on thermo-hydraulic actuators

This research focuses on developing a prototype for a disruptive Self-Sustaining Power Machine (SSPM) that consists of cascaded power units (PUs). Each PU integrates thermo-mechanical and thermo-hydraulic actuators to drive hydraulic pumps connected to generators. The prototype's design leverages two thermal cycle types, sVsVs and VsVs, which enable self-sustaining operations by employing several strategic capabilities that challenge the limitations of second-kind perpetual motion machines (PMMs). Therefore, key capabilities include: 1- Performing useful mechanical work through the expansion and contraction of the Thermal Working Fluid (TWF) by adding and removing heat. 2- Utilizing recovered heat through potential superposition techniques, thereby upgrading the heat to a higher grade, which enhances heat recovery strategies. 3- Designing an efficient energy transfer chain from thermal to electrical energy via thermo-mechanical or thermo-hydraulic actuators, a hydraulic energy drive system, and conversion from hydraulic to electrical energy. 4- Configuring the system to achieve more useful work than the heat added to the initial PU downstream. Two main prototype types are proposed to demonstrate these proposed capabilities: 1- Continuous motion using the sVsVs thermal cycle, with volumetric reservoirs for thermal working fluids (TWF) located outside the thermo-mechanical or thermo-hydraulic actuators. 2- Discontinuous motion using the VsVs thermal cycle, with volumetric reservoirs for TWF located inside the active volume of the thermo-mechanical or thermo-hydraulic actuators. The prototypes were evaluated through case studies using air and helium as real TWFs. Results indicate that the SSPM composed of five cascaded PUs operating on an sVsVs cycle achieved a global efficiency of 149.6% (SSI of 49.6%) with helium and 126% (SSI of 26%) with air. In contrast, the VsVs cycle yielded a global efficiency of 183% (SSI of 83%) with helium and 133% (SSI of 33%) with air

Collaborative human and computer controls of smart machines – A proposed hybrid control

Human-Machine Interaction (HMI) and Brain-Computer Interface (BCI) are evolving technologies that show the great potentials to extract and utilize humans’ intents in controlling smart machines. However, existing HMI and BCI technologies are limited in terms of (1) the number of Degrees- of-Freedom (DoF) to be controlled and (2) the ways the performance of BCI-enabled control systems are verified and validated. This study aimed to explore the solutions to addree both of above concerns; we proposed a hybrid control system that is capable of training, detecting, and interpreting humans’ intents, and utilizing humans’ intents in real-time controls of smart machines. More specifically, the system acquired brain signals in the form of Electroencephalography (EEG) by an Emotiv Epoc X and processed these signals to detect and extract humans’ intents in real-time machine controls. To cope with the frequency difference of humans’ thinking and machine motion controls, we developed a hybrid control module to fuse humans’ and machine's intelligence so that low-frequency humans’ intents could be used in real-time machine controls. The system was prototyped and verified experimentally. The system was verified to achieve the accuracy of over 90 % in recognizing humans’ intents and controlling a robot by the operator's intents with a satisfactory responding time and accuracy.

Synthetic ground motions in heterogeneous geologies from various sources: the HEMEWS-3D database

Abstract. The ever-improving performances of physics-based simulations and the rapid developments of deep learning are offering new perspectives to study earthquake-induced ground motion. Due to the large amount of data required to train deep neural networks, applications have so far been limited to recorded data or two-dimensional (2D) simulations. To bridge the gap between deep learning and high-fidelity numerical simulations, this work introduces a new database of physics-based earthquake simulations. The HEterogeneous Materials and Elastic Waves with Source variability in 3D (HEMEWS-3D) database comprises 30 000 simulations of elastic wave propagation in 3D geological domains. Each domain is parametrized by a different geological model built from a random arrangement of layers augmented by random fields that represent heterogeneities. Elastic waves originate from a randomly located pointwise source parametrized by a random moment tensor. For each simulation, ground motion is synthesized at the surface by a grid of virtual sensors. The high frequency of waveforms (fmax⁡=5 Hz) allows for extensive analyses of surface ground motion. Existing and foreseen applications range from statistical analyses of the ground motion variability and machine learning methods on geological models to deep-learning-based predictions of ground motion that depend on 3D heterogeneous geologies and source properties. Data are available at https://doi.org/10.57745/LAI6YU (Lehmann, 2023).

Special issue on adaptive motion of animals and machines

Special issue on adaptive motion of animals and machines

Muscle intent-based continuous passive motion machine in a gaming context using a lightweight CNN

Muscle intent-based continuous passive motion machine in a gaming context using a lightweight CNN

Information-Theoretic Bayesian Inference for Multi-Agent Localization and Tracking of an Radio Frequency Target With Unknown Waveform

Abstract Information-theoretic motion planning and machine learning through Bayesian inference are exploited to localize and track a dynamic radio frequency (RF) emitter with unknown waveform (uncooperative target). A target-state estimator handles non-Gaussian distributions, while mutual information is utilized to coordinate the motion control of a network of mobile sensors (agents) to minimize measurement uncertainty. The mutual information is computed for pairs of sensors through a four-permutation-with-replacement process. The information surfaces are combined to create a composite map, which is then used by agents to plan their motion for more efficient and effective target estimation and tracking. Simulations and physical experiments involving micro-aerial vehicles with time difference of arrival (TDOA) measurements are performed to evaluate the performance of the algorithm. Results show that when two or three agents are used, the algorithm outperforms state-of-the-art methods. Results also show that for four or more agents, the performance is as competitive as an idealized static sensor network.

Analysis and Design of Engraving Machine Movement

CNC routers play a significant role in several markets such as furniture design, circuit board manufacturing, plastic and foam fabrication. It can allow to complete projects in few hours that used to take several days CNC routers can work on sheets of woods, plastic, rubber, acrylics, and non-ferrous metal and CNC router machine moves and cuts in three directions using computer aided design software.A computer program has been established to design the power screws of any engraving machine. The power required to cut material was calculated by the program. The resisting force was analyzed and all stresses act on the power screws. The power screws were designed by using the main common theory of failures. The buckling and maximum deflection was checked in this program.An example of the output results was designed and drawn in Advanced Centre of Technology using solid works software. The nut connected to the screws was also drawn. The parts of engraving machine have been manufactured and tested in Advanced Centre Technology A.C.T in Libya.

Prototyping a Disruptive Self-Sustaining Power Plant enabled to overcome Perpetual Motion Machines

This research discusses a strategic methodology for implementing a disruptive Self-Sustaining Power Plant (SSPP) characterized by the cascading coupling of a group of Power Units (PUs). In this configuration, the heat released from each PU due to the cooling of the thermal working fluid (TWF) is efficiently recovered and reused as supply heat for the first PU in the cascade. Two case studies on the SSPP have been conducted using air and helium as TWFs. The first deals with PUs coupled in cascade operating with closed processes-based Vsp thermal cycles, while the second involves PUs coupled in cascade operating with closed processes-based VsVs thermal cycles. Following the corresponding analysis of both case studies, significant results were obtained. These results, derived from this preliminary design study, will be applied to the implementation of the disruptive SSPP prototype operating with real gases as working fluids. This allows for a precise and clear understanding of the issue of generating useful work through expansion, contraction, or both. Moreover, according to the results, the SSPP composed by a group of power units where the efficiency of each power unit operating with air as working fluid only approaches a value of the efficiency of 22%, can exceed 100% of the nominal design power under certain conditions, which supposes a flagrant violation of the principle of conservation of energy due to the fact that such disruptive Self-Sustaining Power Plant is enabled to overcome a Perpetual Motion Machine of second kind.

Optimal placement of inherent zeros in polynomial-based motion profiles for minimizing residual vibration and travel time under system uncertainties

Various industrial processes require motion profiles that determine machine movement over time for workpiece transfer, with the goal of minimizing transfer time to enhance productivity. However, pursuing the maximum speed can trigger excessive motion-induced vibration, which can reduce the manufacturing efficiency, accuracy and operational lifespan of the system. This study proposes a generalized motion profile optimization method that considers the strategic placement of inherent zeros within the motion profile: each inherent zero contributes to the reduction of residual vibration or optimization of arrival time. By offering freedom to the placement of zeros, four optimization options for polynomial-based motion profiles of each order are proposed, expanding on existing work that offered a single option. All proposed optimization options have closed-form solutions, making them easily applicable to industrial applications. The practical applicability of the suggested methodology is demonstrated through case studies and experiments.

Design and Development of Automated Lower Limb Continuous Passive Motion (CPM) Machine

Abstract: Post-operative rehabilitation is critical in orthopedic surgery, especially for hip joint surgeries. Traditional therapies like manual exercises and resource limits in rehabilitation centers might be tough, but early mobilization and rehabilitation are critical for regaining joint function and allowing patient return to normal activities. Continuously Passive Motion (CPM) devices, primarily developed for knee joint rehabilitation, offer a non-invasive method for passive joint mobility, restoring joint range of motion and lowering post-operative stiffness risk. Their application in hip joint healing is gaining pace, offering better results and increased patient satisfaction. The research also investigates abduction mobility in the hip joint, which is necessary for daily actions like stepping to the side, getting out of bed, or exiting a car. Understanding hip joint biomechanics and range of motion parameters is vital for establishing efficient rehabilitation approaches. By merging clinical insights with technology innovations, this research intends to optimize post-surgery rehabilitation regimens, enhancing patient outcomes and quality of life. The subject of orthopedic rehabilitation continues to expand through interdisciplinary collaboration and innovation, bringing new choices for enhancing patient care and recovery trajectories.

Dextran-tryamine hydrogel maintains position and integrity under simulated loading in a human cadaver knee model

ObjectiveThis dextran-tyramine hydrogel is a novel cartilage repair technique, filling focal cartilage defects to provide a cell-free scaffold for subsequent cartilage repair. We aim to asses this techniques’ operative feasibility in the knee joint and its ability to maintain position and integrity under expected loading conditions. MethodSeven fresh-frozen human cadaver legs (age range 55–88) were used to create 30 cartilage defects on the medial and lateral femoral condyles dependent of cartilage quality, starting with 1.0 ​cm2; augmenting to 1.5 ​cm2 and eventually 2.0 ​cm2. The defects were operatively filled with the injectable hydrogel scaffold. The knees were subsequently placed on a continues passive motion machine for 30 ​min of non-load bearing movement, mimicking post-operative rehabilitation. High resolution digital photographs documented the hydrogel scaffold after placement and directly after movement. Three independent observers blinded for the moment compared the photographs on outline attachment, area coverage and hydrogel integrity. ResultsThe operative procedure was uncomplicated in all defects, application of the hydrogel was straightforward and comparable to common cartilage repair techniques. No macroscopic iatrogenic damage was observed. The hydrogel scaffold remained predominately unchanged after non-load bearing movement. Outline attachment, area coverage and hydrogel integrity were unaffected in 87%, 93% and 83% of defects respectively. Larger defects appear to be more affected than smaller defects, although not statistically significant (p ​> ​0.05). ConclusionThe results of this study show operative feasibility of this cell-free hydrogel scaffold for chondral defects of the knee joint. Sustained outline attachment, area coverage and hydrogel integrity were observed after non-load bearing knee movement.

Study results in curvilinear motion of high-speed track machine with electromechanical transmission

Introduction. Transport and technological means based on tracked undercarriages have found their use in both military and civilian industries. Their widespread use is due to a number of advantages that contribute to the further development of mechanization of production, increasing the efficiency of transportation of minerals, and developing infrastructure during the development of new territories. Ensuring cross-country ability and mobility of vehicles with tracked undercarriages, including tracked conveyor-tractors, is possible through the use of hybrid electromechanical transmissions. One of the components of scientific research in this direction is carrying out simulation modeling of the movement of equipment. Modeling the motion process will make it possible to substantiate the energy characteristics of the electromechanical transmission of a tracked vehicle and confirm the adequacy of previously performed theoretical studies.Research methods. The main objective of the simulation was to confirm the effectiveness of the theoretical studies performed. The studies in the VISSIM programming environment using typical motion cycles that equivalently reflect the operating conditions and use of a tracked machine were carried out.Results. As a result of the research, quantitative estimates of the influence of the power of a diesel generator and the charge of an energy storage device on the dynamic performance of equipment were obtained. It has been established that in order to meet the requirements for promising samples, the power of the energy storage device should be at least 2.5 kWh when using a standard internal combustion engine.Discussion and conclusion. The research results can be used to create, based on the existing scientific and technical background, a promising robotic complex with an electromechanical transmission.

Development and verification of shield thrust vector self-adaptive control technology in soft soil strata

To solve the difficulty in automatically obtaining an effective total thrust vector relative to the shield posture adjustment requirements during self-driving in soft soil strata, a shield thrust vector self-adaptive control technology for shield machines was proposed. Subsequently, a large-scale model platform was established to simulate the straight-line advancement of the testing shield machine under dynamic loads, and the feasibility of steady shield driving was verified. The test results showed that: the actual total thrust force exhibited the same variation characteristics according to load force, while a relatively fixed difference of 1000 kN between the two caused by the system friction was observed. A quick recovery after an abrupt jump of the shield speed was discovered once there was a sudden, significant change in the load. The actual resultant moment of total thrust force effectively responded to the load force, and the shield postures were maintained well. Further, the driving speed and the horizontal stroke difference were controlled in the ranges of ±3 mm/min and ±5 mm of each set values, respectively. Subsequently, this technology was applied to the Wusongkou Yangtze River Tunnel project in Shanghai, and the on-site test results verified its feasibility in actual soft soil strata. The shield speed remained stable as the actual thrust forces shared the same changing low of the target values, and a fixed difference between the two was maintained to ensure the movement of the shield machine. The variation curves of the actual steering angles in both the horizontal and vertical directions coincided with those of the target steering angles because the resultant horizontal and vertical moments of the thrust force effectively responded to each steering requirement, which was executed with high quality.

Adaptive fuzzy weighted median filter for microcalcifications detection in digital breast tomosynthesis images

Breast cancer is a global leading cause of female mortality. Digital breast tomosynthesis (DBT) is pivotal for early breast cancer detection, with microcalcifications serving as crucial indicators. However, the movement of the DBT machine introduces blurry artefacts, potentially impacting accurate diagnosis. This study addresses this challenge by proposing an adaptive fuzzy weighted median filter (AFWMF) to enhance DBT images and aid microcalcification diagnosis. AFWMF automatically determines optimal parameters based on input images, outperforming conventional methods with a threshold range (C) from peak to end of switching. Quantitative assessment reveals peak signal to noise ratio (PSNR), and mean absolute error (MAE) values of 96.2267 and 0.0000636, respectively, demonstrating a significant improvement in microcalcification detection. This study contributes an effective and adaptive enhancement technique for DBT images, promising better breast cancer diagnosis, particularly in microcalcification scenarios.

Laser and microwave instrumentation for ITER and future reactors

ITER diagnostics include an extensive set oflaser and microwave diagnostics to give access to a wealth of information on thecore and edge plasma and to support high performance operation of ITER. Forexample, Core and Edge Thomson scattering systems build detailed density andtemperature profiles on time scales much faster than τ E to follow transientevents; ECE and reflectometry add time resolution to follow MHDevents. Implementing these diagnostics is challenging, needing a panoply oftechnologies to keep them functioning reliably for thousands of hours despiteextreme events such as disruptions and wall conditioning cycles. Shielding,shutters and cleaning systems protect the forward elements of most opticalsystems from the build-up of deposits and damage. Still, plasma-facing mirrorsmust survive laser loads and endure erosion, deposition and in-situ RFcleaning. Calibration and monitoring systems ensure accurate and drift-freeoperation. These support systems are also not straightforward and requiredspecific R&D. Access also drives the design: to deal with the neutronand gamma sources yet allow maintenance of activated components, ITER useslarge, multi-purpose ports that couple otherwise distinct systems into modulesfor maintenance. Machine movement requires provisions to maintain alignment andcalibration, from these port plugs, shown in figure 1, to theaccessible areas 10–50 m away. A final complication comes from the difficulty ofemploying electronics near the plugs. Extensive qualification for radiationresistance is needed. This paper examines design adaptations that ITER adoptedfor its near-reactor environment, consider the lessons learnt from the ITERdesign activity specifically for laser and microwave systems and lays out somepossible evolution paths for the reactor diagnostician that must follow a moreindustrial approach.

Фундаментальний аналіз та оптимізація (мінімізація) динамічних навантажень у пружних елементах механізмів підйому вантажу кранів. Частина І

The fundamental analysis and optimization (minimization) of dynamic loads in elastic elements (ropes) of load lifting mechanisms of cranes used in urban development is carried out. The basis of the analysis and methodology of optimization of motion modes of the mentioned mechanisms is the approach implemented in the classical calculus of variations, namely: the integral functional is minimized, which reflects undesirable properties of the mechanical system. Optimized modes of motion of the crane load lifting mechanism, which is represented in the paper by a mechanical system with a linear function of the position of its elements (the load on the rope and the drive mechanism). The significant influence of motion modes of exactly drive mechanisms on dynamic loads in elastic elements (ropes) of the load lifting mechanism of a city-building crane is shown. Usually separate typical modes of motion optimize only one certain property of the specified mechanism. In many practical cases, it is necessary to select modes of motion that optimize a set of properties of a machine or mechanism (respectively, a crane or a load lifting mechanism of a city-building crane). It is for the selection of such modes of motion of machines and mechanisms that dynamic criteria for their evaluation are needed. All existing criteria for evaluating machines and mechanisms can be conditionally divided into two classes: 1) positional (maximum values of kinematic characteristics of links, dynamic loads, amplitudes and frequencies of oscillations, dynamics coefficients, etc.); 2) integral (rms values of kinematic characteristics of links and dynamic loads, energy costs, etc.). In the work the fundamental analysis of the mentioned criteria is carried out and it is shown that for estimation of motion modes of hoisting machines, as well as mechanisms of cargo lifting cranes (boom, bridge, gantry, city cranes) it is necessary to use integral criteria, because they are the ones that estimate motion during the whole cycle. Integral criteria for evaluating urban construction cranes and load lifting mechanisms are presented, which fully reflect their dynamic properties, motion characteristics and, in particular, minimize dynamic loads on elastic elements (ropes). The results obtained in this study can be further used to clarify and improve the existing engineering methods of calculation of hoisting cranes used in urban planning, as well as their load lifting mechanisms, both at the design stages and in the modes of proper operation.

Design study of a disruptive self-powered power plant prototype

This research work discusses a preliminary disruptive prototype design of a self-powered thermal power plant doing work by strictly isothermal closed processes using forced convection heat transfer both for adding and extracting heat. It includes useful work by expansion and vacuum-based contraction due to adding heat to and extracting heat from a working fluid. A cycle analysis considering useful work due to vacuum-based contraction is the core of the problem-solving methodology. The findings will be applied to the prototyping implementation task, which includes the cascade and series of cascade coupling of several regenerative power units. The empirical results of the case studies provide the data needed to carry out a prototyping task considering the results of real cases subjected to realistic irreversibilities and heat recovery factors that make the self-feeding power plant an interesting design option. This extraordinary result confirms the technical viability of real machines that exhibit the ability to provide more energy than they use, that is, second-class perpetual motion machines

Cloud center energy consumption control for predictability in neural fuzzy systems

Cloud computing provides tool-based IT services to customers worldwide. It is built on a fee-for-service model and enables the hosting of large programs from consumer, scientific, and commercial domains. However, cloud application hosting data centers have enormous energy consumption, which leads to high operating expenses and a carbon footprint. Cloud centers get a lot of requests from different users every day. The centers need strong servers that consume a lot of energy and peripherals in order to run in order to meet these needs. It should go without saying that reducing cloud center energy usage requires efficient resource utilization. We have taken a novel hybrid method in this study. Neural fuzzy systems have been employed for the dynamic resource allocation in the cloud with the goal of minimizing energy consumption and load prediction, and the ant colony optimization method has been utilized for the virtual machine's movement. The experimental results show that the proposed strategy works optimally, as compared to other methods in the literature that have the same objective. When compared to other comparable approaches, the suggested solution has an average resource loss of 23.1 % in 720 time periods and an average request denial rate that is 6.5 % lower. Moreover, extensive testing with the SPECpower benchmark has confirmed the proposed methodology, yielding a forecast accuracy of over 97 % for the proposed energy consumption model.