Rolling Bearing Condition Monitoring Patent Landscape
The rolling bearing condition monitoring field is in an active growth phase, with 1,328 patent families on record and a 60% rise in filings over the recent multi-year window; annual volume peaked around 2023 and the most recent period is subject to publication lag. AB SKF holds the top commercial position with 83 patent families, but Chinese universities collectively dominate the mid-tier, reflecting a field where academic-applied AI research and established bearing manufacturers are both shaping the frontier.
SKF leads a moderately concentrated field shaped by Chinese academic output
AB SKF heads the applicant ranking with 83 patent families, followed by Kunming University of Science and Technology at 55 and NSK Ltd at 49. The top five filers — SKF, Kunming University of Science and Technology, NSK, NTN Corporation, and Harbin University of Science and Technology — together account for 24% of the hundred largest filers’ combined total, indicating moderate rather than tight concentration.
A clear two-tier structure is visible: one industrial leader (SKF) and two established bearing manufacturers (NSK, NTN) sit above a dense layer of Chinese universities, including Xi’an Jiaotong University, Beijing University of Technology, and Chongqing University of Posts and Telecommunications, each contributing 22–34 patent families. The gap between the leader and the mid-tier is meaningful but not prohibitive.
| # | Applicant | Patent families | Share |
|---|---|---|---|
| 1 | AB SKF | 83 | |
| 2 | KUNMING UNIV OF SCI & TECH | 55 | |
| 3 | NSK Ltd | 49 | |
| 4 | NTN Corporation | 46 | |
| 5 | HARBIN UNIV OF SCI & TECH | 39 | |
| 6 | Xi’an Jiaotong University | 34 | |
| 7 | Beijing University of Technology | 23 | |
| 8 | The Chugoku Electric Power Company | 23 | |
| 9 | Chongqing University OF POSTS & TELECOMM | 22 | |
| 10 | Shenyang Aerospace University | 22 |
| # | Applicant | Patent families | Share |
|---|---|---|---|
| 11 | NANJING UNIV OF AERONAUTICS & ASTRONAUTICS | 20 | |
| 12 | Yanshan University | 19 | |
| 13 | Siemens AG | 19 | |
| 14 | Hefei University of Technology | 18 | |
| 15 | Shandong University | 17 | |
| 16 | Wenzhou University | 16 | |
| 17 | Kobe Steel Ltd | 14 | |
| 18 | Beihang University | 14 | |
| 19 | Lanzhou University of Technology | 13 | |
| 20 | Southeast University | 13 |
SKF’s lead reflects long-standing investment in bearing-integrated sensing and wireless diagnostics. The depth of Chinese university participation signals that algorithm-centric and AI-driven diagnostics represent the main area of competitive expansion, with academic pipelines feeding both domestic and international filings.
Filing counts for 2024 and 2025 are understated due to typical patent publication lag of 12–18 months and should not be read as a change in underlying activity pace. Longer-window growth, applicant concentration, and technology-route coverage are therefore more reliable signals than the latest-year bar alone.
Sustained filing growth driven by AI diagnostics layered onto core mechanical testing IP
Annual filings grew from 49 patent families in 2017 to a peak of 216 in 2023, with 2024 and 2025 figures understated by publication lag. The technology composition shows a dominant mechanical-testing core (G01M) augmented by a substantial and growing AI and digital processing layer.
Annual filing trend
Filings climbed steadily from 2017 through 2023, reaching 216 patent families at the peak. The apparent dip in 2024 and 2025 should be read cautiously — publication lag typically understates the most recent 18–24 months, so the true trajectory cannot yet be confirmed as a decline.
↗ Hover for values · click a bar to ask EurekaTechnology composition
G01M (Testing machine and structure balance) is the dominant branch by a wide margin, reflecting the field’s foundation in bearing test methods. G06F (electric digital data processing) and G06N (AI models) together form a substantial second layer, confirming that machine-learning-based fault diagnosis has become a structural feature of the IP landscape rather than a niche. F16C (shafts, bearings and couplings) and G01H (vibration and sound measurement) represent smaller but technically central branches.
↗ Hover for values · click a bar to ask EurekaHighly cited patent families surfaced by the query
Citation-heavy patent families returned by the query. Use this section as citation context, not as a curated list of the most topic-specific patents.
Acoustic emission measurements of a bearing assembly
A bearing assembly comprising a rolling element bearing and an acoustic emission unit. The rolling element bearing is provided with at least a bearing seal, wherein the acoustic emission unit is arranged on the bearing seal. The assembly also provides an improved method for measuring acoustic emissions in a bearing assembly. (excerpt from the patent abstract)
| # | Patent | Citations |
|---|---|---|
| 1 | Wireless sensor, rolling bearing with sensor, mana… | 273 |
| 2 | Method for Fault Diagnosis of an Aero-engine Rolli… | 209 |
| 3 | Wireless sensor, rolling bearing with sensor, mana… | 172 |
| 4 | Bearing with wireless self-powered sensor unit | 159 |
| 5 | 一种基于CNN和LSTM的滚动轴承剩余使用寿命预测方法 | 153 |
| 6 | 基于特征迁移学习的变工况下滚动轴承故障诊断方法 | 127 |
| 7 | Method And Device For Assessing Residual Service L… | 123 |
| 8 | Abnormality diagnosis apparatus and abnormality di… | 122 |
Ranked by total forward citations. Citation counts favour older and broadly cited patent families, and broad or adjacent patents may appear when they match the search scope. Treat this section as citation context, not as a curated list of the most topic-specific patents. Some patent titles may be shown in their original, non-English language where an accurate translation could not be guaranteed.
What the structure means for R&D investment decisions
The combination of growth-stage dynamics, moderate concentration, active industry–academia collaboration, and. China-dominant jurisdiction coverage creates both entry opportunities and navigation challenges for new entrants and incumbents alike.
Active growth phase with filings still rising on a multi-year basis
The field is classified as Growth stage: annual filings rose 60% over the recent multi-year window and peaked at 216 patent families in 2023. The most recent years are understated by publication lag, so the field has not demonstrably passed its peak. New IP positions can still be established in differentiating sub-domains before the landscape consolidates.
Growth stageModerate concentration with a strong commercial leader and dense academic mid-tier
The top five filers hold 24% of the hundred largest filers’ combined total — a level that indicates competitive but not locked-up space. SKF’s lead is primarily in bearing-integrated hardware and sensor design, while the Chinese university cluster competes heavily in algorithmic and AI-based diagnostics. Entrants with differentiated hardware-software integration propositions face the most open terrain.
Moderate HHINTN, Shinkawa Sensor Technology, and The Chugoku Electric Power form the most active co-filing cluster
The most active co-filing relationships are among NTN Corporation, Shinkawa Sensor Technology, and The Chugoku Electric Power Company, each pair sharing 8 co-filed patent families. The Chugoku Electric Power Company and the individual inventor Takuzo Iwatsubo also appear prominently with 7 co-filed families. SKF co-files with SKF Aerospace France, reflecting internal group collaboration. These clusters suggest utility-manufacturer and bearing-maker partnerships are a productive IP development model in this field.
Industry–utility clustersChina dominates filings; Japan, the US, and EPO are the principal international venues
China accounts for 1,309 patent records at the jurisdiction level, far ahead of Japan at 85, the United States at 79, and the EPO at 62. WIPO PCT filings stand at 43, indicating selective but active international prosecution by leading filers. Competitors seeking enforceable positions outside China — particularly in industrial equipment markets in Europe and North America — face a less crowded filing environment.
China-dominantGo beyond the landscape: Eureka’s TRIZ Solution agent breaks down an R&D problem and returns patented concept solutions, each with a technical approach and cited patent & literature evidence.
| Applicant | Collaborator | Co-filings |
|---|---|---|
| NTN Corporation | Shinkawa Sensor Technology | 8 |
| NTN Corporation | The Chugoku Electric Power Company | 8 |
| The Chugoku Electric Power Company | Shinkawa Sensor Technology | 8 |
| The Chugoku Electric Power Company | Takuzo Iwatsubo | 7 |
| NTN Corporation | Takuzo Iwatsubo | 4 |
| The Chugoku Electric Power Company | Takuzo Iwatsubo | 4 |
| AB SKF | SKF Aerospace France | 2 |
| NTN Corporation | Hideyuki Tsutsui | 2 |
| NTN Corporation | Takuzo Iwatsubo | 2 |
| NTN Corporation | Tomoya Sakaguchi | 2 |
Co-filing pairs, ranked by the number of jointly-filed patent families.
SKF anchors hardware integration; Kunming University of Science and Technology leads academic AI diagnostics
The top two filers represent distinct strategic profiles: SKF’s portfolio is hardware-centric and spans bearing-integrated sensing and mechanical testing, while Kunming University of Science and Technology focuses on algorithm-driven fault recognition and data processing methods.
AB SKF
AB SKF holds 83 patent families, the largest portfolio in the field. Its technology emphasis centers on G01M 13 (bearing test methods), F16C 19 and F16C 41 (bearing design and integration), reflecting a strategy of embedding condition monitoring capability directly into bearing hardware. SKF’s recent-period momentum is marked as a new entrant in the most recent filing window, which from a large incumbent base likely reflects portfolio restructuring or filing consolidation rather than a genuine new entry.
families: 83Kunming University of Science and Technology
Kunming University of Science and Technology holds 55 patent families, placing it second overall and first among academic filers. Its focus is on G01M 13 (testing methods), G06K 9 (data recognition), and G06F 18 (digital data processing), reflecting an AI and pattern-recognition-led approach to fault diagnosis. Recent-period momentum shows a 42% decline from the prior three-year base, suggesting a possible plateau or strategic refocus rather than continued aggressive filing.
families: 55| Applicant | Recent (3 yrs) | Trend |
|---|---|---|
| AB SKF | 12 | ▲ new entrant |
| Kunming University of Science and Technology | 14 | ▼ -42% |
| NSK Ltd | 13 | ▲ new entrant |
| NTN Corporation | 4 | ▲ new entrant |
| Harbin University of Science and Technology | 10 | ▼ -33% |
| Xi’an Jiaotong University | 11 | ▼ -15% |
| Beijing University of Technology | 8 | ▲ new entrant |
| Chongqing University of Posts and Telecommunications | 12 | ▲ new entrant |
Under-served adjacent branches in vibration sensing, image recognition, and materials analysis
Several IPC branches adjacent to the dominant G01M core show relatively low filing share, representing areas where the condition monitoring application layer is less developed. These are observations of relative sparsity; technical and commercial value should be validated against specific use-case requirements.
G01H · Vibration and sound measurement
G01H accounts for 143 patent records at a 4% share of classified filings — sparse relative to its direct relevance to bearing diagnostics, where vibration signatures are a primary fault indicator. Most current IP routes the vibration signal through G01M test methods rather than treating the measurement physics as a separate innovation layer. Entrants developing novel sensor modalities (e.g., MEMS-based acoustic emission or ultrasonic transduction optimized for bearing geometries) could stake distinct claims in this branch without directly contesting the crowded G01M space.
Search this in Eureka →G06V · Image and video recognition
G06V holds only 38 patent records at a 1% share, despite visual inspection and thermographic imaging being established bearing diagnostic methods in industrial practice. The low filing density suggests that vision-based condition monitoring — including infrared thermography, surface defect imaging, and video-based anomaly detection for exposed bearing races — is under-protected relative to its technical maturity. Applicants combining G06V methods with bearing-specific training datasets or edge-inference hardware face a relatively open filing environment.
Search this in Eureka →How leading applicants differ by technology route emphasis
Route coverage across the main technology branches in the current evidence set.
| Player | G01M 13 · Testing machine & structure balance | G06N 3 · Computing based on AI models | G06F 18 · Electric digital data processing | G06K 9 · Data recognition & presentation | F16C 19 · Shafts, bearings & couplings |
|---|---|---|---|---|---|
| Kunming University of Science and Technology | Strong · 58 | Moderate · 13 | Moderate · 13 | Moderate · 18 | Absent |
| AB SKF | Strong · 51 | Absent | Absent | Absent | Strong · 45 |
| Harbin University of Science and Technology | Strong · 43 | Moderate · 21 | Moderate · 11 | Moderate · 10 | Absent |
| NTN Corporation | Strong · 43 | Absent | Absent | Absent | Moderate · 19 |
| NSK Ltd | Strong · 38 | Absent | Absent | Absent | Moderate · 16 |
| Chongqing University of Posts and Telecommunications | Strong · 22 | Strong · 13 | Strong · 16 | Absent | Absent |
| Xi’an Jiaotong University | Strong · 35 | Absent | Moderate · 8 | Absent | Absent |
Frequently asked questions
The landscape comprises 1,328 patent families in scope. China is the dominant filing jurisdiction, accounting for 1,309 patent records at the jurisdiction level, with Japan at 85, the United States at 79, and the EPO at 62.
AB SKF holds the largest portfolio with 83 patent families, ahead of Kunming University of Science and Technology at 55 and NSK Ltd at 49. SKF’s strength lies in bearing-integrated sensing hardware, while the university leaders focus on AI-based diagnostic algorithms.
Filings grew 60% over the recent multi-year window, rising from 49 patent families in 2017 to a peak of 216 in 2023. The 2024 and 2025 figures are understated due to publication lag and should not be interpreted as a confirmed decline.
G01M (Testing machine and structure balance) is the dominant branch with 1,579 patent records. G06F (Electric digital data processing) and G06N (Computing based on AI models) together account for 1,197 records, confirming that machine-learning-based fault diagnostics has become a structural component of the IP landscape.
The most active co-filing cluster involves NTN Corporation, Shinkawa Sensor Technology, and The Chugoku Electric Power Company, with each pair sharing 8 co-filed patent families. The Chugoku Electric Power Company and individual inventor Takuzo Iwatsubo co-filed 7 families, and NTN Corporation and Iwatsubo co-filed 4 families.
G01H (Measuring vibrations and sound) at 4% share and G06V (Image and video recognition) at 1% share are notably sparse relative to their direct technical relevance to bearing diagnostics. G01N (Material analysis and testing) at 1% share is also comparatively underdeveloped, particularly for lubrication state and surface degradation monitoring applications.
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