Tool Wear Monitoring Using Microphone Signals and Recurrence Quantification Analysis when Drilling Composites

2013 ◽  
Vol 711 ◽  
pp. 239-244 ◽  
Author(s):  
Eshetu D. Eneyew ◽  
M. Ramulu
Keyword(s):  
Condition Monitoring ◽  
Cutting Tool ◽  
Flank Wear ◽  
Recurrence Quantification Analysis ◽  
Tool Condition Monitoring ◽  
Monitoring Method ◽  
Online Tool ◽  
Tool Condition ◽  
Quantification Analysis

The quality of the hole produced during the drilling of composite materials is one of the controlling factors for the resulting joint strength and integrity of the structural component. Quality of the hole depends on the condition of the cutting tool. Continuous cutting tool condition monitoring method is vital to accomplish the desired hole quality. To address this concern, an online tool condition monitoring technique using a simple audio microphone as a sensor is developed and Recurrence Quantification Analysis (RQA) methodology was used as a signal analysis tool to predict the tool condition in terms of flank wear. A series of experimental drilling operation was carried out on uni-directional carbon fiber reinforced plastic (CFRP) composite. It was found that the amplitude of the microphone signal decreases with the increase of the tool flank wear. In addition, from the selected eight RQA output variables, six of them show an increasing trend with the increase of the measured flank wear, whereas, two of them show a decreasing trend with the increase of tool wear. The same trend has been observed in both set of experiments. These results demonstrate that, this novel approach is an effective and economical online tool condition monitoring method.

Intelligent Tool Condition Monitoring System Based on Rough Sets and Mathematical Morphology

2007 ◽  
Vol 10-12 ◽  
pp. 722-726 ◽  
Author(s):  
Li Zhang ◽  
Shi Ming Ji ◽  
Yi Xie ◽  
Qiao Ling Yuan ◽  
Yin Dong Zhang ◽  
...  
Keyword(s):  
Tool Wear ◽  
Mathematical Morphology ◽  
Condition Monitoring ◽  
Rough Sets ◽  
Cutting Tool ◽  
Cutting Tools ◽  
Tool Condition Monitoring ◽  
Online Tool ◽  
Tool Condition ◽  
Condition Monitoring System

The image of cutting tools provides reliable information regarding the extent of tool wear. In this paper, we propose the theory of image processing based on rough sets and mathematical morphology to analyzing the flank faces which are chosen as our monitoring object. First, through plotting the appropriate subset, the rough sets filter is used to enhancement the image of tool wear. Then, the mathematical morphology theory is applied to process the translated binary image. Finally, tool condition monitoring is realized by measuring the area of tool wear. This paper gives the corresponding monitoring principal and proposes a new algorithm to process the cutting tool image. The algorithm is also flexible and fast enough to be implemented in real time for online tool wear or tool condition monitoring.

Development of multi sensor fusion based DAQ for in-process TCMS: Experimental and empirical analysis

2021 ◽  
pp. 095440892110580
Author(s):  
Balla Srinivasa Prasad ◽  
Aruna Prabha Kolluri ◽  
Rajesh B. Kumar ◽  
Medidi Rajasekhar
Keyword(s):  
Sensor Fusion ◽  
Condition Monitoring ◽  
Cutting Tool ◽  
Flank Wear ◽  
Tool Condition Monitoring ◽  
Sensor Data ◽  
Process Conditions ◽  
Vibration Signals ◽  
Thermal Images ◽  
Tool Condition

In order to manufacture low-cost, high-quality goods, in-process tool condition monitoring is an essential responsibility in the manufacturing industry. In this study, a multisensor fusion technique was used to build and execute an effective and reliable TCM system in turning operations with coated and uncoated tungsten carbide inserts. In dry turning, an attempt has been made to optimize the turning process parameter and monitor the tool's condition. Acoustic optic emission based sensor i.e., Laser Doppler Vibrometer and FLIR E60 infrared thermal camera are strategically placed near the machining zone. Thermal images and vibration signals are recorded using an appropriate charge amplifier. To extract characteristics from numerous sensor data, a National Instruments data acquisition (NI-DAQ) system is constructed utilizing LabVIEW software. Thermal images are used to gather temperatures from tool-work piece locations. Vibration signals are translated into vibration parameters. These characteristics serve as the foundation for establishing in-process TCMS. Tool wear, vibrational displacements (Disp), and cutting temperature are investigated as a result of varied tool insert materials and process conditions (CT). Utilizing ISO 10816-3, ISO 3685, and ISO-18434-2008 standards, the cutting tool condition was assessed using extracted features from multi sensor fusion techniques. For Ti-6Al-4 V, the displacement of uncoated and coated tools increased by 65.28% and 44.71%, respectively. For AISI 316L flank wear, the uncoated insert effected 41% and the coated insert impacted 24.14%, respectively. While machining Al7075, the relationship of depth of cut and feed rate on flank wear maintains an identical trend. It is discovered that both temperature and displacement have a significant role in the evolution of flank wear, which is examined in depth. This paper recognizes the use of multi-sensor data in tool condition monitoring when rotating with various cutting tool inserts.

Tool condition monitoring: unscented Kalman filter for tool flank wear estimation in turning of Inconel 718

2021 ◽  
pp. 1-13
Author(s):  
Chandrani Sadhukhan ◽  
Swarup Kumar Mitra ◽  
Ranjib Biswas ◽  
Mrinal Kanti Naskar
Keyword(s):  
Kalman Filter ◽  
Condition Monitoring ◽  
Inconel 718 ◽  
Flank Wear ◽  
Unscented Kalman Filter ◽  
Tool Condition Monitoring ◽  
Tool Flank Wear ◽  
Tool Condition

scholarly journals Acoustic Emission Studies on Carbon/Phenolic Ablative Composites using PCD and PCBN Tools

1999 ◽  
Vol 8 (3) ◽  
pp. 096369359900800 ◽  
Author(s):  
P. S. Sreejith ◽  
R. Krishnamurthy
Keyword(s):  
Acoustic Emission ◽  
Condition Monitoring ◽  
Cutting Tool ◽  
Tool Condition Monitoring ◽  
Tool Condition ◽  
The Status ◽  
Emission Studies ◽  
Pcbn Tools ◽  
Cutting Speeds ◽  
Phenolic Composite

During manufacturing, the performance of a cutting tool is largely dependent on the conditions prevailing over the tool-work interface. This is mostly dependent on the status of the cutting tool and work material. Acoustic emission studies have been performed on carbon/phenolic composite using PCD and PCBN tools for tool condition monitoring. The studies have enabled to understand the tool behaviour at different cutting speeds.

scholarly journals Metacognitive learning approach for online tool condition monitoring

2017 ◽  
Vol 30 (4) ◽  
pp. 1717-1737 ◽  
Author(s):  
Mahardhika Pratama ◽  
Eric Dimla ◽  
Chow Yin Lai ◽  
Edwin Lughofer
Keyword(s):  
Condition Monitoring ◽  
Tool Condition Monitoring ◽  
Learning Approach ◽  
Online Tool ◽  
Tool Condition ◽  
Metacognitive Learning

scholarly journals Researches regarding cutting tool condition monitoring

2017 ◽  
Vol 121 ◽  
pp. 02002
Author(s):  
Marinela Inţă ◽  
Achim Muntean ◽  
Sorin-Mihai Croitoru
Keyword(s):  
Condition Monitoring ◽  
Cutting Tool ◽  
Tool Condition Monitoring ◽  
Tool Condition

Enabling a cutting tool iPSS based on tool condition monitoring

2017 ◽  
Vol 94 (9-12) ◽  
pp. 3265-3274 ◽  
Author(s):  
Guohai Zhang ◽  
Huibin Sun
Keyword(s):  
Condition Monitoring ◽  
Cutting Tool ◽  
Tool Condition Monitoring ◽  
Tool Condition

TOOL CONDITION MONITORING SYSTEM IN SERIAL PRODUCTION CONDITIONS

2020 ◽  
Vol 4 (2) ◽  
pp. 161-168
Author(s):  
V.I. GOLOVIN ◽  
S.Yu. RADCHENKO
Keyword(s):  
Monitoring System ◽  
Condition Monitoring ◽  
Cutting Tool ◽  
Tool Condition Monitoring ◽  
Serial Production ◽  
Tool Condition ◽  
Decision Making System ◽  
Software And Hardware ◽  
Condition Monitoring System ◽  
The Cost

One of the most important tasks of serial and mass production is to maintain the continuity of the technological process in order to reduce equipment downtime and, as a result, the cost of production. One of the systems is the tool condition monitoring system. However, the solutions used today are complex software and hardware systems that are not available for most medium and small productions. The article proposes a system based on a comparative analysis of the applied tool with reference instances. The results of the analysis are sent to the decision-making system, which determines the feasibility of further use of the cutting tool for subsequent machining. An example of an experimental study of milling processing is given. The results obtained show the possibility and rationality of using this model to predict the state of the instrument.

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