A5045852434- Anomaly Detection Techniques and Applications
- Lower Extremity Biomechanics and Pathologies
- Health and Wellbeing Research
- Fault Detection and Control Systems
- Education and Learning Interventions
- Muscle activation and electromyography studies
- Autonomous Vehicle Technology and Safety
- Smart Agriculture and AI
- Stroke Rehabilitation and Recovery
- Balance, Gait, and Falls Prevention
- Occupational Health and Safety Research
Korea Institute of Industrial Technology
2023
Kyungpook National University
2023
This paper proposes fault diagnosis methods aimed at proactively preventing potential safety issues in robot systems, particularly human coexistence robots (HCRs) used industrial environments. The data were collected from durability tests of the driving module for HCRs, gathering time-series vibration until failed. In this study, to apply classification absence post-failure data, initial 50% designated as normal section, and 10 h immediately preceding failure selected section. To generate...
The objective of this study was to propose the method detect failure in driving module collaborative robots (cobots). We used three image generation algorithms and four convolutional neural network (CNN) models failures compared performance using time-series vibration data acquired from durability test for cobots. recurrence plot, Gramian angular field, spectrogram as applied AlexNet, GoogleNet, ResNet, DenseNet CNN models. generated images data, input, we failures. Subsequently, detection...
Trampolines are recognized as a valuable tool in exercise and rehabilitation due to their unique properties like elasticity, rebound force, low-impact exercise, enhancement of posture, balance, cardiopulmonary function. To quantitatively assess the effects trampoline exercises, it is essential estimate factors such stiffness, elements influencing jump dynamics, user safety. Previous studies assessing characteristics had limitations performing repetitive experiments at various locations on...