Mold Steel Grinding Process Application in Furniture Design Based on Machine Vision and Wireless Sensor Network Equipment

Abstract

With the continuous development of furniture design, the machining accuracy and surface quality of die steel have been paid more and more attention. The traditional grinding process has problems such as low efficiency and unstable quality, so it is urgent to introduce advanced technical means to improve the intelligent level of the processing process. This study aims to explore the application of the die steel grinding process based on machine vision and wireless sensor network equipment in furniture design, and improve the efficiency and quality of the grinding process through real-time monitoring and data analysis. A grinding monitoring platform integrating machine vision system and wireless sensor network was developed. A machine vision system is used to capture critical image data during the grinding process in real time, while a wireless sensor network is used to collect and transmit grinding parameters, including temperature, vibration and acoustic emission signals. By analyzing the acquired data, the optimized grinding parameters and control strategy are worked out. The experimental results show that the grinding process using machine vision and wireless sensor network has improved the relevant parameters compared with the traditional methods. The real-time monitoring capability of the system significantly reduces the failure rate during grinding and provides a more stable and reliable die steel processing solution for furniture design.