From virtual models to real-world insights: inertial sensors power digital twins in mining

From BIM to digital twins: connecting models with reality

Building Information Modeling (BIM) has long moved beyond its origins in building design. Its ability to create detailed digital representations of physical assets offers considerable potential for mining and underground engineering, where operators manage complex networks of shafts, tunnels, caverns, access routes and technical installations – often under demanding and continuously changing conditions.

BIM can bring geological, structural and engineering information together within a common digital environment. During planning and construction, this helps engineers understand spatial relationships, coordinate infrastructure and identify potential conflicts. But once excavation, mining or drilling begins, another question becomes paramount: How is the real structure or machine behaving?

This is where digital twins go beyond conventional BIM models. By incorporating real-world data, they allow engineers to continuously compare expected and actual behavior.

ASC inertial sensor technology provides an important part of this information: precise accelerometers that make changing conditions and their impact on underground structures, machinery and equipment visible.

Turning sensor data into operational intelligence

In mining environments, acceleration and vibration measurements can provide valuable insights into the condition of machinery and equipment, as well as dynamic loads affecting structures and installations.

Applications range from monitoring crushers, conveyors, drilling equipment and other machinery to tracking vibrations in underground infrastructure. Changes in vibration patterns or unusual dynamic behavior can indicate conditions that warrant closer investigation.

Combined with other monitoring information, the sensor data supports condition-based and predictive maintenance strategies, helping operators intervene before deterioration leads to unplanned downtime – or more serious consequences.

The same principle extends to underground structures. Measurements at selected points in tunnels, shafts or other excavations provide additional real-world information for structural health monitoring. Instead of relying exclusively on periodic inspections or static engineering models, operators can progressively enrich their digital twins with actual measured behavior.

The benefit: a more informed view of asset conditions, better maintenance planning and greater operational reliability.

Four sensor solutions. One goal: smart infrastructure monitoring

Reliable measurement data is essential to making this approach work – particularly in challenging underground environments.

Capacitive MEMS-based accelerometers from the ASC ECO series offer uni-, bi- or triaxial configurations. All models are available with measurement ranges from ±2 g to ±40 g and a noise density of 22.5 to 90 µg/√Hz. With IP68 protection and shock resistance of up to 10,000 g, they are well suited to installations exposed to dust, moisture and mechanical loads. 

• ASC ECO – Analog with Voltage Output: differential analog voltage output (±2.4 V), robust design. Ideal for conventional measurement systems and integration into existing data acquisition architectures.

• ASC ECO CS – Analog with Current Output: for demanding installations with long cables or requiring high electromagnetic compatibility (EMC) immunity. Its 4–20 mA current output enables reliable signal transmission over extended distances with excellent immunity to electromagnetic interference. Ideal solution for large-scale infrastructure projects and bridge monitoring.

• ASC DiSens ECO – Digital: next step toward connected measurement technology. Featuring integrated A/D conversion, configurable filter settings and digital CAN interface. Enables efficient data transmission and seamless integration into digital monitoring systems.

• ASC AiSys ECO – Digital & Smart: more than just measurement – this intelligent sensor system captures and analyzes acceleration data directly within the sensor. Integrated filtering, frequency analysis and feature extraction algorithms help reduce downstream data processing requirements.

From visualization to prediction: making digital twins work for mining

The real value of digital twins lies beyond visualization. It comes from connecting virtual representations with continuously acquired real-word data from the actual worksite.

As mining operations become increasingly connected and data-driven, this feedback loop allows engineers to identify changes, validate their models and make maintenance decisions based on current asset conditions rather than assumptions alone.

BIM creates the digital framework. Inertial sensors add physical reality. Bringing the two together turns a virtual model of the mine into value-adding intelligence – supporting safer, more reliable, more efficient operations.