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Executive Summary

This case study examines how a large integrated chemical plant successfully deployed a drone system equipped with the MR-FAT Fourier Transform Infrared (FTIR) Remote Spectrometer to address long-standing challenges of low inspection efficiency, numerous blind spots, and high personnel entry risks associated with gas leak detection across its vast premises. Utilizing a mobile and flexible aerial monitoring platform, the plant achieved automatic identification, localization, and semi-quantitative analysis of target gas clouds, improving inspection efficiency by approximately 80% and significantly reducing safety risks associated with manual inspections in high-risk areas.

1. Client Background & Challenge: Efficiency and Safety Dilemmas Under Traditional Inspection Models

The client is a large petrochemical complex located in a coastal region, featuring an extensive site area with dense equipment and complex, interconnected pipelines, involving numerous flammable, explosive, toxic, and harmful gases. For a long time, the facility relied on a combination of fixed gas detectors and manual patrols with handheld devices for safety monitoring.

However, this approach had clear limitations: fixed detectors offered limited coverage, leaving monitoring blind spots; manual inspections were time-consuming and labor-intensive, ineffective for hard-to-reach areas like high towers, top-level pipe racks, and remote tank farms, while also exposing personnel to close proximity with potential hazards, creating significant safety pressure. Particularly when responding to suspected sudden leaks, it was impossible to quickly conduct large-scale screening and localization, hampering emergency response timeliness. Management urgently needed a more efficient, safer, and more comprehensive leak detection method.

2. Solution Design: Giving MR-FAT "Wings"

Addressing the client's pain points, the technical team proposed an innovative "Drone + Infrared Remote Sensing" solution. The core was the MR-FAT Passive Fourier Transform Infrared Spectrometer. This device, based on the principle of infrared spectral absorption, can detect and identify multiple gases non-invasively.

The solution involved integrating the lightweight MR-FAT unit with an industrial-grade multi-rotor drone platform. This combination brought revolutionary advantages:

1. High Mobility: Drones can quickly reach any corner of the facility, seamlessly covering blind spots like aerial pipe racks and towering reactor tops that are difficult for ground patrols to access.
2. Rapid Large-Area Screening: Drones follow pre-set automated flight paths while MR-FAT performs continuous scanning. A single mission can complete a survey of an area spanning hundreds of thousands of square meters.
3. Operation from a Safe Distance: Operators control the system remotely from safe areas, enabling remote detection of suspected risk zones and completely avoiding personnel exposure.
4. Real-Time Data Transmission: Detection data and infrared images of gas clouds are transmitted back to the ground station in real-time, allowing on-site personnel to immediately identify and locate leaks.

3. Implementation Process: Customized Flight Plans and Intelligent Algorithm Synergy

The project implementation was divided into three phases. First, the team conducted a detailed site survey of the client's facility. Based on historical risk points, equipment distribution, and prevailing wind directions, they planned multiple periodic inspection routes and detailed scanning plans for key areas. Second, hardware integration of MR-FAT with the drone, electromagnetic compatibility debugging, and aerial calibration were completed to ensure stable data acquisition. Finally, the supporting ground control and data analysis software was deployed. This software features automatic gas identification algorithms capable of real-time alarm generation for target gases from vast amounts of spectral data.

Challenges included interference with wireless data transmission in the complex plant environment and precise retrieval of gas location from dynamic flight data. The team successfully achieved accurate 2D localization of gas clouds on the plant's electronic map by optimizing communication links and combining the drone's high-precision GPS and attitude data.

4. Results & Data: A Leap in Efficiency and Safety

Since the system was put into routine inspection service, the results have been significant:

• Substantial Efficiency Gain: The time required to complete one round of gas inspection for key areas across the entire plant was reduced from approximately 2 working days for manual methods to about 2.5 hours, representing an efficiency improvement of around 80%.
• Comprehensive Blind Spot Coverage: The system cumulatively identified and located 3 instances of minor chronic leaks at connection points on elevated pipe racks—locations that were effectively undetectable by ground patrols.
• Accelerated Emergency Response: During one night shift, the system, via automated patrol, preliminarily pinpointed the spread range of abnormal volatile organic compounds in a process unit area within 10 minutes, providing critical guidance for the emergency team.
• Reduced Safety Risk: The frequency of manual inspections in high-risk zones decreased by 60%, directly reducing frontline employee exposure to hazardous environments.
• Data Traceability: All inspection data (including spectral data, gas type, estimated concentration level, GPS location, time) is completely recorded, forming a traceable electronic archive for safety analysis and compliance management.

5. Client Feedback & Value Summary

"This drone-mounted MR-FAT system has transformed our safety inspection model," commented the chemical plant's Safety Director. "It's like giving us a pair of flying 'clairvoyant eyes'. Areas we used to worry about 'not seeing' are now clear at a glance. It not only enhances our ability to find hidden dangers but, more importantly, keeps our personnel away from unnecessary risks—this is value that can't be measured in money."

This project successfully validates the practicality and outstanding value of the MR-FAT drone-based remote sensing system for gas monitoring in large-scale industrial facilities. It is not merely a new detection tool but represents a new paradigm for intelligent, mobile safety inspection. Its value is reflected in: enhancing monitoring efficiency, covering traditional blind spots, reducing personnel risk, and strengthening emergency response capabilities—ultimately constructing a multi-dimensional technological defense line for the enterprise's safe production and stable operation.

Conclusion

This case demonstrates the immense potential of combining cutting-edge spectral technology with unmanned platforms. The MR-FAT drone-based gas monitoring solution offers high replicability and scalability. It is not only suitable for petrochemicals but can also provide powerful assistance for scenarios requiring rapid, large-area gas screening, such as natural gas storage and transportation, landfill sites, and environmental supervision. For enterprises seeking to upgrade their safety monitoring systems, this is a proven, future-oriented, and highly efficient solution.