Journal Description
Machines
Machines
is an international, peer-reviewed, open access journal on machinery and engineering published monthly online by MDPI. The IFToMM is affiliated with Machines and its members receive a discount on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), Inspec, and many other databases.
- Journal Rank: JCR - Q2 (Engineering, Mechanical) / CiteScore - Q1 (Mechanical Engineering)
- Rapid Publication: manuscripts are peer-reviewed and a first decision provided to authors approximately 13.1 days after submission; acceptance to publication is undertaken in 3 days (median values for papers published in this journal in the first half of 2021).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
2.428 (2020)
;
5-Year Impact Factor:
2.467 (2020)
Latest Articles
An Improved Invariant Kalman Filter for Lie Groups Attitude Dynamics with Heavy-Tailed Process Noise
Machines 2021, 9(9), 182; https://doi.org/10.3390/machines9090182 (registering DOI) - 27 Aug 2021
Abstract
Attitude estimation is a basic task for most spacecraft missions in aerospace engineering and many Kalman type attitude estimators have been applied to the guidance and navigation of spacecraft systems. By building the attitude dynamics on matrix Lie groups, the invariant Kalman filter
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Attitude estimation is a basic task for most spacecraft missions in aerospace engineering and many Kalman type attitude estimators have been applied to the guidance and navigation of spacecraft systems. By building the attitude dynamics on matrix Lie groups, the invariant Kalman filter (IKF) was developed according to the invariance properties of symmetry groups. However, the Gaussian noise assumption of Kalman theory may be violated when a spacecraft maneuvers severely and the process noise might be heavy-tailed, which is prone to degrade IKF’s performance for attitude estimation. To address the attitude estimation problem with heavy-tailed process noise, this paper proposes a hierarchical Gaussian state-space model for invariant Kalman filtering: The probability density function of state prediction is defined based on student’s t distribution, while the conjugate prior distributions of the scale matrix and degrees of freedom (dofs) parameter are respectively formulated as the inverse Wishart and Gamma distribution. For the constructed hierarchical Gaussian attitude estimation state-space model, the Lie groups rotation matrix of spacecraft attitude is inferred together with the scale matrix and dof parameter using the variational Bayesian iteration. Numerical simulation results illustrate that the proposed approach can significantly improve the filtering robustness of invariant Kalman filter for Lie groups spacecraft attitude estimation problems with heavy-tailed process uncertainty.
Full article
(This article belongs to the Special Issue Modeling, Sensor Fusion and Control Techniques in Applied Robotics)
Open AccessArticle
RISE-Based Composite Adaptive Control of Electro-Hydrostatic Actuator with Asymptotic Stability
Machines 2021, 9(9), 181; https://doi.org/10.3390/machines9090181 - 26 Aug 2021
Abstract
The electro-hydrostatic actuator (EHA), the actuator of electric drive and hydraulic transmission, is competitive since it is small in size, light in weight and high in power density. However, the existence of the velocity loop error of servo motors, unmodeled dynamics and highly
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The electro-hydrostatic actuator (EHA), the actuator of electric drive and hydraulic transmission, is competitive since it is small in size, light in weight and high in power density. However, the existence of the velocity loop error of servo motors, unmodeled dynamics and highly nonlinear uncertainties restrict the improvement of the tracking accuracy of the EHA system. In order to achieve high-precision motion control of EHAs, a RISE-based composite adaptive control scheme is proposed in this paper. In the proposed composite adaptive control design, a novel parameter adaptive law is synthesized to compensate for the parametric uncertainties and a robust integral of the sign of error (RISE) feedback is utilized to suppress the adverse effects caused by the lumped disturbances, including the velocity loop error of a servo motor and other unmodeled dynamics. The synthesized parameter adaptive law possesses the advantage of fast convergence, which is beneficial to achieve transient tracking performance improvement. In addition, the proposed controller is more suitable for practical applications since it is chattering free. The closed-loop system stability analysis shows that the proposed control scheme guarantees an excellent asymptotic tracking performance. Finally, comparative simulations are conducted to verify the high-performance nature of the proposed controller.
Full article
(This article belongs to the Special Issue Advanced Control of Industrial Electro-Hydraulic Systems)
Open AccessArticle
On-Machine Measurement and Error Compensation for 6061 Aluminum Alloy Hexagonal Punch Using a Turn-Milling Machine
by
and
Machines 2021, 9(9), 180; https://doi.org/10.3390/machines9090180 - 25 Aug 2021
Abstract
For machining parts with complex shapes, consisting of computer numerical control (CNC) machine tools, different CNC machine tools will be used according to the machining method. If the workpiece is removed for off-machine measurement after machining, when the size is incorrect, it will
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For machining parts with complex shapes, consisting of computer numerical control (CNC) machine tools, different CNC machine tools will be used according to the machining method. If the workpiece is removed for off-machine measurement after machining, when the size is incorrect, it will need to be returned to the CNC machine tool for secondary machining. In this case, the workpiece surface quality and machining accuracy will be affected, which is very time-consuming. On-machine measurement and complex machine center is a key to solve this problem. In the recent researches that the touch probe was integrated on three or five axis machine for error compensation and shape construction based on on-machine measurement, but turning-milling machine was rare. In addition, the most types of parts were thin-walled parts or thin web parts. In this study, a contact measurement system is integrated into a CNC combined turning-milling machine for on-machine measuring. Macro-programming is used to design the machining path of A6061-T6 aluminum alloy hexagonal punch, and the action of probe measurement is added to the machining path. As the measured data exceed the tolerance range, the calculated data are fed back to the controller for machining improvement by compensation. The finished hexagonal punch is measured in a 3D coordinate measuring machine and the error is compared. The experimental results show that the contact probe needs to be corrected before machining, and the size of the corrected workpiece can reach the tolerance range of ±0.01 mm. The size error of rough machining is larger than that of fined machining, and the size error of rough machining will increase with the length of the workpiece.
Full article
(This article belongs to the Special Issue Advances and Trends in Non-conventional, Abrasive and Precision Machining 2021)
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Sub-Health Identification of Reciprocating Machinery Based on Sound Feature and OOD Detection
Machines 2021, 9(8), 179; https://doi.org/10.3390/machines9080179 - 23 Aug 2021
Abstract
It is inevitable that machine parts will be worn down in production, causing other mechanical failures. With the appearance of wearing, the accuracy and efficiency of machinery gradually decline. The state between healthy and impaired is defined as sub-health. By recognizing the sub-health
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It is inevitable that machine parts will be worn down in production, causing other mechanical failures. With the appearance of wearing, the accuracy and efficiency of machinery gradually decline. The state between healthy and impaired is defined as sub-health. By recognizing the sub-health state of machinery, accuracy and efficiency can be effectively guaranteed, and the occurrence of mechanical failure can be prevented. Compared with simple fault detection, the identification of s sub-health state has more practical significance. For this reason, the sound characteristics of large-scale reciprocating machinery, combined with the concept of OOD (out-of-distribution) detection, are used, and a model for detecting machinery sub-health state is proposed. A planer sound dataset was collected and collated, and the recognition of mechanical sub-health state was realized by a model combining a VGG network and the threshold setting scheme of OOD detection. Finally, an auxiliary decision-making module was added, and Mahalanobis distance was used to represent spatial relationships among samples, further improving the recognition effect.
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(This article belongs to the Section Machines Testing and Maintenance)
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Open AccessArticle
Influence of Aerodynamic Preloads and Clearance on the Dynamic Performance and Stability Characteristic of the Bump-Type Foil Air Bearing
by
and
Machines 2021, 9(8), 178; https://doi.org/10.3390/machines9080178 - 23 Aug 2021
Abstract
The dry lubricated bump-type foil air bearing enables a carrying load capacity due to a pressure build up in a convergent air film. Since the air bearing provides low power dissipation above the lift-off speed and the flexible foil provides an adaptivity against
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The dry lubricated bump-type foil air bearing enables a carrying load capacity due to a pressure build up in a convergent air film. Since the air bearing provides low power dissipation above the lift-off speed and the flexible foil provides an adaptivity against high temperatures, manufacturing errors or rotor growth, the bump-type foil air bearing is in particular suitable for high speed rotating machineries. The corresponding dynamic behavior depends on the operational parameters, the behavior of the flexible foil structure, and in particular on the circumferential clearance. In order to avoid or suppress the critical subsynchronous motion at high rotational speeds, many researchers recommend adding an aerodynamic preload to the bore shape, representing a transition from a circular to a lobed bearing bore shape. In addition to positive effects on the stability, preliminary studies demonstrated degrading effects on the stiffness and damping due to increasing preload values. This observation leads to the assumption, that the preload value meets an optimum with respect to stability, load-capacity, and lift-off speed. With the aim of deriving an appropriate lobe configuration for the design of the bump-type foil air bearing, this work performs comprehensive numerical investigations on the dynamic performance and the stability characteristic as a function of preload and minimum clearance. To this end, this work uses steady-state and transient stability analysis methods to recommend optimal aeroydnamic preload values with respect to the corresponding minimum clearance.
Full article
(This article belongs to the Special Issue High Speed Air Compressor for a Fuel Cell System for Use in a Vehicle)
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Open AccessArticle
A Performance-Driven MPC Algorithm for Underactuated Bridge Cranes
Machines 2021, 9(8), 177; https://doi.org/10.3390/machines9080177 - 20 Aug 2021
Abstract
A crane system often works in a complex environment. It is difficult to model or learn its true dynamics by traditional system identification approaches. If a dynamics model is created by minimizing its prediction error, its use tends to introduce inaccuracies and thus
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A crane system often works in a complex environment. It is difficult to model or learn its true dynamics by traditional system identification approaches. If a dynamics model is created by minimizing its prediction error, its use tends to introduce inaccuracies and thus lead to suboptimal performance. Is it possible to learn the dynamics model of a crane that can achieve the best performance, instead of learning its true dynamics? This work answers the question by presenting a performance-driven model predictive control (P-MPC) algorithm for a two-dimensional underactuated bridge crane. In the proposed dual-layer control architecture, an inner-loop controller uses a proportional–integral–derivative controller to achieve anti-sway rapidly. An outer-loop controller uses MPC to ensure accurate trolley positioning under control constraints. Compared with classical MPC, this work proposes a data-driven method for plant modeling and controller parameter updating. By considering the control target at the learning stage, the method can avoid adjusting the controller to deal with uncertainty. We use Bayesian optimization in an active learning framework where a locally linear dynamics model is learned with the intent of maximizing control performance and then used in conjunction with optimal control schemes to efficiently design a controller for a given task. The model is updated directly based on the performance observed in experiments on the physical system in an iterative manner till a desired performance is achieved. The controller parameters and prediction models of the best closed-loop performance can be found through continuous experiments and iterative optimization. Simulation and experiment results show that we can explicitly find the dynamics model that produces the best performance for an actual system, and the method can quickly suppress swing and realize accurate trolley positioning. The results verified its effectiveness, feasibility, and superior performance on comparing it with state-of-the-art methods.
Full article
(This article belongs to the Special Issue Design and Control of Advanced Mechatronics Systems)
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A Unified Framework for the H∞ Mixed-Sensitivity Design of Fixed Structure Controllers through Putinar Positivstellensatz
by
and
Machines 2021, 9(8), 176; https://doi.org/10.3390/machines9080176 - 20 Aug 2021
Abstract
In this paper, we present a novel technique to design fixed structure controllers, for both continuous-time and discrete-time systems, through an mixed sensitivity approach. We first define the feasible controller parameter set, which is the set of the controller parameters that
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In this paper, we present a novel technique to design fixed structure controllers, for both continuous-time and discrete-time systems, through an mixed sensitivity approach. We first define the feasible controller parameter set, which is the set of the controller parameters that guarantee robust stability of the closed-loop system and the achievement of the nominal performance requirements. Then, thanks to Putinar positivstellensatz, we compute a convex relaxation of the original feasible controller parameter set and we formulate the original controller design problem as the non-emptiness test of a set defined by sum-of-squares polynomials. Two numerical simulations and one experimental example show the effectiveness of the proposed approach.
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(This article belongs to the Special Issue Design and Control of Advanced Mechatronics Systems)
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Aeroacoustic Optimization of the Bionic Leading Edge of a Typical Blade for Performance Improvement
by
, , , , , , , and
Machines 2021, 9(8), 175; https://doi.org/10.3390/machines9080175 - 18 Aug 2021
Abstract
New, innovative optimization approaches to improve turbomachine performance and reduce turbomachine noise are significant in engineering. In this paper, based on the bionic concept, a wave structure is used to shape the leading edge of the blade. Using an NACA0018 blade as the
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New, innovative optimization approaches to improve turbomachine performance and reduce turbomachine noise are significant in engineering. In this paper, based on the bionic concept, a wave structure is used to shape the leading edge of the blade. Using an NACA0018 blade as the basic blade, a united parametric approach controlled by three parameters is proposed to configure the wavy leading edge. Then, a new optimization strategy boosting design efficiency is established to output the optimal design results. Finally, the corresponding performance and flow mechanism are analyzed. Taking into account the existence of the hub wall and the shroud wall from the closed impeller, a near-wall adjustment factor is added, the significance of which is herein demonstrated. An optimal bionic blade is successfully obtained by the optimization strategy, which can reduce the mean drag coefficient by about 6% and the overall sound pressure level by about 3 dB, in relative to the original blade. Mechanism analysis revealed that the wave structure can induce spanwise velocity at the leading edge and cause a further delay in flow separation in the downstream region, synchronously reducing drag and noise.
Full article
(This article belongs to the Special Issue Emerging Techniques and Their Application in Turbomachinery)
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Operator-Based Nonlinear Control of Calorimetric System Actuated by Peltier Device
by
and
Machines 2021, 9(8), 174; https://doi.org/10.3390/machines9080174 - 18 Aug 2021
Abstract
Recently, the development of SiC and GaN high-performance semiconductor devices has led to higher efficiency in power conversion equipment. In order to perform thermal design of power conversion equipment and evaluation of the equipment, it is necessary to measure the power loss of
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Recently, the development of SiC and GaN high-performance semiconductor devices has led to higher efficiency in power conversion equipment. In order to perform thermal design of power conversion equipment and evaluation of the equipment, it is necessary to measure the power loss of the equipment with high accuracy. In a previous study, a system to measure the power loss from the amount of heat emitted from power conversion devices using a Peltier device was proposed. In this study, aiming to improve the measurement accuracy, the temperature dependence of the thermal conductivity of a Peltier device, which was treated as a constant value in the previous study, was considered. The control system considering the temperature dependence of the thermal conductivity was designed based on operator theory, which is a nonlinear control theory. The simulation and experimental results show that the measurement accuracy was improved when the power loss was 10 W and 15 W compared to the case without considering the temperature dependence. In addition, the measurement time was reduced by about 100 s by considering the temperature dependence. The effectiveness of the proposed system was shown when the power loss was 10 W and 15 W.
Full article
(This article belongs to the Special Issue Design and Control of Advanced Mechatronics Systems)
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Open AccessArticle
Fault Detection and Severity Level Identification of Spiral Bevel Gears under Different Operating Conditions Using Artificial Intelligence Techniques
Machines 2021, 9(8), 173; https://doi.org/10.3390/machines9080173 - 18 Aug 2021
Abstract
Spiral bevel gears are known for their smooth operation and high load carrying capability; therefore, they are an important part of many transmission systems that are designed for high speed and high load applications. Due to high contact ratio and complex vibration signal,
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Spiral bevel gears are known for their smooth operation and high load carrying capability; therefore, they are an important part of many transmission systems that are designed for high speed and high load applications. Due to high contact ratio and complex vibration signal, their fault detection is really challenging even in the case of serious defects. Therefore, spiral bevel gears have rarely been used as benchmarking for gears’ fault diagnosis. In this research study, Artificial Intelligence (AI) techniques have been used for fault detection and fault severity level identification of spiral bevel gears under different operating conditions. Although AI techniques have gained much success in this field, it is mostly assumed that the operating conditions under which the trained AI model is deployed for fault diagnosis are same compared to those under which the AI model was trained. If they differ, the performance of AI model may degrade significantly. In order to overcome this limitation, in this research study, an effort has been made to find few robust features that show minimal change due to changing operating conditions; however, they are fault discriminating. Artificial neural network (ANN) and K-nearest neighbors (KNN) are used as classifiers and both models are trained and tested by using the selected robust features for fault detection and severity assessment of spiral bevel gears under different operating conditions. A performance comparison between both classifiers is also carried out.
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(This article belongs to the Special Issue Structural Health Monitoring for Mechanical Systems)
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Open AccessCommunication
Improved Haptic Transparency of Bilateral Control Using Torque-Measured Magnetic Coupling
Machines 2021, 9(8), 172; https://doi.org/10.3390/machines9080172 - 18 Aug 2021
Abstract
The integrity and transparency of a haptic feedback in a bilateral control is crucial for precise and accurate operators’ sensation during human–machine interactions. Conventional master and slave bilateral control systems are often subject to unknown or unwanted disturbances and dynamics in the actuators
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The integrity and transparency of a haptic feedback in a bilateral control is crucial for precise and accurate operators’ sensation during human–machine interactions. Conventional master and slave bilateral control systems are often subject to unknown or unwanted disturbances and dynamics in the actuators and powertrain linkages that hamper the haptic feedback integrity and transparency. Force sensor torque sensing and feedback control are required to mitigate these effects. In contrast to the conventional approach of introducing torque sensing using a mechanical spring, this paper introduces a magnetic coupling as a torque sensor to detect reaction torque between the human input and the master actuator. Disturbance observer-based torque feedback control is designed to suppress the disturbances and tailor the haptic transparency dynamics. Experimental results on a virtual reality interaction system, which involves the steering wheel bilateral control in a cyber-physical driving simulator system, demonstrate the feasibility and effectiveness of the proposed method with improved haptic integrity and transparency.
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(This article belongs to the Special Issue Design and Control of Electrical Machines)
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A Redundantly Actuated Chewing Robot Based on Human Musculoskeletal Biomechanics: Differential Kinematics, Stiffness Analysis, Driving Force Optimization and Experiment
Machines 2021, 9(8), 171; https://doi.org/10.3390/machines9080171 - 18 Aug 2021
Abstract
Human masticatory system exhibits optimal stiffness, energy efficiency and chewing forces needed for the food breakdown due to its unique musculoskeletal actuation redundancy. We have proposed a 6PUS-2HKP (6 prismatic-universal-spherical chains, 2 higher kinematic pairs) redundantly actuated parallel robot (RAPR) based on its
[...] Read more.
Human masticatory system exhibits optimal stiffness, energy efficiency and chewing forces needed for the food breakdown due to its unique musculoskeletal actuation redundancy. We have proposed a 6PUS-2HKP (6 prismatic-universal-spherical chains, 2 higher kinematic pairs) redundantly actuated parallel robot (RAPR) based on its musculoskeletal biomechanics. This paper studies the stiffness and optimization of driving force of the bio-inspired redundantly actuated chewing robot. To understand the effect of the point-contact HKP acting on the RAPR performance, the stiffness of the RAPR is estimated based on the derived dimensionally homogeneous Jacobian matrix. In analyzing the influence of the HKP on robot dynamics, the driving forces of six prismatic joints are optimized by adopting the pseudo-inverse optimization method. Numerical results show that the 6PUS-2HKP RAPR has better stiffness performance and more homogenous driving power than its non-redundant 6-PUS counterpart, verifying the benefits that the point-contact HKP brings to the RAPR. Experiments are carried out to measure the temporomandibular joint (TMJ) force and the occlusal force that the robot can generate. The relationship between these two forces in a typical chewing movement is studied. The simulation and experimental results reveal that the existence of TMJs in human masticatory system can provide more homogenous and more efficient chewing force transmission.
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(This article belongs to the Special Issue Design and Control of Advanced Mechatronics Systems)
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3D Measurement of Structured Specular Surfaces Using Stereo Direct Phase Measurement Deflectometry
Machines 2021, 9(8), 170; https://doi.org/10.3390/machines9080170 - 17 Aug 2021
Abstract
With the rapid development of modern manufacturing processes, ultra-precision structured freeform surfaces are being widely explored for components with special surface functioning. Measurement of the 3D surface form of structured specular objects remains a challenge because of the complexity of the surface form.
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With the rapid development of modern manufacturing processes, ultra-precision structured freeform surfaces are being widely explored for components with special surface functioning. Measurement of the 3D surface form of structured specular objects remains a challenge because of the complexity of the surface form. Benefiting from a high dynamic range and large measuring area, phase measurement deflectometry (PMD) exhibits great potential in the inspection of the specular surfaces. However, the PMD is insensitive to object height, which leads to the PMD only being used for smooth specular surface measurement. Direct phase measurement deflectometry (DPMD) has been introduced to measure structured specular surfaces, but the surface form measurement resolution and accuracy are limited. This paper presents a method named stereo-DPMD for measuring structured specular objects by introducing a stereo deflectometor into DPMD, so that it combines the advantages of slope integration of the stereo deflectometry and discontinuous height measurement from DPMD. The measured object is separated into individual continuous regions, so the surface form of each region can be recovered precisely by slope integration. Then, the relative positions between different regions are evaluated by DPMD system to reconstruct the final 3D shape of the object. Experimental results show that the structured specular surfaces can be measured accurately by the proposed stereo-DPMD method.
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(This article belongs to the Special Issue Precision Measurement and Machines)
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Open AccessArticle
Effects of Different Hard Finishing Processes on Gear Excitation
Machines 2021, 9(8), 169; https://doi.org/10.3390/machines9080169 - 16 Aug 2021
Abstract
Gearboxes are essential in mechanical drive trains for power transmission. A low noise emission and thus an optimized excitation behavior is a substantial design objective for many applications in terms of comfort and operational safety. There exist numerous processes for manufacturing gears, which
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Gearboxes are essential in mechanical drive trains for power transmission. A low noise emission and thus an optimized excitation behavior is a substantial design objective for many applications in terms of comfort and operational safety. There exist numerous processes for manufacturing gears, which all show different properties in relation to the process variables and, therefore, differences in the resulting accuracy and quality of the gear flank. In this paper, the influence of three different manufacturing processes for hard finishing—continuous generating grinding, polish grinding and gear skiving—on the surface structure of gear flanks and the excitation behavior is investigated experimentally and analyzed by the application force level. A tactile scanning of the gear flanks determines the flank surface structure and the deviations from the desired geometry. A torsional acceleration measurement during speed ramp-ups at different load levels is used to analyze the excitation of the gears. The results show only a minor influence of the surface structure on the application force level. The excitation behavior is dominated by the influence of the flank modification and its deviation from the design values.
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(This article belongs to the Special Issue Structural Health Monitoring for Mechanical Systems)
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A Simple Soft Computing Structure for Modeling and Control
by
and
Machines 2021, 9(8), 168; https://doi.org/10.3390/machines9080168 - 14 Aug 2021
Abstract
Using the interpolation/extrapolation skills of the core function of an iterative adaptive controller, a structurally simple single essential layer neural network-based topological structure is suggested with fast and explicit single-step teaching and data-retrieving abilities. Its operation does not assume massive parallelism, therefore it
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Using the interpolation/extrapolation skills of the core function of an iterative adaptive controller, a structurally simple single essential layer neural network-based topological structure is suggested with fast and explicit single-step teaching and data-retrieving abilities. Its operation does not assume massive parallelism, therefore it easily can be simulated by simple sequential program codes not needing sophisticated data synchronization mechanisms. It seems to be advantageous in approximate model-based common, robust, or adaptive controllers that can compensate for the effects of minor modeling imprecisions. In this structure a neuron can be in either a firing or a passive (i.e., producing zero output) state. In firing state its activation function realizes an abstract rotation that maps the desired kinematic data into the space of the necessary control forces. The activation function allows the use of a simple and fast incremental model modification for slowly varying dynamic models. Its operation is exemplified by numerical simulations for a van der Pol oscillator in free motion, and within a Computed Torque type control. To reveal the possibility for efficient model correction, a robust Variable Structure/Sliding Mode Controller is applied, too. The novel structure can be obtained by approximate experimental observations as e.g., the fuzzy models.
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(This article belongs to the Special Issue Modeling, Sensor Fusion and Control Techniques in Applied Robotics)
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Adaptive Data-Driven Control for Linear Time Varying Systems
Machines 2021, 9(8), 167; https://doi.org/10.3390/machines9080167 - 13 Aug 2021
Abstract
In this paper, we propose an adaptive data-driven control approach for linear time varying systems, affected by bounded measurement noise. The plant to be controlled is assumed to be unknown, and no information in regard to its time varying behaviour is exploited. First,
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In this paper, we propose an adaptive data-driven control approach for linear time varying systems, affected by bounded measurement noise. The plant to be controlled is assumed to be unknown, and no information in regard to its time varying behaviour is exploited. First, using set-membership identification techniques, we formulate the controller design problem through a model-matching scheme, i.e., designing a controller such that the closed-loop behaviour matches that of a given reference model. The problem is then reformulated as to derive a controller that corresponds to the minimum variation bounding its parameters. Finally, a convex relaxation approach is proposed to solve the formulated controller design problem by means of linear programming. The effectiveness of the proposed scheme is demonstrated by means of two simulation examples.
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(This article belongs to the Special Issue Design and Control of Advanced Mechatronics Systems)
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Fault Detection and Diagnosis for Plasticizing Process of Single-Base Gun Propellant Using Mutual Information Weighted MPCA under Limited Batch Samples Modelling
Machines 2021, 9(8), 166; https://doi.org/10.3390/machines9080166 - 12 Aug 2021
Abstract
Aiming at the lack of reliable gradual fault detection and abnormal condition alarm and evaluation ability in the plasticizing process of single-base gun propellant, a fault detection and diagnosis method based on normalized mutual information weighted multiway principal component analysis (NMI-WMPCA) under limited
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Aiming at the lack of reliable gradual fault detection and abnormal condition alarm and evaluation ability in the plasticizing process of single-base gun propellant, a fault detection and diagnosis method based on normalized mutual information weighted multiway principal component analysis (NMI-WMPCA) under limited batch samples modelling was proposed. In this method, the differences of coupling correlation among multi-dimensional process variables and the coupling characteristics of linear and nonlinear relationships in the process are considered. NMI-WMPCA utilizes the generalization ability of a multi-model to establish an accurate fault detection model in limited batch samples, and adopts fault diagnosis methods based on a multi-model SPE statistic contribution plot to identify the fault source. The experimental results demonstrate that the proposed method is effective, which can realize the rapid detection and diagnosis of multiple faults in the plasticizing process.
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(This article belongs to the Section Industrial Systems)
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Open AccessArticle
The Development of an Automated Multi-Spit Lamb Rotisserie Machine for Improved Productivity
Machines 2021, 9(8), 165; https://doi.org/10.3390/machines9080165 - 11 Aug 2021
Abstract
Innovations in food manufacturing support the agenda for sustainable development goal 9 (SDG9) on industry, innovation and infrastructure. Pursuant to this goal, this study aims to develop an automated multi-spit lamb rotisserie machine that potentially improves the lamb-roasting productivity for small and medium
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Innovations in food manufacturing support the agenda for sustainable development goal 9 (SDG9) on industry, innovation and infrastructure. Pursuant to this goal, this study aims to develop an automated multi-spit lamb rotisserie machine that potentially improves the lamb-roasting productivity for small and medium enterprises (SMEs). The conceptualisation involved patents, scholarly literature and product reviews of lamb-roasting devices. The design and analysis are performed using Autodesk Inventor 2019. A scaled-down prototype is developed and tested with (1) roasting output, (2) roasting time and (3) temperature stability tests. The data for test (1) are analysed by comparing the means between control and experimental groups. The data for tests (2) and (3) are analysed using the t-test and Mann–Whitney U test, respectively. Significant differences are observed in tests (1) and (2), with outcomes being in favour of the proposed invention. The prototype cooks 92.27% faster with 700% more meat than a regular lamb roaster. It also cooks at a stable temperature. The cost analysis indicated that this invention could be sold at USD 278 if mass-produced. The design is structurally simple, inexpensive and easy to manufacture, allowing SMEs that rely on traditional spit-based machines to enhance their ability in producing roast lamb.
Full article
(This article belongs to the Collection Machines, Mechanisms and Robots: Theory and Applications)
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Open AccessArticle
Behavior of Rotary Ultrasonic Machining of Ceramic Materials at a Wide Range of Cutting Speeds
by
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Machines 2021, 9(8), 164; https://doi.org/10.3390/machines9080164 - 11 Aug 2021
Abstract
The paper deals with the behavior of the rotary ultrasonic machining process at different cutting speeds of ceramic materials. This process is relatively new; therefore, there are gaps in information about its behavior at near-critical parameters. We adjusted cutting speeds 10 times lower
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The paper deals with the behavior of the rotary ultrasonic machining process at different cutting speeds of ceramic materials. This process is relatively new; therefore, there are gaps in information about its behavior at near-critical parameters. We adjusted cutting speeds 10 times lower and 10 times higher than the recommended one. The observed parameters were machine load, tool wear, and surface roughness. Alumina and zirconia ceramics were used as materials. The results will help with the optimization of the cutting parameters of the rotary ultrasonic machining process.
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(This article belongs to the Section Advanced Manufacturing)
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Study on the Importance of a Slicer Selection for the 3D Printing Process Parameters via the Investigation of G-Code Readings
by
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Machines 2021, 9(8), 163; https://doi.org/10.3390/machines9080163 - 11 Aug 2021
Abstract
The work deals with the investigation of the variation of the selected 3D printing process properties that originate from the choice of a slicer. Specifically, the main aim of the present study was to assess the induced changes of the kinematic and geometric
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The work deals with the investigation of the variation of the selected 3D printing process properties that originate from the choice of a slicer. Specifically, the main aim of the present study was to assess the induced changes of the kinematic and geometric properties considered by the slicer for the printing process making use of the G-code readings. The paper provides adequate definitions and formulas required to characterize the slicer’s configuration. Next, the selected cases of the process parameters’ changes were studied, primarily taking into account varying layer height and infill. The authors performed a detailed analysis regarding the geometric implications at the mesoscale due to the slicer’s settings. Appropriate modifications of the slicer’s properties were also proposed and verified, making it possible to match the geometric and kinematic characteristics of the printed part.
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(This article belongs to the Special Issue Advances and Trends in Non-conventional, Abrasive and Precision Machining 2021)
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