Conference Publications

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3D mapping and photogrammetry sensor payload for unmanned aerial vehicles
(2023-11) Purdon, Kyla; Van Niekerk, T; Phillips, R; Marais, Stephen T
Unmanned Aerial Vehicles (UAVs) have shown great potential for data collection and monitoring of areas. Sensors such as LiDARs and cameras can be used on UAVs for high-resolution data collection and used for various applications like Digital Surface Models (DSM), photogrammetry, inspection systems, and maintenance applications. This paper describes the design and implementation of a sensor payload for UAVs using a LiDAR sensor, camera, Inertial Measurement Unit (IMU), and Global Positioning System (GPS). The payload collects data that can be used to georeference LiDAR and camera data, which can later be used to generate a georeferenced map and perform object detection and classification.
4-RRS PKM for stabilisation on a mobile sensor platform
(2023-11) Ramruthan, Kshir; Kuchwa-Dube, C
Disturbances experienced by an inspection robot can reduce the quality of its sensor measurements, which can in turn negatively affect the robot’s functionality. This research aimed to design a Parallel Kinematic Mechanism (PKM) for use as a stabilisation mechanism. The research focused on designing, simulating, building, testing, and analysing the mechanism. The PKM was modelled and simulated using MATLAB®, designed and developed using NX CAD software, and it was tested using a custom-built test rig that could simulate rotational disturbances. Using the metric of absement, the PKM significantly reduced the disturbances, depending on the disturbance induced.
A digital twin framework to support vehicle interaction risk management in the mining industry
(2023-08) Verster, Jacobus J; Roux, Pieter W; Magweregwede, Fleckson; De Ronde, Willis; Crafford, Gerrie; Mashaba, Mathews M; Turundu, Safiya L; Mpofu, Mvikel; Prinsloo, Jacobus V; Ferreira, Pieta; Brodner, Hartmut D
In recent years, transport-related accidents, notably those involving trackless mobile machinery (TMM), have consistently ranked among the top three causes of fatalities and injuries in the South African mining industry (SAMI) [1]. These accidents arise from a combination of mechanical and technical malfunctions, environmental factors, and human or machine operator errors. Remarkably, these incidents persist despite the existence of specific regulations, standards, and codes of practice for transportation and machinery. This paper introduces a digital twin framework for TMM, which employs a systems engineering approach combined with software tools and computational analysis. This framework aims to enhance the current regulations by offering a continuous, quantitative risk assessment. By modelling and detecting non-conformance and adverse vehicle interaction events, the framework provides a quantitative risk analysis that complements the prevailing qualitative methods reliant on historical data and operational experience. A case study conducted at the CSIR main campus in Pretoria showcases the potential of the TMM Digital Twin.
Applying design for additive manufacturing to existing aerospace parts
(2023-11) Bester, Duwan C
Additive Manufacturing has widely been used in the aerospace industry. However, local uptake in the aerospace industry has been slow with mostly additively manufactured polymer parts being used. The Advanced High Performance Reconnaissance Light Aircraft (AHRLAC), which is a locally produced military aircraft, is well positioned to prove the local capabilities in Metal Additive Manufacturing to the local Aerospace industry. Two parts of this aircraft were identified through prior experience in Additive Manufacturing and taken through the Design for Additive Manufacturing process. The identified parts were a forward cockpit control cable mount and a canopy guide. The parts were redesigned using topology optimisation and, in both instances, a weight, cost, and lead time reduction was achieved.
ARGUS: A pole climbing surveillance robot
(2023-11) De Ronde, Wiilis; Bosscha, Peter A; Marais, Stephen T; Pretorius, A
Due to the high prevalence and unpredictability of violent protest action in South Africa, a need has arisen for rapidly deployable surveillance. This paper proposes an Automated Robotic Guardian for Urban Surveillance (ARGUS) platform, a wheeled, pole climbing robot as a potential solution. The platform is designed to attach to and traverse up existing cylindrically shaped infrastructure, such as light posts, enabling easy deployment in urban environments. The robot is intended for varioussurveillance needs, such as public safety at events, and periods of unrest or protest action. Following a detailed concept design stage, simulated results are presented for the proposed robot. This includes comprehensive CAD modelling, static force and torque calculations of the pole climbing robot, and finite element analysis of the component stresses while positioned on the pole. The robotic platform is currently in production and future work will include experimental validation of the simulated system.
Assembly line quality assurance through hand tracking and object detection
(2022-10) Mokuwe, Mamuku W; Goorun, Yurisha; Crafford, Gerhardus J
This work presents a vision-based quality assurance system that does assembly line monitoring. The system is developed using machine learning hand tracking and object detection methods to monitor the worker’s hand movement while evaluating the correctness of the assembly. Feedback about the order of the steps the worker has taken is continuously shown to the user. This work has the potential to reduce the amount of manual work required for quality assurance in assembly line.
Biosensing multidrug-resistant TB genes using SPR
(2024-01) Chauke, Sipho H; Ombinda-Lemboumba, Saturnin; Dube, FS; Mthunzi-Kufa, Patience
Tuberculosis (TB) is one of the most prevalent infectious diseases globally. Although it is curable, several factors, such as the inappropriate use of treatment drugs lead to drug-resistant strains of TB. The burden of infection is disproportionately high in low-income and resource-limited settings. Furthermore, this disparity is exacerbated in patients with already compromised immune systems. Therefore, early detection and treatment of TB play an important role in reducing the spread and progression to drug-resistant disease forms. There are currently a few rapid multi-drug resistant TB diagnostic tests available, however, most are limited due to costs and accessibility. Several genes, such as catalase-peroxidase (katG) and enoyl reductase (inhA) genes, contain mutations that are responsible for resistance to the TB drug, isoniazid. We therefore, aim to use a custom-built surface plasmon resonance (SPR) system to detect katG and inhA genes. Deoxyribonucleic acid (DNA) probes, specific for katG and inhA, were used as biorecognition elements to capture katG and inhA target DNA. The katG and inhA gene-specific DNA probes were immobilized on a gold-coated glass sensor chip before the target DNA was introduced for detection. As a negative control, a mismatched probe, unspecific to both genes was used for confirmation of the absence of the two genes in the experimental setup. The specificity and sensitivity of the capture probes to the target DNA were investigated using the gold-coated glass sensor chip on the SPR setup. The changes in the resonance angle dip indicated the hybridization of the target DNA and the capture probe. The results from this study will contribute to the optimization of an optical-based biosensor detecting drug-resistant mutations.
A cloud-based road infrastructure analysis system using machine learning
(2022-11) Naidoo, Thegaran; Verster, Jacobus J; Marais, Stephen T
A cloud-based road infrastructure analysis system was developed to assist as an information management system for detecting and managing information about road defects and road assets. The system uses computer vision and machine learning algorithms and is accessed through a web interface. The detection results are viewed through an online, account-based web interface.
Comparing amplitude-based and phase-based quantum plasmonic biosensing
(2024) Mpofu, Kelvin T; Mthunzi-Kufa, Patience
The utilization of quantum resources can enhance the sensitivity of conventional measurement techniques beyond the standard quantum limit (SQL). The objective of quantum metrology is to enable such quantum enhancements in practical devices. To achieve this objective, it is essential to have devices that are compatible with existing quantum resources operating within the SQL. Plasmonic sensors are promising candidates among these devices since they are extensively employed in biochemical sensing applications. Plasmonic sensors exhibit a response to slight variations in the local refractive index, which manifests as a shift in their resonance response. This shift, in turn, induces changes in the amplitude and phase of the probing light. By utilizing quantum states of light, such as NOON states, squeezed states, or Fock states, to probe these sensors, the measurement noise floor can be lowered, enabling the detection of signals below the SQL. In this study, we compare two configurations of quantum plasmonic sensing: phase-based and amplitude-based. By considering the Quantum Cram´er Rao bound for both configurations, we demonstrate that the phase-based configuration can more effectively exploit the available quantum resources than the amplitude-based configuration. A limitation of this work is that it did not consider loss.
A comparison of visual place recognition methods using a mobile robot in an indoor environment
(2023-11) Van Eden, Beatrice; Botha, Natasha; Rosman, B
Spatial awareness is an important competence for a mobile robotic system. A robot needs to localise and perform context interpretation to provide any meaningful service. With the deep learning tools and readily available sensors, visual place recognition is a first step towards identifying the environment to bring a robot closer to spatial awareness. In this paper, we implement place recognition on a mobile robot considering a deep learning approach. For simple place classification, where the task involves classifying images into a limited number of categories, all three architectures; VGG16, Inception-v3 and ResNet50, perform well. However, considering the pros and cons, the choice may depend on available computational resources and deployment constraints.
Design of HERMES: a mobile autonomous surveillance robot for security patrol
(2023-11) Dickens, John S; Maweni, Thabisa; Setati, Tiro; Suddoo, Zubair
The HERMES autonomous surveillance robot platform is a low-cost outdoor autonomous surveillance vehicle. It is designed to autonomously patrol outdoor areas performing surveillance and providing automated alerts of detected vehicles and people. The design and testing of this system are covered in this paper. The design philosophy focused on the use of off-the-shelf components wherever possible with the base of the robot being a modified electric quadbike. The testing has verified that the surveillance robot can perform real-time person and vehicle detection, video streaming, manual and autonomous navigation on a low-cost platform. The development of the robot platform is continuing with the current focus being on the improvement of the autonomous navigation, ingress protection (IP) rating and verification of the battery life.
Detection and quantification of iodine in biological fluids using photonic-based systems: UV-Vis and Transmission spectroscopy
(2024-01) Mcotshana, Zenande KS; Thwala, Nomcebo L; Ombinda-Lemboumba, Saturnin; Ramokolo, Lesiba R; Lugongolo, Masixole Y; Van Steen, E; Mthunzi-Kufa, Patience
Iodine is a crucial trace element that occurs in minute amounts in nature and is necessary for the development of bones, thyroid function, and several metabolic processes. Iodine deficiency, also known as hypothyroidism, affects millions of individuals worldwide, and an overabundance of iodine in the body is known as hyperthyroidism. The early identification of iodine with high sensitivity and selectivity is crucial for physiological impact since the abnormalities caused by iodine disorder can increase the frequency of mortality and mental impairments. This work aims to detect iodine using UV-Vis and Transmission spectroscopy and utilizing selenium nanoparticles as a probe. Selenium nanoparticles (SeNPs) were synthesized by ND: YAG laser method and characterized by Dynamic light scattering (DLS), and High-resolution transmission electron microscopy (HRTEM), while the conjugation of iodine to SeNPs was confirmed by Ultraviolet-visible (UV-vis) spectroscopy. For iodine detection, UV-Vis and Transmission spectroscopy were used and compared and the synthesized colloidal and spherical selenium nanoparticles were utilized as a probe to detect iodine. The absorption peaks and a red shift for SeNPs changed upon the reaction with iodine and this shift may allow for the estimation of iodine concentration. The two methods will enable the detection and monitoring of iodine at different concentrations in the body thus preventing the onset of iodine-related diseases.
Detection of viral pathogens using optical photonic techniques with the aid of selenium nanoparticles
(2024-01) Mcotshana, Zenande KS; Thwala, Nomcebo L; Ombinda-Lemboumba, Saturnin; Ramokolo, Lesiba R; Thobakgale, Setumo L; Lugongolo, Masixole Y; Van Steen, E; Mthunzi-Kufa, Patience
Viral infections such as HIV and SARS-CoV-2 have significantly increased morbidity in humans and resulted in a significant number of fatalities globally, hence early detection is crucial, particularly at a point-of-care (POC) setting to prevent the spread of these diseases. Localized surface plasmon resonance (LSPR) and green light-based Transmission spectroscopy techniques were used in this study to assess real-time molecular interactions between virus-spiked and non-spiked samples. The current study focuses on integrating selenium nanoparticles (SeNPs) with different optical photonic techniques for enhanced detection of HIV. Selenium nanoparticles were synthesized and functionalized with antibodies specific to HIV. Before and after bioconjugation with viral secondary antibodies, the SeNPs were characterized using Ultraviolet–visible (UV-Vis) spectroscopy, Dynamic light scattering (DLS), High-resolution transmission electron microscopy (HRTEM), and Raman spectroscopy, to elucidate their properties and confirm the presence of functional groups. After that, the NPs were integrated with plasmonic systems and used for the enhanced detection of HIV in comparison to traditional LSPR and Transmission spectroscopy. Colloidal selenium nanoparticles were successfully synthesized, using ND: YAG laser. The orange-colored, spherically shaped nanoparticles were evenly distributed and easily resuspended. Anti-HIV antibodies conjugated to SeNPs were added after HIV-specific antibodies were successfully immobilized on a glass slide substrate to react with HIV pseudovirus. The pseudovirus was effectively identified by the use of Transmission Spectroscopy and LSPR techniques. The two optical techniques for HIV detection were more sensitive after integrating selenium nanoparticles, as compared to the conventional Transmission spectroscopy and LSPR methods. This improved and highly sensitive approach may be utilized to identify viral infections early, thus combating the spread of infectious diseases.
Development of a graphical user interface as a learning tool for artificial intelligence
(2021-11) Botha, Natasha; Marais, Stephen T
This study developed a Graphical User Interface (GUI) aimed at teaching the concepts of Machine Learning (ML) algorithms which form the backbone of Artificial Intelligence (AI). This is done by means of tutorial videos and allowing the student to interact with example datasets through a dashboard within the GUI before completing an assessment. This GUI is referred to as a practical station and is one of ten other Industry 4.0 technology practical stations within the MerSETA funded CSIR Learning Factory. The GUI provides an interactive learning experience to introduce the user to three machine learning concepts.
Development of a multipurpose, outdoor autonomous ground vehicle for agricultural inspection
(2021-11) Dickens, John S; Goorun, Yurisha; De Ronde, Willis
The Dassie robot platform is a rugged outdoor autonomous vehicle, capable of moving through rough terrain whilst carrying a heavy payload and operating for extended periods of time. It is designed to autonomously perform inspections of rows of grape vines in a vineyard. The design and testing of this system are covered in this paper.
Effect of heat treatment temperature on the microstructure and microhardness of TiC/Ti6Al4V composite manufactured with laser metal deposition
(2023-11) Kgoahla, Reneilwe M; Lekoadi, Paul M; Masina, Bathusile N
This study presented the investigation of the influence of post heat treatment temperature on the microstructure and hardness of TiC/Ti6Al4V composite manufactured with laser metal deposition. Heat treatment was performed to improve the microstructural homogeneity. It was found that the addition of TiC into Ti6Al4V results in the formation of a Widmanstätten microstructure with different grain sizes on the matrix. Heat treatment of the TiC/Ti6Al4V promoted phase transformations from acicular in the as built to lamella (a + ß) and equiaxial phases in the heat treated samples. The 900°C heat treated sample showed a uniform distribution of a and ß phases, and 1100°C showed an increase in ß phases, which resulted in an equiaxial microstructure. Moreover, Heat treatment at 1100°C resulted in the highest microhardness of 665±13HV.
Effect of LSP parameters on the corrosion and hardness properties of TI6Al4V
(2019-09) Kubjane, SM; Arthur, Nana KK; Masina, Bathusile N; Popoola, API; Pityana, Sisa L
Because of its low density, high corrosion resistance and high strength to weight ratio, titanium and its alloys are widely used in aerospace applications. As a result, the material is exposed to detrimental environment. An enhancement in surface integrity of the alloy is believed to have the potential to prevent the materials from experiencing premature failure in these aggressive environments. One of the promising surface modification techniques for improving the properties of metals is laser shock peening (LSP), which induces compressive residual stresses in the surface of layer of alloy and results in an increase in strength and fatigue life of the part. In the present study, Laser shock peening is employed to modify the microstructure, mechanical properties and corrosion behaviour of LENS-built titanium alloy components. The surface roughness, microstructural evolution, microhardness and corrosion behaviour of the LENS-built is examined before and after laser shock peening treatment. The effect of LSP overlaps on the corrosion and hardness properties of wrought titanium alloy and LENS-built were investigated. LSP treatment with 90, 95 and 99% overlapping were chosen. The mechanical behaviour of the Ti6Al4V was characterized by material hardness measurements to assess the effect of the peening process on material properties. The microstructure of the peened samples revealed a homogeneous a + ß phases. Electrochemical tests indicated that LSP improved the corrosion resistance of Ti6Al4V in sodium chloride. In addition, the hardness of Ti6Al4V increased from 375 HV before LSP to 389 HV after LSP. These results demonstrated that LSP is a promising surface modification method that can be used to improve the mechanical properties and corrosion resistance of Ti6Al4V.
The effect of vanadium and nickel on the microstructure and transformation temperatures of Ti50Pt50 alloy
(2022-11) Motsai, Tebogo; Makhatha, E; Camagu, Sigqibo; Machio, Christopher N; Daswa, Pfarelo; Radingoana, Precious; Motsi, Glenda
Significant research has been done to produce shape memory alloys that have good shape memory properties and high martensitic transformation temperatures. The Ti50Pt50 alloys have been found to have high transformation temperature of around 1050 however, they exhibit negligible shape memory properties. The solid solution strengthening, and improved shape memory properties could be enhanced by ternary alloying. Therefore, this work investigates the effect of varying V and Ni contents, in the range of 6.25 to 12.5at%, on the austenitic and martensitic transformation temperatures, and hardness of the equi-atomic Ti50Pt50 alloy. Arc melting followed by casting and solution heat treatment was carried out to produce the alloys. As-produced alloys were characterized by using scanning electron microscopy, differential scanning calorimetry and hardness testing. The microstructures showed high volume fraction of second phases formed in the TiPtV alloy compared with Ti50Pt50 and TiPtNi alloys. The multiple phases formed in the TiPtV alloys could be the cause of high hardness values observed in these alloys as compared withTi50Pt50 and TiPtNi alloys. Thermal transformation studies revealed that TiPtV alloys exhibit transformation temperature close to Ti50Pt50 alloy, in contrast with TiPtNi alloys. TiPtNi alloys thermal behaviour was improved by solution heat treatment.
Effects of energy density on the microstructure evolution of TiC/Ti6Al4V-ELI metal composite fabricated with laser metal deposition
(2022-11) Ramasobane, P; Mashinini, MP; Masina, Bathusile N
This study investigated the microstructural evolution of Ti6Al4V-ELI reinforced with TiC, fabricated via in-situ laser metal deposition technique. The 3.85% volume fraction TiC/Ti6Al4V-ELI metal composite samples were fabricated at two different energy densities (ED). It was observed that in-situ reaction resulted in various morphologies (unmelted or partially melted, chain-shaped eutectic, granular eutectic, granular primary eutectic, and dendritic primary) of TiC embedded with the beta grain boundary and the acicular alpha prime matrix. The size of dendritic structures decreases with respect to ED. Additionally, the hardness average of 457.59 ± 39.73 and 455.08 ± 18.03 HV0.3 for 96 and 102 J/mm2 ED respectively.
Effects of laser shock peening on the mechanisms of fatigue short crack initiation and propagation of AA7075-T651
(2020-11) Sanchez, AG; You, C; Leering, M; Glaser, Daniel; Furfari, D; Fitzpatrick, ME; Wharton, J; Reed, PAS
A laser shock peening (LSP) treatment was performed on AA7075-T651 for maximum fatigue improvement. Surface and microstructural characterisation techniques (micro-hardness, SEM-EBSD, contact-profilometry) showed LSP surface modification was limited, and LSP generated deep compressive residual stresses above - 300 MPa. Fatigue testing showed a two-order magnitude increase in overall life, due to the mechanism of crack initiation changing from surface second-phase particles to subsurface crack initiation dependent on the local stress field. Modelling highlights the sensitive balance between surface roughness (including LSP-induced pits) and residual stress on the micro-mechanism of crack initiation, and how this can be used to maximise fatigue life extension.

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