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Experimental investigation of the bullet-proof properties of different kevlar, comparing .22 inch with 9 mm projectiles

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Current Materials Science 2020年第1期13卷 26-38页

作者： stopforth, Riaan Adali, Sarp Stopforth Mechatronics Robotics and Research Lab Discipline of Mechanical Engineering University of KwaZulu-Natal Durban South Africa Discipline of Mechanical Engineering University of KwaZulu-Natal Durban South Africa

Background: Results of an experimental study are given involving high-impact ballistic tests using .22 inch diameter ammunition (commonly known only as .22 ammuni-tion) with the target set up as a combination of different numbers and weights of Kevlar layers. These experimental tests are conducted as literature indicating that the .22 projectiles are not as effective as with larger calibre ammunition. Present work is part of a research study to assess the safety limits of Kevlar layers of different weights against various calibre projectiles. Objective: The objective is to obtain test data to determine the number of Kevlar layers and weights needed for the design of safe bullet proof vests capable of stopping various size ammunition. In the present study, results are given for .22 inch ammunition, which provide data on the characteristics of high-speed ballistic penetration of .22 bullets into Kevlar layers and stopping distances in gel/Kevlar combinations. Methods: Tests were performed with Kevlar fabrics of different weights of Gram per Square Meter (GSM) to provide a comparison among different Kevlar fabrics as well as with different number of Kevlar layers. The tests were conducted with the use of a chronograph in a controlled test environment. The penetration depth in ballistic gelatine was recorded. Results: The results identify the number of layers of Kevlar required to stop a .22 projectile and the relationship between the different layers and weights of Kevlar materials. The results of the .22 projectile penetration are compared with those of different 9 mm Parabellum projectiles to assess the effect of different size ammunition on the bullet-proof capabilities of Kevlar. Experimental data on the penetration depths of different types of bullets into the gel/Kevlar combinations are presented using various graphs. Conclusion: The .22 projectiles perform similar penetration depths compared to that of 9 mm projectiles, and therefore cannot be considered as inef

关键词： Projectiles

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Generic gripper for an unmanned aerial vehicle 30

Generic gripper for an unmanned aerial vehicle

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30th CIRP Design on Design, CIRP Design 2020

作者： Setty, Kiran Van Niekerk, Theo stopforth, Riaan Nelson Mandela University Port Elizabeth South Africa Stopforth Mechatronics Robotics and Research Lab University of KwaZulu-Natal Durban South Africa

research has been performed on the use of a robotic hand to be used as a UAV gripper and the contributions it would make to implement such a product with a UAV. An overview was performed on UAV grippers available for purchase to determine what contributions would be of greatest need from a newly developed UAV gripper. It was found that there is a lack of grippers capable of gripping objects of a variety of shapes. Design features of the mechanical system and control system of the robotic hand that provides functionality of a UAV gripper which is designed to grip objects of various sizes was then discussed. The robotic hand was tested on performing grips on objects of various shapes and sizes to determine its versatility as a gripper and was shown to be used on all the objects tested. Grip tests performed by the robotic hand to evaluate its functionality showed that the robotic hand was capable of lifting 30.4 N if an object is hooked onto it. © 2017 The Authors. Published by Elsevier B.V.

关键词： Grippers

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Experimental study of bullet-proofing capabilities of Kevlar, of different weights and number of layers, with 9mm projectiles

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Defence Technology（防务技术） 2019年第2期15卷 186-192页

作者： Riaan stopforth Sarp Adali Stopforth Mechatronics Robotics and Research Lab Discipline of Mechanical Engineering University of Kwazulu-Natal Centre for Composite Materials and Structures Discipline of Mechanical EngineeringUniversity of KwaZulu-Natal

Kevlar is the most commonly used material as armour for protection against bullets used in hand guns because of its impact resistance, high strength and low weight. These properties make Kevlar an ideal material to be used in bullet-proof vests as compared to other materials. In the present study, different numbers of layers of Kevlar with different weights are tested to determine the weights and the number of layers needed to design a safe bullet-proof vest. For this purpose, several ballistic tests were performed on combinations of ballistic gel and Kevlar layers of different weights. Ballistic impacts are generated by 9 mm Parabellum ammunition. The objective is to assess the characteristics of high-speed ballistic penetration into a combination of a gel and Kevlar and determine the number of layers needed to safely stop the 9 mm bullet and thereby contribute to the design of safe bullet-proof vests. The tests provide information on the distances the bullets can travel in a gel/Kevlar medium before they are stopped and to identify the resistance capabilities of Kevlar of different grams per square meter(GSM). The tests were conducted with the use of a chronograph in a controlled test environment. Specifically, results identify the number of layers of Kevlar required to stop a 9 mm Parabellum projectile, and the effectiveness of using different number of layers of GSM Kevlar material.

关键词： Kevlar 9mm Parabellum bullet Ballistic impact Ballistic gel Material testing

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Generic gripper for an unmanned aerial vehicle

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Procedia CIRP 2020年 91卷 486-488页

作者： Kiran Setty Theo van Niekerk Riaan stopforth Nelson Mandela University Port Elizabeth South Africa Stopforth Mechatronics Robotics and Research Lab University of KwaZulu-Natal Durban South Africa

关键词： gripper unmanned aerial vehicle design

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Sunrise, Sunset and Temperature Now-cast model comparisons for local Safe Drone Flights Predictions: Case study of Durban, South Africa

Sunrise, Sunset and Temperature Now-cast model comparisons f...

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robotics and mechatronics Conference (RobMech)

作者： Riaan stopforth Shaniel Davrajh Stopforth Mechatronics Robotics and Research Lab University of KwaZulu-Natal Durban South Africa CSIR Pretoria South Africa

ISBN: (数字)9781728141626

ISBN: (纸本)9781728141633

The need for climate predictions by the aviation, maritime and agriculture sector, has led to now-casting models being investigated. Now-casting is the climatic prediction of up to 6 hours into the future. The accuracy of the now-casting temperature predictions is dependent on the sunrise and sunset times. The now-casting sunrise and sunset times prediction model is compared with the NOAA model sunrise and sunset times. Using these two models, the temperature now-casting predictions for daytime and nighttime is determined to compared and identify the accuracy between them.

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Autonomous Landing of a Multirotor Aircraft on a Docking Station

Autonomous Landing of a Multirotor Aircraft on a Docking Sta...

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robotics and mechatronics Conference (RobMech)

作者： Benjamin Nelson Jacques Du Preez Theo van Niekerk Russell Phillips Riaan stopforth Nelson Mandela University Port Elizabeth South Africa Stopforth Mechatronics Robotics and Research Lab University of Kwazulu-Natal Durban South Africa

ISBN: (数字)9781728141626

ISBN: (纸本)9781728141633

A multirotor aircraft was developed to help test if an aircraft could land autonomously on a docking station. A docking station was designed to allow for the autonomous charging of an aircraft. The docking station makes use of a XY-Positioning table to accurately position an aircraft on the landing platform once an aircraft has successfully landed. A contact charging method was developed to allow for a charge connection between the aircraft and the docking station, once the aircraft had been correctly positioned. An ArUco marker was used in order to help the aircraft detect and accurately land on the docking station. The aircraft contained an onboard computer running ROS (including MAVROS) to control the Pixhawk flight controller, which was running PX4 open source firmware. A simulation of the landing system was successfully performed in Gazebo.

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Real-Time Optimization of Single Pole Low Pass Filter using Signal-to-Noise Ratio Maximization

Real-Time Optimization of Single Pole Low Pass Filter using ...

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robotics and mechatronics Conference (RobMech)

作者： Winston Dyason Theo Ian van Niekerk Russell Phillips Riaan stopforth Advanced Mechatronics Technology Center Nelson Mandela University Port Elizabeth South Africa Stopforth Mechatronics Robotics and Research Lab University of KwaZulu-Natal Durban South Africa

ISBN: (数字)9781728141626

ISBN: (纸本)9781728141633

In this paper, further studies have been made on improving the output performance optimization of the exponentially weighted moving average filter for real-time system applications. It has been shown in prior research that the filter is an effective, low-cost filtering algorithm; however, its output performance is dependent on the calibration of its gain parameter. As a result, the filter will produce sub-optimal outputs if not calibrated correctly. A method is sought that can provide an appropriate gain parameter for maximizing the signal-to-noise ratio of the filter's resulting output, thereby increasing the effectiveness of the filter for real-time system applications. A trial-and-error experimental approach was used to find the filter's optimal parameter gain that maximizes the filter's output signal to noise ratio for a known signal that is sampled using a Gaussian distribution model. It was found that the output signal performance of the complementary filter is highly dependent on its chosen parameter gain, and using a static parameter gain value is unsuitable. An equation was found that approximates an optimal parameter gain to produce a filtered output with the best signal to noise ratio and applied to a real-world application.

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Using Deep Learning Techniques for South African Power Distribution Networks Load Forecasting

Using Deep Learning Techniques for South African Power Distr...

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International Conference on Optimization of Electrical and Electronic Equipment, OPTIM

作者： Sibonelo Motepe Ali N. Hasan Bhekisipho Twala Riaan stopforth Faculty of Engineering and the Built Environment University of Johannesburg Johannesburg South Africa Faculty of Engineering University of South Africa Johannesburg South Africa Stopforth Mechatronics Robotics and Research Lab School of Engineering University of South Africa Durban South Africa

ISBN: (数字)9781538676875

ISBN: (纸本)9781538676882

Load forecasting has many benefits for utilities. Artificial Intelligence (AI) has been seen to be effective in load forecasting. Deep Learning AI techniques have been found to perform better than traditional AI techniques. The study of deep learning techniques application in South African load forecasting is in its infancy. This paper presents a study of a South African distribution substation using two deep learning techniques, deep belief networks (DBN) and long short-term memory (LSTM), to address this. The impact of temperature and cleaning up the loading data is also studied. It was found that an LSTM model achieved the lowest errors with a symmetric mean absolute percentage error (sMAPE) of 3.3%, an), mean absolute error (MAE) of 4.6% and root mean square error (RMSE) of 5.5%. These errors were achieved with non-cleaned data with temperature not used as a variable for the training the model. Deep learning techniques can thus be used without weather parameters to forecast distribution substation data with low errors.

关键词： Load forecasting Machine learning Substations Loading Load modeling Temperature distribution Input variables

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South African Power Distribution Network Load Forecasting Using Hybrid AI Techniques: ANFIS and OP-ELM

South African Power Distribution Network Load Forecasting Us...

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International Conference on Optimization of Electrical and Electronic Equipment, OPTIM

作者： Sibonelo Motepe Ali N. Hasan Bhekisipho Twala Riaan stopforth Nancy Alajarmeh Faculty of Engineering and the Built Environment University of Johannesburg Johannesburg South Africa Faculty of Engineering University of South Africa Johannesburg South Africa Stopforth Mechatronics Robotics and Research Lab School of Engineering University of KwaZulu Natal Durban South Africa Tafila Technical University Tafila Jordan

ISBN: (数字)9781538676875

ISBN: (纸本)9781538676882

South Africa has been a late participant in the previous industrial revolutions. With the fourth industrial revolution upon us, South Africa cannot afford to be left behind. Artificial Intelligence (AI) and big data, which are at the center of this revolution, are improving humans lives. Load forecasting has been shown to have benefits in power systems maintenance and operation. The study of load foreasting in South African (SA) power distribution networks using AI is limited. This paper presents a comparative study of hybrid AI techniques, adaptive neuro-fuzzy inference systems (ANFIS) and OP-ELM, in South African distribution load forecasting. This is achieved with a case study on a real South African large power consuming substation using three performance measures, root mean square error (RMSE), mean absolute error (MAE) and symmetric mean absolute percentage error (sMAPE). The paper also investigates the impact of cleaning up loading data and the inclusion of temperature on the two techniques' models' performance. OP-ELM achieved the lowest error in comparison to ANFIS, achieving an sMAPE of 3.83%, MAE of 5.32% and RMSE of 6.52%. Hybrid AI techniques can thus be used to forecast load in South African distribution networks. This application of AI can lead to costs savings for S.A. power utilities.

关键词： Load forecasting Artificial intelligence Loading Substations Temperature measurement Measurement uncertainty Input variables

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Performance evaluation and comparison of filters for real time embedded system applications

Performance evaluation and comparison of filters for real ti...

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robotics and mechatronics Conference (RobMech)

作者： Winston Dyason Theo Ian van Niekerk Russell Phillips Riaan stopforth Advanced Mechatronics Technology Center Nelson Mandela University Port Elizabeth South Africa Stopforth Mechatronics Robotics and research Lab University of KwaZulu-Natal Durban South Africa

This paper focuses on an evaluation of an exponentially weighted moving average (EWMA) filter which has its results compared to the well known Kalman filter (KF) and a proportional (P) filter. The KF is well known and widely used in a variety of applications because of its accuracy, robustness and relative computational simplicity. Scenarios however do exist where the KF is not a suitable filter to use due to perhaps computational resource restrictions or smooth results requirements where the KF's performance can be lacking. The EWMA filter is proposed as a viable alternative to the KF, by providing a similar accuracy, improved robustness and dynamic response whilst being substantially less computationally expensive. A P filter is also presented as an effective and robust filter with minimal computational requirements. Performance comparisons are made between the three filter types and specific use cases are highlighted for that will enable designers to select the most appropriate filter for their needs based on signal-to-noise ratios.

关键词： Kalman filters Signal processing algorithms Mathematical model Noise measurement Algorithm design and analysis Real-time systems Robustness

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