Rotating Machinery Condition Monitoring Patents: Leaders & Trends 2026
- 37 patent families total, with filing activity flat to declining since a 2024 peak of 9 — this is not a fast-growing claim space.
- China files 26 of 37 families, more than five times the next-largest jurisdiction, concentrating most active claim-writing in one region.
- G06F and G06N together touch 24 records, showing diagnostic software and AI-model claims now ride alongside, not instead of, the sensing hardware.
What this landscape covers
Rotating machinery condition monitoring patents in this corpus center on bearing fault detection methods that read envelope spectrum, defect frequency or acoustic emission signals to flag a trend alarm or estimate remaining useful life. The search scope is narrow by design — it sits inside the G01M13, G01H1 and F16C41 subclasses — so the 37 families here represent a specific slice of diagnostic method claims rather than all bearing or vibration patents generally.
The composition skews toward mechanical fault-detection testing (G01M, present in every record) layered with data-processing and AI-model classifications, indicating that the diagnostic method itself, not just the sensor hardware, is now routinely part of the claim scope.
Filing trends and technology composition
Thirty-seven patent families make up this corpus, filed against a search string tuned to envelope-spectrum, defect-frequency, acoustic-emission and remaining-useful-life claims within the G01M13, G01H1 and F16C41 subclasses.
Filing activity is flat, not growing
Filings sit at zero in 2017, climb to a peak of 9 in 2024, and the 2022 midpoint of 3 confirms the growth curve has been shallow rather than accelerating. Recent-year figures are always understated because publication typically lags filing by around 18 months, so 2025-2026 counts will revise upward as records publish.
G01M dominates, but software subclasses are catching up
Every record in this corpus carries a G01M classification, as expected given the search scope, but G06F (14 records) and G06N (10 records) show that data-processing and AI-model claims now attach to a large share of bearing and rotating-machinery filings — the diagnostic method is increasingly claimed alongside, not instead of, the sensing hardware.
Shares are the percentage of the 37 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Rotating Machinery Condition Monitoring with Eureka
This page is one run against one query. Ask Eureka your own question about rotating machinery condition monitoring and every answer comes back with the patent numbers behind it.
Try EurekaThe records anchoring this landscape
US11714028B2 — System and method for health monitoring of a bearing system
A method of bearing fault detection including measuring a signal of torsional energy transfer from a rotating device to a non-rotating device at a distance away from the rotating device, calculating a health status of the rotating device based on a comparison of the measured signal to a baseline signal, and calculating a remaining useful life of the rotating device.Assigned to Rockwell Collins, Inc.; granted 2023-08-01.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | EP2581725A2 | Methods and systems for automatic rolling-element bearing fault detection | 53 |
| 2 | CN113255437A | 滚动轴承深度卷积稀疏自动编码器故障诊断方法 | 22 |
| 3 | CN104614182A | 一种轴承故障检测方法 | 17 |
| 4 | CN109932179A | 一种基于DS自适应谱重构的滚动轴承故障检测方法 | 14 |
| 5 | CN111272427A | 基于加权稀疏正则的轴承故障检测方法 | 10 |
| 6 | CN114778115A | 一种基于声发射信号的轴承故障检测系统及方法 | 9 |
| 7 | CN113269169A | 一种轴承故障检测方法和装置 | 8 |
| 8 | US20210072116A1 | System and method for health monitoring of a bearing system | 8 |
| 9 | CN103048132A | 用于自动滚动元件轴承故障检测的方法和系统 | 7 |
| 10 | CN116304848A | 一种滚动轴承故障诊断系统及方法 | 5 |
Ranked by citation count within the searched corpus; older grants are structurally favoured, so read this as a map of influence rather than of current filing activity.
Patent titles are shown in the language they were filed in, not translated, so that each record stays verifiable against the original filing — a translated title will not match in Eureka or in any national register. Each row carries its publication number; clicking a row searches Eureka by that number.
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The numbers point to a mature, narrowly-claimed field rather than an emerging one — filing volume is small, geographically concentrated, and increasingly layered with software and AI classifications on top of the same sensing methods.
One foundational reference dominates
EP2581725A2's 53 citations outweigh the next four most-cited records combined, marking envelope-spectrum bearing fault detection as the reference point the rest of the field builds against.
Growth is flat, not accelerating
From zero filings in 2017 to a 2022 midpoint of 3 and a 2024 peak of 9, the trajectory shows a shallow climb rather than sustained growth, and the most recent years are still understated by publication lag.
Software claims now ride with sensing hardware
Nearly two-thirds of the corpus carries a data-processing or AI-model classification alongside the core G01M testing classification, showing diagnostic method claims are increasingly bundled with the underlying sensor or signal-processing hardware.
Filing activity is geographically concentrated
China accounts for the large majority of families in this corpus, with India, Europe, South Korea and the US each contributing a small remainder — freedom-to-operate work outside China is working from a thinner local record.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to rotating machinery condition monitoring, with the prior art for and against each one.
Who holds the ground, and where it's open
With 37 families spread across a handful of active filers and no assignee showing growth in the latest year, this is a field of established positions rather than a race for new ground — the more useful question is which mechanical-integration branches remain thinly claimed.
No assignee is currently accelerating
Every assignee tracked for recent-year momentum, including established filers, shows zero filings in the latest year, with one showing a -100% year-on-year drop. This is consistent with the corpus-wide flat trend rather than a shift away from any single player.
A single European grant anchors the field
The most-cited record in this corpus is a European filing on rolling-element bearing fault detection, not a Chinese one, despite China holding the majority of filing volume — influence and volume sit with different players.
Most active filers are China-based
The bulk of recent filing activity, including several university and research-institute assignees, originates in China, which is where most of the incremental claim-writing in fault-classification methods is happening now.
| Assignee | Recent year | YoY |
|---|---|---|
| Simmonds Precision Products | 0 | — |
| General Electric Company | 0 | — |
| University of Ulsan Foundation for Industry Cooperation | 0 | — |
| Dalian Measurement & Control Technology Research Institute | 0 | — |
| Youji Technology (Shanghai) Co., Ltd. | 0 | -100% |
| Foshan University | 0 | — |
| Angang Group Mining Co., Ltd. | 0 | — |
| Chongqing University of Posts and Telecommunications | 0 | — |
Where to take this analysis
The filing data marks out where claim density is heavy and where it thins out. The next step is turning that into a filing or freedom-to-operate decision specific to your own technical approach.
Map your method against the envelope-spectrum core
If your diagnostic approach touches vibration or defect-frequency analysis, check it against the EP2581725A2 citation lineage before drafting claims in that space.
Run a claim comparison in EurekaCheck the mechanical-integration white space
F02B and F16C branches carry only 2 records each against a 37-family corpus — worth a closer freedom-to-operate look if your work ties diagnostics to specific hardware.
Explore white space in EurekaVerify jurisdiction coverage beyond China
With 26 of 37 families filed in China, confirm whether the families you care about have parallel filings in your target jurisdiction before assuming open space.
Check jurisdiction coverage in EurekaCommon questions about rotating machinery condition monitoring patents
EP2581725A2, covering automatic rolling-element bearing fault detection, carries 53 citations in this corpus, well ahead of any other record. That level of citation reflects its role as a foundational reference for envelope-spectrum-based bearing diagnostics rather than a claim about its current commercial dominance. Citation counts inside any fixed corpus skew toward older filings simply because they have had more years to accumulate references, so treat this as a measure of influence, not of what is being filed today.
China accounts for 26 of the 37 families in this dataset, far ahead of India (4), and Europe, South Korea and the United States (2 each). That concentration suggests most active claim-writing in this specific search scope — envelope spectrum, defect frequency, acoustic emission and remaining-useful-life methods under G01M13/G01H1/F16C41 — is happening in Chinese-language filings, which is worth checking directly if you are clearing freedom-to-operate in that jurisdiction.
Not clearly. The trend across this corpus runs flat to declining rather than climbing: filings were at zero in 2017, reached a midpoint of 3 by 2022, and peaked so far at 9 in 2024. Because publication lags filing by roughly 18 months, the 2025-2026 figures will understate true filing activity and may revise the picture once later records publish, but the shape through 2024 does not show sustained acceleration.
US11714028B2, assigned to Rockwell Collins and granted 2023-08-01, covers a bearing health-monitoring method that measures torsional energy transfer from a rotating device to a non-rotating device at a distance, compares that signal to a baseline, and calculates both a health status and a remaining useful life. The claim is anchored to a specific non-contact torsional-sensing architecture rather than to remaining-useful-life estimation in general, so it does not block RUL methods built on radial vibration or acoustic-emission sensing paths.
The thinnest branches in this corpus are the mechanical-integration classes: F02B (internal-combustion engine integration) and F16C (shafts, bearings and couplings) each carry only 2 records against a 37-family total, versus 37 records touching G01M and 14 touching G06F. That gap points to an opening for claims that tie a specific diagnostic method to a named piece of rotating hardware — engine-mounted or coupling-mounted sensing geometry — rather than claiming the signal-processing step on its own, where the prior art is already dense.
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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.