Time-domain Network Research Articles

Time-Domain Transfer Coupled Response of Antennas—Reciprocity Theorem Approach

A complete time-domain network representation of a transmit–receive two-port perfect electric conducting antenna system in an arbitrary distance is presented. We utilize a scattering matrix setting, which, as the impedance matrix formulation, is a proper setting for the time-domain formulation in antenna system representations. The formulation is derived directly in the time domain using both the convolution-type and the correlation-type reciprocity relations. We derive the general expressions for the matrix, in particular the transfer coupled coefficients between the antennas (transfer coupled response), followed by closed-form example of parallel staggered dipole antennas that provides a clear and transparent physical interpretation for the time-domain phenomenology.

Bearing Fault Diagnosis Based on Statistical Feature Extraction in Time and Frequency Domain and Neural Network

Bearing is an important component of almost every mechanical system used in industrial environment. Hence the defect in bearing must be detected in advance to avoid catastrophic failure. This paper aims to diagnose the defect in bearing automatically using machine intelligence. A condition monitoring setup is designed for analyzing the defects in outer race, inner race and rolling element of bearing. MATLAB is used for feature extraction and neural network is used for diagnosis. It is found that the amplitude at defect frequencies may not always clearly indicate the increment; hence statistical analysis of bearing signature is a better alternative. The work presents an experimental investigation carried out on an experimental set-up for the study of bearing fault at same angular speed and load. This paper proposes an approach of damage detection in which defects in bearing are accurately analysed using vibration signal and neural network.

Numerical simulation on onset characteristics of traveling-wave thermoacoustic engines based on a time-domain network model

Onset characteristics of thermoacoustic engines are of great importance for understanding the internal working mechanisms of thermoacoustic conversion. A one-dimensional time-domain network model for predicting the onset characteristics of traveling-wave thermoacoustic engines with helium as working gas is built. The acoustic resistance, inertance, compliance, and thermal-relaxation effects of all the acoustic components are included. The viscous and heat transfer terms in the time-domain governing equations of the acoustic tubes and the heat exchangers are deduced from the frequency-domain linear thermoacoustic theory. Combining the time-domain governing equations of the regenerator, numerical simulations of the whole onset process are then conducted in a wide operating condition range. The complete dynamic pressure wave evolution processes are simulated successfully. It is shown that a steady standing-wave acoustic field forms in almost all parts of the traveling-wave thermoacoustic engine except for the regenerator area. Onset temperature, operating frequency, and quality factor are calculated with a relatively high accuracy. The thermal relaxation effects in the regenerator are found to have a remarkable impact on the onset characteristics, especially at high mean pressures. It is also shown that the experimental damping temperature is closer to the calculated onset temperature than the experimental onset temperature. Furthermore, the reasonable distributions of the pressure and volume flow rate and the phase relationship between them in the whole system are obtained and analyzed.

Fibre‐tree network for water‐surface ranging using an optical time‐domain reflectometry technique

To monitor water level at long distance, a fibre-based time-domain reflectometry network is proposed. A collimator at each fibre end of a tree-type network retrieves 1.55 μm wavelength pulses that are reflected back from remote surfaces. Since this enables a power-supply-free sensor network with non-metal media, this system is expected to be less susceptible to lightning strikes and power cuts than conventional systems that use electrically powered sensors and metal cables. In the present Letter, a successful simultaneous monitoring experiment of two water levels in the laboratory, as well as a trial for detecting a disturbed surface by beam-expanding is reported.

Propagation and Responses of EMP on Transmission-Line Networks

This paper discusses the use of Baum-Liu-Tesche (BLT) equation for analyzing and calculating the propagation and load responses of transmission-line networks in frequency domain and time domain. The derivation and each parameters of BLT equation is introduced, and using BLT equation, two examples of specific coaxial cable networks are established, and the propagation and responses of networks are analyzed and calculated. The responses of networks terminals are measurement, and calculation results and measurement results are compared. The results show the excellent agreement between measurement and calculation results. The study results of this paper can be used for cable networks design and protection against EMP.

The Evolution and Stability of the Maximal Connected Sub-graph of Holding-based Network of China's Listed Energy Company

Listed energy company is the principal part of the energy market, including the energy investment, energy trade, energy operation etc. Stockholders are the owners of the listed energy companies, whose relationships would affect the stability of the energy market directly. In order to analyze the evolution features and stability of the relationships between the stockholders, we constructed a generator holding-based structural equivalence network of the shareholders based on the primitive affiliation network of the listed companies and their shareholders. The main data used in this paper is the semi-annual reports from 2003 to 2012 which contain the information about Chinese listed energy companies’ top 10 shareholders. The holding-based network takes the shareholders as the nodes, whether holding the same listed energy companies’ stock at the same period as the edges, and the number of the listed energy companies holding at the same time as the weights. In this paper, we improved the traditional Heuristic method and then found the maximal connected sub-graphs of the holding-based networks in different time domain by the improved Heuristic method. The main method and theory used in this paper is complex network, we calculated and analyzed the evolution and the stability of the maximal connected sub-graphs. This paper comes up with a new angle to analyze the relationships in the energy stock market, and present a new method to analyze the stockholders’ behaviors.

Review of Harmonic Detection Methods for Active Power Filters

The problem of more and more serious reactive power and harmonic pollution to power systems is getting more and more serious, which has caused great concern. One of the key points for proper implementation of an APF is to use a reliable method for current/ voltage reference generation. Consequently, how to detect harmonic quickly and accurately becomes a crucial problem. From the perspective of historical development of detection methods, it experienced a course from frequency domain and time domain and neural network to Adaptive parameter identification. Several methods of measuring harmonic, such as wavelet/ S transform, Fourier transform are introduced and compared in this paper.

Physical layer network coding with channel and delay estimation

Decode-and-forward physical layer network coding (PLNC) is one of the promising high-performance techniques for wireless relay networks. This study presents a channel and delay estimation algorithm along with a detection scheme for time-domain two-way relay network in Rayleigh block fading channels. Preambles are attached for frame-based synchronisation and channel estimation. Moreover, to achieve low-complexity estimation, the preambles are designed in Alamouti code structure. The Cramer-Rao bound (CRB) of the channel estimation is given, and simulations show that the mean-square error of channel estimation of the proposed scheme could reach the CRB. Compared with the traditional approach, the newly proposed combined scheme can achieve almost the same performance, but with significant improvement in computational complexity. At last, bit-error-rate performances analysis is given. Simulation validates the authors' analysis, and shows the upper bound and lower bound are tight.

An Introduction to Wireless Mobile Social Networking in Opportunistic Communication

Next generation networks will certainly face requesting access from different parts of the network. The heterogeneity of communication and application software’s changing situations in the environment, from the users, the operators, the business requirements as well as the technologies. Users will be more and more mobile, protocols, etc. will increase and render the network more complex to manage. Opportunistic communication has emerged as a new communication paradigm to cope with these problems. Opportunistic networksexploits the variation of channel conditions, provides an additional degree of freedom in the time domain and increase network performance.The limited spectrum and the inefficiency in the spectrum usage require such a new communication to exploit the existing wireless spectrum opportunistically by allocation of spectrum based on best opportunity among all possibilities.

Joint damage identification using Improved Radial Basis Function (IRBF) networks in frequency and time domain

In this paper, a novel two-stage Improved Radial Basis Function (IRBF) neural network technique is proposed to predict the joint damage of a fifty member frame structure with semi-rigid connections in both frequency and time domain. The effective input patterns as normalized design signature indices (NDSIs) in frequency domain and acceleration responses in time domain are simulated numerically from finite element analysis (FEA) by considering different levels of damage severity using Latin hypercube sampling (LHS) technique. The conventional RBF network is used in the first stage of IRBF network and in the second stage reduced search space moving technique is employed for accurate prediction with less than 3% error. The numerical simulation of the substructural joint damage identification of a fifty member frame structure with and without addition of 5% Gaussian random noise to the input patterns is presented and compared with conventional CPN–BPN hybrid method. The two-stage IRBF method is found to be superior in accuracy to conventional hybrid methods as well as to conventional RBF method. An important benefit of the proposed novel IRBF method is the significant reduction in the computational time with good accuracy of joint damage identification.

위너 필터와 충격 펄스 카운팅을 이용한 저속 기계용 구름 베어링의 결함 검출

The low speed machinery faults are usually caused by the bearing failure of the rolling elements. As the life time of the bearing is limited, the condition monitoring of bearing is very important to maintain the continuous operation without failures. A few monitoring techniques using time domain, frequency domain and fuzzy neural network vibration analysis are introduced to detect and diagnose the faults of the low speed machinery. This paper presents a method of fault detection for the rolling element bearing in the low speed machinery using the Wiener filtering and shock pulse counting techniques. Wiener filter is used for noise cancellation and it clearly makes the shock pulse emerge from the time signal with the high level of noise. The shock pulse counting is used to determine the various faults obviously from the shock signal with transient pulses not related with the bearing fault. Machine fault simulator is used for the experimental measurement in order to verify this technique is the powerful tool for the low speed machine compared with the frequency analysis. The test results show that the method proposed is very effective parameter even for the signal with high contaminated noise, speed variation and very low energy. The presented method shows the optimal tool for the condition monitoring purpose to detect the various bearing fault with high accuracy.

A Frequency-Domain INS/GPS Dynamic Response Method for Bridging GPS Outages

We develop a new frequency-domain dynamic response method to model integrated Inertial Navigation System (INS) and Global Positioning System (GPS) architectures and provide an accurate impulse-response-based INS-only navigation solution when GPS signals are denied (GPS outages). The input to such a dynamic system is the INS-only solution and the output is the INS/GPS integration solution; both are used to derive the transfer function of the dynamic system using Least Squares Frequency Transform (LSFT). The discrete Inverse Least Squares Frequency Transform (ILSFT) of the transfer function is applied to estimate the impulse response of the INS/GPS system in the time domain. It is shown that the long-term motion dynamics of a DQI-100 IMU/Trimble BD950 integrated system are recovered by 72%, 42%, 75%, and 40% for north and east velocities, and north and east positions respectively, when compared with the INS-only solution (prediction mode of the INS/GPS filter). A comparison between our impulse response model and the current state-of-the-art time-domain feed-forward neural network shows that the proposed frequency-dependent INS/GPS response model is superior to the neural network model by about 26% for 2D velocities and positions during GPS outages.

Thermoacoustic Modeling of a Gas Turbine Using Transfer Functions Measured Under Full Engine Pressure

Thermoacoustic transfer functions of a full-scale gas turbine burner operating under full engine pressure have been measured. The excitation of the high-pressure test facility was done using a siren that modulated a part of the combustion airflow. Pulsation probes have been used to record the acoustic response of the system to this excitation. In addition, the flame’s luminescence response was measured by multiple photomultiplier probes and a light spectrometer. Three techniques to obtain the thermoacoustic transfer function are proposed and employed: two acoustic-optical techniques and a purely acoustic technique. The first acoustical-optical technique uses one single optical signal capturing the chemiluminescence intensity of the flame as a measure for the heat release in the flame. This technique only works if heat release fluctuations in the flame have only one generic source, e.g., equivalence ratio or mass flow fluctuations. The second acoustic-optical technique makes use of the different response of the flame’s luminescence at different optical wavelengths bands to acoustic excitation. It also works, if the heat release fluctuations have two contributions, e.g., equivalence ratio and mass flow fluctuation. For the purely acoustic technique, a new method was developed in order to obtain the flame transfer function, burner transfer function, and flame source term from only three pressure transducer signals. The purely acoustic method could be validated by the results obtained from the acoustic-optical techniques. The acoustic and acoustic-optical methods have been compared and a discussion on the benefits and limitations of each is given. The measured transfer functions have been implemented into a nonlinear, three-dimensional, time domain network model of a gas turbine with an annular combustion chamber. The predicted pulsation behavior shows a good agreement with pulsation measurements on a field gas turbine.

Extraction of Capacitive Profiles with CRLH Transmission Lines

Different methods for extracting the capacitive profile with a CRLH (composite right/left-handed) transmission line are presented. Using broadband techniques the input impedance in the LH and RH bands can be measured. The capacitance values along the line can be evaluated by applying extraction methods such as time domain reflectometry, perturbation theory or network synthesis. The areas of application of these methods is for sensing applications that range from transportation of materials in industrial processes to biomedical applications where the characteristics of an organic tissue is necessary.

A Time-Domain Network Model for Nonlinear Thermoacoustic Oscillations

Lean premixed prevaporized (LPP) combustion can reduce NOx emissions from gas turbines but often leads to combustion instability. Acoustic waves produce fluctuations in heat release, for instance, by perturbing the fuel-air ratio. These heat fluctuations will in turn generate more acoustic waves and in some situations linear oscillations grow into large-amplitude self-sustained oscillations. The resulting limit cycles can cause structural damage. Thermoacoustic oscillations will have a low amplitude initially. Thus linear models can describe the initial growth and hence give stability predictions. An unstable linear mode will grow in amplitude until nonlinear effects become sufficiently important to achieve a limit cycle. While the frequency of the linear mode can often provide a good approximation to that of the resulting limit cycle, linear theories give no prediction of its resulting amplitude. In previous work, we developed a low-order frequency-domain method to model thermoacoustic limit cycles in LPP combustors. This was based on a “describing-function” approach and is only applicable when there is a dominant mode and the main nonlinearity is in the combustion response to flow perturbations. In this paper that method is extended into the time domain. The main advantage of the time-domain approach is that limit-cycle stability, the influence of harmonics, and the interaction between different modes can be simulated. In LPP combustion, fluctuations in the inlet fuel-air ratio have been shown to be the dominant cause of unsteady combustion: These occur because velocity perturbations in the premix ducts cause a time-varying fuel-air ratio, which then convects downstream. If the velocity perturbation becomes comparable to the mean flow, there will be an amplitude-dependent effect on the equivalence ratio fluctuations entering the combustor and hence on the rate of heat release. Since the Mach number is low, the velocity perturbation can be comparable to the mean flow, with even reverse flow occurring, while the disturbances are still acoustically linear in that the pressure perturbation is still much smaller than the mean. Hence while the combustion response to flow velocity and equivalence ratio fluctuations must be modeled nonlinearly, the flow perturbations generated as a result of the unsteady combustion can be treated as linear. In developing a time-domain network model for nonlinear thermoacoustic oscillations an initial frequency-domain calculation is performed. The linear network model, LOTAN, is used to categorize the combustor geometry by finding the transfer function for the response of flow perturbations (at the fuel injectors, say) to heat-release oscillations. This transfer function is then converted into the time domain through an inverse Fourier transform to obtain Green’s function, which thus relates unsteady flow to heat release at previous times. By combining this with a nonlinear flame model (relating heat release to unsteady flow at previous times) a complete time-domain solution can be found by stepping forward in time. If an unstable mode is present, its amplitude will initially grow exponentially (in accordance with linear theory) until saturation effects in the flame model become significant, and eventually a stable limit cycle will be attained. The time-domain approach enables determination of the limit cycle. In addition, the influence of harmonics and the interaction and exchange of energy between different modes can be simulated. These effects are investigated for longitudinal and circumferential instabilities in an example combustor system and the results are compared with frequency-domain limit-cycle predictions.

Extraction of causal time-domain network parameters from their band-limited frequency-domain counterparts using rational functions

Network parameters of a lumped element device are usually given in a limited frequency band of interest, or in an operation frequency range. To include them in time-domain simulations, they need to be converted to their causal time-domain correspondences. However, direct conversion with a simple technique such as the Fourier transform often leads to noncausal time-domain network parameters. Even when causal parameters are found, convolutions with them in the time domain are usually too computationally inefficient to carry out for a simulation with a large number of time steps. In this paper, a technique that extracts the causal time-domain parameters using rational function approximations is proposed. It results in time-domain parameters which are not only causal but also of exponential form in time. Consequently, the convolutions with them can be performed in a recursive manner. Numerical examples are provided to verify the effectiveness.

Applied Time-Domain Network Characterization and Simulation

Characterizations or models of electrical networks assist designers in predicting how a network will perform in a proposed system without physically constructing the complete system. This allows engineers to quickly test, by simulation, various options and thereby reduce design costs and schedules. For linear networks, characterizations may be obtained from measurements made at the network ports. These models are commonly developed in the frequency domain; such models can be applied directly in frequency-domain simulation and indirectly in time-domain simulation. Alternatively, measurements taken at the ports can also be used to develop time-domain models that are directly applicable for time-domain simulation. This alternate approach has the advantages of avoiding sometimes-difficult transformations and requiring only time-domain instrumentation.

A simulation technique for the evaluation of random error effects in time-domain measurement systems

While many papers deal with time-domain network analyzer calibration procedures for the correction of systematic errors, little work has been published about the treatment of random errors. This paper is focused on the evaluation of random error effects in time-domain measurement systems. As a first step, an experimental identification of the measurement system random errors is achieved. Random errors addressed are jitter, vertical noise, and fast time drifts. Based on this identification, mathematical models are developed to simulate random errors. At a second step, time-domain measurements are simulated with these random errors. These simulations are used to predict measurement system repeatability and dynamic range. Then, as an application example, simulations of the measurement of the complex propagation coefficient and S parameters of a lossy mismatched microstrip line are achieved. By comparison with real measurements, it is shown that random error effects can be accurately predicted by Monte Carlo simulations.

A PDAE Model for Interconnected Linear RLC Networks

In electrical circuit simulation, a refined generalized network approach is used to describe secondary and parasitic effects of interconnected networks. Restricting our investigations to linear RLC circuits, this ansatz yields linear initial-boundary value problems of mixed partial-differential and differential-algebraic equations, so-called PDAE systems. If the network fulfils some topological conditions, this system is well-posed and has perturbation index 1 only: the solution of a slightly perturbed system does not depend on derivatives of the perturbations. As method-of-lines applications are often used to embed PDAE models into time-domain network analysis packages, it is reasonable to demand that the analytical properties of the approximate DAE system obtained after semidiscretization are consistent with the original PDAE system. Especially, both should show the same sensitivity with respect to initial and boundary data. We will learn, however, that semidiscretization may act like a deregularization of an index-1 PDAE model, if an inappropriate type of semidiscretization is used.

Time domain network analysis of write head coil impedance

In this paper, time domain network analysis methods are used to measure the electrical impedance of a magnetic disk drive write head, An incident step capable of delivering /spl plusmn/73 mA to the write coil simulates typical operating levels. The paper compares results to more common vector network analysis measurements, which are done at small-signal levels. It discusses the application of the measured transient response to high data rate recording.