East Tennessee State University Digital Commons @ East Tennessee State University Electronic Theses and Dissertations Student Works 12-2005 Monitoring PC Hardware Sounds in Linux Systems Using the Daubechies D4 Wavelet. Robert Karns Henry East Tennessee State University Follow this and additional works at: https://dc.etsu.edu/etd Part of the Computer Sciences Commons Recommended Citation Henry, Robert Karns, "Monitoring PC Hardware Sounds in Linux Systems Using the Daubechies D4 Wavelet." (2005). Electronic Theses and Dissertations. Paper 1076. https://dc.etsu.edu/etd/1076 This Thesis - Open Access is brought to you for free and open access by the Student Works at Digital Commons @ East Tennessee State University. It has been accepted for inclusion in Electronic Theses and Dissertations by an authorized administrator of Digital Commons @ East Tennessee State University. For more information, please contact [email protected]. Monitoring PC Hardware Sounds in Linux Systems Using the Daubechies D4 Wavelet A thesis presented to the faculty of the Department of Computer Science East Tennessee State University In partial fulfillment of the requirements for the degree Master in Applied Computer Science by Robert K. Henry December, 2005 David Tarnoff, Chair Phillip Pfeiffer Jeff Knisley Keywords: Wavelet, Daubechies, DSP, Monitor, S.M.A.R.T., ALSA, Linux, failure prediction, remote, vibration analysis ABSTRACT Monitoring PC Hardware Sounds in Linux Systems Using the Daubechies D4 Wavelet by Robert K. Henry Users of high availability (HA) computing require systems that run continuously, with little or no downtime. Modern PCs address HA needs by monitoring operating system parameters such as voltage, temperature, and hard drive status in order to anticipate possible system failure. However, one modality for PC monitoring that has been underutilized is sound. The application described here uses wavelet theory to analyze sounds produced by PC hard drives during standard operation. When twenty-nine hard drives were tested with the application and the results compared with the drives’ Self-Monitoring, Analysis, and Reporting Technology (S.M.A.R.T.) data, the binomial distribution’s low p-value of 0.012 indicated better than chance agreement. While the concurrence between the two systems shows that sound is an effective tool in detecting hardware failures, the disagreements between the systems show that the application can complement S.M.A.R.T. in an HA system. 2 COPYRIGHT Copyright 2005 by Robert K. Henry All Rights Reserved 3 ACKNOWLEDGEMENTS Thank you to the members of the thesis committee for your time and guidance in this research. Thank you to Dr. Terry Countermine, David Robinson, and the East Tennessee State University seniors who worked so diligently in the ETSU “Providing Area Schools with Technical Assistance” (PASTA) program for providing hard drives for testing. Your time and conscientious effort in collecting the hardware components helped make this research possible. Thank you, Dr. Edith Seier, Department of Mathematics, ETSU, for your statistical consultation. Your advice has been helpful in designing the project and in evaluating the system. Thank you, Professor Penny Smith, Department of Math, Lehigh University, for your friendship, mathematical advice on wavelets, and your encouragement, without which this project would never have begun. Thank you to Terri Henry Briggs, my sister. Your donation of the computer for developing the Linux software was helpful in advancing the project. Thank you to Jo Watson Henry, my mother, for your help in proofreading. Thank you to the ALSA Development Team for help on ALSA through articles on the ALSA website and the ALSA mail list. 4 CONTENTS Page ABSTRACT..................................................................................................................................... 2 COPYRIGHT................................................................................................................................... 3 ACKNOWLEDGEMENTS............................................................................................................. 4 CONTENTS..................................................................................................................................... 5 LIST OF TABLES........................................................................................................................... 9 LIST OF FIGURES ....................................................................................................................... 10 Chapter Page 1. INTRODUCTION ..................................................................................................................... 11 1.1 Motivation for Research ...................................................................................................... 11 1.2 Results.................................................................................................................................. 12 1.3 Overview of Thesis.............................................................................................................. 14 2. BACKGROUND ....................................................................................................................... 15 2.1 Hardware Sensors ................................................................................................................ 15 2.1.1 Basic Sensors ................................................................................................................ 15 2.1.2 Self-Monitoring, Analysis, and Reporting Technology (S.M.A.R.T.) ......................... 16 2.2 Sensing Sound...................................................................................................................... 19 2.2.1 Accelerometers and Microphones................................................................................. 19 2.2.2 Sampling Sounds .......................................................................................................... 20 2.2.3 Sampling Programming Practice .................................................................................. 21 2.3 Analyzing Sounds................................................................................................................ 23 2.3.1 Fourier Transform......................................................................................................... 23 2.3.2 Fast Fourier Transform ................................................................................................. 24 2.3.3 Localizing in Time........................................................................................................ 26 2.3.4 Wavelets........................................................................................................................ 27 5 Chapter Page 2.3.5 Haar Wavelet ................................................................................................................ 28 2.3.6 Daubechies Wavelet...................................................................................................... 30 2.3.7 Multiresolution Analysis and the Fast Wavelet Transform (FWT) .............................. 33 2.3.8 Lifting ........................................................................................................................... 37 2.3.9 Wavelet Packets............................................................................................................ 38 2.4 Classifying Signals .............................................................................................................. 39 2.5 Wavelet Software Solutions................................................................................................. 39 2.6 Summary.............................................................................................................................. 42 3. METHODOLOGY .................................................................................................................... 43 3.1 Software Specification......................................................................................................... 43 3.2 Programming Environment.................................................................................................. 43 3.3 Prototype Development ....................................................................................................... 43 3.4 Filtering................................................................................................................................ 44 3.4.1 Collection of Failed Components ................................................................................. 44 3.4.2 Obtaining Hard Drive Data........................................................................................... 45 3.4.3 Testing of Wavelet Transform Class ............................................................................ 46 3.5 Sound Sampling................................................................................................................... 46 3.6 Classifier .............................................................................................................................. 47 3.7 Limitations........................................................................................................................... 47 3.8 Licensing.............................................................................................................................. 48 3.9 Summary.............................................................................................................................