Oil Debris Monitoring Patents: Leaders, Trends & White Space 2026
A data-driven look at lubricating-oil wear debris monitoring patents: filing trends, technology composition, leading assignees and open claim space, based on 320 records filed 2015-2026.
Filing growth = 2021 (13 records) → 2024 (1); 2024 is the last year we treat as complete. Top-5 share = the 5 largest assignees ÷ all 320 records in scope (CR5), not the ranked leaders only.
What this landscape covers
This landscape maps 320 patent records filed between 2015 and 2026 around oil debris monitoring, wear particle detection and related sensing methods for lubricated rotating machinery — turbines, gearboxes, bearings and engines. The scope pulls together art tagged under material analysis, lubrication systems and turbine testing, so a single record can carry claims that span several of those subclasses at once. Patent families, not raw document counts, are the fairer way to read concentration here, since they neutralise repeat filings from the same applicant chasing continuation or multi-jurisdiction coverage.
Filing activity is not evenly spread: a small number of assignees hold a disproportionate share of the record set, and the technology composition skews heavily toward general material-analysis methods rather than debris-specific sensing hardware. The sections below break down where the volume sits, who filed it, and which branches remain comparatively open.
Filing trends and technology composition
Two views of the same 320-record set: how filing volume has moved year on year, and which IPC subclasses carry the claim weight.
A filing peak already behind us
Annual filings rose from 17 in 2017 to a peak of 31 in 2020, then declined sharply — 13 filings in 2021 down to 1 in 2024, a -92% move over that span. 2025 and 2026 figures are still filling in under normal publication lag and should not be read as a continued drop.
Publication lags filing by roughly 18 months, so 2025 onwards are still filling in. Growth rates on this page therefore end at 2024; running them to the last bar would understate the field.
Material analysis dominates the class mix
G01N (material analysis & testing) appears in 49.1% of the 320 records, more than double the next subclass, F16N (lubrication systems) at 17.8%. Engine lubrication (F01M), turbine testing (F01D) and machine testing (G01M) each sit in the 10-13% band, with bearing-specific claims under F16C narrower still at 6.3%. Because records can carry multiple classes, these shares are read against the full 320-record base, not against each other.
Shares are the percentage of the 320 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Tribology & Lubrication: Lubricating-Oil Wear Debris Monitoring Patent Landscape with Eureka
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Try EurekaRepresentative filing and most-cited prior art
US20180107203A1 — Oil debris monitoring (ODM) with adaptive learning
A system and method for debris particle detection with adaptive learning: it receives oil debris monitoring sensor data alongside fleet data, detects a feature in that sensor data, generates an anomaly signal by comparing the feature against a limit drawn from stored fleet information, selects a maintenance action, and then adjusts the feature, the anomaly threshold, the limit or the maintenance request through an adaptive learning algorithm applied to the ODM data stream.Filed by RTX Corporation, published 2018-04-19.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US5982847A | Compact X-ray fluorescence spectrometer for real-time wear metal analysis of lubrucating oils | 166 |
| 2 | EP0407179A1 | Aircraft health and usage monitoring systems | 163 |
| 3 | US20020057152A1 | Electronically controlled rotary fluid-knob as a haptical control element | 135 |
| 4 | US20070277613A1 | Method And Device For Assessing Residual Service Life Of Rolling Bearing | 123 |
| 5 | US5194910A | Use of optical spectrometry to evaluate the condition of used motor oil | 117 |
| 6 | US6706071B1 | Prosthetic hip joint assembly | 107 |
| 7 | US6571886B1 | Method and apparatus for monitoring and recording of the operating condition of a downhole drill bit during d… | 100 |
| 8 | US20100109686A1 | Metal wear detection apparatus and method employing microfluidic electronic device | 97 |
| 9 | WO2017055788A1 | Shape memory alloy actuator arrangement | 80 |
| 10 | US4219805A | Lubricating oil debris monitoring system | 75 |
Citation counts favour older filings that have had more time to accumulate citations inside the searched corpus — read them as a signal of influence on the field, not of current commercial relevance.
Each row carries its publication number; clicking a row searches Eureka by that number.
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Four read-outs from the record set that matter for a filing or freedom-to-operate decision.
Top 5 hold over a third of the field
The five leading assignees account for 116 of the 320 records in scope, 36.3% of the total. The single leader alone holds 60 records — roughly half of that top-5 total — which points to one dominant filer rather than a tight cluster of equals.
Volume peaked in 2020 and has since cooled
Annual filings fell from 13 in 2021 to 1 in 2024, a -92% move across the last three years that can be read as complete. The 2020 peak of 31 filings marks the high point of activity so far; 2025-2026 counts are still incomplete under normal publication lag.
General material analysis, not debris-specific sensors, carries the weight
Nearly half the record set sits under G01N (material analysis & testing), well ahead of F16N lubrication systems at 17.8% and F01M engine lubrication at 12.5%. That skew suggests much of the claim space is written around analytical method rather than dedicated debris-sensor hardware.
Filing is US-led with a solid European second tier
The United States receives the largest single share of filings at 114 records, with the EPO route at 58 and China at 32. Germany and the United Kingdom each sit in the mid-teens, indicating the field is prosecuted mainly through US and European offices rather than concentrated in one regional system.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to tribology & lubrication: lubricating-oil wear debris monitoring patent landscape, with the prior art for and against each one.
| Assignee | Co-assignee | Shared families |
|---|---|---|
| The Chugoku Electric Power Co., Inc. | IWATSUBO TAKUZO | 11 |
| Siemens AG | GRAM & JUHL | 11 |
| The Chugoku Electric Power Co., Inc. | Xinchuan Sensing Science & Technology Co., Ltd. | 2 |
| The Chugoku Electric Power Co., Inc. | NTN Corporation | 2 |
| IWATSUBO TAKUZO | Xinchuan Sensing Science & Technology Co., Ltd. | 2 |
| IWATSUBO TAKUZO | NTN Corporation | 2 |
| The Chugoku Electric Power Co., Inc. | IWATSUBO TAKUZO SUITA SHI | 1 |
Only 7 co-assignee pairs appear in the dataset, and the strongest pairings recur at low double-digit counts — a sign that most of this field is filed by single owners rather than through joint development arrangements.
Where to take this analysis
The record set points to a field with a dominant filer, a shrinking recent filing rate, and claim space still weighted toward general analytical method rather than dedicated sensor hardware.
Check freedom-to-operate against the leading assignee
With one assignee holding 60 of 320 records, any new filing in adaptive-learning debris detection or fleet-data comparison should be checked against that portfolio first.
Explore assignee portfolios in EurekaProbe the under-claimed branches
Bearing-specific sensing (F16C, 6.3%) and electric/magnetic measurement methods (G01R, 4.7%) carry far fewer records than material analysis — worth a closer look before assuming the space is closed.
Run a white-space search in EurekaCommon questions on this landscape
The dataset's assignee ranking is led by a single company holding 60 of the 320 records in scope, well ahead of the rest of the field. The top 5 ranked assignees combined account for 36.3% of all 320 records, meaning a large share of filing activity is concentrated among a small number of owners. Anyone entering this space should review the leader's portfolio specifically, rather than assuming the field is evenly split across many players.
Filing volume peaked in 2020 at 31 records and has fallen sharply since, with annual filings dropping from 13 in 2021 to 1 in 2024 — a -92% move over that span. 2024 is the most recent year that publication lag allows to be read as complete; 2025 and 2026 figures will keep filling in and should not yet be read as a continued decline. Overall the pattern points to a field past its filing peak rather than one still accelerating.
Material analysis and testing methods, classified under G01N, appear in 49.1% of the 320 records, making it by far the largest single technology bucket. Lubrication systems (F16N, 17.8%) and engine lubrication (F01M, 12.5%) follow at much lower shares. Because a single patent can carry several IPC classes, these percentages overlap rather than sum to 100%, but the gap between G01N and everything else is consistent and wide.
The United States receives the largest share of filings at 114 records, followed by the European Patent Office at 58 and China at 32, with Germany and the United Kingdom each in the mid-teens. This distribution suggests prosecution is centred on US and European offices rather than any single regional system, which matters for anyone planning where to file or watch for competing applications.
US20180107203A1, filed by RTX Corporation and published in 2018, covers an oil debris monitoring system that uses adaptive learning: it compares sensor-detected features against fleet-data-derived limits, raises an anomaly signal, and adjusts its own thresholds and maintenance recommendations over time. It is treated here as a representative record because it captures the shift from static threshold detection toward fleet-informed, self-adjusting anomaly detection. Anyone building a comparable adaptive-learning maintenance trigger should review its claims closely before designing a similar feature-comparison loop.
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Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, or validity search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. Any patent, commercial, or strategic decision should be verified independently and reviewed with qualified patent, legal, and domain professionals. Patsnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.
Machine translation. Assignee and organisation names originally recorded in Chinese, Japanese or Korean have been rendered into English by an AI translation step so that the tables stay readable. These renderings are best-effort and may not match a company’s registered English name; the original name is what the underlying patent record carries, and it is what any Eureka query launched from this page uses.