MATLAB Application Research Articles

Simulation of AI-Based PID Controllers on DC Machines Using the MATLAB Application

Simulation of AI-Based PID Controllers on DC Machines Using the MATLAB Application

ТЕОРЕТИЧЕСКИЕ ПРЕДПОСЫЛКИ ОПРЕДЕЛЕНИЯ ФОРМЫ И РАЗМЕРА ОЧАГА РАСПРОСТРАНЕНИЯ ОЗОНА В ЗЕРНОВОМ ВОРОХЕ

It is known that at the present stage of development of the agro-industrial complex, the ozonation process is increasingly being used. This is an environmentally friendly method of processing agricultural raw materials in order to disinfect, deodorize, disinsect, increase the growth qualities of seeds, etc. It is worth noting that, despite such an active use of ozone, the question remains not fully understood how the gas spreads in the grain during its processing. The article presents the results of research to determine the shape and size of the source of the ozone-air mixture divergence in the grain heap. It has been experimentally established that the ozone in the grain diverges in a shape close to an ellipsoid. The size of the lesion depends on the saturation time and, as a result, the received dose of ozone treatment. As the duration of the experiment increases, the radius of the ellipsoid increases more than its height. Based on the results of experimental studies in the Matlab program, a model of the behavior of ozone in grain is constructed depending on its processing modes. Using regressions based on Gauss processes, the shape and size of the distribution center of the ozone-air mixture in the grain were predicted with a change in the ozonation time. The selection of model parameters is based on Bayesian optimization in the Regression Learner application from the Statistics and Machine Learning Toolbox of the Matlab application software package. The electronic program allows you to optimize hyperparameters and obtain confidence intervals for predicted values. The research results make it possible to predict the behavior of ozone in grain, which is necessary to determine the number of gas supply nozzles inside a granary of any volume.

ТЕОРЕТИЧЕСКИЕ АСПЕКТЫ ВЗАИМОДЕЙСТВИЯ ОЗОНА С ЗЕРНОМ

Despite the popularization of ozone technologies in agriculture, the theoretical aspects of the interaction of an ozone-air mixture with grain material remain under study. The simplified assumption that the change in the amount of ozone absorbed by the grain is proportional to the initial gas concentration does not accurately describe this process. Attempts to analytically determine a certain constant of the rate of ozone absorption by a unit of grain volume were also unsuccessful. The resulting expression was transcendental at that time. Its solution was possible only when performing repetitive calculations, that is, using the iteration method on a personal computer. The use of the modern Matlab application software package made it possible to establish a constant rate of ozone absorption per unit grain volume. However, the experiments have shown that during the experiment this constant changes significantly, including depending on the conditions, therefore this theoretical approach requires clarification. The laws known in physics describing the diffusion process have been adapted to the ozone treatment process. The application of the Langmuir-Schaefer equation for the number of ozone molecules adsorbed on the grain surface and Fick's second law made it possible to determine the rate of ozone diffusion and the change in ozone concentration over time, taking into account the characteristics of the grain pile. A dependence was obtained for the ozone diffusion coefficient, which characterizes the ability of grains to absorb ozone through cell membranes, and the ozone decomposition constants. Under normal storage conditions, these temperature-dependent values can be considered constant. The analytically obtained dependences will allow us to determine the ozone diffusion coefficient and the ozone decomposition constant experimentally.

ДОСЛІДЖЕННЯ ПОДВІЙНИХ ЗАМКНЕНЬ НА ЗЕМЛЮ В МЕРЕЖАХ 10 КВ З ІЗОЛЬОВАНОЮ НЕЙТРАЛЛЮ

Reliability indicators of power supply systems as a whole are largely determined by the level of reliability of distribution electrical networks with a voltage of 6-35 kV. Emergency in networks with a voltage of 6-35 kV, operating in the mode with an isolated neutral, is often associated with internal overvoltages. Single-phase short-circuits occur in places of defects in the insulation of cable lines and substation equipment due to the aging of the insulation, non-compliance with the manufacturing technology of insulating structures at factories, non-compliance with the requirements of the instructions during the installation and operation of the equipment, as well as due to mechanical damage, which, sometimes at the time of their appearance, lead to only a partial decrease in electrical strength. Overloads lead to defects. Single-phase short-circuits in 10 kV networks that are not eliminated in time can lead to double earth faults. For protection in these networks, such protections as current cut-off, maximum current protection, current cut-off, zero-sequence current protection, current protections with blocking at minimum voltage are used. However, there are cases when there are cases of negative operation of such protections at a 10 kV substation during double earth faults. For example, a phase A short circuit occurred on the first line, which receives power from the buses of the investigated substation, and another short circuit (phase B) occurred on the second line. Instead of tripping the two damaged lines, the input circuit breaker tripped by mistake. This de-energized other (undamaged) lines that are fed from the same bus section as the damaged lines. Under such conditions, further studies of the currents in the lines during double circuits are required. For this, the use of the Matlab application program package is justified. This will significantly reduce the costs of physical modeling and verification of proposed proposals. The paper presents the results of studies of double earth faults in 10 kV networks with an isolated neutral in the "MATLAB" program package.

Adaptive Beamforming Based on Artificial Neural Networks

Adaptive beamforming is technique of signal processing play important role to increasing capacity of the wireless communication and radar systems by configured the steerable of radiation pattern and maximize gain and directivity in a direction of arrival (DoA) of desired users in order to minimizing side lobe and reducing signal to interference. We review recently the classic technique of adaptive algorithms; we specified tow method for this preprocessing beam former LMS and RLS. The least Mean Square (LMS) operate the weight vectors of antenna array elements for beamforming by iterative process as well need to be continuously adapted to the ever-changing environment. Moreover recursive least square (RLS) give advantage for fast convergence beamforming. In this paper we proved the performance of this algorithms by updating the weights in addition process based on estimated vectors using neural network, The first phase for smart beam former are used by direction of arrival (DoA) estimated using radial basis neural network (RBFNN). In next step the targets is generated from the optimum weight calculated using Minimum Variance Distortion less method (MVDLM). Finally, the simulation result for the new process is synthetized and shows using Matlab application.

Artificial neural network-based home energy management system for smart homes

<p>Energy efficiency is widely recognized as one of the most significant and economical ways to lower greenhouse gas (GHG) emissions. The aims and goals are that smart meters can evaluate and communicate in-depth real-time electricity usage, enable remote real-time monitoring and management of power consumption, and provide consumers with real-time pricing and analyzed usage information. The house energy management controller decides which loads will be powered based on the real home energy demands and the predefined load priorities. Artificial intelligence (AI) is being used increasingly in control applications due to its great effectiveness and efficiency. As a result, in this work, the author designed, simulated, and optimized an artificial neural network-based model simulation framework that simulates a home with a variety of home appliances and optimizes the total energy consumption of the home realistically through intelligent control of home appliances. The MATLAB application was used to model and examine the performance of four common household appliances: the water heater (WH), washing machine (WM), air conditioner (AC), and refrigerator (RG). The result shows a considerable reduction and savings in energy consumption without a decrease in consumer comfort.<strong></strong></p>

Nanopore Fabrication Made Easy: A Portable, Affordable Microcontroller-Assisted Approach for Tailored Pore Formation via Controlled Breakdown.

With growing interest in solid-state nanopore sensing─a single-molecule technique capable of profiling a host of analyte classes─establishing facile and scalable approaches for fabricating molecular-size pores is becoming increasingly important. The introduction of nanopore fabrication by controlled breakdown (CBD) has transformed the economics and accessibility of nanopore fabrication. Here, we introduce the design of an Arduino-based, portable USB-powered CBD device, with an estimated cost of <150 USD, which is ≈10-100× cheaper than most commercial solutions, capable of fabricating single nanopores conducive for single molecule sensing experiments. We demonstrate the facile fabrication of 60 tailored nanopores (∼2.6-12.6 nm) with ∼80% of the pores within 1 nm of the target diameter. Selected pores were then tested with double-stranded DNA, the canonical molecular ruler, demonstrating their performance for single-molecule sensing applications. The device is constructed with off-the-shelf readily available components and controlled using a highly customizable MATLAB application, which has capabilities encompassing pore fabrication, pore enlargement, and current-voltage acquisition for pore size estimation. When combined with a portable amplifier, this device also provides a fully portable sensing platform, an important step toward portable solid-state nanopore sensing applications.

Preissmann Four-Point Methods for Solution of Simplified Saint-Venant Equations Applied to Flood Routing in Prismatic Open Channels

This research goal to compare the flow properties in the rectangular and trapezoidal open channels by examining the influence of the channel side slope is depicted by simplified Saint Venant Equations. The solution of these equations has been completed numerically by using Preissmann four-point scheme. The model is simulated using the Matlab application to point out the flow properties. The proposed model is validated by the model without simplification which was selected from the literature. The validation outcomes indicate that in common, the simulation outcomes of the two models have a good agreement. The simulation results show that the greater the slope of the channel side, the greater the peak discharge and the greater the time shift. The analysis emphasizes how channel geometry influences flow behavior, indicating that trapezoidal channels, with inclined side slopes z, yield slightly higher peak discharges compared to rectangular ones. For z = 0, discharge of peak Q = 7.38 m3/s and t = 18 s. For z = 2, discharge of peak Q = 7.39 m3/s and t = 21 s. For z = 4, discharge of peak Q = 7.45 m3/s and t = 23 s. For z = 6, discharge of peak Q = 7.51 m3/s and t = 24 s.

Achieving Green Construction Rating in Building Projects with Fuzzy System Approach

Green construction is a way of planning and managing construction projects to minimise the impact of the construction process on the environment so that there is a balance between environmental capabilities and human needs for current and future generations. Appropriate Land Use (ASD), Energy Efficiency and Conservation (EFC), Water Conservation (WAC), Material Sources and Cycles (MRC), Air Quality and Space Comfort (IHC), and Building Environmental Management (BEM) are six guidelines for evaluating green building assessments. These are used as a benchmark for green buildings; a check is carried out to determine the rating of the building. The evaluation is carried out by distributing questionnaires. The data is processed using the Fuzzy method through the Matlab application, which refers to the Greenship 1.2. The results showed that the calculation analysis with the help of MS Excel and modelling with a fuzzy system in the Matlab application gave the same predicate results. Validation of modelling results with case studies on Building Projects in Malang City showed Bronze predicates with a total index of 44 Points and Silver predicates with a complete index of 57 Points.

Application of Mathematical Modeling Based on MATLAB in Experimental Data Analysis

In order to serve the "Manufacturing Power", adapt to the new scientific and technological revolution and industrial change, and support the innovation-driven development, the Ministry of Education (MOE) has been vigorously promoting the construction of the "new engineering discipline", exploring a new engineering education model in China, and serving the construction of the "Education Power". Education Power". New Engineering is an important initiative for Chinese universities to realise the principle of cultivating innovative talents, and it is also a major development trend and choice for the development of Chinese higher education. In the rapid development of education today, the integration of modern information technology into classroom experiments is essential to improve the teaching effect. This paper discusses the application of MATLAB in mathematical modelling to analyse experimental data, especially in physics experiments. Using MATLAB, students can deepen their understanding of mathematical concepts and physical principles through visualisation and interactive programming. In this study, MATLAB was used to assist teaching and learning, and a comparison experiment was conducted between a control group and an experimental group. The results show that MATLAB can significantly improve students' understanding and retention of knowledge, stimulate learning interest and enhance modelling ability. Analysis of the experimental data showed that the average score of students in the MATLAB-assisted class was 71.06, which was significantly higher than that of the traditional class (65.64), highlighting the effectiveness of MATLAB in enhancing students' understanding and retention of physics concepts. However, some challenges such as increased complexity and additional learning burden were also identified. The paper concludes with recommendations for the effective integration of MATLAB into the curriculum, emphasising its role as an aid to traditional physics teaching.

НЕЙРОНЕЧЕТКИЙ КЛАССИФИКАТОР ОЦЕНКИ УРОВНЯ ЗНАНИЙ ОБУЧАЮЩИХСЯ

This article is devoted to the solution of the problem of constructing a neuro-fuzzy classifier for assessing the level of students' knowledge. Currently, intelligent systems for assessing complex technical, biophysical and socio-economic systems have undergone rapid development and are often based on the use of neural networks, fuzzy logic methods and procedures for forming rule bases based on data analysis. In this work, a neuro-fuzzy classifier was used to assess the level of students' knowledge. The User Knowledge Modeling dataset for training the fuzzy neural network was obtained from the open source Machine Learning Repository. The number of copies in the dataset is 403, and the number of attributes for classification is 5. Four gradations are distinguished for the level of students' knowledge - very low, low, medium and high. This corresponds to the Russian assessment system: unsatisfactory, satisfactory, good and excellent. In the Deductor environment, a preliminary analysis of data quality, work with outliers and extreme values, checking for duplicates and contradictions, as well as correlation analysis of input and output parameters were carried out. After processing, the data were randomly divided into training and test samples in the ratio of 70% and 30%, respectively. To build a neuro-fuzzy model, the ANFIS editor from the MATLAB application package was used. The fuzzy inference system contained 5 input variables with 3 fuzzy gradations and 1 output variable. As a result of training, 128 fuzzy rules corresponding to the model structure were formed. When building a neuro-fuzzy classifier, fuzzy neural networks with various combinations of the training method, type of membership function of the input and output parameters were used. The lowest value of the root mean square error, equal to 0.16, was achieved in the model with the following parameters: training method - back propagation of the error, membership function of the input variables - double Gaussian, membership function of the output variable - constant. To assess the adequacy of the neuro-fuzzy model, errors of the first and second kind were calculated. The error of the first kind on the test data was 0%, the error of the second kind - 4.6%. The accuracy of the neuro-fuzzy model was 95.6% and was higher than when using other methods of data mining: neural network, decision tree, linear and logistic regression. Thus, the constructed neuro-fuzzy model showed high accuracy in assessing students' knowledge and can be effectively used in the educational process to solve the task.

УПРОЩЕННАЯ КОМПЬЮТЕРНАЯ МОДЕЛЬ ВЕТРОЭНЕРГЕТИЧЕСКОЙ СИСТЕМЫ НА ОСНОВЕ ДВУХ МАГНИТОЭЛЕКТРИЧЕСКИХ ГЕНЕРАТОРОВ С РЕКОНФИГУРИРУЕМЫМИ ОБМОТКАМИ

Relevance Due to the growing demand for electricity and the reduction in reserves of traditional energy sources, energy conservation and the use of alternative sources are becoming increasingly important. Wind energy is an important growth industry in the production of electricity from renewable wind energy, playing an important role in diversifying energy sources and reducing dependence on the unstable political and economic factors associated with the extraction and transportation of fossil fuels. Wind energy, from a scientific point of view, is a field of science and technology that develops the theoretical foundations, methods and means of using wind energy. To convert the kinetic energy of the wind flow into mechanical energy of rotation of the generator rotor with its subsequent conversion into electrical energy, wind power plants of various configurations are used, installed in open areas where the wind has a suitable speed for generating electricity. Of particular interest to researchers, engineers and the public around the world is the issue of developing new wind power plants and improving existing ones. Thus, wind energy has great interest in the modern world, representing an important and promising option for diversifying the energy system, reducing environmental pollution and providing a sustainable and economically attractive source of energy for future generations. Aim of research To study the operating modes at low and normal wind speeds of a wind power system model based on two magnetoelectric generators with reconfigurable windings in the Matlab application package (Simscape). Research methods Simulation of operating modes at low and normal wind speeds of a wind energy system based on two magnetoelectric generators with reconfigurable windings in the Matlab application package (Simscape). Results A study was carried out of the operating modes at low and normal wind speeds of a wind energy system based on two magnetoelectric generators with reconfigurable windings in the Matlab application package (Simscape). This voltage regulation method can provide the ability to stabilize voltage and maintain high efficiency at an acceptable level over a wider range of low and normal wind speeds.

Establishing a Mouse Genotyping Core Facility Based on Automation, High-resolution Melting Analysis, and Purpose-developed MATLAB Applications for Sample Tracking, Data Analysis, and Report Generation

An in-house genotyping facility should aim to be more cost-effective than outsourced service and more reliable than genotyping performed by short-term employees or students of individual research groups. Reliable genotyping allows efficient and economical management of mice colonies and promotes accurate and reproducible research results. Here we provide a detailed description of our approach to establishing a genotyping core facility, relying on automated PCR assembly and high-resolution melting (HRM) analysis (first derivative). The workflow we devised was tightly managed by purpose-designed applications developed using MATLAB App Designer that allowed straightforward work planning, ensured sample tracking throughout the process, and provided a platform for reliable data analysis and generation of genotyping reports. We successfully transitioned PCR product analysis of more than 250 different target genes from standard gel electrophoresis to the more advanced HRM analysis. About 23% of the target genes required a redesign of primers to adapt to our protocol. The process was highly universal, and only 2% of the target genes required deviation from the standard PCR method to a more restricted protocol that reduces the amplification of nonspecific products. We currently run more than 1,000 PCR reactions weekly, of samples taken at weaning or experimental endpoint, and assemble a large variety of target genes in every PCR plate. We also showed that genotyping of blastocytes instead of embryos can serve as quality control of cryopreservation. Thus, our genotyping protocol promotes the 3Rs (Replacement, Reduction, and Refinement) principles. Our refined genotyping process facilitates cost-effective colony management, replaces tissue types as well as traditional methods with advanced ones, and provides reliable results in a timely manner. MATLAB codes and related data are available in supplementary materials and online.

Studying the resistance to ultraviolet radiation of products with paintwork in a UV chamber

The research presented in this article is devoted to testing samples of plastic cladding panels with paint coating of different colors, in order to assess its technical characteristics and resistance to climatic conditions. Paint and varnish coatings form a barrier preventing the penetration of moisture and aggressive substances, thereby extending the service life of the equipment. As part of the experiment, two samples of paintwork were provided for further analysis. The test methodology included visual inspection of the objects, roughness measurement and microscopic analysis with further application of Matlab application program package. The experimental results showed that both paintwork samples changed their color. Analysis of the roughness data showed that the white sample performed slightly better, as well as when analyzing the data obtained from the microscope. Additional research and testing can be done to improve the design of the switches and increase their durability in service.

Establishing a Mouse Genotyping Core Facility Based on Automation, High-resolution Melting Analysis, and Purpose-developed MATLAB Applications for Sample Tracking, Data Analysis, and Report Generation.

An in-house genotyping facility should aim to be more cost-effective than outsourced service and more reliable than genotyping performed by short-term employees or students of individual research groups. Reliable genotyping allows efficient and economical management of mice colonies and promotes accurate and reproducible research results. Here we provide a detailed description of our approach to establishing a genotyping core facility, relying on automated PCR assembly and high-resolution melting (HRM) analysis (first derivative). The workflow we devised was tightly managed by purpose-designed applications developed using MATLAB App Designer that allowed straightforward work planning, ensured sample tracking throughout the process, and provided a platform for reliable data analysis and generation of genotyping reports. We successfully transitioned PCR product analysis of more than 250 different target genes from standard gel electrophoresis to the more advanced HRM analysis. About 23% of the target genes required a redesign of primers to adapt to our protocol. The process was highly universal, and only 2% of the target genes required deviation from the standard PCR method to a more restricted protocol that reduces the amplification of nonspecific products. We currently run more than 1,000 PCR reactions weekly, of samples taken at weaning or experimental endpoint, and assemble a large variety of target genes in every PCR plate. We also showed that genotyping of blastocytes instead of embryos can serve as quality control of cryopreservation. Thus, our genotyping protocol promotes the 3Rs (Replacement, Reduction, and Refinement) principles. Our refined genotyping process facilitates cost-effective colony management, replaces tissue types as well as traditional methods with advanced ones, and provides reliable results in a timely manner. MATLAB codes and related data are available in supplementary materials and online.

РОЗРОБКА МАНІПУЛЯТОРА ДЛЯ ПОВНОЇ АВТОМАТИЗАЦІЇ ПРОЦЕСУ ЗАРЯДЖАННЯ ЕЛЕКТРОМОБІЛЕЙ

Electric cars are gradually gaining popularity both in the world and in Ukraine. But in order for them to be freely used throughout the country, an appropriate infrastructure is needed. Unlike traditional cars with internal combustion engines, electric cars can be refuelled anywhere there is access to an electrical outlet. The main problems of electric cars during their operation over long distances are related to the duration of the journey on one charge and the low development of the infrastructure for them. Systems of automated charging stations are also gradually developing. There are already terminals of charging stations with payment by bank card and other payment systems, but they work on the principle of self-service. For full automation of the charging process, connecting the charging station to the electric car without human intervention is not enough. Wireless charging can solve this problem, but at this stage of development, the power transferred in this way is not always enough. To solve this problem, a combination of a manipulator arm and a typical charging station was proposed. The manipulator will determine the vehicle's position and insert the charging station's socket into the car's plug using sensors and machine vision. As part of this work, we made a conceptual project of a manipulator that will automatically connect the connector of the charging station to the car. Also, for this charging complex, a system of monitoring and protection of the electrical connection of the charger with the consumer against short circuit, overheating, sparking and arcing connector was developed, taking into account various interchangeable connectors. When developing the manipulator's arms, the following tasks were taken into account: ensuring sufficient kinematic freedom of movement to cover the working area of the charging station service and maximally simplifying the design. To reliably ensure access to any point of the working space, a kinematic scheme with two translational and three rotational links was used. Next, to determine the position of the manipulator in the workspace, the direct and inverse kinematics problems for this scheme were solved. The physical model of the manipulator along with servomotors, PID controllers and control system based on the equations of kinematics problems was simulated in the Matlab application software package. The implementation of a machine vision system and a switching device protection system is proposed for a full-fledged control system of the automated charging station. The resulting design of the automated charging station is experimental and does not have many analogues in the world. The modularity of the design ensures the versatility of its use at other types of charging stations, as well as the possibility of its modernization.

Clustering Disease on Settlements Inhabitant In place seedy With Use Clustering Method

Residents living in slum areas often face serious problems related to public health, where the prevalence of disease tends to be high and its spread is difficult to control. The impact of the formation of slums for the community is that safety is threatened, health deteriorates, and social conditions worsen, causing many diseases for people living in slums. Therefore, this study aims to identify patterns and clusters of diseases that exist in residential areas in slums Binjai city using clustering method. The K-Means Algorithm clustering method was chosen because it is able to group data based on similar characteristics, so that it can help identify diseases in a more focused and efficient manner, using the MATLAB application is also very appropriate in this problem so that it can produce output from data mining that can be used in decision making. future decisions. By utilizing the data mining process using the clustering method, clustering can be a problem of grouping diseases in slum settlements. Based on the results of trials with 20 sample data conducted with MATLAB obtained in cluster 1 DHF cases with high slums, Cluster 2 cases of vomiting with moderate slums and cluster 3 cases of diarrhea with moderate slums. The results of this study are expected to provide in-depth insight into disease patterns and clusters in residential areas in slums.

The Application of MATLAB in Mathematics: An Overview

This research paper aims to provide an overview of the application of MATLAB in mathematics. MATLAB is a widely used software tool in the field of mathematics, providing a user-friendly environment for numerical computations and visualization of data. The paper covers various areas of mathematics in which MATLAB can be applied, including linear algebra, calculus, differential equations, and statistics. The paper also highlights the advantages of using MATLAB in mathematical research, such as its ability to handle large data sets and its ability to perform complex numerical computations efficiently. The paper concludes with a discussion on the future of MATLAB in mathematical research and its potential to revolutionize the field.

Identification of metabolites from complex mixtures by 3D correlation of 1H NMR, MS and LC data using the SCORE-metabolite-ID approach

Not only in metabolomics studies, but also in natural product chemistry, reliable identification of metabolites usually requires laborious steps of isolation and purification and remains a bottleneck in many studies. Direct metabolite identification from a complex mixture without individual isolation is therefore a preferred approach, but due to the large number of metabolites present in natural products, this approach is often hampered by signal overlap in the respective 1H NMR spectra. This paper presents a method for the three-dimensional mathematical correlation of NMR with MS data over the third dimension of the time course of a chromatographic fractionation. The MATLAB application SCORE-metabolite-ID (Semi-automatic COrrelation analysis for REliable metabolite IDentification) provides semi-automatic detection of correlated NMR and MS data, allowing NMR signals to be related to associated mass-to-charge ratios from ESI mass spectra. This approach enables fast and reliable dereplication of known metabolites and facilitates the dynamic analysis for the identification of unknown compounds in any complex mixture. The strategy was validated using an artificial mixture and further tested on a polar extract of a pine nut sample. Straightforward identification of 40 metabolites could be shown, including the identification of β-d-glucopyranosyl-1-N-indole-3-acetyl-N-l-aspartic acid (1) and Nα-(2-hydroxy-2-carboxymethylsuccinyl)-l-arginine (2), the latter being identified in a food sample for the first time.

Impedance network-based oscillatory stability analyzer (INOSA) – A frequency domain tool for investigating IBR-grid interactions

Unstable subsynchronous oscillations (SSOs) may be excited due to adverse interactions between inverter-based resources (IBRs) and series-compensated or weak ac networks. The frequency-sweep impedance modeling and analysis method is widely used for scanning grid-tied IBRs against the risk of SSO. The stability of such a system is heavily influenced by system-wide parameters such as IBR dispatching conditions (input resource, and different dispatch scenarios), and network status (short-circuit and/or series-compensation levels). The variation in the operating conditions must be taken into account when conducting frequency-scanned impedance-based modeling and analysis. This paper proposes a tool, named impedance network-based oscillatory stability analyzer (INOSA), which integrates decades of research on impedance-based analysis to investigate the risk of SSO under varying operating conditions. The INOSA tool is developed as a MATLAB application package. It takes the available system parameters and frequency-scanned impedance data as input and processes it to carry out impedance network-based stability analysis under all operating conditions. The developed tool outputs key stability information such as damping and frequency of each oscillation mode, and a multi-dimensional security boundary/region plot that can be used to assess the risk of SSO and take appropriate measures. A case study on an actual power system is presented to demonstrate the features and capability of the analysis tool.