Rotation Accuracy Analysis of Aerostatic Spindle Considering Shaft’s Roundness and Cylindricity

The rotation accuracy of the aerostatic spindle can easily be affected by shaft shape errors due to the small gas film clearance. Thus, the main shaft shape errors with the largest scale—that is, the roundness and cylindricity errors—are studied in this paper, and a dynamic mathematical model is established with the consideration of the roundness, cylindricity errors, and spindle speed. In order to construct the shaft model, the discrete coefficient index of the shaft radius based on roundness measurement data are proposed. Then, the simulation calculations are conducted based on the measured cylindricity data and the constructed shaft model. The calculation results are compared with the spindle rotation accuracy measured using the spindle error analyzer. The results show that the shaft with a low discrete coefficient is subjected to less unbalanced force and smaller rotation errors, as obtained by the experiment.

NEW MODEL OF MACHINE FOR PROCESSING SURFACES OF LARGE-SIZED PARTS HAVING THE SHAPE OF BODIES OF ROTATION

During long-term operation of rotating parts of technological machines, which include tires and support rollers of rotary kilns, rolling surfaces lose their shape accuracy and quality. Built-in machine modules are used to restore large-sized parts in the form of bodies of revolution. Such repair work requires special technological approaches and careful preparation before starting. It is necessary to take into account the real geometry of the surface of the part being repaired, which may have shape errors in the longitudinal and cross section due to wear, and conduct a preliminary analysis of the state of the part. It is also necessary to take into account the large dimensions and weight of the workpiece, and the inconsistent position of its axis during rotation. The technologies used and mobile machines for carrying out these repairs still have drawbacks that do not allow for efficient processing and affect the accuracy and quality of the resulting surface. The solution to this problem can be the development of new models of machine tools for processing large-sized bodies of revolution, the design of which will be more perfect in comparison with the previous models. To achieve this goal, it is necessary to study and analyze the existing domestic and foreign models of mobile machines and the principle of their operation. The proposed new machine model should have sufficient static and dynamic rigidity, as well as have a module responsible for adaptive control of the machining process, which will compensate for unstable positioning of parts during machining.

Material Removal Predictions in the Robot Glass Polishing Process Using Machine Learning

Robot polishing is increasingly being used in the production of high-end glass workpieces such as astronomy mirrors, lithography lenses, laser gyroscopes or high-precision coordinate measuring machines. The quality of optical components such as lenses or mirrors can be described by shape errors and surface roughness. Whilst the trend towards sub nanometre level surfaces finishes and features progresses, matching both form and finish coherently in complex parts remains a major challenge. With increasing optic sizes, the stability of the polishing process becomes more and more important. If not empirically known, the optical surface must be measured after each polishing step. One approach is to mount sensors on the polishing head in order to measure process relevant quantities. On the basis of these data, Machine Learning algorithms can be applied for surface value prediction. Due to the modification of the polishing head by the installation of sensors and the resulting process influences, the first Machine Learning model could only make removal predictions with insufficient accuracy. The aim of this work is to show a polishing head optimised for the sensors, which is coupled with a Machine Learning model in order to predict the material removal and failure of the polishing head during robot polishing. The artificial neural network (ANN) is developed in the Python programming language using the Keras deep learning library. It starts with a simple network architecture and common training parameters. The model will then be optimized step-by-step using different methods and optimized in different steps. The data collected by a design of experiments with the sensor-integrated glass polishing head are used to train the machine learning model and to validate the results. The neural network achieves a prediction accuracy of the material removal of 99.22 %.

Spatial data analysis for laser scanning based shape error inspection

Laser scanning, a widely used technology, has been highly developed and adopted in various industrial applications. The methodologies used for scanner date processing are mostly point based. In this thesis, a new approach is presented to analyze spatial data obtained from a 3-D laser scanner for shape error inspection. Different from traditional methodologies, the method proposed in this research is frequency based. The method utilizes the Fourier transform to decompose a 2-D curve or 3-D shape into its spatial components by applying two 1-D FFT (Fast Fourier Transform) on 2-D curves or two 2-D FFT on 3-D shapes. The spatial components including frequency, amplitude, and phase are defined as shape characteristics to represent the shape under inspection. By relating spatial components with GD&T (Geometric Dimensioning and Tolerancing) standards using proper analysis techniques, such as frequency spectrum and cross correlation, shape errors can be detected and characterized. One of the applications of this method is automated inspection. In this research, the spatial data method is applied to MIG (Metal Inert Gas) weld inspection. Experiments are carried out to analyze the 2-D curve of a projection weld data, and the 3-D scanning data directly. A MIG weld inspection system is also developed for production use.

Spatial data analysis for laser scanning based shape error inspection

Laser scanning, a widely used technology, has been highly developed and adopted in various industrial applications. The methodologies used for scanner date processing are mostly point based. In this thesis, a new approach is presented to analyze spatial data obtained from a 3-D laser scanner for shape error inspection. Different from traditional methodologies, the method proposed in this research is frequency based. The method utilizes the Fourier transform to decompose a 2-D curve or 3-D shape into its spatial components by applying two 1-D FFT (Fast Fourier Transform) on 2-D curves or two 2-D FFT on 3-D shapes. The spatial components including frequency, amplitude, and phase are defined as shape characteristics to represent the shape under inspection. By relating spatial components with GD&T (Geometric Dimensioning and Tolerancing) standards using proper analysis techniques, such as frequency spectrum and cross correlation, shape errors can be detected and characterized. One of the applications of this method is automated inspection. In this research, the spatial data method is applied to MIG (Metal Inert Gas) weld inspection. Experiments are carried out to analyze the 2-D curve of a projection weld data, and the 3-D scanning data directly. A MIG weld inspection system is also developed for production use.

FUNDAMENTALS OF THE DESIGN OF FUNDAL MANDRELS FOR THE INSTALLATION OF THIN-WALLED WORKPIECES. PART 1

There are a number of problems in mechanical engineering technology. One of them is related to the installation on the machine and the previous processing of thin-walled rings, which are widely used in mechanical engineering. Due to the low bending stiffness of thin-walled rings after processing there are a large magnitude of rigidity of the form (deviation from roundness). As production experience has shown, in the conditions of mass production, it is advisable to use fungal mandrels and adjustments to reduce shape errors. They allow for a small radial gap between the holes of the ring and the fungal cam to have extended contact rings with cams along the angular coordinate. However, there are no methods for calculating the parameters of contact interaction with cams, considering a number of factors, primarily the radial clearance. Hence, it is impossible to calculate more accurately the error of the form after processing. In this paper (it is supposed to be continued), based on methods for calculating flat rings of construction mechanics of machines, a method for determining the stress-strain state of a thin-walled state is proposed, considering the contact pressure. In this case, the semiangle of contact of the ring with the fungal cam and the shape of the contact pressure plot are determined. This allows you to calculate the stress state of the thin-walled ring and the shape error when processing more accurately in a fungal mandrel, as well as reasonably assign the dimensions of the mandrel parts. Due to the exceptionally large number of calculations in the calculations according to the proposed method, it can only be implemented using a computer program, which creates great difficulties in analyzing different source data. Therefore, it is planned to rework the completed developments into an engineering calculation method with graphs in dimensionless form.

Research on multi-sensor measurement system and evaluation method for roundness and straightness errors of deep-hole parts

Precision deep-hole parts are widely used in various fields of industrial production and their machining quality has a great impact on fatigue limit, geometric accuracy, and stability of products. Since roundness and straightness errors are essential technical indexes to evaluate the machining quality of deep-hole parts, accurate measurement and effective evaluation of them are of great significance to ensure the performance of related products. A multi-sensor integrated device that can measure two kinds of shape errors simultaneously was developed based on laser displacement sensor, two-dimensional position-sensitive detector, angle sensor, and laser distance sensor. Aiming at the problem of roundness error evaluation, the solution process of the control points of the minimum zone circle was optimized by calculating the distance between points and searching according to the polygon removal rule. Besides, the rotating projection method was used to evaluate the straightness error effectively. Eventually, the effectiveness of the measuring device and the shape error evaluation method was verified by experimental research.

Analysis of Dynamic Response of a Two Degrees of Freedom (2-DOF) Ball Bearing Nonlinear Model

Often the input values used in mathematical models for rolling bearings are in a wide range, i.e., very small values of deformation and damping are confronted with big values of stiffness in the governing equations, which leads to miscalculations. This paper presents a two degrees of freedom (2-DOF) dimensionless mathematical model for ball bearings describing a procedure, which helps to scale the problem and reveal the relationships between dimensionless terms and their influence on the system’s response. The derived mathematical model considers nonlinear features as stiffness, damping, and radial internal clearance referring to the Hertzian contact theory. Further, important features are also taken into account including an external load, the eccentricity of the shaft-bearing system, and shape errors on the raceway investigating variable dynamics of the ball bearing. Analysis of obtained responses with Fast Fourier Transform, phase plots, orbit plots, and recurrences provide a rich source of information about the dynamics of the system and it helped to find the transition between the periodic and chaotic response and how it affects the topology of RPs and recurrence quantificators.

Tool Path Design of the Counter Single Point Incremental Forming Process to Decrease Shape Error

Incremental sheet metal forming can manufacture various sheet metal products without a dedicated punch and die set. In this study, we developed a two-stage incremental forming process to decrease shape errors in the conventional incremental forming process. The forming process was classified into the first single point incremental forming (1st SPIF) process for forming a product and the counter single point incremental forming (counter SPIF) process to decrease shape error. The counter SPIF gives bending deformation in the opposite direction. Furthermore, the counter SPIF compensates for shape errors, such as section deflection, skirt spring-back, final forming height, and round. The tool path of the counter SPIF has been optimized through a relatively simple optimization method by modifying the tool path of the previous step. The tool path of the 1st SPIF depends on the geometry of the product. An experiment was performed to form a circular cup shape to verify the proposed tool path of the 1st and counter SPIF. The result confirmed that the shape error decreased when compared to the conventional SPIF. For the application, the ship-hull geometry was adopted. Experimental results demonstrated the feasibility of the two-stage incremental forming process.