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Designing and Implementing Real-Time Deep Learning Object Detection in Unmanned Aerial Vehicles
Get PDFThe rapid development of surveillance technology is readily apparent, particularly in monitoring vast and remote locations that present difficulties for human accessibility. Within the realm of contemporary surveillance methods, the utilization of Unmanned Aerial Vehicles (UAVs) has garnered a considerable amount of interest. The swift advancements in science and technology have led to the progressive incorporation of Artificial Intelligence (AI) technologies, particularly in tasks such as monitoring and reconnaissance. The results of this research contribute to the creation of a prototype for a UAV capable of conducting autonomous monitoring missions and integrating artificial intelligence technologies for real-time video processing. This study utilized an experimental methodology, and a Raspberry Pi was utilized for artificial intelligence processes integrated with the aircraft controller. During the decisive experiment, the unmanned aerial vehicle UAV could effectively travel to the designated area, reaching an accuracy of 78.6% in its AI processing.
ABSTRAK: Perkembangan pesat teknologi pemantauan kini semakin ketara, terutamanya dalam pemantauan kawasan yang luas dan terpencil sukar diakses manusia. Dalam konteks kaedah pemantauan kontemporari, penggunaan Kenderaan Udara Tanpa Pemandu (UAV) telah menarik minat ramai. Kemajuan pesat sains dan teknologi telah menghasilkan gabungan teknologi Kecerdasan Buatan (AI) secara progresif, terutama dalam bidang pemantauan dan peninjauan. Penyelidikan ini memberi sumbangan kepada penciptaan prototaip UAV yang mampu menjalankan misi pemantauan sendiri, disamping gabungan teknologi kecerdasan buatan bagi memproses video masa nyata. Kajian ini menggunakan metodologi eksperimen dan Raspberry Pi yang disepadukan dengan pengawal pesawat bagi proses kecerdasan buatan. Semasa eksperimen penentuan, UAV berjaya bergerak dengan berkesan ke kawasan yang ditetapkan, mencapai ketepatan 78.6% dalam pemprosesan AI
Probability of Single-Vehicle Accidents Among Elderly Motorcyclists in Indonesia
Get PDFThe number of accidents involving elderly motorcyclists is relatively high compared to other age groups. This is due to various limitations commonly experienced by older riders. This study aims to determine the probability of single-vehicle accidents among elderly motorcyclists in relation to human, road, and environmental factors. A total of 564 respondents participated in the study conducted in Riau Province, Indonesia. Data were collected through interviews with elderly motorcyclists who had previously experienced accidents. The data were analyzed using a Bayesian Network model with GeNIe 2.0 software. The results showed that the probability of single-vehicle accidents among elderly motorcyclists is 59%. Model validation indicated a Mean Absolute Deviation (MAD) of 23%. Male elderly motorcyclists have a 60% likelihood of experiencing single-vehicle accidents (Scenario 1), while female elderly motorcyclists have a 59% likelihood (Scenario 2). Those who ride while fatigued have a 65% probability of a single-vehicle accident (Scenario 3), compared to 57% for those who are not fatigued (Scenario 4). Riding in rainy conditions increases the probability to 70% (Scenario 5), whereas riding in dry conditions reduces it to 55% (Scenario 6). Elderly motorcyclists riding on potholed roads have a 64% chance of accidents (Scenario 7), compared to 57% on roads without potholes (Scenario 8). These findings indicate that elderly riders are highly vulnerable to single-vehicle accidents. Among human factors, fatigue is the most significant variable influencing accident probability. Regarding environmental factors, driving in the rain plays a key role, while riding on potholed roads is the primary influence for road factors. This study highlights the dominant factors contributing to single-vehicle accidents among elderly motorcyclists by integrating human, road, and environmental considerations.
ABSTRAK: Bilangan kemalangan dalam kalangan penunggang motosikal warga emas agak tinggi berbanding kumpulan umur yang lain.Hal ini disebabkan oleh beberapa batasan yang dialami oleh penunggang motosikal warga emas.Tujuan kajian ini adalah untuk menentukan kebarangkalian kemalangan bujang dalam kalangan penunggang motosikal warga emas berkaitan faktor manusia, jalan raya dan persekitaran.Jumlah sampel ialah 563 responden dan lokasi kajian adalah di Wilayah Riau, Indonesia. Pengumpulan data yang pernah dialami oleh penunggang motosikal dengan menggunakan analisis elderata. Rangkaian Bayesian dengan Perisian GeNie 2.0. Keputusan menunjukkan kebarangkalian kemalangan bujang dalam kalangan penunggang motosikal warga emas ialah 59%.Hasil pengesahan model menunjukkan nilai MAD sebanyak 23%. Penunggang motosikal warga emas lelaki berkemungkinan mengalami kemalangan bujang sebanyak 60% (senario 1), penunggang motosikal warga emas wanita sebanyak 59% (senario 2). Penunggang motosikal warga emas yang memandu semasa keletihan berkemungkinan mengalami satu kemalangan sebanyak 65% (senario 3), dalam keadaan tidak letih 57% (senario 4 yang memandu dalam keadaan hujan yang berkemungkinan besar dalam keadaan hujan). 70% (senario 5), dalam keadaan tidak hujan 55% (senario 6). Penunggang motosikal warga emas yang memandu di jalan berlubang berkemungkinan akan mengalami satu kemalangan sebanyak 64% (senario 7), di jalan tanpa jalan berlubang 57% (senario 8). Bermakna pemandu warga emas sangat terdedah untuk mengalami kemalangan bujang. Pembolehubah yang paling mempengaruhi kemungkinan pemandu warga emas mengalami kemalangan bujang ialah keletihan dari segi faktor manusia. Bagi faktor persekitaran, pembolehubah yang mempengaruhi pemandu warga emas yang mengalami kemalangan bujang ialah memandu dalam hujan. Bagi faktor jalan raya, pembolehubah yang mempengaruhi kemalangan tunggal ialah memandu di jalan berlubang. Dapatan kajian ini mendapat faktor dominan yang menyebabkan kemalangan bujang pada pemandu warga emas dengan mengambil kira faktor manusia, jalan raya dan persekitaran
Modification of Grey Relational Analysis for Dynamic Criteria Weighting in Decision-Making Systems
Get PDFGrey relational analysis (GRA) is a grey system theory method used to solve multi-criteria decision problems with incomplete or uncertain data. The GRA analyzes the level of closeness or relationship between several alternatives based on a series of criteria. One of the limitations in using the GRA method is the weight of the criteria, which is often fixed or subjective. In many GRA applications, the criterion weights are set based on expert considerations or decision-maker preferences, which can be highly subjective and influenced by individual biases. Grey relational analysis change data driven (GRA-C) method emphasizes the increased effectiveness and flexibility of this method in performance appraisal for multi-criteria decision-making. GRA-C allows for more precise adjustments according to the importance of each criterion, leading to more accurate and relevant evaluation results. By modifying the weights, the GRA-C becomes more flexible and can be adapted to different contexts and specific decision-making needs, so that it can be applied in various industry sectors. These modifications help reduce bias due to improper weight allocation, resulting in more objective performance assessments. The results of the modified GRA-C can provide better insights for decision-makers, supporting a more effective and informed decision-making process. The comparison with the Spearman correlation shows that the GRA-C method has a very strong degree of conformity in producing alternative rankings, with a correlation value 1. This indicates that these methods provide similar results, making them reliable for consistent decision-making.
ABSTRAK: Analisis Perhubungan Kelabu (Grey Relational Analysis, GRA) merupakan satu kaedah dalam teori sistem kelabu yang digunakan untuk menyelesaikan masalah keputusan berbilang kriteria (multi-criteria decision-making) yang melibatkan data tidak lengkap atau tidak pasti. GRA menganalisis tahap keterkaitan atau hubungan antara beberapa alternatif berdasarkan satu siri kriteria. Salah satu kekangan dalam penggunaan kaedah GRA ialah pemberat kriteria yang sering kali bersifat tetap atau subjektif. Dalam banyak aplikasi GRA, pemberat kriteria ditentukan berdasarkan pertimbangan pakar atau keutamaan pembuat keputusan, yang boleh menjadi sangat subjektif dan dipengaruhi oleh bias individu. Kaedah Grey Relational Analysis Change Data Driven (GRA-C) menekankan keberkesanan dan fleksibiliti yang lebih tinggi dalam penilaian prestasi bagi sistem keputusan berbilang kriteria. GRA-C membolehkan pelarasan yang lebih tepat mengikut kepentingan setiap kriteria, yang membawa kepada keputusan penilaian yang lebih tepat dan relevan. Dengan pengubahsuaian pemberat, GRA-C menjadi lebih fleksibel dan boleh disesuaikan dengan pelbagai konteks serta keperluan khusus dalam membuat keputusan, membolehkannya diaplikasikan dalam pelbagai sektor industri. Pengubahsuaian ini membantu mengurangkan bias akibat pengagihan pemberat yang tidak sesuai, sekali gus menghasilkan penilaian prestasi yang lebih objektif. Hasil daripada GRA-C yang telah diubah suai dapat memberikan pandangan yang lebih baik kepada pembuat keputusan, seterusnya menyokong proses membuat keputusan yang lebih berkesan dan berasaskan maklumat. Perbandingan dengan korelasi Spearman menunjukkan bahawa kaedah GRA-C mempunyai tahap kesesuaian yang sangat tinggi dalam menghasilkan kedudukan alternatif, dengan nilai korelasi sebanyak 1. Ini menunjukkan bahawa kaedah-kaedah tersebut memberikan hasil yang serupa dan boleh dipercayai untuk proses membuat keputusan yang konsisten
Enhancement of the Photocatalytic Activity of MIL-53 Metal–Organic Frameworks Through the Addition of Reduced Graphene Oxide for Improved Degradation of Organic Dye Pollutants in Water Treatment Applications
Get PDFA simple nanocomposite consisting of MIL-53(Al) and reduced graphene oxide (rGO), denoted as MIL-53(Al)/rGO, was synthesized as a photocatalyst driven by sunlight and UV light to study the decomposition of methylene orange and methylene blue in aqueous solution. The MIL-53(Al)/rGO ultrafine particles were produced by an in situ method using the solvothermal technique. The nanocomposite was made with two different amounts of rGO, 2.5% and 5% by weight. Various tests, including XRD, N2 adsorption-desorption isotherms, SEM, SEM-EDS, UV-Vis DRS (Diffuse Reflectance Spectroscopy), and FTIR, were performed on all photocatalyst variations to analyse their properties. Results from SEM and EDS showed the creation of small MIL-53(Al) particles measuring 10-20 ?m and rGO spread evenly on the MIL-53(Al) surface, particularly in the 2.5% rGO sample. The photocatalytic effectiveness of the MIL-53(Al)/rGO nanocomposites was tested for degrading organic dyes (MO and MB) in water under both sunlight and UV light for 60- and 120-minute durations. The 2.5% rGO photocatalyst showed the highest performance, removing over 96% and 98% of the dyes after one hour of sunlight exposure for MB and MO, respectively. This demonstrates that the combined effect of MIL-53(Al) and rGO composite can be seen as an effective photocatalyst for breaking down reactive dyes, such as MO and MB, in water treatment applications.
ABSTRAK: Kajian ini adalah berkaitan nanokomposit sederhana daripada MIL-53(Al) dan grafit oksida yang tereduksi (rGO), atau MIL-53(Al)/rGO, berjaya disintesis sebagai fotopemangkin oleh cahaya matahari dan cahaya UV bagi mengkaji penguraian metil jingga (MO) dan metilena biru (MB) dalam larutan akueus. Zarah ultrahalus MIL-53(Al)/rGO dihasilkan melalui kaedah in situ menggunakan teknik solvotermal. Nanokomposit dibuat dengan dua jumlah rGO berat berbeza, 2.5 wt% dan 5 wt%. Pelbagai ujian termasuk XRD, N2 penyerapan-nyahserapan isoterma (BET), SEM, SEM-EDS, UV-Vis DRS, dan FTIR telah dilakukan pada semua variasi fotopemangkin bagi mengkaji sifatnya. Dapatan kajian dari SEM dan EDS menunjukkan penciptaan zarah kecil MIL-53(Al) berukuran 10-20 ?m dan rGO tersebar secara rata pada permukaan MIL-53(Al), terutamanya dalam sampel rGO 2.5%. Keberkesanan fotopemangkin nanokomposit MIL-53(Al)/rGO telah diuji bagi mengurai pewarna organik dalam air, di bawah kedua-dua cahaya matahari dan cahaya UV selama tempoh 60 dan 120 minit. Fotopemangkin rGO 2.5% menunjukkan prestasi tertinggi, dengan penyingkiran lebih dari 96% MB dan 98% MO, selepas pendedahan cahaya matahari selama satu jam. Ini menunjukkan, kesan gabungan komposit MIL-53(Al) dan rGO, boleh dilihat sebagai fotopemangkin yang berkesan bagi memecahkan pewarna reaktif, seperti MO dan MB, dalam aplikasi rawatan air
Editorial
Get PDFThe IIUM Engineering Journal, Vol. 25 No. 1, showcases a diverse array of pioneering research that pushes the boundaries of engineering and technology. This issue reflects a commitment to addressing critical challenges, exploring innovative solutions, and advancing sustainable practices across various disciplines. From air pollution modeling and flood mapping to groundbreaking healthcare and renewable energy applications, this edition captures the essence of interdisciplinary collaboration and ingenuity.
Environmental sustainability is a recurring theme in this issue. Researchers have tackled pressing global issues such as air pollution, water purification, and waste management with novel solutions. Developing deep, sparse autoencoder models for predicting the Air Pollution Index in Malaysia exemplifies how artificial intelligence can guide impactful environmental decisions. Similarly, advancements in green cementless mortar and geopolymer technology utilizing waste paper sludge ash highlight engineering's role in reducing carbon footprints and repurposing industrial by-products.Solar-driven innovations also take center stage, with the introduction of PVA-Chitosan/PANi hydrogels demonstrating a leap forward in solar vapor generation efficiency. This research addresses freshwater scarcity and opens new avenues for sustainable material development.
Healthcare and safety remain pivotal in this issue, with studies delving into early autism screening using federated learning and diabetic retinopathy detection leveraging deep convolutional neural networks. These works underscore the transformative potential of artificial intelligence in improving diagnostic accuracy and protecting sensitive medical data.
Another noteworthy contribution is a study on lightning protection systems for large-scale solar photovoltaic plants in Malaysia. This study provides critical insights into safeguarding renewable energy infrastructures in lightning-prone regions. Such research bridges the gap between technological advancement and safety, ensuring resilience in natural adversities.
This issue also highlights the integration of AI and machine learning in optimizing engineering systems. From a fuzzy logic-based indoor navigation system to an energy management system for standalone microgrids, these innovations demonstrate AI's capability to enhance decision-making, reduce costs, and improve system reliability. For instance, using a Model Predictive Control-based EMS for microgrids presents a tangible solution to balancing renewable energy intermittency and load demands.Interdisciplinary efforts shine through research on 4D radar imaging and its fusion with deep learning for road-crossing classification, emphasizing the role of technology in creating safer urban environments. Similarly, the application of fuzzy logic for vehicle speed control and the development of SolatExo—a passive exoskeleton for individuals with physical disabilities—illustrate how engineering transcends traditional boundaries to address societal needs.
This volume stands as a testament to the vital role of engineering research in shaping a sustainable, inclusive, and technologically advanced future. The diversity of topics and the depth of innovation presented in this issue underline the IIUM Engineering Journal's dedication to advancing knowledge and fostering impactful solutions to global challenges.
We extend our gratitude to the authors, reviewers, and editorial board for their unwavering commitment to excellence. Your contributions ensure that this journal continues to thrive as a beacon of scholarly inquiry and practical impact. Let us embrace these breakthroughs as stepping stones to a brighter, more sustainable future.
Prof. Dr. Teddy Surya GunawanExecutive EditorIIUM Engineering Journal
ISSN: 1511-788X E-ISSN: 2289-7860
Published by:IIUM Press,International Islamic University MalaysiaJalan Gombak, 53100 Kuala Lumpur, MalaysiaPhone (+603) 6421-5014, Fax: (+603) 6421-629
Machine Learning Models for Predicting the Compressive Strength of Concrete with Shredded PET Bottles and M-Sand as Fine Aggregate
Get PDFMachine Learning (ML) and Artificial Intelligence (AI) are closely intertwined and represent the latest cutting-edge technologies that facilitate the development of intelligent prototypes. Machine learning is a critical subset of AI that deliberates the development of self-trained algorithms that use previous databases and analysis for result predictions. By leveraging past data, machine learning empowers computers to make predictions and decisions. This study investigates the use of ML algorithms to predict the compressive strength of grade 30 concrete, incorporating shredded PET bottles and M-sand as fine aggregates. The experimental setup involved preparing concrete specimens with shredded PET bottle aggregates, varying the volume from 0% to 2% in increments of 0.5%. Different percentages of M-sand were incorporated at 25%, 50%, 75%, and 100%. The mixing proportions adhered to the standards defined by the Department of Environment (DOE). Cubic specimens were cast and cured for 7, 28, and 90 days. The study employs Multiple Linear Regression (MLR), Artificial Neural Network (ANN), and Decision Tree (DT) models, using the experimental data for predictive analysis. The evaluation of the three models for predicting compressive strength yielded interesting results: The Decision Tree (DT) model demonstrated the best performance, with a relatively low Mean Squared Error (MSE) of 5.125 and Mean Absolute Error (MAE) of 1.642 and a high R² value of 0.918, indicating that the model explains approximately 91.8% of the variance in the target variable. The DT model's ability to handle complex, non-linear data relationships made it particularly effective in evaluating concrete strength. The Multiple Linear Regression (MLR) model provided reasonable predictions but showed higher errors compared to the DT model, with MSE and MAE values of 26.663 and 4.298, respectively, and an R² score of 0.571, demonstrating a moderate ability to explain the variance in the data. Conversely, the Artificial Neural Network (ANN) model exhibited the least accuracy, with the highest errors (MSE of 112.33 and MAE of 8.52) and a negative R² score (-0.64), indicating poor model training and an inability to capture the relationships between parameters effectively, partly due to the relatively small dataset. The study highlights the potential of DT models in sustainable construction practices, emphasizing the importance of comprehensive datasets and further exploration of alternative algorithms. The findings advocate for using ML in concrete strength prediction, contributing to advancements in sustainable engineering and material science.
ABSTRAK: Pembelajaran Mesin (ML) dan Kecerdasan Buatan (AI) saling berkait rapat dan mewakili teknologi canggih terkini yang membantu pembangunan prototaip pintar. Pembelajaran mesin adalah subset kritikal AI yang menumpukan pada pembangunan algoritma dilatih sendiri menggunakan pangkalan data dan analisis terdahulu bagi meramal hasil. Dengan memanfaatkan data masa lalu, pembelajaran mesin memberi kuasa kepada komputer bagi membuat ramalan dan keputusan. Kajian ini menyelidik penggunaan algoritma ML bagi meramalkan kekuatan mampatan konkrit gred 30, menggabungkan botol PET yang dicincang dan pasir-M sebagai agregat halus. Susunan eksperimen melibatkan penyediaan spesimen konkrit dengan agregat botol PET yang dicincang, memvariasikan isipadu dari 0% hingga 2% dalam kenaikan 0.5%. Peratusan berbeza bagi pasir-M telah digabungkan pada 25%, 50%, 75%, dan 100%. Nisbah campuran mematuhi piawaian yang ditetapkan oleh Jabatan Alam Sekitar (DOE). Spesimen kubik dipadatkan dan diawetkan selama 7, 28, dan 90 hari. Kajian ini menggunakan model Regresi Linear Berganda (MLR), Rangkaian Neural Buatan (ANN), dan Pokok Keputusan (DT), manakala data eksperimen digunakan bagi analisis ramalan. Penilaian terhadap tiga model bagi meramal kekuatan mampatan menghasilkan keputusan yang menarik: Model Pokok Keputusan (DT) menunjukkan prestasi terbaik, dengan Ralat Kuasa Dua Min (MSE) yang agak rendah iaitu 5.125 dan Ralat Mutlak Min (MAE) 1.642, serta nilai R² yang tinggi iaitu 0.918, menunjukkan bahawa kira-kira 91.8% daripada model varian ini dalam pemboleh ubah sasaran. Keupayaan model DT bagi mengurus data kompleks dan tidak linear menjadikannya sangat berkesan dalam menilai kekuatan konkrit. Model Regresi Linear Berganda (MLR) memberi ramalan munasabah tetapi menunjukkan ralat lebih tinggi berbanding model DT, dengan nilai MSE dan MAE masing-masing 26.663 dan 4.298, dan skor R² 0.571, menunjukkan keupayaan sederhana bagi menjelaskan varians data. Sebaliknya, model Rangkaian Neural Buatan (ANN) menunjukkan ketepatan paling rendah, dengan ralat tertinggi (MSE 112.33 dan MAE 8.52) dan skor R² negatif (-0.64), yang menunjukkan latihan model yang lemah dan ketidakmampuan menangkap hubungan antara parameter dengan berkesan, sebahagiannya disebabkan oleh dataset yang kecil. Kajian ini menekankan potensi model DT dalam amalan pembinaan lestari, menekankan kepentingan dataset yang komprehensif dan penerokaan lanjut mengenai algoritma alternatif. Dapatan kajian menyokong penggunaan ML dalam ramalan kekuatan konkrit, menyumbang kepada kemajuan dalam kejuruteraan lestari dan sains bahan
Modelling of the Pi-Shape Low-Concentrating Photovoltaic Solar Cells
Get PDFOne of the cheapest ways to improve photovoltaic (PV) systems is to create LCPV systems with polycrystalline silicon solar cells, which require less cost and have high optical efficiency. Additional reflective mirrors were added to improve the optical efficiency of the low concentrating photovoltaic (LCPV) system based on a Fresnel lens. Pi-shaped LCPV cells were obtained and compared with an ordinary LCPV based on a Fresnel lens. The proposed LCPV shows high optical efficiency even at 50 mm of cell-lens distance, while the ordinary LCPV presents a maximum of 30% of optical efficiency. The concentration ratio of 8 suns can be achieved at 150 mm of cell-lens distance at the range ±20° of the incidence angle. When the cell-lens distance is 100 mm or 125 mm, the optical efficiency is more than 80%, and the concentration ratio (CR) is more than 2 suns at the range of incidence angle ±25°. The proposed LCPV design helps to work the system at ±25° without the help of a solar tracking system. Hence, when developing the LCPV system, increasing the acceptance angle might reduce the work of solar tracking systems and the tracking errors. Good irradiance uniformity can be achieved, and the acceptance angle can be increased.
ABSTRAK: Salah satu cara termurah bagi menambah baik sistem fotovoltaik (PV) adalah dengan mencipta sistem LCPV menggunakan sel solar silikon polihabluran, di mana kos lebih rendah dan kecekapan optik tinggi. Bagi meningkatkan kecekapan optik fotovoltaik rendah tumpuan (LCPV) berasaskan kanta Fresnel, cermin pantulan tambahan diperlukan dan bentuk Pi LCPV diperolehi dan dibanding dengan LCPV biasa berasaskan kanta Fresnel. LCPV yang dicadangkan ini menunjukkan kecekapan optik tinggi walau pada jarak 50 mm antara sel dan kanta, manakala LCPV biasa mencapai kecekapan optik maksimum sebanyak 30%. Nisbah tumpuan sebanyak 8 kali pencahayaan matahari dapat dicapai pada jarak 150 mm antara sel dan kanta dalam julat sudut kejadian ±20°. Apabila jarak antara sel dan kanta sebanyak 100 - 125 mm, kecekapan optik adalah melebihi 80% dan nisbah tumpuan (CR) melebihi 2 pencahayaan matahari dalam julat sudut kejadian ±25°. LCPV yang dicadangkan ini dapat membantu sistem beroperasi pada julat sudut ±25° tanpa bantuan sistem penjejak suria. Oleh itu, dengan meningkatkan sudut penerimaan sistem LCPV semasa mencipta sistem, ini berkemungkinan mengurangkan keperluan sistem penjejak suria dan mengurangkan ralat penjejak, mencapai taburan pencahayaan seragam, serta meningkatkan sudut penerimaan secara keseluruhan
Sheet Metal Manual Handling Aids: Effects of Design Differences on Muscle Activity and Subjective Assessment
Get PDFManual material handling is a common task in various industries and has been linked to work-related musculoskeletal injuries. Handling heavy and bulky sheet metal manually can cause awkward postures and forceful exertion, leading to intense biomechanical load on the workers. A trolley lifter was designed and fabricated to address this issue to improve work postures during sheet metal transfer tasks. This study aimed to investigate the potential ergonomic benefits of the trolley lifter design compared to the traditional hydraulic table cart. The study aims to determine the effect of the design differences between the two devices on muscle activities during sheet metal handling operations and to compare subjective perceptions of the subjects on these devices. The independent variable in this study was the type of device used for sheet metal handling (i.e., trolley lifter vs. traditional hydraulic table cart) and types of sheet metals (vary by thickness). The dependent variables were muscle activities in four different muscles (biceps brachii, triceps brachii, erector spinae, and trapezius) and subjective perceptions of the devices. A randomized repeated-measure experimental design was employed, surface electromyography was used to measure muscle activities, and a subjective questionnaire was administered to gather data on the participants' perceptions of the devices. Participants were asked to perform separate sheet metal handling operations using both devices. The relationship between the dependent and independent variables was examined. The non-parametric test indicated that there were significant decreases in muscle activation levels in the biceps brachii, triceps brachii, erector spinae, and trapezius muscles when using the trolley lifter compared to the traditional hydraulic table cart. Moreover, participants rated the trolley lifter as more usable, useful, and desirable than the traditional hydraulic table cart. In conclusion, the trolley lifter was a more effective and ergonomically beneficial tool for handling large sheet metals than the traditional hydraulic table cart. This study highlights the importance of ergonomic interventions in manual material handling tasks, advocating for adopting tools and equipment that can enhance worker safety, reduce physical strain, and improve overall job satisfaction.
ABSTRAK: Pengendalian bahan secara manual adalah tugas biasa dalam pelbagai industri dan telah dikaitkan dengan kecederaan muskuloskeletal yang berkaitan dengan kerja. Mengendalikan kepingan logam yang berat dan besar secara manual boleh menyebabkan postur yang janggal dan tenaga yang kuat yang membawa kepada beban biomekanikal yang kuat pada pekerja. Untuk menangani isu ini, pengangkat troli telah direka untuk memperbaiki postur kerja semasa tugas pemindahan kepingan logam. Kajian ini bertujuan untuk menyiasat lebih lanjut potensi faedah ergonomik reka bentuk pengangkat troli berbanding troli meja hidraulik tradisional. Objektif kajian ini adalah untuk menentukan kesan perbezaan reka bentuk antara kedua-dua peranti pada aktiviti otot semasa operasi pengendalian kepingan logam dan untuk membandingkan persepsi subjektif subjek kepada peranti ini. Pembolehubah bebas dalam kajian ini ialah jenis peranti yang digunakan untuk pengendalian kepingan logam (iaitu, pengangkat troli berbanding troli meja hidraulik tradisional) dan jenis kepingan logam (berbeza mengikut ketebalan). Pembolehubah bersandar ialah aktiviti otot dalam empat otot yang berbeza (biceps brachii, triceps brachii, erector spinae, dan trapezius) dan persepsi subjektif pada peranti. Reka bentuk eksperimen ukuran berulang secara rawak telah digunakan dan elektromiografi permukaan digunakan untuk mengukur aktiviti otot, serta soal selidik subjektif telah diberikan untuk mengumpul data mengenai persepsi peserta kepada peranti. Peserta diminta melakukan operasi pengendalian kepingan logam menggunakan kedua-dua peranti pada masa yang berasingan. Hubungan antara pembolehubah bersandar dan tidak bersandar telah dikaji. Ujian bukan parametrik menunjukkan bahawa terdapat penurunan ketara dalam tahap pengaktifan otot dalam bisep brachii, triceps brachii, erector spinae, dan otot trapezius apabila menggunakan pengangkat troli berbanding dengan troli meja hidraulik tradisional. Selain itu, peserta menilai pengangkat troli sebagai lebih boleh digunakan, berguna dan diingini daripada troli meja hidraulik tradisional. Kesimpulannya, pengangkat troli telah terbukti sebagai alat yang lebih berkesan dan ergonomik untuk mengendalikan kepingan logam yang besar berbanding dengan kereta meja hidraulik tradisional. Kajian ini menyerlahkan kepentingan campur tangan ergonomik dalam tugas pengendalian bahan manual, menyokong penggunaan alatan dan peralatan yang boleh meningkatkan keselamatan pekerja, mengurangkan ketegangan fizikal, dan meningkatkan kepuasan kerja secara keseluruhan
Regenerative Braking System (RBS) MOSFET Switching-Based Drive Cycle for an Electric Motorcycle
Get PDFA regenerative braking system is an advanced technology applicable to transportation, particularly electric vehicles. The purpose of incorporating regenerative braking is to recover energy during braking and deceleration, which can be stored in the battery. This paper aims to study the operation of the regenerative braking system based on an urban drive cycle. This study selects the US60 and NEDC drive cycles as inputs to evaluate future powertrain systems and vehicle concepts. The output torque is calculated longitudinally based on the vehicle dynamic equation to determine whether the torque is negative or positive. When the torque is negative, regenerative braking applies, and the state of charge (SoC) of the battery increases. The concept of regenerative braking is that this system uses four MOSFETs as switches. As a result, at the 50% level of SoC, the first regeneration improved performance by 12.22%, whereas the second showed a smaller gain of 5.96%. Similarly, at the 80% level of SoC, the first regeneration yielded a 12.55% increase, while the second achieved only a 6.19% improvement. The rise in SoC for both levels demonstrates that energy can be recovered when implementing regenerative braking. Therefore, the results obtained from the MATLAB simulation will be used for future studies in implementing a regenerative braking control strategy.
ABSTRAK: Sistem brek jana semula adalah teknologi canggih yang digunakan untuk pengangkutan, terutamanya kenderaan elektrik. Tujuan menggabungkan brek jana semula adalah bagi memulihkan tenaga semasa brek dan nyahpecutan, yang boleh disimpan dalam bateri. Kajian ini bertujuan bagi mengkaji operasi sistem brek jana semula berdasarkan kitaran pacuan bandar. Dalam kajian ini, kitaran pemacu US60 dan NEDC dipilih sebagai input bagi menilai sistem powertrain dan konsep kenderaan masa hadapan. Tork keluaran dikira berdasarkan persamaan dinamik membujur kenderaan bagi menentukan tork negatif atau positif. Apabila tork negatif, brek jana semula terpakai, dan keadaan cas (SoC) bateri meningkat. Konsep brek sistem jana semula ini menggunakan empat MOSFET sebagai suis. Hasilnya, pada tahap 50% SoC, penjanaan semula pertama meningkatkan prestasi sebanyak 12.22%, manakala tahap kedua menunjukkan kenaikan lebih kecil iaitu 5.96%. Begitu juga, pada tahap 80% SoC, penjanaan semula pertama menghasilkan peningkatan 12.55%, manakala yang kedua hanya mencapai peningkatan 6.19%. Peningkatan SoC bagi kedua-dua tahap menunjukkan bahawa tenaga boleh dipulihkan bagi melaksanakan brek jana semula. Oleh itu, dapatan kajian yang diperoleh dari simulasi MATLAB akan digunakan untuk kajian masa hadapan dalam melaksanakan strategi kawalan brek jana semula
Dynamic Analysis on an Aerial Work Platform Using a Hybrid CAD Approach for Satellite Testing Applications
Get PDFThis paper presents a dynamic analysis using a hybrid CAD model approach, focusing on a motorized adjustable vertical platform's lifting and baseplate loading subsystems as a case study. The hybrid CAD model approach allows for examining mechanism behaviours such as acceleration torque, speed variation, and jerk rates, as well as their impact on the total torque required by the subsystems. The analysis starts by developing 3D and 2D models with velocity profiles, followed by comprehensive analyses. The most interesting part of the study is that while the acceleration torque rate is high, its influence is minimal due to small accelerations and decelerations at approximately -5 × 10-5 m/s3 to 3.1 × 10-5 m/s3 within the subsystem. Additionally, torque requirements for the lifting subsystem remain consistent at 631.22 N · m at the highest position and 364.16 N · m at the lowest position across different speed modes. The study also evaluates jerk rates during acceleration and deceleration to ensure compliance with ISO standards for ride quality. This approach shows promise for developing heavy-duty autonomous aerial work platforms, especially in the space industry, where understanding system behaviours is crucial before the development process begins.
ABSTRAK: Kajian ini membentangkan analisis dinamik menggunakan pendekatan model hibrid CAD, dengan tumpuan kepada subsistem pengangkatan dan pemuatan plat asas (baseplate loading subsystem) bagi platfom menegak boleh laras bermotor (motorised adjustable vertical platform) sebagai kajian kes. Pendekatan model hibrid CAD ini membolehkan pemerhatian terhadap tingkah laku mekanisme seperti kadar tork pecutan, variasi kelajuan, dan kadar kejutan, serta impaknya terhadap jumlah tork yang diperlukan oleh subsistem. Analisis dimulakan dengan pembangunan model 3D dan 2D dengan profil kelajuan, diikuti dengan analisis komprehensif. Penemuan paling menarik yang didapati pada kajian ini adalah walaupun kadar tork pecutan tinggi, pengaruhnya sangat minimum kerana pecutan dan penghentian kecil dalam subsistem iaitu sekitar -5 x 10-5 m/s3 hingga 3.1 x 10-5 m/s3. Tambahan, keperluan tork bagi mengangkat subsistem kekal konsisten pada 631.22 N.m pada posisi tertinggi dan posisi terendah pada 364.16 N.m merentasi pelbagai mod kelajuan. Kajian ini juga menilai kadar kejutan semasa pecutan dan pengurangan kelajuan bagi memastikan pematuhan piawaian ISO bagi kualiti tunggangan. Pendekatan ini menunjukkan potensi dalam membangunkan platform kerja berat di udara secara autonomi, terutama dalam industri angkasa, di mana pemahaman tingkah laku sistem adalah penting sebelum proses pembangunan bermula