NON-INVASIVE MONITORING SYSTEM FOR DETECTION OF TOOL WEAR IN POLYMER MILLING PROCESS

2021 ◽  
Author(s):  
Janaina Gonçalves ◽  
Roger Michels ◽  
Mayther Gimenez ◽  
Rafael Tanganini Boa Sorte ◽  
Elizabeth Mie Hashimoto
Keyword(s):  
Tool Wear ◽  
Monitoring System ◽  
Milling Process ◽  
Invasive Monitoring ◽  
Non Invasive

scholarly journals Methodology: non-invasive monitoring system based on standing wave ratio for detecting water content variations in plants

Plant Methods ◽  
2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Yunjeong Yang ◽  
Ji Eun Kim ◽  
Hak Jin Song ◽  
Eun Bin Lee ◽  
Yong-Keun Choi ◽  
...  
Keyword(s):  
Water Content ◽  
Monitoring System ◽  
Standing Wave ◽  
Magnetic Particles ◽  
Experimental Plant ◽  
Invasive Monitoring ◽  
Monitoring Method ◽  
Non Invasive ◽  
Content Variation ◽  
Stem Water

Abstract Background Water content variation during plant growth is one of the most important monitoring parameters in plant studies. Conventional parameters (such as dry weight) are unreliable; thus, the development of rapid, accurate methods that will allow the monitoring of water content variation in live plants is necessary. In this study, we aimed to develop a non-invasive, radiofrequency-based monitoring system to rapidly and accurately detect water content variation in live plants. The changes in standing wave ratio (SWR) caused by the presence of stem water and magnetic particles in the stem water flow were used as the basis of plant monitoring systems. Results The SWR of a coil probe was used to develop a non-invasive monitoring system to detect water content variation in live plants. When water was added to the live experimental plants with or without illumination under drought conditions, noticeable SWR changes at various frequencies were observed. When a fixed frequency (1.611 GHz) was applied to a single experimental plant (Radermachera sinica), a more comprehensive monitoring, such as water content variation within the plant and the effect of illumination on water content, was achieved. Conclusions Our study demonstrated that the SWR of a coil probe could be used as a real-time, non-invasive, non-destructive parameter for detecting water content variation and practical vital activity in live plants. Our non-invasive monitoring method based on SWR may also be applied to various plant studies.

Tool Wear Monitoring of High Speed Milling Based on Vibratory Signal Processing

2014 ◽  
Vol 565 ◽  
pp. 36-45
Author(s):  
Hadjadj Abdechafik ◽  
Kious Mecheri ◽  
Ameur Aissa
Keyword(s):  
Signal Processing ◽  
Tool Wear ◽  
Monitoring System ◽  
High Speed ◽  
Milling Process ◽  
Machining Performance ◽  
High Speed Milling ◽  
Tool Wear Estimation ◽  
On Line ◽  
Wear Monitoring

The objective of this study is to develop a process of treatment of the vibratory signals generated during a horizontal high speed milling process without applying any coolant in order to establish a monitoring system able to improve the machining performance. Thus, many tests were carried out on the horizontal high speed centre (PCI Météor 10), in given cutting conditions, by using a milling cutter with only one insert and measured its frontal wear from its new state that is considered as a reference state until a worn state that is considered as unsuitable for the tool to be used. The results obtained show that the first harmonic follow well the evolution of frontal wear, on another hand a wavelet transform is used for signal processing and is found to be useful for observing the evolution of the wavelet approximations through the cutting tool life. The power and the root mean square (RMS) values of the wavelet transformed signal gave the best results and can be used for tool wear estimation. All this features can constitute the suitable indicators for an effective detection of tool wear and then used for the input parameters of an on-line monitoring system. Nevertheless we noted the remarkable influence of the machining cycle on the quality of measurements by the introduction of a bias on the signal; this phenomenon appears in particular in horizontal milling and in the majority of studies is ignored

A real time non-invasive monitoring system for detection of hypovolemic state using RR interval variability in very low frequency ranges

2004 ◽  
Vol 58 ◽  
pp. S28-S30 ◽  
Author(s):  
Takemi Matsui ◽  
Bonpei Takase ◽  
Kousuke Hagisawa ◽  
Makoto Kikuchi ◽  
Minoru Suzuki ◽  
...  
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Low Frequency ◽  
Invasive Monitoring ◽  
Very Low Frequency ◽  
Non Invasive ◽  
Rr Interval

scholarly journals A Neuro-Fuzzy Approach Based Tool Condition Monitoring in AISI H13 Milling

2018 ◽  
Author(s):  
Md. Shafiul Alam ◽  
Maryam Aramesh ◽  
Stephen Veldhuis
Keyword(s):  
Tool Wear ◽  
Monitoring System ◽  
Condition Monitoring ◽  
Manufacturing Industry ◽  
Cutting Tool ◽  
Milling Process ◽  
Tool Condition Monitoring ◽  
Tool Wear Monitoring ◽  
Tool Condition ◽  
Wear Monitoring

In the manufacturing industry, cutting tool failure is a probable fault which causes damage to the cutting tools, workpiece quality and unscheduled downtime. It is very important to develop a reliable and inexpensive intelligent tool wear monitoring system for use in cutting processes. A successful monitoring system can effectively maintain machine tools, cutting tool and workpiece. In the present study, the tool condition monitoring system has been developed for Die steel (H13) milling process. Effective design of experiment and robust data acquisition system ensured the machining forces impact in the milling operation. Also, ANFIS based model has been developed based on cutting force-tool wear relationship in this research which has been implemented in the tool wear monitoring system. Prediction model shows that the developed system is accurate enough to perform an online tool wear monitoring system in the milling process.

scholarly journals Non-invasive monitoring system of synchronous generator using external field

2017 ◽  
Vol 16 (1) ◽  
pp. 70-89 ◽  
Author(s):  
H. F. dos Santos ◽  
M. Rigoni ◽  
R. de A. Elias ◽  
L. A. Feler ◽  
C. A. C. Wengerkievicz ◽  
...  
Keyword(s):  
External Field ◽  
Monitoring System ◽  
Synchronous Generator ◽  
Invasive Monitoring ◽  
Non Invasive
Sign in / Sign up

Export Citation Format

Share Document