In the semiconductor manufacturing industry, efficient operation of wafer transfer robots has a direct impact on productivity and product quality. Ball screw misalignment anomalies are a critical factor affecting precision transport of robots. Early diagnosis of these anomalies is essential to maintaining system efficiency. This study proposed a method to effectively diagnose ball screw misalignment anomalies using 1D-CNN and 2D-CNN models. This method mainly uses binary classification to distinguish between normal and abnormal states. Additionally, explainable artificial intelligence (XAI) technology was applied to interpret diagnostic decisions of the two deep learning models, allowing users to convince prediction results of the AI model. This study was based on data collected through acceleration sensors and torque sensors. It compared accuracies of 1D-CNN and 2D-CNN models. It presents a method to explain the model"s predictions through XAI. Experimental results showed that the proposed method could diagnose ball screw misalignment anomalies with high accuracy. This is expected to contribute to the establishment of reliable abnormality diagnosis and preventive maintenance strategies in industrial sites.
The ball screw can be included in steering systems, the brake system, seat moving devices, and transmission systems of vehicles. Performance of the ball screw in these systems plays a key role in delivering agile and accurate power transmission. The purpose of this study is to improve performance by focusing on performance of the ball screw, by applying various conditions based on a design factor in the circulation system. The selected single design factor is to apply the cycloid curve to a circulation area. The circulation part to obtain a cycloid curve with highest performance, can have the smoothest ball flow. In addition, based on results, we intend to reduce failure cost that may be incurred in developing future ball screws for automobiles, and to establish databases that can be applied to developed products by deriving optimal shape.
This paper investigates the relationship between the preload level of a ball screw drive and the detected natural frequency of the system in an axial direction. A dynamic model to study the preload variation of the system is derived, and then a preload feature is proposed for extracting preload conditions based on the detected natural frequency of the system. A modified double-nut ball screw drive system with adjustable preload level is constructed. This is for the purpose of experimental verification. An accelerometer is attached to the ball screw nuts of the drive system to acquire vibration signals. The signals are analyzed to obtain the natural frequency of the ball screw drive system in an axial direction. By investigating the variation of the detected natural frequency, it is shown that the preload level can be diagnosed by the proposed preload feature. Both the experiment results and mathematical model show a direct correlation between the natural frequency and preload levels. Natural frequency increases when the preload level increases. This study provides a method to monitor the preload of a ball screw system which can be used as an indicator of the health status of the drive system.
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Elastic contact analysis and fatigue life prediction of ball screws in automotive REPS systems Helong Wu, Xinrong Long, Xiaoyan Peng, Zheng Zhang, Minwei Wan, Wei Wu, Wangxin Jiang Mechanics Based Design of Structures and Machines.2025; : 1. CrossRef
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The parallel slider system can be configured as a parallel robot by combining with other link devices. Therefore, the degree of positioning of the parallel slider would have considerable influence on the smooth operation of the parallel robot. In order to examine the degree of positioning of each slider, the following trajectory is equally presented, and the possibility of tracking the slider trajectory examined by application of the PD and PND control. From the experimental results, the dynamic characteristics of the slider show different responses to differing equivalent frictional forces acting on the slider. The PND control can make the rise time shorter than the PD control, and the PND control and PD control can smoothly follow the same trajectory given to each slider. It is therefore anticipated that the PND control and the PD control could be successfully implemented to follow the trajectory of a parallel robot based on a parallel slider system. It would then be necessary to fabricate slider experimental equipment capable of generating torque of sufficient magnitude to successfully reduce the trajectory error of the slider.
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