Robot arm damage detection using vibration data and deep learning

The life prediction of robotic arm components is an important basis for equipment maintenance and production plan optimization. The current existing prediction models have a single data source, making it difficult to achieve reliable and comprehensive prediction of their operating status. In order to improve prediction accuracy and ensure the smooth progress of production work, this article combines sensor data fusion to study the life prediction of robotic arm components. In this article, the arm component is taken as the object, and based on sensor data collection, multi-source data is fused. A prediction model is constructed using support vector machine (SVM). To verify the effectiveness of the model, this article conducts experimental analysis from two aspects: feature recognition and prediction accuracy. In accuracy analysis, compared to artificial neural network (ANN) and convolutional neural network (CNN), the average prediction accuracy of our method has been improved by 11.5% and 12.2%, respectively. The conclusion indicates that the life prediction of robotic arm components based on sensor data fusion has good accuracy results and can provide objective reference for production technology.

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Soft Robot Design, Manufacturing, and Operation Challenges: A Review

Ambaye,

Boldsaikhan,

Krishnan

2024

JMMP

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Advancements in smart manufacturing have embraced the adoption of soft robots for improved productivity, flexibility, and automation as well as safety in smart factories. Hence, soft robotics is seeing a significant surge in popularity by garnering considerable attention from researchers and practitioners. Bionic soft robots, which are composed of compliant materials like silicones, offer compelling solutions to manipulating delicate objects, operating in unstructured environments, and facilitating safe human–robot interactions. However, despite their numerous advantages, there are some fundamental challenges to overcome, which particularly concern motion precision and stiffness compliance in performing physical tasks that involve external forces. In this regard, enhancing the operation performance of soft robots necessitates intricate, complex structural designs, compliant multifunctional materials, and proper manufacturing methods. The objective of this literature review is to chronicle a comprehensive overview of soft robot design, manufacturing, and operation challenges in conjunction with recent advancements and future research directions for addressing these technical challenges.

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Robot arm damage detection using vibration data and deep learning

Cited by 3 publications

References 46 publications

A Novel Method Based on Stepwise Variational Modal Decomposition and Gramian Angular Difference Field for Bearing Health Monitoring

A Novel Method Based on Stepwise Variational Modal Decomposition and Gramian Angular Difference Field for Bearing Health Monitoring

Predicting the lifespan of robotic arm components based on sensor data fusion

Soft Robot Design, Manufacturing, and Operation Challenges: A Review

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