Error Uncertainty Analysis in Planar Closed-Loop Structure with Joint Clearances

For planar closed-loop structures with clearances, the angular and positional error uncertainties are studied. By using the vector translation method and geometric method, the boundaries of the errors are analyzed. The joint clearance is considered as being distributed uniformly in a circle area. A virtual link projection method is proposed to deal with the clearance affected length error probability density function (PDF) for open-loop links. The error relationship between open loop and closed loop is established. The open-loop length PDF and the closed-loop angular error PDF both approach being Gaussian distribution if there are many clearances. The angular propagation error of multi-loop structures is also investigated by using convolution. The positional errors of single and multiple loops are both discussed as joint distribution functions. Monte Carlo simulations are conducted to verify the proposed methods.

Effect of Joint Clearance on Landing Gear Retraction Failure

A simple method of investigating the effect of joint clearances on landing gear retraction failure is presented and applied to the main landing gear with a single sidestay and a hydraulic actuator. A geometric model is presented with assumptions of each link as a rigid body and their relative positions geometrically determined by considering the size of the clearances. We conducted a sensitivity analysis based on a geometric model of the main landing gear. The model was calibrated using the data from the technical order. A Monte Carlo simulation (MCS) was conducted, and whose input was the distance of each clearance based on the experimental design that combined the modified Latin hypercube sampling (LHS) and central composite design (CCD). As a result, we were able to find that the joint had a high potential to operate abnormally. We validated the model by using the actual failure data. Finally, the physical meaning of the sensitivity analysis results was interpreted by comparing them with the values obtained through an amplification index method that is a modified linearization method.

Error modeling and singularity analysis of planar parallel mechanisms using optimized expression of joint clearances and link deformation

A fast error modeling method is proposed to analyze the pose deviation of 3-RPR planar parallel mechanisms with multiple revolute joint clearances. The pose error arisen from clearances and limb deformation is modeled from the point of inverse kinematics and estimated numerically. Manipulator poses are represented by elements of the Lie group SE(2) and the discontinuous deformation of limbs due to clearances are modeled by the Heaviside function, which is then approximated with the hyperbolic tangent function. After establishing the error model, an efficient error compensation method is introduced. The proposed error modeling and accuracy analysis method are validated by case study of a 3-RPR mechanism. The results show that the hyperbolic tangent function runs faster than the step function and it provides better convergence. Finally, the singularity of the 3-RPR mechanism with load is analyzed and the results reveal the effects of loads and clearances on mechanism singularities.

A Fuzzy Approach for the Kinematic Reliability Assessment of Robotic Manipulators

SUMMARY This paper aims at developing a novel method to assess the kinematic reliability of robotic manipulators based on the fuzzy theory. The kinematic reliability quantifies the probability of obtaining positioning errors within acceptable limits. For this purpose, the fuzzy reliability evaluates the effect of the joint clearances on the end-effector position to compute a failure possibility index. As an alternative to the conventional methods reported in the literature, this failure possibility index conveys a novel assessment of the kinematic performance. The numerical results are compared with the well-known probabilistic approach based on the Monte Carlo simulation.

Statistical Tolerance Analysis of 3D-Printed Non-Assembly Mechanisms in Motion Using Empirical Predictive Models

Fused Deposition Modelling (FDM) enables the fabrication of entire non-assembly mechanisms within a single process step, making previously required assembly steps dispensable. Besides the advantages of FDM, the manufacturing of these mechanisms implies some shortcomings such as comparatively large joint clearances and geometric deviations depending on machine-specific process parameters. The current state-of-the-art concerning statistical tolerance analysis lacks in providing suitable methods for the consideration of these shortcomings, especially for 3D-printed mechanisms. Therefore, this contribution presents a novel methodology for ensuring the functionality of fully functional non-assembly mechanisms in motion by means of a statistical tolerance analysis considering geometric deviations and joint clearance. The process parameters and hence the geometric deviations are considered in terms of empirical predictive models using machine learning (ML) algorithms, which are implemented in the tolerance analysis for an early estimation of tolerances and resulting joint clearances. Missing information concerning the motion behaviour of the clearance affected joints are derived by a multi-body-simulation (MBS). The exemplarily application of the methodology to a planar 8-bar mechanism shows its applicability and benefits. The presented methodology allows evaluation of the design and the chosen process parameters of 3D-printed non-assembly mechanisms through a process-oriented tolerance analysis to fully exploit the potential of Additive Manufacturing (AM) in this field along with its ambition: ‘Print first time right’.

Accuracy analysis and optimization of an extendible support structure with joint clearances

An extendible support structure (ESS) used for unfolding and supporting the antenna array of the Synthetic Aperture Radar (SAR) satellite is reviewed and modeled in this paper. The structure is parameterized by calibrating 12 independent parameters, and following which, angular accuracy of the ESS with joint clearances is modeled. The maximum angular error is obtained by the particle swarm optimization (PSO) and validated by the Monte Carlo simulation. A novel error reduction method is then proposed to improve the accuracy of the structure. In the proposed method, the uncertainty of the joint clearance is eliminated using force constraints by adding small torsional springs. Various joint clearance models with force constraints are proposed to obtain the optimal spring allocation, and based on which, the angular error is further reduced by optimizing the structure of the ESS. The Quasi-Monte-Carlo-based Sobol method for global sensitivity analysis is used to select the design parameters for optimization. Finally, the angular error is greatly reduced.