Electrical Signature Analysis

One signal. Full drivetrain visibility.

Every AC motor draws current and voltage in patterns that reflect the mechanical condition of the full drivetrain — motor, coupling, gearbox, and driven load. Electrical Signature Analysis reads those patterns from the motor control cabinet. No sensors on the asset. No physical access required.

At Schiphol Airport, SAM4 detected 9 out of 9 developing faults — including bearing damage that the existing vibration programme missed. Read the case study →

The science

How a motor's electrical signature reveals drivetrain condition

ESA works because the motor's electrical supply and mechanical load are physically coupled. Every fault in the drivetrain — from bearing wear to cavitation — creates a measurable change in the electrical signature at the MCC.

A degrading bearing changes the air gap. A blocked impeller shifts the torque profile. A misaligned coupling creates periodic load oscillations. All of these appear as patterns in the current and voltage signals captured by CTs and VTs clamped at the motor control cabinet.

AI models — trained on data from over 10,000 industrial assets — compare each motor's signature against known fault patterns and its own baseline behaviour. The result: continuous condition monitoring for every connected drivetrain, without a single sensor on the asset.

Motor Control Cabinet CT/VT clamps capture current and voltage
AI Models Trained on 10,000+ assets
Expert Validation Engineer reviews every anomaly
SAM4 Dashboard Validated alerts and recommended actions

The science is only half the story

ESA captures the signal. AI identifies the anomaly. But every alert is reviewed by a Samotics reliability engineer before it reaches your team. They confirm fault type, assess severity, and recommend a specific action. Time-critical alerts are escalated immediately.

See the full service model →

Detection capability

What ESA detects across the drivetrain

ESA detects faults across the full drivetrain — weeks to months before failure. The matrix below maps fault types to equipment categories, with detection confidence based on over 10,000 monitored assets.

Fault type AC Motors Pumps Fans Gearboxes Compressors
Bearing degradation
Misalignment
Imbalance
Cavitation
Clogging / blockage
Electrical faults
Process deviations
Efficiency degradation
Full detection Partial / emerging Not applicable

This matrix is non-exhaustive. ESA can detect additional fault types depending on asset configuration and operating conditions.

See customer results →

What's different

Same physics. Different experience.

Motor Current Signature Analysis has existed for over 40 years. It works — but it requires a specialist, a scheduled visit, and manual interpretation. SAM4 turns ESA into a continuous, automated service.

Legacy MCSA

  • Monitoring mode Periodic — scheduled visits
  • Operator Specialist with oscilloscope
  • Data interpretation Manual expert analysis
  • Scale One asset at a time
  • Output Report (days–weeks later)
  • Fleet coverage Typically 5–20 critical assets

SAM4 ESA

  • Monitoring mode Continuous — 24/7 automated
  • Operator No specialist required
  • Data interpretation AI models + diagnostic team
  • Scale Entire fleet simultaneously
  • Output Real-time alerts + dashboard
  • Fleet coverage 1,000+ assets per site

The physics hasn't changed. The experience has — from a specialist tool to an operational platform your maintenance team can use.

See how ESA compares to vibration monitoring →

Validation

From IEEE papers to 10,000 monitored assets

40+ years of ESA science
10,000+ assets monitored globally
>90% of developing faults detected
80+ customers across 5 continents

ISO 20958

The international standard for condition monitoring using electrical signatures. SAM4's approach aligns with ISO 20958 methodology.

ABB integration

ABB evaluated every ESA approach on the market and chose Samotics. SAM4 ESA is integrated into ABB's ACS880 drives. ABB holds a 10% equity stake.

Peer-reviewed research

ESA methods have been published in IEEE, EPRI, and leading journals since the 1980s. The physics is established.

“Instead of needing to be placed on the asset in the field, SAM4 installs inside the motor control cabinet, out of harm's way. And its advanced analytics were just what we needed.”

Andy Roegis Industrial Digitalization Manager, ArcelorMittal

See SAM4 ESA with your own data

Request a demo and speak with one of our reliability engineers. We'll show you what ESA detects on assets like yours.

See how SAM4 monitors the assets your sensors can't reach.

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