In the paper there are presented tools for structural modelling of throttle diagrams that are developed as a basis to building transducers used for measuring fluid parameters. The definitions of throttle diagrams are improved and their classification is developed. Dependences are obtained to calculate the number of measuring channels in a throttle diagram and the number of possible variants of measuring transducers using the combinatory apparatus. A procedure for mathematical description of throttle diagrams in the form of graphs is proposed which makes it possible to obtain all diagrams with different measuring channels on the basis of certain throttle diagram. The model is developed in the form of a graph. A schematic diagram and a mathematical model of a transducer measuring physical and mechanical parameters of Bingham plastic fluid are developed based on a throttle diagram.
Knowledge of gravitational acceleration in metrology is required for traceable force and pressure calibrations, furthermore the redefinition of the SI base unit of kilogram requires absolute accomplishment of the gravitational acceleration. A direct free-fall gravimeter is developed using pneumatic grippers for test mass handling and a semi-rotary actuator for repositioning, i.e. automated re-launching. The catch and release system is powered by compressed air. This eliminates electric interferences around the test mass. A simplified method of signal capturing and processing is used on the designed gravimeter. A digital frequency trigger is implemented in the post processing algorithms to ensure that the signals are analysed from the identical effective height. The experimental results measured the site gravitational acceleration of 9.786043 ms��2 with a statistical uncertainty of #6;29 ms��2.
This paper presents two methods for evaluation of the effective wavenumber of nearly-Gaussian beams in laser interferometers that can be used for determination of a so called diffraction correction in absolute gravimeters. The first method, that can be simply used in situ, is an empirical procedure based on the evaluation of the variability of g measurements against the amount of light limited by an iris diaphragm and transmitted to a photodetector. However, precision of this method depends on the beam quality similarly as in the case of the conventional method based on measurement of a beam width. The second method, that is more complex, is based on beam profiling in various distances and on calculation of the effective wavenumber using the second spatial derivative of a non-ideal beam field envelope. The measurement results achieved by both methods are presented on an example of two absolute gravimeters and the determined diffraction corrections are compared with the results obtained by measurements of beam width. Agreement of methods within about 1 mGal have been obtained with average diffraction corrections slightly exceeding +2 mGal for three FG5(X) gravimeter configurations.
A mode-locked Tm3+-doped fibre laser and amplifier operating at a central wavelength of 1994.3 nm is demonstrated. A thulium oscillator is passively mode-locked by a semiconductor saturable absorber mirror to generate an average power of 17 mW at a fundamental repetition rate of 81 MHz in a short linear cavity. This 2-mm laser train is amplified to an average power to 20.26 W by two double-clad thulium-doped allfibre amplifiers. The pulse energy, duration and peak power is 250 nJ, 23 ps and 9.57 kW, respectively. This represents one of the highest values of average power at #24; 2-mm-wavelength for picosecond thulium-doped fibre lasers and amplifiers. The performance of the laser system is described in details.
The field of mechanical manufacturing is becoming more and more demanding on machining accuracy. It is essential to monitor and compensate the deformation of structural parts of a heavy-duty machine tool. The deformation of the base of a heavy-duty machine tool is an important factor that affects machining accuracy. The base is statically indeterminate and complex in load. It is difficult to reconstruct deformation by traditional methods. A reconstruction algorithm for determining bending deformation of the base of a heavy-duty machine tool using inverse Finite Element Method (iFEM) is presented. The base is equivalent to a multi-span beam which is divided into beam elements with support points as nodes. The deflection polynomial order of each element is analysed. According to the boundary conditions, the deformation compatibility conditions and the strain data measured by Fiber Bragg Grating (FBG), the deflection polynomial coefficients of a beam element are determined. Using the coordinate transformation, the deflection equation of the base is obtained. Both numerical verification and experiment were carried out. The deflection obtained by the reconstruction algorithm using iFEM and the actual deflection measured by laser displacement sensors were compared. The accuracy of the reconstruction algorithm is verified.
Terrestrial laser scanning (TLS) is one of the instruments for remote detection of damage of structures (cavities, cracks) which is successfully used to assess technical conditions of building objects. Most of the point clouds analysis from TLS relies only on spatial information (3D–XYZ). This study presents an approach based on using the intensity value as an additional element of information in diagnosing technical conditions of architectural structures. The research has been carried out in laboratory and field conditions. Its results show that the coefficient of laser beam reflectance in TLS can be used as a supplementary source of information to improve detection of defects in constructional objects.
The three-dimensional (3D) coordinate measurement of radio frequency identification (RFID) multi-tag networks is one of the important issues in the field of RFID, which affects the reading performance of RFID multi-tag networks. In this paper, a novel method for 3D coordinate measurement of RFID multitag networks is proposed. A dual-CCD system (vertical and horizontal cameras) is used to obtain images of RFID multi-tag networks from different angles. The iterative threshold segmentation and the morphological filtering method are used to process the images. The template matching method is respectively used to determine the two-dimensional (2D) coordinate and the vertical coordinate of each tag. After that, the 3D coordinate of each tag is obtained. Finally, a back-propagation (BP) neural network is used to model the nonlinear relationship between the RFID multi-tag network and the corresponding reading distance. The BP neural network can predict the reading distances of unknown tag groups and find out the optimal distribution structure of the tag groups corresponding to the maximum reading distance. In the future work, the corresponding in-depth research on the neural network to adjust the distribution of tags will be done.
A concept of a highly sensitive and fast-response airborne optoelectronic hygrometer, based on the absorption spectroscopy with laser light tuned to an intense ro-vibronic absorption line of H2O in the 1391– 1393 nm range is presented. The target application of this study is airborne atmospheric measurements, in particular at the top of troposphere and in stratosphere. The cavity ring-down spectroscopy was used to achieve high sensitivity. In order to avoid interference of the results by water desorbed from the instrument walls, the open-path solution was applied. Tests of the instrument, performed in a climatic chamber, have shown some advantages of this concept over typical hygrometers designed for similar applications.
Automatic gender detection is a process of determining the gender of a human according to the characteristic properties that represent the masculine and feminine attributes of a subject. Automatic gender detection is used in many areas such as customer behaviour analysis, robust security system construction, resource management, human-computer interaction, video games, mobile applications, neuro-marketing etc., in which manual gender detection may be not feasible. In this study, we have developed a fully automatic system that uses the 3D anthropometric measurements of human subjects for gender detection. A Kinect 3D camera was used to recognize the human posture, and body metrics are used as features for classification. To classify the gender, KNN, SVM classifiers and Neural Network were used with the parameters. A unique dataset gathered from 29 female and 31 male (a total of 60 people) participants was used in the experiment and the Leave One Out method was used as the cross-validation approach. The maximum accuracy achieved is 96.77% for SVM with an MLP kernel function.
Understanding the factors that influence the quality of unmanned aerial vehicle (UAV)-based products is a scientifically ongoing and relevant topic. Our research focused on the impact of the interior orientation parameters (IOPs) on the positional accuracy of points in a calibration field, identified and measured in an orthophoto and a point cloud. We established a calibration field consisting of 20 materialized points and 10 detailed points measured with high accuracy. Surveying missions with a fixed-wing UAV were carried out in three series. Several image blocks that differed in flight direction (along, across), flight altitude (70 m, 120 m), and IOPs (known or unknown values in the image-block adjustment) were composed. The analysis of the various scenarios indicated that fixed IOPs, computed from a good geometric composition, can especially improve vertical accuracy in comparison with self-calibration; an image block composed from two perpendicular flight directions can yield better results than an image block composed from a single flight direction.
Real-time monitoring of deformation of large structure parts is of great significance and the deformation of such structure parts is often accompanied with the change of curvature. The curvature can be obtained by measuring changes of strain, surface curve and modal displacement of the structure. However, many factors are faced with difficulty in measurement and low sensitivity at a small deformation level. In order to measure curvature in an effective way, a novel fibre Bragg grating (FBG) curvature sensor is proposed, which aims at removing the deficiencies of traditional methods in low precision and narrow adjusting. The sensor combines two FBGs with a specific structure of stainless steel elastomer. The elastomer can transfer the strain of the structure part to the FBG and then the FBG measures the strain to obtain the curvature. The performed simulation and experiment show that the sensor can effectively amplify the strain to the FBG through the unique structure of the elastomer, and the accuracy of the sensor used in the experiment is increased by 14% compared with that of the FBG used for direct measurement.
The paper presents a method of measuring the angle of rotation and twist using a tilted fibre Bragg grating (TFBG) periodic structure with a tilt angle of 6◦, written into a single-mode optical fibre. It has been shown that the rotation of the sensor by 180◦ causes a change in the transmission coefficient from 0.5 to 0.84 at a wavelength of 1541.2 nm. As a result of measurements it was determined that the highest sensitivity can be obtained for angles from 30◦ to 70◦ in relation to the basic orientation. The change in the transmission spectrum occurs for cladding modes that change their intensity with the change in the polarization of light propagating through the grating. The same structure can also be used to measure the twist angle. The possibility of obtaining a TFBG twist by 200◦ over a length of 10 mm has been proved. This makes it possible to monitor both the angle of rotation and the twist of an optical fibre with the fabricated TFBG.
The advance of MEMS-based inertial sensors successfully expands their applications to small unmanned aerial vehicles (UAV), thus resulting in the challenge of reliable and accurate in-flight alignment for airborne MEMS-based inertial navigation system (INS). In order to strengthen the rapid response capability for UAVs, this paper proposes a robust in-flight alignment scheme for airborne MEMS-INS aided by global navigation satellite system (GNSS). Aggravated by noisy MEMS sensors and complicated flight dynamics, a rotation-vector-based attitude determination method is devised to tackle the in-flight coarse alignment problem, and the technique of innovation-based robust Kalman filtering is used to handle the adverse impacts of measurement outliers in GNSS solutions. The results of flight test have indicated that the proposed alignment approach can accomplish accurate and reliable in-flight alignment in cases of measurement outliers, which has a significant performance improvement compared with its traditional counterparts.
Conventionally, the filtering technique for attitude estimation is performed using gyros or attitude dynamics models. In order to extend the application range of an attitude filter, this paper proposes a quaternionbased filtering framework for gyroless attitude estimation without an attitude dynamics model. The attitude estimation system is established based on a quaternion kinematic equation and vector observation models. The angular velocity in the system is determined through observation vectors from attitude sensors and the statistical properties of the angular velocity error are analysed. A Kalman filter is applied to estimate the attitude error such that the effect from the angular velocity error is compensated with its statistical properties at each sampling moment. A numerical simulation example is presented to illustrate the performance of the proposed algorithm.
This paper presents a novel sideslip angle estimator based on the pseudo-multi-sensor fusion method. The kinematics-based and dynamics-based sideslip angle estimators are designed for sideslip angle estimation. Also, considering the influence of ill-conditioned matrix and model uncertainty, a novel sideslip angle estimator is proposed based on the wheel speed coupling relationship using a modified recursive least squares algorithm. In order to integrate the advantages of above three sideslip angle estimators, drawing lessons from the multisensory information fusion technology, a novel thinking of sideslip angle estimator design is presented through information fusion of pseudo-multi-sensors. Simulations and experiments were carried out, and effectiveness of the proposed estimation method was verified.
Beamforming is an advanced signal processing technique used in sensor arrays for directional signal transmission or reception. The paper deals with a system based on an ultrasound transmitter and an array of receivers, to determine the distance to an obstacle by measuring the time of flight and – using the phase beamforming technique to process the output signals of receivers for finding the direction from which the reflected signal is received – locates the obstacle. The embedded beam-former interacts with a PID-based line follower robot to improve performance of the line follower navigation algorithm by detecting and avoiding obstacles. The PID (proportional-integral-derivative) algorithm is also typically used to control industrial processes. It calculates the difference between a measured value and a desired set of points, then attempts to minimize the error by adjusting the output. The overall navigation system combines a PID-based trajectory follower with a spatial-temporal filter (beamformer) that uses the output of an array of sensors to extract signals received from an obstacle in a particular direction in order to guide an autonomous vehicle or a robot along a safe path.
The micro-Particle Image Velocimetry (micro-PIV) was used to measure flow velocities in micro-channels in two passive micromixers: a microfluidic Venturi mixer and a microfluidic spiral mixer, both preceded by standard “Y” micromixers. The micro-devices were made of borosilicate glass, with micro-engineering techniques dedicated to micro-PIV measurements. The obtained velocity profiles show differences in the flow structure in both cases. The micro-PIV enables understanding the micro-flow phenomena and can help to increase reproducibility of micromixers in mass production.
The task of generating fast and accurate three-dimensional (3D) models of objects or scenes through a sequence of non-calibrated images is an active field of research. The recent development in algorithm optimization has resulted in many automatic solutions that can provide an accurate 3D model from texture-full objects. Structure-from-motion (SfM) is an image-based method that uses discriminative point-based feature identifier, such as SIFT, to locate feature points in the images. This method faces difficulties when presented with the objects made of homogenous or texture-less surfaces. To reconstruct such surfaces a well-known technique is to apply an artificial variety by covering the surface with a random texture pattern prior to the image capturing process. In this work, we designed three series of image patterns which are tested based on the contrast and density ratio which increases from the first to the last pattern within the same series. The performance of the patterns is evaluated by reconstructing the surface of a texture-less object and comparing it with the true data. Using the best-found patterns from the experiments, a 3D model of a Moai statue is reconstructed. The experimental results demonstrate that the density and structure of a pattern highly affects the quality of the reconstruction.