The surging interest in planetary exploration underscores the need for deployable aerodynamic decelerators with a low ballistic coefficient. This study introduces a novel approach to designing and constructing mechanically deployable aerodynamic decelerators (MDADs) that utilize an umbrella-like mechanism and proposes a new mechanism of MDADs through this method. The proposed method utilizes plane-symmetric 7R (R: revolute joint) linkages, and the kinematics of these linkages are systematically analyzed using the product of exponentials method. The 7R linkage kinematics are equated to an equivalent joint, the foundation for constructing umbrella-like deployable mechanisms. Three distinct types of mechanisms are synthesized using this methodology. Subsequently, their kinematics are analyzed based on the equivalent joint, and the configurations are experimentally validated through 3D-printed models and kinematic simulations. Trajectory simulations and structural analyses are conducted to assess the performance of the deployable mechanisms and provide valuable insights into their capabilities. This research contributes to advancing deployable aerodynamic decelerator technology and offers a promising avenue for future planetary entry, descent, and landing applications.
This study addresses the challenges of tendon-driven continuum robots in terms of high-performance joint design, high-accuracy and -efficiency mechanical modeling, and inverse kinetostatic-based control. First, a general design framework for rigid–flexible coupled continuum robots is proposed inspired by the Freedom and Constraint Topology theory. Based on this framework, a novel claw-type continuum robot with high torsion resistance, high-precision positioning, and excellent anti-buckling performance is developed. Consequently, a novel kinetostatic model named the separated beam equilibrium model (SBEM) is proposed by solving the equilibrium equations for each unit individually rather than recursively, which achieves high modeling accuracy and efficiency. Finally, an iterative inverse kinetostatic-based control method involving mechanic factors is proposed. Comparative experimental results demonstrate that the claw-type continuum robot outperforms the twin-pivot continuum robot in terms of torsion resistance by more than 300 times. Moreover, the SBEM achieves high morphology estimation accuracy with errors less than 2.91% of manipulator length and high efficiency with more than 20 times improvement for computation reduction compared with the conventional chained beam constraint model. Furthermore, the iterative inverse kinetostatic model-based control obtains a tip error less than 3.70% of manipulator length by only using the open-loop method. The proposed design, modeling, and control method exhibits vast potential for continuum robots when tackling challenging tasks such as inspection, maintenance, and medical surgery in confined and unstructured environments including engine flow paths, nuclear conduits, and human body cavities.
In curling competitions, the throwing strategy has a decisive influence on the outcome of the game. When robots are applied to the sport of curling, they first need to understand the various throwing strategies in curling competitions and then adjust their motion control parameters to achieve the corresponding strategic throws. However, current curling strategy research lacks mathematical analysis and descriptive methods for throwing strategies tailored to robots. Moreover, research on how robots can solve for corresponding throwing strategies is lacking. These limitations have restricted the application and development of curling robots in the sport. Here, the concepts of the curling stone’s hitting domain and hitting tree are introduced to analyze and describe the curling strategies for robots by constructing the curling hitting domain through a curling collision model and by building the hitting tree through operations such as combination, permutation, and pruning. Furthermore, based on the solution methods for hitting domains and hitting trees, a search solution method for the control parameters of robots is developed. The research findings are integrated into a curling robot auxiliary decision-making software. With the help of the auxiliary software, the curling robot achieves victory in competitions against humans. The research outcomes are of great importance for the application and development of curling robots and legged robots.
In the rotor system of aero-engines, the main purpose of a bolted flange connection structure is to transfer torque and speed, and the rotor system may exhibit bolt loosening and connection structure failure under complex working conditions, high speed rotation, and external excitation unbalanced force. In addition, the bolted connection structure in the rotor system is mainly subjected to torsional vibration excitation, and using experimental methods to analyze the dynamic response law of different structural parameters of a bolted connection structure under torsional vibration excitation is complicated. Therefore, on the basis of the concentrated mass method and the elastic interaction characteristics within the bolted system, this study establishes dynamic models of one-bolted and multi-bolted connection structural systems under torsional excitation. On the basis of this dynamic model, the dynamic response characteristics of different thread parameters, external excitation, bolt stiffness, and compression stiffness of the connected parts in a one-bolted connection system and the influence laws of different elastic modulus, bolt numbers, and the thickness of the connected parts on the loosening of the multi-bolted connection system are analyzed. Results show that small thread pitch, external excitation amplitude and frequency, compressive stiffness, bolt stiffness, and elastic modulus and large tooth angle, number of bolts, and thickness of connected parts can appropriately improve the anti-loosening performance of the bolted connection system. This study also uses a comparative verification method combining finite element simulation and experiment to verify the correctness of the established dynamic model effectively.
Tool anomalies in computer numerical control (CNC) milling processes are unpredictable, hindering the promotion of fully automated machining. Traditional detection systems often struggle with stability due to the irregular and non-parametric nature of signals generated during dynamic milling. This study proposes an improved probability and statistics-based model for constructing tool anomaly thresholds in the time domain, with the decision-making strategy seamlessly integrated into CNC milling systems. A robust data acquisition and preprocessing framework was developed to improve the accuracy and reliability of real-time monitoring data. A Gaussian process model was employed to construct an anomaly detection threshold data set from irregular signals. Anomalies were identified when monitoring indicators surpassed the established threshold. The proposed method was validated through milling experiments of a turbine blisk, demonstrating an overall anomaly detection accuracy of 91.45%, which exceeds those of four other typical anomaly detection methods. These results confirm the effectiveness of the proposed method and its potential applicability in industry.
The heat transfer process is a critical topic in the field of cutting and grinding machining, playing a vital role in reducing machining temperatures and improving machining quality. In these operations, heat transfer is generally characterized by specific parameters, including the energy distribution coefficient and the convective heat transfer coefficient. These parameters affect the magnitude and direction of energy flow in the heat transfer process, directly impacting cutting and grinding temperatures. However, comprehensive reviews summarizing current studies on heat transfer processes are lacking. To effectively control heat transfer, thereby managing cutting/grinding temperatures while improving workpiece surface quality, it is essential that we understand how machining parameters, material properties, and cooling methods influence the heat transfer, and this knowledge is critical for guiding the practical production. This paper analyzes and summarizes heat transfer process parameter models in cutting and grinding operations. First, the study examines energy flow and distribution ratios during cutting and grinding processes, classifying and summarizing various energy partition coefficient models based on different research methods. Second, convective cooling mechanisms in cutting and grinding machining are analyzed, summarizing models of convective heat transfer coefficients. The paper then reviews the practical application of these models, highlighting the influence law of each factor on the models. Finally, the most widely recognized and accurate models of heat transfer process parameters are summarized and identified, analyzing the mechanisms by which different factors alter these parameters. Based on current challenges in heat transfer process parameter research, the paper proposes possible future research directions. The goal is to provide theoretical guidance and technical support for advancing research in heat transfer and improving thermal control in machining.
A material removal mechanism is a prerequisite to maintaining high-quality surfaces for high-shear and low-pressure grinding using body-armor-like grinding wheels (BAGWs). However, the pressure distribution and material removal efficiency for machining brittle materials using BAGWs remain unclear. This research investigated two types of elastic deformations during grinding by analyzing the contact mechanism between BAGWs and the workpiece. Additionally, the model of elastohydrodynamic pressure distribution was refined, and the material removal mechanism for machining brittle materials, incorporating the maximum undeformed chip thickness, was revealed. A material removal rate (MRR) model was established based on Hertzian contact, ductile-brittle transition, and spherical indentation theory. The theoretical model was validated through single-factor experiments utilizing a high-shear and low-pressure grinding experimental platform. At a normal grinding force of 15 N and a grinding speed of 10 m/s, the MRR could reach up to 0.276 mm3/s. The experimental results revealed that the model could accurately predict the MRR under various grinding parameters, with an average prediction error of 8.5%.
