Steel is a basic material, and vision-based defect recognition is important for quality. Recently, deep learning, especially convolutional neural network (CNN), has become a research hotspot. However, steel defects have poor class separation, which is similar to the background, and different defects show similar textures. This causes some defects unrecognizable and influences production greatly. Thus

The mobile robot is the essential equipment for automated logistics in the intelligent workshop, but the literature on shop scheduling rarely considers transport resources. This paper studies the integrated scheduling of machines and mobile robots, which can facilitate the efficiency of production systems. For the job shop scheduling problem with mobile robots (JSPMR), the existing mathematical models

Sharp abrasion of the abrasive belt always causes surface quality to deteriorate in the robotic grinding of thin-walled blades, which has stymied the further advancement of robot machining technology. A novel belt wear prediction approach based on the acoustic emissions (AE) signal is presented in this study to monitor belt wear conditions to achieve the expected machining result. A time-varying model

This paper presents a novel optimization process for the proposed general asymmetric S-curve (AS-curve) profile to achieve fast movement and low residual vibration. The general AS-curve profile, which is the superset of traditional symmetric S-curve and prior asymmetric S-curve profiles, enables independent manipulation of accelerations and jerks at the starting and arrival phases. To minimize the

Online monitoring and health assessment of rotating bladed disks have always been a hot topic in the engineering field. However, the existing monitoring methods cannot fully perceive the vibration state of the bladed disk. Therefore, a dynamic response field reconstruction method based on blade tip timing (BTT) data is proposed to evaluate the global vibration state of the rotating bladed disk online

Unmanned air vehicles are intrinsically non-linear, unstable, uncertain, and prone to a variety of faults, most commonly the motor faults. The main objective of this paper is to develop a fault-tolerant control algorithm for the quadrotors with the motor faults. Accordingly, a novel adaptive modified incremental nonlinear dynamic inversion (MINDI) control is proposed to stabilize and control the quad-rotor

Maglev trains are strongly nonlinear, open-loop unstable, and flexible track systems. Vehicle-guideway self-excited vibration, which occurs mainly due to the deflection of the flexible guideway, may take place when a train is levitated on the guideway, even if the train is stationary. In this research, maglev vehicle-guideway coupling vibration is studied by employing the Hopf bifurcation criterion

Materials with electroprogrammable stiffness and adhesion can enhance the performance of robotic systems, but achieving large changes in stiffness and adhesive forces in real time is an ongoing challenge. Electroadhesive clutches can rapidly adhere high stiffness elements, although their low force capacities and high activation voltages have limited their applications. A major challenge in realizing

Vibration data from physical systems, such as civil structures and machinery, often carries important information about the dynamic characteristics, but streaming acquisition of higher-frequency vibration often accrue large volumes of data, resulting in data transmission and storage challenges. Compressive sensing (CS) is a relatively newly-developed technique for efficient data representation, capable

Tool breakage occurs randomly during machining operations, which induces more severe impacts on the quality of components compared to progressive tool wear. It is widely acknowledged that the unpredictable changes in cutting conditions will cause fluctuations in the signal amplitude and thus generate false alarms. This study introduced a novel method for tool breakage monitoring based on dimensionless

Establishing accurate dynamic models in a form that is suitable for integration with model-based control methods, is of great significance for further improving the dynamic motion control precision of ball-screw drives. However, due to the nonlinear time-varying factors such as position-dependent dynamics and nonlinear friction disturbance, it is difficult to model the dynamic characteristics of ball-screw

Automatic joint motion planning is very important in robotic wheel hub polishing systems. Higher flexibility is achieved based on the joint configuration with multiple solutions, which means that the robot has kinematic redundancy for machining tasks. Redundant joints can be used to optimize the motion of the robot, but less research has been done on multi-dimensional redundant optimization. In this

Automatic and fast weld type classification, tacked spot recognition and weld ROI (region of interest) determination are key links for intelligent welding robot, because they directly affect the seam tracking and welding parameters such as current, voltage and torch inclination. Nevertheless, there are few studies on weld type classification, tacked spot recognition, and weld ROI determination. Considering

Multichannel signals collected by multiple sensors contain richer condition information of equipment than single-channel signals. However, such issues as simultaneous denoising, adaptive decomposition and synchronous extraction are still challenging for multichannel signals, which are beneficial to accurate fault diagnosis. Thus, a useful multichannel feature synchronous extraction tool is proposed

Markers with high-contrast patterns are commonly used to improve the accuracy of image intensity-based motion estimation techniques. It has been proven that the phase, which can be extracted by using quadrature pair filters, is more robust to light condition changes than the intensity of the image. However, the marker design for utilizing and stabilizing the phases using phase-based motion estimation

Extracting governing physics from data is a key challenge in many areas of science and technology. The existing techniques for equation discovery are mostly applicable to deterministic systems and require both input and state measurements. We here propose a novel data-driven framework for discovering nonlinear stochastic dynamical systems with Gaussian white noise. The proposed framework blends concepts

Dynamic health monitoring (DHM) and performance degradation assessment (PDA) is critical for mechanical bearings throughout their long in-service life. For this issue, it is currently rare to find a framework with interpretable and automatic approaches developed from pure signal processing techniques and statistical theories. Therefore, an integrated framework via key-spectrum entropy and statistical

A new hierarchical Bayesian framework (HBM) is proposed for identification of Gaussian processes or fields, which are usually used for simulating uncertainty in temporal variability of loads or spatial variability of material properties. An improved orthogonal series expansion (iOSE) is embedded into the proposed framework by simulating the Gaussian process or field through correlated Gaussian variables

The commissioning of Computerized Numerical Control Machine Tools (CNCMTs) is particularly important and the commissioning quality directly affects its product processing. However, traditional commissioning methods are not suitable for complex and changeable machining conditions during operation, and the derived commissioning results have limited effectiveness. Therefore, this paper proposes a digital

Robotic leg prostheses promise to improve the mobility and quality of life of millions of individuals with lower-limb amputations by imitating the biomechanics of the missing biological leg. Unfortunately, existing powered prostheses are much heavier and bigger and have shorter battery life than conventional passive prostheses, severely limiting their clinical viability and utility in the daily life

Tiny “gnat robots,” weighing just a few milligrams, were first conjectured in the 1980s. How to stabilize one if it were to hover like a small insect has not been answered. Challenges include the requirement that sensors be both low mass and high bandwidth and that silicon-micromachined rate gyroscopes are too heavy. The smallest robot to perform controlled hovering uses a sensor suite weighing hundreds

Abstract not available

Nowadays, most studies on the dynamic properties of annular gaps focus only on the force characteristics due to translational motions, while the tilt and moment coefficients are less well studied. Therefore, there is hardly any reliable experimental data for the additional coefficients that can be used for validation purpose. To improve this, a test rig first presented by Kuhr (2022); Kuhr et al. (2022a)

Unmanned Aerial Vehicle (UAV)-based autonomous damage inspection has become a promising technique to replace certain human-performed inspections due to both safety and cost considerations. While current UAV-based damage inspection methods have been successful in minimizing the length of the flying path considering potential defect locations, the impact of flying path on the quality of structural health

In this study, we propose an efficient mathematical equation to describe incompressible fluid flow-coupled crystallization. By using the L2-gradient flow, the evolutional equation is derived from an energy functional and a nonlocal Lagrange multiplier is introduced to preserve the total mass. Various physical phenomena of colloidal crystals can be modeled using a generalized nonlinearity and the fluid

Dynamic mode decomposition (DMD) has emerged as a popular data-driven modeling approach to identifying spatio-temporal coherent structures in dynamical systems, owing to its strong relation with the Koopman operator. For dynamical systems with external forcing, the identified model should not only be suitable for a specific forcing function but should generally approximate the input–output behavior

This paper proposed a method to control the circumferential motion of the constraint boundary of the flexible inverted pendulum to achieve its fast stability. Firstly, the dynamic equation of the system is obtained by the beam theory. The displacement of the flexible inverted pendulum is used as the input to explore the relationship between the output of the constrained boundary and the displacement

Triboelectric-nano-generator (TENG) is able to produce a very small current and a large voltage compared to piezoelectric or electromagnetic generators. The large voltages from the TENGs are suitable for operating MEMS devices without external AC or DC generators. Producing micro-sized TENG using MEMS fabrication process enables integration of them with MEMS sensors and actuators. This combination

The hydropower generation system is a typical complex nonlinear system with hybrid state responses. The interaction between the state responses of the system is affected closely by the coupling of hydraulic, mechanical, and electromagnetic factors and the frequent changes in working conditions during operation. However, the precise roles of the interaction relationship are unknown. Here, we show that