Volume 18 (2018): Edizione 2 (April 2018)

Software supported procedure for generation of long-time complex test sentences, suitable for testing the instruments for detection of standard voltage quality (VQ) disturbances is presented in this paper. This solution for test signal generation includes significant improvements of computer-based signal generator presented and described in the previously published paper [1]. The generator is based on virtual instrumentation software for defining the basic signal parameters, data acquisition card NI 6343, and power amplifier for amplification of output voltage level to the nominal RMS voltage value of 230 V. Definition of basic signal parameters in LabVIEW application software is supported using Script files, which allows simple repetition of specific test signals and combination of more different test sequences in the complex composite test waveform. The basic advantage of this generator compared to the similar solutions for signal generation is the possibility for long-time test sequence generation according to predefined complex test scenarios, including various combinations of VQ disturbances defined in accordance with the European standard EN50160. Experimental verification of the presented signal generator capability is performed by testing the commercial power quality analyzer Fluke 435 Series II. In this paper are shown some characteristic complex test signals with various disturbances and logged data obtained from the tested power quality analyzer.

The simplified metrological software test (MST) for modeling the method of determining the thermocouple (TC) error in situ during operation is considered in the paper. The interaction between the proposed MST and a temperature measuring system is also reflected in order to study the error of determining the TC error in situ during operation. The modelling studies of the random error influence of the temperature measuring system, as well as interference magnitude (both the common and normal mode noises) on the error of determining the TC error in situ during operation using the proposed MST, have been carried out. The noise and interference of the order of 5-6 μV cause the error of about 0.2-0.3°C. It is shown that high noise immunity is essential for accurate temperature measurements using TCs.

This paper presents a fundamental and accurate approach to study numerical analysis of fluid flow and heat transfer inside a channel. In this study, the Finite Element Method is used to analyze the channel, which is divided into small subsections. The small subsections are discretized using higher number of domain elements and the corresponding number of nodes. MATLAB codes are developed to be used in the analysis. Simulation results showed that the analyses of fluid flow and temperature are influenced significantly by the changing entrance velocity. Also, there is an apparent effect on the temperature fields due to the presence of an energy source in the middle of the domain. In this paper, the characteristics of flow analysis and heat analysis in a channel have been investigated.

High precision and high efficiency measurement is becoming an imperative requirement for a lot of mechanical parts. So in this study, a subpixel-level edge detection algorithm based on the Gaussian integral model is proposed. For this purpose, the step edge normal section line Gaussian integral model of the backlight image is constructed, combined with the point spread function and the single step model. Then gray value of discrete points on the normal section line of pixel edge is calculated by surface interpolation, and the coordinate as well as gray information affected by noise is fitted in accordance with the Gaussian integral model. Therefore, a precise location of a subpixel edge was determined by searching the mean point. Finally, a gear tooth was measured by M&M3525 gear measurement center to verify the proposed algorithm. The theoretical analysis and experimental results show that the local edge fluctuation is reduced effectively by the proposed method in comparison with the existing subpixel edge detection algorithms. The subpixel edge location accuracy and computation speed are improved. And the maximum error of gear tooth profile total deviation is 1.9 μm compared with measurement result with gear measurement center. It indicates that the method has high reliability to meet the requirement of high precision measurement.

The present paper covers a review of documents that specify measurement methods of voltage waveform distortion. It also presents measurement stages of waveform components that are uncommon in the classic fundamentals of electrotechnics and signal theory, including the creation process of groups and subgroups of harmonics and interharmonics. Moreover, the paper discusses selected distortion factors of periodic waveforms and presents analyses that compare the values of these distortion indices. The measurements were carried out in the cycle per cycle mode and the measurement methodology that was used complies with the IEC 61000-4-7 norm. The studies showed significant discrepancies between the values of analyzed parameters.

Magnetic resonance imaging (MRI) can precisely capture the anatomy of the vocal tract. However, the crowns of teeth are not visible in standard MRI scans. In this study, a marker-based teeth alignment method is presented and evaluated. Ten patients undergoing orthognathic surgery were enrolled. Supraglottal airways were imaged preoperatively using structural MRI. MRI visible markers were developed, and they were attached to maxillary teeth and corresponding locations on the dental casts. Repeated measurements of intermarker distances in MRI and in a replica model was compared using linear regression analysis. Dental cast MRI and corresponding caliper measurements did not differ significantly. In contrast, the marker locations in vivo differed somewhat from the dental cast measurements likely due to marker placement inaccuracies. The markers were clearly visible in MRI and allowed for dental models to be aligned to head and neck MRI scans.