Abstract
The application of signal processing techniques, specifically the Fourier series and Fast Fourier Transform (FFT), in the context of modern industrial systems, with a focus on seismic data analysis is considered. The study begins by investigating the role of vibration sensors in capturing seismic activity, particularly within water cooling systems, where accurate monitoring is crucial for maintaining operational stability and safety. Given the limitations of current SCADA systems in handling such complex data, a novel approach is proposed, wherein seismic signals captured by vibration sensors are transformed using FFT to reveal their frequency components. The results of this study, illustrated through the FFT of seismic data, uncover the hidden frequency components that characterize seismic events. These findings provide critical insights into the patterns and behaviors of seismic activity, offering a robust foundation for enhanced monitoring and predictive maintenance in industrial environments. This paper not only demonstrates the efficacy of FFT in signal processing but also highlights the potential for integrating advanced algorithms and tools into SCADA systems, paving the way for more sophisticated and responsive industrial control systems. Keywords: Seismic Data Analysis, Fast Fourier Transform (FFT), Vibration Sensors, Siemens PLC, Signal Processing.
Published Version
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