فصلنامه روشهای هوشمند در صنعت برق
پیاپی 51 (پاییز 1401)

 In the handling of medical images, the main priority is to secure protection for the patient’s documents against any act of tampering by unauthorized persons. Thus, the main concern of the existing electronic medical system is to develop some standard solution to preserve the authenticity and integrity of the content of medical images.Accordingly, digital image watermarking has many applications, one of its most important applications in Protection of medical images, engrave names, Signatures and Patient data on pictures, Videos etc. that are not so clear.There are several ways to digital image watermarking, but one of the most widely used methods to achieve robust watermarking to all kinds of attacks using the combination dwt and svd.We used in this research 2 level of haar wavelet transform on the host image and one level of single value decomposition on its low frequency subset and combined with a watermark coefficient and another level of singular value decomposition to embed the watermark and increase the watermark robustness in a way that when extracting a watermark can be done semi-blindly. With this method, we were able to improve the average peak signal to noise ratio of 55 and 7% improvement for the invisibility of the watermark and also the average correlation coefficient of 0.97 and 34% improvement to increase the resistance of the watermark to various attacks.

According to the critical role of gas turbines in the industry, monitoring the performance of gas turbines is an important issue since it can prevent unexpected shutdowns and the serious consequent financial harms. One of the most important parts of a gas turbine is the combustion chamber. Although the internal pressure and temperature of the combustion chamber can directly affect the performance and useful life of this part, however, it is not possible to measure it directly through sensors. Therefore, estimation of pressure variable is a good choice to achieve greater performance and more relative stability comparing with the methods in which there is no access to the internal pressure of the chamber. In this research, a suitable nonlinear dynamic model with produced power and exhausted gas temperature as its outputs is chosen. Thereafter, an adaptive surface sliding observer is designed in order to estimate the combustion pressure and temperature which are the state variables of the gas turbine. Afterward, utilizing a sliding mode controller and applying the estimated states, the produced power and exhaustion gas temperature of the gas turbine is controlled. In this paper, the stability of the closed-loop system in the presence of the state observer through the Lyapunov approach is guaranteed. Finally, simulation results are provided to verify the validity and efficiency of the proposed method.

Most control systems use a dedicated communication network with specific protocols. Intrusion detection systems developed based on network traffic with standard protocols, or existing datasets can not detect significant threats on these control systems. New sophisticated malicious codes usually attacked these systems by sending known and understandable commands to the control systems and ultimately sabotaging the physical process. These attacks do not alter network traffic, so they are not detectable with standard network-based intrusion detection systems. In this paper, we proposed an innovative combined method for identifying different types of attacks on control systems with a dedicated network. We have provided a combination of methods for detecting semantic or stealth attacks and identifying attacks that affect the traffic of the control system network. For the first time in practice, the effect of common types of attacks on a control system with a specific network has been investigated, and the rules for detecting these attacks have been obtained. Experimental results in this study show that the extracted rules identify 100% of the already known attacks. The proposed new approach, based on identifying the control system commands from the extracted network records, also thoroughly detects semantic attacks. The process data behavioral method used in this study can detect about 99% of semantic attacks using classification algorithms base on Data set which is created in this study.

Today, with the depletion of fossil fuels, the trend towards using renewable energies has increased. Among the various types of renewable energy resources, solar systems received more attention due to technical, environmental and economic reasons. However, the efficiency of solar panels is not high due to several reasons. In addition to using high-efficiency control equipment such as maximum power point tracking (MPPT) methods, cleaning the surface of solar panels is one of the best and easiest ways to improve their efficiency and performance. In this paper, to increase the efficiency of solar panels, a robot for cleaning solar panels with the ability to adjust the height with the help of tank wheel technology has been developed. Moreover, due to water shortages in the country, the design of this robot has been done without the use of water. Considering that the designed robot has a telecommunication system with remote control capability, the speed of cleaning is very high and there is no need for the operator. The used software in the robot provides proper scheduling for the cleaning of solar panels. In addition to the aforementioned advantages, the proposed robot has a much lower price than foreign products. The performance of this robot on the five kW solar power plant of Tafresh University has been evaluated. Increasing the efficiency of the power plant, more revenue from the sale of energy to the grid and significant savings in water consumption are the main advantages of this intelligent robot.

In this paper, an ultra-low-power, second-order, discrete-time sigma-delta converter is proposed for hearing aids application. In portable biomedical devices such as hearing aids that permanently use, the battery lifetime and power dissipation are very considerable. In a typical delta-sigma modulator, the OTAs are the most power-consuming parts. The OTAs elimination in the converters is now challenging. Therefore the converter with a self-biased fully differential inverter-based amplifier was designed with only 1.15 µw static power dissipation at a 1-volt power supply. The inverter-based amplifier was used instead of the OTAs in two stages of the modulator. The modulator’s structure is CIFB, single-loop, and single bit. The proposed differential modulator was designed and simulated using a standard 180 nm CMOS technology, which obtained SFDR and SNDR of 95.2878 dB and 64.004 dB, respectively. The sampling frequency is considered 2.56 MHz, and the input signal bandwidth is 10kHz. The modulator consumes power just about 5.1091 µW, and the FOMW achieves 0.197 pj/step.

In this paper, the design of damping supplementary controller in VSC HVDC transmission systems, which is the interface of Offshore Wind Power Plant (OWPP) with the main power system, is studied. First, it is shown that the speed-power curve in a wind turbine affects the damping of oscillation and electromechanical modes of the power system, and depending on the operating conditions of the turbine, the extent of this effect varies. Then, to improve the dynamic stability of the power system, the use of an optimized supplementary controller in the VSC HVDC system will be proposed. The proposed controller is added as an additional loop to the converter control circuits in VSC HVDC and will amplify the damping torque in the generators by correcting the damping coefficient of the system oscillation modes. In addition, a solution is provided to use the supplementary controller in the most optimal path, so that the most controllability on the oscillation modes and the least interference with other channels between the input-output signals are provided. To design the proposed controller, a fractional order PID controller will be used whose coefficients are adjusted through an optimized exchange market algorithm. The optimization of the algorithm is done by using mutation and crossover operators in the genetic algorithm with the aim of avoiding bats being trapped at local extremum. The simulation results show that the method proposed in this paper not only improves the dynamic stability of the power system but also strengthens the voltage profile.

In this paper, the impact of different operative variables on the quality of cutting of Inconel material 718 is studied. Utilizing Taguchi test design, the input variables including carbon dioxide laser power and the cutting speed for cutting three different thicknesses of Inconel 718 alloy were investigated in order to achieve the optimal conditions. After obtaining experimental test results, dataset was modeled using artificial neural networks. The neural network model is then used for evaluating candidate solutions in particle swarm optimization (PSO) algorithm which is employed for optimization of cutting conditions. The results indicated that when the laser power of is 1714 (W), the cutting speed is 1382 (mm/min) and the thickness of the material is 0.8 (mm), The best quality for cutting Inconel 718 is achieved with a carbon dioxide laser cutting machine. The results of optimal cutting parameters of Inconel alloy with carbon dioxide laser which were obtained by PSO were verified through an experimental test and similar papers. The results of this experimental test were very close to the optimal values of the PSO, which demonstrates the efficiency of neural network model in predicting the quality of cutting and the efficiency of PSO in finding optimal conditions.

In this paper, a new soft switched non-isolated high step-up DC-DC converter is proposed. An auxiliary circuit with minimum number of elements is added to the converter to provide the soft switching conditions for all the semiconductors solving the reverse recovery problem of the diodes, and reducing the conduction and the switching losses of the power switches. Moreover, there is only one magnetic core used in the converter decreasing the copper resistance; thus, the power losses and the electromagnetic interference of the converter is reduced so the efficiency of the proposed converter compared to the conventional hard switched boost converter, is improved. Further, in order to adjust the output voltage of the proposed converter to the desired value under the load variations, a PI controller has been applied to the output of the proposed converter and its operation is simulated by MATLAB. In order to verify the theoretical analysis of the soft switching operations, a 250W prototype is implemented and its experimental results are provided.

Renewable energy has been developed in recent years due to the limited sources of fossil fuels, their possibility of depletion, and the related environmental issues. The main challenges of these type of systems is reaching to the optimum size in order to have an affordable system based on storing the solar and wind energy. In this paper, optimization of a solar-wind hybrid system is presented with a saving battery system for supplying a specific hourly load annually to minimize annual system expenses and the probability of Loss of Power Supply Probability (LPSP). Annual expenses of the system include initial investment, maintenance, and replacement costs. The purpose of optimization is to determine the numbers of solar panels, wind turbines, batteries, the height of the wind tower, and the angle of the solar panel toward solar radiation. For this issue, a new method named Grasshopper Optimization Algorithm (GOA) is employed. Also, the effects of changes in inverter efficiency, load demand, and of maximum probability of LPSP on system designing are evaluated. Simulation results show that the efficiency reduction, load increase, and increasing the load and maximum reliability in the system in the form of reducing of LPSP lead to an increase in annual energy costs of systems. Furthermore, the results indicate the superiority of the GOA method toward particle swarm optimization (PSO) in reaching better target function and less cost.