Design and implementation of an acoustic-based car engine fault diagnostic system in the android platform

Date of Publication


Document Type

Master's Thesis

Degree Name

Master of Science in Electronics and Communications Engineering


Gokongwei College of Engineering


Electronics And Communications Engg

Thesis Adviser

Edwin Sybingco

Defense Panel Chair

Cesar A. Llorente

Defense Panel Member

Reggie C. Gustilo
Melvin K. Cabatuan
Rosemary R. Seva


This study aims to design and implement an acoustic-based car engine fault diagnostic system in the Android platform.

A smart phone running the Adroid operating system is used in order to analyze sounds coming from the car engine. Fault diagnosis covers engine start problem detection, drive-belt analysis and tune-up detection based on valve clearance. The system is equipped with signal processing algorithms that process the sounds obtained to come up with a diagnostic result and further recommend some possible solutions. The algorithm is based on the correlation coefficient of the spectral power densities (SPD), collected using two distinct clustering techniques, of the audio signals which are fed into a fuzzy logic inference system.

The system design and implementation was made successful in a smart phone running in the Android platform. Results show that the system was able to diagnose the engine not just in a single brand of car models.

Abstract Format






Accession Number


Shelf Location

Archives, The Learning Commons, 12F Henry Sy Sr. Hall

Physical Description

xi, 91 p. ; ill. ; 28 cm. + 1 computer optical disc ; 4 3/4 in.

This document is currently not available here.