Article
Engineering, Multidisciplinary
Snehsheel Sharma, S. K. Tiwari, Sukhjeet Singh
Summary: This paper introduces an integrated approach using permutation entropy and flexible analytical wavelet transform for the detection and classification of faults in rolling bearings of rotary machines. By comparing the classification results of two different methods, it is demonstrated that the FAWT-PE approach is more effective for fault detection and classification.
Review
Physics, Multidisciplinary
Rodrigo Capobianco Guido
Summary: Wavelet-based analyses have made remarkable achievements in physics and related sciences. However, many people still misunderstand the fundamentals of wavelets. This article provides clear explanations of different types of wavelet transforms and their applications, helping readers to effectively utilize wavelets in their research.
PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS
(2022)
Article
Chemistry, Analytical
Huibin Zhu, Zhangming He, Juhui Wei, Jiongqi Wang, Haiyin Zhou
Summary: This paper proposes a bearing fault diagnosis method based on feature fusion, which extracts the time-frequency features of bearing signals through Wavelet Packet Transform and constructs Multi-Weight Singular Value Decomposition to effectively diagnose bearings. The proposed method shows better fault diagnosis and feature extraction capabilities compared to traditional methods.
Article
Computer Science, Information Systems
Hidangmayum Saxena Devi, Hitesh Mohapatra
Summary: This paper aims to develop a new, robust, and efficient blind watermarking system for medical images such as CT scan, X-ray, MRI, and Ultrasound Dicom images. The proposed scheme uses three binary watermark images to hide them in the cover image using a novel GWO-optimized hybrid DWT-DCT-SVD approach. The combination of DWT and DCT is used to determine the hiding positions, while SVD transforms the DCT matrix into a singular matrix and grey wolf optimization determines the gain value for inserting message bits. The proposed method outperforms existing systems in most image processing attacks, as observed from the experimental results.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Acoustics
Shaul Hameed Syed, V. Muralidharan
Summary: This study investigates the fault diagnosis of planetary gearbox using discrete wavelet analysis combined with Artificial Neural Network and Support Vector Machine. The research finds that the mean square energy of detailed coefficients of Discrete Wavelet Transform shows excellent fault diagnosing characteristics.
Article
Computer Science, Information Systems
Yuniel Leon-Ruiz, Mario Gonzalez-Garcia, Ricardo Alvarez-Salas, Juan Cuevas-Tello, Victor Cardenas
Summary: Support Vector Machine algorithm is selected as the most suitable classifier for fault diagnosis, capable of online operation without increasing the overall system cost, and proven reliable even under measurement errors in a wide range of irradiance levels.
Article
Mathematics, Interdisciplinary Applications
Guodong Ye, Huishan Wu, Min Liu, Xiaoling Huang
Summary: In this paper, a reversible image-hiding algorithm based on a novel chaotic system is proposed using compressive sensing and singular value sampling techniques. The algorithm extracts the plain messages from the secret image and encrypts them using the RSA algorithm. It then transforms the messages into initial keys, which are used to produce a random key stream. The secret image is scrambled and partitioned, and the non-zero blocks are sampled using CS. The new sampling values are embedded into the wavelet coefficients to obtain a new carrier image containing the secrets.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Engineering, Multidisciplinary
K. S. Swarna, Arangarajan Vinayagam, M. Belsam Jeba Ananth, P. Venkatesh Kumar, Veerapandiyan Veerasamy, Padmavathi Radhakrishnan
Summary: This study introduces an ensemble Random Subspace classifier for discrimination of High Impedance Fault in photovoltaic power network, achieving higher accuracy and success rate through feature extraction and learning.
Article
Agriculture, Multidisciplinary
Deepak Mishra, Anil Kumar, Vijaypal Singh Rathor, G. K. Singh
Summary: This paper proposes a hybrid compression technique based on DWT and SVSR, which is quite effective for compressing different types of crop images and achieves significantly higher compression over existing techniques.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2023)
Article
Energy & Fuels
Feifei Xu, Yang Liu, Lei Wang
Summary: To solve the problems of random initialization of weights and thresholds in extreme learning machines (ELM) and the lack of distance selection in fault detection using artificial intelligence algorithms, a fault diagnosis method for microgrids based on whale algorithm optimization-extreme learning machine (WOA-ELM) is proposed. The results show that the WOA-ELM method improves accuracy in fault detection by 22.5% compared to the traditional ELM method, and it has faster learning speed, stronger generalization ability, and higher recognition accuracy. This is of great significance in improving the security of smart grid.
FRONTIERS IN ENERGY RESEARCH
(2023)
Article
Engineering, Mechanical
Rismaya Kumar Mishra, Anurag Choudhary, A. R. Mohanty, S. Fatima
Summary: This paper proposes an intelligent vibration signal-based fault diagnosis approach for early identification of bearing faults, regardless of speed conditions. The approach combines frequency shift-based hybrid signal processing technique, sliding window-based feature extraction, and Henry Gas Solubility Optimization algorithm for feature selection, followed by Artificial Neural Network model training for fault classification. Experimental validation under constant and varying speed conditions demonstrates the tremendous potential of this approach in eliminating unplanned failures caused by bearing in rotating machinery.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE
(2022)
Article
Engineering, Aerospace
Mingming Zhang, Pan Kong, Anping Hou, Aiguo Xia, Wei Tuo, Yongzhao Lv
Summary: In this paper, a method for identifying signs of instability in the aerodynamic system of an axial compressor is proposed. It uses the wavelet singular spectral entropy algorithm to describe the distribution complexity of the spatial modalities in the flow field. This method accurately distinguishes the stable and unstable states of the internal flow field and shows significant advantages in early warning for compressor stall.
Article
Automation & Control Systems
Jae-Beom Ahn, Hyun-Bin Jo, Hong-Je Ryoo
Summary: This article introduces a method for detecting series arc faults in photovoltaic systems based on noise pattern analysis. The proposed method distinguishes between system noise and arc noise and prevents false detection. The method uses periodic feature analysis and zero-range density analysis to achieve false detection prevention and detect arc noise. The reliability of the method is verified through noise distinction experiments.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Computer Science, Information Systems
Yuan-Min Li, Deyun Wei, Lina Zhang
Summary: This paper proposes a robust double-encrypted watermarking algorithm based on FRFT and DCT in the invariant wavelet domain, achieving high robustness against different attacks by utilizing RIDWT and cosine transform to obtain a hybrid domain. The algorithm enhances security by double-encrypting the watermark with the Arnold transform and FRFT before applying singular value decomposition. The optimal embedding factors are obtained using multiparameter particle swarm optimization to balance invisibility and robustness.
INFORMATION SCIENCES
(2021)
Article
Computer Science, Information Systems
Chengyi Qu, Xu Xi, Jinglong Du, Tong Wu
Summary: This paper proposes a novel watermarking algorithm based on the geometric invariance of the ratios of discrete wavelet transform (DWT) and complex singular value decomposition (CSVD) coefficients. The algorithm addresses the disadvantages of traditional frequency-domain watermarking algorithms for vector geographic data and shows robustness against common attacks and the ability to extract watermark images with a high probability under random multiple attacks.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2022)
Article
Engineering, Multidisciplinary
Masoud Ahmadipour, Muhammad Murtadha Othman, Zainal Salam, Moath Alrifaey, Hussein Mohammed Ridha, Veerapandiyan Veerasamy
Summary: In this paper, a new optimal load shedding method using a grasshopper optimization algorithm (GOA) is proposed for the stability of islanded power systems with distributed energy resources (DER). The effectiveness of the method is evaluated through a comprehensive study on an IEEE 33-bus system with four DG units under different scenarios. The results show that the proposed GOA-based load shedding method outperforms other optimization approaches in terms of load curtailment and voltage stability.
AIN SHAMS ENGINEERING JOURNAL
(2023)
Article
Energy & Fuels
Bashar Abbas Fadheel, Noor Izzri Abdul Wahab, Ali Jafer Mahdi, Manoharan Premkumar, Mohd Amran Bin Mohd Radzi, Azura Binti Che Soh, Veerapandiyan Veerasamy, Andrew Xavier Raj Irudayaraj
Summary: This paper proposes an optimization technique using the hybrid SSAGWO algorithm to optimize the gain values of the proportional integral derivative controller for frequency regulation. The technique is applied to a two-area hybrid power system model developed in Simulink and shows superior performance compared to other algorithms. The method is also robust under real-time conditions.
Article
Energy & Fuels
Anith Khairunnisa Ghazali, Mohd Khair Hassan, Mohd Amran Mohd Radzi, Azizan As'arry
Summary: Recycling braking energy is crucial for enhancing the energy efficiency of electric vehicles. This study investigates a parallel-distribution braking system that transfers as much energy as possible from the wheel to the battery and proposes an integrated braking force distribution strategy with gain-scheduling super-twisting sliding mode control. Simulation results validate the effectiveness of the proposed control strategy in practical applications.
Article
Energy & Fuels
Chi Zhang, Binyue Xu, Jasronita Jasni, Mohd Amran Mohd Radzi, Norhafiz Azis, Qi Zhang
Summary: Faced with the energy crisis and environmental pollution, the development of new energy electric vehicles has been accelerated due to the resistance against traditional internal combustion engine vehicles. Permanent magnet synchronous motors are widely used in electric vehicles and other fields because of their simple structure, light weight, small size, and high power density. This paper proposes an optimized model predictive torque control strategy based on voltage vector expansion, which effectively controls the flux linkage vector and achieves optimal duty cycle control.
Article
Engineering, Electrical & Electronic
Ahmad Hafiz Mohd Hashim, Norhafiz Azis, Jasronita Jasni, Mohd Amran Mohd Radzi, Masahiro Kozako, Mohamad Kamarol Mohd Jamil, Zaini Yaakub
Summary: This article examines the acoustic partial discharge (PD) localization in oil using adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) approaches. Impedance matching circuit (IMC) is used to measure the electrical PD, while acoustic PD is obtained through an acoustic emission (AE) sensor and preamplifier gain unit. The location of the PD is evaluated by utilizing 112 coordinates for each AE sensor. Data is preprocessed using moving average (MA) and analyzed using time of arrival (TOA), ANFIS, and ANN. The distance between PD and AE sensor is calculated based on TOA for PD localization. ANFIS has a higher accuracy in predicting PD source compared to ANN, based on root mean square error (RMSE) and coefficient of determination ( ${R}<^>{{2}}{)}$). ANN has a faster computation time of 1.75 s for PD localization based on AE PD signals.
IEEE TRANSACTIONS ON DIELECTRICS AND ELECTRICAL INSULATION
(2023)
Article
Energy & Fuels
Hussein Mohammed Ridha, Hashim Hizam, Seyedali Mirjalili, Mohammad Lutfi Othman, Mohammad Effendy Ya'acob, Masoud Ahmadipour
Summary: Photovoltaic (PV) and Wind turbine (WT) systems are promising for rural energy delivery. Existing studies mainly focus on economic efficiency and ignore reliability maximization. This paper proposes an improved bi-archive approach to find four optimum sets of PF solutions. The proposed method, incorporating best worst method (BWM) and preference ranking organization for enrichment evaluations (PROMETHEE II) method, can rank and select the most desired design for the PV/WT/Battery system with fast convergence and high diversity.
Article
Energy & Fuels
Amaal Habeeb, Hashim Hizam, Mohammad Lutfi Othman, Noor Izzri Abdul Wahab, Wesam Rohouma
Summary: Starting from the power requirements of the clinic, an appropriate sizing of a standalone PV system is determined and a simulation model is built using MATLAB/Simulink (R2018b) software for a clinic in Malaysia. The proposed simulation model is able to harvest maximum power in all test scenarios according to the evaluation results.
Proceedings Paper
Energy & Fuels
Raihanah Naja Redan, Muhammad Murtadha Othman, Kamrul Hasan, Masoud Ahmadipour
Summary: In this paper, the random forest technique is used to forecast solar irradiance by collecting raw information such as solar irradiance, current, temperature, and power. The data is then processed to remove noise and extract multiple time lags features to improve the accuracy of the forecast. The proposed method is important for maintaining the efficiency and stability of solar power plants.
2023 IEEE 3RD INTERNATIONAL CONFERENCE IN POWER ENGINEERING APPLICATIONS, ICPEA
(2023)
Proceedings Paper
Energy & Fuels
Mohamad Soleheen Mohd Tamam, Muhammad Murtadha Othman, Kamrul Hasan, Masoud Ahmadipour
Summary: Major power quality issues such as voltage harmonic and swell/sag can be mitigated by installing the Dynamic Voltage Restorer (DVR), which injects the required voltage to sustain power quality. This study integrates a DVR, a solar PV-Battery, and a supercapacitor (SCAP) to improve power quality and meet grid power demand. The suggested system effectively reduces power quality disruptions by compensating for voltage sag and swell without interrupting the grid, using solar energy and a high-power density supercapacitor.
2023 IEEE 3RD INTERNATIONAL CONFERENCE IN POWER ENGINEERING APPLICATIONS, ICPEA
(2023)
Proceedings Paper
Energy & Fuels
Justin Anak Tigong, Muhammad Murtadha Othman, Kamrul Hasan, Masoud Ahmadipour
Summary: In this study, a supercapacitor (SCAP) connected at the DC-link of the DVR is used to inject the required voltage for sustaining the mitigation of power quality problems in a system. SCAP offers the advantage of rapid power charge and discharge, enabling immediate and sustainable mitigation of power quality issues associated with the DC-link voltage. The bidirectional DC-DC converter is used to control the output voltage transmitted from the DC link to the inverter, depending on the type of power quality problem. MATLAB/Simulink simulation results validate the effectiveness of the proposed DVR-SCAP configuration in compensating for grid disturbances.
2023 IEEE 3RD INTERNATIONAL CONFERENCE IN POWER ENGINEERING APPLICATIONS, ICPEA
(2023)
Proceedings Paper
Energy & Fuels
Adibah Binti Mashudi, Muhammad Murtadha Othman, Masoud Ahmadipour, Kamrul Hasan
Summary: This project introduces generation expansion planning considering the reliability of grid-connected PV Generator and Wind turbine. The Markov model is used to calculate the forced outage rate (FOR) of PV generator and Wind turbine with embedded data. Then, the loss of load expectation (LOLE) is obtained using a 24-bus system and a variant number of the population comprising kW sizing of PV Generator and Wind turbine. The EP technique with Roulette wheel and crossover is applied for optimization of expansion planning to enhance the system reliability of PV Generator and Wind turbine. The generation expansion planning results in the best sizing of PV Generator and Wind turbine with LOLE less than 2.4, and ultimately achieves the objective function of the lowest installation cost.
2023 IEEE 3RD INTERNATIONAL CONFERENCE IN POWER ENGINEERING APPLICATIONS, ICPEA
(2023)
Proceedings Paper
Energy & Fuels
Nurul Thasyahirah Ellya Mohd Jailaini, Muhammad Murtadha Othman, Masoud Ahmadipour, Kamrul Hasan
Summary: This study proposes an optimal PV system allocation considering weather conditions. The Markov model is used to calculate a forced outage rate (FOR) by incorporating data from the PV generator and weather conditions. The combined FOR is then used along with a load and different population sizes of PV system to obtain the expected unserved energy (EUE) and loss of load expectation (LOLE). The EP technique is applied to optimize the sizing and generating unit (GU) of the PV system with EUE close to zero and LOLE less than 2.4 hours per year. The impact of weather conditions on PV systems is analyzed in this paper.
2023 IEEE 3RD INTERNATIONAL CONFERENCE IN POWER ENGINEERING APPLICATIONS, ICPEA
(2023)
Article
Computer Science, Information Systems
Kamrul Hasan, Muhammad Murtadha Othman, Sheikh Tanzim Meraj, Masoud Ahmadipour, M. S. Hossain Lipu, Mohsen Gitizadeh
Summary: In fuel-cell-connected utility networks, reactive power generated by electrical loads attached to the power network results in wasted energy, increased electricity demand, system overload, and higher utility costs. This is mainly caused by non-linear loads and voltage dips. Existing solutions fail to effectively remove harmonics and compensate for reactive power. To address this, a novel self-regulating active/reactive sustainable energy management system (SEM) is proposed, which can adjust the power factor, compensate for power outages and reactive power, and remove harmonics from the electricity network. The proposed SEM can effectively decrease harmonics and maintain the power factor near unity under various load circumstances.
Article
Computer Science, Artificial Intelligence
Masoud Ahmadipour, Zaipatimah Ali, Muhammad Murtadha Othman, Rui Bo, Mohammad Sadegh Javadi, Hussein Mohammed Ridha, Moath Alrifaey
Summary: The optimal power flow (OPF) is a crucial tool in power system operation and control that aims to obtain the most economical combination of power plants to meet operational, economic, and environmental constraints. This study proposes an enhanced democratic political algorithm (DPA) to solve multi-objective OPF problems. The proposed method is tested on different power system cases and compared with other popular multi-objective evolutionary algorithms, showing its effectiveness in handling different scales and non-convex optimization problems.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Chemistry, Physical
T. T. Dele-Afolabi, Masoud Ahmadipour, M. A. Azmah Hanim, A. A. Oyekanmi, M. N. M. Ansari, Surajudeen Sikiru, Niraj Kumar
Summary: The impact of multi-walled carbon nanotubes (MWCNTs) on the development of intermetallic compounds (IMCs) at the interface of Sn5Sb/Cu solder joints was investigated. The presence of MWCNTs significantly prevented IMC formation and enhanced the shear strength of the solder joints. An extreme learning machine (ELM) prediction model refined by Aquila optimizer (AO) was used to accurately predict the IMC thickness and shear strength of the solder joints.
JOURNAL OF ALLOYS AND COMPOUNDS
(2024)
