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Design and optimization of clamp–shear–grab integrated attachment

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Journal of the Brazilian Society of Mechanical Sciences and Engineering Aims and scope Submit manuscript

Abstract

Aiming at the lack of functional versatility in current engineering attachments, an innovative clamp–shear–grab integrated attachment (CSGI attachment), which combines clamping, shearing, and grabbing functions, is proposed based on the author’s US patent. The variable frame four-bar mechanism and separate frame design ideas are adopted in mechanism design, and the attachment’s motion scheme and virtual prototype are presented. In optimization, the optimization objectives of the CSGI attachment are chosen as the gripper opening size, the transmission angle of the clamp–shear mechanism, and the weight, so a multi-objective optimization model with mechanism dimension and topological structure is established. Next, an improved nondominated sorting genetic algorithm (WINSGA-II) is proposed by improving the crossover and search strategies, while its effectiveness is tested using standard indicators and data sets. Testing results show that the WINSGA-II algorithm has better convergence, population diversity, and uniformity than the nondominated sorting genetic algorithm (NSGA-II). Subsequently, the WINSGA-II algorithm is used to obtain the optimal results for the CSGI attachment. Finally, the engineering prototype is made and tested with clamping, shearing, and grabbing. The results show that the CSGI attachment can achieve the intended function. Regarding optimization, the gripper opening size of the CSGI attachment is expanded by 24.2%, and the weight is reduced by 10.1%. The HV and Spacing indicators of the WINSGA-II algorithm are 2.7% higher and 29.6% lower than those of the NSGA-II algorithm for this problem.

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Abbreviations

\(L_{iqb}\) :

The length of the link \(i\) in the state of the clamp–shear mode jaw is closed

\(L_{iqk}\) :

The length of the link \(i\) in the state of the clamp–shear mode jaw is fully open

\(L_{ibb}\) :

The length of the link \(i\) in the state of the grabbing mode gripper is closed

\(L_{ibk}\) :

The length of the link \(i\) in the state of the grabbing mode gripper is fully open

\(\theta_{iqb}\) :

The angle of angle \(i\) in the state of the clamp–shear mode jaw is closed

\(\theta_{iqk}\) :

The angle of angle \(i\) in the state of the clamp–shear mode jaw is fully open

\(\theta_{ibb}\) :

The angle of angle \(i\) in the state of the grabbing mode gripper is closed

\(\theta_{ibk}\) :

The angle of angle \(i\) in the state of the grabbing mode gripper is fully open

\(L_{iq}\) :

The length of the link \(i\) in two states of the clamp–shear mode

\(L_{ib}\) :

The length of the link \(i\) in two states of the grabbing mode

\(\theta_{iq}\) :

The angle of angle \(i\) in two states of the clamp–shear mode

\(\theta_{ib}\) :

The angle of angle \(i\) in two states of the grabbing mode

\(L_{i}\) :

The length of the link \(i\) in two states of in two modes

\(L_{6b}\) :

The length of link 6 when the power hydraulic cylinder protrudes to the limited position

\(L_{6k}\) :

The length of link 6 when the power hydraulic cylinder retracts to the limited position

\(L_{wj}\) :

The length between point \(w\) and point \(j\)

\(X_{j}\) :

The horizontal coordinate of \(j\)

\(\theta_{{{\text{BG}}}}\) :

The angle BCG

\(F_{2}\) :

The thrust of the power hydraulic cylinder

\(F_{c}\) :

The shear force

\(L_{c}\) :

The length of cutting-edge

\(L_{51}\) :

The length in the horizontal direction between point A and point B

\(L_{52}\) :

The length in the vertical direction between points A and B

\(m_{\min }\) :

The minimum mass of each topology-optimized component after topological structure optimization

\(M\) :

Original weight of each the topology-optimized component

\(f\left( x \right)_{g\min }\) :

The gth minimization objective function

\(f\left( x \right)_{g\max }\) :

The gth maximization objective function

\(\sigma_{\max }\) :

The maximum stress of each topology-optimized component after topological structure optimization

\({\text{Nop}}\) :

Number of populations

\({\text{Noi}}\) :

Number of iterations

\({\text{Cp}}\) :

Crossover probability

\({\text{Mp}}\) :

Mutation probability

\({\text{It}}\) :

Initial temperature

\({\text{Tt}}\) :

Termination temperature

\({\text{Cf}}\) :

Cooling factor

\({\text{Noili}}\) :

Number of inner loop iterations

\({\text{Cpf}}\) :

Crossover probability factor

\({\text{Nofp}}\) :

Number of reference points

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Funding

This work was supported by the National Key Research and Development Program of China(2021YFC3002003).

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Authors and Affiliations

  1. Faculty of Materials and Manufacturing, Beijing University of Technology, Beijing, China

    Jing Zhao, Xudong Wang & Xin Wang

  2. The National Enterprise Research and Develop Center, Sunward Intelligence Equipment Co., Ltd., Changsha, 410131, China

    Daqing Zhang

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  1. Jing Zhao
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Correspondence to Daqing Zhang.

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Zhao, J., Wang, X., Zhang, D. et al. Design and optimization of clamp–shear–grab integrated attachment. J Braz. Soc. Mech. Sci. Eng. 46, 296 (2024). https://doi.org/10.1007/s40430-024-04715-2

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