A fault database includes a fault identifier, a signature or pattern that indicates the presence of the fault, and a set of mitigation control steps. The fault database is intermittently updated and downloaded to an agricultural machine. A fault identification system on the agricultural machine scans data logs that are generated by a log generation system on the agricultural machine and compares information in the data logs to the signature or pattern in the fault database to determine whether any of the faults in the fault database are present on the agricultural machine. If a fault in the fault database is present, a mitigation control step is identified to mitigate the fault, and a control signal is generated on the agricultural machine to implement the mitigation control step.

Systems, apparatus, and program code, and methods for monitoring the health and other conditions of the valve, are provided. An exemplary system for monitoring the condition of the gate valve includes a logic module configured to perform the operations of receiving sensor data providing an acoustic emission, vibration, and/or stream level signature and determining the level of lubricity, level of friction, level of surface degradation, and leakage rate at a gate-valve seat interface. An exemplary method for monitoring the condition of the gate valve includes receiving sensor data providing an acoustic emission, vibration, and/or stream level signature and determining the level of lubricity, level of friction, level of surface degradation, and leakage rate at a gate-valve seat interface.

A system and method for outlier detection based on process fingerprints from robot cycle data includes a data collection component, which is configured to collect cyclic data, wherein the cyclic data comprises multiple vectors each of which comprises data from one individual cycle of the robot cycle data; a data storage component, wherein which is configured to store the collected cyclic data; and a data processing component, which is configured to perform cloud processing of the stored cyclic data triggered by a cycle-start signal, wherein the data processing component is configured to parse the stored cyclic data and to process the stored cyclic data based on a configuration file defining metadata of the stored cyclic data, wherein the data processing component is configured extract process fingerprints from the stored cyclic data using the metadata.

A method for controlling a technical system via a control system, wherein the control system, after processing a request from an operator, generates a response message to the request such that if a faulty state of the technical system occurs, then associated fault messages are linked in an automated manner to the request and the response message in the time between the request and the generation of the response message, and a corresponding item of information relating thereto is presented to the operator, where the link between the request, response message and fault messages is provided with a digital signature of the operator who made the request to the control system.

Various embodiments of the present technology generally relate to condition monitoring in industrial environments. More specifically, some embodiments relate to an embedded analytic engine for motor drives that monitors induction motor conditions for potential failures including rotor faults and stator faults. In an embodiment, a condition monitoring module is configured to obtain runtime signal data from a controller within a drive, derive runtime metrics from the runtime signal data based on an induction motor fault condition, provide the runtime metrics as input to a machine learning model constructed to identify a status of the induction motor based on the runtime metrics and output the status, and monitor the induction motor fault condition based on the status of the induction motor output by the machine learning model.

An abnormality detection device is configured so as to include: an outlier score calculating unit for calculating, from abnormality detection time-series data indicating states of equipment which is an abnormality detection target at a plurality of times in time series, a degree of abnormality of the equipment at each of the plurality of times as an abnormality detection outlier score; an outlier data extracting unit for extracting, from among pieces of the abnormality detection time-series data, a piece of abnormality detection time-series data in a time period in which an abnormality may have occurred in the equipment as abnormality detection outlier data on the basis of the abnormality detection outlier score at each of the plurality of times calculated by the outlier score calculating unit; and an abnormality determining unit for collating a waveform of the abnormality detection outlier data extracted by the outlier data extracting unit with a waveform condition for determining that a waveform indicating a change in the abnormality detection outlier data is a waveform obtained when the equipment is operating normally, and determining whether or not the equipment is operating abnormally on the basis of a collation result between the waveform condition and the waveform of the abnormality detection outlier data.

A configuration manager is associated with a Networked Control System (NCS) comprising a plurality of sensors and actuators. The configuration manager automatically discovers the hardware and/or software configurations of the sensors and actuators, and analyzes that information in order to detect whether any of the sensors and actuators have been tampered with. Provided the configuration manager detects such tampering, the configuration manager indicates the tampering to a control manager of the NCS, which then functions to minimize potential damage to the NCS.

A configuration manager is associated with a Networked Control System (NCS) comprising a plurality of sensors and actuators. The configuration manager automatically discovers the hardware and/or software configurations of the sensors and actuators, and analyzes that information in order to detect whether any of the sensors and actuators have been tampered with. Provided the configuration manager detects such tampering, the configuration manager indicates the tampering to a control manager of the NCS, which then functions to minimize potential damage to the NCS.

The invention relates to a system (1) for the automatic detection of a state of a device (2), comprising: a signal acquisition means (10) for acquiring defective measurement data (D) of a physical variable characterising the device (2); and an analysis unit (11) for identifying a specified pattern (M) in the measurement data (D) acquired by the signal acquisition means (10). The analysis unit (11) is designed: to compare at least two different pattern sections (M1-M14) of the specified pattern (M) separately from each other with the measurement data (D): on the basis of the respective comparison, to determine at least one position of each of the pattern sections (M1-M14) in the measurement data (D): on the basis of the positions determined and the order of the positions of the pattern sections (M1-M14), to detect the specified pattern (M) at one or more positions in the measurement data (D) and, on the basis of the one or more positions of the specified pattern (M), to determine the state of the device (2).

A fault database includes a fault identifier, a signature or pattern that indicates the presence of the fault, and a set of mitigation control steps. The fault database is intermittently updated and downloaded to an agricultural machine. A fault identification system on the agricultural machine scans data logs that are generated by a log generation system on the agricultural machine and compares information in the data logs to the signature or pattern in the fault database to determine whether any of the faults in the fault database are present on the agricultural machine. If a fault in the fault database is present, a mitigation control step is identified to mitigate the fault, and a control signal is generated on the agricultural machine to implement the mitigation control step.