“Smart” sensor data analytics for equipment diagnosis

This invention describes a system that monitors rotary equipment by analyzing data from its sensors. It looks for specific 'alarm signatures' in the time-stamped sensor data and compares them to known 'diagnostic signatures'. If a match is found, the system determines the problem and can then trigger an action, such as shutting down the equipment, sounding an alarm, or scheduling maintenance.

Why it matters: Filed before widespread adoption of advanced AI for time-series data. Modern machine learning can now automatically learn complex diagnostic signatures, making the system more adaptable than the rule-based methods implied in 2018.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedSoftware logic, sensor integration, pattern matching.

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