Inserts
Deep Hole Drill Insert Wear Analysis
Deep Hole Drill Insert Wear Analysis
The deep hole drill insert is one of the most important components in the machining process.deep hole drill insert wear analysis Especially when drilling hard materials such as carbon steel or super alloys such as Inconel-718, the machining accuracy and hole quality depend heavily on the state of the insert. Therefore, it is very important to understand how the insert wears, and how its state changes with changing process parameters. This article presents an analysis of the deep hole drill insert wear using a wavelet fractal dimension (WFD) method, and it investigates the variation laws of WFD with deep hole drilling process parameters such as speed, feed, and drilling depth.
As a special field of machining, deep hole drilling requires very high performance tools and machines to achieve good results.deep hole drill insert wear analysis Amongst the key factors that affect the machining accuracy and hole surface quality are abnormal tool wear and the machinability of the material being processed. For example, spiral tool marks are produced on the hole bottom and wall when machining difficult-to-machine materials such as Inconel 718. In addition, chatter is a common phenomenon in the drilling process and can significantly influence the machining accuracy and quality of the hole.
To improve the machining accuracy and hole surface quality, it is critical to reduce the impact of abnormal wear on the drill inserts. Several methods have been proposed to detect and evaluate the abnormal wear state of the drill inserts, including the use of vibration sensors to measure the current signal from the spindle motor. However, all these methods have their limitations in that they cannot accurately capture the small fluctuations of the current signal and are prone to interference from other noise sources.
The use of a wavelet-based approach to analyzing the fractal dimension of the current signal offers the advantages of being non-intrusive, easy to implement, and highly effective in monitoring the machining state of the drill inserts. This method combines the properties of the binary wavelet function and fractal theory to estimate the fractal dimension of the current signal and provides the best correlation with the actual value. Furthermore, the WFD of the current signal can be directly displayed on the screen of the machine control system, making it easier to monitor and diagnose the machining condition of the drill inserts.
During deep hole drilling, the rake face of the cutting insert undergoes compression and friction contact with the drilled hole bottom, resulting in high contact stress and temperature, which decreases the red hardness of the rake edge. Flank wear on the chisel edge also influences the machining quality by causing poor centering of the chip in the drilled hole.
In order to increase the durability of the deep-hole drilling drills, various methods have been proposed, such as ion implantation, high pressure lubrication, and high-speed machining. However, most of these techniques require a complex and expensive tool system. As a result, only a limited number of industrial applications can apply these methods. In contrast, a new tool design that utilizes the characteristics of the BTA-type insert can significantly simplify and improve the deep-hole drilling process and provide more reliable and cost-effective processing.
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