1. Frequency Domain Analysis of Sensor Data for Event Classification in Real-Time Robot Assisted Deburring
- Author
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Bobby K. Pappachan, Tegoeh Tjahjowidodo, Tomi Wijaya, Wahyu Caesarendra, School of Mechanical and Aerospace Engineering, and Rolls-Royce@NTU Corporate Lab
- Subjects
0209 industrial biotechnology ,Engineering ,Technology ,02 engineering and technology ,computer.software_genre ,lcsh:Chemical technology ,Biochemistry ,Signal ,Article ,Analytical Chemistry ,020901 industrial engineering & automation ,machining ,deburring ,Welch’s estimate ,Sampling (signal processing) ,Welch's estimate ,0202 electrical engineering, electronic engineering, information engineering ,lcsh:TP1-1185 ,Electrical and Electronic Engineering ,Instrumentation ,Instruments & Instrumentation ,Signal processing ,Science & Technology ,Event (computing) ,business.industry ,Chemistry, Analytical ,Process (computing) ,Spectral density ,Engineering, Electrical & Electronic ,Atomic and Molecular Physics, and Optics ,Vibration ,MODEL ,Chemistry ,Frequency domain ,Physical Sciences ,020201 artificial intelligence & image processing ,Data mining ,business ,computer - Abstract
Process monitoring using indirect methods relies 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 are used 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 40-51.2 kHz was calculated and the corelation 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 Welch's estimate method. A comparison between Welch's estimate method and statistical methods is also discussed. A clear co-relation was observed using Welch's estimate to classify the number of cycles/passes. The paper also succeeds in classifying vibration signal generated by the spindle from the vibration signal acquired during finishing process. ispartof: SENSORS vol:17 issue:6 ispartof: location:Switzerland status: published
- Published
- 2017