Real Time Tool Wear Condition Monitoring in Hard Turning of Inconel 718 Using Sensor Fusion System

被引:24
作者
Mali, Rahul [1 ]
Telsang, M. T. [2 ]
Gupta, T. V. K. [1 ]
机构
[1] Visvesvaraya Natl Inst Technol, Dept Mech Engn, Nagpur 440010, Maharashtra, India
[2] Rajarambapu Inst Technol, Dept Mech Engn, Islampur 415414, Sangli, India
关键词
Vibration; Force; Tool Wear; Sensor Fusion System; MATLAB; ACOUSTIC-EMISSION; OPERATIONS;
D O I
10.1016/j.matpr.2017.07.208
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The work presented here is an attempt to introduce a sensor based tool wear monitoring system for hard turning of Inconel718 material. Tool wear is a significant factor which influences surface finish, production time and economy of tooling. Hence, an online tool wear monitoring system has been developed using a sensor fusion system, consisting of a vibration sensor and a force based measurement system. Nine experimental runs based on L-9 orthogonal array of Taguchi method are performed and analysis of variance (ANOVA) is carried out to identify the significant parameters. The second part of the study include extended period turning operation performed till the tool is worn out completely. Both vibration and force signals are captured by a data acquisition system. The study shows that force data is quite useful to establish a strong correlation between the cutting force and tool wear. Cutting forces establishes a uniform correlation with tool wear which can effectively be used for online tool wear measurement. The effectiveness of these signals to predict tool wear has been established with a MATLAB based GUI that directly displays the real time tool wear. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:8605 / 8612
页数:8
相关论文
共 19 条
[1]   Optimizing power consumption for CNC turned parts using response surface methodology and Taguchi's technique - A comparative analysis [J].
Aggarwal, Aman ;
Singh, Hari ;
Kumar, Pradeep ;
Singh, Manmohan .
JOURNAL OF MATERIALS PROCESSING TECHNOLOGY, 2008, 200 (1-3) :373-384
[2]   On modeling of tool wear using sensor fusion and polynomial classifiers [J].
Deiab, Ibrahim ;
Assaleh, Khaled ;
Hammad, Firas .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2009, 23 (05) :1719-1729
[3]   Sensor signals for tool-wear monitoring in metal cutting operations - a review of methods [J].
Dimla, DE .
INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE, 2000, 40 (08) :1073-1098
[4]   Studies on Bayes classifier for condition monitoring of single point carbide tipped tool based on statistical and histogram features [J].
Elangovan, M. ;
Ramachandran, K. I. ;
Sugumaran, V. .
EXPERT SYSTEMS WITH APPLICATIONS, 2010, 37 (03) :2059-2065
[5]   Monitoring online cutting tool wear using low-cost technique and user-friendly GUI [J].
Ghani, J. A. ;
Rizal, M. ;
Nuawi, M. Z. ;
Ghazali, M. J. ;
Haron, C. H. C. .
WEAR, 2011, 271 (9-10) :2619-2624
[6]   Wear monitoring of single point cutting tool using acoustic emission techniques [J].
Kulandaivelu P. ;
Kumar P.S. ;
Sundaram S. .
Sundaram, S. (sundaram1160@gmail.com), 1600, Springer (38) :211-234
[7]   An intelligent sensor fusion system for tool monitoring on a machining centre [J].
Lou, KN ;
Lin, CJ .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 1997, 13 (08) :556-565
[8]   Optimization of Machining Parameters for End Milling of Inconel 718 Super Alloy Using Taguchi Based Grey Relational Analysis [J].
Maiyar, Lohithaksha M. ;
Ramanujam, R. ;
Venkatesan, K. ;
Jerald, J. .
INTERNATIONAL CONFERENCE ON DESIGN AND MANUFACTURING (ICONDM2013), 2013, 64 :1276-1282
[9]   Diagnostic approach for turning tool based on the dynamic force signals [J].
Oraby, SE ;
Al-Modhuf, AF ;
Hayhurst, DR .
JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME, 2005, 127 (03) :463-475
[10]  
Pratap Rudra, 2010, INTRO MATLAB 7