Work

Condition-Based Maintenance Plus (CBM+) for Single-Board Computers: Accelerated Testing and Precursor Signal Identification

Year: 2025

Type: article

Abstract: Condition-Based Maintenance Plus (CBM+) has been widely adopted in aerospace and mechanical systems, but its application to single-board computers (SBCs) remains difficult due to scarce failure data and subtle degradation signatures. This study investigates CBM+ for the MVME6100 SBC using accelerated life testing (ALT) to generate degradation trajectories and capture precursor signals. Temperature–humidity cycling and vibration tests were performed, while CPU temperature, memory temperature, and output voltage were continuously monitored. Under stable operation, signals followed ambient variations and showed little statistical drift, making degradation visually indistinguishable. However, precursors emerged before failure: CPU temperature exhibited abnormal behavior during thermal cycling, while vibration stress induced communication noise and irregular thermal behavior. These findings indicate that thermal responses provide reliable precursors for electronic degradation. To evaluate data-driven detection, two neural approaches were applied: an Autoencoder (AE) trained only on normal data and a Long Short-Term Memory (LSTM) network trained on both normal and faulty datasets. The Autoencoder reliably detected anomalies via reconstruction error, while the LSTM accurately classified health states and reproduced lifecycle progression. Together, the results demonstrate that precursor-informed CBM+ is feasible for SBCs and that a hybrid AE–LSTM framework enhances prognostics and health management in mission-critical electronics.

Source: Applied Sciences

DOI: 10.3390/app152011203

Authors: Gwang-Hyeon Mun, Youngchul Kim, Youngmin Park, Dong-Won Jang

Institution: Myongji University

Language: English

Topic: Reliability and Maintenance Optimization

Subfield: Safety, Risk, Reliability and Quality

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,896

Funders: Korea Research Institute for Defense Technology Planning and Advancement, Defense Acquisition Program Administration