Statistical approach to the process of tunnel ionisation of impurity centres near the heterointerface

To date, the processes of tunnel ionisation of impurities near the interface between two different semiconductors have been comprehensively studied. The most important parameters of the contact electron states of impurities have been determined. However, the calculated expressions for these parameters have been of local nature, as applied to individual impurities. Meanwhile, it is easy to understand that a number of processes, such as the flow of charge carriers and their diffusion through a heterojunction, are clearly statistical in nature. The same applies to the processes of tunnel ionisation of shallow and/or deep impurities near the interface. A statistical approach to the calculation of the parameters of tunnel ionisation of impurities broadens the opportunities for obtaining fundamental information regarding surface electronstates.The aim of this work was to use a statistical approach to study the effect of the heterointerface on the energy spectrum of shallow and deep centres. For this purpose, the expansion of the reflected quasi-classical wave function within the complete system of spherical harmonics and the subsequent extraction of the zero harmonic amplitude (s-component) was used to estimate the minimum distance from the impurity to the heterobarrier and to specify the limitations of the applicability of the results obtained in other works. The article analyses the conditions of the quasi-classical approximation which are used to estimate the order of the value for the minimum height of the potential barrier (pit).This work (with due consideration given to the minimum distance estimate) presents averaged formulas obtained for the energy shift of the ground state and the lifetime of the quasi-stationary state depending on the distance from the heterobarrier. Some qualitatively new considerations can also be found in the article. The distribution of impurity centres near the heterobarrier is assumed to be uniform. The article discusses the role of electron transitions in causing the buffer field effect for both shallow and deep centres. The focus of the article is on the estimates of various physical parameters characterising electron transitions near the heterobarrier.

PSXII-17 Fertility prediction model for Nilli-Ravi buffalo bulls through Fourier harmonic analysis of sperm

A model to predict Nili-ravi buffalo bull fertility was developed based on Fourier harmonic analysis of sperm. Seventeen bulls with 3032 AI records were categorizes based on fertility rate (FR) as low (36.5±0.2, n = 6: SD< ˗1 from mean FR), medium (39.9±0.2, n = 3; SD +1 to -1 from mean FR) and high fertility (41.4±0.1, n = 8; SD > +1 from mean FR). Cryopreserved semen samples from these bulls were investigated for Fourier harmonic analysis of sperm nuclear shape. Hoechst-33342 and YOYO-1 fluorescent stains were used to identify live and dead sperm. Digital images were analyzed to get sperm nuclear perimeter points at different phase angles to generate Fourier functions. Mean harmonic amplitude (HA) 0 was different (P < 0.05) for 1700 live vs. 1294 dead sperm from the 17 bulls, thus live sperm were used for remaining analyses. The mean, variance, skewness and kurtosis values of 100 live sperm nuclei/bull were compared for HA0-5 between high (n = 6) and low (n = 6) fertility groups, considering equal number of bulls in each category. The mean HA2 (0.739±0.01 vs 0.686±0.00) and 4 (0.105±0.001 vs 0.007±0.001) were higher in high vs low fertility group respectively (P < 0.05). Sperm nuclear perimeter among high fertility group sperm was more elongated. There was also an increased skewness of HA0 as fertility increased (P < 0.05). Discriminant analysis defined a fertility model by using mean HA4, skewness HA0 and variance HA2, that resulted in 91.7% bulls into their correct fertility group upon cross-validation (canonical correlation=0.928; P < 0.05). Higher values of mean HA4, skewness HA0 and variance HA2 increase the chance of bulls being placed in the high fertility group. In conclusion, sperm nuclear shape in Nili-ravi buffalo bull is related to in vivo fertility. A fertility model using reported discriminant measures could be used to objectively identify Nili-ravi buffalo bulls of varying fertility.

CHOOSING A NEURAL NETWORK STRUCTURE FOR SIGNAL PROCESSING AS AN EXPERIMENT PLANNING

The paper is devoted to the use of artificial neural networks for signal processing in electrical engineering and electric power industry. Direct propagation neural network (perceptron) is considered as an object in the theory of experiment planning. The variants of the neural network structure empirical choice, the quality criteria of its training and testing are analyzed. It is shown that the perceptron structure choice, the training sample, and the training algorithms require planning. Variables and parameters of neuro algorithm that can act as factors, state parameters, and disturbing influences in the framework of the experimental planning theory are discussed. The proposed approach is demonstrated by the example of neural network analysis of the industrial frequency signal of 50 Hz nonlinear distortions. The possibility of using an elementary perceptron with one hidden layer and a minimum number of neurons to correct the transformer saturation current is analyzed. The conditions under which the neuro algorithm allows one to restore the values of the main harmonic amplitude, frequency and phase with an error of no more than one percent are revealed. The signal processing in a «sliding window» with a duration of a fraction of the fundamental frequency period is proposed, and the neuro algorithm accuracy characteristics are estimated. The possibility to automate the neural network structure choosing for signal processing is discussed.

Key Technology Optimization and Development of New Energy Enterprises of Photovoltaic Power Generation

In order to improve the algorithm of time-varying parameters and unknown parameters adaptability, avoid assuming the approximate part deviation caused by the algorithm, this paper proposes a adaptive control algorithm, the algorithm based on lyapunov direct method to predict the output voltage in the process of estimating each parameter in a reasonable manner to parameter estimation error with the actual output current and current automatic adjustment. The adaptive control of current tracking is realized and the error caused by assuming voltage or current and neglecting line resistance is avoided in the predictive current control algorithm. The simulation results show that the tracking current can track the target current with high precision from t = 0 in the presence of random noise, and the power factor is close to 1, showing a good steady-state performance. Frequency domain waveform, the calculated harmonic distortion rate is 2.2418%, waveform quality is good and each harmonic amplitude is small. Conclusion: adaptive control algorithm can quickly and accurately realize current tracking and greatly suppress the noise.

Harmonic Amplitude Summation for Frequency-tagging Analysis

In the approach of frequency tagging, stimuli that are presented periodically generate periodic responses of the brain. Following a transformation into the frequency domain, the brain's response is often evident at the frequency of stimulation, F, and its higher harmonics (2F, 3F, etc.). This approach is increasingly used in neuroscience, as it affords objective measures to characterize brain function. However, whether these specific harmonic frequency responses should be combined for analysis—and if so, how—remains an outstanding issue. In most studies, higher harmonic responses have not been described or were described only individually; in other studies, harmonics have been combined with various approaches, for example, averaging and root-mean-square summation. A rationale for these approaches in the context of frequency-based analysis principles and an understanding of how they relate to the brain's response amplitudes in the time domain have been missing. Here, with these elements addressed, the summation of (baseline-corrected) harmonic amplitude is recommended.

A Fast and Simple Fault Diagnosis Method for Interleaved DC-DC Converters Based on Output Voltage Analysis

Interleaved DC-DC converters have been widely used in power conversion due to their high efficiency and reliability. In the application of new energy, this plays an increasingly important role in the grid-connected power generation of wind, solar, and tidal energy. Therefore, it is crucial to ensure the reliability and proper operation of interleaved DC-DC converters. We studied an open circuit fault (OCF) diagnosis method for a three-phase interleaved buck converter. We propose a non-invasive diagnosis method based on the output voltage using the harmonic amplitude and phase at the switching frequency as the diagnostic criteria. Evaluation was carried out on a hardware-in-the-loop (HIL) test platform to prove the validity of the proposed method. The results show that the presented method had high accuracy and robustness against OCFs, which could otherwise damage the system.

Transmission Phase Control of Annular Array Transducers for Efficient Second Harmonic Generation in the Presence of a Stress-Free Boundary

The through-transmission (TT) method is mainly used to measure the amplitude of the second harmonic from which the acoustic nonlinear parameter is determined for early damage detection of materials. The pulse echo (PE) method, however, has been excluded from nonlinear studies of solid materials because the stress-free boundary suppresses the generation of second harmonics. It is more demanding to develop the PE method for practical applications and this paper considers a novel phase shift technique of annular array transducers to improve second harmonic generation (SHG) at the stress-free boundary. The fundamental and second harmonic fields after phase-shifted radiation are calculated, and their received amplitudes are investigated. The phase difference between the two second harmonic components after reflection from the stress-free boundary is analyzed to explain the enhanced SHG. The PE method with optimal phase shift can generate an improved second harmonic amplitude as high as about 45% of the TT method. Four element array transducers are also found to be more efficient in improved SHG than two element transducers.

A Genetic-Based Hybrid Algorithm Harmonic Minimization Method for Cascaded Multilevel Inverters with ANFIS Implementation

Selective harmonic elimination pulse-width modulation (SHEPWM) is a widely adopted method to eliminate harmonics in multilevel inverters, yet solving harmonic amplitude equations is both time consuming and not accurate. This method is applied here for a 7-level cascaded multilevel inverter (CMLI) with erroneous DC sources. To meet the seven harmonic amplitude equations, two notches are applied with the use of higher switching frequency than nominal. These notches can be placed in six different positions in the voltage wave, and each was assessed in a separate manner. In order to solve the equations, a hybrid algorithm composed of genetic algorithm (GA) and Newton–Raphson (N-R) algorithm is applied to achieve faster convergence and maintain the accuracy of stochastic methods. At each step of the modulation index (M), different positions for the notches are compared based on the distortion factor (DF2%) benchmark, and the position with lowest DF2% is selected to train an artificial neural fuzzy interface system (ANFIS). ANFIS will receive the DC sources’ voltages together with required M and will produce one output; thus, eight ANFISs are applied to produce seven firing angles, and the remaining one is to determine which one of the notches’ positions should be used. Software simulations and experimental results confirm the validity of this proposed method. The proposed method achieves THD 8.45% when M is equal to 0.8 and is capable of effectively eliminating all harmonics up to the 19th order.

The Effects of Damage to the Outer Race Bearing on the Efficiency of the Induction Motor Using Fast Fourier Transform (FFT) Method

Bearing is an induction motor component that helps the rotor to move freely, in industrial applications it is important to maintain bearing performance in induction motors. In its use, bearing damage is one of the biggest types of damage that is often found in induction motors. Bearing damage can lead to increased vibration, increased noise, increased working temperature, and decreased efficiency. Efficiency reduction can be used as information on the condition of the motor so that this information can be used to detect damage before more serious damage occurs. This research discusses the stator current analysis method and the efficiency of damage to the motor through two harmonic amplitude ratios equipped with the fast Fourier transform (FFT) algorithm in detecting damage to the outer race bearing. It is hoped that this efficiency can be used as an evaluation of the extent to which motor energy waste occurs before more severe damage. The efficiency results on the damage to the outer race bearing using the FFT method get the highest efficiency value of 1.47 and the lowest value of 0.66.

Acoustic Method for Estimation of Marine Low-Speed Engine Turbocharger Parameters

The article presents the acoustic method of marine low-speed engine turbocharger parameter estimation under operating conditions when a prompt assessment of instantaneous turbocharger speed and rotor vibration level is required. The method lies in the analysis of the acoustic signal that is generated by the compressor of the turbocharger with the diesel engine running under load. The spectral analysis reveals that the compressor blades generate acoustic oscillations that are always present in the overall acoustic spectrum of the turbocharger regardless of its technical condition. The harmonic components corresponding to the blades can be detected in the spectrum using the limit method. The calculated instantaneous turbocharger speed makes it possible to analyze the main harmonic amplitude in the spectrum. The method presented in this paper helps eliminate discrete Fourier transform (DFT) spectral leakage so that the amplitude of the main harmonic can be estimated. Further analysis of the amplitude of the main harmonic allows for efficient estimation of the turbocharger rotor vibration level when in operation. The method can be practically applied by means of a smartphone or a computer that has the dedicated software installed. The proposed method lays the foundations for a permanent monitoring system of turbocharger speed and vibration in industrial and marine diesel engines.