Motion Machine Research Articles

Modeling of Running Equipment of Mobile Lifts

Problem. Mobile lifts with working platforms have found wide application in various fields of industry. One of the main requirements when designing such machines is to ensure the stability and trouble-free performance of technological operations. The article presents the results of the development of a digital three-dimensional model of such a machine, and also describes virtual studies on controlling the machine's movement at different positions of the running gear. Goal. It was decided to divide the entire set of tasks to be solved into clusters in which it is possible to obtain reliable information with minimal time for the development of the models, as well as with the least load of the software. The main task was to develop a computer model of the running gear to study the maneuverability of the machine. Methodology. Geometric modeling was performed with limited initial data, the properties of the materials used for parts were not taken into account, and welding was not modeled. However, the geometry of the frame and all components was reproduced almost completely in the dimensions and configurations of the real object. Results. The computer model enabled establishing of the dependence of the machine's turning radii from the geometric design parameters of the chassis, as well as from the turning patterns and position of the longitudinal beams. Originality. The computer model made it possible to maneuver in three independent schemes: the classic 4x2 wheeled vehicle turning mechanism, turning with all four wheels (on the front and rear axles in opposite directions), and when all wheels turn in one direction, the so-called "crab stroke". Practical value. The proposed models and algorithms will significantly speed up the design process for this class of vehicles.

Methods for improving the efficiency of a small forklift with an on-board steering system

In the known scientific and technical literature, insufficient attention is paid to the study of the dynamic processes of wheeled vehicles with an on-board steering system. An overview of the operation of small-sized loaders is presented. The aim of this work is to improve the methodology for calculating the parameters of the turning process and the dynamic stability of a small-sized loader with a 4x4 wheel configuration. A single-axle nonlinear mathematical model with five degrees of freedom is presented. Based on the Lagrange equations of the second kind, analytical dependencies of the machine's motion were compiled. The following main parameters were varied during the modeling process: the mass of the load to be lifted, and the position of the center of mass of the entire machine, the height of the bucket above the bearing surface, and the initial speed of the loader. The 4th order Runge-Kutt numerical method was used to solve the composite mathematical model. When comparing the calculated and experimental oscillograms, they practically coincide in terms of the main form of oscillation and the nature of the change in traction force, with a discrepancy of 11%. When the loader turns as a result of sliding the running wheels on the bearing surface, the oscillatory process is undamped and close in nature to self-oscillations. In this case, the running wheels are detached from the bearing surface, and with an increase in the outreach and height of the load, the intensity of oscillations increases and, under certain circumstances, it is possible to lose machine stability or to hit the bucket bottom against the bearing surface. When the center of mass of the loader passes through the axle of the front wheels, the machine becomes unstable. This corresponds to the maximum angle of deviation of the center of mass forward. As a criterion for the stability of a loader during a turn, it is proposed to calculate the angle of deviation of its center of mass relative to the static position. At the maximum overhang of the bucket with a full load, its value should not exceed 170.

Design and Development of Power Transmission System for Tractor Operated Hybrid Bio-Composite Mulch Sheet Laying Machine

Tractor 3 point hitch drawn hybrid bio-composite bio degradable mulch laying machine was designed and developed based on the formulation of the hybrid bio-composite mulch sheets with a intension of the integrate the field operations at easy pace and conserve the time and labour. The prototype was fabricated and tested in the fields in order to perform the operations such as hybrid bio-composite mulch sheet laying, Mulch sheet pressing and guiding and soil covering on the edges of the mulch sheets in one forward movement of the machine. The machine was fabricated with design of many components but the power transmission system was plays a major role in this machine as the entire forward movement of machine and performance of the mulch sheet laying unit was depends on the power transmission system only. Various components of power transmission system was designed such as shafts, chain, bearings and sprockets etc. The shaft design was done considering the two conditions of fields while in operation like considering twisting and bending moments of the shaft as well as sudden applied shocks and fluctuated loads. Considering the two conditions, the main shaft, counter shaft and rear wheel shafts diameters were designed based on this two conditions and obtained results were 30 mm, 40 mm and 25 mm respectively The chain and sprocket will be used for the transmitting the power from one shaft to other one. The length of the chain was calculated 162.56 cm and the HP transmitted by the selected chain and HP of chain drive system were calculated as 2.05 hp and 0.339 hp respectively. Based on the results, the calculated horse power was less than the horse power of selected chain that means required horse power was 0.339 hp but we have got 2.05 hp, hence the design was safe and machine will be operate without any hassles.

A digital twin-based machining motion simulation and visualization monitoring system for milling robot

A digital twin-based machining motion simulation and visualization monitoring system for milling robot

Technical note: Feasibility of gating for dynamic trajectory radiotherapy - Mechanical accuracy and dosimetric performance.

Dynamic trajectory radiotherapy (DTRT) extends state-of-the-art volumetric modulated arc therapy (VMAT) by dynamic table and collimator rotations during beam-on. The effects of intrafraction motion during DTRT delivery are unknown, especially regarding the possible interplay between patient and machine motion with additional dynamic axes. To experimentally assess the technical feasibility and quantify the mechanical and dosimetric accuracy of respiratory gating during DTRT delivery. A DTRT and VMAT plan are created for a clinically motivated lung cancer case and delivered to a dosimetric motion phantom (MP) placed on the table of a TrueBeam system using Developer Mode. The MP reproduces four different 3D motion traces. Gating is triggered using an external marker block, placed on the MP. Mechanical accuracy and delivery time of the VMAT and DTRT deliveries with and without gating are extracted from the logfiles. Dosimetric performance is assessed by means of gamma evaluation (3% global/2 mm, 10% threshold). The DTRT and VMAT plans are successfully delivered with and without gating for all motion traces. Mechanical accuracy is similar for all experiments with deviations<0.14° (gantry angle),<0.15° (table angle),<0.09° (collimator angle) and<0.08 mm (MLC leaf positions). For DTRT (VMAT), delivery times are 1.6-2.3 (1.6- 2.5) times longer with than without gating for all motion traces except one, where DTRT (VMAT) delivery is 5.0 (3.6) times longer due to a substantial uncorrected baseline drift affecting only DTRT delivery. Gamma passing rates with (without) gating for DTRT/VMAT were ≥96.7%/98.5% (≤88.3%/84.8%). For one VMAT arc without gating it was 99.6%. Gating is successfully applied during DTRT delivery on a TrueBeam system for the first time. Mechanical accuracy is similar for VMAT and DTRT deliveries with and without gating. Gating substantially improved dosimetric performance for DTRT and VMAT.

Photoresponsive Rotaxane-Branched Dendrimers: From Nanoscale Dimension Modulation to Macroscopic Soft Actuators.

Aiming at the construction of novel soft actuators through the amplified motions of molecular machines at the nanoscale, the design and synthesis of a new family of photoresponsive rotaxane-branched dendrimers through an efficient controllable divergent approach was successfully realized for the first time. In the third-generation rotaxane-branched dendrimers, up to 21 azobenzene-based rotaxane units located at each branch, thus making them the first successful synthesis of light-control integrated artificial molecular machines. Notably, upon alternative irradiation with UV and visible light, photoisomerization of the azobenzene stoppers leads to the collective and amplified motions of the precisely arranged rotaxane units, resulting in controllable and reversible dimension modulation of the integrating photoresponsive rotaxane-branched dendrimers in solution. Moreover, novel macroscopic soft actuators were further constructed based on these photoresponsive rotaxane-branched dendrimers, which revealed fast shape transformation behaviors with an actuating speed up to 21.2 ± 0.2° s-1 upon ultraviolet irradiation. More importantly, the resultant soft actuators could produce mechanical work upon light control that has been further successfully employed for weight-lifting and cargo transporting, thus laying the foundation toward the construction of novel smart materials that can perform programmed events.

Simulation-driven bandpass filter in association with an optimal bandwidth to detect faults in axial piston pumps

Due to the special working environments of axial piston pumps in engineering, fault features are disrupted by the natural periodic impulses. A finite element method (FEM) simulation-driven bandpass filter (BPF) is provided for detecting bearings. However, the bandwidth of the BPF is designed empirically through human experience with uncertainty. To overcome the associated limitations, a bandwidth optimization strategy of FEM simulation-driven BPF is proposed by using an integrated kurtosis, which is a combination of two kinds of kurtosis indices. The new index is used as a discrimination value for a success–failure algorithm to iteratively determine the optimal bandwidth of the BPF. Finally, compared to the original BPF and its improved version, experimental results of faulty bearings in an axial piston pump verify the fault feature extraction ability for the reciprocating motion machine under heavy impact-induced natural periodic impulses.

Sequencing of operations and repeatable machines in smart manufacturing

In traditional manufacturing, a machine is treated as having one operation function, but in smart manufacturing, each machine can have more than one operation function. Traditional group technology (GT) focuses on whether a part has been operated on by a machine, but this study focuses on the sequencing of operations for a part, the volume (batch) of a part, and repeatable machines. This study proposes two algorithms based on the close-neighbor concept and takes into account these three factors. One of the algorithms considers volume (batch); the other does not. A GT efficiency measurement is proposed that considers part movement, machine movement, part volume, and group size, the last three being factors commonly excluded from the literature on GT efficiency calculations and operation sequence. Six numerical examples, which demonstrate the algorithm’s implementation, are compared with solutions generated by other algorithms from the literature, and the proposed algorithm is shown to have superior GT efficiency. Although increasing the number of groups can increase the GT efficiency, it can also, due to the effect of group size, increase the movements of the parts and/or the machines. All the resolutions can be used by managers making plant layout decisions.

Evaluation of Soil Infiltration Variability in Compacted and Uncompacted Soil Using Two Devices

Infiltration is defined by the expression of the hydraulic conductivity of the soil, which we decided to monitor on an experimental field applying a modern system of land management (control traffic farming). The present study compared two different methods of monitoring the hydraulic conductivity of soil on a selected 16 ha plot of land in the suburbs of the village Kolíňany (Slovak Republic). During the growing seasons, crops such as oilseed rape, winter wheat, spring barley, winter barley, spring peas, and maize alternated in individual years. In addition to the study of hydraulic conductivity, a long-term experiment is underway to investigate the influence of technogenic factors on soil degradation using a system of controlled movement of machines in the field. A mini disk infiltrometer (method one) was used to evaluate the unsaturated hydraulic conductivity of the soil, and a double ring infiltrometer (method two) was used to measure the saturated hydraulic conductivity. Monitoring changes in soil infiltration capacity within the compacted and uncompacted lines required 26 monitoring points (20 for method one and 6 for method two). The first longitudinal line was compacted by an agricultural machinery chassis, and the second line remained uncompressed. The research also created transverse compacted lines at eight monitoring points (six for method one and two for method two). The results did not show a statistically significant difference when examining the effect of soil infiltration monitoring (compacted p = 0.123; uncompacted p = 0.99). When evaluating the statistical dependence on the compression caused by machinery in the track line, the hypothesis of significance was not confirmed (p = 0.12, at the level of 0.05). However, the results showed variability in the value of the difference factor between the two methods, ranging from 0 to 0.24. On average, it can be concluded that the results achieved using the double ring infiltrometer were 4.16 times higher than those measured with the mini disk infiltrometer. The variability of hydraulic conductivity was demonstrated not only in the compacted but also in the non-compacted part of the plot. In some places, the phenomenon of water repellency appeared, which could be caused by the drier location of the targeted plot.

Method for Determining the Dominant Type of Human Breathing Using Motion Capture and Machine Learning

Since the COVID-19 pandemic, the demand for respiratory rehabilitation has significantly increased. This makes developing home (remote) rehabilitation methods using modern technology essential. New techniques and tools, including wireless sensors and motion capture systems, have been developed to implement remote respiratory rehabilitation. Significant attention during respiratory rehabilitation is paid to the type of human breathing. Remote rehabilitation requires the development of automated methods of breath analysis. Most currently developed methods for analyzing breathing do not work with different types of breathing. These methods are either designed for one type (for example, diaphragmatic) or simply analyze the lungs’ condition. Developing methods of determining the types of human breathing is necessary for conducting remote respiratory rehabilitation efficiently. We propose a method of determining the type of breathing using wireless sensors with the motion capture system. To develop that method, spectral analysis and machine learning methods were used to detect the prevailing spectrum, the marker coordinates, and the prevailing frequency for different types of breathing. An algorithm for determining the type of human breathing is described. It is based on approximating the shape of graphs of distances between markers using sinusoidal waves. Based on the features of the resulting waves, we trained machine learning models to determine the types of breathing. After the first stage of training, we found that the maximum accuracy of machine learning models was below 0.63, which was too low to be reliably used in respiratory rehabilitation. Based on the analysis of the obtained accuracy, the training and running time of the models, and the error function, we choose the strategy of achieving higher accuracy by increasing the training and running time of the model and using a two-stage method, composed of two machine learning models, trained separately. The first model determines whether the breath is of the mixed type; if it does not predict the mixed type of breathing, the second model determines whether breathing is thoracic or abdominal. The highest accuracy achieved by the composite model was 0.81, which surpasses single models and is high enough for use in respiratory rehabilitation. Therefore, using three wireless sensors placed on the patient’s body and a two-stage algorithm using machine learning models, it was possible to determine the type of human breathing with high enough precision to conduct remote respiratory rehabilitation. The developed algorithm can be used in building rehabilitation applications.

DeepWild: Application of the pose estimation tool DeepLabCut for behaviour tracking in wild chimpanzees and bonobos.

Studying animal behaviour allows us to understand how different species and individuals navigate their physical and social worlds. Video coding of behaviour is considered a gold standard: allowing researchers to extract rich nuanced behavioural datasets, validate their reliability, and for research to be replicated. However, in practice, videos are only useful if data can be efficiently extracted. Manually locating relevant footage in 10,000 s of hours is extremely time-consuming, as is the manual coding of animal behaviour, which requires extensive training to achieve reliability. Machine learning approaches are used to automate the recognition of patterns within data, considerably reducing the time taken to extract data and improving reliability. However, tracking visual information to recognise nuanced behaviour is a challenging problem and, to date, the tracking and pose-estimation tools used to detect behaviour are typically applied where the visual environment is highly controlled. Animal behaviour researchers are interested in applying these tools to the study of wild animals, but it is not clear to what extent doing so is currently possible, or which tools are most suited to particular problems. To address this gap in knowledge, we describe the new tools available in this rapidly evolving landscape, suggest guidance for tool selection, provide a worked demonstration of the use of machine learning to track movement in video data of wild apes, and make our base models available for use. We use a pose-estimation tool, DeepLabCut, to demonstrate successful training of two pilot models of an extremely challenging pose estimate and tracking problem: multi-animal wild forest-living chimpanzees and bonobos across behavioural contexts from hand-held video footage. With DeepWild we show that, without requiring specific expertise in machine learning, pose estimation and movement tracking of free-living wild primates in visually complex environments is an attainable goal for behavioural researchers.

Computerized Simulation of Meshing of S-gears and Modification Geometry

S-gear is a new type of gear with the advantages of small sliding coefficient, high meshing efficiency and large load-bearing capacity due to the concave-convex contact in a vicinity of the meshing start and end. In view of the excellent characteristics and potential value of S-gears, this paper deeply studies the designation and meshing characteristics of the S-gears. First, based on the relationship of S-shaped rack-cutter and machining motion, the tooth surface of the S-gears is generated. Second, by superimposing the surface of modified volume with the standard tooth surface, the modified tooth surface of S-gears is constructed. On this basis, using MATLAB programming, the coordinates of 3D grid node of modified S-gears are calculated. Third, loaded tooth contact analysis (LTCA) is used to study the meshing characteristics of the S-gears with longitudinal modifications and misalignment angle errors. Ultimately, one example is presented and the result shows that after tooth surface modification, the load distribution of S-gears is effectively improved and error sensitivity is greatly reduced. S-gear is a new type of gear which is different from involute gears and has great potential application prospect in large load-bearing field, which will be further studied in the future.

Performance enhancement of PV system using VSG with ANFIS controller

With the enormous stress of energy lack and air pollution, renewable energy sources such as photovoltaic sources become an effective solution to solve these problems. The penetration of inertia-less photovoltaic sources into power system has adverse effects on the overall system inertia which threatens system stability. As a solution for this problem, virtual inertia technique can be used as a system controller in order to enhance the system performance and maintain its stability. In this paper, an adaptive virtual synchronous generator (VSG) controller based on the oscillation motion of the synchronous machine is introduced. Then, a proposed VSG with adaptive neuro-fuzzy inference system (ANFIS) is presented as an inverter controller. The system response is investigated and compared with other control methods under different operating scenarios. To verify the effectiveness of the proposed adaptive VSG, an experimental setup is presented with real-time implementation for the system using dSPACE DS1104 interfacing with MATLAB software, and the system response is investigated under different operating scenarios. Upon the presented results, there is an enhancement in the system response when the proposed adaptive VSG with ANFIS controller is used, and this emphasizes the superiority of using such controller in PV systems over other techniques.

Historical Forms of Gradual Transnationalisation of Tourism and the Perpetual Motion Machine behind It

The growing importance of international trade is affecting national tourism. Transnational companies (TNCs) are becoming increasingly important in the tourism sector. The purpose of the article is to clarify the significance of the transnationalization of tourism for economic processes throughout the world and in individual countries. To achieve the goal, the article used the methods of analysis and study of statistical data. As a result, it can be noted that the influence of TNCs on the economic sector is considerable, but reciprocal. The economic component of each country determines the level of opportunities for the development of a tourist destination. In the future, tourism will mainly grow in developing destinations. Many of these countries are at least partly dependent on international tourism to support their economic development. TNCs can contribute to the socio-economic development of these countries, for example, through foreign direct investment and transfer of technology and expertise, concluding management contracts or franchising.

A novel tool path planning and feedrate scheduling algorithm for point to point linear and circular motions of CNC-milling machines

The manufacturing process on CNC machines is directed by the Numerical Control (NC) files which include the main tool paths as a combination of numerous instructions such as lines and arcs specified by the G01 and G02/G03 commands. In the literature, the lines and arcs generally are converted to a parametric curve based on the global tool path smoothing or local corner smoothing algorithms. However, the smoothing methods cause the deflection from the tool path in NC-File. In cases where the deflection from the main tool path is not acceptable, point-to-point motion is necessary instead of the smooth trajectory. This study presents a novel trajectory planning and feedrate scheduling algorithm for point-to-point control of linear and circular paths in the NC-File. The proposed method prevents the feedrate fluctuations at the junction points and generates the tool path without deflection from the NC-File. Also, the feedrate scheduling algorithm decrease the operating time of the machine significantly compared to traditional method of point-to-point motion. This study is verified on an industrial 3-Axis CNC-Milling machine by the operating of the roughing milling, drilling, slotting, and face milling process. The measurements of final product and real-time trajectory tracking results show that the proposed method is effective in industrial applications of CNC-Milling machines in which point-to-point motion is necessary.

Projecting robot dynamics onto trajectories

AbstractMachines and mechanisms realize processes, from the shaping process of a milling machine and the motion process of an automotive system to the trajectory realization of a robot. The dynamics of a machine generated by a properly chosen set of constraints in combination with an appropriate drive system is designed to meet the prescribed requirements of the process, which is done by projecting the machine equations of motion on the process dynamics. We get a set of nonlinear relations, which represent the machine motion in terms of the required process motion. A well-known example is the projection of arbitrary many robot degrees of freedom (DOFs) on a given path resulting in a set of nonlinear equations with one DOF only, the path coordinate s. Application of this idea can be used to construct a mobility space $(\ddot{s}, \dot{s}, s)$ for any combination of coordinates and constraints. The paper presents a corresponding approach for n-link robots by applying multibody system theory. Method might be interesting for layout of machines and mechanisms. Practical aspects are discussed, and an example is given.

Reducing the intensity of machine movement in the field improves the structure of the soil

Reducing the intensity of machine movement in the field improves the structure of the soil

Reconstruction of physical dance teaching content and movement recognition based on a machine learning model

With the technological development of movement recognition based on machine learning model algorithms, the content and movements for physical dance teaching are also seeking changes and innovations. In this paper, a set of three-dimensional convolutional neural network recognition algorithms based on a machine learning model is constructed through the collection to recognition of sports dance movement data. By collecting the skeleton information of typical movements of physical dance, a typical movement dataset of physical dance is constructed, which is recognized by the improved 3D convolutional neural network recognition algorithm under the machine learning model, and the method is validated on the public dataset. The experimental results show that the 3D CNNs in this paper can produce relatively satisfactory results for sports dance action recognition with high accuracy of action recognition, which verifies the feasibility of the 3D convolutional neural network action recognition algorithm under the machine learning model for the acquisition to recognition of sports dance actions. It illustrates that the future can be better to open a new direction of physical dance education content through machine learning models in this form.

Time and energy optimal trajectory generation for coverage motion in industrial machines

The increase in computer numerical control machine efficiency highly contributes to environmental emission reduction and energy-savings. Path and trajectory optimizations are used to improve machine efficiency in a coverage motion such as pocket milling, polishing, inspection, gluing, and additive manufacturing. Several studies have proposed coverage motion optimization in improving machine efficiency for time and energy consumption. Ensuring the smoothness and satisfaction of the machine constraints in coverage motion is necessary. This paper proposes a multi-objective path and trajectory optimization to obtain a trade-off between time and energy consumption for coverage motion. Jerk limited acceleration profiles describe the trajectory where velocity profiles generated for each linear segment attain desirable velocities. The energy model of an industrial two-axis feed drive system is used in finding solutions to the optimization problem. The non-dominated sorting genetic algorithm II generates a Pareto front for trade-off time and energy consumption solutions. Simulation results of the proposed method are validated through experiments using the industrial two-axis feed drive system. Experimental results show the effectiveness of the proposed approach where time reduction and energy savings are 10.05% and 2.10%, respectively. In addition, the optimized path has a lower maximum error of 76.6% compared to the constantly commanded velocity optimized path.

MODERN PROBLEMS OF ENERGY SAVING OF GENERAL PURPOSE TRACTORS

The article based on well-known publications summarizes the results of research on the energy saving of generalpurpose tractors, based on the analysis of the specific traction resistances of agricultural machines aggregated with the tractor. The well-known method of estimating the resistance to the movement of agricultural machines based on the acceleration of the tractor acceleration is analyzed. The unsolved problem of energy saving of the tractor unit with GPS in the precision farming system is formulated. The energy saving of the tractor is considered to be one of the most costeffective, for the assessment of which the various publications have suggested different methods. But they is not primed on the method of assigning specific work (on unit of work) to fuel consumption a tractor unit, even when we are has the information of elemental energy consumption. It is recommended to evaluate the energy consumption of the tractor during the technological process behind the traction resistance of the machines by the difference in the acceleration of the tractor acceleration.