Mindaugas Zilys

Dynamic Vehicle Detection via the Use of Magnetic Field Sensors.

The vehicle detection process plays the key role in determining the success of intelligent transport management system solutions. The measurement of distortions of the Earth’s magnetic field using magnetic field sensors served as the basis for designing a solution aimed at vehicle detection. In accordance with the results obtained from research into process modeling and experimentally testing all the relevant hypotheses an algorithm for vehicle detection using the state criteria was proposed. Aiming to evaluate all of the possibilities, as well as pros and cons of the use of anisotropic magnetoresistance (AMR) sensors in the transport flow control process, we have performed a series of experiments with various vehicles (or different series) from several car manufacturers. A comparison of 12 selected methods, based on either the process of determining the peak signal values and their concurrence in time whilst calculating the delay, or by measuring the cross-correlation of these signals, was carried out. It was established that the relative error can be minimized via the Z component cross-correlation and Kz criterion cross-correlation methods. The average relative error of vehicle speed determination in the best case did not exceed 1.5% when the distance between sensors was set to 2 m.

Peculiarities of the Third Natural Frequency Vibrations of a Cantilever for the Improvement of Energy Harvesting

This paper focuses on several aspects extending the dynamical efficiency of a cantilever beam vibrating in the third mode. A few ways of producing this mode stimulation, namely vibro-impact or forced excitation, as well as its application for energy harvesting devices are proposed. The paper presents numerical and experimental analyses of novel structural dynamics effects along with an optimal configuration of the cantilever beam. The peculiarities of a cantilever beam vibrating in the third mode are related to the significant increase of the level of deformations capable of extracting significant additional amounts of energy compared to the conventional harvester vibrating in the first mode. Two types of a piezoelectric vibrating energy harvester (PVEH) prototype are analysed in this paper: the first one without electrode segmentation, while the second is segmented using electrode segmentation at the strain nodes of the third vibration mode to achieve effective operation at the third resonant frequency. The results of this research revealed that the voltage generated by any segment of the segmented PVEH prototype excited at the third resonant frequency demonstrated a 3.4–4.8-fold increase in comparison with the non-segmented prototype. Simultaneously, the efficiency of the energy harvester prototype also increased at lower resonant frequencies from 16% to 90%. The insights presented in the paper may serve for the development and fabrication of advanced piezoelectric energy harvesters which would be able to generate a considerably increased amount of electrical energy independently of the frequency of kinematical excitation.

Optimizing strategic control of integrated security systems

The motivation to write this work was induced by the need to evaluate the parameters of security systems, to analyze in detail the processes, which occur in security system evaluation and suggest the possible ways of their optimization. The concept, which is formulated, enables strategic control of integrated security systems (ISS) considering from the influence-reaction parameter point. Reaction strategy algorithm selection allows minimizing reaction time to danger influence and maximizing efficiency of security system. Modern computer technologies allow real time strategies simulation and ISS reaction control. The analysis of the event streams experimental data and integrated security systems net model simulation algorithms enable the further development and perfection of the security system

Information flow model of integrated security system

The goal of this paper is to study the effectivity and reliability of signal transferring by security systems via communication channels, as well as to define the main criteria of the available communication channels affecting the total response time of security systems. This paper mainly models and empirically solves the following tasks: application of information theory on streams in telecommunication systems to integrated security systems and calculations of system losses. With respect to the fundamentals of massive service systems, a model is imitated for the security systems. Using this model, experiments on the reliability and effectiveness of security systems are performed, so as to find more effective and reliable operating algorithms for security systems

Vehicle Speed and Length Estimation Using Data from Two Anisotropic Magneto-Resistive (AMR) Sensors

Methods for estimating a car’s length are presented in this paper, as well as the results achieved by using a self-designed system equipped with two anisotropic magneto-resistive (AMR) sensors, which were placed on a road lane. The purpose of the research was to compare the lengths of mid-size cars, i.e., family cars (hatchbacks), saloons (sedans), station wagons and SUVs. Four methods were used in the research: a simple threshold based method, a threshold method based on moving average and standard deviation, a two-extreme-peak detection method and a method based on the amplitude and time normalization using linear extrapolation (or interpolation). The results were achieved by analyzing changes in the magnitude and in the absolute z-component of the magnetic field as well. The tests, which were performed in four different Earth directions, show differences in the values of estimated lengths. The magnitude-based results in the case when cars drove from the South to the North direction were even up to 1.2 m higher than the other results achieved using the threshold methods. Smaller differences in lengths were observed when the distances were measured between two extreme peaks in the car magnetic signatures. The results were summarized in tables and the errors of estimated lengths were presented. The maximal errors, related to real lengths, were up to 22%.

Research of the Defects in PET preform

Image technologies nowadays are used not only for keeping personal events safe, but also are widely applied in conjunction with automated electronic systems. Computer vision is widely used for inspection of the production quality in industries. Food industry is not an exception. Containers for food industry are made in very large quantities. This article contains of defect analysis of both external and side area of the bottleneck. Defects were divided into groups according to which the filters are created. For the control of PET preparation quality an automated computer vision algorithms were developed. The algorithms and methods were used for the detection of defective products mainly based on the image segmentation, digital production, erosion, smoothing. The most effective filters for the defect detection of the workpieces have been determined. It was carried out that efficiency of algorithms are close to 100 %.

Traffic Image Processing Systems

This paper is about image processing systems and its ability to use in traffic surveillance and analysis. Growing car number is cause of bigger traffic jams and city pollution. With intelligent vision systems we can control traffic and reduce this problem. These systems have tremendous perspective. This paper presents the fundamental principles of traffic image processing system in moving object detection and extraction.

Crossroads load modelling

The main purpose of this article is to evaluate the impact of newly emerging big leisure and shopping centers with spacious parking in the cities to the traffic flows. The experiment was performed for this purpose. The results of this experiment were used for forecasting the traffic flows. After performing the traffic flow forecasting, the results were used in the development of the crossroad model. By applying the developed crossroad model we could perform the modelling and identify the impact of the released different traffic flows from parking to the transport flows in crossroads.

Electronic traffic jam detection in parking facilities

This paper explores the possibility of traffic jam control and detection systems modelling. The traffic jam detection model was developed This paper proposes jam forecasting and detection method using the neural network and fast Fourier transform. In this method, time series data of traffic flow events considered as a combination of frequency are transformed into several frequency data.

Practical Methods for Vehicle Speed Estimation Using a Microprocessor-Embedded System with AMR Sensors

The proper operation of computing resources in a microprocessor-embedded system plays a key role in reducing computing time. Processing the variable amount of collected data in real-time improves the performance of a microprocessor-embedded system. In this regard, a vehicle’s speed measurement system is no exception. The computing time for evaluating any speed value is expected to be reduced as much as possible. Four computational methods, including cross-correlation, are discussed. An exemplary pair of recorded signals presenting the change in magnetic field magnitude is analyzed. The sample delay values are compared. The results of the evaluated speed and the execution time of the program code are presented for each method based on a dataset of 200 randomly driven vehicles. The results of the performed tests confirm that the cross-correlation-based methods are not always reliable in situations when the sample size is small, i.e., it is a segment of the impulse response caused by a driving vehicle.