In this study, we use the inverse distance weighting algorithm to establish the solar irradiation estimation model. The model was built by obtaining information from 20 solar irradiation monitoring stations in central...
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ISBN:
(纸本)9781538643426
In this study, we use the inverse distance weighting algorithm to establish the solar irradiation estimation model. The model was built by obtaining information from 20 solar irradiation monitoring stations in central and southern Taiwan, and field verification was implemented at Yuan Chang Township town hall and Liujia Campus of Tainan. The Mean Absolute Percentage Error (MAPE) values of the solar irradiation estimation model at the two field verifications were 4.30% and 3.71% respectively.
Force and acceleration are the most well-known signals for the monitoring of milling vibration. However, the noncontact and low-cost microphone is also a potential choice for cutting vibration measurement. The superio...
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Force and acceleration are the most well-known signals for the monitoring of milling vibration. However, the noncontact and low-cost microphone is also a potential choice for cutting vibration measurement. The superior detection sensitivity of the microphone against milling dynamics was preliminarily verified. However, the limitations of microphones to record milling vibration have also been reported over the past two decades, such as the vibration identification accuracy under the influence of environmental noise. In this work, the microphone signal beyond 5 kHz is employed in the milling stability analysis to diminish the effect of low-frequency environmental noise. In addition, almost all current studies for cutting noise analyses are conducted without cutting fluid (dry cutting). This is far from most practical manufacturing processes. The cutting fluid is used in this work and a waterproof device is particularly designed to ensure the microphone operation against the cutting fluid. The microphone signal is analyzed on the basis of the scatter diagram of time domain (SDTD) to discuss the variation trend due to the milling stability. In addition, both the fast Fourier transform (FFT) and short-time Fourier transform (STFT) were employed to clarify the signal characteristics in the frequency domain. Finally, the finished workpiece surface was examined with the stability lobe diagram (SLD) to verify the acoustic analysis results.
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