One of the core challenges of intelligent fault diagnosis is that the diagnosis model requires numerous labeled training datasets to achieve satisfactory performance. Generating training data using a virtual model is a potential solution for addressing such a problem, and the construction of a high-fidelity virtual model is fundamental and critical for data generation. In this study, a digital twin-assisted dynamic model updating method for fault diagnosis is thus proposed to improve the fidelity and reliability of a virtual model, which can enhance the generated data quality. First, a virtual model is established to mirror the vibration response of a physical entity using a dynamic modeling method. Second, the modeling method is validated through a frequency analysis of the generated signal. Then, based on the signal similarity indicator, a physical–virtual signal interaction method is proposed to dynamically update the virtual model in which parameter sensitivity analysis, surrogate technique, and optimization algorithm are applied to increase the efficiency during the model updating. Finally, the proposed method is successfully applied to the dynamic model updating of a single-stage helical gearbox; the virtual data generated by this model can be used for gear fault diagnosis.

This paper proposes a novel continuous footholds optimization method for legged robots to expand their walking ability on complex terrains. The algorithm can efficiently run onboard and online by using terrain perception information to protect the robot against slipping or tripping on the edge of obstacles, and to improve its stability and safety when walking on complex terrain. By relying on the depth camera installed on the robot and obtaining the terrain heightmap, the algorithm converts the discrete grid heightmap into a continuous costmap. Then, it constructs an optimization function combined with the robot’s state information to select the next footholds and generate the motion trajectory to control the robot’s locomotion. Compared with most existing footholds selection algorithms that rely on discrete enumeration search, as far as we know, the proposed algorithm is the first to use a continuous optimization method. We successfully implemented the algorithm on a hexapod robot, and verified its feasibility in a walking experiment on a complex terrain.

Earth rover is a class of emerging wheeled-leg robots for nature exploration. At present, few methods for these robots’ leg design utilize a side-mounted spatial parallel mechanism. Thus, this paper presents a complete design process of a novel 5-degree-of-freedom (5-DOF) hybrid leg mechanism for our quadruped earth rover BJTUBOT. First, a general approach is proposed for constructing the novel leg mechanism. Subsequently, by evaluating the basic locomotion task (LT) of the rover based on screw theory, we determine the desired motion characteristic of the side-mounted leg and carry out its two feasible configurations. With regard to the synthesis method of the parallel mechanism, a family of concise hybrid leg mechanisms using the 6-DOF limbs and an L_1F1C limb (which can provide a constraint force and a couple) is designed. In verifying the motion characteristics of this kind of leg, we select a typical (3-UPRU&RRRR)&R mechanism and then analyze its kinematic model, singularities, velocity mapping, workspace, dexterity, statics, and kinetostatic performance. Furthermore, the virtual quadruped rover equipped with this innovative leg mechanism is built. Various basic and specific LTs of the rover are demonstrated by simulation, which indicates that the flexibility of the legs can help the rover achieve multitasking.

Next-generation optoelectronics should possess lightweight and flexible characteristics, thus conforming to various types of surfaces or human skins for portable and wearable applications. Flexible photodetectors as fundamental devices have been receiving increasing attention owing to their potential applications in artificial intelligence, aerospace industry, and wise information technology of 120, among which perovskite is a promising candidate as the light-harvesting material for its outstanding optical and electrical properties, remarkable mechanical flexibility, low-cost and low-temperature processing methods. To date, most of the reports have demonstrated the fabrication methods of the perovskite materials, materials engineering, applications in solar cells, light-emitting diodes, lasers, and photodetectors, strategies for device performance enhancement, few can be seen with a focus on the processing strategies of perovskite-based flexible photodetectors, which we will give a comprehensive summary, herein. To begin with, a brief introduction to the fabrication methods of perovskite (solution and vapor-based methods), device configurations (photovoltaic, photoconductor, and phototransistor), and performance parameters of the perovskite-based photodetectors are first arranged. Emphatically, processing strategies for photodetectors are presented following, including flexible substrates (i.e., polymer, carbon cloth, fiber, paper, etc.), soft electrodes (i.e., metal-based conductive networks, carbon-based conductive materials, and two-dimensional (2D) conductive materials, etc.), conformal encapsulation (single-layer and multilayer stacked encapsulation), low-dimensional perovskites (0D, 1D, and 2D nanostructures), and elaborate device structures. Typical applications of perovskite-based flexible photodetectors such as optical communication, image sensing, and health monitoring are further exhibited to learn the flexible photodetectors on a deeper level. Challenges and future research directions of perovskite-based flexible photodetectors are proposed in the end. The purpose of this review is not only to shed light on the basic design principle of flexible photodetectors, but also to serve as the roadmap for further developments of flexible photodetectors and exploring their applications in the fields of industrial manufacturing, human life, and health care.

Morphing aircraft can adaptively regulate their aerodynamic layout to meet the demands of varying flight conditions, improve their aerodynamic efficiency, and reduce their energy consumption. The design and fabrication of high-performance, lightweight, and intelligent morphing structures have become a hot topic in advanced aircraft design. This paper discusses morphing aircraft development history, structural characteristics, existing applications, and future prospects. First, some conventional mechanical morphing aircraft are examined with focus on their morphing modes, mechanisms, advantages, and disadvantages. Second, the novel applications of several technologies for morphing unmanned aerial vehicles, including additive manufacturing for fabricating complex morphing structures, lattice technology for reducing structural weight, and multi-mode morphing combined with flexible skins and foldable structures, are summarized and categorized. Moreover, in consideration of the further development of active morphing aircraft, the paper reviews morphing structures driven by smart material actuators, such as shape memory alloy and macro-fiber composites, and analyzes their advantages and limitations. Third, the paper discusses multiple challenges, including flexible structures, flexible skins, and control systems, in the design of future morphing aircraft. Lastly, the development and application of morphing structures in the aerospace field are discussed to provide a reference for future research and engineering applications.

To examine the environmental characteristics of the microgravity force and the weathered layer on an asteroid surface, a symmetric wheel brush asteroid sampler is proposed for the collection of particles on the asteroid surface. To study the influence of the wheel brush rotation speed on the sampling efficiency and the driving torque required for the wheel brush, the contact dynamics model between particles and sampling wheel brushes is established and a simulation and experimental verification of the sampling process are conducted. The parameter calibration of the sampled particles is studied first, and the calibrated particle parameters are used in the numerical simulation of the sampling process. The sampling results and the particle stream curves are obtained for the working conditions of different rotation speeds, and the effects of different parameter settings on the sampling efficiency are analyzed. In addition, a set of rotating symmetrical sampling wheel brush devices is built for the ground test, and the dynamic torque sensor is used to test the torque change of the wheel brush during the sampling process. The relationship between the speed of the wheel brush and the driving torque of the wheel brush motor is determined by comparing the simulation results with the test results. Results indicate that when the rotating speed of the wheel brush is faster, the sampling efficiency is higher, and the driving torque required for the sampling wheel brush is greater. Moreover, a numerical simulation analysis of the sampling process of the wheel brush sampler in a microgravity environment is conducted to determine the optimal speed condition, and the brushing test of the wheel brush sampler in the microgravity environment is verified with the drop tower method. This research proposes the structural optimization design and motor selection of a wheel brush asteroid sampler, which provides important reference value and engineering significance.

Energy field-assisted machining technology has the potential to overcome the limitations of machining difficult-to-machine metal materials, such as poor machinability, low cutting efficiency, and high energy consumption. High-speed dry milling has emerged as a typical green processing technology due to its high processing efficiency and avoidance of cutting fluids. However, the lack of necessary cooling and lubrication in high-speed dry milling makes it difficult to meet the continuous milling requirements for difficult-to-machine metal materials. The introduction of advanced energy-field-assisted green processing technology can improve the machinability of such metallic materials and achieve efficient precision manufacturing, making it a focus of academic and industrial research. In this review, the characteristics and limitations of high-speed dry milling of difficult-to-machine metal materials, including titanium alloys, nickel-based alloys, and high-strength steel, are systematically explored. The laser energy field, ultrasonic energy field, and cryogenic minimum quantity lubrication energy fields are introduced. By analyzing the effects of changing the energy field and cutting parameters on tool wear, chip morphology, cutting force, temperature, and surface quality of the workpiece during milling, the superiority of energy-field-assisted milling of difficult-to-machine metal materials is demonstrated. Finally, the shortcomings and technical challenges of energy-field-assisted milling are summarized in detail, providing feasible ideas for realizing multi-energy field collaborative green machining of difficult-to-machine metal materials in the future.

Servo-hydraulic actuators (SHAs) are widely used in mechanical equipment to drive heavy-duty mechanisms. However, their energy efficiency is low, and their motion characteristics are inevitably affected by uncertain nonlinearities. Electromechanical actuators (EMAs) possess superior energy efficiency and motion characteristics. However, they cannot easily drive heavy-duty mechanisms because of weak bearing capacity. This study proposes and designs a novel electromechanical-hydraulic hybrid actuator (EMHA) that integrates the advantages of EMA and SHA. EMHA mainly features two transmission mechanisms. The piston of the hydraulic transmission mechanism and the ball screw pair of the electromechanical transmission mechanism are mechanically fixed together through screw bolts, realizing the integration of two types of transmission mechanisms. The control scheme of the electromechanical transmission mechanism is used for motion control, and the hydraulic transmission mechanism is used for power assistance. Then, the mathematical model, structure, and parameter design of the new EMHA are studied. Finally, the EMHA prototype and test platform are manufactured. The test results prove that the EMHA has good working characteristics and high energy efficiency. Compared with the valve-controlled hydraulic cylinder system, EMHA exhibits a velocity tracking error and energy consumption reduced by 49.7% and 54%, respectively, under the same working conditions.

Capacitive sensors are efficient tools for biophysical force measurement, which is essential for the exploration of cellular behavior. However, attention has been rarely given on the influences of external mechanical and internal electrical interferences on capacitive sensors. In this work, a bionic swallow structure design norm was developed for mechanical decoupling, and the influences of structural parameters on mechanical behavior were fully analyzed and optimized. A bionic feather comb distribution strategy and a portable readout circuit were proposed for eliminating electrostatic interferences. Electrostatic instability was evaluated, and electrostatic decoupling performance was verified on the basis of a novel measurement method utilizing four complementary comb arrays and application-specific integrated circuit readouts. An electrostatic pulling experiment showed that the bionic swallow structure hardly moved by 0.770 nm, and the measurement error was less than 0.009% for the area-variant sensor and 1.118% for the gap-variant sensor, which can be easily compensated in readouts. The proposed sensor also exhibited high resistance against electrostatic rotation, and the resulting measurement error dropped below 0.751%. The rotation interferences were less than 0.330 nm and (1.829 × 10⁻⁷)°, which were 35 times smaller than those of the traditional differential one. Based on the proposed bionic decoupling method, the fabricated sensor exhibited overwhelming capacitive sensitivity values of 7.078 and 1.473 pF/µm for gap-variant and area-variant devices, respectively, which were the highest among the current devices. High immunity to mechanical disturbances was maintained simultaneously, i.e., less than 0.369% and 0.058% of the sensor outputs for the gap-variant and area-variant devices, respectively, indicating its great performance improvements over existing devices and feasibility in ultralow biomedical force measurement.

Many processes may be used for manufacturing functionally graded materials. Among them, additive manufacturing seems to be predestined due to near-net shape manufacturing of complex geometries combined with the possibility of applying different materials in one component. By adjusting the powder composition of the starting material layer by layer, a macroscopic and step-like gradient can be achieved. To further improve the step-like gradient, an enhancement of the in-situ mixing degree, which is limited according to the state of the art, is necessary. In this paper, a novel technique for an enhancement of the in-situ material mixing degree in the melt pool by applying laser remelting (LR) is described. The effect of layer-wise LR on the formation of the interface was investigated using pure copper and low-alloy steel in a laser powder bed fusion process. Subsequent cross-sectional selective electron microscopic analyses were carried out. By applying LR, the mixing degree was enhanced, and the reaction zone thickness between the materials was increased. Moreover, an additional copper and iron-based phase was formed in the interface, resulting in a smoother gradient of the chemical composition than the case without LR. The Marangoni convection flow and thermal diffusion are the driving forces for the observed effect.

Flanks of end mills are prone to wear in a long machining process. Regrinding is widely used in workshops to restore the flank to an original-like state. However, the traditional method involves material waste by trial and error and dramatically decreases the potential regrinding. Moreover, over-cut would happen to the flutes of worn cutters in the regrinding processes because of improper wheel path. This study presented a new approach to planning the wheel path for regrinding worn end mills to minimize material loss and recover the over-cut. In planning, a scaling method was developed to determine the maximum size of the new cutter according to the similarity of cutter shapes before and after regrinding. Then, the wheel path is first generated by envelope theory to regrind the worn area with a four-axis computer numerical control grinder according to the new size of cutters. Moreover, a second regrinding strategy is applied to recover the flute shape over-cut in the first grinding. Finally, the proposed method is verified by an experiment. Results showed that the proposed approach could save 25% of cutter material compared with the traditional method and ensure at least three regrinding times. This work effectively provides a general regrinding solution for the worn flank with maximum material-saving and regrinding period.

This study focused on the development of austempered ductile iron (ADI) with desirable combination of mechanical properties for crankshaft applications by the combined effect of vanadium (V) alloying and an optimized heat treatment process. The produced unalloyed GGG60, 0.15% V-alloyed GGG60 (V-15), and 0.30% V-alloyed GGG60 samples were subjected to austenitizing at 900 °C for 1 h and subsequent austempering processes at 250, 300, and 350 °C for 15, 30, 60, 90, and 180 min. As a result of these austempering processes, different bainitic structures were obtained, which led to the formation of diverse combinations of mechanical properties. The mechanical properties of the austempered samples were tested comprehensively, and the results were correlated with their microstructures and the stability of the retained austenite phases. From the microstructural observations, the V-alloyed samples exhibited a finer microstructure and a more acicular ferrite phase than unalloyed samples. The V addition delayed the coarsening of the acicular ferrite structures and considerably contributed to the improvement of the mechanical properties of GGG60. Moreover, the X-ray diffraction results revealed that the retained austenite volume and the carbon enrichment of austenite phases in ADI samples were remarkably affected by the addition of vanadium. The increase in volume fraction of retained austenite and its carbon content provided favorable ductility and toughness to V-15, as confirmed by the elongation and impact test results. Consequently, the dual-phase ausferrite microstructure of V-15 that was austempered at 300 °C for 60 min exhibited high strength with substantial ductility and toughness for crankshaft applications.

In-situ maintenance is of great significance for improving the efficiency and ensuring the safety of aero-engines. The cable-driven continuum robot (CDCR) with twin-pivot compliant mechanisms, which is enabled with flexible deformation capability and confined space accessibility, has emerged as a novel tool that aims to promote the development of intelligence and efficiency for in-situ aero-engine maintenance. The high-fidelity model that describes the kinematic and morphology of CDCR lays the foundation for the accurate operation and control for in-situ maintenance. However, this model was not well addressed in previous literature. In this study, a general kinetostatic modeling and morphology characterization methodology that comprehensively contains the effects of cable-hole friction, gravity, and payloads is proposed for the CDCR with twin-pivot compliant mechanisms. First, a novel cable-hole friction model with the variable friction coefficient and adaptive friction direction criterion is proposed through structure optimization and kinematic parameter analysis. Second, the cable-hole friction, all-component gravities, deflection-induced center-of-gravity shift of compliant joints, and payloads are all considered to deduce a comprehensive kinetostatic model enabled with the capacity of accurate morphology characterization for CDCR. Finally, a compact continuum robot system is integrated to experimentally validate the proposed kinetostatic model and the concept of in-situ aero-engine maintenance. Results indicate that the proposed model precisely predicts the morphology of CDCR and outperforms conventional models. The compact continuum robot system could be considered a novel solution to perform in-situ maintenance tasks of aero-engines in an invasive manner.

Recently, advanced sensing techniques ensure a large number of multivariate sensing data for intelligent fault diagnosis of machines. Given the advantage of obtaining accurate diagnosis results, multi-sensor fusion has long been studied in the fault diagnosis field. However, existing studies suffer from two weaknesses. First, the relations of multiple sensors are either neglected or calculated only to improve the diagnostic accuracy of fault types. Second, the localization for multi-source faults is seldom investigated, although locating the anomaly variable over multivariate sensing data for certain types of faults is desirable. This article attempts to overcome the above weaknesses by proposing a global method to recognize fault types and localize fault sources with the help of multi-sensor relations (MSRs). First, an MSR model is developed to learn MSRs automatically and further obtain fault recognition results. Second, centrality measures are employed to analyze the MSR graphs learned by the MSR model, and fault sources are therefore determined. The proposed method is demonstrated by experiments on an induction motor and a centrifugal pump. Results show the proposed method’s validity in diagnosing fault types and sources.

In recent years, the robot industry has developed rapidly, and researchers and enterprises have begun to pay more attention to this industry. People are barely familiar with climbing robots, a kind of special robot. However, from their practical value and scientific research value, climbing robots should studied further. This paper analyzes and summarizes the key technologies of climbing robots, introduces various kinds of climbing robots, and examines their advantages and disadvantages to provide a reference for future researchers. Many countries have studied climbing robots and made some achievements. However, due to the complexity of climbing robots, their climbing efficiency and accuracy need to be further improved. The new structure can improve the climbing efficiency. This paper analyzes climbing robots such as mechanical arms, magnetic attraction, and claws. Optimization methods and path planning can improve the accuracy of work. This paper involves some control methods, including complex intelligent control methods such as behavior-based robot control. This paper also investigates various kinematic planning methods and expounds and summarizes various path planning algorithms, including machine learning and reinforcement learning of artificial intelligence, ant colony algorithm, and other algorithms. Therefore, by analyzing the research status of climbing robots at home and abroad, this paper summarizes three important aspects of climbing robots, namely, structural design, control methods, and climbing strategies, elaborates on the achievements and existing problems of these key technologies, and looks forward to the future development trend and research direction of climbing robots.

Polycrystalline tin is an ideal excitation material for extreme ultraviolet light sources. However, the existence of grain boundary (GB) limits the surface roughness of polycrystalline tin after single-point diamond turning (SPDT). In this work, a novel method termed inductively coupled plasma (ICP)-assisted cutting was developed for the sub-nanometer finishing of polycrystalline tin. The relationship between ICP power, processing time, and modification depth was established by thermodynamic simulation, and the fitted heat transfer coefficient of polycrystalline tin was 540 W/(m²·K). The effects of large-thermal-gradient ICP treatment on the microstructure of polycrystalline tin were studied. After 0.9 kW ICP processing for 3.0 s, corresponding to the temperature gradient of 0.30 K/µm, the grain size of polycrystalline tin was expanded from a size of approximately 20–80 μm to a millimeter scale. The Taguchi method was used to investigate the effects of rotational speed, depth of cut, and feed rate on SPDT. Experiments conducted based on the ICP system indicated that the plasma-assisted cutting method promoted the reduction of the influence of GB steps on the finishing of polycrystalline tin, thereby achieving a surface finish from 8.53 to 0.80 nm in Sa. The results of residual stress release demonstrated that the residual stress of plasma-assisted turning processing after 504 h stress release was 10.7 MPa, while that of the turning process without the ICP treatment was 41.6 MPa.

To fully utilize the in-situ resources on the moon to facilitate the establishment of a lunar habitat is significant to realize the long-term residence of mankind on the moon and the deep space exploration in the future. Thus, intensive research works have been conducted to develop types of 3D printing approach to adapt to the extreme environment and utilize the lunar regolith for in-situ construction. However, the in-situ 3D printing using raw lunar regolith consumes extremely high energy and time. In this work, we proposed a cost-effective melting extrusion system for lunar regolith-based composite printing, and engineering thermoplastic powders are employed as a bonding agent for lunar regolith composite. The high-performance nylon and lunar regolith are uniformly pre-mixed in powder form with different weight fractions. The high-pressure extrusion system is helpful to enhance the interface affinity of polymer binders with lunar regolith as well as maximize the loading ratio of in-situ resources of lunar regolith. Mechanical properties such as tensile strength, elastic modulus, and Poisson’s ratio of the printed specimens were evaluated systematically. Especially, the impact performance was emphasized to improve the resistance of the meteorite impact on the moon. The maximum tensile strength and impact toughness reach 36.2 MPa and 5.15 kJ/m², respectively. High-pressure melt extrusion for lunar regolith composite can increase the effective loading fraction up to 80 wt.% and relatively easily adapt to extreme conditions for in-situ manufacturing.

Most parallel manipulators have multiple solutions to the direct kinematic problem. The ability to perform assembly changing motions has received the attention of a few researchers. Cusp points play an important role in the kinematic behavior. This study investigates the cusp points and assembly changing motions in a two degrees of freedom planar parallel manipulator. The direct kinematic problem of the manipulator yields a quartic polynomial equation. Each root in the equation determines the assembly configuration, and four solutions are obtained for a given set of actuated joint coordinates. By regarding the discriminant of the repeated roots of the quartic equation as an implicit function of two actuated joint coordinates, the direct kinematic singularity loci in the joint space are determined by the implicit function. Cusp points are then obtained by the intersection of a quadratic curve and a cubic curve. Two assembly changing motions by encircling different cusp points are highlighted, for each pair of solutions with the same sign of the determinants of the direct Jacobian matrices.

Biopsy is a method commonly used for early cancer diagnosis. However, bleeding complications of widely available biopsy are risky for patients. Safer biopsy will result in a more accurate cancer diagnosis and a decrease in the risk of complications. In this article, we propose a novel biopsy needle that can reduce bleeding during biopsy procedures and achieve stable hemostasis. The proposed biopsy needle features a compact structure and can be operated easily by left and right hands. A predictive model for puncture force and tip deflection based on coupled Eulerian–Lagrangian (CEL) method is developed. Experimental results show that the biopsy needle can smoothly deliver the gelatin sponge hemostatic plug into the tissue. Although the hemostatic plug bends, the overall delivery process is stable, and the hemostatic plug retains in the tissue without being affected by the withdrawal of the needle. Further experiments indicate that the specimens are well obtained and evenly distributed in the groove of the outer needle without scattering. Our proposed design of biopsy needle possesses strong ability of hemostasis, tissue cutting, and tissue retention. The CEL model accurately predicts the peak of puncture force and produces close estimation of the insertion force at the postpuncture stage and tip position.

To achieve the collision-free trajectory tracking of the four-wheeled mobile robot (FMR), existing methods resolve the tracking control and obstacle avoidance separately. Guaranteeing the synergistic robustness and smooth navigation of mobile robots subjected to motion uncertainties in a dynamic environment using this non-cooperative processing method is difficult. To address this challenge, this paper proposes an obstacle-circumventing adaptive control (OCAC) framework. Specifically, a novel anti-disturbance terminal slide mode control with adaptive gains is formulated, incorporating specified control laws for different stages. This formulation guarantees rapid convergence and simultaneous chattering elimination. By introducing sub-target points, a new sub-target dynamic tracking regression obstacle avoidance strategy is presented to transfer the obstacle avoidance problem into a dynamic tracking one, thereby reducing the burden of local path searching while ensuring system stability during obstacle circumvention. Comparative experiments demonstrate that the proposed OCAC method can strengthen the convergence and obstacle avoidance efficiency of the concerned FMR system.

The smart toolholder is the core component in the development of intelligent and precise manufacturing. It enables in situ monitoring of cutting data and machining accuracy evolution and has become a focal point in academic research and industrial applications. However, current table and rotational dynamometers for milling force, vibration, and temperature testing suffer from cumbersome installation and provide only a single acquisition signal, which limits their use in laboratory settings. In this study, we propose a wireless smart toolholder with multi-sensor fusion for simultaneous sensing of milling force, vibration, and temperature signals. We select force, vibration, and temperature sensors suitable for smart toolholder fusion to adapt to the cutting environment. Thereafter, structural design, circular runout, dynamic balancing, static stiffness, and dynamic inherent frequency tests are conducted to assess its dynamic and static performance. Finally, the smart toolholder is tested for accuracy and repeatability in terms of force, vibration, and temperature. Experimental results demonstrate that the smart toolholder accurately captures machining data with a relative deviation of less than 1.5% compared with existing force gauges and provides high repeatability of milling temperature and vibration signals. Therefore, it is a smart solution for machining condition monitoring.

Selective laser melting (SLM) is a unique additive manufacturing (AM) category that can be used to manufacture mechanical parts. It has been widely used in aerospace and automotive using metal or alloy powder. The build orientation is crucial in AM because it affects the as-built part, including its part accuracy, surface roughness, support structure, and build time and cost. A mechanical part is usually composed of multiple surface features. The surface features carry the production and design knowledge, which can be utilized in SLM fabrication. This study proposes a method to determine the build orientation of multi-feature mechanical parts (MFMPs) in SLM. First, the surface features of an MFMP are recognized and grouped for formulating the particular optimization objectives. Second, the estimation models of involved optimization objectives are established, and a set of alternative build orientations (ABOs) is further obtained by many-objective optimization. Lastly, a multi-objective decision making method integrated by the technique for order of preference by similarity to the ideal solution and cosine similarity measure is presented to select an optimal build orientation from those ABOs. The weights of the feature groups and considered objectives are achieved by a fuzzy analytical hierarchy process. Two case studies are reported to validate the proposed method with numerical results, and the effectiveness comparison is presented. Physical manufacturing is conducted to prove the performance of the proposed method. The measured average sampling surface roughness of the most crucial feature of the bracket in the original orientation and the orientations obtained by the weighted sum model and the proposed method are 15.82, 10.84, and 10.62 μm, respectively. The numerical and physical validation results demonstrate that the proposed method is desirable to determine the build orientations of MFMPs with competitive results in SLM.

The noncontact blade tip timing (BTT) measurement has been an attractive technology for blade health monitoring (BHM). However, the severe undersampled BTT signal causes a significant challenge for blade vibration parameter identification and fault feature extraction. This study proposes a novel method based on the minimum variance distortionless response (MVDR) of the direction of arrival (DoA) estimation for blade natural frequency estimation from the non-uniformly undersampled BTT signals. First, based on the similarity between the general data acquisition model for BTT and the antenna array model in DoA estimation, the circumferentially arranged probes on the casing can be regarded as a non-uniform linear array. Thus, BTT signal reconstruction is converted into the DoA estimation problem of the non-uniform linear array signal. Second, MVDR is employed to address the severe undersampling issue and recover the BTT undersampled signal. In particular, spatial smoothing is innovatively utilized to enhance the estimation of covariance matrix of the BTT signal to avoid ill-condition or singularity, while improving efficiency and robustness. Lastly, numerical simulation and experimental testing are employed to verify the validity of the proposed method. Monte Carlo simulation results suggest that the proposed method behaves better than conventional methods, especially under a lower signal-to-noise ratio condition. Experimental results indicate that the proposed method can effectively overcome the severe undersampling problem of BTT signal induced by physical limitations, and has a strong potential in the field of BHM.

Continuum robot has attracted extensive attention since its emergence. It has multi-degree of freedom and high compliance, which give it significant advantages when traveling and operating in narrow spaces. The flexural virtual-center of motion (VCM) mechanism can be machined integrally, and this way eliminates the assembly between joints. Thus, it is well suited for use as a continuum robot joint. Therefore, a design method for continuum robots based on the VCM mechanism is proposed in this study. First, a novel VCM mechanism is formed using a double leaf-type isosceles-trapezoidal flexural pivot (D-LITFP), which is composed of a series of superimposed LITFPs, to enlarge its stroke. Then, the pseudo-rigid body (PRB) model of the leaf is extended to the VCM mechanism, and the stiffness and stroke of the D-LITFP are modeled. Second, the VCM mechanism is combined to form a flexural joint suitable for the continuum robot. Finally, experiments and simulations are used to validate the accuracy and validity of the PRB model by analyzing the performance (stiffness and stroke) of the VCM mechanism. Furthermore, the motion performance of the designed continuum robot is evaluated. Results show that the maximum stroke of the VCM mechanism is approximately 14.2°, the axial compressive strength is approximately 1915 N/mm, and the repeatable positioning accuracies of the continuum robot is approximately ±1.47° (bending angle) and ±2.46° (bending direction).

Many heat transfer tubes are distributed on the tube plates of a steam generator that requires periodic inspection by robots. Existing inspection robots are usually involved in issues: Robots with manipulators need complicated installation due to their fixed base; tube mobile robots suffer from low running efficiency because of their structural restricts. Since there are thousands of tubes to be checked, task planning is essential to guarantee the precise, orderly, and efficient inspection process. Most in-service robots check the task tubes using row-by-row and column-by-column planning. This leads to unnecessary inspections, resulting in a long shutdown and affecting the regular operation of a nuclear power plant. Therefore, this paper introduces the structure and control system of a dexterous robot and proposes a task planning method. This method proceeds into three steps: task allocation, base position search, and sequence planning. To allocate the task regions, this method calculates the tool work matrix and proposes a criterion to evaluate a sub-region. And then all tasks contained in the sub-region are considered globally to search the base positions. Lastly, we apply an improved ant colony algorithm for base sequence planning and determine the inspection orders according to the planned path. We validated the optimized algorithm by conducting task planning experiments using our robot on a tube sheet. The results show that the proposed method can accomplish full task coverage with few repetitive or redundant inspections and it increases the efficiency by 33.31% compared to the traditional planning algorithms.

Reliable foot-to-ground contact state detection is crucial for the locomotion control of quadruped robots in unstructured environments. To improve the reliability and accuracy of contact detection for quadruped robots, a detection approach based on the probabilistic contact model with multi-information fusion is presented to detect the actual contact states of robotic feet with the ground. Moreover, a relevant control strategy to address unexpected early and delayed contacts is planned. The approach combines the internal state information of the robot with the measurements from external sensors mounted on the legs and feet of the prototype. The overall contact states are obtained by the classification of the model-based predicted probabilities. The control strategy for unexpected foot-to-ground contacts can correct the control actions of each leg of the robot to traverse cluttered environments by changing the contact state. The probabilistic model parameters are determined by testing on the single-leg experimental platform. The experiments are conducted on the experimental prototype, and results validate the contact detection and control strategy for unexpected contacts in unstructured terrains during walking and trotting. Compared with the body orientation under the time-based control method regardless of terrain, the root mean square errors of roll, pitch, and yaw respectively decreased by 60.07%, 54.73%, and 64.50% during walking and 73.40%, 61.49%, and 61.48% during trotting.

The internal force antagonism (IFA) problem is one of the most important issues limiting the applications and popularization of redundant parallel robots in industry. Redundant cable-driven parallel robots (RCDPRs) and redundant rigid parallel robots (RRPRs) behave very differently in this problem. To clarify the essence of IFA, this study first analyzes the causes and influencing factors of IFA. Next, an evaluation index for IFA is proposed, and its calculating algorithm is developed. Then, three graphical analysis methods based on this index are proposed. Finally, the performance of RCDPRs and RRPRs in IFA under three configurations are analyzed. Results show that RRPRs produce IFA in nearly all the areas of the workspace, whereas RCDPRs produce IFA in only some areas of the workspace, and the IFA in RCDPRs is milder than that RRPRs. Thus, RCDPRs more fault-tolerant and easier to control and thus more conducive for industrial application and popularization than RRPRs. Furthermore, the proposed analysis methods can be used for the configuration optimization design of RCDPRs.

Compacted graphite iron (CGI) is considered to be an ideal diesel engine material with excellent physical and mechanical properties, which meet the requirements of energy conservation and emission reduction. However, knowledge of the microstructure evolution of CGI and its impact on flow stress remains limited. In this study, a new modeling approach for the stress–strain relationship is proposed by considering the strain hardening effect and stored energy caused by the microstructure evolution of CGI. The effects of strain, strain rate, and deformation temperature on the microstructure of CGI during compression deformation are examined, including the evolution of graphite morphology and the microstructure of the pearlite matrix. The roundness and fractal dimension of graphite particles under different deformation conditions are measured. Combined with finite element simulation models, the influence of graphite particles on the flow stress of CGI is determined. The distributions of grain boundary and geometrically necessary dislocations (GNDs) density in the pearlite matrix of CGI under different strains, strain rates, and deformation temperatures are analyzed by electron backscatter diffraction technology, and the stored energy under each deformation condition is calculated. Results show that the proportion and amount of low-angle grain boundaries and the average GNDs density increase with the increase of strain and strain rate and decreased first and then increased with an increase in deformation temperature. The increase in strain and strain rate and the decrease in deformation temperature contribute to the accumulation of stored energy, which show similar variation trends to those of GNDs density. The parameters in the stress–strain relationship model are solved according to the stored energy under different deformation conditions. The consistency between the predicted results from the proposed stress–strain relationship and the experimental results shows that the evolution of stored energy can accurately predict the stress–strain relationship of CGI.

Given the limited operating ability of a single robotic arm, dual-arm collaborative operations have become increasingly prominent. Compared with the electrically driven dual-arm manipulator, due to the unknown heavy load, difficulty in measuring contact forces, and control complexity during the closed-chain object transportation task, the hydraulic dual-arm manipulator (HDM) faces more difficulty in accurately tracking the desired motion trajectory, which may cause object deformation or even breakage. To overcome this problem, a compliance motion control method is proposed in this paper for the HDM. The mass parameter of the unknown object is obtained by using an adaptive method based on velocity error. Due to the difficulty in obtaining the actual internal force of the object, the pressure signal from the pressure sensor of the hydraulic system is used to estimate the contact force at the end-effector (EE) of two hydraulic manipulators (HMs). Further, the estimated contact force is used to calculate the actual internal force on the object. Then, a compliance motion controller is designed for HDM closed-chain collaboration. The position and internal force errors of the object are reduced by the feedback of the position, velocity, and internal force errors of the object to achieve the effect of the compliance motion of the HDM, i.e., to reduce the motion error and internal force of the object. The required velocity and force at the EE of the two HMs, including the position and internal force errors of the object, are inputted into separate position controllers. In addition, the position controllers of the two individual HMs are designed to enable precise motion control by using the virtual decomposition control method. Finally, comparative experiments are carried out on a hydraulic dual-arm test bench. The proposed method is validated by the experimental results, which demonstrate improved object position accuracy and reduced internal force.

Given limited terrain adaptability, most existing multirobot cooperative transportation systems (MRCTSs) mainly work on flat pavements, restricting their outdoor applications. The connectors’ finite deformation capability and the control strategies’ limitations are primarily responsible for this phenomenon. This study proposes a novel MRCTS based on tracked mobile robots (TMRs) to improve terrain adaptability and expand the application scenarios of MRCTSs. In structure design, we develop a novel 6-degree-of-freedom passive adaptive connector to link multiple TMRs and the transported object (the communal payload). In addition, the connector is set with sensors to measure the position and orientation of the robot with respect to the object for feedback control. In the control strategy, we present a virtual leader–physical follower collaborative paradigm. The leader robot is imaginary to describe the movement of the entire system and manage the follower robots. All the TMRs in the system act as follower robots to transport the object cooperatively. Having divided the whole control structure into the leader robot level and the follower robot level, we convert the motion control of the two kinds of robots to trajectory tracking control problems and propose a novel double closed-loop kinematics control framework. Furthermore, a control law satisfying saturation constraints is derived to ensure transportation stability. An adaptive control algorithm processes the wheelbase uncertainty of the TMR. Finally, we develop a prototype of the TMR-based MRCTS for experiments. In the trajectory tracking experiment, the developed MRCTS with the proposed control scheme can converge to the reference trajectory in the presence of initial tracking errors in a finite time. In the outdoor experiment, the proposed MRCTS consisting of four TMRs can successfully transport a payload weighing 60 kg on an uneven road with the single TMR’s maximum load limited to 15 kg. The experimental results demonstrate the effectiveness of the structural design and control strategies of the TMR-based MRCTS.