# US 12,216,445 B1 · Fluid condition sensor and maintenance systems and methods > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,216,445 B1 - Document ID: US12216445B1 - Status: Granted - Kind: B1 - Application number: 17/732,455 - Filed: 2022-04-28 - Granted: 2025-02-04 - Earliest claimed: 2021-05-14 - Assignees: ESL TEKnologies LLC - Applicants: ESL TEKnologies LLC - Inventors: John Tiffany Jaeger, Jr.; Jason Lamb - Web page: https://patentgrep.com/patent/US12216445B1 ## CPC - G05B 19/058: {Safety, monitoring} - G01N 33/00: Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00 - H04W 4/38: for collecting sensor information - H04W 88/16: Gateway arrangements - G05B: CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS (systems for controlling or regulating non-electric variables G05D; systems for regulating electric or magnetic variables G05F; control devices or systems insofar as characterised by mechanical features only G05G) - G01N: INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES (measuring or testing apparatus or processes other than immunoassay, involving enzymes or microorganisms C12M, C12Q) - H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72) ## Abstract An industrial internet of things (IoT) gateway is communicatively coupled to (a) fluid condition sensor(s) monitoring (an) operating parameter(s) of fluid power system fluid, via a programmable logic controller (PLC) data communications protocol interface. The IoT gateway includes a PLC data communications protocol interface master function, a cloud computing interface module and program instructions to periodically sample fluid condition sensor readings, format the readings, and send the readings to a cloud computing message queuing telemetry transport broker for processing by a cloud monitoring system. Machine learning provides predictions of fluid quality and buildup of varnish in the fluid system, applies a scoring algorithm to predict fluid system failure. These predictions may be used to automatically create (a) work ticket(s) related to the fluid system. Servicing by mitigation of varnish, installation of the sensor system, issuance of a warranty, guarantee and/or service contract, and/or financing thereof, may be provided. ## Claims ### Claim 1 A fluid condition sensor system, comprising: one or more fluid condition sensors configured to monitor one or more operating parameters of fluid in a fluid power system; and a gateway communicatively coupled to the one or more fluid condition sensors for communication of the one or more operating parameters of the fluid in the fluid power system via a data communications protocol interface, wherein the data communications protocol interface polls the one or more fluid condition sensors at a frequency that increases when non-nominal sensor readings are received, the gateway comprising: a data communications protocol interface master function; a cloud computing interface module; and program instructions, that when executed by the gateway, causes the gateway to periodically sample fluid condition sensor readings via the data communications protocol interface, format the readings, and send the readings to a cloud computing message queuing telemetry transport broker for processing by a cloud monitoring system. ### Claim 2 (depends on 1) The system of claim 1, wherein the program instructions include machine learning employed to provide predictions of fluid quality. ### Claim 3 (depends on 2) The system of claim 2, wherein the predictions of fluid quality are used by the program instructions to create a work ticket related to the fluid power system. ### Claim 4 (depends on 1) The system of claim 1, wherein the program instructions include machine learning employed to provide predictions of buildup of varnish in the fluid power system. ### Claim 5 (depends on 4) The system of claim 4, wherein the predictions of buildup of varnish in the fluid power system are used by the program instructions to create a work ticket related to the fluid power system. ### Claim 6 (depends on 1) The system of claim 1, wherein a scoring algorithm applies machine learning to predict fluid power system failure. ### Claim 7 (depends on 6) The system of claim 6, wherein the program instructions are further executable to develop trend data to provide predictive analytics, wherein the predictive analytics use sensor readings over time to generate trend analytics data that feeds into a predictive data model, and the predictive data model determines a future state of a varnish level. ### Claim 8 (depends on 7) The system of claim 7, wherein the program instructions are further executable to provide preemptive alerts, via text messages, emails, an application program interface of a third-party system, and/or on a user interface of the cloud monitoring system, of the predictions of fluid quality, buildup of varnish in the fluid power system and/or fluid power system failure. ### Claim 9 A fluid condition sensor method comprising: monitoring, by one or more fluid condition sensors, one or more parameters of fluid in a fluid power system; communicating the one or more parameters of the fluid in the fluid power system to a gateway via a data communications protocol interface, wherein the data communications protocol interface polls the one or more fluid condition sensors at a frequency that increases when non-nominal sensor readings are received; employing, by the gateway, a data communications protocol interface master function, a cloud computing interface module, and program instructions to: periodically sampling fluid condition sensor readings via the data communications protocol interface; formatting the readings; sending the readings to a cloud computing message queuing telemetry transport broker for processing by a cloud monitoring system. ### Claim 10 (depends on 9) The method of claim 9, wherein the program instructions include machine learning providing predictions of fluid quality. ### Claim 11 (depends on 10) The method of claim 10, further comprising the program instructions using the predictions of fluid quality to create a work ticket related to the fluid power system. ### Claim 12 (depends on 9) The method of claim 9, wherein the program instructions include machine learning providing predictions of buildup of varnish in the fluid power system. ### Claim 13 (depends on 12) The method of claim 12, further comprising the program instructions using the predictions of buildup of varnish in the fluid power system to create a work ticket related to the fluid power system. ### Claim 14 (depends on 9) The method of claim 9, further comprising applying, by a scoring algorithm, the machine learning to predict fluid power system failure. ### Claim 15 (depends on 14) The method of claim 14, wherein the program instructions are further executable to develop trend data to provide predictive analytics, wherein the predictive analytics use sensor readings over time to generate trend analytics data that feeds into a predictive data model, and the predictive data model determines a future state of a varnish level. ### Claim 16 (depends on 15) The method of claim 15, further comprising providing preemptive alerts, via text messages, emails, an application program interface of a third-party system, and/or on a user interface of the cloud monitoring system, of the predictions of fluid quality, buildup of varnish in the fluid power system and/or fluid power system failure. ### Claim 17 A method for providing servicing for a fluid power system, comprising: cleaning varnish off of surfaces in the fluid power system; installing a fluid condition sensor system, comprising: one or more fluid condition sensors monitoring one or more operating parameters of fluid in the fluid power system; and an industrial internet of things a gateway communicatively coupled to the one or more fluid condition sensors, the industrial internet of things gateway communicating the one or more operating parameters of the fluid in the fluid power system, via a programmable logic controller data communications protocol interface, the industrial internet of things gateway comprising: a programmable logic controller data communications protocol interface master function; a cloud computing interface module; and program instructions, that when executed by the industrial internet of things gateway, causes the industrial internet of things gateway to periodically sample fluid condition sensor readings via the programmable logic controller data communications protocol interface, format the readings, and send the readings to a cloud computing message queuing telemetry transport broker for processing by a cloud monitoring system; issuing or obtaining a warranty, guarantee and/or service contract covering repair and/or replacement of named components that breakdown due to failure of the fluid power system; providing, by the cloud monitoring system, monitoring of the one or more operating parameters of fluid in the fluid power system; providing, by machine learning in the program instructions, predictions of fluid quality; providing, by the machine learning, predictions of buildup of varnish in the fluid power system; applying, by a scoring algorithm, machine learning to predict fluid power system failure; and using the predictions of fluid quality, the predictions of buildup of varnish in the fluid power system and/or a prediction of fluid power system failure, by the program instructions, to create a work ticket related to the fluid power system. ### Claim 18 (depends on 17) The method of claim 17, further comprising polling, by the programmable logic controller data communications protocol interface, the connected one or more sensors at a frequency that increases as indication of non-nominal sensor readings are received and the program instructions are further executable to develop trend data to provide predictive analytics. ### Claim 19 (depends on 17) The method of claim 17, further comprising providing preemptive alerts, via text messages, emails, an application program interface of a third-party system, and/or on a user interface of the cloud monitoring system, of the predictions of fluid quality, buildup of varnish in the fluid power system and/or fluid power system failure. ### Claim 20 (depends on 17) The method of claim 17, further comprising financing one or more of the cleaning varnish off of surfaces in the fluid power system, installing the fluid condition sensor system, issuing or obtaining the warranty, guarantee and/or service contract, monitoring of the one or more operating parameters of fluid in the fluid power system, providing predictions of fluid quality and varnish in the fluid power system and predicting fluid power system failure.