Machines

In order to improve vehicle control safety in intelligent and connected environments, a fuzzy drive control strategy is proposed. Through the fusion of vehicle driving data, an early warning level model was established, and the fuzzy control method was used to obtain the appropriate torque command under the vehicle condition; torque optimization processing was performed according to the different corresponding vehicle following characteristics. The control strategy was tested and verified on an established platform. Based on the experimental results, compared with the traditional drive strategy in one-way front and rear following scenarios, the vehicle avoided excessive opening and closing of the accelerator pedal when the distance between vehicles was close, maintained the correct distance in the following situation, and had better dynamic response when the distance between vehicles was large, indicating that the proposed drive strategy had a better real-time and security performance. Full article

Measurement noise, parametric uncertainties, and external disturbances broadly exist in electro-hydraulic servo systems, which terribly deteriorate the system control performance. To figure out this problem, a novel finite-time output feedback controller with parameter adaptation is proposed for electro-hydraulic servo systems in this paper. First, to avoid using noise-polluted signals and attain active disturbance compensation, a finite-time state observer is adopted to estimate unknown system states and disturbances, which attenuates the impact of measurement noise and external disturbances on tracking performance. Second, by adopting a parameter adaptive law, the parametric uncertainties in the electro-hydraulic servo system can be much lessened, which is beneficial to averting the high-gain feedback in practice. Then, integrating the backstepping framework and the super-twisting sliding mode technique, a synthesized output feedback controller is constructed to achieve high-accuracy tracking performance for electro-hydraulic servo systems. Lyapunov stability analysis demonstrates that the proposed control scheme can acquire finite-time stability. The excellent tracking performance of the designed control law is verified by comparative simulation results. Full article

In this paper, a parameter estimation method is proposed to predict the simultaneous joint dynamics of a surgical robotic arm that is tracking trajectories. It mainly deals with the design, modeling, prototyping and control of a serial robotic arm for robot-assisted urological surgery. This robot is composed of many joints mounted in series with the surgical tool end performing both a translational workspace and a cone-shaped orientation workspace. The joints dynamics is obtained by trajectory planning of the tool end in the virtual prototype modeling environment. The motor drive system is parameterized for design, and its comprehensive performance in motion is predicted accurately. The heterogeneous master–slave control system was built, and the performances of the master–slave prototype were experimentally evaluated by measuring the positioning error of the virtual fixed point and the surgical tool end along the planned trajectory. Full article

Associated vibrations in mechanical power transmission elements such as gears and bearings significantly contribute to the dynamic behavior of the system to which they belong. Most research in this field describes measurements and signal processing methods to determine the effect of some design modifications. However, the number of investigations that try to solve the problem from the design stage is much smaller. The following study presents a review of the trends in the analysis of vibrations of power transmission elements and their relationship to the use of systematic design methodologies in the principal power transmission elements. A revision is shown in design considerations to prevent mechanical vibrations or reduce them to acceptable levels. The effects in terms of improvement in reducing vibrations of the most important works that have taken into account the vibrations in design stages are shown. The results show the importance of considering the mechanical vibrations in the design of power transmission elements. Moreover, the analysis of the state of the art shows the areas to be investigated that contemplate the development or application of formal design methodologies that take into account mechanical vibrations. Full article

The paper presents a coupled machine learning and pattern recognition algorithm to enable early-stage fatigue damage detection in aerospace-grade aluminum alloys. U- and V-notched Al7075-T6 specimens are instrumented with a pair of ultrasonic sensors and, thereafter, tested on an MTS apparatus integrated with a confocal microscope and a digital microscope. The confocal microscope is focused on the notch root of the specimens, whereas the digital microscope is focused on the side of the notch. Two features, viz., the crack opening displacement (COD) and the crack length, are extracted during the tests in addition to the ultrasonic signal data. These signal data are analyzed using a machine learning framework that is built upon a symbolic time-series algorithm. This framework is interrogated for crack detection in the crack coalescence (CC) regime defined by COD of ~3 μm and detected through the confocal microscope. Additionally, the framework is probed in the crack propagation (CP) regime characterized by a crack length of ~0.2 mm and detected via the digital microscope. For the CC regime, training accuracies of 79.82% and 81.94% are achieved, whereas testing accuracies of 68.18% and 74.12% are observed for the U- and V-notched specimens, respectively. For the CP regime, overall training accuracies of 88.3% and 91.85% are observed, and accordingly, testing accuracies of 81.94% and 85.62% are obtained for the U- and V-notched specimens, respectively. The results show that a combined machine learning and pattern recognition algorithm enables robust and reliable fatigue damage detection in aerospace structural components. Full article

While increasing digitalization enables multiple advantages for a reliable operation of technical systems, a remaining challenge in the context of condition monitoring is seen in suitable consideration of uncertainties affecting the monitored system. Therefore, a suitable prognostic approach to predict the remaining useful lifetime of complex technical systems is required. To handle different kinds of uncertainties, a novel Multi-Model-Particle Filtering-based prognostic approach is developed and evaluated by the use case of rubber-metal-elements. These elements are maintained preventively due to the strong influence of uncertainties on their behavior. In this paper, two measurement quantities are compared concerning their ability to establish a prediction of the remaining useful lifetime of the monitored elements and the influence of present uncertainties. Based on three performance indices, the results are evaluated. A comparison with predictions of a classical Particle Filter underlines the superiority of the developed Multi-Model-Particle Filter. Finally, the value of the developed method for enabling condition monitoring of technical systems related to uncertainties is given exemplary by a comparison between the preventive and the predictive maintenance strategy for the use case. Full article

This paper describes the design of a prosthetic hand for wrist amputations. The mechanism considers the use of three actuators: one each for the movement of the little finger, annular finger, and middle finger. The second actuator controls the index finger, and the third controls the thumb. The prototype is considered relevant as it is able to move the distal phalanx in all fingers; the little, annular, and middle fingers are able to adapt to the shape of the object being gripped (adaptive grip). The sequence of movements achieved with the thumb emulate the opposition/reposition and flexion/extension movements, commanded by a single actuator. The proposed design was built by additive manufacturing and effortlessly achieves a large number of grips. Additionally, the prosthesis could perform specific movements, such as holding a needle, although this grip demands higher precision in the control of the fingers. Due to the manufacturing method, the prosthesis weighs only 200 g, increasing to 450 g when the actuators are included, therefore weighing less than an average adult’s hand. Full article

In a traditional system paradigm, an enterprise reference model provides the guide for practitioners to select manufacturing elements, configure elements into a manufacturing system, and model system options for evaluation and comparison of system solutions against given performance metrics. However, a smart manufacturing system aims to reconfigure different systems in achieving high-level smartness in its system lifecycle; moreover, each smart system is customized in terms of the constraints of manufacturing resources and the prioritized performance metrics to achieve system smartness. Few works were found on the development of systematic methodologies for the design of smart manufacturing systems. The novel contributions of the presented work are at two aspects: (1) unified definitions of digital functional elements and manufacturing systems have been proposed; they are generalized to have all digitized characteristics and they are customizable to any manufacturing system with specified manufacturing resources and goals of smartness and (2) a systematic design methodology has been proposed; it can serve as the guide for designs of smart manufacturing systems in specified applications. The presented work consists of two separated parts. In the first part of paper, a simplified definition of smart manufacturing (SM) is proposed to unify the diversified expectations and a newly developed concept digital triad (DT-II) is adopted to define a generic reference model to represent essential features of smart manufacturing systems. In the second part of the paper, the axiomatic design theory (ADT) is adopted and expanded as the generic design methodology for design, analysis, and assessment of smart manufacturing systems. Three case studies are reviewed to illustrate the applications of the proposed methodology, and the future research directions towards smart manufacturing are discussed as a summary in the second part. Full article

Rapidly developed information technologies (IT) have continuously empowered manufacturing systems and accelerated the evolution of manufacturing system paradigms, and smart manufacturing (SM) has become one of the most promising paradigms. The study of SM has attracted a great deal of attention for researchers in academia and practitioners in industry. However, an obvious fact is that people with different backgrounds have different expectations for SM, and this has led to high diversity, ambiguity, and inconsistency in terms of definitions, reference models, performance matrices, and system design methodologies. It has been found that the state of the art SM research is limited in two aspects: (1) the highly diversified understandings of SM may lead to overlapped, missed, and non-systematic research efforts in advancing the theory and methodologies in the field of SM; (2) few works have been found that focus on the development of generic design methodologies for smart manufacturing systems from the practice perspective. The novelty of this paper consists of two main aspects which are reported in two parts respectively. In the first part, a simplified definition of SM is proposed to unify the existing diversified expectations, and a newly developed concept named digital triad (DT-II) is adopted to define a reference model for SM. The common features of smart manufacturing systems in various applications are identified as functional requirements (FRs) in systems design. To model a system that is capable of reconfiguring itself to adapt to changes, the concept of IoDTT is proposed as a reference model for smart manufacturing systems. In the second part, these two concepts are used to formulate a system design problem, and a generic methodology, based on axiomatic design theory (ADT), is proposed for the design of smart manufacturing systems. Full article

In order to better control the vibration of the rotor system so as to improve the stability and safety of the rotor, a novel vibration control solution is needed. In this paper, the multi-objective optimization problem is used for designing a novel integral squeeze film bearing damper (ISFBD). The method attempts to reduce the stiffness and stress convergence of ISFBD, which can greatly decrease the transmitted force of the rotor system and better use the damping effect to dissipate the vibration energy. The finite element model of ISFBD is established to analyze the stiffness and stress, and the correctness of the calculation is verified by setting up a stiffness test platform. The sensitivity of different structural parameters of stiffness and stress is analyzed by ANOVA. Meanwhile, the non-dominated sorting genetic algorithm (NSGA-II) and grey correlation analysis (GRA) algorithms are coupled for multi-objective optimization of stiffness and stress. The results indicate that optimized ISFBD can distribute 26.6% of the rotor system’s energy and reduce 59.3% of the transmitted force at the bearing location. It is also proved that the optimization strategy is effective, which can provide a useful method for ISFBD design in practical applications. Full article

This paper develops a decoupled multi-loop control for a two-wheeled inverted pendulum (TWIP) robot that can assist user’s with walking. The TWIP robot is equipped with two wheels driven by electrical motors. We derive the system’s transfer function and design a robust loop-shaping controller to balance the system. The simulation and experimental results show that the TWIP system can be balanced but might experience velocity drifts because its balancing point is affected by model variations and disturbances. Therefore, we propose a multi-loop control layout consisting of a velocity loop and a position loop for the TWIP robot. The velocity loop can adjust the balancing point in real-time and regulate the forward velocity, while the position loop can achieve position tracking. For walking assistance, we design a decoupled control structure that transfers the linear and rotational motions of the robot to the commands of two parallel motors. We implement the designed controllers for simulation and experiments and show that the TWIP system employing the proposed decoupled multi-loop control can provide satisfactory responses when assisting with walking. Full article

The difficulty of adding external excitation and the asynchronous data collection from the industrial robot operation limited the online parameter identification of industrial robots. In this regard, this study proposes an identification method that only uses the amplitude of the frequency response function (FRF) of the system to identify robot joint torsional stiffness and dynamic parameters. The error criterion function shows that this method is feasible and comparable to applying the complete frequency response for identification. The Levenberg–Marquardt (L-M) algorithm is used to find the global optimal value of the error criterion function. In addition, an operational excitation method is proposed to excite the system. The speed profile is set as a triangle wave to excite the system using rectangular wave electromagnetic torques. The simulation results show that using the amplitude of the FRF to identify parameters applies to asynchronous data. The experiments on a single-degree-of-freedom articulated arm test bench show that the motion excitation method is effective, and both stiffness and inertia are identifiable. Full article

Three-phase induction motors (IMs) are the main workhorse in industry due to their many advantages as compared to other types of industrial motors. However, the efficiency and lifetime of IMs can be considerably affected by some operating conditions, in particular those related to unbalanced supply voltages (USV), which is quite a common condition in industrial plants. Therefore, early detection and a precise severity estimation of the USV for all working conditions can prevent major breakdowns and increase reliability and safety of industrial facilities. This paper proposes a reliable method allowing for a precise and online detection of the USV condition, by monitoring a pertinent indicator calculated using the voltage symmetrical components. The effectiveness of the proposed method is validated experimentally for several different working conditions, and a comparison with other indicators available in the literature is also performed. Full article

Trajectory tracking is a common application method for manipulators. However, the tracking performance is hard to improve if the manipulators contain flexible joints and mismatched uncertainty, especially when the trajectory is nonholonomic. On the basis of the Udwadia–Kalaba Fundamental Equation (UKFE), the prescribed position or velocity trajectories are creatively transformed into second-order standard differential form. The constraint force generated by the trajectories is obtained in closed form with the help of UKFE. Then, a high-order fractional type robust control with an embedded fictitious signal is proposed to achieve practical stability of the system, even if the mismatched uncertainty exists. Only the bound of uncertainty is indispensable, rather than the exact information. A leakage type of adaptive law is proposed to estimate such bound. By introducing a dead-zone, the control will be simplified when the specific parameter enters a certain area. Validity of the proposed controller is verified by numerical simulation with two-link flexible joint manipulator. Full article

Stability of the rotor motion is the precondition for the reliable operation of magnetically levitated slice motors (MLSMs). However, with gyroscopic effect and non-collocated structure existing simultaneously, its stability analysis faces a tremendous challenge, because the torsional motions couple with the radial translational ones, making MLSM a multiple-input and multiple-output (MIMO) system with high order. Therefore, in this paper, we first establish a novel MIMO rotor dynamics closed-loop model and further convert it into an equivalent single-input and single-out (SISO) feedback control system by constructing complex variables, meanwhile reducing the system order by half. Beneficial from the equivalence between the MIMO and SISO systems, the sufficient and necessary conditions of the absolute stability of MLSM are derived by the extended inverse Nyquist stability criterion in the complex domain. Additionally, the effectiveness of the proposed modelling and stability analysis method is evaluated by simulation and experimental results. Thus, apart from PID parameters, this paper demonstrates that the stability of MLSM is also affected by the coupling of gyroscopic effect and non-collocated structure, which should serve as an essential guideline for system regulation of MLSM. Full article

In additive manufacturing (AM), especially for advanced powder fusion machines, it is of high importance to develop an in situ inspection system to monitor the printed surface and pre-print powder bed as the build cycle proceeds. Consequently, high resolution, high precision and fast detection measurement systems need to be investigated, as such optically based measurement systems can provide feedback for manufacturing process optimisation. Fringe projection technology has a great advantage in the measurement of topography in such environments. The implementation of a fringe projection system requires that the system is pre-calibrated in order to obtain high measurement resolution and repeatability. This paper presents a simple calibration method for an AM-based in situ fringe projection system using a phase-depth calibration model. If a calibration plate with certificated marks is used, however, the texture of the plate will affect the measured phase accuracy. A simple calibration method to reduce the calibration plate texture effect in the process of calibration is outlined. Experimental results show that the proposed method can eliminated these effects and improve measurement resolution and repeatability. The proposed in situ/in process inspection technique has been implemented within a commercial electron beam powder bed fusion additive manufacturing machine (EBAM), to demonstrate the capability for effective feedback during the manufacturing process. Full article

Bearings prevent damage caused by frictional forces between parts supporting the rotation and they keep rotating shafts in their correct position. However, the continuity of work under harsh conditions leads to inevitable bearing failure. Thus, methods for bearing fault diagnosis (FD) that can predict and categorize fault type, as well as the level of degradation, are increasingly necessary for factories. Owing to the advent of deep neural networks, especially convolutional neural networks (CNNs), intelligent FD methods have achieved significantly higher performance in terms of accuracy. However, in addition to accuracy, the efficiency issue still needs to be weathered in complicated diagnosis scenarios to adapt to real industrial environments. Here, we introduce a method based on multi-output classification, which utilizes the correlated features extracted for bearing compound fault type classification and crack-size classification to serve both aims. Additionally, the synergy of a time–frequency signal processing method and the proposed two-dimensional CNN helped the method perform well under the condition of variable rotational speeds. Monitoring signals of acoustic emission also had advantages for incipient FD. The experimental results indicated that utilizing correlated features in multi-output classification improved both the accuracy and efficiency of multi-task diagnosis compared to conventional CNN-based multiclass classification. Full article

In order to carry out various detections of system indicators during the research and development phase of infrared guided missiles, the article first analyzes several main design schemes of the infrared guided missile detection simulator and finds that it has the disadvantages of difficult processing technology and low detection accuracy. The overall structure of the detection device was designed, including the design of the rotation and swing mechanism, lens mechanism, optical system and control system. The optical system error analysis is performed on the infrared guided missile detection simulator. The position of the receiving light source is obtained by analyzing the mechanism characteristics of the detection simulator and the kinematics model of the device. The phase difference analysis of the eccentricity and tilt system is obtained. The image quality was evaluated by the optical transfer function (MTF), and the system error was found to meet the requirements of imaging quality. The experiments show that the simulation of 1.7~4.9 um medium wave infrared dynamic target signals provides an accurate and reasonable experimental environment for the missile and the verification of the light source target and meets the experimental requirements. Full article

The continuous evolution of modern technology has led to the creation of increasingly complex and advanced systems. This has been also reflected in the technology of Unmanned Aerial Vehicles (UAVs), where the growing demand for more reliable performance necessitates the development of sophisticated techniques that provide fault diagnosis and fault tolerance in a timely and accurate manner. Typically, a UAV consists of three types of subsystems: actuators, main structure and sensors. Therefore, a fault-monitoring system must be specifically designed to supervise and debug each of these subsystems, so that any faults can be addressed before they lead to disastrous consequences. In this survey article, we provide a detailed overview of recent advances and studies regarding fault diagnosis, Fault-Tolerant Control (FTC) and anomaly detection for UAVs. Concerning fault diagnosis, our interest is mainly focused on sensors and actuators, as these subsystems are mostly prone to faults, while their healthy operation usually ensures the smooth and reliable performance of the aerial vehicle. Full article