US 12,140,930 B2
Method for determining service event of machine from sensor data
Charles Howard Cella, Pembroke, MA (US); Mehul Desai, Oak Brook, IL (US); Gerald William Duffy, Jr., Philadelphia, PA (US); and Jeffrey P. McGuckin, Philadelphia, PA (US)
Assigned to Strong Force IoT Portfolio 2016, LLC, Fort Lauderdale, FL (US)
Filed by Strong Force IoT Portfolio 2016, LLC, Fort Lauderdale, FL (US)
Filed on Jan. 19, 2023, as Appl. No. 18/099,121.
Application 18/099,121 is a continuation of application No. 17/154,687, filed on Jan. 21, 2021, abandoned.
Application 17/154,687 is a continuation of application No. 16/803,689, filed on Feb. 27, 2020, granted, now 10,983,507, issued on Apr. 20, 2021.
Application 16/803,689 is a continuation of application No. PCT/US2018/060034, filed on Nov. 9, 2018.
Application PCT/US2018/060034 is a continuation in part of application No. 15/859,238, filed on Dec. 29, 2017, granted, now 10,394,210, issued on Aug. 27, 2019.
Application 15/859,238 is a continuation in part of application No. PCT/US2017/031721, filed on May 9, 2017.
Claims priority of provisional application 62/584,099, filed on Nov. 9, 2017.
Claims priority of provisional application 62/427,141, filed on Nov. 28, 2016.
Claims priority of provisional application 62/412,843, filed on Oct. 26, 2016.
Claims priority of provisional application 62/350,672, filed on Jun. 15, 2016.
Claims priority of provisional application 62/333,589, filed on May 9, 2016.
Prior Publication US 2023/0273594 A1, Aug. 31, 2023
Int. Cl. G05B 19/4155 (2006.01); G05B 23/02 (2006.01)
CPC G05B 19/4155 (2013.01) [G05B 23/0259 (2013.01); G05B 2219/31001 (2013.01)] 26 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
collecting, from at least one sensor associated with a group of industrial machines, sensor data indicating at least one current health state indicator associated with at least one industrial machine of the group of industrial machines, wherein the at least one current health state indicator includes a fault condition of the at least one industrial machine;
providing the sensor data as an input to a neural network of a machine learning system, the neural network trained to determine the at least one current health state indicator based on patterns in the sensor data;
receiving the at least one current health state indicator as an output from the neural network of the machine learning system;
receiving, from the machine learning system, an indication of an additional sensor associated with the group of industrial machines from which to collect sensor data in order to diagnose the at least one current health state indicator; and
based on the at least one current health state indicator, determining a schedule of a service event, wherein the service event is associated with the at least one industrial machine, the determining the schedule of the service event including:
providing the at least one current health state indicator to the machine learning system, and receiving, from the machine learning system, the schedule of the service event,
wherein, based on iterative feedback, the machine learning system considers additional signals from at least one of the at least one sensor, the additional sensor, or another sensor to increase confidence in the fault condition.