GFRP Defect Detection & Cure AI/ML Patent Snapshot
The application of AI and ML to glass-fibre-reinforced polymer (GFRP) defect detection and cure monitoring is a nascent, highly fragmented field with activity concentrated almost entirely in China. Filing volume remained near zero through 2023 before a sharp uptick in 2024–2025, signalling early-stage formation rather than an established competitive front.
A fragmented field with no dominant player — all leading filers hold a single patent record each
The corpus spans 9 patent families, with no single applicant holding more than 1 patent record. Nanjing Forestry University, Hunan University of Science and Technology, Jiangxi Investment Group, Graphic Era Deemed to be University, and Fuzhou University each hold 1 patent record — together accounting for 45% of the top hundred filers’ combined total.
There is effectively no tier gap: every ranked applicant sits at the same count, which makes this one of the most diffuse competitive structures observable. No incumbent has accumulated a blocking portfolio, and no single organization has established a recognisable lead.
| # | Applicant | Patent records | Share |
|---|---|---|---|
| 1 | Nanjing Forestry University | 1 | |
| 2 | HUNAN UNIV OF SCI & TECH | 1 | |
| 3 | Jiangxi Investment Group Co., Ltd. | 1 | |
| 4 | Graphic Era Deemed to be University | 1 | |
| 5 | Fuzhou University | 1 | |
| 6 | Guizhou Ganxing Coal Industry Co., Ltd. | 1 |
| # | Applicant | Patent records | Share |
|---|---|---|---|
| 7 | Qingdao Lanmeng Industry Co., Ltd. | 1 | |
| 8 | Shanghai Jiaqi Intelligent Technology Co., Ltd. | 1 | |
| 9 | Zhenjiang Shenlong Electrical Pipe Fittings Co., Ltd. | 1 | |
| 10 | Shenzhen University | 1 | |
| 11 | CHINA HELICOPTER RES & DEV INST | 1 |
The flat ranking implies that first-movers who build even a modest, coherent patent portfolio in the near term could establish a durable positional advantage. The absence of consolidation also suggests that collaboration or licensing barriers are low.
The most recent filing years (2024–2025) are subject to publication lag and likely under-count actual activity; the true recent-period volume may be higher than the trend currently shows. Longer-window growth, applicant concentration, and technology-route coverage are therefore more reliable signals than the latest-year bar alone.
Activity surged in 2025 after years of near-zero filings; AI computing dominates the technology mix
Two charts together reveal both the timing of market entry and the technical approach: filing volume shows when interest crystallised, while the IPC branch breakdown shows how applicants are framing their inventions.
Annual filing trend
Filings were zero from 2017 through 2021, a single record appeared in 2022, and then 2 records were filed in 2024 followed by 6 in 2025. Because 2024–2025 filings are still working through examination and publication pipelines, the 2025 bar is likely a floor, not a ceiling. The pattern indicates that the field transitioned from a conceptual curiosity to active patenting only around 2024.
↗ Hover for values · click a bar to ask EurekaTechnology composition
G06N (Computing based on AI models) leads with 8 patent records, followed closely by G06F (Electric digital data processing) with 7 — confirming that algorithmic and computational framing is visible in. Physical measurement branches G01D (Measuring, general and recording) and G01N (Material analysis and testing) each appear in 2 records, reflecting a minority of filings that anchor the AI methods to physical sensing. G16C (Computational chemistry), F03D (Wind motors), G06V (Image/video recognition), and power-system branches each appear in 1 record, indicating scattered application-domain coverage.
↗ 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.
基于自适应小波包分解与深度学习的锚杆锚索无损检测法
本发明属于岩土工程无损检测技术领域，具体涉及基于自适应小波包分解与深度学习的锚杆锚索无损检测法，尤其适用于复杂工况下的多缺陷识别与高精度定位。该方法通过激励锚杆锚索，采集锚杆锚索的应力波信号，对信号进行预处理，使用动态优化小波基与分解层数，实现信号的高分辨率时频分析，并且结合时频图卷积神经网络与多源特征融合，显著提升复杂噪声环境下的缺陷检测精度，同时还支持钢质、GFRP等多种材质的自适应检测，具备工程推广应用价值。 (excerpt from the patent abstract)
| # | Patent | Citations |
|---|---|---|
| 1 | 一种基于神经网络的GFRP耐久性评估方法 | 2 |
| 2 | A system and method for multi-objective optimizati… | 1 |
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.
Assignee snapshot from the current evidence set
The applicants below are visible in this query result. Because the evidence set is relatively small, read this section as a directional snapshot rather than a full competitive ranking.
Nanjing Forestry University
Nanjing Forestry University holds 1 patent record and is flagged as a new entrant in the recent filing period. Its technical focus centres on G06F digital data processing sub-classes (G06F 111, G06F 113, G06F 30), indicating a simulation and computational-design orientation rather than physical sensing. Fuzhou University shares the same IPC profile, making these two institutions the closest technical peers in the corpus.
patent records: 1China Helicopter Research and Development Institute
China Helicopter Research and Development Institute holds 1 patent record and is also a new entrant in the recent period. Its IPC focus spans G06F 113, G06F 119, and G06F 30 — structural simulation and optimisation sub-classes — suggesting GFRP AI work motivated by aerospace composite certification or structural-health-monitoring requirements. The defence/aerospace origin distinguishes it from the university-driven majority of filers.
patent records: 1Frequently asked questions
The PatSnap Eureka corpus for this specific intersection contains 9 patent families. This is a very small corpus, consistent with a field that only began generating regular filings in 2024.
China is visible in with 8 patent records. India accounts for 1. No filings have been recorded in the United States, Europe, Japan, or other major composite-manufacturing jurisdictions within this topic.
No applicant leads by volume — every filer in the corpus holds exactly 1 patent record. Nanjing Forestry University, Hunan University of Science and Technology, Jiangxi Investment Group, Graphic Era Deemed to be University, and Fuzhou University are the five filers whose combined records account for 45% of the top hundred filers’ total.
G06N (Computing based on AI models) appears in 8 patent records and G06F (Electric digital data processing) in 7, indicating that neural-network and data-processing framings are visible in. Physical sensing branches such as G01N (material analysis) and G01D (general measurement) each appear in only 2 records, so sensor-integrated AI methods are comparatively rare.
Three co-filing pairs are on record, all within China: Guizhou Ganxing Coal Industry with Hunan University of Science and Technology, Guizhou Ganxing Coal Industry with Jiangxi Investment Group, and Hunan University of Science and Technology with Jiangxi Investment Group. No international co-filing is present in the corpus.
The sparsest adjacent branches are G01N (material analysis and testing, 2 records) and F03D (wind motors, 1 record). G01N is adjacent to established industrial NDT practice, and F03D maps onto the high-volume wind turbine blade market — both represent technically plausible areas where AI/GFRP patenting activity is thin relative to the commercial opportunity.
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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.
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