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MULTIDOMAIN WAVEFORM ANALYSIS FOR SOH-PROXY DEVELOPMENT IN SEISMIC DIGITIZERS BASED ON MINISEED DATA USING ANOMALY DETECTION AND PROXY-PPSD Universitas Indonesia Abstract Seismic digitizers generally do not provide internal telemetry for continuous monitoring of instrumental health conditions. As a result, degradation is often identified only after waveform quality deteriorates or instrument failure occurs. This study proposes DigiHealth, a passive waveform-based predictive maintenance framework that utilizes MiniSEED data to construct a State of Health Proxy (SOH-Proxy) for seismic digitizers without requiring additional sensors or hardware telemetry. The framework performs waveform preprocessing, temporal segmentation, multidomain feature extraction, and anomaly detection using a robust Median Absolute Deviation (MAD) approach. Spectral stability is evaluated using a Proxy-Probabilistic Power Spectral Density (Proxy-PPSD) representation derived from waveform behavior. The anomaly score is then transformed into a continuous SOH-Proxy index to represent instrumental degradation. Experimental results at station SWCM-SHZ show that anomaly scores increased progressively before digitizer replacement, followed by a significant decrease in SOH-Proxy values toward critical conditions. After replacement, anomaly scores decreased while SOH-Proxy values increased, indicating recovery of instrumental stability. The proposed framework also distinguishes no-data conditions from actual instrument failure without replacing waveform gaps with artificial zero values. These results demonstrate that MiniSEED waveform data can be utilized not only for seismic-event analysis but also as passive indicators of digitizer health to support predictive maintenance in seismic monitoring networks. Keywords: MiniSEED, SOH-Proxy, Predictive Maintenance, Proxy-PPSD, Seismic Digitizer, Anomaly DetectionPlease Just Try to Submit This Sample Abstract Topic: Instrumentation and Computational Physics |
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