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This paper examines factors affecting tool wear and a tool wear monitoring method using various sensors, such as accelerometers, force and acoustic emission sensors in micro-milling.
In this paper, a new statistical process monitoring method using dynamic independent component analysis (DICA) is proposed to overcome these disadvantages.
A monitoring method using the full spectral signals was more effective in evaluating the impact damages in detail than that using the center wavelength.
Furthermore, incorporating the non-linearity of the measurements as well as a state-space model, a spatio-temporal rainfall monitoring method using an extended Kalman filter (EKF) is described in [11].
Through this research, we propose to overcome such restrictions by implementing a contact less heart rate monitoring method using the real-time speech recordings based on different emotions of the patient.
The product ion spectra obtained were then compared to match with the standard solution samples (Supplementary Fig. S1) and with data from the published literature obtained with the multiple reaction monitoring method using a triple quadrupole instrument.
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The proposed monitoring method uses WiAMS devices and an array of embedded "smart aggregates" and externally bonded piezoelectric transducers.
Applying this property, it is shown in this paper the evolution of the power density monitoring methods, using neutron flux measurements in commercial reactors of the PWR type.
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