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IoT & IndustrialEnergy
PipeHealth
AI Smart Pipe Corrosion Monitor based on STM32L4
Clamp-on ultrasonic sensor that measures pipe wall thickness and predicts corrosion rates using edge AI.
Thickness Accuracy
±0.1mm
Max Pipe Temp
150°C
PipeHealth
Client
An oil & gas integrity management company looking for a non-invasive, clamp-on corrosion monitoring solution for pipeline networks.
Challenge
Measuring pipe wall thickness through coatings and rust, at pipe temperatures up to 150°C, with sufficient accuracy to detect corrosion rates as low as 0.1mm/year.
Product Concept & Architecture
The STM32L4 MCU controls a 2.25MHz dual-element ultrasonic transducer. A Quectel BG96 modem provides LTE-M/NB-IoT backhaul. The sensor mounts via rare-earth magnets and includes a high-temperature silicone thermal break.
Engineering Solution
The STM32L4's hardware timer generates the excitation pulse, and its high-speed comparator captures echo return with 1ns resolution. Wall thickness is computed from round-trip time using temperature-compensated acoustic velocity. A moving-average trend filter extracts the corrosion rate from thickness measurements.
Result
±0.1mm thickness measurement accuracy. Corrosion rate detection as low as 0.05mm/year.
Deep Tech FAQ
What makes the AI Smart Pipe Corrosion Monitor based on STM32L4 unique?+
The AI Smart Pipe Corrosion Monitor based on STM32L4 leverages custom hardware and edge AI to deliver industry-leading performance and efficiency.
What are the core technical benefits?+
Key benefits include low power consumption, real-time processing, robust connectivity, and a compact form factor tailored for deployment.
Can this architecture be adapted for other use cases?+
Absolutely. The underlying methodology is modular and can be retargeted for various applications with minimal redesign.
Project Profile
Services Delivered
Hardware DesignEmbedded Software
Core Technologies
LTE-M/NB-IoTTinyMLRTOS
Silicon & Vendors
STMicroelectronicsTI
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