MFD: Multi-object Frequency Feature Recognition and State Detection Based on RFID-single Tag
Citations Over TimeTop 20% of 2023 papers
Abstract
Vibration is a normal reaction that occurs during the operation of machinery and is very common in industrial systems. How to turn fine-grained vibration perception into visualization, and further predict mechanical failures and reduce property losses based on visual vibration information, which has aroused our thinking. In this article, the phase information generated by the tag is processed and analyzed, and MFD is proposed, a real-time vibration monitoring and fault-sensing discrimination system. MFD extracts phase information from the original RF signal and converts it into a Markov transition map by introducing White Gaussian Noise and a low-pass filter for denoising. To accurately predict the failure of machinery, a deep and machine learning model is introduced to calculate the accuracy of failure analysis, realizing real-time monitoring and fault judgment. The test results show that the average recognition accuracy of vibration can reach 96.07%, and the average recognition accuracy of forward rotation, reverse rotation, oil spill, and screw loosening of motor equipment during long-term operation can reach 98.53%, 99.44%, 97.87%, and 99.91%, respectively, with high robustness.
Related Papers
- → Views on Visualization(2006)124 cited
- → Discussion on the Application of Visualization Technology in Modeling and Simulation(2011)5 cited
- → ‘Visualization’ for Decision Aids(2009)
- → Selecting Visualization Web Services Based on Visualization Characteristics(2013)
- Visualization and New Product Evaluation: the Role of Memory- and Imagination-Focused Visualization(2007)