Kurumun Atıf Alan Makalesi
Atıf Alan Yayın
Investigation of signal behaviors for sensor fusion with tool condition monitoring system in turning
Scopus
Toplam 185 atıf DOI
Monitoring of the cutting area with different type of sensors requires confirmation for composing sensor fusion to obtain longer tool life and high-quality product. The complex structure of machining and interaction between variables affect the influence of parameters on quality indicators. Using multiple sensors provide comparison of information acquired from different resources and make easier to decide about tool and workpiece condition. In this experimental research for the first time, five different sensors were adopted to a lathe for collecting data to measure the capability of each sensor in reflecting the tool wear. Cutting forces, vibration, acoustic emission, temperature and current measurements were carried out during turning of AISI 5140 with coated carbide tools. Considering the graphical investigation, the successes of sensors on detection of progressive flank wear and tool breakage were investigated. Besides, the effects of cutting parameters on measured variables were interpreted considering graphs. According to results, temperature and acoustic emission signals seem to be effective about 74% for flank wear. In addition, fuzzy logic based prediction of flank wear was performed with the assistance of temperature and acoustic emission sensors with high accuracy which demonstrates their availability for sensor fusion. Tool breakage occurs instantly which can prevent with the assistance of sensor signals and tangential and feed cutting forces, acoustic emission and vibration signals seem as reliable indicators for approaching major breakage. Sensor fusion based turning provides confirmed information which enables more reliable, robust and consistent machining.
Atıf Kaynağı
Atıf Yapan Yayın
Estimation, optimization and analysis based investigation of the energy consumption in machinability of ceramic-based metal matrix composite materials
Scopus
Havuzumuzda Open Access 53 atıf almış
The current study aims to determine the influence of machining and production parameters during the milling of Cu/B–CrC composites. The relationship between energy consumption and cutting speed, feed rate and reinforcement ratio were investigated. For this purpose, 2d and 3d graphs for comparison of the effects of input parameters were demonstrated and analyzed. The predictability of the energy consumption during milling was measured by a fuzzy inference system (FIS). According to the graphical and optimization results, the optimum conditions to obtain the minimum energy consumption were 5% reinforcement ratio, 125 m/min cutting speed and 0.2 mm/rev feed rate. A reinforcement ratio of 52.71% was the most effective factor on energy demand followed by the feed rate (24.26%) and cutting speed (12.85%). According to the obtained results, there was a minor margin of error between the actual and predicted findings ranging from 1.6 to 2.4%. Considering the energy consumption is one of the key factors among machinability criteria, the study proposes a comprehensive approach for industrial and academic works.
Atıf Yapan Makale Bilgileri
Kurumlar (6)
Bingöl Üniversitesi
Bingol, Turkey
Inönü Üniversitesi
Malatya, Turkey
Politechnika Poznanska
Poznan, Poland
Selçuk Üniversitesi
Selçuklu, Turkey
South Ural State University
Chelyabinsk, Russian Federation
University of Portsmouth
Portsmouth, United Kingdom