Mechatronic Platform Research Articles

Formation of Vibration Fields for a Mechatronic Platform Driven by Dual Asynchronous Motors

This paper investigates the formation of vibration fields in a mechatronic setup driven by dual induction motors, relying on the controlled synchronization of unbalanced rotors. The proposed algorithm enables precise control over rotor speeds and phase shifts. Experimental results from a multi-resonance vibration laboratory setup demonstrate this approach’s ability to form the vibration fields. The ability to control these fields is crucial for applications such as vibratory transportation and the mixing of bulk materials. The results obtained can ensure a diverse picture of the complex trajectories of motion for various points of the platform, primarily in the screens, making various useful effects for vibration technologies. Additionally, the practical value of this research is that in the case of double synchronous mode the ordinate of the lower point of the trajectory is lower than in the case of single synchronous mode, which improves the efficiency of unloading and prevents congestion formation. The experimental data highlight the practical advantages and potential improvements in efficiency and reliability offered by this method.

Precision Phenotyping of Wild Rocket (Diplotaxis tenuifolia) to Determine Morpho-Physiological Responses under Increasing Drought Stress Levels Using the PlantEye Multispectral 3D System

The PlantEye multispectral scanner is an optoelectrical sensor automatically applied to a mechatronic platform that allows the non-destructive, accurate, and high-throughput detection of morphological and physiological plant parameters. In this study, we describe how the advanced phenotyping platform precisely assesses changes in plant architecture and growth parameters of wild rocket salad (Diplotaxis tenuifolia L. [DC.]) under drought stress conditions. Four different irrigation supply levels from moderate to severe, required to keep 100, 70, 50, and 30% of the water-holding capacity, were adopted. Growth rate and plant architecture were recorded through the digital measure of biomass, leaf area, Canopy Light Penetration Depth, five convex hull traits, plant height, Surface Angle Average, and Voxel Volume Total. Vegetation color assessments included hue, lightness, and saturation. Vegetation and senescence indices were calculated from canopy reflectance in the red (620–645 nm), green (530–540 nm), blue (peak wavelength 460–485 nm), near-infrared (820–850 nm), and 3D laser (940 nm) ranges. The temperature, relative humidity, and solar radiation of the environment were also recorded. Overall, morphological parameters, color, multispectral data, and vegetation indices provided over 7200 data points through daily scans over three weeks of cultivation. Although a general decrease in growth parameters with increasing stress severity was observed, plants were able to maintain the same morpho-physiological performances as the control during the early growth stages, keeping both 70% and 50% of the total water-holding capacity. Among indices, the Normalized Differential Vegetation Index (NDVI) contributed the most to the differentiation between different stress levels during the cultivation cycle. Across the 3 weeks of growth, statistically significant differences were observed for all traits except for the Saturation Average. Comparisons with respect to the control highlighted the strong impact of drought stress on morphological plant traits. This study provided meaningful insights into the health status of wild rocket salad under increasing drought stress.

Contamination Detection Using a Deep Convolutional Neural Network with Safe Machine—Environment Interaction

In the food and medical packaging industries, clean packaging is crucial to both customer satisfaction and hygiene. An operational Quality Assurance Department (QAD) is necessary for detecting contaminated packages. Manual examination becomes tedious and may lead to instances of contamination being missed along the production line. To address this issue, a system for contamination detection is proposed using an enhanced deep convolutional neural network (CNN) in a human–robot collaboration framework. The proposed system utilizes a CNN to identify and classify the presence of contaminants on product surfaces. A dataset is generated, and augmentation methods are applied to the dataset for nine classes such as coffee, spot, chocolate, tomato paste, jam, cream, conditioner, shaving cream, and toothpaste contaminants. The experiment was conducted using a mechatronic platform with a camera for contamination detection and a time-of-flight sensor for safe machine–environment interaction. The results of the experiment indicate that the reported system can accurately identify contamination with 99.74% mean average precision (mAP).

Magnetically Actuated Surface Microstructures for Efficient Transport and Tunable Separation of Droplets and Solids

Efficient transportation of droplets (≈101–102 μL) and small solid objects (≈101–102 mm3) have important applications in many fields, such as microfluidics, lab‐on‐a‐chip devices, drug delivery, etc. A novel multifunctional surface consisting of a periodic array of micro‐lamellae from a soft magnetoactive elastomer on a plastic substrate is reported for these purposes. The physical origin of the propulsion is the bending of soft magnetic lamellae in nonuniform magnetic fields, which is also observed in uniform magnetic fields. The magnetoactive surface is fabricated using a facile and rapid method of laser ablation. The propulsion of items is realized using a four‐pole rotating magnet. This results in a cyclic lamellar fringe motion over the microstructured surface and brings an advantage of easy reciprocation of transport by rotation reversal. Two modes of object transportation are identified: “pushing” mode for precise control of droplet and solid positioning and “bouncing” mode for heavier solid objects transportation. A water droplet of 5 μL or a glass sphere with a 2.1 mm diameter can be moved at a maximum speed of 60 mm s−1. The multifunctionality of the proposed mechatronic platform is demonstrated on the examples of selective solid–liquid separation and droplet merging.

Smart Platform for Monitoring and Control of Discrete Event System in Industry 4.0 Concept

We are now living in a time when the fourth industrial revolution is bringing new technologies with intensive digitalization of all levels of production. This paper presents a complex solution for the monitoring, diagnosis, and control of the production process, in our case, discrete event systems. The proposed solution—a mechatronic platform—further develops and extends our recent results where the overall concept was outlined and some partial tasks were studied. The present paper provides the complete structure of the proposed platform together with implementation details for all functionalities. The developed platform uses the latest technologies, such as OPC UA; industrial communication and visualization protocols and tools; and augmented reality, which enables comfortable interaction with real processes. The laboratory-scaled case study shows the qualities of the proposed solution.

Handiski simulator performance under PSO-based washout and control parameters optimization

The transfer of advanced technology to the person with a disability who wishes to practice a sporting activity is gaining momentum in the science/engineering world. This paper seeks to approve more comfort and sensations for people with paraplegia on a motion simulation platform during a ski operation. The Motion Cueing Algorithm (MCA) has proven itself for sensation reproduction, which we propose to improve by integrating the physical limits of our 8-DoF mechatronics platform. An extended classical MCA is proposed to respond to the significant lack of restored sensation in the intermediate frequency range. A Particle Swarm Optimization (PSO) is constructed to perform optimal washout filter parameters and control law parameters. Consequently, the reproduced skier trajectory stability is obtained. The results show that the proposed algorithm will overcome the physical limitation problem in the Handiski simulator, improve the realism of movement sensation, and reduce the false cues to enhance dynamic fidelity.

Design and Implementation of a Ball-Plate Control System and Python Script for Educational Purposes in STEM Technologies.

This paper presents the process of designing, fabricating, assembling, programming and optimizing a prototype nonlinear mechatronic Ball-Plate System (BPS) as a laboratory platform for engineering education STEM. Due to the nonlinearity and complexity of BPS, the task presents challenges such as: (1) difficulty in controlling the stabilization of a particular position point, known as steady-state error, (2) position resolution, known as specific distance error, and (3) adverse environmental effects—light-shadow error, which is also discussed in this paper. The laboratory prototype BPS for education was designed, manufactured and installed at Karlovac University of Applied Sciences in the Department of Mechanical Engineering, Mechatronics program. The low-cost two-degree BPS uses a USB HD camera for computer vision as a feedback sensor and two DC servo motors as actuators. Due to control problems, an advanced block diagram of the control system is proposed and discussed. An open-source control system based on Python scripts, which allows the use of ready-made functions from the library, allows the color of the ball and the parameters of the PID controller to be changed, indirectly simplifying the control system and performing mathematical calculations directly. The authors will continue their research on this BPS mechatronic platform and control algorithms.

Bionic for Training: Smart Framework Design for Multisensor Mechatronic Platform Validation.

Home monitoring supports the continuous improvement of the therapy by sharing data with healthcare professionals. It is required when life-threatening events can still occur after hospital discharge such as neonatal apnea. However, multiple sources of external noise could affect data quality and/or increase the misdetection rate. In this study, we developed a mechatronic platform for sensor characterizations and a framework to manage data in the context of neonatal apnea. The platform can simulate the movement of the abdomen in different plausible newborn positions by merging data acquired simultaneously from three-axis accelerometers and infrared sensors. We simulated nine apnea conditions combining three different linear displacements and body postures in the presence of self-generated external noise, showing how it is possible to reduce errors near to zero in phenomena detection. Finally, the development of a smart 8Ws-based software and a customizable mobile application were proposed to facilitate data management and interpretation, classifying the alerts to guarantee the correct information sharing without specialized skills.

A mechatronics data collection, image processing, and deep learning platform for clinical posture analysis: a technical note.

Static and dynamic posture analysis was a critical clinical examination in physiotherapy and rehabilitation. It was a time-consuming task for clinicians, so a semi-automatic method can facilitate this process as well as provide well-documented medical records and strong infrastructure for deep learning scenarios. The current research presents a mechatronics platform for static and real-time dynamic posture analysis, which consisted of hybrid computational modules. Our study was a developmental and applied research according to a system development life cycle. The designed modules are as follows: (1) a mechanical structure includes patient place, 360-degree engine, mirror, laser, distance meter, and cams; (2) a software module includes data collection, electronic medical record, semi-automatic image analysis, annotation, and reporting, and (3) a network to exchange raw data with deep learning server. Patients were informed about the research by their healthcare provider and all data were transformed into a Fourier format, in which the patients remained autonomous without a bit of information. The results show acceptable reliability and validity of the instruments. Also, a telerehabilitation application was designed to cover the patients after diagnosis. We suggest a longer time for data acquisition. It will lead to a more accurate and fully automated dynamic posture analysis. The result of this study suggest that the designed mechatronics device used in conjunction with smartphone application is a valid tool that can be used to obtain reliable measurements.

A benchmark mechatronics platform to assess the inspection around pipes with variable pitch quadrotor for industrial sites

This paper investigates the inspection-of-pipe topic in a new framework, by rotation around a pipe, peculiar to industrial sites and refineries. The evolution of the ultimate system requires prototype design and preliminary tests. A new benchmark has been designed and built to mimic the rotation around a pipe, with the main purpose of assessing the different types of rotors and control systems. The benchmark control system presents a mechatronics package including mechanical design and machining, electronics and motor drive, motor-blade installation, computer programming, and control implementation. The benchmark is also modular, working with two modes of one- and two-degree-of-freedom (DoF), easily interchangeable. To cover a full rotation, conventional fixed-pitch drones fail to provide negative thrusts; nonetheless, variable-pitch (VP) rotor quadcopters can produce that in both directions. A closed-loop nonlinear optimal method is chosen as a controller, so-called, “the state-dependent Riccati equation (SDRE)” approach. Optimal control policies are challenging for experimentation though it has been successfully done in this report. The advantage of the VP is also illustrated in a rotation plus radial motion in comparison with fixed-pitch rotors while a wind gust disturbs the inspection task. The proposed VP system compensated the disturbance while the fixed pitch was pushed away by the wind gust. The solution methods to the SDRE were mixed, a closed-form exact solution for the one-DoF system, and a numerical one for the two-DoF. Solving the Riccati online in each time step is a critical issue that was effectively solved by the implementation approach, through online communication with MATLAB software. Both simulations and experiments have been performed along with a discussion to prove the application of VP systems in rotary-motion pipe inspection.

Early balance impairment in Parkinson’s Disease: Evidence from Robot-assisted axial rotations

ObjectiveEarly postural instability (PI) is a red flag for the diagnosis of Parkinson’s disease (PD). Several patients, however, fall within the first three years of disease, particularly when turning. We investigated whether PD patients, without clinically overt PI, manifest abnormal reactive postural responses to ecological perturbations resembling turning. MethodsFifteen healthy subjects and 20 patients without clinically overt PI, under and not under L-Dopa, underwent dynamic posturography during axial rotations around the longitudinal axis, provided by a robotic mechatronic platform. We measured reactive postural responses, including body displacement and reciprocal movements of the head, trunk, and pelvis, by using a network of three wearable inertial sensors. ResultsPatients showed higher body displacement of the head, trunk and pelvis, and lower joint movements at the lumbo-sacral junction than controls. Conversely, movements at the cranio-cervical junction were normal in PD. L-Dopa left reactive postural responses unchanged. ConclusionsPatients with PD without clinically overt PI manifest abnormal reactive postural responses to axial rotations, unresponsive to L-Dopa. The biomechanical model resulting from our experimental approach supports novel pathophysiological hypotheses of abnormal axial rotations in PD. SignificancePD patients without clinically overt PI present subclinical balance impairment during axial rotations, unresponsive to L-Dopa.

System Designs and Experimental Assessment of a Seven-Mode Vehicle-Oriented Hybrid Powertrain Platform

This study developed a mechatronics platform for a seven-mode vehicle-oriented powertrain system. The innovative “all-in-one” concept was used for flexibly arranging various power or energy sources to be combined for various hybrid powertrains. Hence, it significantly reduces the cost and human resources for evaluating new-type power systems or developed vehicle control strategies on the same experimental platform. In this study, three power sources were chosen for providing hybrid power. The first source is a 125 c.c. spark ignition (SI) engine, where a controllable throttle valve governs the output torque, while a fuel meter measures the consumed fuel. The second one is a 1.5kW hub motor, where a motor control unit (MCU) and a 48V lithium battery pack properly provide the required electric power. The third source is an air engine, where a 220V air compressor and other components provide the pneumatic power. For the experimental platform, a developed Matlab/Simulink package receives the measured signals and sends the control commands to actuators. Through the on/off state control of three controllable e-clutches, three single-source modes, three dual-source modes, and one three-source mode (3+3+1) can be conducted. A 1.1kW/24V magnetic powder brake emulates the road load. The results show that three dual-source modes and a three-source mode were successfully operated. The efficiencies, torques and speeds, mass flow rates, etc. have been measured and calculated. This platform is aimed for the research fields of green energies, advanced powertrains, and power flow management.

In-Fiber Capillary-Based Micro Fabry-Perot Interferometer Strain Sensor

Air-cavity fiber Fabry-Perot interferometers (FFPIs), composed by a micrometric section of capillary fiber (CF) spliced between two single-mode fibers (SMFs), were fabricated and tested to longitudinal strain using a high-precision, semi-automatic, and reconfigurable mechatronic platform. It was observed that strain sensitivity increased from 2.11 to 27.5 pm/ $\mu \varepsilon $ , to our knowledge one of the largest ever reported for a single FFPI, as the length of the air cavity decreased from 270.9 to $2.189~\mu \text{m}$ . The characteristics of the reflected spectra of the FFPIs fabricated, high contrast and large free spectral range (FSR), made feasible the intensity-monitoring of strain. A remarkable sensitivity of 3.51 nW/ $\mu \varepsilon $ was obtained with an air-cavity of $16.79~\mu \text{m}$ . The intensity interrogation of the FFPI allows the reduction of the sensor cost, making the proposed strain sensor very competitive in a wide range of practical applications.

An affordable 3D-printed positioner fixture improves the resolution of conventional milling for easy prototyping of acrylic microfluidic devices.

We present a simple and low-cost positioner fixture to improve the fabrication resolution of acrylic microchannels using conventional milling machines. The positioner fixture is a mechatronic platform that consists of three piezoelectric actuators assembled in a housing made of 3D printer parts. The upper part of the housing is raised by the simultaneous actuation of the piezoelectric elements and by the deformation of 3D-printed hinge-shaped supports. The vertical positioning (Z-axis) can be controlled with a resolution of 500 nm and an accuracy of ±1.5 μm; in contrast, conventional milling machines can achieve resolutions of 10 to 35 μm. Through simulations, we found that 3D-printed hinges can deform to reach heights up to 27 μm without suffering any mechanical or structural damage. To demonstrate the capabilities of our fixture, we fabricated microfluidic devices with three weir filters that selectively capture microbeads of 3, 6 and 10 μm. We used a similar weir filter design to implement a bead-based immunoassay. Our positioner fixture increases the resolution of conventional milling machines, thus enabling the fast and easy fabrication of thermoplastic fluidic devices that require finer microstructures in their design.

Case Study of Hierarchical Interface-Based Supervisory Control for a Mechatronic Platform

Abstract Industrial manufacturing systems are becoming more complex by inserting properties aligned with the precepts of Industry 4.0. In this context, this paper seeks to define a reference model for the Mecatrime platform based on hierarchical interface-based supervisory control (HISC) with a parallel architecture, in order to validate the existing control logic and impose a hierarchy that limits complexity, adds flexibility and facilitates future improvements to the system.

Ankle Mechanical Impedance During the Stance Phase of Running.

Differences in locomotor biomechanics between walking and running provide fundamental information about human ambulation. Joint mechanical impedance is a biomechanical property that governs the body's instantaneous response to disturbances, and is important for stability and energy transfer. Ankle impedance has been characterized during walking, but little is known about how humans alter joint impedance during running. The purpose of this study was to estimate ankle impedance during the stance phase of running, and compare to previously reported estimates during walking. Perturbations were applied to the ankle using a one-degree-of-freedom (DOF) mechatronic platform. Least-squares system identification was performed using a parametric model consisting of stiffness, damping, and inertia. The model accounted for 89% ± 16% of variance. Ankle stiffness reached a maximum of 10 Nm/rad/kg at the end of mid-stance, decreasing in terminal stance phase to values previously reported during swing phase. Quasi-stiffness values differed significantly from stiffness across the stance phase of running. Comparing ankle impedance estimates between walking and running showed differences in both magnitude, and temporal variation. Ankle impedance differs significantly between walking and running. This study provides novel information about the biomechanics of running and broadens our understanding of how the mechanical impedance of the ankle joint differs between locomotor tasks, motivating the need for future studies.

A Mechatronic Platform for Computer Aided Detection of Nodules in Anatomopathological Analyses via Stiffness and Ultrasound Measurements.

This study presents a platform for ex-vivo detection of cancer nodules, addressing automation of medical diagnoses in surgery and associated histological analyses. The proposed approach takes advantage of the property of cancer to alter the mechanical and acoustical properties of tissues, because of changes in stiffness and density. A force sensor and an ultrasound probe were combined to detect such alterations during force-regulated indentations. To explore the specimens, regardless of their orientation and shape, a scanned area of the test sample was defined using shape recognition applying optical background subtraction to the images captured by a camera. The motorized platform was validated using seven phantom tissues, simulating the mechanical and acoustical properties of ex-vivo diseased tissues, including stiffer nodules that can be encountered in pathological conditions during histological analyses. Results demonstrated the platform’s ability to automatically explore and identify the inclusions in the phantom. Overall, the system was able to correctly identify up to 90.3% of the inclusions by means of stiffness in combination with ultrasound measurements, paving pathways towards robotic palpation during intraoperative examinations.

Identification of Slippage on Naturalistic Surfaces via Wavelet Transform of Tactile Signals

The effort toward replicating human skills into artificial systems is growing constantly. While artificial vision has reached a certain reliability, the sense of touch is still hard to introduce into robotic devices. Human manipulation comprises a sequence of static and dynamic actions, which may include unforeseen events, such as variation of object position, movement of the fingers, and modification of the object dimensions and shape (e.g., with soft objects) due to inappropriate force levels. These circumstances are likely to produce the slippage of the object being manipulated. Artificial manipulators are not yet able to be effective in dynamic environments. This paper intends to provide a method for the identification and prevention of slippage with tactile sensors. The method is based on filtering the tactile signals to extract slippage information. The filtering has been executed by means of the stationary wavelet transform that consists of recursive filtering operations. Then, the transformed signal has been rectified and its root mean square has been computed. Finally, an on/off signal has been generated according to a threshold logic. Eight natural surfaces, featuring diverse tactile properties, have been used with the aim of validating the ability of the method to be applied regardless the surface properties. To evaluate repeatability and generalization ability, a total of 2000 experiments have been performed, 250 per each stimulus, with a mechatronic platform: five velocities combined with five indentation force levels, repeating each combination 10 times. Results are provided in terms of true positive detection and of delay between onset of slippage and algorithm output.

Digital implementation of a self-triggered control approach for a mechatronic platform: experimental results

Digital implementation of a self-triggered control approach for a mechatronic platform: experimental results

Digital implementation of a self-triggered control approach for a mechatronic platform: experimental results

This paper addresses the design and presents the experimental results of an aperiodic remote-controlled mechatronic plant using a MiniDK2 electronic development board. We compare the classic periodic control solution with our self-triggered approach. The triggering mechanism consists of evaluating if the measurement error exceeds a predefined value. This measurement error is defined as the difference between the output signal of a model with and without a sample-and-hold that is activated only at the triggering instants. The minimum inter-execution time is the reference period and the maximum time is set by the designer, guaranteeing the stability of the closed loop system. At each new triggering instant, the remote controller receives a new measurement of the system and sends the actuation signal to the mechatronic plant.