No. 1

 Theoretical Problems of Measurement

    Pages

M. Kušnerová, J. Valíček, M. Harničárová, T. Hryniewicz, K. Rokosz, Z. Palková, V. Václavík, M. Řepka, M. Bendová:

A Proposal for Simplifying the Method of Evaluation of Uncertainties in Measurement Results

Abstract: The paper deals with the innovative ways of nonstandard, simplifying applications of the valid method for evaluating uncertainties in measurement results and with the definition of conditions of their usability. The evaluation of a substitute criterion for measurement accuracy by means of a relative difference between the measurand and its reference value is proposed. This nonstandard relative uncertainty is comparable with the overall relative standard uncertainty in the measurement result, and thus the evaluation of it enables other simplifications in the calculations of measurement result uncertainties. The use of the simplified evaluation of measurement results is illustrated in two experiments in measurement of the coefficient of thermal conductivity of an insulating material newly developed for the needs of building practice, namely measurement using commercial instruments, and measurement using a newly developed original measuring instrument.

Measurement in Biomedicine

P. Mishra, S. K. Singla:

Artifact Removal from Biosignal using Fixed Point ICA Algorithm for Pre-processing in Biometric Recognition

Abstract: In the modern world of automation, biological signals, especially Electroencephalogram (EEG) and Electrocardiogram (ECG), are gaining wide attention as a source of biometric information. Earlier studies have shown that EEG and ECG show versatility with individuals and every individual has distinct EEG and ECG spectrum. EEG (which can be recorded from the scalp due to the effect of millions of neurons) may contain noise signals such as eye blink, eye movement, muscular movement, line noise, etc. Similarly, ECG may contain artifact like line noise, tremor artifacts, baseline wandering, etc.  These noise signals are required to be separated from the EEG and ECG signals to obtain the accurate results. This paper proposes a technique for the removal of eye blink artifact from EEG and ECG signal using fixed point or FastICA algorithm of Independent Component Analysis (ICA). For validation, FastICA algorithm has been applied to synthetic signal prepared by adding random noise to the Electrocardiogram (ECG) signal. FastICA algorithm separates the signal into two independent components, i.e. ECG pure and artifact signal. Similarly, the same algorithm has been applied to remove the artifacts (Electrooculogram or eye blink) from the EEG signal.

  Measurement of Physical Quantities

E. Jarošová, E. Kureková:

Determination of Optimal Technological Parameters of a Compaction Process: Case Study

Abstract: Pelletizing as a complicated compaction process is under continuous improvement. One of the problems – determination of optimal technological parameters to attain a sufficiently high density of pellets - is solved in this paper. The statistical model of density depending on four technological factors is built based on data obtained through a central composite design. Canonical analysis is used to find the stationary point, and as the received point is a saddle point, the optimal setting is determined by means of ridge analysis. Special attention is paid to the uncertainty associated with the indirect measurement of the pellet density. Substantial differences in the density exist between pellets created under the same conditions, and especially the type-A uncertainty must be taken into consideration.

Zhiyong Li, Zhiqiang Sun:

Development of the Vortex Mass Flowmeter with Wall Pressure Measurement

Abstract: Mass flow measurement is essential to the understanding and control of processes concerning fluid flow. The availability of reliable mass flowmeters, however, is far inadequate to meet the demand. In this paper we developed a practical vortex mass flowmeter with wall pressure measurement. The meter coefficient of mass flow rate was acquired through experiments with air at Reynolds numbers from 1.3×103 to 9.8×103. Here we show that the meter coefficient of mass flow rate is nearly constant at Reynolds numbers greater than 5.5×103. To further extend the lower limit, a correction factor related to the Reynolds number was introduced into the vortex mass flowmeter. The results show that the relative errors of the vortex mass flowmeter developed are basically within ±5%. This device can satisfy a diversity of requirements of mass flow measurement in engineering fields.

Yanping Fan, Xiaojun Ji, Ping Cai, Qianhui Lu:

Non-Destructive Detection of Rebar Buried in a Reinforced Concrete Wall with Wireless Passive SAW Sensor

Abstract: In order to reduce the damage to the old reinforced concrete walls and work out the best construction scheme during the renovation of old buildings, it is often required to detect the position of rebar buried in concrete walls. In this paper, we propose a non-destructive method to detect the buried rebar by self-inductive sensor combined with surface acoustic wave resonator (SAWR). The proposed method has the advantages of wireless, passive and convenient operations. In our new design, the sensing element of self-inductance coil was made as a component of SAWR matching network. The distribution of rebar could be measured according to the system resonant frequency, using a signal demodulation device set. The depth of buried rebar and the deviation of output resonant frequency from inherent frequency of SAWR have an inverse relation. Finally, the validity of the method was verified in theoretical calculation and simulation.

A. Wozniak, M. Byszewski, M. Jankowski :

Setup for Triggering Force Testing of Touch Probes for CNC Machine Tools and CMMs

Abstract: Touch-trigger probes are commonly used both in coordinate measuring machines (CMM) and in computer numerical control (CNC) machine tools. In both cases accuracy of measurement of the overall system and probing unit are closely interrelated. Key parameters of the probes are repeatability and pre-travel variation dependent on adjustable stylus force. To enable testing of the triggering force of the probes, the new setup was developed. The principle of the method and set-up is presented and its validity is experimentally confirmed.

Hanshan Li, Zhiyong Lei:

Projectile Two-dimensional Coordinate Measurement Method Based on Optical Fiber Coding Fire and its Coordinate Distribution Probability

Abstract: To improve projectile coordinate measurement precision in fire measurement system, this paper introduces the optical fiber coding fire measurement method and principle, sets up their measurement model, and analyzes coordinate errors by using the differential method. To study the projectile coordinate position distribution, using the mathematical statistics hypothesis method to analyze their distributing law, firing dispersion and probability of projectile shooting the object center were put under study. The results show that exponential distribution testing is relatively reasonable to ensure projectile position distribution on the given significance level. Through experimentation and calculation, the optical fiber coding fire measurement method is scientific and feasible, which can gain accurate projectile coordinate position.

Li Bing-jie, Zhao Jia-hong, Wang Xu, Mohamode. Amuer, Wang Zhi-liang:

Research on Air Flow Measurement and Optimization of Control Algorithm in Air Disinfection System

Abstract: As the air flow control system has the characteristics of delay and uncertainty, this research designed and achieved a practical air flow control system by using the hydrodynamic theory and the modern control theory. Firstly, the mathematical model of the air flow distribution of the system is analyzed from the hydrodynamics perspective. Then the model of the system is transformed into a lumped parameter state space expression by using the Galerkin method. Finally, the air flow is distributed more evenly through the estimation of the system state and optimal control. The simulation results show that this algorithm has good robustness and anti-interference ability.

Xiu-zhi Meng, Zong-sheng Wang, Zeng-zhi Zhang, Feng-qian Wang:

A Method for Monitoring the Underground Mining Position Based on the Blasting Source Location

Abstract: Some small and medium-sized coal mines are mining beyond their mining boundary driven by profit. The illegal activities cause many mine disasters but effective supervision is very hard to achieve, especially for underground coal mining. Nowadays, artificial blasting operation is widely used in tunneling or mining in small and medium-sized coal mines. A method for monitoring the underground mining position by monitoring the blasting source position is firstly introduced in this paper. The blasting vibration waves are picked up by the detectors and dealt by the signal acquisition sub-station, and then sent to the principal computer. The blasting source is located by the principal computer and displayed in the mine’s electronic map. The blasting source position is located in 10 seconds after the first P wave reaching the detector, whose error is registered within 20 meters by field-proven method.  Auto-monitoring of the underground mining position in real-time is solved better and management level is improved using this method.

Top ↑

 Theoretical Problems of Measurement

I. Lira, D. Grientschnig

A Formalism for Expressing the Probability Density Functions of Interrelated Quantities

Abstract: In this paper we address measurement problems involving several quantities that are interrelated by model equations. Available knowledge about some of these quantities is represented by probability density functions (PDFs), which are then propagated through the model in order to obtain the PDFs attributed to the quantities for which nothing is initially known. A formalism for analyzing such models is presented. It comprises the concept of a „base parameterization“, which is used in conjunction with the change-of-variables theorem. The calculation procedure that results from this formalism is described in very general terms. Guidance is given on how to employ it in practice by presenting both an elementary example and a much more involved one.

  Measurement of Physical Quantities

Han Lianfu, Fu Changfeng, Wang Jun, Tang Wenyan

Outlier Detection and Correction for the Deviations of Tooth Profiles of Gears

Abstract: To decrease the influence of outlier on the measurement of tooth profiles, this paper proposes a method of outlier detection and correction based on the grey system theory. After studying the characteristics of outliers from the deviations of tooth profiles, this paper proposes a preprocessing method for the modeling data which include abnormal value, and establishes an outlier detection and correction model for the deviations of tooth profiles. Simulation results show that the precision of ONDGM(1,1)(one order and one variable non-homogenous discrete grey model whose outlier is processed by the preprocessing method proposed in this paper) is higher than that of NDGM(1,1)(one order and one variable non-homogenous discrete grey model), and the ONDGM(1,1) is more suitable than the NDGM(1,1) for dealing with the outliers from the deviations of tooth profiles. The experiment results show that the outlier detection and correction model detects and corrects the outliers from the deviations of tooth profiles, and the correction value of the outlier is basically in accordance with the actual deviation. Therefore, the method of outlier detection and correction decreases the influence of outlier and improves the precision in the measurement of tooth profiles.

J. Hrabina, J. Lazar, M. Holá, O. Číp

Investigation of Short-term Amplitude and Frequency Fluctuations of Lasers for Interferometry

Abstract: One of the limiting factors of accuracy and resolution in laser interferometry is represented by noise properties of the laser powering the interferometer. Amplitude and especially frequency fluctuations of the laser source are crucial in precision distance measurement. Sufficiently high long-term frequency stability of the laser source must be achieved especially in applications in fundamental metrology. Furthermore, the short-term frequency variations are also important primarily for measurements done at high acquisition speeds. This contribution presents practical results of measurements of short-term amplitude and frequency noises of a set of laser sources commonly used in laser interferometry. The influence of the interferometer design and electrical parameters of the detection system are also discussed.

M. R. I. Faruque, M. T. Islam, M. A. M. Ali

A New Design of Metamaterials for SAR Reduction

Abstract: The purpose of this paper is to calculate the reduction of specific absorption rate (SAR) with a new design of square metamaterials (SMMs). The finite-difference time-domain (FDTD) method with lossy-Drude model is adopted in this analysis. The method of SAR reduction is discussed and the effects of location, distance, and size of metamaterials are analyzed. SMMs have achieved a 53.06% reduction of the initial SAR value for the case of 10 gm SAR. These results put forward a guideline to select various types of metamaterials with the maximum SAR reducing effect for a cellular phone.

G. Genta, A. Astolfi, P. Bottalico, G. Barbato, R. Levi

Management of Truncated Data in Speech Transmission Evaluation for Pupils in Classrooms

Abstract: Speech intelligibility is a subjective performance index defined as the percentage of a message understood correctly. Often the results of speech intelligibility tests would suggest that conditions are acceptable, with Intelligibility Score (IS) of the order of 90% or more, while speech transmission performance may not be satisfactory. Subjective ratings of the Listening Easiness Score (LES), based on a discrete questionnaire, provide an alternative approach. A total of 239 primary school pupils, aged 7 to 11, evenly distributed among the grades, participated in the survey. The objective indicator Speech Transmission Index (STI) was also measured for each test setting in seven different positions in the laboratory classroom used for the test. Both IS and LES are inherently bounded, and their data distributions exhibit a significant accumulation of scores in the upper and lower parts. The resulting truncation problem has been addressed with a method based on the normal probability plot, enabling identification of mathematical models relating IS and LES to STI, as well as the estimation of related uncertainties. IS and LES exhibit substantially similar metrological capabilities, as, for both, model relative uncertainty does not exceed 4% and uncertainties in prediction of new observations are about twice as large.

Zhiqiang Sun, Shuai Shao, Hui Gong

Gas–liquid Flow Pattern Recognition Based on Wavelet Packet Energy Entropy of Vortex-induced Pressure Fluctuation

Abstract: Here we report a novel flow-pattern map to distinguish the gas–liquid flow patterns in horizontal pipes at ambient temperature and atmospheric pressure. The map is constructed using the coordinate system of wavelet packet energy entropy versus total mass flow rate. The wavelet packet energy entropy is obtained from the coefficients of vortex-induced pressure fluctuation decomposed by the wavelet packet transform. A triangular bluff body perpendicular to the flow direction is employed to generate the pressure fluctuation. Experimental tests confirm the suitability of the wavelet packet energy entropy as an ideal indicator of the gas–liquid flow patterns. The overall identification rate of the map is 92.86%, which can satisfy most engineering applications. This method provides a simple, practical, and robust solution to the problem of gas–liquid flow pattern recognition.

Deng-Fa Lin, Po-Hung Chen, Mike Williams

Measurement and Analysis of Current Signals for Gearbox Fault Recognition of Wind Turbine

Abstract: This paper presents a novel solution method based on measurement and analysis of current signals for gearbox fault recognition of wind turbine. A gearbox with typical oil-leakage fault is purposely made. The oil-leakage gearbox and a normal gearbox are used as experimental models to measure and analyze the current signals of generator. This work employs wavelet transform (WT), empirical mode decomposition (EMD) and fast Fourier transform (FFT) to analyze the current signals for both the oil-leakage and the normal gearboxes. K-nearest neighbors (KNN) is used on automatic fault recognition. First, the normal gearbox and the oilleakage gearbox are separately applied to practical power platform experiments. Second, empirical mode decomposition is applied on analyzing the intrinsic mode function (IMF) of the current signals, and fast Fourier transform is used to get the intrinsic mode function spectrum. Finally, the features of the spectrum are extracted, and K-nearest neighbors is used on gearbox fault recognition of wind turbine. Experimental results indicate that the proposed solution method can effectively recognize the oilleakage fault of gearboxes.

Shaosheng Fan, Qingchang Zhong

Prediction of Fouling in Condenser Based on Fuzzy Stage Identification and Chebyshev Neural Network

Abstract: The prediction of fouling in condenser is heavily influenced by the periodic fouling process and dynamics change of the operational parameters, to deal with this problem, a novel approach based on fuzzy stage identification and Chebyshev neural network is proposed. In the approach, the overall fouling is separated into hard fouling and soft fouling, the variation trends of these two kinds of fouling are approximated by using Chebyshev neural network, respectively, in order to make the prediction model more accurate and robust, a fuzzy stage identification method and adaptive algorithm considering external disturbance are introduced, based on the approach, a prediction model is constructed and experiment on an actual condenser is carried out, the results show the proposed approach is more effective than asymptotic fouling model and adaptive parameter optimization prediction model.

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 Theoretical Problems of Measurement

A. Meo, L. Profumo, A. Rossi, M. Lanzetta

Optimum Dataset Size and Search Space for Minimum Zone Roundness Evaluation by Genetic Algorithm

Abstract: Roundness is one of the most common features in machining. The minimum zone tolerance (MZT) approach provides the minimum roundness error, i.e. the minimum distance between the two concentric reference circles containing the acquired profile; more accurate form error estimation results in less false part rejections. MZT is still an open problem and is approached here by a Genetic Algorithm. Only few authors have addressed the definition of the search space center and size and its relationship with the dataset size, which greatly influence the inspection time for the profile measurement and the convergence speed of the roundness estimation algorithm for a given target accuracy. Experimental tests on certified roundness profiles, using the profile centroid as the search space center, have shown that the search space size is related to the number of dataset points and an optimum exists, which provides a computation time reduction up to an order of magnitude.

  Measurement of Physical Quantities

Chun-Yao Lee, Cheng-Chien Kuo, Ryan Liu, I-Hsiang Tseng, Lu-Chen Chang

Detection of Gearbox lubrication Using PSO-Based WKNN

Abstract: This paper proposes an optimization classification model, which combines particle swarm optimization (PSO) with weighted k-nearest neighbors (WKNN), namely PWKNN. The model optimizes the weight and k parameter of WKNN to improve the detection accuracy of gearbox lubrication levels. In the experiment, the current signals of the generator are measured, and the relative frequency spectrum of the measured signals is illustrated by using fast Fourier transform (FFT). The features from the spectrum are extracted, and then the optimal weight and k parameter of WKNN are obtained by using PSO. The average detection accuracy of gearbox lubrication levels is 96% by using PWKNN, which the result shows that the proposed PWKNN can efficiently detect the lubrication level of gearboxes. The experiment also shows that the performance of the proposed PWKNN by using the current signals of the generator is superior to that by using typical vibration signals of a gearbox. In addition, the accuracy can reach 95.4% even in environments with 20 dB noise interference.

K. Arun Venkatesh, N. Mathivanan

CAN Network Based Longitudinal Velocity Measurement Using Accelerometer and GPS Receiver for Automobiles

Abstract:  A design of Controller Area Network (CAN) based longitudinal velocity measurement system using MEMS accelerometer and GPS receiver is presented. CAN is a serial communication protocol which efficiently supports distributed control system with high level of security. The system consists of a master node and a slave node built around LPC1768 and LPC2129 microcontrollers respectively. The master and slave nodes are linked with CAN bus. The slave node gets velocity data from GPS receiver and transfers to the master node. The master node samples the accelerometer output, and saves the sampled data and the velocity data received from the slave node on a microSD card.   A LabVIEW program has been developed to study the measured parameters in offline by applying a Kalman filter and computing the estimate of longitudinal velocity. Typical measurements with the present system in a standard driving maneuvers and computation of estimate of longitudinal velocity using the LabVIEW program are presented. The measurement system produces comparable results with the conventional meter.

Jian Wu, Zhiming Cui, Victor S. Sheng, Pengpeng Zhao, Dongliang Su, Shengrong Gong

A Comparative Study of SIFT and its Variants

Abstract:  SIFT is an image local feature description algorithm based on scale-space. Due to its strong matching ability, SIFT has many applications in different fields, such as image retrieval, image stitching, and machine vision. After SIFT was proposed, researchers have never stopped tuning it. The improved algorithms that have drawn a lot of attention are PCA-SIFT, GSIFT, CSIFT, SURF and ASIFT. In this paper, we first systematically analyze SIFT and its variants. Then, we evaluate their performance in different situations: scale change, rotation change, blur change, illumination change, and affine change. The experimental results show that each has its own advantages. SIFT and CSIFT perform the best under scale and rotation change. CSIFT improves SIFT under blur change and affine change, but not illumination change. GSIFT performs the best under blur change and illumination change. ASIFT performs the best under affine change. PCA-SIFT is always the second in different situations. SURF performs the worst in different situations, but runs the fastest.

Measurement in Biomedicine

Dongliang Su, Jian Wu, Zhiming Cui, Victor S. Sheng, Shengrong Gong

CGCI-SIFT: A More Efficient and Compact Representation of Local Descriptor

Abstract:  This paper proposes a novel invariant local descriptor, a combination of gradient histograms with contrast intensity (CGCI), for image matching and object recognition. Considering the different contributions of sub-regions inside a local interest region to an interest point, we divide the local interest region around the interest point into two main sub-regions: an inner region and a peripheral region. Then we describe the divided regions with gradient histogram information for the inner region and contrast intensity information for the peripheral region respectively. The contrast intensity information is defined as intensity difference between an interest point and other pixels in the local region. Our experimental results demonstrate that the proposed descriptor performs better than SIFT and its variants PCA-SIFT and SURF with various optical and geometric transformations. It also has better matching efficiency than SIFT and its variants PCA-SIFT and SURF, and has the potential to be used in a variety of real-time applications.

Muhammad Ibn Ibrahimy, Md. Rezwanul Ahsan, Othman Omran Khalifa

Design and Optimization of Levenberg-Marquardt based Neural Network Classifier for EMG Signals to Identify Hand Motions

Abstract:  This paper presents an application of artificial neural network for the classification of single channel EMG signal in the context of hand motion detection. Seven statistical input features that are extracted from the preprocessed single channel EMG signals recorded for four predefined hand motions have been used for neural network classifier. Different structures of neural network, based on the number of hidden neurons and two prominent training algorithms, have been considered in the research to find out their applicability for EMG signal classification. The classification performances are analyzed for different architectures of neural network by considering the number of input features, number of hidden neurons, learning algorithms, correlation between network outputs and targets, and mean square error. Between the Levenberg-Marquardt and scaled conjugate gradient learning algorithms, the aforesaid algorithm shows better classification performance. The outcomes of the research show that the optimal design of Levenberg-Marquardt based neural network classifier can perform well with an average classification success rate of 88.4%. A comparison of results has also been presented to validate the effectiveness of the designed neural network classifier to discriminate EMG signals.

V. Novickij, A. Grainys, J. Novickij

Finite Element Method Analysis of Microfluidic Channel with Integrated Dielectrophoresis Electrodes for Biological Cell Permeabilization and Manipulation

Abstract: The microfluidic channel with a planar inductive microcoil for the cell membrane permeabilization and the integrated planar electrodes for cell dielectrophoretic manipulation is proposed and analyzed in the study. The analyzed setup is based on the dielectrophoretic entrapment of the biological cell followed by membrane permeabilization using high pulsed magnetic field. The finite element method analysis of the DEP force and the generated pulsed magnetic field is performed. Based on finite element method analysis the potential applications of the setup in the fields of drug delivery, biomedicine and biotechnology are discussed.

E. Pinheiro, O. Postolache, P. Girão

Contactless Impedance Cardiography Using Embedded Sensors

Abstract:  Impedance cardiography is a technique developed with the intent of monitoring cardiac output. By inspecting a few properties of the obtained signal (impedance cardiogram (ICG), the left ventricular ejection time can be derived with certainty, and an estimate of cardiac output is available. This signal is nowadays used in non-invasive monitoring, requiring the placement of electrodes over the subject’s skin, either ECG-type or in the form of encircling bands. The work here reported describes the implementation steps and the results obtained when embedding the ICG circuitry in a wheelchair’s backrest. The subject is seated normally, is normally dressed, and is completely unaware that monitoring is taking place. That means that the variation of tenths of ohm produced due to the cardiac cycle has to be detected with electrodes having substantial coupling impedance. Contactless ICG with embedded sensors was developed and tested on fourteen healthy subjects. The signal was always acquired, although respiratory activity is also important, constituting a noteworthy innovation in the area.

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  Measurement of Physical Quantities

 165-168

D. Gogola, A. Krafčík, O. Štrbák, I. Frollo

Magnetic Resonance Imaging of Surgical Implants Made from Weak Magnetic Materials

Abstract:  Materials with high magnetic susceptibility cause local inhomogeneities in the main field of the magnetic resonance (MR) tomograph. These inhomogeneities lead to loss of phase coherence, and thus to a rapid loss of signal in the image. In our research we investigated inhomogeneous field of magnetic implants such as magnetic fibers, designed for inner suture during surgery. The magnetic field inhomogeneities were studied at low magnetic planar phantom, which was made from four thin strips of magnetic tape, arranged grid-wise. We optimized the properties of imaging sequences with the aim to find the best setup for magnetic fiber visualization. These fibers can be potentially exploited in surgery for internal stitches. Stitches can be visualized by the magnetic resonance imaging (MRI) method after surgery. This study shows that the imaging of magnetic implants is possible by using the low field MRI systems, without the use of complicated post processing techniques (e.g., IDEAL).

Ahmed Toaha Mobashsher, Mohammad Tariqul Islam

Design, Investigation and Measurement of A Compact Ultra Wideband Antenna for Portable Applications

Abstract:  The design of a printed compact planar antenna of asymmetrical structure with ultra wide bandwidth is described and investigated in this paper. The antenna provides more than 114% impedance bandwidth below VSWR 2 (from 3.3 to more than 12 GHz) with a center frequency of 7.65 GHz; thus it covers the bandwidth requirement for portable UWB wireless device applications. The structure of the asymmetric proposed antenna is very simple and composed of a small hexagonal shaped patch with two asymmetrical coplanar ground planes. It occupies an area of only 20 × 24.5 mm2 when printed on one side of an FR4 substrate with a thickness of 1.6 mm.

J. Mohan, V. Krishnaveni, Yanhui Guo

A New Neutrosophic Approach of Wiener Filtering for MRI Denoising

Abstract:  In this paper, a new filtering method based on neutrosophic set (NS) approach of wiener filter is presented to remove Rician noise from magnetic resonance image. A neutrosophic set, a part of neutrosophy theory, studies the origin, nature and scope of neutralities, as well as their interactions with different ideational spectra. Now, we apply the neutrosophic set into image domain and define some concepts and operators for image denoising. The image is transformed into NS domain, described using three membership sets: True (T), Indeterminacy (I) and False (F). The entropy of the neutrosophic set is defined and employed to measure the indeterminacy. The ω-wiener filtering operation is used on T and F to decrease the set indeterminacy and remove noise. The experiments have conducted on simulated Magnetic Resonance images (MRI) from Brainweb database and clinical MR images corrupted by Rician noise. The results show that the NS wiener filter produces better denoising results in terms of visual perception, qualitative and quantitative measures compared with other denoising methods, such as classical wiener filter, the anisotropic diffusion filter, the total variation minimization scheme and non local means filter.

Bo Wu, Ping Cai

Decoupling Analysis of a Sliding Structure Six-axis Force/Torque Sensor

Abstract: This paper analyzes the decoupling of a sliding structure six-axis force/torque sensor, which is used to measure the interactive force between surgical tools and soft tissue for the establishment of soft-tissue force model. Because this decoupling structure requires accurate sliding clearance and symmetric grooves, the influence of contact force between the elastic body and the groove sidewall on decoupling is analyzed. The analysis results indicate that the contact force will produce additional coupling error. The robust design method of elastic body size optimization is used to eliminate the influence of contact force. In the calibration test, the expanded uncertainty of the calibration device is evaluated and the calibration results validate the good decoupling.

Shugui Liu, Hongling Zhang, Yinghua Dong, Shaliang Tang, Zhenzhu Jiang

Portable Light Pen 3D Vision Coordinate Measuring System-Probe Tip Center Calibration

Abstract: For different tasks, probe tip should be changed in the 3D vision coordinate measuring system and the accurate determination of probe tip center position is critical. A novel and simple approach for calibrating the probe tip center position of the light pen is presented in this paper. Hundreds of images of the light pen with different postures are collected while the probe tip is kept in firm contact with a reference conical hole. The probe tip position is determined by computing the rotation matrix and translation vector from the obtained images by using the least square fitting method. The experimental results demonstrate the effectiveness of the proposed approach. Its repeatability reaches 0.033 mm, 0.030 mm, and 0.043 mm in x, y, and z axes, respectively, and its convergence speed is satisfactory.

Wang Tong, Wu Jiyi, Xu He, Zhu Jinghua, Charles Munyabugingo

A Cross Unequal Clustering Routing Algorithm for Sensor Network

Abstract: In the routing protocol for wireless sensor network, the cluster size is generally fixed in clustering routing algorithm for wireless sensor network, which can easily lead to the “hot spot” problem. Furthermore, the majority of routing algorithms barely consider the problem of long distance communication between adjacent cluster heads that brings high energy consumption. Therefore, this paper proposes a new cross unequal clustering routing algorithm based on the EEUC algorithm. In order to solve the defects of EEUC algorithm, this algorithm calculating of competition radius takes the node’s position and node’s remaining energy into account to make the load of cluster heads more balanced.  At the same time, cluster adjacent node is applied to transport data and reduce the energy-loss of cluster heads.  Simulation experiments show that, compared with LEACH and EEUC, the proposed algorithm can effectively reduce the energy-loss of cluster heads and balance the energy consumption among all nodes in the network and improve the network lifetime.

P. Mlynek, J. Misurec, M. Koutny

Random Channel Generator for Indoor Power Line Communication

Abstract: The paper deals with creating an indoor power line model based on random parameters. This model approximates the real parameters of the power line communication with sufficient precision. A detailed analysis of earlier and current research in power line communication modelling, especially for power line models, is described. Measurement of transmission line parameters and power line model verification follows. Based on model analysis and load impedance measurement, a mathematical description of the model is designed. A reference model for different scenarios is realized too. The last part gives the analysis of this model and simulation results.

Jin Guofeng, Zhang Wei, Shi Jun, Yang Zhengwei, Hu Yu, Huang Zhiyong, Tian Gan

Numerical Analysis of Influencing Factors and Capability for Thermal Wave NDT in Liquid Propellant Tank Corrosion Damage Detection

Abstract: Due to the disadvantages of traditional NDT methods for liquid propellant tank corrosion detection, Thermal Wave Nondestructive Testing (ITWNDT) technology was applied. The heat exchange process of thermal wave in corrosion tank was simulated by the numerical method. Parameters of TWNDT as the best detection time (tbest), the maximum surface temperature difference (ΔTmax), and the temperature difference holding time (τΔT>0.1) were discussed as the targets. Based on these parameters, factors influencing the detection results of tank materials, dressed liquid (also considered as the corrosion product), pit characters (depth and size), heat flux and thermal excitation time length (pulsed width), environmental conditions and other factors were analyzed. Simulation results show that ITWNDT can identify the defect depth, size and position rapidly and effectively. Material properties of the tank were influencing the tbest, ΔTmax and τΔT>0.1, while the dressed liquid, thermal excitation parameters and the conditions of environment do not influence the tbest. Pit characters of the depth and size have close relationship with tbest and ΔTmax, therefore, for a tank with certain material and certain liquid dressed in, the pit corrosion damage can be accurately evaluated.

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Measurement in Biomedicine

P. Dvořák, W. G. Kropatsch, K. Bartušek

Automatic Brain Tumor Detection in T2-weighted Magnetic Resonance Images

Abstract: This work focuses on fully automatic detection of brain tumors. The first aim is to determine, whether the image contains a brain with a tumor, and if it does, localize it. The goal of this work is not the exact segmentation of tumors, but the localization of their approximate position. The test database contains 203 T2-weighted images of which 131 are images of healthy brain and the remaining 72 images contain brain with pathological area. The estimation, whether the image shows an afflicted brain and where a pathological area is, is done by multi resolution symmetry analysis. The first goal was tested by five-fold cross-validation technique with 100 repetitions to avoid the result dependency on sample order. This part of the proposed method reaches the true positive rate of 87.52% and the true negative rate of 93.14% for an afflicted brain detection. The evaluation of the second part of the algorithm was carried out by comparing the estimated location to the true tumor location. The detection of the tumor location reaches the rate of 95.83% of correct anomaly detection and the rate 87.5% of correct tumor location.

T. Buczkowski, D. Janusek, H. Zavala-Fernandez, M. Skrok, M. Kania, A. Liebert

Influence of Mobile Phones on the Quality of ECG Signal  Acquired by Medical Devices

Abstract: Health aspects of the use of radiating devices, like mobile phones, are still a public concern. Stand-alone electrocardiographic systems and those built-in, more sophisticated, medical devices have become a standard tool used in everyday medical practice. GSM mobile phones might be a potential source of electromagnetic interference (EMI) which may affect reliability of medical appliances. Risk of such event is particularly high in places remote from GSM base stations in which the signal received by GSM mobile phone is weak. In such locations an increase in power of transmitted radio signal is necessary to enhance quality of the communication. In consequence, the risk of interference of electronic devices increases because of the high level of EMI.  In the present paper the spatial, temporal, and spectral characteristics of the interference have been examined. The influence of GSM mobile phone on multilead ECG recordings was studied. It was observed that the electrocardiographic system was vulnerable to the interference generated by the GSM mobile phone working with maximum transmit power and in DTX mode when the device was placed in a distance shorter than 7.5 cm from the ECG electrode located on the surface of the chest. Negligible EMI was encountered at any longer distance.

T. Y. Wu, S. F. Lin

A Method for Extracting Suspected Parotid Lesions in CT Images using Feature-based Segmentation and Active Contours based on Stationary Wavelet Transform

Abstract: Automatic suspected lesion extraction is an important application in computer-aided diagnosis (CAD). In this paper, we propose a method to automatically extract the suspected parotid regions for clinical evaluation in head and neck CT images.  The suspected lesion tissues in low contrast tissue regions can be localized with feature-based segmentation (FBS) based on local texture features, and can be delineated with accuracy by modified active contour models (ACM). At first, stationary wavelet transform (SWT) is introduced. The derived wavelet coefficients are applied to derive the local features for FBS, and to generate enhanced energy maps for ACM computation. Geometric shape features (GSFs) are proposed to analyze each soft tissue region segmented by FBS; the regions with higher similarity GSFs with the lesions are extracted and the information is also applied as the initial conditions for fine delineation computation. Consequently, the suspected lesions can be automatically localized and accurately delineated for aiding clinical diagnosis. The performance of the proposed method is evaluated by comparing with the results outlined by clinical experts. The experiments on 20 pathological CT data sets show that the true-positive (TP) rate on recognizing parotid lesions is about 94%, and the dimension accuracy of delineation results can also approach over 93%.

  Measurement of Physical Quantities

E. Kabalci, Y. Kabalci

A Measurement and Power Line Communication System Design for Renewable Smart Grids

Abstract: The data communication over the electric power lines can be managed easily and economically since the grid connections are already spread around all over the world. This paper investigates the applicability of Power Line Communication (PLC) in an energy generation system that is based on photovoltaic (PV) panels with the modeling study in Matlab/Simulink. The Simulink model covers the designed PV panels, boost converter with Perturb and Observe (P&O) control algorithm, full bridge inverter, and the binary phase shift keying (BPSK) modem that is utilized to transfer the measured data over the power lines. This study proposes a novel method to use the electrical power lines not only for carrying the line voltage but also to transmit the measurements of the renewable energy generation plants. Hence, it is aimed at minimizing the additional monitoring costs such as SCADA, Ethernet-based or GSM based systems by using the proposed technique. Although this study is performed with solar power plants, the proposed model can be applied to other renewable generation systems. Consequently, the usage of the proposed technique instead of SCADA or Ethernet-based systems eliminates additional monitoring costs.

Qiaokang Liang, Dan Zhang, Yaonan Wang, Yunjian Ge

Design and Analysis of a Novel Six-Component F/T Sensor based on CPM for Passive Compliant Assembly

Abstract: This paper presents the design and analysis of a six-component Force/Torque (F/T) sensor whose design is based on the mechanism of the Compliant Parallel Mechanism (CPM). The force sensor is used to measure forces along the x-, y-, and z-axis (Fx, Fy and Fz) and moments about the x-, y-, and z-axis (Mx, My and Mz) simultaneously and to provide passive compliance during parts handling and assembly. Particularly, the structural design, the details of the measuring principle and the kinematics are presented. Afterwards, based on the Design of Experiments (DOE) approach provided by the software ANSYS®, a Finite Element Analysis (FEA) is performed. This analysis is performed with the objective of achieving both high sensitivity and isotropy of the sensor. The results of FEA show that the proposed sensor possesses high performance and robustness.

K. Simunovic, G. Simunovic, T. Saric

Predicting the Surface Quality of Face Milled Aluminium Alloy Using a Multiple Regression Model and Numerical Optimization

Abstract: The surface roughness is a very significant indicator of surface quality. It represents an essential exploitation requirement and influences technological time and costs, i.e. productivity. For that reason, the main objective of this paper is to analyse the influence of face milling cutting parameters (number of revolution, feed rate and depth of cut) on the surface roughness of aluminium alloy. Hence, a statistical (regression) model has been developed to predict the surface roughness by using the methodology of experimental design. Central composite design is chosen for fitting response surface. Also, numerical optimization considering two goals simultaneously (minimum propagation of error and minimum roughness) was performed throughout the experimental region. In this way, the settings of cutting parameters causing the minimum variability in response were determined for the estimated variations of the significant regression factors.

P. Koštial, Z. Jančíková, D. Bakošová, J.Valíček, M. Harničárová I. Špička

Artificial Neural Networks Application in Modal Analysis of Tires

Abstract: The paper deals with the application of artificial neural networks (ANN) to tires’ own frequency (OF) prediction depending on a tire construction. Experimental data of OF were obtained by electronic speckle pattern interferometry (ESPI). A very good conformity of both experimental and predicted data sets is presented here. The presented ANN method applied to ESPI experimental data can effectively help designers to optimize dimensions of tires from the point of view of their noise.

J. Valíček, M. Harničárová, M. Kušnerová, R. Grznárik, J. Zavadil

Proposition of a Solution for the Setting of the Abrasive Waterjet Cutting Technology

Abstract: The submitted paper aims to clarify the abrasive waterjet technology, particularly from the point of view of produced surface topography. It provides a new insight into the deformation process caused by the effect of abrasive waterjet and into the possibilities of using the surface topography for solving the issues of optimization of the process. The subject of study is a system of cutting tool, material and final surface topography and optimization of their parameters. The cutting or disintegrating tool of abrasive waterjet technology is flexible. The trajectory of its cut traces is strictly determined here by disintegration resistance at critical moments of tool-material interaction. The physico-mechanical character of the interaction within the cut will manifest itself in the final surface condition.  This process can be re-analysed by measuring the selected elements of topography and roughness on the final surface, namely depending on the depth of the cut, technological parameters of the tool and mechanical parameters of the material. The mentioned principle is the basis of the presented solution. It lies in the analytical processing and description of correlation interrelations between set technological and measured topographical quantities in relation to the depth of cut and the type of material. 

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  Measurement of Physical Quantities

J. Roj

Neural Network Based Real-time Correction of Transducer Dynamic Errors

Abstract: In order to carry out real-time dynamic error correction of transducers described by a linear differential equation, a novel recurrent neural network was developed. The network structure is based on solving this equation with respect to the input quantity when using the state variables. It is shown that such a real-time correction can be carried out using simple linear perceptrons. Due to the use of a neural technique, knowledge of the dynamic parameters of the transducer is not necessary. Theoretical considerations are illustrated by the results of simulation studies performed for the modeled second order transducer. The most important properties of the neural dynamic error correction, when emphasizing the fundamental advantages and disadvantages, are discussed.

S. Kosarevsky, V. Latypov

Detection of Screw Threads in Computed Tomography 3D Density Fields

Abstract: Measurements and inspection in production must be rapid, robust and automated. In this paper a new method is proposed to automatically detect screw threads in 3D density fields obtained from computed tomography measurement devices. The described method can be used to automate many operations during screw thread inspection process and drastically reduce operator’s influence on the measurement process resulting in lower measurement times and increased repeatability.

M. Shahbazi

Hybrid 3D Dynamic Measurement by Particle Swarm Optimization and Photogrammetric Tracking

Abstract:  High-accuracy motion modeling in three dimensions via digital images has been increasingly the matter of interest in photogrammetry and computer vision communities. Although accurate sub-pixel image registration techniques are the key elements of measurement, they still demand enhanced intelligence, autonomy, and robustness. In this paper, a new correlation-based technique of stereovision is proposed to perform inter-frame feature tracking, inter-camera image registration, and to measure the 3D state vector of features simultaneously. The developed algorithm is founded on population-based intelligence (particle swarm optimization) and photogrammetric modeling. The proposed technique is mainly aimed at reducing the computational complexities of non-linear optimization methods of digital image registration for deformation measurement, and passing through 2D image correlation to 3D motion modeling. The preliminary results have illustrated the feasibility of this technique to detect and measure sub-millimeter deformations by performing accurate, sub-pixel image registration.

P. Kinnell, R. Habeb

Abstract: In 3D tactile micro-metrology the contamination of probing devices is a major problem that affects the accuracy and repeatability of measured dimensions. Despite a large body of research in the field of micro CMM and micro probe design there is limited research which has been done so far to explain and tackle this problem. In this work, experimental probing on a range of materials using a micro coordinate measuring machine was conducted to investigate the mechanism of stylus tip contamination. In addition the effects of surface finish on the build-up of stylus tip contamination were also studied. The results provide practitioners with guidelines which allow for the likely build-up of stylus tip contamination to be minimized based on sample material type and surface finish.

R. Harťanský, V. Smieško, L. Maršálka

Numerical Analysis of Isotropy Electromagnetic Sensor Measurement Error

Abstract:  The article deals with classification and quantification of electromagnetic field measurement errors in case an isotropic sensor as a field probe is used. The focus is mainly on the error of measurement method, resulting from mutual interaction of the field probe sensors associated with the origin of the so-called mutual impedance.

E. Garcia, T. Hausotte

The Parallel Bayesian Toolbox for High-performance Bayesian Filtering in Metrology

Abstract: The Bayesian theorem is the most used instrument for stochastic inferencing in nonlinear dynamic systems and also the fundament of measurement uncertainty evaluation in the GUM. Many powerful algorithms have been derived and applied to numerous problems. The most widely used algorithms are the broad family of Kalman filters (KFs), the grid-based filters and the more recent particle filters (PFs). Over the last 15 years, especially PFs are increasingly the subject of researches and engineering applications such as dynamic coordinate measurements, estimating signals from noisy measurements and measurement uncertainty evaluation. This is rooted in their ability to handle arbitrary nonlinear and/or non-Gaussian systems as well as in their easy coding. They are sampling-based sequential Monte-Carlo methods, which generate a set of samples to compute an approximation of the Bayesian posterior probability density function. Thus, the PF faces the problem of high computational burden, since it converges to the true posterior when number of particles NP→∞. In order to solve these computational problems a highly parallelized C++ library, called Parallel Bayesian Toolbox (PBT), for implementing Bayes filters (BFs) was developed and released as open-source software, for the first time.

In this paper the PBT is presented, analyzed and verified with respect to efficiency and performance applied to dynamic coordinate measurements of a photogrammetric coordinate measuring machine (CMM) and their online measurement uncertainty evaluation.

Yu. Chugui, A. Verkhoglyad, A. Poleshchuk, V. Korolkov, E. Sysoev, P. Zavyalov

3D Optical Measuring Systems and Laser Technologies for Scientific and Industrial Applications

Abstract:  Modern industry and science require novel 3D optical measuring systems and laser technologies with micro/nanometer resolution for solving actual problems. Such systems, including the 3D dimensional inspection of ceramic parts for electrotechnical industry, laser inspection of wheel pair diagnostic for running trains and 3D superresolution low-coherent micro-/nanoprofilometers are presented. The newest results in the field of laser technologies for high-precision synthesis of microstructures by updated image generator using the semiconductor laser are given. The measuring systems and the laser image generator developed and produced by TDI SIE and IAE SB RAS have been tested by customers and used in different branches of industry and science.

M. Zukal, R. Beneš, P. Číka, K. Říha

Towards an Optimal Interest Point Detector for Measurements in Ultrasound Images

Abstract: This paper focuses on the comparison of different interest point detectors and their utilization for measurements in ultrasound (US) images. Certain medical examinations are based on speckle tracking which strongly relies on features that can be reliably tracked frame to frame. Only significant features (interest points) resistant to noise and brightness changes within US images are suitable for accurate long-lasting tracking. We compare three interest point detectors – Harris-Laplace, Difference of Gaussian (DoG) and Fast Hessian – and identify the most suitable one for use in US images on the basis of an objective criterion. Repeatability rate is assumed to be an objective quality measure for comparison. We have measured repeatability in images corrupted by different types of noise (speckle noise, Gaussian noise) and for changes in brightness. The Harris-Laplace detector outperformed its competitors and seems to be a sound option when choosing a suitable interest point detector for US images. However, it has to be noted that Fast Hessian and DoG detectors achieved better results in terms of processing speed.

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