A Frontier Statistical Approach Towards Online Tool Condition Monitoring and Optimization for Dry Turning Operation of SAE 1015 Steel

• Autorzy: Moganapriya Chinnasamy , Rajasekar Rathanasamy , Gobinath Velu Kaliyannan , Prabhakaran Paramasivam , Jaganathan Saravana Kumar

Identyfikatory

DOI

10.24425/amm.2021.136396

• Języki publikacji: EN

Abstrakty

EN

This research study intends to develop an online tool condition monitoring system and to examine scientifically the effect of machining parameters on quality measures during machining SAE 1015 steel. it is accomplished by adopting a novel microflown sound sensor which is capable of acquiring sound signals. The dry turning experiments were performed by employing uncoated, TiAlN, TiAlN/WC-C coated inserts. The optimal cutting conditions and their influence on flank wear were determined and predicted value has been validated through confirmation experiment. During machining, sound signals were acquired using Ni DAQ card and statistical analysis of raw data has been performed. Kurtosis and I-Kaz coefficient was determined systematically. The correlation between flank wear and I-Kaz coefficient was established, which fits into power-law curve. The neural network model was trained and developed with least error (3.7603e-5). It reveals that the developed neural network can be effectively utilized with minimal error for online monitoring.

Słowa kluczowe

EN

coated inserts; microflown sensor; flank wear; I-Kaz; neural network

• Wydawca: Institute of Metallurgy and Materials Science of Polish Academy of Sciences ; Committee of Materials Engineering and Metallurgy of Polish Academy of Sciences
• Czasopismo: Archives of Metallurgy and Materials
• Rocznik: 2021
• Tom: Vol. 66, iss. 3
• Strony: 901--909
• Opis fizyczny: Bibliogr. 19 poz., fot., rys., tab., wykr.

Twórcy

autor

Moganapriya Chinnasamy

• Kongu Engineering College, Department of Mechanical Engineering, Perundurai - 638060, Tamil Nadu State, India

• https://orcid.org/0000-0003-0635-3328

autor

Rajasekar Rathanasamy

• Kongu Engineering College, Department of Mechanical Engineering, Perundurai - 638060, Tamil Nadu State, India

• https://orcid.org/0000-0002-6539-1466

autor

Gobinath Velu Kaliyannan

• Kongu Engineering College, Department of Mechatronics Engineering, Perundurai - 638060, Tamil Nadu State, India

• https://orcid.org/0000-0002-0393-3012

autor

Prabhakaran Paramasivam

• Kongu Engineering College, Department of Mechanical Engineering, Perundurai - 638060, Tamil Nadu State, India

• https://orcid.org/0000-0003-3575-6118

autor

Jaganathan Saravana Kumar

• Bionanotechnologyresearch Group, Ton Duc Thang University, Ho Chi Minh City, Vietnam
• Faculty of Applied Sciences, Ton Duc Thang University, Ho Chi Minh City, Vietnam
• Department of Engineering, Faculty of Science and Engineering, University of Hull, HU6 7RX, United Kingdom

• https://orcid.org/0000-0002-2785-137X

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).