Mechanical Science and Engineering is an international, peer-reviewed open access journal dedicated to advancing research the field of mechanical engineering. The journal provides a rapid publication process to ensure wide dissemination of high-quality articles to scientists, professionals, and interested individuals worldwide. Our goal is to serve as an efficient, reliable, and trusted platform for scholars and readers, publishing cutting-edge research in the field.
Abstract: The kinematics of robots are key factors affecting the real-time performance and stability of robot control systems. The solution of inverse kinematics is also a fundamental problem in kinematics. The difficulty of inverse kinematics lies in the ever-changing geometric shapes of the robotic arm or robot itself, as well as the complex computational problems caused by nonlinear triangular equations that describe the mapping between Cartesian space and joint space. Therefore, there is currently no more universal method. The traditional matrix method involves a large number of matrix operations, and its solution process is complex. This article proposes a hybrid method of geometric method and DH method. In the process of inverse kinematics solving, the geometric method is used to solve the first three joint angles of the robotic arm, and the last three joint angles are solved using vector method, ultimately obtaining the inverse solution. Taking three commonly used industrial robots as examples, this paper provides a detailed introduction to the process of solving using geometric and DH methods, and then uses MATLAB simulation to verify the effectiveness of the geometric solution. Compared with the commonly used inverse transformation matrix method, iterative method, etc. in traditional algorithms, the pose error of the algorithm proposed in this paper is basically the same for the same number of inverse solutions, and it has relatively high efficiency. Therefore, it can be seen that the algorithm proposed in this article has certain advantages and practicality.Abstract: The kinematics of robots are key factors affecting the real-time performance and stability of robot control systems. The solution of inverse kinematics is also a fundamental problem in kinematics. The difficulty of inverse kinematics lies in the ever-changing geometric shapes of the robotic arm or robot itself, as well as the complex computational ...Learn More
Abstract: Bearings are the core components of motors, and they often rotate at high speeds during operation, which can easily cause wear and fatigue. The failure of rolling bearings can lead to equipment downtime, production delays, and increased maintenance costs. The fault diagnosis of rolling bearings has become the key to ensuring the safety, efficiency, and availability of motor systems. Fault diagnosis of rolling bearings usually involves processing and analyzing their vibration signals to make judgments. In this paper, Complete Ensemble Empirical Mode Decomposition (CEEMAND), Singular Value Decomposition, Renyi Entropy, and Convolutional Neural Networks are used to process the bearing vibration signals for fault diagnosis. The intrinsic mode function (IMF) components obtained from the vibration signal of rolling bearings after CEEMDAN decomposition contain false components that cannot describe the characteristic information. Therefore, based on the calculation of the correlation coefficients between the original signal and each IMF component, IMF components with higher correlation coefficients are selected, and singular value decomposition is performed on the selected IMF components with higher correlation coefficients to obtain their singular values, Calculate the Renyi entropy of the singular value again to form the fault feature vector. Finally, the fault feature vector is input into a Convolutional Neural Network (CNN) for fault category recognition. When the training set accounts for 20%, the accuracy rate is 99.3%. The accuracy of fault signal detection is 100%, indicating that the method proposed in this paper has good fault recognition performance.Abstract: Bearings are the core components of motors, and they often rotate at high speeds during operation, which can easily cause wear and fatigue. The failure of rolling bearings can lead to equipment downtime, production delays, and increased maintenance costs. The fault diagnosis of rolling bearings has become the key to ensuring the safety, efficiency,...Learn More
Lu Yuankui,
Hu Yanjie,
Zhang Chao,
Liu Jiajia*,
Zhang Chenglei,
Li Xiaoqian,
Song Bao,
Sheng Dazhong,
Sheng Guodong,
Zhou Yifei,
Yin Delong,
Li Haoyuan
Abstract: With the continuous innovation of science and technology, the research and future development trends of intelligent robots have been attracting much attention. Among them, how to realize the quadruped robots to complete the delivered tasks in complex and changing environments has become the main direction of research in the future. Therefore, this design is based on relevant theoretical knowledge to design an intelligent environment-aware small quadrupedal robot that can work in complex environments. This design firstly analyzes the current status and trend of the research and development of quadrupedal robots and has a certain understanding of the content of the design and the objectives to be achieved. Through relevant information, the overall design program of the quadruped robot is determined. The mechanical structure of the quadruped robot is designed separately, and after the design of the mechanical parts structure is completed, the important parts are calibrated and calculated, and the relevant parts of the quadruped robot are analyzed statically. The designed quadrupedal robot realizes the compact and simple structure through simplified design, which is of certain reference significance to the research of quadrupedal robots.Abstract: With the continuous innovation of science and technology, the research and future development trends of intelligent robots have been attracting much attention. Among them, how to realize the quadruped robots to complete the delivered tasks in complex and changing environments has become the main direction of research in the future. Therefore, this ...Learn More
Abstract: Generally, peanuts as export products or deep-processing products need to be shelled. When peanuts are extracted from peanut oil, in order to improve the oil yield, peanuts will be shelled. As the current peanut sheller has problems such as unstable performance, contradictory sheller rate and breakage rate, poor adaptability to the environment, low versatility and low utilization rate, by improving the technical scheme of the peanut sheller, the key parts of the scraper peanut sheller, such as sheller device, cleaning device and transmission device, are designed. It is known that the scraper peanut sheller has the characteristics of impact method, rolling method, shearing method and extrusion method. At the same time, the modal analysis of the frame is carried out. Compared with the highest vibration frequency generated by the belt operation under the theoretical calculation, it can be seen that the highest vibration frequency generated by the normal operation of the belt is lower than the first natural frequency of the frame modal analysis, and the resonance phenomenon of the shucker will not be produced, so the shucking efficiency is high, the effect is good, and it is expected to meet the needs of people.Abstract: Generally, peanuts as export products or deep-processing products need to be shelled. When peanuts are extracted from peanut oil, in order to improve the oil yield, peanuts will be shelled. As the current peanut sheller has problems such as unstable performance, contradictory sheller rate and breakage rate, poor adaptability to the environment, low...Learn More
Abstract: In facing the challenge of extracting difficult data from complex rolling bearings, the uncertainty of data has become a significant issue. Among various approaches, evidence theory stands out as a crucial method. However, in practical applications, traditional evidence theory exhibits certain limitations, especially in its core component—the conflict management mechanism—when dealing with highly conflicting evidence. Accurately quantifying and managing conflicts between pieces of evidence becomes a key issue in enhancing fusion effectiveness during the process of multi-source information fusion. To address this issue, this study introduces an innovative evidence conflict measurement method aimed at improving the capability of traditional evidence theory to handle highly conflicting evidence. This method starts from the perspective of "distance" and conducts a thorough analysis of the properties required by such a distance measurement. By proving these properties, the theoretical rationality and applicability of the proposed conflict measurement method are ensured. Further, through a series of theoretical proofs and numerical calculations, this study demonstrates the accuracy of the method in dealing with completely conflicting and completely non-conflicting evidence. Simultaneously, the method can effectively measure evidence with varying degrees of conflict, showing higher flexibility and broad applicability. This is achieved by applying the new method to classic cases of conflicting evidence and comparing it with existing methods. The comparison not only verifies the effectiveness of the new method on both theoretical and experimental levels but also reveals its significant advantages in handling highly conflicting evidence. The innovation of this research is primarily reflected in the following aspects: Initially, a novel conflict measurement framework is introduced, predicated on an exhaustive analysis and understanding of the "distance" between evidences. Subsequently, the rationality and efficacy of this measurement approach are corroborated through rigorous theoretical validation. Finally, comparative analyses with conventional methodologies underscore the effectiveness of this new approach in addressing highly conflicting evidences in practical applications.Abstract: In facing the challenge of extracting difficult data from complex rolling bearings, the uncertainty of data has become a significant issue. Among various approaches, evidence theory stands out as a crucial method. However, in practical applications, traditional evidence theory exhibits certain limitations, especially in its core component—the confl...Learn More
