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Crack identification in beam-like structures using multi-mass system and wavelet transform

EARTHQUAKES AND STRUCTURES 2024年第4期27卷 263-283页

作者： Ghadimi, Siamak Kourehli, Seyed Sina Zamani, Gholamreza Urmia Univ Fac Engn Dept Civil Engn Orumiyeh Iran Azarbaijan Shahid Madani Univ Dept Civil Engn Tabriz Iran

This research introduces a new composite system that utilizes multiple moving masses to identify cracks in structures resembling beams. The process starts by recording displacement time data from a set of these moving masses and converting this information into a relative time history through weighted aggregation. This relative time history then undergoes wavelet transform analysis to precisely locate cracks. Following wavelet examinations, specific points along the beam are determined as potential crack sites. These points, along with locations on the beam susceptible to cracked point due to support conditions, are marked as crack locations within the optimization algorithm's search domain. The model uses equations of motion based on the finite element method for the moving masses on the beam and employs the Runge-Kutta numerical solution within the state space. The proposed system consists of three successive moving masses positioned at even intervals along the beam. To assess its effectiveness, the method is tested on two examples: a simply supported beam and a continuous beam, each having three scenarios to simulate the presence of one or multiple cracks. Additionally, another example investigates the influence of mass speed, spacing between masses, and noise effect. The outcomes showcase the method's effectiveness and efficiency in localizing crack, even in the presence of noise effect in 1%, 5% and 20%.

关键词： crack dynamic deflection Euler Bernoulli finite element method moving sprang mass optimization algorithm

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Hybridized optimization oriented fast negative sequential patterns mining

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MULTIMEDIA TOOLS AND APPLICATIONS 2022年第4期81卷 5279-5303页

作者： Yadav, Poonam DAV Coll Engn & Technol Kanina 123027 Haryana India

Recently, negative sequential patterns (NSP) (like missing medical treatments) mining is important in data mining research since it includes negative correlations between item sets, which are overlooked by positive sequential pattern mining (PSP) (for instance, utilization of medical service). Yet, discovering the NSP is very complex than finding PSP because of the important problem complexity occurred by high computational cost, non-occurring elements, as well as huge search space in evaluating NSC, and most of the NSP based existing works are inefficient. Therefore, this paper intends to propose a fast NSP mining algorithm for the disease prediction model. This model includes Data normalization, Data separation based on labels, and Pattern recognition phases. In the midst of data separation, the maximum occurring data is optimally selected using a new algorithm that hybridizes the FireFly (FF) algorithm and Grey Wolf optimization (GWO). This proposed Firefly induced Grey Wolf optimization (F-GWO) algorithm automatically selects the maximum occurring information as per the PSP support. The proposed model is compared over other conventional methods with varied measures. Especially, the computation cost of our model is 46.87%, 6.27%, 9.37%, 2.76%, and 66.62% better than the existing GA, ABC, PSO, FF, and GWO models respectively.

关键词： Positive sequential pattern Negative sequential pattern optimization algorithm GWO FF

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Trajectory optimization and Control of a Free-Floating Two-Arm Humanoid Robot

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2022年第9期45卷 1661-1675页

作者： Ramon, Jose L. Calvo, Ramon Trujillo, Adrian Pomares, Jorge Felicetti, Leonard Univ Alicante Dept Phys Syst Engn & Signal Theory Alicante 03690 Spain Cranfield Univ Sch Aerosp Transport & Mfg Cranfield MK43 0AL Beds England

An optimization algorithm for planning the motion of a humanoid robot during extravehicular activities is presented in this paper. The algorithm can schedule and plan the movements of the two robotic arms to move the humanoid robot by using the handrails present outside the International Space Station. The optimization algorithm considers the eventual constraints imposed by the topology of the handrails and calculates the sequence of grasping and nongrasping phases needed to push and pull the robot along the handrails. A low-level controller is also developed and used to track the planned arms and end-effectors trajectories. Numerical simulations assess the applicability of the proposed strategy in three different typical operations that potentially can be performed in an extravehicular activity scenario.

关键词： Humanoid Robot Trajectory optimization ISS Extravehicular Activity optimization algorithm Numerical Simulation Motion Planning Linear Quadratic Regulator Nonlinear Programming Robot End Effector

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A optimization algorithm of Obstacle Limit Takeoff Weight

A optimization Algorithm of Obstacle Limit Takeoff Weight

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3rd International Conference on Civil Engineering and Transportation (ICCET 2013)

作者： Chen Hongying Luo Wen Tian Civil Aviat Flight Univ China Flight Technol Coll Guanghan Sichuan Peoples R China Civil Aviat Flight Univ china Aviat Engn Inst Deyang Peoples R China

ISBN: (纸本)9783038350064

This method is explained and demonstrated how to calculate obstacle limit takeoff weight. According regulation requirement, under an engine failure conditions, it needs to consider the takeoff flight path different segments which can clear all obstacles([1]). In this paper, take-off gross flight path and net flight path are analyzed, and taking an aircraft for example, obstacle limit takeoff weight are calculated, Simulation results show the feasibility of optimization algorithm.

关键词： Obstacle limit takeoff weight Take-off gross flight path engine failure Take off net flight path optimization algorithm

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Hybrid Beamfocusing Architecture and algorithm for Microwave Wireless Power Transmission Systems

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IEEE ACCESS 2024年 12卷 53677-53685页

作者： Kim, Ho Yeol Nam, Sangwook Seoul Natl Univ Inst New Media Commun Sch Elect & Comp Engn Seoul 08826 South Korea

This study investigates a hybrid beamfocusing method for microwave wireless power transmission (MPT). We propose an optimization algorithm to obtain an optimal coefficient of phase shifters and amplitude controllers with maximum RF power transfer efficiency (RF-PTE) for the hybrid beamfocusing architecture. The optimization algorithm is proposed by iteratively solving the alternative optimization problem. The algorithm is simulated by applying it to an MPT system with a transmitter and receiver composed of patch array antennas operating at 10 GHz. Additionally, we implement a test bed operating at 5.8 GHz. Through the simulations and experiments, the amplitude controllers of partially-connected hybrid beamfocusing architecture can be reduced by half compared with the fully digital beamfocusing to achieve the optimal RF-PTE. Therefore, an economical and less complex MPT system can be implemented by using the hybrid beamfocusing method.

关键词： Radio frequency Transmitting antennas optimization Computer architecture Receiving antennas Array signal processing Antenna arrays Wireless power transmission Microwave wireless power transmission optimization algorithm hybrid beamfocusing array antenna

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Competition Over Resources: A New optimization algorithm Based on Animals Behavioral Ecology 6

Competition Over Resources: A New optimization Algorithm Bas...

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2014 International Conference on Intelligent Networking and Collaborative Systems (IEEE INCoS 2014)

作者： Mohseni, Sina Gholami, Reza Zarei, Niloofar Zadeh, Arash Roomi Noshirvani Univ Technol Fac Elect Engn Babol Sar Iran Amirkabir Univ Technol Fac Elect Engn Tehran Iran Polytech Univ Turin Dept Automat & Comp Sci Turin Italy

ISBN: (纸本)9781479963874

In the recent years, many heuristic optimization algorithms have been developed. A majority of these heuristic algorithms have been derived from the behavior of biological or physical systems in nature. In this paper, we propose a new optimization algorithm based on competitive behavior of animal groups. In the proposed algorithm, the whole population is divided into a number of groups. In each group, the best searching agent spreads its children in its owned territory. Any group which is not able to find rich resources will be eliminated form competition. The competition gradually results in an increase in population of wealthy group which gives a fast convergence to proposed optimization algorithm. In the following, after a detailed explanation of the algorithm and pseudo code, we compare it to other existing algorithms, including genetics and particle swarm optimizations. Applying the proposed algorithm on various benchmark cost functions, shows faster and superior results compared to other optimization algorithms.

关键词： optimization algorithm animals behavioral ecology nature inspired algorithm

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A new approach for optimum operation of multi-stage water pump stations

JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GA...

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JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY 2024年第2期39卷 1179-1191页

作者： Alsanabani, Huseyin Iskefiyeli, Murat Yarali, Kadir Kucuk, Hayri Turan, Mustafa Sakarya Univ Dept Comp Engn Grad Sch Nat & Appl Sci TR-54050 Sakarya Turkiye Sakarya Univ Grad Sch Nat & Appl Sci Dept Elect & Elect Engn TR-54050 Sakarya Turkiye

Purpose: To optimize pumping in water distribution systems by making use of electricity unit price differences and minimizing the cost of electricity used for *** and Methods: OSDPA automatically calculates the desired optimum level values when switching from the cheapest electricity tariff to the most expensive one to reach this optimal value when switching between tariffs. It can also optimize an entire complex pumping system by optimizing each subsystem ***: Compared to the currently used CWLC approach, the implementation of SDPA reduces the unit pumping cost from 0.6331 ₺/m3 to 0.5194 ₺/m3, 1.2948 ₺/m3 to 1.0112 ₺/m3 and 0.7378 ₺/m3 to 0.5983 ₺/m3 for pumps C, B, and A respectively. Implementing OSDPA showed that the unit pumping cost could be reduced to 0.3853 ₺/m3, 0.7686 ₺/m3 and 0.5647 ₺/m3 for pumps C, B, and A ***: When compared with the conventional water level control (CWLC) approach, SDPA saves about 18% for pump C in the second stage, 22% for pump B in the second stage, and 19% for pump A in the first stage. However, with OSDPA savings of 39%, 41% and 24% for pumps C, B and A respectively were achieved. Considering all the pumping stations in the work area, SDPA could save around 101,000 ₺ per year, while OSDPA could save around 142,000 ₺ per year.

关键词： Multistage pumping stations Optimum operation of pumping stations Load shifting Dynamic programming optimization algorithm

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An effective framework of human abnormal behaviour recognition and tracking using multiscale dilated assisted residual attention network

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EXPERT SYSTEMS WITH APPLICATIONS 2024年 247卷

作者： Vidya, Queen Mary Selvakumar, S. Sathyabama Inst Science&Technol Dept Comp Sci & Engn Chennai 600119 Tamilnadu India Visvesvaraya Coll Engn & Technol Dept Comp Sci & Engn Hyderabad 501510 Telangana India

The prevention of certain unwanted crime events and eliminating them even before their execution can be done by automatic identification of abnormal behavior in humans. Hence automatic prediction of abnormal human behavior is a difficult task to perform. Some of the automated model has been implemented and provided the most promising results. The manual intervention is being the greatest approach in earlier time, yet it brings with numerous errors, consumes more time and more cost effective. Henceforth, the automated model is suggested for identifying the activities. As the scholar focus on machine and deep learning, this classifier may extract the handcrafted features. But it fails to yield the appropriate solution for finding the activities. Since it belongs to the video frames, the object detection is highly Ineffective feature vector and inadequate scale measures of the learning model paves the way for performance degradation. This issue can be resolved by including an attention mechanism in the deep learning model for both monitoring and classification purposes. The recommended Human Abnormal Behavior Recognition and Tracking (HABRT) model performs the following operations, such as the collection of video, categorizing the behavior in the video as normal or abnormal, monitoring, extraction of the object, and classification of the abnormality. The input video with such frames is initially gathered from publically available databases. By using these frames, the abnormal behavior classification is done by Multiscale Dilated assisted Residual Attention Network (MD -RAN), For further enhancement, the hyper-parameters in the MD -RAN are optimally selected by novel Modified Random Parameter-based Chimp optimization algorithm (MRP-ChOA). Once the abnormal frames are obtained, the activity tracking is achieved by Adaptively Modified You Only Look Once (YOLO) V3 (AM-YOLO V3). This model encompasses with multiple layers, so that utilized number of layers are determined op

关键词： Human Abnormal Behavior Recognition Human Activity Tracking Adaptively Modified You Only Look Once V3 Modified Random Parameter-based Chimp optimization algorithm Multiscale Dilated assisted Residual Attention Network

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Woa-fism planning hexapod robot various gaits

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INTELLIGENT SERVICE ROBOTICS 2024年第4期17卷 963-979页

作者： Hu, Pingzhi Zhang, Mengjian Wang, Deguang Guizhou Commun Polytech Dept Mech & Elect Engn Guiyang 551400 Peoples R China South China Univ Technol Sch Comp Sci & Engn Guangzhou 510000 Guangdong Peoples R China Guizhou Univ Coll Elect Engn Guiyang 550025 Peoples R China

Compared to wheeled and tracked robots, hexapod robots have higher adaptability and higher flexibility in complex terrains. With various gaits, hexapod robots can fulfill different needs better. Existing researches mainly focused on three common gaits, they are single-leg swing gait, wave gait, and tripod gait. Instead of directly planning gaits with swarm intelligence algorithms (SIA), a gait planning method for hexapod robots named finite incremental state machine (FISM) is proposed. FISM focuses on four incremental states between two adjacent gaits of the robot, which greatly reduces the complexity of the gait planning algorithm so that gait planning with SIA is simplified to set the optimal transfer conditions of FISM. In addition, after comparing five optimization algorithms, the whale optimization algorithm (WOA) can set the optimal transfer conditions of FISM. The computer simulation shows WOA-FISM can plan various gaits, finally, a real robot test verifies the effectiveness of various gaits.

关键词： Hexapod robots Finite incremental state machine Incremental states Various gaits optimization algorithm Whale optimization algorithm

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OR based multi-objective decision-making in e-commerce improvement

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SERVICE ORIENTED COMPUTING AND APPLICATIONS 2025年 1-11页

作者： Gollavilli, Venkata Surya Bhavana Harish Nagarajan, Harikumar Alagarsundaram, Poovendran Gattupalli, Kalyan Sitaraman, Surendar Rama Khalid, Haris M. Under Armour Baltimore MD 21202 USA Global Data Mart Inc GDM South Plainfield NJ USA Humetis Technol Inc Kingston NJ USA Yash Tek Inc Mississauga ON Canada Intel Corp Santa Clara CA USA Univ Dubai Coll Engn & Informat Technol Dubai 14143 U Arab Emirates

The inefficiencies and high costs of traditional business process redesign techniques, which frequently rely on manual optimization and lack systematic approaches, are discussed in this study. Our suggestion to address these issues is a computational fuzzy model that combines multi-objective decision-making methods with operational research. This model analyses corporate goals, resources, and limitations in an organized manner to improve the efficacy of business redesign. Our approach makes finding the best redesign tactics easier while considering various goals and trade-offs. Test results show that the suggested methodology delivers an astounding 98.62% average accuracy in redesign results. Its efficiency is further demonstrated by the fact that the average time needed for the redesign process is reduced to 11.55 s, and related expenditures are kept to a minimum. The results show that using the computational fuzzy model makes decision-making more accessible and generally raises the standard of business operations. This model offers a valuable tool for businesses looking to improve operational effectiveness and save expenses in fast-paced e-commerce by providing an organized approach to company redesign. The outcomes show how sophisticated decision-making frameworks may be integrated into business process management to enable more efficient and flexible organizational procedures.

关键词： Decision-making optimization algorithm e-commerce Business process Multi-objectives

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