This article presents the simulation of a BLDC motor and its closed control system in FPGA. The simulation is based on a mathematical model of the motor, including the electromagnetic torque, phase currents, back electromotive force, etc. In order to ensure calculation precision, the equations describing the motor were solved using a floating point representation of real numbers, and a small step of numerical calculations of 1 μs was assumed. The time step selection methodology has been discussed in detail. The motor model was executed with the use of Textual Programming Languages (with HDL codes).
The Internet of Things (IoT) is an emerging technology that was conceived in 1999. The key components of the IoT are intelligent sensors, which represent objects of interest. The adjective ‘intelligent’ is used here in the information gathering sense, not the psychological sense. Some 30 billion sensors that ‘know’ the current status of objects they represent are already connected to the Internet. Various studies indicate that the number of installed sensors will reach 212 billion by 2020. Various scenarios of IoT projects show sensors being able to exchange data with the network as well as between themselves. In this contribution, we discuss the possibility of deploying the IoT in cartography for real-time mapping. A real-time map is prepared using data harvested through querying sensors representing geographical objects, and the concept of a virtual sensor for abstract objects, such as a land parcel, is presented. A virtual sensor may exist as a data record in the cloud. Sensors are identifi ed by an Internet Protocol address (IP address), which implies that geographical objects through their sensors would also have an IP address. This contribution is an updated version of a conference paper presented by the author during the International Federation of Surveyors 2014 Congress in Kuala Lumpur. The author hopes that the use of the IoT for real-time mapping will be considered by the mapmaking community.
Natural gas is a mixture of 21 components and it is widely used in industries and homes. Knowledge of its thermodynamic properties is essential for designing appropriate processes and equipment. This paper presents simple but precise correlations of how to compute important thermodynamic properties of natural gas. As measuring natural gas composition is costly and may not be effective for real time process, the correlations are developed based on measurable real time properties. The real time properties are temperature, pressure and specific gravity of the natural gas. Calculations with these correlations are compared with measured values. The validations show that the average absolute percent deviation (AAPD) for compressibility factor calculations is 0.674%, for density is 2.55%, for Joule-Thomson coefficient is 4.16%. Furthermore, in this work, new correlations are presented for computing thermal properties of natural gas such as enthalpy, internal energy and entropy. Due to the lack of experimental data for these properties, the validation is done for pure methane. The validation shows that AAPD is 1.31%, 1.56% and 0.4% for enthalpy, internal energy and entropy respectively. The comparisons show that the correlations could predict natural gas properties with an error that is acceptable for most engineering applications.
In this paper, an algorithm that monitors the power system to detect and classify power quality events in real time is presented. The algorithm is able to detect events caused by waveform distortions and variations of the RMS values of the voltage. Detection of the RMS events is done by comparing the RMS values with certain thresholds, while detection of waveform distortions is made using an algorithm based on multiharmonic leasts-squares fitting.
In this paper, some issues of building a reliable, distributed measurement system for monitoring of water quality in reservoir Lake Dobczyckie are presented. The system is based on a measurement station that has the shape of a floating buoy which is supposed to be at anchor on the reservoir. Wireless data transmission problems that were encountered during the development of the buoy, modeling a radio link, and measurements of actual signal strength on the reservoir are discussed. A mathematical approach to procedures of early situation assessment was conducted, and specialized procedures were designed for measurement stations of the system. It is also discussed how such computations can improve a qualitative assessment of system performance in terms of real-time messaging
The paper encompasses the overview of hardware architecture and the systems characteristics of the Fraunhofer driving simulator. First, the requirements of the real-time model and the real-time calculation hardware are defined and discussed in detail. Aspects like transport delay and the parallel computation of complex real-time models are presented. In addition, the interfacing of the models with the simulator system is shown. Two simulator driving tests, including a fully interactive rough terrain driving with a wheeled excavator and a test drive with a passenger car, are set to demonstrate system characteristics. Furthermore, the simulator characteristics of practical significance, such as simulator response time delay, simulator acceleration signal bandwidth obtained from artificial excitation and from the simulator driving test, will be presented and discussed.
In this study, a SYBR Green-based real-time quantitative polymerase chain reaction (qPCR) assay was developed for rapid detection of porcine parvovirus (PPV) 6. Primer pairs targeting the conserved regions of PPV6 Capsid gene were designed. Sensitivity analyses revealed the lowest detection limit of the SYBR Green-based real-time PCR assay to be 47.8 copies/μL, which indicated it was 1000 times higher than that found in the conventional PCR investigations. This assay was specific and showed no cross-species amplification with other six porcine viruses. The assay demonstrated high repeatability and reproducibility; the intra- and inter-assay coefficients of variation were 0.79% and 0.42%, respectively. The positive detection rates of 180 clinical samples with SYBR Green-based real-time PCR and conventional PCR were 12.22% (22/180) and 4.44% (8/180), respectively. Our method is sensitive, specific, and reproducible. The use of SYBR Green-based real-time PCR may be suitable for the clinical detection and epidemiological investigation of PPV6.
The complexity of power system phenomena challenges power system protection testing to obtain the required adequacy of the testing environment. Hardware-in-the-loop simulation in real-time substantially increases testing capabilities. However, there is still the question of the availability of commercial solutions. To address the challenges, a new hardware-in-the loop system has been designed and implemented utilizing the easily available Matlab/Simulink environment and Linux RT Preempt OS. The custom software part prepared for the presented system is based on the Matlab/Simulink s-function mechanism, Embedded Coder toolbox and Advantech biodaq library as the interface for the utilized I/O cards. The simulator’s real-time performance limits on Linux RT Preempt have been verified, and it was shown that its performance is sufficient to conduct successful tests of protection relays. Consequently, a simple power system protection relay testing example is provided, including a discussion of results. Finally, it has been proven that the presented system can be utilized as a simpler and more accessible hardware-in-the-loop testing alternative to commercial simulators.
This paper develops a new model of market abuse detection in real time. Market abuse is detected, as Minenna (2003) proposed, on the basis of prediction intervals. The model structure is based on the discrete-time, extended market model introduced by Monteiro, Zaman, Leitterstorf (2007) to analyze the market cleanliness. Parameters of the expected return equation are assumed, however, to be time-varying and estimated under the state-space framework using the extended Kalman filter postulated by Chou, Engle, Kane (1992) to capture the GARCH effect in returns. QML estimation is performed on intraday data; its utilization is proposed as an alternative to the continuous time modeling by Minenna (2003). This framework is generalized to the bivariate case which enables the analysis of daily open/close data. The paper also extends procedures of the statistical verification of the estimated state-space model to include the uncertainty arising from time-invariant parameters.
A variety of algorithms allows gesture recognition in video sequences. Alleviating the need for interpreters is of interest to hearing impaired people, since it allows a great degree of self-sufficiency in communicating their intent to the non-sign language speakers without the need for interpreters. State-of-theart in currently used algorithms in this domain is capable of either real-time recognition of sign language in low resolution videos or non-real-time recognition in high-resolution videos. This paper proposes a novel approach to real-time recognition of fingerspelling alphabet letters of American Sign Language (ASL) in ultra-high-resolution (UHD) video sequences. The proposed approach is based on adaptive Laplacian of Gaussian (LoG) filtering with local extrema detection using Features from Accelerated Segment Test (FAST) algorithm classified by a Convolutional Neural Network (CNN). The recognition rate of our algorithm was verified on real-life data.
Modern control and measurement systems are equipped with interfaces to operate in local area networks and are typically intended to perform complicated data processing and control algorithms. The authors propose a digital system for rapid prototyping of target application devices. The concept solution separates the processing and control section from the hardware interface and user interface section. Both sections constitute independent ARM-based controllers interconnected via a direct USB link. Popular libraries can be used and low-level procedures developed, which enhances the system’s economic viability. A test unit developed for the purpose of the study was built around a SoC ARM7 microsystem and an off-the-shelf palmtop device. It demonstrated a continuous data stream transfer capability up to 150 kB per second, which was sufficient to monitor the performance of an electricity line.