# US 10,503,145 B2 · System and method for asset fleet monitoring and predictive diagnostics using analytics for large and varied data sources > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,503,145 B2 - Document ID: US10503145B2 - Status: Granted - Kind: B2 - Application number: 14/871,205 - Filed: 2015-09-30 - Published: 2016-09-29 - Granted: 2019-12-10 - Earliest claimed: 2015-03-25 - Assignees: Honeywell International Inc. - Applicants: Honeywell International Inc. - Inventors: David J. Germann; Gregory E. Stewart; Marc Light; Dinkar Mylaraswamy - Web page: https://patentgrep.com/patent/US10503145B2 ## CPC - G05B 19/4065: Monitoring tool breakage, life or condition - B23K 11/00: Resistance welding; Severing by resistance heating - G05B 23/0216: {Human interface functionality, e.g. monitoring system providing help to the user in the selection of tests or in its configuration} - G05B 23/0243: {model based detection method, e.g. first-principles knowledge model} - G05B 2219/34427: Diagnostic, monitoring incorporated in controller - Y02P 90/80: Management or planning - 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) - B23K: SOLDERING OR UNSOLDERING; WELDING; CLADDING OR PLATING BY SOLDERING OR WELDING; CUTTING BY APPLYING HEAT LOCALLY, e.g. FLAME CUTTING; WORKING BY LASER BEAM - Y02P: CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS ## Abstract A method includes receiving information associated with operation of multiple pieces of industrial equipment at multiple sites. The multiple pieces of industrial equipment are of a same or similar type, and the information represents different types of data including operational data associated with the multiple pieces of industrial equipment and text-based data associated with the multiple pieces of industrial equipment. The method also includes analyzing the information to identify correlations in the information associated with one or more conditions involving the pieces of industrial equipment. The method further includes, based on the analyzing, generating one or more monitoring rules or routines to be used to identify the one or more conditions. The multiple pieces of industrial equipment could include machines with rotating components, machines with heat transfer equipment, or general process equipment. ## Claims ### Claim 1 A method for rule based monitoring of industrial equipment, the method comprising: receiving information associated with the operation of multiple pieces of industrial equipment at one or more sites, the multiple pieces of industrial equipment being of a same or similar type, the information comprising different types of data including operational data associated with the multiple pieces of industrial equipment and text-based data associated with the multiple pieces of industrial equipment; analyzing the information to identify normal behavior characteristics and abnormal behavior characteristics involving the pieces of industrial equipment, wherein the analysis of the information comprises: clustering the information to identify normal or abnormal behavioral characteristics of the industrial equipment; analyzing the information to identify faults and their potential causes, the probabilities of faults occurring, and the remaining lifetime of industrial equipment experiencing those faults; performing text mining in order to identify root causes and corrective actions for the faults and to catalogue behavioral characteristics; and generating one or more monitoring rules or routines based on the normal behavior characteristics and abnormal behavior characteristics; deploying the generated one or more monitoring rules or routines to a monitoring system; detecting by the monitoring system one or more conditions involving the pieces of industrial equipment violating the generated one or more monitoring rules or routines; and transmitting a notification by the monitoring system, upon detecting a condition of the one or more conditions that indicates the abnormal behavior characteristics involving the pieces of industrial equipment, to a user device associated with the industrial equipment. ### Claim 2 (depends on 1) The method of claim 1, further comprising: receiving additional information comprising at least one of: (i) more information associated with the operation of the pieces of industrial equipment and (ii) information associated with operation of additional pieces of industrial equipment; and generating one or more new or updated monitoring rules or routines using the additional information. ### Claim 3 (depends on 1) The method of claim 1, wherein analyzing the information comprises performing statistical modeling augmented with at least one of: one or more physical first principles models and one or more semi-empirical models. ### Claim 4 (depends on 1) The method of claim 1, wherein the multiple pieces of industrial equipment comprise at least one of: machines with rotating components, machines with heat transfer equipment, and general process equipment. ### Claim 5 (depends on 1) The method of claim 1, wherein: the operational data comprises real-time or time-stamped instrumentation data associated with the multiple pieces of industrial equipment; and the text-based data comprises maintenance information associated with the multiple pieces of industrial equipment. ### Claim 6 (depends on 1) The method of claim 1, wherein the information associated with the operation of the pieces of industrial equipment comprises information associated with historical operations of the pieces of industrial equipment. ### Claim 7 (depends on 1) The method of claim 1, wherein the one or more conditions involving the pieces of industrial equipment comprise one or more faults with the pieces of industrial equipment. ### Claim 8 An apparatus system comprising: at least one interface configured to: receive information associated with operation of multiple pieces of industrial equipment at one or more sites, the multiple pieces of industrial equipment being of a same or similar type, the information comprising different types of data including operational data associated with the multiple pieces of industrial equipment and text-based data associated with the multiple pieces of industrial equipment; and at least one processing device configured to: analyze the information to identify normal behavioral characteristics and abnormal behavioral characteristics correlations in the information associated with one or more conditions involving the pieces of industrial equipment wherein the analysis of the information comprises: clustering the information to identify the normal behavioral characteristics and the abnormal behavioral characteristics of the pieces of industrial equipment; processing the clustered information using machine learning to identify at least one of possible causes of the abnormal behavioral characteristics of the pieces of industrial equipment, and probabilities of a probability that the abnormal behavioral characteristics exist, and determining a life span of the pieces of industrial equipment with the abnormal behavioral characteristics; performing text mining to identify root causes and solutions for the abnormal behavioral characteristics and catalogue the abnormal behavioral characteristics of the pieces of industrial equipment; and based on the analysis, generate one or more monitoring rules or routines to be used to identify the one or more conditions based on the normal behavioral characteristics and abnormal behavioral characteristics; deploy the generated one or more monitoring rules or routines to a monitoring system; detect by the monitoring system one or more conditions involving the pieces of industrial equipment violating the generated one or more monitoring rules or routines; and transmit a notification by the monitoring system, upon detecting a condition of the one or more conditions that indicates the abnormal behavioral characteristics involving the pieces of industrial equipment, to a user device associated with the industrial equipment. ### Claim 9 (depends on 8) The apparatus of claim 8, wherein: the at least one interface is further configured to receive additional information comprising at least one of: (i) more information associated with the operation of the pieces of industrial equipment and (ii) information associated with operation of additional pieces of industrial equipment; and the at least one processing device is further configured to generate one or more new or updated monitoring rules or routines using the additional information. ### Claim 10 (depends on 8) The apparatus of claim 8, wherein the at least one processing device is configured to analyze the information by performing statistical modeling augmented with at least one of: one or more physical first principles models and one or more semi-empirical models. ### Claim 11 (depends on 8) The apparatus of claim 8, wherein: the operational data comprises real-time or time-stamped instrumentation data associated with the multiple pieces of industrial equipment; and the text-based data comprises maintenance information associated with the multiple pieces of industrial equipment. ### Claim 12 (depends on 8) The apparatus of claim 8, wherein the one or more conditions involving the pieces of industrial equipment comprise at least one of: one or more user-defined conditions involving the pieces of industrial equipment; and one or more faults with the pieces of industrial equipment. ### Claim 13 A non-transitory computer readable medium containing computer readable program code that when executed causes at least one processing device to: obtain information associated with operation of multiple pieces of industrial equipment at one or more sites, the multiple pieces of industrial equipment being of a same or similar type, the information comprising different types of data including operational data associated with the multiple pieces of industrial equipment and text-based data associated with the multiple pieces of industrial equipment; analyze the information to identify correlations in the information associated with one or more conditions of normal behavioral characteristics and abnormal behavioral characteristics involving the pieces of industrial equipment wherein the analysis of the information comprises: clustering the information to identify the normal behavioral characteristics and the abnormal behavioral characteristics of the pieces of industrial equipment; processing the clustered information using machine learning to identify at least one of possible causes of the abnormal behavioral characteristics of the pieces of industrial equipment, and probabilities of a probability that the abnormal behavioral characteristics exist, and determining a life span of the pieces of industrial equipment with the abnormal behavioral characteristics; performing text mining to identify root causes and solutions for the abnormal behavioral characteristics and catalogue the abnormal behavioral characteristics of the pieces of industrial equipment; and based on the analysis, generate one or more monitoring rules or routines to be used to identify the one or more conditions based on the normal behavioral characteristics and abnormal behavioral characteristics; deploy the generated one or more monitoring rules or routines to a monitoring system; detecting by the monitoring system one or more conditions involving the pieces of industrial equipment violating the generated one or more monitoring rules or routines; and transmitting a notification upon detecting a condition of the one or more conditions that indicates the abnormal behavioral characteristics involving the pieces of industrial equipment, to a user device associated with the industrial equipment. ### Claim 14 (depends on 13) The non-transitory computer readable medium of claim 13, further comprises containing computer readable program code that when executed causes the at least one processing device to: receive additional information comprising at least one of: (i) more information associated with the operation of the pieces of industrial equipment and (ii) information associated with operation of additional pieces of industrial equipment; and generate one or more new or updated monitoring rules or routines using the additional information. ### Claim 15 (depends on 13) The non-transitory computer readable medium of claim 13, wherein to analyze the information, the non-transitory computer readable medium further comprises computer readable program code that when executed causes the at least one processing device to analyze the information comprises: computer readable program code that when executed causes the at least one processing device to perform statistical modeling augmented with at least one of: one or more physical first principles models and one or more semi-empirical models. ### Claim 16 (depends on 13) The non-transitory computer readable medium of claim 13, wherein: the operational data comprises real-time or time-stamped instrumentation data associated with the multiple pieces of industrial equipment; and the text-based data comprises maintenance information associated with the multiple pieces of industrial equipment. ### Claim 17 A method for rule based monitoring of industrial equipment, the method comprising: providing first information associated with the operation of at least one piece of industrial equipment at a site, the first information comprising different types of data including operational data associated with the at least one piece of industrial equipment and text-based data associated with the at least one piece of industrial equipment; analyze the information to identify correlations in the information associated with one or more conditions normal behavioral characteristics and abnormal behavioral characteristics involving the pieces of industrial equipment wherein analysis of the information comprises: clustering the information to identify the normal behavioral characteristics and the abnormal behavioral characteristics of the pieces of industrial equipment; processing the clustered information using machine learning to identify at least one of possible causes of the abnormal behavioral characteristics of the pieces of industrial equipment, and probabilities of a probability that the abnormal behavioral characteristics exist, or determining a life span of the pieces of industrial equipment with the abnormal behavioral characteristics; performing text mining to identify root causes and solutions for the abnormal behavioral characteristics and catalogue the abnormal behavioral characteristics of the pieces of industrial equipment; and receiving one or more monitoring rules or routines, the one or more monitoring rules or routines based on second information associated with operation of multiple pieces of industrial equipment at multiple sites, the multiple pieces of industrial equipment being of a same or similar type; deploying the generated one or more monitoring rules or routines to a monitoring system; identifying detecting by the monitoring system any conditions with the at least one piece of industrial equipment violating the one or more monitoring rules or routines.