An equipment for calculating 2nd, 3rd, and higher order geometric moments by using accumulators, adders, subtractors, and multiplier blocks has been presented. The performance analysis of the proposed equipment with the existing systems in terms of speed and power dissipation has been carried out and has been shown that the computational time to calculate the geometric moments is reduced to half and the power dissipation is reduced by a factor of about 3 at a clock frequency of 10 MHz. The hardware has been implemented in BSIM4.3.0 50 nm technology operating at 1 V and its functionality has been verified using P-Spice simulator.
A new technique of x-ray focusing crystal spectrometers' calibration is the desired result. For this purpose the spectrometer is designed to register radiated copper Kα and Kβ lines by using a flat α-quartz crystal. This experiment uses pre-breakdown x-ray emissions in low vacuum of about 2.5-3 mbar. At this pressure the pinch will not form so the plasma will not radiate. The anode material is copper and the capacity of the capacitor bank is 22.6 nF. This experiment designed and mounted a repetitive triggering system to save the operator time making hundreds of shots. This emission amount is good for calibration and geometrical adjustment of an optical crystal x-ray focusing spectrometer.
Tapered fibre tips fabricated using mechanical polishing method is studied. The fibre tips are formed by sequential polishing flat-ended single mode fibres with decreasing aluminium oxide polishing film grit size. Based on the proposed technique, tapered fibre tips with cone angle ranging from 30° to 130° are fabricated by controlling the polishing angle. Besides the variety of cone angle, considerable smoothness of the fibre tip surface may assist in good metal coating and hence a well-defined aperture can be obtained. In addition, this paper presents a two-step hybrid fabrication method combining the proposed polishing method with chemical etching method to increase the possible fibre tip cone angles achievable by chemical etching method.
This article reports on the effect of aluminum (Al) volume fraction concentration on the thermal conductivity and thermal diffusivity of Al nanoparticles suspended in water, ethylene glycol, and ethanol based fluids prepared by the one step method. The Al nanoparticles were independently produced and then mixed with a base fluid to produce the nanoparticles suspension. The thermal conductivity and thermal diffusivity of the nanofluids were measured using the hot wire-laser beam displacement technique. The thermal conductivity and thermal diffusivity were obtained by fitting the experimental data to the numerical data simulated for Al in distilled water, ethylene glycol, and ethanol. The thermal conductivity and thermal diffusivity of the nanofluids increase with an increase in the volume fraction concentration.
The static (unloaded) electrical parameters of a capacitor bank are of utmost importance for the purpose of modeling the system as a whole when the capacitor bank is discharged into its dynamic electromagnetic load. Using a physical short circuit across the electromagnetic load is usually technically difficult and is unnecessary. The discharge can be operated at the highest pressure permissible in order to minimize current sheet motion, thus simulating zero dynamic load, to enable bank parameters, static inductance L(0), and resistance r(0) to be obtained using lightly damped sinusoid equations given the bank capacitance C(0). However, for a plasma focus, even at the highest permissible pressure it is found that there is significant residual motion, so that the assumption of a zero dynamic load introduces unacceptable errors into the determination of the circuit parameters. To overcome this problem, the Lee model code is used to fit the computed current trace to the measured current waveform. Hence the dynamics is incorporated into the solution and the capacitor bank parameters are computed using the Lee model code, and more accurate static bank parameters are obtained.
This article addresses time-domain ultrawide band (UWB) electromagnetic tomography for reconstructing the unknown spatial characteristic of an object from observations of the arrivals of short electromagnetic (EM) pulses. Here, the determination of the first peak arrival of the EM traces constitutes the forward problem, and the inverse problem aims to reconstruct the EM property distribution of the media. In this article, the finite-difference time-domain method implementing a perfectly matched layer is used to solve the forward problem from which the system sensitivity maps are determined. Image reconstruction is based on the combination of a linearized update and regularized Landweber minimization algorithm. Experimental data from a laboratory UWB system using targets of different contrasts, sizes, and shapes in an aqueous media are presented. The results show that this technique can accurately detect and locate unknown targets in spite of the presence of significant levels of noise in the data.
We investigate the enhancement of heat transfer in the nucleate boiling regime by inducing high frequency acoustic waves (f ∼ 10(6) Hz) on the heated surface. In the experiments, liquid droplets (deionized water) are dispensed directly onto a heated, vibrating substrate. At lower vibration amplitudes (ξs ∼ 10(-9) m), the improved heat transfer is mainly due to the detachment of vapor bubbles from the heated surface and the induced thermal mixing. Upon increasing the vibration amplitude (ξs ∼ 10(-8) m), the heat transfer becomes more substantial due to the rapid bursting of vapor bubbles happening at the liquid-air interface as a consequence of capillary waves travelling in the thin liquid film between the vapor bubble and the air. Further increases then lead to rapid atomization that continues to enhance the heat transfer. An acoustic wave displacement amplitude on the order of 10(-8) m with 10(6) Hz order frequencies is observed to produce an improvement of up to 50% reduction in the surface temperature over the case without acoustic excitation.
Hydrogen is a kind of promising clean energy resource with a wide application prospect, which will, however, cause a serious security issue upon the leakage of hydrogen gas. The measurement of its concentration is of great significance. In a traditional approach of ultrasonic hydrogen sensing, a temperature drift of 0.1 °C results in a concentration error of about 250 ppm, which is intolerable for trace amount of gas sensing. In order to eliminate the influence brought by temperature drift, we propose a feasible approach named as linear compensation algorithm, which utilizes the linear relationship between the pulse count and temperature to compensate for the pulse count error (ΔN) caused by temperature drift. Experimental results demonstrate that our proposed approach is capable of improving the measurement accuracy and can easily detect sub-100 ppm of hydrogen concentration under variable temperature conditions.
Top oil temperature (TOT) is an important parameter to evaluate the running state of a transformer. According to the variation trend of TOT, the internal thermal state of transformers can be predicted so as to arrange operation and maintenance reasonably and prevent the occurrence of accidents. However, due to the complex working environment in the field, there are often a large number of missing values in online monitoring data, which seriously affects the prediction of TOT. At the same time, it is affected by various factors such as load, ambient temperature, wind speed, and solar radiation, which cause the information of different time scales to be mixed in its monitoring data. Therefore, it is difficult to achieve the desired accuracy with a single model. In this article, a model for predicting TOT based on data quality enhancement is proposed. First, the Markov model is used to complete the online monitoring data containing missing values to obtain a complete and continuous time series. Then, using the ensemble empirical modal decomposition method, the time series of TOT is decomposed into multiple time series components to eliminate the interaction between different time scales of information, thus reducing the prediction difficulty. Finally, the sub-prediction model of the extreme learning machine is constructed, and the prediction results of all the sub-models are reconstructed to obtain the final prediction results of TOT. In order to verify the effectiveness of the model, the TOT of an operating transformer for the next two days is predicted in the article, and its mean absolute percentage error (MAPE) is 5.27% and its root mean square error (RMSE) is 2.46. Compared with the BP neural network model and the support vector machines (SVM) model, the MAPE is reduced by 69.56% and 61.92%, respectively, and the RMSE is reduced by 67.02% and 59.87%. The results of this study will provide important support for the fault diagnosis of the top oil temperature online monitoring system.
The stayed-cable is an important component of cable-stayed bridges, with cable force being a focal point during construction and bridge operation. The advancement of camera and image processing technology has facilitated the integration of computer vision technology in structural inspection and monitoring. This paper focuses on enhancing cable force measurement methods and addressing the limitations of traditional testing techniques by conducting experimental research on cable force estimation using video recording. The proposed approach involves capturing video footage of the target on the cable with a smartphone. Subsequently, a combination of techniques such as the background subtraction method, image morphology processing, and Hough transform image processing technology are employed to detect the precise center coordinates and ultimately obtain the accurate displacement-time curve of the cable's vibration. In addition, the graphic Circularity Coefficient (CC) has been introduced to assess its effectiveness in post-motion-blur image processing for circular targets. The fundamental frequency of the cable is determined by the fast Fourier transformation, and the relationship between the cable force and the fundamental frequency is used to estimate the cable force. The experimental results are compared with data from accelerometers and force gauges, demonstrating that the frequency measurement error is below 1.2% and the cable force test error is less than 3%. In the process of acquiring the cable's fundamental frequency, the test directly employs the pixel as the displacement unit, eliminating the need for image calibration. The innovative use of the CC in processing motion-blurred targets ensured accurate recognition of target coordinates. The experimental findings highlight the method's simplicity, speed, and accuracy.