High-precision Machinery Research Articles

Bearing fault detection system based on a deep diffusion model

Bearings are crucial components of modern high-precision machinery and rotating machines. Excellent bearing failure detection systems are vital for ensuring that machines operate precisely. Advances in artificial neural networks (ANNs) and increases in computer processing speed have led to the application of many ANN models in various fields, including bearing failure detection, with excellent outcomes being achieved. However, to construct an ANN model that can precisely detect bearing failures, large quantities of data must be collected on various types of bearing failures. Thus, considerable time must be spent in data collection before rotating machines are operated on the production line, which increases costs for manufacturers. To overcome this problem, the present study used a diffusion model for data augmentation to improve the accuracy of an ANN model trained on a small quantity of bearing sound data. This study performed time-delay mapping to preprocess the data and convert them into a two-dimensional time-delay mapping diagram to reduce the dimensionality of the data features, a novel approach in the field of bearing failure detection. Finally, this study used a convolutional neural network model, which exhibited the optimal classification performance for time-delay mapping diagrams, for bearing failure detection. By comparing the results obtained from augmented and raw data, this study confirmed that using a diffusion model to augment data can improve the generalization ability of bearing failure detection models trained on a small quantity of data.

Nonlinear Dynamic Analysis and Forecasting of Symmetric Aerostatic Cavities Bearing Systems

Symmetric Aerostatic Cavities Bearing (SACB) systems have attracted increasing attention in the field of high-precision machinery, particularly rotational mechanisms applied at ultra-high speeds. In an air bearing system, the air bearing serves as the main support, and the load-carrying capacity is not as high as that of oil film bearings. However, the aero-spindle can operate at considerably high rotational speeds with relatively lower heat generated from rotation compared with that of oil film bearings. In addition, the operating environment of air bearings does not easily cause the rotor to deform. Hence, through adequate design, air pressure systems exhibit a certain level of stability. In general, the pressure distribution function of air bearings exhibits strong nonlinearity when there are changes in the rotor mass or rotational speed, or when the bearing system is inadequately designed. These issues may lead to instabilities in the rotor, such as unpredictable nonperiodic movements, rotor collisions, or even chaotic movements under certain parameters. In this study, rotor oscillation was analyzed using the maximum Lyapunov exponent to identify whether chaotic behavior occurred. Machine learning methods were then used to establish models and predict the rotor behavior. Especially, random forest and extreme gradient boosting were combined to develop a new model and confirm whether this model offered higher prediction performance and more accurate results in predicting tendencies with considerable changes compared with other models. The results can be effectively used to predict the SACB system and prevent nonlinear behavior from occurring.

A Method for Reducing Sub-Divisional Errors in Open-Type Optical Linear Encoders with Angle Shift Pattern Main Scale

In this research, a novel approach is presented to enhance the precision of open-type optical linear encoders, focusing on reducing subdivisional errors (SDEs). Optical linear encoders are crucial in high-precision machinery. The overall error in optical linear encoders encompasses baseline error, SDE, and position noise. This study concentrates on mitigating SDEs, which are recurrent errors within each pitch period and arise from various contributing factors. A novel method is introduced to improve the quality of sinusoidal signals in open-type optical linear encoders by incorporating specially designed angle shift patterns on the main scale. The proposed method effectively suppresses the third order harmonics, resulting in enhanced accuracy without significant increases in production costs. Experimental results indicate a substantial reduction in SDEs compared to traditional methods, emphasizing the potential for cost-effective, high-precision optical linear encoders. This paper also discusses the correlation between harmonic suppression and SDE reduction, emphasizing the significance of this method in achieving higher resolutions in optical linear encoders.

Ultra-compact displacement and vibration sensor with a sub-nanometric resolution based on Talbot effect of optical microgratings.

Based on Talbot effect of optical microgratings, we report an ultra-compact sensor for displacement and vibration measurement with resolution down to sub-nanometer level. With no need of optical components such as reflectors, splitters, polarizers, and wave plates, the proposed sensor based on a common-path structure shows a high compactness. Using gratings with period of 3 µm, displacement measurement within a range of 1 mm is demonstrated experimentally. Associated with an interpolation circuit with subdividing factor of 4096, a resolution of 0.73 nm is obtained. The experimental results also show the ability for the sensor to detect in-plane vibration with frequency below 900 Hz. With a sub-nanometer resolution and an ultra-compact structure, the miniature sensor shows potential in applications such as high-precision machinery manufacturing and semiconductor processing.

나노 가공을 위한 듀얼 서보 시스템에 관한 연구

In the framework of the 4th industrial revolution, modern machine building rapidly converges with IOT technology. This requires a very high level of precision machining of parts and assemblies, such as electronics, vehicle and components, agricultural and construction machines, optical instruments, and machine tools. However, high precision machinery is considerably expensive, and so a general need for low-cost equipment exists. While many researchers study this, they focus mainly on cutting tools. This study, for its part, focused on compensating errors and enhancing machinery precision, by adding a servo controller to the processing unit. As a result, we designed a fine dual servo system, ensuring 10 nm positioning accuracy and 40 nm of surface roughness.

Numerical Simulation of Vapor-Liquid Two-Phase Saturated Steam Fluent Flow and Atomizing Jet Cleaning

In order to reduce the serious impact of polluting particles on the performance and quality of high-precision machinery and equipment, a cleaning system that uses saturated steam to clean the surface of parts and components is designed to achieve high cleanliness requirements. Based on the standard k-ε model, the large-scale fluid simulation software ANSYS is used to simulate the flow pattern of the steam nozzle to obtain the best distance for steam cleaning. According to the simulation results, a steam cleaning machine was developed and put into an automated cleaning production line to clean three different types of aviation parts. The residual masses of the parts were 0.1 mg, 0.1 mg, and 0.2 mg, and the maximum particle diameters were 549.461 μm, 275.464 μm, and 399.660 μm. The cleaning results show that the saturated steam cleaner can meet the cleaning requirements and get better surface quality parts after cleaning.

New applications for shape memory alloys in angular - contact ball bearings preloading systems

Shape Memory Alloys (SMA) have been researched extensively in the past forty years. The different available compositions of these alloys can make them suitable for certain applications with specific requirements. The increasing demand for high precision machinery and equipment brought forward the need to search for alloys that that can perform better under stress than conventional materials. This is the case of Shape Memory Alloys. As their name suggests, these alloys can regain their initial shape after being subjected to external stresses, up to a specific degree. Due to the research carried out over the past two decades on these alloys, they became better known and more accessible, being tested in order to be integrated in various applications. One such application consists of using a shape memory alloy formed into disc springs in order to optimize the preloading of angular contact ball bearings. The tests were conducted using a device especially developed for this research, with the purpose of recording the friction torque evolution and the preload induced by disc springs during the operation of the rolling bearings in order to assess the possibility of using elastic elements for active ball bearings preloading systems.

High-Precision Low-Cost Gimballing Platform for Long-Range Railway Obstacle Detection.

Increasing demand for rail transportation results in denser and more high-speed usage of the existing railway network, making new and more advanced vehicle safety systems necessary. Furthermore, high traveling speeds and the large weights of trains lead to long braking distances—all of which necessitates a Long-Range Obstacle Detection (LROD) system, capable of detecting humans and other objects more than 1000 m in advance. According to current research, only a few sensor modalities are capable of reaching this far and recording sufficiently accurate data to distinguish individual objects. The limitation of these sensors, such as a 1D-Light Detection and Ranging (LiDAR), is however a very narrow Field of View (FoV), making it necessary to use high-precision means of orienting to target them at possible areas of interest. To close this research gap, this paper presents a high-precision pointing mechanism, for the use in a future novel railway obstacle detection system, capable of targeting a 1D-LiDAR at humans or objects at the required distance. This approach addresses the challenges of a low target price, restricted access to high-precision machinery and equipment as well as unique requirements of our target application. By combining established elements from 3D printers and Computer Numerical Control (CNC) machines with a double-hinged lever system, simple and low-cost components are capable of precisely orienting an arbitrary sensor platform. The system’s actual pointing accuracy has been evaluated using a controlled, in-door, long-range experiment. The device was able to demonstrate a precision of 6.179 mdeg, which is at the limit of the measurable precision of the designed experiment.

Low-harmonic trajectory synthesis using trajectory pattern method (TPM) for high-speed and high-precision machinery

Abstract. In high-speed and high-precision machinery, trajectories with high-frequency harmonic content are one of the main sources of reduction of operational precision. Trajectories with high-frequency harmonic content generally demand even higher-harmonic actuating forces/torques due to the nonlinear dynamics of such systems, which may excite natural modes of vibration of the system and/or be beyond the dynamic response limitation of the actuation devices. In this paper, a global interpolation algorithm that uses the trajectory pattern method (TPM) for synthesizing low-harmonic trajectories is presented. The trajectory synthesis with the TPM is performed with a prescribed fundamental frequency and continuous jounce boundary condition, which would minimize the number of high-harmonic components in the required actuation forces/torques and avoid excitation of the system modes of vibration. The minimal curvature variation energy method, Lagrange multiplier method, and contour error control are used to obtain smooth kinematic profiles and satisfy the trajectory accuracy requirements. As an example, trajectory patterns that consist of a fundamental frequency sinusoidal time function and its first three harmonics are used to synthesize the desired trajectories for a selected dynamic system. The synthesized trajectories are shown to cause minimal system vibration during its operation. A comparison with a commonly used trajectory synthesis method clearly shows the superiority of the developed TPM-based approach in reducing vibration and demand on the actuator dynamic response, thereby allowing the system to operate at higher speeds and precision.

초정밀 가공을 위한 ECTS 제어에 관한 연구

In the framework of the 4th industrial revolution, modern machine-building rapidly converges with IOT technology. This requires very high precision machining of the parts and assemblies, such as electronics, vehicle and components, agricultural and construction machines, optical instruments, and machine tools. However, high precision machinery is quite expensive, and there exists a general need for low-cost equipment. While many researchers are working on this, their major focus is on cutting tools. This study aimed to compensate for errors and enhance machinery precision by adding a servo controller to the processing unit. Consequently, the study is on servo control and processing precision for processing utilizing ECTS (Error Compensation Tool Servo) to compensate for errors.

Missing value recovery for encoder signals using improved low-rank approximation

Rotary encoders have been increasingly equipped in high precision machinery, and their data missing may pose great challenges for both numeric control and health monitoring. In view of this limitation, a new methodology, termed improved low-rank approximation (ILRA), is proposed for encoder signal recovery. In this approach, phase space representation (PSR) is first introduced to transform the one-dimensional encoder signal into a matrix for low-rank exploration. Bidirectional centralization with cumulative energy ratio is then proposed to identify and extract the principal components embedded in phase space. Finally, an improved low-rank approximation scheme is employed to recover the missing values in an iterative manner. The performance of the proposed ILRA is evaluated by both simulation and experimental analysis. The results show that the proposed method can recover the missing values efficiently. Furthermore, the method yields satisfactory results for subsequent instantaneous angular speed estimation. Therefore, it may offer a promising tool for numerical data recovery in industrial applications.

Self-tuning MIMO disturbance feedforward control for active hard-mounted vibration isolators

This paper proposes a multi-input multi-output (MIMO) disturbance feedforward controller to improve the rejection of floor vibrations in active vibration isolation systems for high-precision machinery. To minimize loss of performance due to model uncertainties, the feedforward controller is implemented as a self-tuning generalized FIR filter. This filter contains a priori knowledge of the poles, such that relatively few parameters have to be estimated which makes the algorithm computationally efficient. The zeros of the filter are estimated using the filtered-error least mean squares (FeLMS) algorithm. Residual noise shaping is used to reduce bias. Conditions on convergence speed, stability, bias, and the effects of sensor noise on the self-tuning algorithm are discussed in detail. The combined control strategy is validated on a 6-DOF Stewart platform, which serves as a multi-axis and hard-mounted vibration isolation system, and shows significant improvement in the rejection of floor vibrations.

Three-dimensional fractal model of normal contact damping of dry-friction rough surface

According to the influence of the normal contact damping of joint surfaces on the dynamic characteristics of high-precision machinery (machine tool, robot, etc.), in this article, a three-dimensional fractal model of normal contact damping of dry-friction rough joint surfaces based on Hertz theory and fractal theory is established. The three-dimensional surface topography is constructed, according to the modified double variable Weierstrass–Mandelbrot function. The fractal model of strain energy [Formula: see text], dissipated energy [Formula: see text], damping loss factor [Formula: see text], and normal contact damping [Formula: see text] are deduced in detail, and the influence of fractal parameters and dynamic friction coefficient [Formula: see text] on them are simulated. The simulation curves show that strain energy [Formula: see text], dissipated energy [Formula: see text], damping loss factor [Formula: see text], and normal damping [Formula: see text] increase with the increase in the fractal roughness G; the influence of fractal dimension D on [Formula: see text] is more changeable, first [Formula: see text] decreases with the increase in D and then increases. [Formula: see text], [Formula: see text], and [Formula: see text] increase with the increase in D and [Formula: see text], respectively; the effect of [Formula: see text] on [Formula: see text] is not obvious, so simple change in [Formula: see text] has no significant change in [Formula: see text]; a comparative analysis of the theoretical calculation of normal damping and experimental results show that their general trend is consistent, and they increase with the increase in total normal contact load P, the relative error is 5%–25%. The theoretical model can provide reference for the design of normal contact damping of the joint surfaces.

Математическое моделирование процесса доводки прецизионных поверхностей упругих пластин с поверхностно-активными веществами

At present a significant problem at the production of high-precision machinery and devices is the ensuring of stability of quality specified parameters and increase of working productivity. The simultaneous achievement of these values may be obtained only at the expense of the destination of optimum modes and methods of manufacturing operations control for that there were necessary adequate mathematical models. The existing engineering processes are formed on determined procedures without taking into account a stochastic nature of a process and the interference of chemical and mechanical phenomena in the area of working. In the paper the mechanism of allowance removal at finishing with abrasive pastes having in their composition as fillers the surface-active matters as a factor defining the effectiveness of a finishing procedure is investigated. A process mathematical model is developed allowing the computation of material removal at any time at different algorithms of modes changes including parameters of a contact area, a current state of a surface layer in a blank. A model formed taking into account the process of passivation, machine cutting, takes into account a stochastic character of a process and allows estimating differentially the impact of separate factors upon material removal.

Mathematical Model Design on Online Virtual Processing Platform of Machinery Manufacturing

This paper designs the virtual online platform of high precision machinery processing. And we use it to forecast the safety coefficient k and lift coefficient of auto machining process, and based on the safety coefficient and the lift coefficient we improve the automobile working procedure real-time, and obtain a reasonable body safety structure and external driving performance of the structure, which achieves good comprehensive design effect. At the end of this paper, we apply the system in the online virtual platform of computer higher occupation education. According to the cycle mechanism of the lift coefficient, we design the teaching task of cultivating innovative talents, and arrange the teaching tasks of applied science. It provides the theory reference for research on the higher occupation school personnel training.

Research on Key Technology of Data Mining for Volleyball Game Based on Service System

During the processing of aircraft and other high precision machinery workpieces, if using the traditional machining methods, it will consume a amount of machining costs, and the mechanical processing cycle is long. In this context, this paper designs a kind of robot intelligent processing system with high precision machinery. And it has realized the intelligent online control on the machining process by using the high precision machining intelligent online monitoring technology and the numerical simulation prediction technology. Finally, this system is introduced into the process of data mining for volleyball game, and designs the partial differential variational data mining model, which has realized the key parameter data mining of volleyball games service system, and has provided reliable parameters and technical support for the training of volleyball players.

Development of an integrated look-ahead dynamics-based NURBS interpolator for high precision machinery

Methodologies for planning motion trajectory of parametric interpolation such as non-uniform rational B-spline (NURBS) curves have been proposed in the past. However, most of the algorithms were developed based on the constraints of feedrate, acceleration/deceleration (acc/dec), jerk, and chord errors. The errors caused by servo dynamics were rarely included in the design process. This paper proposes an integrated look-ahead dynamics-based (ILD) algorithm which considers geometric and servo errors simultaneously. The ILD consists of three different modules: a sharp corner detection module, a jerk-limited module, and a dynamics module. The sharp corner detection module identifies sharp corners of a curve and then divides the curve into small segments. The jerk-limited module plans the feedrate profile of each segment according to the constraints of feedrate, acc/dec, jerk, and chord errors. To ensure that the contour errors are bounded within the specified value, the dynamics module further modifies the feedrate profile based on the derived contour error equation. Simulations and experiments are performed to validate the ILD algorithm. It is shown that the ILD approach improves tracking and contour accuracies significantly compared to adaptive-feedrate and curvature-feedrate algorithms.

Effects of Restriction Characteristics on Characteristics of Air Suspension

In this study we make clear the characteristics of an air suspension with a flow channel connected from a cylinder to a reservoir tank. The flow resistance of channel is given by a viscous restriction or an orifice restriction. Differences between approximated analytical results, which are based on the 3-element model, of stiffness and damping coefficients of the air suspension with the viscous restriction and results of numerical analysis considering non-linear characteristics are very small. Moreover, the approximated analytical results of a transfer function of the air suspension and the experimental results of it are good well. Dependence of the oscillating amplitude on the maximum value of the transfer function of the air suspension system with the viscous restriction is very small since dependence of the oscillating amplitude on the stiffness and the damping is almost negligible. However, it depends on the oscillating amplitude of air suspension system with the orifice restriction because the damping coefficient of that decreases when the oscillating amplitude decreases. We can choose the optimal restriction coefficient of viscous restriction to minimize resonance amplitude easily. However, it is difficult to choose the optimal restriction coefficient of orifice restriction to minimize resonance amplitude because the oscillating amplitude often fluctuates generally. Thus, the air suspension with the viscous restriction is better for isolating the small vibration, in case of the high precision machinery.

Deformation, Alignment, and Vibration in Large Turbine-Generator Set

Within the Industrial Alignment Project (1990–93) and the Dynamic Alignment Project (1993–96), collaborative research and development efforts involving the department of geomatics engineering at The University of Calgary, the Natural Sciences and Engineering Research Council of Canada, and a number of industrial partners in western Canada, many high-precision machinery surveys have been carried out. In a project for one of the industrial partners, a number of epochs of deformation, alignment, and vibration measurements were made on a large turbine-generator set. Measurements were made in order to identify the root cause of high vibration levels. Analysis of these measurements reveals that high vibration levels are a result of a “soft foot” condition caused by structural weakness in the reinforced concrete table that supports the turbine-generator set. It was recommended that the owner consider stiffening the table by making solid (i.e. moment resisting) connections between the table and all supporting columns.

Close-range high-precision surveys for machinery alignment

Electronic theodolite systems can be used to carry out close-range high-precision machinery alignment surveys in near real time. Within the Industrial Alignment Project, a cooperative research and ...