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Non-Destructive Testing Landscape 2026 — PatSnap Eureka

Non-Destructive Testing Landscape 2026 — PatSnap Eureka
NDT Technology Landscape 2026

Non-Destructive Testing: 2026 Patent Intelligence Report

AI diagnostics, current waveform health indexing, XR-assisted inspection, and risk-based maintenance are reshaping NDT. Explore the full patent landscape — 25+ records, 4 innovation clusters, and emerging white space — powered by PatSnap Eureka.

NDT Patent Filing Activity by Period
NDT Patent Filing Activity by Period: 2008–2013 foundational ~3 filings, 2018–2022 mid-stage ~10 filings, 2023–2025 acceleration 12 of ~25 records Bar chart showing accelerating NDT patent activity across three periods, with 12 of approximately 25 NDT-relevant records published between 2021 and 2025 — the most active window in the dataset. Source: PatSnap Eureka patent dataset analysis. 12 9 6 3 ~3 2008–2013 ~10 2018–2022 12 2023–2025
Source: PatSnap Eureka · ~25 NDT records
25+
NDT-relevant patent records analysed
12
Records published 2021–2025
75–80%
South Korea jurisdiction share
4
Core innovation clusters identified
Technology Overview

Three Core Technical Paradigms Driving NDT Innovation

Non-destructive testing (NDT) encompasses a broad family of techniques used to evaluate the integrity, health, and performance of materials, components, and structures without causing damage. As industrial infrastructure ages and smart manufacturing accelerates, demand for advanced NDT solutions is intensifying across life sciences, power generation, and manufacturing sectors.

Within the PatSnap Eureka dataset, NDT-adjacent innovation clusters around three core technical paradigms: (1) current waveform-based health index detection for electromechanical devices, (2) distribution chart and peak-value analytics for predictive maintenance, and (3) risk-based and reliability-centered maintenance (RCM) frameworks for industrial facilities. A smaller but notable cluster addresses AI/ML-augmented inspection and extended reality (XR)-assisted field inspection.

The dominant technical mechanism involves monitoring the electrical current consumed by a device during operation — constructing waveforms, identifying peak and constant-current sections, and comparing these against baseline models to derive health indices. According to WIPO, patent filings in predictive maintenance and condition monitoring have grown substantially over the past decade, reflecting global industrial adoption. This approach is exemplified by multiple filings from IT Space Co., Ltd., a South Korean firm that has systematically patented variants of current-based health detection across the 2021–2025 period.

Risk-based maintenance and inspection route optimization appear in filings from Korea South-East Power Co., Ltd. and Mitsubishi Heavy Industries, addressing power generation and multi-device inspection planning respectively. The PatSnap Analytics platform enables teams to map these filing patterns across jurisdictions and assignees in real time.

Innovation Snapshot
2008
Earliest filing in dataset (Schlumberger, WO/US)
2025
Most recent filings (IT Space, Tektronix, Turkcell)
6+
IT Space Co., Ltd. filings — most active assignee
8
Distinct assignees with NDT-relevant filings
Dataset Scope Note

This landscape is derived from a limited set of patent and literature records retrieved across targeted searches. It represents a snapshot of innovation signals within this dataset only and should not be interpreted as a comprehensive view of the full industry.

Innovation Clusters

Four Technology Clusters Shaping NDT in 2026

From electrical current monitoring to AI-guided repair, the NDT patent landscape organises into four distinct technical clusters — each with different maturity levels and IP density.

Cluster 1 · Most Dense

Current Waveform-Based Device Health Indexing

The core mechanism involves collecting time-series data on the electrical current consumed by a device during a complete operational cycle, constructing waveforms, and identifying characteristic sections — peak current, constant current, and load time. A standard model waveform is built from repeated normal-state observations. Deviation between the operational waveform and the standard model is quantified as a health index, enabling early fault detection without physical disassembly. At least five distinct patent filings from IT Space Co., Ltd. populate this cluster.

5+ filings · IT Space Co., Ltd. · KR 2021–2025
Cluster 2 · Predictive Maintenance

Distribution Chart & Peak-Value Analytics

A related but distinct approach uses peak energy values and distribution diagrams rather than raw waveforms. The device's energy consumption peak values are collected per work cycle, and first and second distribution charts are constructed at set time intervals. Section thresholds are set within these distributions; deviation toward lower-probability sections triggers maintenance alerts. This approach emphasizes maintenance timing optimization — identifying the earliest reliable signal for impending failure to prevent catastrophic equipment loss.

3 filings · IT Space, NCKU · 2020–2021
Cluster 3 · Facility-Level

Risk-Based & Reliability-Centered Maintenance (RCM)

This cluster addresses facility-level inspection rather than device-level monitoring. Approaches include failure probability and consequence-of-failure weighting (risk matrices), Weibull distribution-based reliability modeling, streamlined RCM analysis, and cost-effectiveness functions for determining preventive maintenance intervals. These frameworks are particularly applied to power generation infrastructure, where scheduled downtime has high economic impact. Korea South-East Power and KEPCO are primary filers.

3 filings · KEPCO, Korea SE Power, Mitsubishi · 2013–2023
Cluster 4 · Emerging

AI/ML-Augmented & XR-Assisted Inspection

The newest cluster integrates machine learning, deep learning, and extended/mixed reality into inspection workflows. One approach uses ML networks to translate margin tester measurements into pass/fail performance predictions for device-under-test (DUT) interfaces. Another uses XR overlays and 3D equipment models to guide field workers through inspection sequences while connected to remote management. A further example from Turkcell applies AI and nanotechnology to detect and repair hardware-level damage. See the PatSnap Analytics platform for deeper cluster mapping.

3 filings · Gauss Lab, Tektronix, Turkcell · 2024–2025
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Data Visualisation

NDT Patent Landscape — Key Metrics

Visual summaries of filing activity, geographic distribution, and assignee concentration derived from the PatSnap Eureka NDT dataset.

Top Assignees by NDT Filing Volume

IT Space Co., Ltd. leads with 6+ filings — more than all other assignees combined — reflecting a focused SME IP strategy in device-level health monitoring.

Top NDT Assignees by Filing Volume: IT Space Co. Ltd. 6+, KEPCO 2, LIG Nex1 2, Korea SE Power 1, Mitsubishi 1, Tektronix 1, Gauss Lab 1 Horizontal bar chart showing IT Space Co., Ltd. as the dominant assignee in the NDT patent dataset with 6+ relevant filings, followed by KEPCO and LIG Nex1 with 2 each. Source: PatSnap Eureka NDT patent dataset analysis. 2 3 4 5+ IT Space 6+ KEPCO 2 LIG Nex1 2 Korea SE Power 1 Mitsubishi HI 1 Tektronix 1 Gauss Lab 1

NDT Patent Filings by Jurisdiction

South Korea accounts for approximately 75–80% of NDT-relevant records in this dataset, with Japan and the US contributing smaller shares.

NDT Patent Filings by Jurisdiction: South Korea (KR) ~75-80%, Japan (JP) ~8%, United States (US) ~6%, Other (CN, EP, TR, RU) ~10% Donut chart showing South Korea's dominant share of approximately 75–80% of NDT-relevant patent filings in the dataset, with isolated entries from Japan, the US, China, Europe, Turkey, and Russia. Source: PatSnap Eureka NDT patent dataset analysis. KR Dominant South Korea (KR) ~75–80% Japan (JP) ~8% United States (US) ~6% Other (CN, EP, TR, RU) ~10%

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Application Domains

Where NDT Innovation Is Being Applied

The dataset spans five distinct application verticals — from power generation to defence — each with different technical approaches and primary assignees.

Application Domain Primary Approach Key Assignees Representative Filing
Power Generation & Utilities Risk-based maintenance; Weibull RCM; failure probability matrices Korea South-East Power, KEPCO Hybrid RCM for Power Generation Facilities (KEPCO, 2022)
Manufacturing & Industrial Equipment Current waveform health indexing; distribution-chart predictive maintenance IT Space Co., Ltd.; National Cheng Kung University Baseline predictive maintenance for semiconductor equipment (NCKU, 2020)
Transportation & Tunnel Infrastructure ITS-based continuous monitoring; cameras, ventilation, lighting, emergency power Taeyoung TS Co., Ltd. ITS-based tunnel environment monitoring (Taeyoung TS, 2025)
Rotating Machinery & Bearings Real-time fault diagnosis; mobile terminal streaming; gear and bearing monitoring Korea Aerospace University IAC Foundation Diagnostic results monitoring system (KAUIACF, 2020)
Defence & Specialised Equipment MTBF-based equipment management; repairable weapon systems analysis LIG Nex1 Co., Ltd. Equipment management via MTBF field data analysis (LIG Nex1, 2021)

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Emerging Directions 2023–2025

Four Directional Signals from the Most Recent Filings

Based on filings from 2023–2025 in this dataset, these signals indicate where NDT innovation is heading — and where early IP positioning may be most valuable.

⚖️

Weighted Multi-Parameter Health Indexing

The most recent IT Space Co., Ltd. filings (July 2025) introduce a "weight setting step" that allows selection of device type (intermittent vs. continuous) and assignment of differential weights to peak current, constant current, and load time detection items. This represents a move from single-metric to configurable multi-parameter health scoring, enabling customization per device class.

🥽

Extended Reality (XR) Integration for Remote-Guided Inspection

Gauss Lab's 2024 patent represents a new workflow paradigm: field workers wearing XR headsets receive real-time 3D equipment model overlays and inspection order sequences, while remote managers co-observe via mixed reality video calls. This spatially-aware inspection guidance reduces dependence on expert on-site presence — a significant operational shift for multi-site industrial operators.

🔒
Unlock 2 More Emerging Directions
Explore AI/ML signal translation (Tektronix, 2025) and nanotechnology-enabled autonomous repair (Turkcell, 2025) — the two newest NDT convergence signals.
AI/ML margin testing (PCIe Gen3/Gen4) Nano-repair convergence + full filing details
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Strategic Implications

What the NDT Patent Landscape Means for R&D and IP Teams

IP white space exists in multi-modal NDT fusion. The dataset reveals deep specialization in current-based electrical monitoring but limited filings combining electrical, acoustic, thermal, or optical sensing modalities. R&D teams pursuing sensor fusion architectures face a relatively uncrowded IP landscape based on this data. The PatSnap Analytics platform can help identify these gaps systematically.

IT Space Co., Ltd. holds a dense, defensible IP cluster in current-waveform health indexing. Competitors building similar device health monitoring products should conduct freedom-to-operate analysis around the peak/constant-current waveform classification methodology and weighted health index calculation steps, particularly for Korean market entry. According to the European Patent Office, freedom-to-operate searches are a critical step before product commercialisation in any technology area with concentrated assignee activity.

XR-guided inspection is an early-stage but high-momentum direction. The single 2024 filing from Gauss Lab suggests commercial pilots are underway but IP density is still low — creating an opportunity window for IP positioning in XR-assisted NDT workflows, particularly for multi-site industrial operators.

Korea dominates this dataset; geographic expansion signals exist. Tektronix's Chinese filing and Turkcell's Turkish filing suggest that NDT innovation is beginning to extend beyond Korea's domestic utility and manufacturing sectors. Investors and technology scouts should monitor Chinese filings in electrical-current-based NDT as potential scale-up indicators. The PatSnap customer community includes teams already tracking these geographic shifts.

The predictive-maintenance-to-autonomous-repair continuum is emerging. The convergence trajectory suggested by the Turkcell nanotechnology repair patent points toward systems that not only detect and classify defects but automatically initiate remediation. Product developers should evaluate roadmap positioning along this continuum and consider where human-in-the-loop inspection requirements will persist versus where autonomous response is regulatorily and technically feasible. For enterprise-grade IP data governance, see the PatSnap Trust Center. Industry bodies such as the American Society for Nondestructive Testing (ASNT) provide additional standards context for regulatory compliance planning.

Key Strategic Signals
  • Multi-modal sensor fusion is an IP white space opportunity
  • Freedom-to-operate analysis needed for Korean current-waveform methods
  • XR-assisted inspection has low IP density — early positioning window
  • Monitor Chinese filings for current-based NDT scale-up signals
  • Autonomous repair convergence is emerging — evaluate roadmap position
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Frequently asked questions

Non-Destructive Testing Technology Landscape 2026 — key questions answered

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References

  1. Method for detecting the health index of a device through a cumulative waveform — IT Space Co., Ltd., 2022, KR
  2. Method of detecting the health index of the device through the distribution chart — IT Space Co., Ltd., 2021, KR
  3. Reasonable health index detection method for devices — IT Space Co., Ltd., 2025, KR
  4. Reasonable health index detection method for devices (weighted) — IT Space Co., Ltd., 2025, KR
  5. Method of preserving the prediction of a device through distribution chart — IT Space Co., Ltd., 2021, KR
  6. Method of preserving the prediction of a device through distribution chart (variant) — IT Space Co., Ltd., 2021, KR
  7. Baseline predictive maintenance method for target device and computer program product thereof — National Cheng Kung University, 2020, EP
  8. Risk based maintenance system for power generation facilities — Korea South-East Power Co., Ltd., 2013, KR
  9. System and Method of Hybrid Reliability Centered Maintenance for Power Generation Facilities — Korea Electric Power Corporation, 2023, KR
  10. System and Method of Hybrid Reliability Centered Maintenance for Power Generation Facilities — Korea Electric Power Corporation, 2022, KR
  11. Inspection route plan proposal system, and inspection route plan proposal method — Mitsubishi Heavy Industries, Ltd., 2023, JP
  12. Method and system for providing extended reality service to operate industrial facilities — Gauss Lab Inc., 2024, KR
  13. Margin tester measurement using machine learning — Tektronix, Inc., 2025, CN
  14. A system that enables the repair of mobile device hardware damages using artificial intelligence-supported nanotechnology — Turkcell Technology Research and Development Inc., 2025, TR
  15. ITS-based tunnel environment monitoring and data analysis methods, devices, and systems — Taeyoung TS Co., Ltd., 2025, KR
  16. Diagnostic results monitoring system and method thereof — Korea Aerospace University Industry–Academic Cooperation Foundation, 2020, KR
  17. Equipment management information providing apparatus through field data analysis based on MTBF — LIG Nex1 Co., Ltd., 2021, KR
  18. Apparatus and method for controlling monitoring device — LIG Nex1 Co., Ltd., 2017, KR
  19. System and method for visualizing equipment health status and forecast maintenance requirements — Wise IT Co., Ltd., 2019, KR
  20. World Intellectual Property Organization (WIPO) — Patent Trends in Predictive Maintenance
  21. European Patent Office (EPO) — Freedom-to-Operate Guidance
  22. American Society for Nondestructive Testing (ASNT) — NDT Standards and Regulatory Context

All data and statistics on this page are sourced from the references above and from PatSnap's proprietary innovation intelligence platform. This landscape is derived from a limited set of patent and literature records retrieved across targeted searches and should not be interpreted as a comprehensive view of the full industry.

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