Event Classification from Sensor Data using Spectral Analysis in Robotic Finishing Processes

Bobby K. Pappachan, Tegoeh Tjahjowidodo, Tomi WIjaya

2017

Abstract

Process monitoring using indirect methods leverages on the usage of sensors. Using sensors to acquire vital process related information also presents itself with the problem of big data management and analysis. Due to uncertainty in the frequency of events occurring, a higher sampling rate is often used in real-time monitoring applications to increase the chances of capturing and understanding all possible events related to the process. Advanced signal processing methods helps to further decipher meaningful information from the acquired data. In this research work, power spectrum density (PSD) of sensor data acquired at sampling rates between 40 kHz-51.2 kHz was calculated and the co-relation between PSD and completed number of cycles/passes is presented. Here, the progress in number of cycles/passes is the event this research work intends to classify and the algorithm used to compute PSD is Welchs estimate method. A comparison between Welchs estimate method and statistical methods is also discussed. A clear co-relation was observed using Welchs estimate to classify the number of cyceles/passes.

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Paper Citation


in Harvard Style

Pappachan B., Tjahjowidodo T. and WIjaya T. (2017). Event Classification from Sensor Data using Spectral Analysis in Robotic Finishing Processes . In Proceedings of the 6th International Conference on Sensor Networks - Volume 1: SENSORNETS, ISBN 978-989-758-211-0, pages 80-86. DOI: 10.5220/0006204900800086


in Bibtex Style

@conference{sensornets17,
author={Bobby K. Pappachan and Tegoeh Tjahjowidodo and Tomi WIjaya},
title={Event Classification from Sensor Data using Spectral Analysis in Robotic Finishing Processes},
booktitle={Proceedings of the 6th International Conference on Sensor Networks - Volume 1: SENSORNETS,},
year={2017},
pages={80-86},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006204900800086},
isbn={978-989-758-211-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Sensor Networks - Volume 1: SENSORNETS,
TI - Event Classification from Sensor Data using Spectral Analysis in Robotic Finishing Processes
SN - 978-989-758-211-0
AU - Pappachan B.
AU - Tjahjowidodo T.
AU - WIjaya T.
PY - 2017
SP - 80
EP - 86
DO - 10.5220/0006204900800086