Equipment
Seeders / spreaders
Tractor-mounted seeders and fertilizer spreaders rely on multiple electric motors for precise, metered delivery. They operate under continuous field vibration — and that vibration is both a source of interference and a cause of failure. The faults that matter most rarely show up cleanly on any single sensor.
In the field, a motor’s trouble seldom announces itself. Current can sit within range while vibration drifts; a startup transient can look ordinary in isolation. The damage shows in how the channels move together — across several motors at once.
Vibration and motor-electrical signals each have well-established analysis methods. EchoSignal doesn’t replace them — it runs them as domain plugins on top of the general engine, then models normal across all of them together. Different methods, combined.
Time–frequency methods such as wavelet analysis capture the non-stationary, transient features that field vibration produces — the kind that fixed-band thresholds miss.
Motor current signature analysis and related methods read the electrical signature of each motor, across both steady-state running and the startup transient.
Per-channel conditioning prepares each signal type before detection — making the combined baseline faster, sharper, and less dependent on manual review.
Analyzed one at a time, each signal is a known problem with mature tools. But across two signal types and several motors at once, the meaningful anomaly is a combination — a pattern no single method, and no human watching dashboards, can reliably hold in view.
That combined, cross-channel anomaly is exactly what EchoSignal surfaces — and brings to your expert to judge.
On a multi-motor seeding-and-fertilizing rig, recurring motor faults — overheating, stalling, unstable speed, and rotation-angle drift — were proving hard to pin down under field vibration. Each channel, read on its own, often looked acceptable. By modeling normal across the combined vibration and motor-electrical signals of all motors together, EchoSignal surfaced the cross-channel deviations that preceded the faults, and brought them to the operator’s engineers to confirm the root cause.
Outcome figures are placeholders, to be filled from your records once cleared for publication.
Bring your own vibration and motor-electrical data — from your own rigs, in your own conditions — and see what the combined baseline surfaces. The best proof runs on your own data.