SAM4 installs inside the motor control cabinet and measures current and voltage from the motor supply. It detects developing electrical, mechanical, drivetrain, and hydraulic load-path fault evidence, validates findings with reliability engineers, and turns them into maintenance actions. No sensor on the asset. Brief planned cabinet intervention to install.
Submerged pumps, enclosed motors, ATEX-zone equipment, remote fans, and large fleets of smaller drives often run without continuous condition data. Not because they are unimportant, but because installing and maintaining sensors on the asset is impractical, expensive, or unsafe.
Manual inspection routes capture snapshots. They do not show how faults develop between visits. That leaves reliability teams reacting late, especially on the assets that are hardest to inspect.
SAM4 closes that gap from the motor control cabinet. It reads current and voltage at the MCC and turns the motor's electrical signal into condition data. No sensor on the machine. No routine asset access for monitoring.
When voltage becomes unbalanced, a bearing wears, a belt slips, a gearbox degrades, a pump cavitates, or a wet-well pump starts to rag, the motor can draw current and voltage differently. The change is small, but repeatable. It appears in the current and voltage waveforms that travel back through the motor cable to the cabinet.
SAM4 measures those waveforms at the MCC, converts them into the frequency domain, and detects patterns linked to electrical faults, drivetrain faults, and process or hydraulic load changes.
No sensor on the asset. The motor cable already carries the signal.
SAM4 measures current and voltage at the motor control cabinet. Those signals contain direct evidence of electrical faults and indirect evidence of mechanical or process faults that change load, torque, speed, or electromagnetic behaviour.
Electrical faults are often visible directly in the motor's own signal. Mechanical and process faults propagate through the drivetrain and appear as load-path changes in the current and voltage spectrum.
Electrical faults are often visible directly. Mechanical and process faults are detected through their effect on the motor's electrical behaviour.
Detection confidence varies by asset type, operating regime, load stability, and available fault history. That is why SAM4 publishes performance by asset type, rather than relying on one blended number across all machines.
SAM4 installs at the motor control cabinet, captures current and voltage, analyses the electrical signal, and delivers validated findings your team can act on.
SAM4 measurement hardware is installed inside the motor control cabinet by qualified personnel, usually during a short planned cabinet intervention.
You avoid: asset-mounted sensors, routine machine access, scaffolding, wet-well entry, or ATEX-zone access for ongoing monitoring.
SAM4 continuously samples high-frequency current and voltage waveforms across real operating conditions. Data is transmitted to the platform via cellular, Ethernet, or Wi-Fi.
You get: a continuous electrical signature for each monitored asset.
SAM4 converts waveform data into frequency spectra and compares each asset against known fault signatures and its own healthy baseline. Models are trained across more than 7,000 continuously monitored assets.
You get: early evidence of developing electrical, mechanical, or process-related fault patterns before they become operational failures.
Validated findings include the likely fault, severity, diagnostic context, supporting evidence, and a recommended next step. Alerts route into your CMMS (SAP PM, IBM Maximo, Infor EAM), dashboard, email, or workflow API.
You get: a maintenance action, not raw signal data.
SAM4 runs two detection tracks in parallel.
Load, speed, and operating context help separate process changes from likely faults. Ambiguous or edge-case findings are reviewed by reliability engineers before they reach your team.
SAM4 does not just flag that something changed. Each alert explains which asset is affected, what fault is likely, how urgent it is, what evidence supports the finding, and what your team should do next.
Beyond fault detection, the same electrical signal supports energy and performance insights: power consumption, load behaviour, operating efficiency, and fleet-level outliers. Explore energy and performance monitoring →
SAM4 supports decisions at three levels using the same signal.
SAM4 performance is measured on resolved customer-facing alerts from live industrial deployments.
“We've chosen Samotics as our sole supplier for ESA technology for the coming years because they have shown strong performance in the water industry and are the only company able to deliver this technology at scale.”
SAM4 gives reliability, operations, and maintenance teams the same source of truth: validated asset condition from the motor control cabinet.
ABB embedded Samotics ESA into its ACS880 drive portfolio. For compatible drives, SAM4 can analyse current and voltage signals already measured by the drive, reducing the need for additional cabinet measurement hardware.
The drive captures the electrical signal. SAM4 applies ESA analytics, expert validation, and maintenance workflow integration. The result is the same: validated findings with likely fault type, severity, evidence, and recommended action.
Compatibility is confirmed during scoping. If your assets do not run on compatible ABB drives, SAM4 can install cabinet measurement hardware at the MCC to capture the same current and voltage signals.
Read the ABB press release · Check ABB drive compatibility →
Typical install is under 60 minutes per drivetrain. Sensors clamp inside the motor control cabinet. During installation, de cabinet needs a brief de-energization. Back online the next shift. On ABB-drive-embedded deployments, there is no cabinet work at all.
Detection starts at install. SAM4 does not require a multi-week training or baseline-building phase. Two analysis tracks run in parallel from day one. Physics-based detection looks for fault types with known electrical signatures — voltage imbalance, current imbalance, stator winding indicators, broken rotor bar sidebands, and bearing-related modulation patterns. These appear at expected frequencies and do not depend on asset history. Asset-specific baseline detection builds each machine's healthy operating envelope from the first measurements and refines it as more operating context comes in. Both tracks contribute to detection from the first measurements onward.
SAM4 supports many VFD-driven motors. Detection confidence depends on drive topology, switching behaviour, load profile, operating regime, and fault mode. The ESA page documents where confidence is reduced. We review these factors during asset-fit scoping.
SAM4 pushes alerts to SAP PM, IBM Maximo, Ultimo, Oracle eAM, and any system with a REST or webhook endpoint. Standard integrations are documented; custom mappings are configured during onboarding.
Current and voltage waveforms are encrypted locally and streamed to the Samotics cloud on EU or regional infrastructure. Data ownership remains with the customer. Contract covers retention, export, and deletion terms.
Two safeguards. First, every candidate alert that lands on your desk has been reviewed by a Samotics reliability engineer; ambiguous detections are filtered before notification. Second, the false-alert share after expert review is in the low single-digit range across customer-facing alerts. If a customer's site is producing noisy alerts, we recalibrate per-asset baselines rather than dump raw output.
Typical first deployment: the assets that stop production when they fail and currently have no condition monitoring. Centrifugal pumps, fans, conveyors, and gearbox-driven motors are the highest-yield entry points. We shortlist candidates together during scoping.
ESA and vibration are complementary, not competitive. Vibration excels on accessible, high-criticality rotating assets. ESA covers what vibration cannot reach: submerged or enclosed motors, electrical faults, fleet-wide low-cost coverage. See the full comparison.
Both. The cabinet gateway pre-processes raw current and voltage into failure indicators locally, which makes the system viable on low-bandwidth and offshore sites. Spectral analysis, baseline comparison, and engineer review happen in the cloud, where each asset benefits from learning across the wider monitored fleet. Customers in restrictive network environments can run with reduced cloud transmission.
A 45-minute walkthrough with a Samotics reliability engineer. Bring an asset list; leave with a deployment shortlist.
