Cylindricity Error Evaluation Research Articles

Cylindricity error evaluation based on an improved artificial gorilla troop optimizer

Cylindricity error evaluation based on an improved artificial gorilla troop optimizer

An Improved Self-Born Weighted Least Square Method for Cylindricity Error Evaluation

In order to improve the stability of the evaluation results and the gross error resistance of the algorithm in view of the widespread gross errors in geometric error evaluation, an improved self-born weighted least square method (ISWLS) is proposed in this paper. First, the nonlinear cylindrical axial model is linearized to establish the error equation of the observed values. We use the conditional equations of the independent observations found as valid information to derive the weights of the observations. The weights of the observations are subjected to least-square iteration to calculate the error values and equation parameters. Meanwhile, the ordinal numbers of the independent sets of equations in the observed equations are updated several times. By updating the ordinal number information of the conditional equations, the influence of gross error data on the solution of the equations is minimized. Through a series of experiments, the algorithm is proved to have a strong resistance to gross differences, and operation time is shorter. According to the evaluation results of cylindricity error, the uncertainty of cylindricity error was calculated by the Guide to the expression of uncertainty in measurement method (GUM)and the Monte Carlo method (MCM). Experiments show that the uncertainty results of the MCM method can verify the results assessed by the GUM method, which proves that the results of the ISWLS method are effective and robust.

Cylindricity Error Measurement and Evaluation Based on Step Acceleration Algorithm in Crankshaft Measuring Machine

Cylindricity Error Measurement and Evaluation Based on Step Acceleration Algorithm in Crankshaft Measuring Machine

A Hybrid Greedy Sine Cosine Algorithm with Differential Evolution for Global Optimization and Cylindricity Error Evaluation

ABSTRACT Sine-cosine algorithm (SCA) has found a widespread application in various engineering optimization problems. However, SCA suffers from premature convergence and insufficient exploitation. Cylindricity error evaluation is a typical engineering optimization problem related to the quality of cylindrical parts. A hybrid greedy sine-cosine algorithm with differential evolution (HGSCADE) is developed in this paper to solve optimization problems and evaluate cylindricity error. HGSCADE integrates the SCA with the opposition-based population initialization, the greedy search, the differential evolution (DE), the success history-based parameter adaptation, and the Levy flight-based local search. HGSCADE is tested on the CEC2014 benchmark functions and is employed in cylindricity error evaluation. The results show the superiority of HGSCADE to other state-of-the-art algorithms for the benchmark functions and cylindricity error evaluation.

A new method for cylindricity error evaluation based on increment-simplex algorithm.

A geometric error determines the quality and function of a product to a certain extent. Cylindricity error is an important indicator of the geometric error of form parts. In recent years, with the development of geometric product verification and specification (GPS), the specification of the cylindricity error and high-precision detection have become the focus in the field of industrial metrology. In this paper, by analyzing the existing cylindricity evaluation strategy, a new method for cylindricity error evaluation based on increment-simplex algorithm is proposed. The purpose is to improve the efficiency of cylindricity error analysis on the basis of ensuring the accuracy requirements. First, according to the GPS specification, the characteristics and applications of the circular section method, the helicoid line method, the generatrix line method, and the bird-cage method for the extraction operation are analyzed. And for the fitting operation, the mathematical models of the cylindricity fitting for the least squares cylinder, minimum circumscribed cylinder, maximum inscribed cylinder, and minimum zone cylinder in cartesian and cylindrical coordinate systems are constructed. Second, a new method of cylindricity error optimization evaluation based on the incremental optimization method is proposed. A theoretical analysis of the new method is made with the circular section method as an example, and the specific steps of cylindricity error analysis based on the circular section method of the new method are given. Finally, experiments and analysis are carried out, and the accuracies and evaluation efficiencies of the cylindricity error of the different cylindricity measurement and evaluation strategies are compared and analyzed. The results and operating efficiency of the increment-simplex algorithm and the traditional algorithms are compared, and the effectiveness and feasibility of the new method are proved.

Five-point cylindricity error separation technique

This study focuses on developing a new error separation technique for the in situ measurement and reconstruction of cylindrical profile. Based on a five-point system proposed, the center vectors of the least squares circle in the cross-sectional profile of the cylinder can are accurately extracted by the error separation model. The vectors are based on a spatial straight line that connects two least squares centers of the fixed cross-sectional profiles, which makes the double integration calculations avoided and the ability to resist interference improved. A cylindrical profile conforming to the mathematical definition can be reconstructed for cylindricity error evaluation. Theories, numerical validations and experiments verified that the spindle’s radial and tilt error motions as well as the probe carriage’s straightness deviations are all removed. This innovative technique solved a crucial problem regarding the accurate and high-precision reconstruction of a cylindrical profile in the in situ measurement.

A modified comprehensive learning particle swarm optimizer and its application in cylindricity error evaluation problem.

Particle swarm optimizer was proposed in 1995, and since then, it has become an extremely popular swarm intelligent algorithm with widespread applications. Many modified versions of it have been developed, in which, comprehensive learning particle swarm optimizer is a very powerful one. In order to enhance its performance further, a local search based on Latin hypercube sampling is combined with it in this work. Due to that a hypercube should become smaller and smaller for better local search ability during the search process, a control method is designed to set the size of the hypercube. Via numerical experiments, it can be observed that the comprehensive learning particle swarm optimizer with the local search based on Latin hypercube sampling has a strong ability on both global and local search. The hybrid algorithm is applied in cylindricity error evaluation problem and it outperforms several other algorithms.

An efficient method for minimum zone cylindricity error evaluation using kinematic geometry optimization algorithm

Cylindricity error evaluation is necessary to verify the cylindrical product function and to control the manufacturing process. This paper proposes a novel method for minimum zone cylindricity error evaluation based on kinematic geometry optimization algorithm (KGOA). The proposed method shows excellent performance in the cylindricity error evaluation process. First, the theoretical basis and representation for the minimum zone programming evaluation model are presented. Next, a new approach for extracting feature points is proposed using projective transformation and convex set construction. Instead of all measured points, the extracted feature points are used for the cylindricity error evaluation. On comparing the proposed method with other existing methods based on some literature data sets, agreement or improved solutions are obtained. The simulation and experiment results show that the proposed method can achieve optimum solutions accurately and improve the implementation efficiency. Compared with the commercial software of Coordinate Measuring Machine, the proposed method can reduce the average calculating time by half while retaining the accuracy of evaluation results. The basis of this method can also be applied for other geometrical error evaluation in engineering metrology.

Cylindricity Error Evaluation Based on an Improved Harmony Search Algorithm

The cylindricity error is one of the basic form errors in mechanical parts, which greatly influences the assembly accuracy and service life of relevant parts. For the minimum zone method (MZM) in international standards, there is no specific formula to calculate the cylindricity error. Therefore, the evaluation methods of the cylindricity error under the MZM have been widely concerned by international scholars. To improve the evaluation accuracy and accelerate the iteration speed of the cylindricity, an improved harmony search (IHS) algorithm is proposed and applied to compute the cylindricity. On the basis of the standard harmony search algorithm, the logistic chaotic initialization is introduced into the generation of initial solution to improve the quality of solutions. During the iterative process, the global and local search capabilities are balanced by adopting the par and bw operators adaptively. After each iteration, the Cauchy mutation strategy is adopted to the best solution to further improve the calculation precision of the IHS algorithm. Finally, four test functions and three groups of cylindricity error examples were applied to validity verification of the IHS algorithm, the simulation test results show that the IHS algorithm has advantages of the computing accuracy and iteration speed compared with other traditional algorithms, and it is very effective for the application in the evaluation of the cylindricity error.

A parallel error separation method for the on-line measurement and reconstruction of cylindrical profiles

An innovative parallel error separation technique for on-line measurement and reconstruction of cylindrical profile is presented. A five-probe system configured to target three adjacent cross-sections of the cylinder is proposed to simultaneously execute the three-probe roundness error separation and three-probe straightness error separation. The curved median line is determined by fitting through the least squares centers of circular cross-sectional profiles. The cylindrical profile conforming to the mathematical definition can then be reconstructed for the cylindricity error evaluation. Theoretical analysis and numerical validation have been performed. The results verify that the spindle’s radial and tilt error motions as well as the probe carriage’s straightness deviations are removed, and the least squares center of each cross-sectional profile of the cylinder is accurately extracted even if the spindle’s error motions are not repeatable in each rotation. This method has thoroughly solved the inherent problem in conventional multi-probe error separation techniques: the suppression of the first-order harmonic in separating the cross-sectional profile of the cylinder and the error motions of the spindle.

Cylindricity Error Evaluation Based on an Improved Biogeography-based Optimization Algorithm

Cylindricity Error Evaluation Based on an Improved Biogeography-based Optimization Algorithm

A hierarchical particle swarm optimizer with latin sampling based memetic algorithm for numerical optimization

Memetic algorithms, one type of algorithms inspired by nature, have been successfully applied to solve numerous optimization problems in diverse fields. In this paper, we propose a new memetic computing model, using a hierarchical particle swarm optimizer (HPSO) and latin hypercube sampling (LHS) method. In the bottom layer of hierarchical PSO, several swarms evolve in parallel to avoid being trapped in local optima. The learning strategy for each swarm is the well-known comprehensive learning method with a newly designed mutation operator. After the evolution process accomplished in bottom layer, one particle for each swarm is selected as candidate to construct the swarm in the top layer, which evolves by the same strategy employed in the bottom layer. The local search strategy based on LHS is imposed on particles in the top layer every specified number of generations. The new memetic computing model is extensively evaluated on a suite of 16 numerical optimization functions as well as the cylindricity error evaluation problem. Experimental results show that the proposed algorithm compares favorably with conventional PSO and several variants.

Method for cylindricity error evaluation using Geometry Optimization Searching Algorithm

According to the geometrical characteristics of cylindricity error, a method for cylindricity error evaluation using Geometry Optimization Searching Algorithm (GOSA) has been presented. The optimization method and linearization method and uniform sampling could not adopt in the algorithm. The principle of the algorithm is that a hexagon are collocated based on the reference points in the starting and the end measured section respectively, the radius value of all the measured points are calculated by the line between the vertexes of the hexagon in the starting and the end measured section as the ideal axes, the cylindricity error value of corresponding evaluation method (include minimum zone cylinder method (MZC), minimum circumscribed cylinder method (MCC) and maximum inscribed cylinder method (MIC)) are obtained according to compare, judgment and arranged hexagon repeatedly. The principle and step of using the algorithm to solve the cylindricity error is detailed described and the mathematical formula and program flowchart are given. The experimental results show that the cylindricity error can be evaluated effectively and exactly using this algorithm.

Optimization Evaluation of Geometric Error Based on Correctional Simplex Method

This paper researches the theory of geometric error evaluation and its application. On the basis of the geometric model of error evaluation, the features of the geometric error enclosure evaluation are analyzed, and the paper has founded the linear programming model of minimum zone association, maximum inscribed association and minimum circumscribed association. By taking the minimum conditions criterion and the theory on minimizing the extremal difference function as rules of geometric error evaluation, a correctional simplex method for direct solution of the programming model is proposed, and also the process is given. Furthermore, the method is verified by giving an example of the cylindricity error evaluation and comparing the experiment results with the ones obtained from other common methods. In addition, this designed method is also used to other geometric error evaluation in practice. The theoretical analysis and experimental results indicate that, the proposed correctional simplex method does provide well accuracy on geometric error evaluation. The outstanding advantages conclude not only high efficiency and stability but also good universality and practicality.

Evaluating the geometric characteristics of cylindrical features

This paper presents mathematical models and efficient methodologies for the evaluation of geometric characteristics that define form and function of cylindrical features; namely cylindricity and straightness of median line. These two problems have similar structures and can be solved by comparable procedures. Based on the proposed methodologies, the cylindricity error evaluation can be performed using any of the following criteria: the least squares cylinders, minimum circumscribed cylinders, maximum inscribed cylinders or minimum zone cylinders. The procedures have been tested for accuracy and efficiency. The results indicate that they provide accurate results quickly.