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AI monitoring enables early fault detection

The above image depicts the Fibre-optic sensors along the conveyor belt system

CONTINUOUS MONITORING By combining distributed acoustic sensing with existing fibre-optic cables, Huawei continuously monitors vibration and acoustic signals along an entire conveyor belt system

14th August 2026

By: Lynne Davies

Creamer Media Features Writer

     

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As mines pursue higher productivity and safer operations, the mining industry is moving towards continuous, AI-driven monitoring that will allow for early fault detection and predictive main-tenance, says information and communications technology company Huawei.

By combining distributed acoustic sensing (DAS) with existing fibre-optic cables, Huawei is able to deploy systems to continuously monitor vibration and acoustic signals along an entire conveyor belt system, making every point along the fibre cables act as a sensor.

Unlike conventional point sensors, a single fibre line can monitor tens of kilometres in real time, making it highly suitable for harsh mining environments while reducing installation and maintenance costs, says Huawei.

Because fibre cabling is made from glass, it provides corrosion resistance, immunity to electromagnetic interference and inherent safety. It also obviates the need for an on-site power supply.

To address pain points that the distributed fibre-optic sensing industry has struggled with, such as high false alarm rates, difficulties in intelligent identification and poor environmental adaptability, Huawei leverages decades of technological experience in optical communications.

“By adopting a proprietary low-noise coherent optical receiver system and high-performance optical digital signal processing algorithms, the signal sampling rate reaches 99.9%, ensuring ultrahigh stability and consistency of signal acquisition from the source – laying a solid foundation for precise analysis,” the company says.

Huawei elaborates that, through proprietary acoustic fingerprint AI algorithms, the system can extract characteristic vectors from sounds such as frequency distribution and temporal variations.

Huawei also leverages deep learning using its acoustic fingerprint AI algorithms trained on real mining data to accurately distinguish normal operating sounds from abnormal equipment behaviour.

This, notes Huawei, significantly improves detection accuracy while reducing false alarms, consequently enabling teams to focus on genuine tasks.

Huawei’s infrastructure also supports open interfaces, enabling integration with supervisory control and data acquisition, as well as the manufacturing of execution systems, maintenance management systems and digital twin platforms.

“At Huawei, fibre sensing is one component of a broader intelligent mining architecture,” the company says.

When combined with high-speed connectivity, AI computing, digital twins and large language models, Huawei says fibre sensing transforms raw operational data into actionable intelligence, enabling mines to move from connected operation to intelligent decision-making.



Edited by Donna Slater
Features Managing Editor and Chief Photographer

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