International Journal of Advanced Mechatronic Systems (5 papers in press)

Regular Issues

• InsuDet: a lightweight insulator defect detection algorithm based on YOLOv8  
  by Jinqing Shen, Hong Ye, Chunjun Tang, Yifu Chen, Yan He, Enhui Zheng 
  Abstract: Failures caused by insulator defects may seriously threaten the normal operation of power systems. Hence, how to detect and maintain insulator defects in a timely and accurate manner is of vital importance. However, the small size of insulator shells coupled with complex backgrounds make such detection an arduous task. To address the issue of low accuracy in detecting insulator defects, this paper proposes InsuDet, an improved lightweight object detection network based on YOLOv8. In order to further reduce the complexity of the model, MobileNetv3 blocks are chosen as the backbone of the model in this paper. Additionally, the bottleneck structure in C2f is replaced with deformable convolution structure and small object detection layers are introduced to enhance the feature-extraction performance of the model, improving its ability to identify dense small objects. Our experimental results show that compared to the YOLOv8-s baseline model, our model has increased precision and recall rates by 2.5% and 1.8%, respectively, reflecting at 96.8% and 95.5%, correspondingly. Furthermore, our proposed model reduces the number of parameters by 21%, and achieves a detection speed of 111.6 frames/second. Our model can accurately and timely detect insulator defects, while its lightweight structure ensures that it can be effortlessly deployed on mobile devices like unmanned aerial vehicles.
  Keywords: YOLOv8 network; insulator defect detection; aerial inspection images; image processing.
  
  
• Artificial neural network-based fault detection and identification in a seven-level fault-tolerant inverter  
  by Aquib Mehdi Naqvi, Pushkar Tripathi, S.P. Singh 
  Abstract: The advantages of multilevel inverters (MLIs) have led to their widespread use in various applications. However, the numerous semiconductor switches in MLIs pose reliability challenges. Researchers have developed fault-tolerant (FT) topologies and operational methods to ensure uninterrupted power supply. Detecting and identifying faults is essential for corrective measures and FT operation. This paper presents an artificial neural network (ANN)-based fault detection and identification method for a seven-level inverter. The MLI possesses high redundancy in switching states, which helps to maintain output voltage during open circuit switch faults. A five-layer ANN is trained with data of total harmonic distortion (THD) and average output voltage under different fault conditions and loads. Identifying the faulty switch allows for adjustments to the switching sequence and angles, ensuring operational continuity and optimal voltage levels. Validation of the fault detection and identification method is confirmed through simulation results.
  Keywords: multilevel inverter; MLI; total harmonic distortion; THD; fault-tolerant; voltage level; neural network; switches.
  
  

Special Issue on: Intelligent Mechatronic Systems and Robotics in Sustainable Development

• Electrostatic discharge test automation using Staubli TX2-90 robot  
  by S. Abhishek, Gokul Jagadish, Shibu Krishnan, Amal Prakash, Arjun R. Nair 
  Abstract: Electrostatic discharge (ESD) testing is a type of EMC immunity test used to make sure that products like actuators, sensors and controllers will continue to function normally in the presence of an electrostatic events rapid release of energy. Growing miniaturisation requires comprehensive product standards. Multi-pin connectors with close arrangements demand meticulous ESD testing. Each pin undergoes multiple discharges, polarities, voltage levels, and RC networks, making manual testing error-prone and time-consuming. Automatic testing offers precise execution, repeatability, and efficiency. Using the Staubli TX2-90 robot with 6 DOF and an ESD simulator gun as the end effector, we developed VAL3 program with SRS software. This allows us to control the robot and simulator. An HMI screen on the teach pendant inputs test parameters and initiates the test, streamlining the entire process. Automatic ESD testing not only ensures quality but also saves significant time and effort in compliance testing for electronic devices.
  Keywords: electrostatic discharge; ESD; Staubli; VAL3; DUT; Staubli robotics suite; SRS; human machine interface; HMI.
  
  
• Enhancing recycling efficiency: a SCARA robot and CNN model for waste segregation  
  by Gokul Jagadish, S. Abhishek, Amal Prakash, Arjun R. Nair 
  Abstract: The development of waste sorting robots, particularly the SCARA robot, has shown promising results in automating the recycling process. By utilising convolutional neural networks (CNNs) for image classification, the SCARA robot can accurately differentiate between recyclable and non-recyclable materials. This technology has the potential to significantly improve waste management practices, enhancing efficiency and accuracy in waste segregation. Future research could focus on integrating additional sensors and implementing advanced algorithms to further optimise the sorting process. Additionally, exploring the potential of deep learning techniques to classify a broader range of refuse materials could further enhance the performance of waste sorting systems. The SCARA robot’s design, which includes a four-DOF base and the use of 3D printing technology, has been carefully analysed and chosen for optimum output and manufacturing simplicity, contributing to its reliability and durability.
  Keywords: SCARA; waste-sorting; CNN; recycling; deep learning.
  
  
• Development of a low cost structured light 3D reconstruction system  
  by G. Karthikeyan, G. Senthilnathan 
  Abstract: 3D reconstruction using structured light scanning has emerged as an indispensable component within the workflows of numerous engineering fields. Structured light scanning has revolutionised design, analysis, and fabrication processes with its ability to capture detailed surface information and produce high-resolution three-dimensional models. By projecting a known pattern of light onto a subject and analysing the distortions caused by its interaction with the surface, this technique enables the precise reconstruction of complex geometries, allowing engineers to visualise, measure, and manipulate objects with unparalleled accuracy. This paper discusses the development of a low-cost and robust structured light scanning system and evaluates its performance based on vertex quality histogram using Hausdorff distance. It also provides an overview of the basic principles of structured light scanning, emphasising the procedure to achieve good calibration results. Its transformative impact on industries such as manufacturing, architecture, medical imaging, and robotics has enhanced the overall process involved. As structured light scanning continues to evolve and adapt to the ever-changing demands of modern engineering, it is poised to further shape the future of design, analysis, and innovation in various industries.
  Keywords: structured light scanning; 3D reconstruction; projector-camera calibration.