Design and Development of Signal Isolation and Enhancement Solution for Machine Health Monitoring

Wong, Jun Qi Yuki (2026) Design and Development of Signal Isolation and Enhancement Solution for Machine Health Monitoring. Final Year Project (Diploma), Tunku Abdul Rahman University of Management and Technology.

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Abstract

In industrial environments, early detection of machine faults is essential to prevent unexpected failures, reduce maintenance costs, and improve operational safety. However, acoustic-based monitoring systems are often affected by environmental noise, which limits their effectiveness. This project presents the design and development of signal isolation and enhancement solution for machine health monitoring using acoustic signals. The proposed system adopts a hybrid architecture consisting of an ESP32 microcontroller for real-time audio acquisition and a computer-based processing unit for advanced signal analysis. A MAX9814 microphone module is used to capture sound signals from machinery, which are then processed using an Infinite Impulse Response (IIR) filter to reduce unwanted noise and enhance relevant frequency components. A frequency-domain analysis is performed using Fast Fourier Transform (FFT) to identify dominant frequency components associated with machine operation, while Signal-to-Noise Ratio (SNR) is used as a quantitative metric to evaluate the effectiveness of the noise suppression technique. Experimental results demonstrate that the implemented filtering approach improves signal clarity and enhances the detection of characteristic frequency components. The system provides a cost-effective solution suitable for small-scale industrial applications and serves as a foundation for further development in predictive maintenance systems