Direct current coefficient is an essential parameter of I/V transducer, which directly affects the measurement results. Traditional method, comparing the measured transducer with the standard transducer, has limitations; failure to solve the problem in essence. To measure the direct current coefficient accurately, a measuring device was developed, which consists of direct current source, standard direct current ratio, adjustable standard direct current ratio, standard I/V transducer, voltage meter and null indicator. A measurement method was proposed, which fixes the value of direct current source and current flowing through the standard I/V transducer; adjusts the current through the high accuracy ratio conversion. The error measurement principle was employed to minimize the influence on the measurement results. Measure the current coefficient of an I/V transducer and restore its actual working state. The result shows that the current coefficients in the four current ranges are all negative, and are basically in the order of 10−5. The proposed method is characterized by breaking dependence on the superior standard device and meets the needs of precise measurement result correction.
In order to further support the development of arrayed impedance-based icing detection technology, a temperature drift self-compensation method that does not depend on traditional temperature sensors is proposed for the ice thickness measurement error problem caused by temperature variation. The method achieves compensation by establishing a mapping relationship between relaxation time and temperature to calculate the temperature of the ice layer. A theoretical model to describe the temperature drift characteristics of complex dielectric constant based on the relaxation polarization principle is established, and the ice layer temperature calculation method is proposed on the basis of complex impedance measurement. The experimental results show that the method reduces the error of ice thickness measurement, and the root mean square error reaches 0.09 mm in ice cases below 4 mm, which is clearly better than the uncompensated results.
Surface microwave field imaging is an important method for evaluating the performance of microwave/millimeter-wave monolithic integrated circuits. It is crucial to conduct the detection at the micro-nano scale. In the near-field scanning microwave microscopy system, the local signal of the surface radiation field is coupled with the tip signal, and the S11 curve related to the reflected signal is obtained. The curve exhibits varying degrees of sinusoidal oscillation as the radiation intensity changes at the specified position. The microwave intensity at this point is represented by the peak-to-peak value of the oscillation curve. Finally, the surface microwave intensity is mapped by scanning point by point. This method is crucial for evaluating the reliability of on-chip integrated circuit signal transmission and for the design and manufacture of devices.
Surface extraction from point clouds has many applications in product design, reverse engineering, industrial manufacturing and more. One of the key challenges is the detection and segmentation of overlapping areas of different surfaces. Existing methods are mainly on local judgment of similarity features, which can lead to either over- or under-segmentation. The proposed method in this paper utilizes DBSCAN for 3D point clouds surface extraction and boundary detection. Prior to extraction, the normal vector at sharp features is estimated based on a voting method. The surface extraction process is comprises two stages. First, the local quadric surface is determined based on the candidate sample points, and the points belonging to the same local surface are clustered. Second, in the merging stage, where the local surfaces are combined into a single smooth surface using three merging conditions. To demonstrate its effectiveness, the proposed approach is accessed on synthetic and real datasets, showing that the method can address the problem of insufficient and excessive segmentation of curved point clouds, and achieve high extraction accuracy.
Aiming at the problem that the current test items of China's electric data acquisition and testing laboratory are not in line with the actual use environment. This paper proposes a simulation scheme of electricity information acquisition link based on fault injection technology. Taking the intelligent electric meter as an example, this scheme uses fault injection technology such as signal interference and message tampering to simulate the abnormal working condition information of the field operation, and detects the function, performance and reliability of the intelligent electric meter in this environment. The comprehensive failure rate decreased by 75.64 % in different scenarios. In addition, the research also provides effective data support for the quality evaluation system of electric data acquisition of the intelligent electric meter, which can better meet the needs of electricity information collection in the actual use environment and improve the accuracy and reliability of detection.
