Optical imaging acquisition for wear particle identification in lubricating oil: A review

The analysis of wear particles in lubricating oil is critical for assessing machine condition. While existing reviews have covered various sensing methods, none have systematically examined how optical imaging acquisition parameters influence particle identification accuracy. This review, based on a search of 135 articles (2000–2025) using Web of Science with three thematic keyword groups, classifies optical imaging techniques into four categories: optical microscopy, ferrography-based imaging, direct optical imaging, and specialized optical imaging. Quantitative comparison reveals fundamental trade-offs in resolution, throughput, capability, and cost. Microscopy and offline ferrography achieve the highest resolution (0.5–15 µm) but lack real-time capability. Direct optical sensors enable inline detection with throughput up to 13–150 ml/min but suffer from motion blur and require substantial post-processing. Unlike previous reviews, this review provides a systematic quantitative framework linking acquisition parameters to identification accuracy, enabling informed technique selection based on application priorities.