嵌入切削力及音訊感測功能之虎鉗開發

Abstract

本研究致力於開發一款嵌入切削力及音訊感測功能之虎鉗，以應對目前自動化加工過程中所遇到的各種加工問題。隨著自動化技術的普及，精確監控加工狀態變得相當重要，尤其是表面粗糙度和切削顫振等問題，對產品品質和加工穩定性的影響顯著。針對這些問題，本研究設計並開發了一種多感測器嵌入式虎鉗，旨在提高數據收集的準確性和即時性。 本研究將壓電材料作為切削力感測元件和微機電麥克風模組整合到虎鉗中，並設計電荷放大器以及利用資料擷取卡進行數據收集。這種嵌入式設計不僅簡化了感測器的安裝過程，還減少了機台停機時間和故障風險。為了驗證此設計的有效性，本研究進行了一系列切削實驗，並對嵌入式虎鉗的量測數據進行分析。 實驗結果顯示，嵌入式虎鉗在切削力和音訊量測方面具有足夠的精確度和穩定性，其性能與傳統商用感測器相當，甚至在一些方面更具優勢，例如，嵌入式設計使麥克風非常靠近切削點，能有效降低環境噪音對音訊數據的干擾，提高了數據的可靠性。此外，該設計在表面粗糙度預測的實際應用中展示出優異的能力，驗證了本研究之嵌入式虎鉗具有實際應用價值。 綜上所述，本研究開發的多感測器嵌入式虎鉗為切削加工過程的實時監控提供了一種可靠的替代方案，未來的研究可以進一步優化感測器設計和預測模型，以應對更多複雜的加工需求。

This study is dedicated to developing a vise embedded with cutting force and audio sensing functions to deal with various machining issues encountered in automated processing. With the popularization of automation technology, precise monitoring of machining conditions has become crucial, especially for problems such as surface roughness and chatter, which significantly affect product quality and machining stability. To tackle these issues, this study designs and develops a multi-sensor embedded vise, aiming to improve the accuracy and real-time collection of data. This study integrates piezoelectric materials as cutting force sensing elements and MEMS microphone modules into the vise. And designs the charge amplifier and uses the data acquisition card for data collection. This embedded design not only simplifies the sensor installation process but also reduces machine downtime and the risk of failures. To verify the effectiveness of this design, this study conducted a series of cutting experiments and analyzed the measurement data from the embedded vise. The experimental results show that the embedded vise demonstrates sufficient accuracy and stability in measuring cutting force and audio, with performance comparable to traditional commercial sensors. It even offers advantages in some aspects. For example, the embedded design puts the microphone very close to the cutting point, which can effectively reduce the interference of other noise on audio data and improve the reliability of the data. Furthermore, this design demonstrated excellent surface roughness prediction capability in practical applications, verifying that the embedded vise developed in this study has practical value. In conclusion, the multi-sensor embedded vise developed in this study provides a reliable alternative for real-time monitoring of the cutting process. Future research can further optimize sensor design and predictive models to cope with more complex machining requirements.