Tool Wear Monitoring in Turning Processes Using Vibratory Analysis

Abstract

The main objective of this paper is to develop a signal processing strategy using vibratory signals in order to provide an efficient tool wear monitoring system able to increase machining performance. The method is based on the changes in the vibration signatures acquired during the turning operation over the tool life. Several signal processing techniques based on time and frequency domain analysis are proposed in order to extract a large number of indicators of the cutting tool state as variance, kurtosis, skewness, and coherence function. In this work, one of the innovative results is the tracking of tool wear by variance and coherence estimation. All of these indicators are correlated and validated by using white light interferometry measurements. This paper focuses on the technologies used in monitoring conventional cutting operations and presents important findings related to this field.

Condition monitoring of the uncoated carbide cutting tool in turning process of the aluminum alloy 6061 via vibration

“…Many of experiments has been carried out to correlate tool wear and the vibration signal produced. The results does show the tool wear are sensitive to the vibration signature features extracted from the time and frequency domain [5][6][7]. In prevoius study, the main purpose of vibration analysis is to identify the features indicative of tool wear.…”

Study on the Cause and Mechanism of Repeating Noise According to the Curing Conditions of Electrodeposition Coating

“…In the automotive market, the interior quietness of a car is as important as its driving performance. Noise and vibration are major concerns for many mechanical devices, household appliances, buildings, and especially automobiles . Meanwhile, noise and vibration are advantageous for their uses in medical diagnosis and the safety diagnosis of machinery and buildings .…”

An automatic system based on vibratory analysis for cutting tool wear monitoring

“…However, to provide a fast response to an unexpected tool failure in order to prevent possible damage to the workpiece, the sensing signals from the cutting process provide one of the most promising methods. The majority of these techniques involve the use of cutting force [4][5][6], motor power [7,8], acoustic emission [9,10] and vibratory signals [11][12][13][14][15][16].…”