| URN | etd-0124125-035529 | Statistics | This thesis had been viewed 15 times. Download 0 times. |
| Author | YU-CHING WU | ||
| Author's Email Address | No Public. | ||
| Department | Institute of Electrical Engineering | ||
| Year | 2024 | Semester | 1 |
| Degree | Master | Type of Document | Master's Thesis |
| Language | zh-TW.Big5 Chinese | Page Count | 56 |
| Title | Development of an Audio Acquisition System for Vehicle Fault Detection Utilizing the Raspberry Pi Platform | ||
| Keyword | |||
| Abstract | Abstract This thesis explores an audio acquisition system based on the Raspberry Pi plat-form, aimed at improving the traditional method of vehicle fault detection that relies on human auditory perception. Traditional vehicle fault detection methods primarily depend on the auditory experience of technicians, which is subjective and easily influenced by environmental noise. To address this issue, this study designs and implements an audio acquisition system based on the Raspberry Pi platform. This system can automatically collect and analyze audio data during vehicle operation, providing more accurate fault diagnosis. The hardware part of the system mainly consists of the Raspberry Pi, a mi-crophone module, and related audio processing circuits. The Raspberry Pi serves as the core processing unit, responsible for collecting, processing, and transmit-ting audio data. The microphone module captures various sound signals gener-ated during vehicle operation. The audio processing circuit amplifies and filters the captured sound signals to improve the quality and accuracy of the signals. In the software part, an integrated development environment is used to write and debug the code, and audio editing software is used to analyze the audio files. Experimental results demonstrate that the system has high accuracy and reliability in vehicle fault detection, effectively assisting technicians in fault diagnosis and reducing errors and omissions in human auditory judgment. In conclusion, the audio acquisition system based on the Raspberry Pi platform provides a new technical means for vehicle fault detection, with broad application prospects and practical value. |
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| Files | indicate access worldwide | ||
| Date of Defense | 2025-01-08 | Date of Submission | 2025-01-24 |