Every claim in this application protects one idea: the diagnosis happens inside the sensor bolted to the machine — not in a cloud, not on an analyst's laptop — and the sensor uses that diagnosis to decide when to wake up next.
Industrial machines vibrate. A failing bearing changes that vibration in ways a trained analyst can read. We put the analyst's skills onto a coin-cell-powered chip, so 500 machines get watched continuously instead of 20 machines getting visited quarterly.
6 independent, 21 dependent. Every independent claim ties to physical hardware — deliberate, to survive Section 3(k) in India.
Validated on 8+ public datasets from five countries, plus two blind tests where labels were hidden until after the run.
Including a dedicated Section 3(k) panel showing each claim's physical hardware effect.
A sensor wakes every hour regardless of whether anything is happening, and raises an alarm when a number crosses a line. It wastes battery on healthy machines and misses slow degradation that never crosses the line.
We measure how fast each indicator is moving relative to that specific machine's own normal variability — then use that to set both the alarm and the time until the next measurement. A machine that starts changing gets watched more closely, automatically.
The competitor patents in this space claim adjusting sampling based on a condition, or correlating patterns across a fleet. Ours is driven by a single machine's own rate of change, normalised by its own baseline — a structurally different mechanism, which is the foundation of our freedom-to-operate position.
Independent claims stand alone. Dependent claims narrow one of them — each adds a specific technique we can point to in a courtroom and in a lab.
Six pillars, twenty-one narrowing claims. Coral chips were added during July 2026.
A battery sensor wakes on a hardware clock alarm, measures vibration, scores urgency across six independent dimensions, and programs its own next wake-up time from that score.
Early bearing damage makes vibration spikier before it makes it bigger. We claim using the divergence between those two measures to stage the damage, name the fault, schedule the next scan, and check the sensor is still healthy — all from one ratio.
Fault patterns from one customer's machines help diagnose another's, shared as anonymised mathematical fingerprints rather than raw data, with a minimum number of contributing sites before any pattern can be used.
Three-axis measurement, hundreds of extracted features, a neural network, a physics rule engine, the verdict, the remaining-life estimate and the next-scan decision — all executed on a battery-powered microcontroller. No prior art puts the whole chain on the device.
The hardware embodiment: vibration, ultrasonic, and temperature sensing in one battery unit with the processing and radio, plus the server that receives it.
The scheduling invention again, written so it also covers permanently-powered installations — closing the loophole of copying the method on a mains-powered box.
No single measurement, however extreme, can raise an alarm alone. Higher severity demands more independent indicators agreeing.
When a technician closes a work order saying "you were right" or "you were wrong", the system moves that specific machine's thresholds up or down. Wrong alarm raises the bar; missed fault lowers it. The neural network is never retrained.
The sensor works out how fast the shaft is turning from the vibration itself, then also measures how much that speed wobbled during the measurement — and throws away any measurement taken while the machine was speeding up or slowing down.
A physics rule engine and a neural network classify the fault separately from the same data. A fixed routing rule decides which to publish — and when they disagree without either being confident, the output is literally UNCERTAIN, with both opinions attached.
The system detects that the neural network is out of its depth and falls back to physics automatically.
A statistical distance check that flags input unlike anything in training even when the network reports high confidence — the failure mode Claim 23's confidence test cannot see.
Training labels are generated by our own physics engine rather than by hand, and only windows that show the fault on their own are labelled faulty.
Every scan's verdict is written to the sensor's own memory in a way that survives power loss — 85,680 records, roughly 39 years of history, readable from the sensor alone with no server and no network.
Centrifugal force grows with the square of speed. As the machine naturally runs at different speeds over weeks, the sensor accumulates the relationship and checks whether vibration follows that squared law — confirming true imbalance and ruling out misalignment and looseness.
| What was tested | Result | Supports |
|---|---|---|
| Blind test, unseen rig — labels revealed only after the run | All 9 faults detected from a cold start, with no history for the machine | Claims 7, 8 |
| Physics-taught training — 2,348 held-out measurements | Healthy accuracy 62.4% → 89.4%; fault detection 98.2% → 99.8% | Claim 25 |
| Unfamiliar bearing geometry — 2,463 measurements | AI alone 3.9%; physics fallback held 100% outer-race precision | Claim 23 |
| Two opinions vs one — 7,730 clean-label measurements | Accuracy score 0.524 → 0.641 with no retraining | Claims 20–22 |
| Imbalance squared-law — 880 public recordings | 133 correct firings, zero false alarms on 547 controls | Claim 27 |
| Chip vs reference maths — 180 real run-to-failure windows | 180/180 agreement, zero decisions flipped at the boundary | Claim 24 |
Every figure above is drawn from a logged experiment recorded in the specification. Nothing is projected or modelled.
Freedom to operate asks a different question from patentability. Not "is it new?" but "does building it step on a live patent?" To infringe, we must perform every step of one of their claims. Missing a single required step means no infringement.
The dangerous competitor family never entered the Indian national phase, and its international application has lapsed. All eight innovations appear clear here — which is exactly where we file first.
Claims adjusting sampling based on a "condition indication". Ours is a six-dimensional urgency score whose main driver is rate of change against the machine's own baseline. Structurally different — but this is the one that needs formal construction before any US filing.
This is the family sitting closest to Claims 18, 19 and 27, and the reason we checked it: it is the patent behind the licensed "Speed Estimate" feature in Emerson's own wireless vibration transmitter.
| What their every claim requires | What we actually do |
|---|---|
| Guess a speed, draw where its harmonics would land, measure how far the real peaks sit from those positions, add up the errors, and pick the best-scoring guess | Nothing like it. We follow the peak through dozens of overlapping time slices and keep the one that moves smoothly — tracking motion, not matching a template |
| Produce one speed number | Produce the speed and how much it wobbled, then use the wobble to discard untrustworthy measurements |
| Stops at "analyse the data using that speed" | Feed it into rate-of-change trending, permanent on-sensor history, and the sleep scheduler |
| Nothing comparable | Claim 27 — the squared-law imbalance test appears nowhere in their family |
Their 2024 continuation dropped the requirement that a user type in the nominal speed, and instead derives the search range from the machine's history — which is closer to how we set our search band. It still does not reach us, because that claim also requires the harmonic-matching step we never perform. Counsel should pull the two continuation patents' claims word-for-word; our reading of the newest one came from a summary, not the verbatim text.
Not yet filed. India is freedom-to-operate clear across all eight innovations, and is the launch market.
Buys 30 months to choose national phases while the product finds its markets.
Construe Augury claim 48; pull the two Emerson continuations verbatim; confirm the competitor family never entered India; confirm startup fee reduction.