"YaqiXun" Inspection System

Robots + Cloud Platform + AI Algorithms

In industrial production, infrastructure operation and maintenance, public security and other fields, inspection serves as a core link to guarantee stable equipment operation, avoid safety risks and cut operation and maintenance costs. The traditional manual inspection model is plagued by drawbacks including high labor costs, low inspection efficiency, prominent safety hazards and non-standard data recording. Its limitations become especially striking in harsh environments featuring high temperature, extreme cold, high radiation, toxic and hazardous substances, making it difficult to meet the high-precision, all-weather and intelligent demands of modern operation and maintenance. Against this backdrop, intelligent inspection systems integrating three core technologies — robots, cloud platforms and AI algorithms — have emerged. These systems build a three-dimensional collaborative inspection architecture of "terminal-edge-cloud", enabling transformative advancement of inspection work from "manual high-risk operations" to "intelligent on-duty monitoring" and from "passive troubleshooting" to "active early warning". They deliver efficient, accurate and secure full-process inspection solutions for various industries.

## I. Core System Architecture: Trinity Collaborative Operation

Centered on the core logic of "data collection – intelligent analysis – cloud management and control", the system deeply integrates inspection robots (front-end execution terminals), cloud management platforms (mid-end control terminals) and AI intelligent algorithms (core driving terminals). The three components operate in synergy with seamless connection to form a closed-loop full-process inspection system. It breaks down data silos and efficiency bottlenecks in traditional inspection and establishes an all-round, multi-level intelligent inspection ecosystem.

(I) Front-end Execution Terminal: Inspection Robots – Mobile Intelligent Perception Terminals

As the "eyes" and "hands" of the system, inspection robots undertake core tasks including on-site data collection and real-time operation execution. Classified into wheeled, rail-mounted, drone and other types according to application scenarios, they adapt to diverse inspection environments and feature core strengths such as autonomous movement, multi-dimensional perception and resistance to harsh environments.

Equipped with multiple high-precision devices including high-definition visible light cameras, infrared thermal imagers, gas sensors, vibration sensors and acoustic sensors, robots can conduct real-time monitoring and data collection of multi-dimensional parameters such as temperature, humidity, gas concentration, equipment vibration and surface defects. They capture subtle anomalies hardly detectable by humans, such as overheating of power equipment connectors, tiny leaks in chemical pipelines and surface cracks on equipment. Meanwhile, incorporating LiDAR, GPS/Beidou positioning, SLAM (Simultaneous Localization and Mapping) and other technologies, robots can perceive surrounding environments in real time, construct map models, independently plan optimal inspection routes and flexibly avoid obstacles to guarantee continuous and accurate inspection operations. Capable of 24-hour uninterrupted monitoring, they break the physical limits of human inspectors and environmental constraints, making them particularly suitable for inspection in high-risk, remote and complex scenarios.

(II) Mid-end Control Terminal: Cloud Management Platform – Central Hub for Inspection Data

Serving as the "central nervous system" of the system, the cloud management platform undertakes core functions including data storage, remote control, instruction distribution and report generation. Adopting a cloud-edge collaborative architecture, it enables efficient interaction between front-end data and back-end management, eliminates spatial restrictions and realizes remote and intensive management of inspection work.

The platform encompasses four core functional modules:

1. Data aggregation and storage: It receives images, videos and sensor data uploaded by inspection robots in real time, conducts standardized data cleansing and classified storage, and builds a unified defect sample library and equipment archives. The data storage cycle satisfies business requirements of no less than 15 years with sufficient reserved expansion space.

2. Remote control and scheduling: Managers can monitor robot operating status and inspection progress in real time via the platform, remotely issue instructions such as inspection route adjustment, task allocation and emergency response, and support coordinated operation of multiple robots to achieve full coverage of inspection areas.

3. Visual presentation and early warning**: Leveraging 3D modeling, digital twins and other technologies, it intuitively displays inspection areas, equipment status and abnormal data. Once anomalies are detected, audible and visual alarms are triggered immediately, and warning notifications are pushed through multiple channels including the platform and mobile APPs, specifying the location, type and risk level of anomalies to win time for emergency disposal.

4. Data statistics and analysis: It automatically generates inspection reports and defect ledgers, supports historical data review and trend analysis, provides data support for equipment maintenance and decision optimization, and facilitates predictive maintenance.

(III) Core Driving Terminal: AI Intelligent Algorithms – Core Engine for Intelligent Identification

As the core enabler of system intelligence and the equivalent of the system’s "brain", AI intelligent algorithms adopt machine learning, deep learning, computer vision and other key technologies to conduct real-time analysis and intelligent identification of massive data collected by inspection robots. Raw data is converted into valuable inspection information to realize automatic defect identification, precise anomaly judgment and fault trend prediction, completely eliminating reliance on human experience.

The system is embedded with multiple core AI algorithms tailored to various inspection scenarios. It can automatically identify defects such as equipment surface damage, insulator cracks, broken wire strands and pipeline corrosion with an identification accuracy of over 90%, and the recognition precision for tiny defects can reach up to 97.7%. In multi-dimensional data fusion analysis, sensor fusion algorithms integrate multi-source data including temperature, vibration, sound and gas to establish normal equipment operation models and accurately identify implicit equipment anomalies such as internal faults and potential leaks. For route optimization, reinforcement learning and path planning algorithms dynamically adjust robot inspection routes based on real-time environmental data to boost inspection efficiency and shorten operation time. In terms of trend prediction, time-series data analysis algorithms forecast equipment performance degradation curves and remaining service life to predict fault risks in advance, facilitating the shift from "post-fault maintenance" to "preemptive prevention". Furthermore, the algorithms feature self-learning capabilities. By continuously accumulating inspection data and optimizing model parameters, they steadily improve recognition accuracy and adaptability to meet inspection demands across diverse industries and scenarios.

II. Core Technical Advantages of the System: Comprehensive Breakthroughs Over Traditional Inspection Bottlenecks (I) High Efficiency and Intelligence to Greatly Boost Inspection Efficiency

Inspection robots deliver nonstop 24-hour inspection without rest or fatigue, lifting inspection efficiency by 3 to 5 times compared with manual inspection. Especially for large-area inspection zones, coordinated operation of multiple robots achieves full regional coverage and drastically shortens inspection cycles. For instance, after deployment in a chemical park, single inspection duration was reduced by 40% and manual inspection frequency cut by 60%. Meanwhile, AI algorithms automatically complete data analysis and defect identification without manual data screening, avoiding human missed and false detections and further improving inspection efficiency and data accuracy.

(II) High Precision and Reliability to Reduce Inspection Errors

High-precision sensors carried by robots paired with AI intelligent algorithms enable precise capture of subtle anomalies, with defect identification accuracy exceeding 90%, far surpassing manual inspection accuracy. This effectively prevents missed and false detections caused by insufficient experience or inadequate accountability of personnel, ensures authenticity and reliability of inspection data, and provides accurate references for equipment maintenance.

(III) Safe and Controllable Operations to Avoid Occupational Risks

In high-risk and harsh environments such as chemical parks, high-radiation zones, underground pipe galleries and overhead power lines, inspection robots can replace human workers to perform inspection tasks. This prevents personnel exposure to hazardous environments featuring toxic substances, high temperatures and high pressure, fundamentally lowering safety risks for inspectors and realizing a safe operation and maintenance model of "unmanned inspection with human supervision". For example, hazardous chemical inspection robots developed by Supcon Technology deployed in chlor-alkali workshops effectively eliminate poisoning and explosion risks for staff entering tanks for inspection, markedly improving the safety operation level of the park.

(IV) Cloud Collaboration to Achieve Intensive Management

Cloud platforms break spatial constraints to realize centralized control over multiple regions and numerous robots. Managers can remotely monitor equipment status and inspection progress at all inspection points without on-site presence, substantially cutting labor and management costs. Meanwhile, cloud-based data sharing and collaborative analysis enable cross-regional and cross-departmental exchange of inspection data, providing data support for enterprises’ overall operation and maintenance decisions and advancing intensive and refined management. In some scenarios, labor costs can be reduced by over 70% while inspection frequency increases fivefold.

(V) Strong Scalability to Adapt to Diverse Industrial Scenarios

Adopting a modular design, the system can flexibly configure robot types, sensor equipment and AI algorithm models according to inspection requirements of different industries and scenarios. It satisfies inspection demands across power, chemical, security, rail transit, photovoltaic, wind power and other sectors. Large-scale system reconstruction is unnecessary, enabling rapid implementation and delivering outstanding scalability and adaptability. Typical applications include intelligent inspection of transmission lines and substations in the power industry, 24-hour patrol and prevention in parks and airports for the security sector, and high-precision inspection of tracks and tunnels in rail transit.

III. System Application Scenarios: Cross-industry Coverage to Empower Intelligent Operation and Maintenance

(I) Power Industry

Suitable for inspection of transmission lines, substations, power distribution rooms, photovoltaic power stations, wind farms and other sites. Robots can independently complete line inspection, equipment temperature measurement, meter reading and defect identification. AI algorithms automatically detect insulator damage, broken wire strands, bird nests, photovoltaic hot spots, wind turbine blade defects and other issues, with data uploaded to the cloud platform in real time. This enables unattended intelligent operation and maintenance of power grids, effectively improving inspection efficiency and power supply reliability while lowering operation costs and safety risks. In a State Grid project, intelligent inspection robots achieved defect identification accuracy above 90% and boosted inspection efficiency by 3 to 5 times.

(II) Chemical Industry

Adaptable to chemical parks, production plant areas, tank zones, pipe galleries and other scenarios. Featuring explosion-proof, waterproof and dustproof protection, robots can conduct toxic and hazardous gas leakage detection, equipment temperature and pressure monitoring, fire hazard screening and pipeline corrosion inspection. AI algorithms rapidly identify hidden dangers including abnormal gas concentration, equipment overheating and pipeline leaks, immediately trigger early warnings and push disposal suggestions, significantly lifting park safety operation standards. After deployment at a large chemical enterprise, the early warning response time for toxic gas leakage incidents was shortened by 80%, effectively avoiding major safety hazards.

(III) Security Industry

Deployed for patrol and prevention in public spaces such as industrial parks, residential communities, airports, stations and large venues. Equipped with high-definition cameras, infrared cameras and facial recognition devices, robots conduct uninterrupted 24-hour patrols. AI algorithms automatically detect anomalies including strangers, suspicious behaviors and abandoned objects, issue timely alerts and coordinate with security staff for disposal. This effectively compensates for blind spots and fatigue-related limitations of manual patrols and raises the intelligence level of security prevention and control.

(IV) Rail Transit Industry

Applicable to inspection of metro and high-speed railway tracks, tunnels, station equipment and power supply systems. Robots move autonomously to detect track cracks, tunnel water seepage, equipment faults and other problems. AI algorithms accurately identify subtle defects to deliver high-precision, all-weather rail transit inspection, safeguard public travel safety and address challenges of heavy workloads and high precision requirements in traditional inspection.

(V) Other Fields

The system can be widely applied in mining, water conservancy, municipal engineering, warehousing and other sectors. Mining inspection robots realize underground environmental monitoring and equipment inspection; water conservancy inspection robots monitor water levels and water quality at reservoirs and rivers; municipal inspection robots conduct intelligent inspection of pipe networks and street lamps, comprehensively empowering the intelligent operation and maintenance transformation of various industries.

IV. Core System Values: Cost Reduction, Efficiency Improvement, Safety Assurance and Intelligent Upgrade

1. Cut operation and maintenance costs: Replace manual inspection to reduce labor input and lower labor and management costs. Meanwhile, it minimizes downtime losses and maintenance expenses stemming from undetected equipment faults, achieving substantial reduction of overall operation and maintenance expenditure.

2. Boost inspection efficiency: Enable 24-hour uninterrupted inspection, optimize inspection routes, shorten inspection cycles, expand inspection coverage and improve data collection efficiency, resolving the pain point of low efficiency in traditional inspection.

3. Secure operational safety: Replace human workers in high-risk and harsh environments, avoid personnel safety hazards, reduce safety accidents and consolidate the foundation of safe production.

4. Realize intelligent operation and maintenance**: Leverage intelligent identification and trend prediction via AI algorithms to forecast equipment faults in advance, support predictive maintenance, cut equipment downtime caused by failures and enhance equipment operational stability and service life.

5. Empower optimized decision-making: Cloud platforms aggregate massive inspection data. Statistical analysis of the data delivers precise support for enterprises’ operation and maintenance decisions, equipment upgrading and process optimization, driving the transformation of operation and maintenance models from "passive response" to "active prevention and control" and facilitating enterprises’ digital and intelligent upgrading.