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DOI: 10.1186/s10033-019-0392-0

A Novel Pneumatic Soft Gripper with a Jointed Endoskeleton Structure

Zhaoping Wu, Xiaoning Li & Zhonghua Guo

Abstract：In current research on soft grippers, pneumatically actuated soft grippers are generally fabricated using fully soft materials, which have the advantage of flexibility as well as the disadvantages of a small gripping force and slow response speed. To improve these characteristics, a novel pneumatic soft gripper with a jointed endoskeleton structure (E-Gripper) is developed, in which the muscle actuating function has been separated from the force bearing function. The soft action of an E-Gripper finger is performed by some air chambers surrounded by multilayer rubber embedded in the restraining fiber. The gripping force is borne and transferred by the rigid endoskeleton within the E-Gripper finger. Thus, the gripping force and action response speed can be increased while the flexibility is maintained. Through experiments, the bending angle of each finger segment, response time, and gripping force of the E-Gripper have been measured, which provides a basis for designing and controlling the soft gripper. The test results have shown that the maximum gripping force of the E-Gripper can be 35 N, which is three times greater than that of a fully soft gripper (FS-Gripper) of the same size. At the maximum charging pressure of 150 kPa, the response time is 1.123 s faster than that of the FS-Gripper. The research results indicate that the flexibility of a pneumatic soft gripper is not only maintained in the case of the E-Gripper, but its gripping force is also obviously increased, and the response time is reduced. The E-Gripper thus shows great potential for future development and applications.

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https://cjme.springeropen.com/articles/10.1186/s10033-019-0392-0

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Zhaoping Wu, Xiaoning Li,Zhonghua Guo. A Novel Pneumatic Soft Gripper with a Jointed Endoskeleton Structure. Chinese Journal of Mechanical Engineering, 2019, 32: 78.

DOI：10.1186/s10033-019-0391-1

A New Flexible Multibody Dynamics Analysis Methodology of Deployable Structures with Scissor-Like Elements

Qi’an Peng, Sanmin Wang, Changjian Zhi & Bo Li

Abstract：There are vast constraint equations in conventional dynamics analysis of deployable structures, which lead to differential-algebraic equations (DAEs) solved hard. To reduce the difficulty of solving and the amount of equations, a new flexible multibody dynamics analysis methodology of deployable structures with scissor-like elements (SLEs) is presented. Firstly, a precise model of a flexible bar of SLE is established by the higher order shear deformable beam element based on the absolute nodal coordinate formulation (ANCF), and the master/slave freedom method is used to obtain the dynamics equations of SLEs without constraint equations. Secondly, according to features of deployable structures, the specification matrix method (SMM) is proposed to eliminate the constraint equations among SLEs in the frame of ANCF. With this method, the inner and the boundary nodal coordinates of element characteristic matrices can be separated simply and efficiently, especially on condition that there are vast nodal coordinates. So the element characteristic matrices can be added end to end circularly. Thus, the dynamic model of deployable structure reduces dimension and can be assembled without any constraint equation. Next, a new iteration procedure for the generalized-α algorithm is presented to solve the ordinary differential equations (ODEs) of deployable structure. Finally, the proposed methodology is used to analyze the flexible multi-body dynamics of a planar linear array deployable structure based on three scissor-like elements. The simulation results show that flexibility has a significant influence on the deployment motion of the deployable structure. The proposed methodology indeed reduce the difficulty of solving and the amount of equations by eliminating redundant degrees of freedom and the constraint equations in scissor-like elements and among scissor-like elements.

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https://cjme.springeropen.com/articles/10.1186/s10033-019-0391-1

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Qi’an Peng, Sanmin Wang, Changjian Zhi, et al. A New Flexible Multibody Dynamics Analysis Methodology of Deployable Structures with Scissor-Like Elements. Chinese Journal of Mechanical Engineering, 2019, 32: 77.

DOI：10.1186/s10033-019-0390-2

Prediction of Eight Earings in Deep Drawing of 5754O Aluminum Alloy Sheet

Haibo Wang, Mingliang Men, Yu Yan, Min Wan & Qiang Li

Abstract：Earings appear easily during deep drawing of cylindrical parts owing to the anisotropic properties of materials. However, current methods cannot fully utilize the mechanical properties of material, and the number of earings obtained differ with the simulation methods. In order to predict the eight-earing problem in the cylindrical deep drawing of 5754O aluminum alloy sheet, a new method of combining the yield stress and anisotropy index (r-value) to solve the parameters of the Hill48 yield function is proposed. The general formula for the yield stress and r-value in any direction is presented. Taking a 5754O aluminum alloy sheet as an example in this study, the deformation area in deep drawing is divided into several equal sectorial regions based on the anisotropy. The parameters of the Hill48 yield function are solved based on the yield stress and r-value simultaneously for the corresponding deformation area. Finite element simulations of deep drawing based on new and existing methods are carried out for comparison with experimental results. This study provides a convenient and reliable way to predict the formation of eight earings in the deep drawing process, which is expected to be useful in industrial applications. The results of this study lay the foundation for the optimization of the cylindrical deep drawing process, including the optimization of the blank shape to eliminate earing defects on the final product, which is of great importance in the actual production process.

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https://cjme.springeropen.com/articles/10.1186/s10033-019-0390-2

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Haibo Wang, Mingliang Men, Yu Yan, et al. Prediction of Eight Earings in Deep Drawing of 5754O Aluminum Alloy Sheet. Chinese Journal of Mechanical Engineering,2019, 32: 76. 

DOI：10.1186/s10033-019-0388-9

Signal-Based Intelligent Hydraulic Fault Diagnosis Methods: Review and Prospects

Juying Dai, Jian Tang, Shuzhan Huang & Yangyang Wang

Abstract：Hydraulic systems have the characteristics of strong fault concealment, powerful nonlinear time-varying signals, and a complex vibration transmission mechanism; hence, diagnosis of these systems is a challenge. To provide accurate diagnosis results automatically, numerous studies have been carried out. Among them, signal-based methods are commonly used, which employ signal processing techniques based on the state signal used for extracting features, and further input the features into the classifier for fault recognition. However, their main deficiencies include the following: (1) The features are manually designed and thus may have a lack of objectivity. (2) For signal processing, feature extraction and pattern recognition are conducted using independent models, which cannot be jointly optimized globally. (3) The machine learning algorithms adopted by these methods have a shallow architecture, which limits their capacity to deeply mine the essential features of a fault. As a breakthrough in artificial intelligence, deep learning holds the potential to overcome such deficiencies. Based on deep learning, deep neural networks (DNNs) can automatically learn the complex nonlinear relations implied in a signal, can be globally optimized, and can obtain the high-level features of multi-dimensional data. In this paper, the main technology used in an intelligent fault diagnosis and the current research status of hydraulic system fault diagnosis are summarized and analyzed. The significant prospect of applying deep learning in the field of intelligent fault diagnosis is presented, and the main ideas, methods, and principles of several typical DNNs are described and summarized. The commonality between a fault diagnosis and other issues regarding typical pattern recognition are analyzed, and research ideas for applying DNNs for hydraulic fault diagnosis are proposed. Meanwhile, the research advantages and development trend of DNNs (both domestically and overseas) as applied to an intelligent fault diagnosis are reviewed. Furthermore, the fault characteristics of a complex hydraulic system are summarized and discussed, and the key problems and possible research ideas of applying DNNs to an intelligent hydraulic fault diagnosis are presented and comprehensively analyzed.

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https://cjme.springeropen.com/articles/10.1186/s10033-019-0388-9

引用本文

Juying Dai, Jian Tang, Shuzhan Huang, et al. Signal-Based Intelligent Hydraulic Fault Diagnosis Methods: Review and Prospects. Chinese Journal of Mechanical Engineering, 2019, 32: 75.

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