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

• Main Author: Navea, Roy Francis R.
• Format: text
• Language: English
• Published: Animo Repository 2012
• Online Access: https://animorepository.dlsu.edu.ph/etd_masteral/4295
• Institution: De La Salle University

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.