Balancing and Simulation of a Double Crank-Rocker Engine Model for Optimum Reduction of Shaking Forces and Shaking Moments

In this paper, a new configuration of Crank-Rocker (CR) model has been proposed by duplicating its mechanism. The method has been implemented to overcome vibration problem on a single-piston Crank-Rocker engine caused by system unbalance. The new method suggests combining conventional method of adding counterweights to reduce shaking forces and eliminating the inertial moments on system by implementing the new layout. A dynamic study of the new model is presented, then the objective function is derived and implemented to perform the optimization process. Related design variables and system constraints are introduced to determine attached counterweights optimized characteristics. For results validation, the simulation, dynamic analysis, and optimization process were conducted using ADAMS VIEW® software. The output results were presented and discussed to verify the validity of the suggested method. It was noticed that the method was very effective and has managed to reduce the total shaking forces by about 91%, shaking moment by about 66%; and the driving torque by 27%.

Balancing of planar six-bar mechanism with genetic algorithm

In the present work, the optimal balancing of the planar six-bar mechanism is investigated to minimize the fluctuations of shaking force and shaking moment. An optimization problem is formulated for balancing the planar six-bar mechanism by developing an objective function. The genetic algorithm and MINITAB software were used to solve the optimization problem. The selection of weighting factors has a crucial role to obtain the optimum values of design parameters. Two sets of weighting factors were considered as per the contribution of X and Y components of the shaking force and shaking moments. Shaking force and shaking moments were minimized drastically and were compared with the original values.

An Alternative Method for Shaking Force Balancing of the 3RRR PPM through Acceleration Control of the Center of Mass

The problem of shaking force balancing of robotic manipulators, which allows the elimination or substantial reduction of the variable force transmitted to the fixed frame, has been traditionally solved by optimal mass redistribution of the moving links. The resulting configurations have been achieved by adding counterweights, by adding auxiliary structures or, by modifying the form of the links from the early design phase. This leads to an increase in the mass of the elements of the mechanism, which in turn leads to an increment of the torque transmitted to the base (the shaking moment) and of the driving torque. Thus, a balancing method that avoids the increment in mass is very desirable. In this article, the reduction of the shaking force of robotic manipulators is proposed by the optimal trajectory planning of the common center of mass of the system, which is carried out by “bang-bang” profile. This allows a considerable reduction in shaking forces without requiring counterweights, additional structures, or changes in form. The method, already presented in the literature, is resumed in this case using a direct and easy to automate modeling technique based on fully Cartesian coordinates. This permits to express the common center of mass, the shaking force, and the shaking moment of the manipulator as simple analytic expressions. The suggested modeling procedure and balancing technique are illustrated through the balancing of the 3RRR planar parallel manipulator (PPM). Results from computer simulations are reported.

Design and optimization of CAM connecting rod system in high-speed drives based on dynamic characteristics and mathematical model

To explore the cause of structure vibration, this study aims to propose a kinematic equation and analyze its movement in relation to cam linkage mechanism for a jacketing machine and shearing mechanism. Finite element method is adopted to construct the kinetic model of linkage subsystem of shearing mechanism. This method can solve the inability of the shearing mechanism to accurately complete the shearing actions of the rubber hose during large vibration of the mechanism. Lumped parameter method is adopted to establish the kinetic model of the cam roller subsystem, and Newmark method is used to solve the kinetic equation of the shearing mechanism. The optimal parameters of the linking rod, cam profile, and shaking force and shaking moment of the mechanism at different rotation speeds are analyzed. Results show that rotation speed and cam profile are factors affecting the performance of the mechanism. The shaking force (shaking moment) is the main cause of the vibration of the mechanism on the rack. As such, the shaking force and shaking moment of the mechanism are selected as the objective functions of the optimization model. The node parameters of B-spline curve movement law and cross-section parameters of the linking rod are used as variables for the optimal design of the cam linkage system. Finally, the obtained optimal value is x = [0.33 0.2 0.54 0.62 8.7 3.0 7.8 16.3] T.

Optimal dynamic design of planar mechanisms using teaching–learning-based optimization algorithm

A two-stage optimization method for optimal dynamic design of planar mechanisms is presented in this paper. For dynamic balancing, minimization of the shaking force and the shaking moment is achieved by finding optimum mass distribution of mechanism links using the equimomental system of point-masses in the first stage of the optimization. In the second stage, their shapes are synthesized systematically by closed parametric curve, i.e. cubic B-spline curve corresponding to the optimum inertial parameters found in the first stage. The multi-objective optimization problem to minimize both the shaking force and the shaking moment is solved using evolutionary optimization algorithm – “Teaching-learning-based optimization (TLBO) algorithm”. The computational performance of TLBO algorithm is compared with another evolutionary optimization algorithm, i.e. genetic algorithm.