Industry 4.1. Группа авторов

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2 Data Acquisition and Preprocessing

       Hao Tieng1, Haw‐Ching Yang2, and Yu‐Yong Li3

       1Associate Research Fellow, Intelligent Manufacturing Research Center, National Cheng Kung University, Tainan, Taiwan, ROC

       2Professor, Department of Electrical Engineering, National Kaohsiung University of Science and Technology, Kaohsiung City, Taiwan, ROC

       3Postdoctoral Research Fellow, Intelligent Manufacturing Research Center, National Cheng Kung University, Tainan, Taiwan, ROC

2.1 Introduction

      Various intelligent applications (such as predictive maintenance, virtual metrology, etc.) should be developed for achieving the goals of Intelligent Manufacturing. Taking predictive‐maintenance‐related applications as the illustrative examples, Chen et al. [1] installed one accelerometer, one acoustic emission (AE) sensor and two current sensors on a lathe to estimate the reliability, and remaining useful life (RUL) for cutting tools based on the logistic regression model using vibration signals. Suprock et al. [2] installed one strain gauge and one instrumentation amplifier with the Bluetooth transmitter on a cutting tool to calculate dynamic torque values, which are as accurate as the real measurements by the dynamometer. Ghosh et al. [3] developed an artificial neural network (ANN)‐based sensor fusion model for tool condition monitoring using cutting force, spindle vibration, spindle current, and sound pressure. Abuthakeer et al. [4] analyzed vibration signals based on the full factorial design and utilized ANN to validate the effect of cutting parameters on cutting tools during machining.

The fundamental steps for developing intelligent applications are depicted in Figure 2.1. As shown in Figure 2.1, before developing an intelligent application, the associated process/metrology data source needs to be acquired followed by appropriate data preprocessing. The main purposes of the aforementioned steps are briefly introduced in this subsection and more details can be found in the remaining subsections of Chapter 2.

Figure 2.1 Fundamental steps for developing an intelligent application.

       Data Acquisition

      Data СКАЧАТЬ