Defence Science Journal最新文献_第10页

Addressing Thermal Distortion in Additive Manufacturing of Topology Optimized Structures Through Reverse Shape Morphing 通过反向形状变形解决拓扑优化结构增材制造中的热变形

IF 0.9 4区工程技术

Defence Science Journal Pub Date : 2022-12-06 DOI: 10.14429/dsj.72.17977

A. Jha, Gyanendra Pandey, H. Bedi

{"title":"Addressing Thermal Distortion in Additive Manufacturing of Topology Optimized Structures Through Reverse Shape Morphing","authors":"A. Jha, Gyanendra Pandey, H. Bedi","doi":"10.14429/dsj.72.17977","DOIUrl":"https://doi.org/10.14429/dsj.72.17977","url":null,"abstract":"Design of light weight structures is an important aspect in the aircraft industry, since minimizing the weightof components improves the overall aircraft performance. However, conventional manufacturing methods work on standard geometries and shapes, and often lead to overdesigning of parts. Additive Manufacturing (AM) overcomes these issues by allowing more design freedom. The present study focuses on two aspects of AM: (1) part consolidation through topology optimization, and (2) addressing thermal distortion through reverse shape morphing. An assembly of two load bearing brackets is first amalgamated into a single Topology Optimized (TO) part, which satisfies the displacement and stress requirements of the original design. After a series of optimization iterations, the final TO part (278 g) weighs 69 % lesser than the original assembled design (909 g), still meeting the design constraints. The TO part thus eliminates the need of fasteners to join both the brackets, thereby, making the design simpler yet effective. Moreover, a homogeneous stress distribution in the optimized part allows for efficient material utilization. In order to overcome thermal distortion that results during the AM process, the shape of the TO part is transformed in a sense opposite to the distortions produced. This is achieved through reverse shape morphing technique, that reduces thermal distortions in the printed part to sub-micron levels, and the morphed TO part conforms to the requirements meeting the design constraints. Therefore, the implementation of topology optimization along with reverse shape morphing makes the design simple and efficient having reduced distortion. This is achieved without any need of modifications in the manufacturing system or equipment, and such a strategy can be replicated and implemented at industrial scale as well.","PeriodicalId":11043,"journal":{"name":"Defence Science Journal","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47339856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Novel Statistical Techniques for Conducting Accelerated Life Test to Demonstrate Product Reliability 进行加速寿命试验以证明产品可靠性的新统计技术

IF 0.9 4区工程技术

Defence Science Journal Pub Date : 2022-11-01 DOI: 10.14429/dsj.72.17838

M. Basha, Nliesh R Ware

引用次数: 0

Experimental Investigation of the Muzzle Blast for the Amphibious Rifles when Shooting Underwater 水陆两栖步枪水下射击炮口冲击波实验研究

IF 0.9 4区工程技术

Defence Science Journal Pub Date : 2022-11-01 DOI: 10.14429/dsj.72.17367

Hung Nguyen Van, Dao Van Doan

引用次数: 1

HILS based Waypoint Simulation for Fixed Wing Unmanned Aerial Vehicle (UAV) 基于HILS的固定翼无人机航路点仿真

IF 0.9 4区工程技术

Defence Science Journal Pub Date : 2022-11-01 DOI: 10.14429/dsj.72.17952

Kaviyarasu A, Saravanakumar A, Rajesh G

引用次数: 0

Simple and Efficient Group Key Distribution Protocol using Matrices 基于矩阵的简单高效的组密钥分发协议

IF 0.9 4区工程技术

Defence Science Journal Pub Date : 2022-11-01 DOI: 10.14429/dsj.72.17461

Indivar Gupta, Atul Pandey, D. Singh

引用次数: 0

Construction and Analysis of Petri Net Model for Distributed Cyber Physical Systems 分布式网络物理系统Petri网模型的构建与分析

IF 0.9 4区工程技术

Defence Science Journal Pub Date : 2022-11-01 DOI: 10.14429/dsj.72.17987

Vikas Sood, M. Nema, Rituraj Kumar, M. Nene

{"title":"Construction and Analysis of Petri Net Model for Distributed Cyber Physical Systems","authors":"Vikas Sood, M. Nema, Rituraj Kumar, M. Nene","doi":"10.14429/dsj.72.17987","DOIUrl":"https://doi.org/10.14429/dsj.72.17987","url":null,"abstract":"A Distributed Cyber-Physical System (DCPS) composition poses challenges in determining its emergent behaviour. These challenges occur due to (1) the appearance of causal loops of information and energy flow through cyber and physical channels and (2) inherent non-determinism in the temporally ordered flow of events within independently evolving interacting processes of Constituent Systems (CSs). Hence, there is a need to construct a model of the envisaged schematic of DCPS composition for analysis and verification of its significant properties in the conceptual design stage of the system development life cycle. \u0000This paper presents a procedure to construct DCPS composition models in Petri net formalism using distributed abstractions. The model for each CS is obtained from elementary constructs using compositional operators. The interaction among CSs occurs through channels obtained by connecting send and receive constructs of two CSs participating in an interaction. The internal processing within a CS characterizing its primary function is abstracted in a generic passthrough construct. Representing these constructs with compositional operators results in the complete DCPS model in Petri net formalism. A toolchain with Reference net workshop (Renew) as an integrated Petri net editing and analysis platform is configured to support DCPS modelling, simulation and analysis. The Renew tool functionality has been enhanced with a plugin designed and developed by authors to facilitate the drawing of the distributed composition model. \u0000A low-level Petri net analysis (Lola) v2.0 plugin is employed to verify the Petri net and temporal properties of the modelled DCPS scenarios. The properties of the resultant model are verified using well-established algorithms to analyze Petri nets. Further, system properties specified using temporal logic can be verified using model-checking algorithms for Petri nets. A moderately complex scenario involving interactions among six CSs illustrates the presented approach.","PeriodicalId":11043,"journal":{"name":"Defence Science Journal","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48375435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal Step Size Technique for Frequency Domain and Partition Block Adaptive Filters for PEM based Acoustic Feedback Cancellation 基于PEM的声反馈抵消频域和分区块自适应滤波器的最优步长技术

IF 0.9 4区工程技术

Defence Science Journal Pub Date : 2022-11-01 DOI: 10.14429/dsj.72.17881

Sripathi Siva Prasad, C. Rama Rao

{"title":"Optimal Step Size Technique for Frequency Domain and Partition Block Adaptive Filters for PEM based Acoustic Feedback Cancellation","authors":"Sripathi Siva Prasad, C. Rama Rao","doi":"10.14429/dsj.72.17881","DOIUrl":"https://doi.org/10.14429/dsj.72.17881","url":null,"abstract":"The adaptive filtering approach has been commonly used to perform acoustic feedback cancellation (AFC) in digital hearing-aids due to its reliable performance and feasibility. Because the loudspeaker and microphone are close together in hearing aids, the corresponding signals are highly correlated, resulting in biased estimation if adaptive filters are used. This problem can be addressed with the help of the decorrelation prefilter by incorporating the Prediction Error Method (PEM) technique into AFC. Frequency-Domain Adaptive Filters (FDAF) are preferable over the time-domain implementation to achieve better performance in terms of convergence and computational complexity. In addition, Partition-Block Frequency-Domain Adaptive Filters (PBFDAF) offers low processing delay. However, because of their fixed step-size, there is a trade-off between initial convergence and steady-state misalignment in the widely used frequency-domain algorithms. While Variable Step-Size (VSS) algorithms can help with this issue, VSS techniques for frequency-domain algorithms have not been extensively studied in the context of PEM-AFC. Hence, in this paper, we presented an Optimal Step-Size (OSS) technique for both the FDAF-PEM_AFC and PBFDAF-PEM_AFC algorithms to simultaneously accomplish fast convergence and minimal steady-state error. A Feedback Path Change Detector (FPCD) was also incorporated into the proposed algorithms to address the problem of convergence in non-stationary feedback paths. The results of simulations show that the proposed algorithms are clearly superior, and they are encouraging.","PeriodicalId":11043,"journal":{"name":"Defence Science Journal","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46827504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

An Optimal Retinanet Model For Automatic Satellite Image Based Missile Site Detection 基于卫星图像的导弹阵地自动检测的最优retanet模型

IF 0.9 4区工程技术

Defence Science Journal Pub Date : 2022-11-01 DOI: 10.14429/dsj.72.18215

Ashwin Yadav, K. Jain, Akshay Pandey, Eshta Ranyal, Joydeep Majumdar

{"title":"An Optimal Retinanet Model For Automatic Satellite Image Based Missile Site Detection","authors":"Ashwin Yadav, K. Jain, Akshay Pandey, Eshta Ranyal, Joydeep Majumdar","doi":"10.14429/dsj.72.18215","DOIUrl":"https://doi.org/10.14429/dsj.72.18215","url":null,"abstract":"Satellite image processing is a manually tedious job and offers scope for automation as part of the information extraction process from satellite images. The process of information extraction involves object detection and one of the challenges is ascertaining the minimum number of images required to train the deep learning model to achieve a certain minimum accuracy. To the best of the authors’ knowledge, work in missile site detection is relatively limited, with an existing exploration of the latest one-shot detection methods, such as RetinaNet, being absent. This work proposes an optimal deep learning model based on the RetinaNet framework and training on a minimal dataset. A comparative analysis with previous work paves the road for future research in one-shot methods and optimally trained models. As part of the study, the key findings are that an optimal training scheme based on a minimal training dataset is possible. This step enables a reduction in training time for the development of an optimal missile site detection model is concerned. One of the many techniques to determine the minimal number of training images required to train the object detection model is plotting the number of training images versus the mean average precision. The same is validated in our work. Further, a hybrid scheme based on the two-model concept is tested wherein one model prioritizes Recall while the other prioritizes Precision. Thus a combination of both models to detect a set of targets provides an optimal framework for object detection. Lastly, the study finds that the single-stage RetinaNet algorithm offers the advantage of balancing speed and accuracy over erstwhile two-stage and other single-stage methods.","PeriodicalId":11043,"journal":{"name":"Defence Science Journal","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46114065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Supervised Machine Learning Model for Tool Condition Monitoring in Smart Manufacturing 智能制造中刀具状态监测的监督机器学习模型

IF 0.9 4区工程技术

Defence Science Journal Pub Date : 2022-11-01 DOI: 10.14429/dsj.72.17533

Ganeshkumar S, D. T, A. Haldorai

{"title":"A Supervised Machine Learning Model for Tool Condition Monitoring in Smart Manufacturing","authors":"Ganeshkumar S, D. T, A. Haldorai","doi":"10.14429/dsj.72.17533","DOIUrl":"https://doi.org/10.14429/dsj.72.17533","url":null,"abstract":"In the current industry 4.0 scenario, good quality cutting tools result in a good surface finish, minimum vibrations, low power consumption, and reduction of machining time. Monitoring tool wear plays a crucial role in manufacturing quality components. In addition to tool monitoring, wear prediction assists the manufacturing systems in making tool-changing decisions. This paper introduces an industrial use case supervised machine learning model to predict the turning tool wear. Cutting forces, the surface roughness of a specimen, and flank wear of tool insert are measured for corresponding spindle speed, feed rate, and depth of cut. Those turning test datasets are applied in machine learning for tool wear predictions. The test was conducted using SNMG TiN Coated Silicon Carbide tool insert in turning of EN8 steel specimen. The dataset of cutting forces, surface finish, and flank wear is extracted from 200 turning tests with varied spindle speed, feed rate, and depth of cut. Random forest regression, Support vector regression, K Nearest Neighbour regression machine learning algorithms are used to predict the tool wear. R squared, the technique shows the random forest machine learning model predicts the tool wear of 91.82% of accuracy validated with the experimental trials. The experimental results exhibit flank wear is mainly influenced by the feed rate followed by the spindle speed and depth of cut. The reduction of flank wear with a lower feed rate can be achieved with a good surface finish of the workpiece. The proposed model may be helpful in tool wear prediction and making tool-changing decisions, which leads to achieving good quality machined components. Moreover, the machine learning model is adaptable for industry 4.0 and cloud environments for intelligent manufacturing systems.","PeriodicalId":11043,"journal":{"name":"Defence Science Journal","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43734373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Experimental Study on the Impact of Seasonal Sound Speed Variability on Signal Detection Range in Arabian Sea 阿拉伯海季节声速变化对信号探测距离影响的实验研究

IF 0.9 4区工程技术

Defence Science Journal Pub Date : 2022-08-26 DOI: 10.14429/dsj.72.17756

Elizabeth Shani N X, Nimmi R Nair, R. Raju, S. R

引用次数: 1