The current solutions for pose estimation problems using coplanar feature points (PnP problems) can be divided into non-iterative and iterative solutions. The accuracy, stability, and efficiency of iterative methods are unsatisfactory. Therefore, non-iterative methods have become more popular. However, the non-iterative methods only consider the correspondence of the feature points with their 2D projections. They ignore the constraints formed between feature points. This results in lower pose estimation accuracy and stability. In this work, we proposed an accurate and stable pose estimation method considering the line constraints between every two feature points. Our method has two steps. In the first step, we solved the pose non-iteratively, considering the correspondence of the 3D feature points with their 2D projections and the line constraints formed by every two feature points. In the second step, the pose was refined by minimizing the re-projection errors with one iteration, further improving accuracy and stability. Simulation and actual experiment results show that our method’s accuracy, stability, and computational efficiency are better than the other existing pose estimation methods. In the -45° to +45° measuring range, the maximum angle measurement error is no more than 0.039°, and the average angle measurement error is no more than 0.016°. In the 0 mm to 30 mm measuring range, the maximum displacement measurement error is no more than 0.049 mm, and the average displacement measurement error is no more than 0.012 mm. Compared to other current pose estimation methods, our method is the most efficient based on guaranteeing measurement accuracy and stability. Keywords:

The properties of a mechanical resonator provide a valuable ability to measure liquid density and viscosity. The viscosity of liquids is of interest to researchers in both industry and medicine. In this paper, a viscosity sensor for liquids is proposed, which is designed based on an electromechanical resonator. In the proposed sensor, a capacitor is used as an electrostatic actuator. The capacitor is also used to monitor the frequency changes of the proposed resonator. The range of displacement of the resonator and capacitor in response to different fluids under test varies according to their viscosity. The design of the proposed sensor and its electrostatic and mechanical simulations are reported in this paper. Also, the effect of viscosity of several different liquids on its performance has been analyzed and presented experimentally using a prototype.

In the paper results of single- and double-pulse LIBS (Laser-Induced Breakdown Spectroscopy) measurements in collinear geometry are described. The experiments were performed using a unique self-made Nd:YAG laser operating in the Q-switching regime, where the laser transmission losses are switched. Such a laser allowed for an easy and quick change of the operating mode (one and two pulses), free shaping of the energy ratio of the two pulses (division of the energy of a single pulse into two parts) and a smooth change of the delay time between pulses in the range from 200 ns to 10 μs. To our knowledge, such a laser was used in LIBS measurements for the first time. LIBS experiments revealed strong self-absorption depending on energy ratios carried out in the first and second laser pulse in the double-pulse mode. This was confirmed also by statistical factorial analysis of LIBS spectra. Plasma temperature and LIBS signal enhancement were measured both for energy proportions between the first and the second laser pulse and for the first-to-second-pulse delay.

This document provides a simplified solution to the problem of calculation of laser hazard distances defined in the Advisory Circular 70-1B by the U.S. Federal Aviation Administration regarding atmospheric attenuation (assuming its constant value) and measurement uncertainties. The calculation approaches and examples presented in this document do not specify the procedure that should be followed in the case of atmospheric attenuation, nor do they take into account the uncertainties associated with the measured parameters. The analysis presented in the article complements to some extent AC 70-1B and can be used by those who need such a simplified solution regarding illumination of landing or taking off aircrafts. The article presents a sample analysis for a typical laser pointer, where the necessary parameters of the laser beam along with the appropriate uncertainties were determined in accordance with the methods accredited by the Polish Centre for Accreditation while the appropriate laser hazard distances were calculated taking into account different atmospheric attenuation coefficients.

In this work, a real-time label-free microwave sensing mechanism for glucose concentration monitoring using a planar biosensor configured with an inset fed microstrip patch antenna has been demonstrated. A microstrip patch antenna with the resonating frequency of 1.45 GHz has been designed and is fabricated on the Flame Retardant (FR-4) substrate. Due to the intense electromagnetic field at the edges of the patch antenna, edge length has been used as the detecting area where the sample under test (SUT) interacts with the electromagnetic field. The Poly-Dimethyl-Siloxane (PDMS) with the trench in the centre has been employed as the sample holder. Here, the SUT is the glucose dissolved in DI (de-ionized) water with the concentration range of 0.2 to 0.6 g/mL. The dielectric constant dependency on the glucose concentration has been used as the distinguishing factor which results in a shift in the S-parameter. The experimentally measured RF parameters were observed closely which showed the shift in S11 magnitude from –40 to –15 dB and resonant frequency from 1.27 to 1.3 GHz w.r.t the SUT solution of 0.2 to 0.6 g/mL with linear regression coefficient of 0.881, and 0.983 respectively.

Hydrogen storage for the purposes of the automotive industry in a form other than under high pressure or cryo conditions has been under careful investigation by researchers over past decades. One of the arising methods is the usage of powdered/granulated beds that contain metal hydrides and/or carbon materials to take advantage of the “spillover” phenomenon. Handling and characterization of such material can be troublesome, which is why the experimental setup needs careful investigation. The apparatus for the analysis of hydrogen sorption/desorption characteristics has been successfully designed and described based on the constructed unit within the scope of this article. The full functionality of that setup covered fuelling the bed as well as the examination of sorption/desorption potential. Moreover, the proposed experimental device can clarify many uncertainties about further development and optimization of hydrogen storage materials.

ZnS-based mechanoluminescent film has been widely used in the fields of stress visualization and stress sensing, due to its high brightness and repeatable stable luminescent characteristics. To evaluate the flexibleelastic deformation performance of ZnS-based mechanoluminescent film, both visual inspection and digital image correlation (DIC) are, respectively, employed for measuring the ZnS-based mechanoluminescent film. ZnS:Cu ²⁺ mechanoluminescent powders are first mixed with polydimethylsiloxane (PDMS) matrix to produce ZnS:Cu ²⁺–PDMS mechanoluminescent film. Then, two measurement experiments are, respectively, conducted to investigate the mechanical response and the flexible-elastic deformation performance of the prepared ZnS:Cu2+–PDMS mechanoluminescent film. On one hand, the mechanical response performance of the ZnS:Cu ²⁺–PDMS mechanoluminescent film is validated by visual monitoring of composite concrete fracture processes. On the other hand, the prepared ZnS:Cu ²⁺–PDMS mechanoluminescent film is also measured by DIC to obtain its full-field deformations and strains information. The flexible-elastic deformation performance of the ZnS:Cu ²⁺–PDMS mechanoluminescent film is well demonstrated by the DIC measured results.

Trueness and precision of a method for determining the water content (%) of food and chemical products based on infrared radiation with a wavelength in the range (2.70÷7.21 μm) was evaluated. The most accurate measurements for food products were obtained when the heat source was a radiant heater with a radiation wavelength of 7.21 μm, a trueness deviation of 0.01%. When heated with radiation with wavelengths (from 3.32 μm to 7.21 μm), the trueness of the measurement ranged (0.03% ÷0.13%) for chemical products. The shortest analysis time for food products was found when the analysis was carried out using an IR source with a wavelength of 7.21 μm, while for chemical products, a heat source with a wavelength of 2.70÷7.21 μm was optimal. According to the results of the analysis, the use of IR radiation with a wavelength range of 3.32÷7.21 μm is an alternative for accurate measurements.

A new solar tracking sensor based on image recognition is proposed and designed to solve the problem of low accuracy of photoelectric tracking in photovoltaic power generation. The sensor can directly output its angular deviation from the sun, and its mechanical structure and working principle are analysed in detail. We use a high-precision camera to collect the image of the two slots on the projector surface and use the Hough transform to identify the image of the light seam. After obtaining the linear equation for the two slots, the coordinate of the intersection point is found, and the calculation of the solar altitude and azimuth can be realized. We have improved the Hough transform scheme by using the skeleton image of the slots instead of the edge image. The improvement of the scheme has been proved to effectively improve the detection accuracy. A calibration test board is used to test the sensor and experimental results show that the scheme can achieve the measurement of azimuth and altitude with the accuracy of be 0.05°, which can meet the detection accuracy requirements of the solar tracking in photovoltaic power generation and many other photoelectric tracking implementations.

Online quantitative analysis of reaction gases or exhaust in industrial production is of great significance to improve the production capacity and process.Anovel method is developed for the online quantitative analysis of reaction gases or exhaust using quantitative mathematical models combined with the linear regression algorithm of machine learning. After accurately estimating the component gases and their contents in the reaction gases or exhaust, a ratio matrix is constructed to separate the relevant overlapping peaks. The ratio and calibration standard gases are detected, filtered, normalized, and linearly regressed with an online process mass spectrometer to correct the ratio matrices and obtain the relative sensitivity matrices. A quantitative mathematical model can be established to obtain the content of each component of the reaction gases or exhaust in real time. The maximum quantification error and relative standard deviation of the method are within 0.3% and 1%, after online quantification of the representative yeast fermenter tail gas.

Sleep apnea syndrome is a common sleep disorder. Detection of apnea and differentiation of its type: obstructive (OSA), central (CSA) or mixed is important in the context of treatment methods, however, it typically requires a great deal of technical and human resources. The aim of this research was to propose a quasi-optimal procedure for processing single-channel electroencephalograms (EEG) from overnight recordings, maximizing the accuracy of automatic apnea or hypopnea detection, as well as distinguishing between the OSA and CSA types. The proposed methodology consisted in processing the EEG signals divided into epochs, with the selection of the best methods at the stages of preprocessing, extraction and selection of features, and classification. Normal breathing was unmistakably distinguished from apnea by the k-nearest neighbors (kNN) and an artificial neural network (ANN), and with 99.98% accuracy by the support vector machine (SVM). The average accuracy of multinomial classification was: 82.29%, 83.26%, and 82.25% for the kNN, SVM and ANN, respectively. The sensitivity and precision of OSA and CSA detection ranged from 55 to 66%, and the misclassification cases concerned only the apnea type.